크래미디어문   

크래미디어문

크래미디어문(Chlamydiae)이란, 그램 음성 세균이다.협의로는 척추동물을 주로 여관 주인으로 하는 크래미디어과등의 「병원성 크래미디어」를 크래미디어라고 부르지만(최협의로는 크래미디어속만), 광의로는 파라크라미지아과등의 아메바를 주된 여관 주인으로 하는 「환경 크래미디어」를 포함한 크래미디어문전체를 크래미디어라고 부르는 일이 있다.

크래미디어문
ChlamydiaTrachomatisEinschlusskorperchen.jpg
분류
드메

: 진정 세균 Bacteria
: 크래미디어문Chlamydiae
학명
"Chlamydiae" Garrity and Holt 2012
하위 분류(밧줄)
  • 크래미디어밧줄
    • 크래미디어눈

주로 척추동물아메바등의 원생 생물을 여관 주인으로 하는 세포내 기생 생물이다.ATP/ADP 트란스로카제등의 각종 수송체를 가지고 있어 여관 주인으로부터 에너지나 영양을 취득해 생육하고 있다.이 때문에 세포외에서는 완전히 증식 하지 못하고, 환경안으로는 감염성이 있는 기본 작은 몸의 형태를 취한다.의학적으로 중요한 세균군이지만, 인공 배양지에서 배양할 수 없기 때문에 배양은 배양 세포나 계란을 사용할 필요가 있어, 연구가 어려운 그룹이다.

프란크트미케스문 등에 근친으로, 똑같이 페프치드그리칸을 결손해, FtsZ를 가지고 있지 않다.PVC군에게 들어간다고 보여지고 있다.

참고 문헌

  • Gupta RS, Bhandari V and Naushad HS (2012) Molecular signatures for the PVC clade (Planctomycetes, Verrucomicrobia, Chlamydiae, and Lentisphaerae) of bacteria provide insights into their evolutionary relationships. Frontiers in evolutionary and genomic microbiology.
  • [1]

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          Noninvasive Cancer Diagnostics and Technologies Market   

Noninvasive Cancer Diagnostics and Technologies Market - Global Share, Industry Overview, Analysis, Growth, Trends Opportunities and Forecast 2012 - 2020

Portland, OR -- (ReleaseWire) -- 08/28/2014 -- Non-invasive diagnostic is a process of identifying the disease conditions with minimal incision in body during diagnosis. The global market for diagnostic/in-vitro diagnostics valued at $49.2 billion in 2012, which shows potential for market growth, especially in chronic diseases. Non-invasive cancer diagnostics is gaining importance over conventional diagnosis due to increase in incidences of chronic cancer such as breast cancer, and lung cancer. According to American Cancer Society, there were more than 1,660,290 new cases diagnosed in 2013.

Get detailed report at:
http://www.reportsandintelligence.com/noninvasive-cancer-diagnostics-market

Commercialization of non-invasive cancer diagnosis is possible due to completion of Human Genome Project (HGP) that gives enormous diagnostic information based on genomic and proteomic. Increase in stringent regulatory guidelines and cost associated with diagnostics is hindering the growth of non-invasive cancer diagnostic market. The Ovarian Cancer National Alliance regulations for monitoring non-invasive diagnostics are issued by FDA, Medicare and Medicaid Services (CMS) and Social Security Administration (SSA).

The global non-invasive market has a huge potential in developing countries; however, cost of diagnosis is creating hurdles to tap this market. Hence, to overcome this problem, the diagnostic market has to be analyzed by the developing countries such as China, Japan, and India. This report provides key market drivers that are driving the market with impact analysis. The report gives intelligence about key regulatory guidelines issued by respective governments.

Key companies included in report are Precision Therapeutics, A&G Pharmaceutical, Affymetrix Inc., AVIVA Biosciences Corporation, BIOVIEW Inc., Laboratory Corporation of America Holdings (LabCorp), Quest Diagnostics Incorporated Cancer Genetics Inc., Digene Corporation, Gen-Probe Incorporated

KEY BENEFITS:

-Key developmental strategies adopted by top market players engaged in this business so that companies involved in development non-invasive cancer diagnostic device can get competitive intelligence of their competitors

-Market estimation for therapeutics techniques and geographic segment is derived from current market scenario and expected market trends

-Market attractiveness analysis has been included for various product segments, therapeutics, techniques and geographic regions with detailed analysis of factors responsible for rapid growth of the market segments

-In depth analysis of key market drivers, restraints and opportunities of non-invasive cancer diagnostic market with impact analysis

-Value chain analysis, Porter's five force model, top investment pockets (GE9 Cell Matrix) are analyzed and presented in detail in the report so that the decision makers can receive clear picture of cancer diagnosis market

KEY MARKET SEGMENTS

GLOBAL MARKET, BY THERAPEUTICS

- Solid tumors
- Blood cancer
- Lung Cancer
- Breast Cancer
- Others

GLOBAL MARKET, BY TECHNIQUES

- Clinical Chemistry
- Immunochemistry/Immunoassay
- Molecular Diagnostics
- Other Clinical Instruments

GLOBAL MARKET, BY GEOGRAPHY

- North America
- Europe
- Asia-Pacific
- RoW

KEY AUDIENCES

- Medical devices manufacturing companies
- Pharmaceutical companies
- Government and Private Research Institutes
- Academic Institutes

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Thiel, who believes that viewing death as inevitable is a sign of “complacency of the western world”, gave the money to Harvard University genomics professor George Church, whose laboratory is attempting to revive the extinct pachyderm.

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Chelsea Manning is to showcase an exhibition at New York’s Fridman Gallery in collaboration with the artist Heather Dewey-Hagborg.

Manning, who was released from prison last month after being sentenced in violation of the Espionage Act for disclosing classified government documents to WikiLeaks in 2013, will share A Becoming Resemblance from 2 August until 5 September. An announcement from the gallery said the exhibit would investigate “emerging technologies of genomic identity construction and our societal moment”, using cheek swabs and hair clippings Manning sent Dewey-Hagborg while she was in prison. Dewey-Hagborg used these DNA samples to create 3D-printed portraits of Manning, whose face was concealed from public view until her release on 17 May.

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          Metabolomics Market Worth $2,500.0 Million and CAGR 25.0% by 2021   

Metabolomics Market sales is growing at 25.0% CAGR till 2021

Deerfield Beach, FL -- (SBWIRE) -- 06/30/2017 -- Zion Market Research has published a new report titled "Metabolomics Market by Technology (Mass Spectrometry, Capillary Electrophoresis, High Performance Liquid Chromatography, Gas Chromatography, and Nuclear Magnetic Resonance Spectroscopy), Indication (Cardiology and Oncology) for Drug Discovery, Biomarker and Nutrigenomics : Global Industry Perspective, Comprehensive Analysis and Forecast, 2015 – 2021". According to the report, the global demand for metabolomics market was valued at over USD 675.0 million in 2015 and it is expected to reach above USD 2,500.0 million in 2021, growing at a CAGR of above 25.0% between 2016 and 2021.

Metabolites are substances or compounds found in the cell, they are intermediate products catalyzed by enzymes in the metabolism process. Signaling molecules, hormones, metabolic intermediates and secondary metabolites are some of the types of metabolites. Metabolism is the process to maintain a living state of cell. Metabolism can be either anabolism or catabolism. Anabolism is the process in which certain compounds are synthesized that is required for cells to process, while the breakdown of molecules for releasing energy is the catabolism. The metabolome is total set of metabolites present in a single organism. Metabolomics is study of chemical reactions related to metabolites and a field of analytical biochemistry. Metabolomics is used to compute and recognize the metabolites present in the cell via analytical technologies together with multi variant and statistical method for data interpretation.

Request For Free Sample Report: https://goo.gl/WsY3Yg

Increasing scope of toxicological studies, clinical trials, rise in awareness for health and government and institution funds for research is expected to drive the demand for the metabolomics market. Lack of adoption of metabolomics technology and complexity of the process can hamper the metabolomics market. Increasing research and development expenditure and existing demand from emerging economies and is likely to open new market avenues in the near future.

The metabolomics market is segmented on the basis of technology, indication, application, and region. Mass spectrometry, capillary electrophoresis, high-performance liquid chromatography, gas chromatography and nuclear magnetic resonance spectroscopy are some of the major segments based on technology. High-performance liquid chromatography was largest technology segment for metabolomics market. Drug discovery, biomarker, and nutrigenomics are some of the key application markets for metabolomics. Drug discovery emerged as dominating segment due to its significant role in optimization, prioritization, and Drug target validation and identification for research. Cardiology and Oncology are the indications for metabolomics.

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North America held 40% share in the global market and dominated the metabolomics market in 2015.This region remains competitive with the presence of a large number of vendors. Europe was the second largest market with over 30% share of the total share in the same year. Asia-Pacific is expected to witness rapid growth in the years to come.

Browse the full report at http://www.marketresearchstore.com/report/metabolomics-market-z55501

Key players in global metabolomics market include Danaher Corporation, Bruker Corporation, Waters Corporation, Metabolon, Inc., Agilent Technologies, Thermo Fisher Scientific and Shimadzu Corporation among others.

This report segments the metabolomics market as follows:

Technology Segment Analysis: High performance liquid chromatography, Mass spectrometry, Capillary electrophoresis, Gas Chromatography, Nuclear magnetic resonance spectroscopy

Indication Segment Analysis: Cardiology, Oncology

Application Segment Analysis: Drug Discovery, Biomarker, Nutrigenomic

Regional Segment Analysis: North America (US), Europe(Germany, France, UK), Asia Pacific(China, Japan, India), Latin America(Brazil), Middle East and Africa

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About Zion Market Research
Zion Market Research is an obligated company. We create futuristic, cutting edge, informative reports ranging from industry reports, company reports to country reports. We provide our clients not only with market statistics unveiled by avowed private publishers and public organizations but also with Vogue and newest industry reports along with pre-eminent and niche company profiles. Our database of market research reports comprises a wide variety of reports from Cardinal Industries. Our database is been updated constantly in order to fulfill our clients with prompt and direct online access to our database. Keeping in mind the client's needs, we have included expert insights on global industries, products, and market trends in this database. Last but not the least, we make it our duty to ensure the success of clients connected to us—after all—if you do well, a little of the light shines on us.

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          Swift Biosciences attracts $12.2 mln Series D   
Swift Biosciences, a provider of library prep solutions for genomic sequencing, has closed $12.2 million in Series D funding. Arboretum Ventures led the round. Concurrent with the funding, Dan Kidle, a principal at Arboretum Ventures and Mark Lewis, a former senior vice president at Illuminato, have been added to Swift's board of directors.
          Genomic Medicine Market Growth Set to Surge Significantly during 2016-2026   
(EMAILWIRE.COM, July 01, 2017 ) The National Human Genome Research Institute defines genomic medicine as “an emerging medical discipline that involves using genomic information about an individual as part of their clinical care (e.g., for diagnostic or therapeutic decision-making) and the health...
          Zika researchers take questions at 10 a.m. today on Reddit   

Curious about Zika virus ? Scientists studying the virus and its transmission will hold a question-and-answer session on Reddit at 10 a.m. Pacific time today. --- Kristian Andersen, an Assistant Professor at The Scripps Research Institute and Director of Infectious Disease Genomics at the Scripps Translational Science Institute.


          POSTHUMOUS SIGHTINGS OF PASSENGER PIGEONS?   

Passenger pigeons (juvenile, left; male, centre; female, right), from Birds of New York by Louis Agassiz Fuertes, 1910 – did this species survive beyond 1914? (public domain)

The most numerous species of wild bird ever known was the phenomenally plentiful passenger pigeon Ectopistes migratorius, a dainty, slender-bodied, long-tailed bird with blue-grey head, neck, back, and wings, and cinnamon-pink underparts. It has been estimated that during the 19thCentury’s early years, its total population contained between five and ten thousand million birds. Or to put it another way, this single species may have accounted for as much as 45 per cent of the entire bird population of America! One of the most evocative descriptions of its immense numbers during its heyday appeared in The Mirror of Literature, Amusement, and Instruction for 16 November 1822:
 
The accounts of the enormous flocks in which the passenger, or wild pigeons, fly about in North America, seem to an European like the tales of Baron Munchausen; but the travellers are ‘all in a story.’ In Upper Canada, says Mr. Howison, in his entertaining ‘Sketches,’ you may kill 20 or 30 at one shot, out of the masses which darken the air. And in the United States, according to Wilson, the ornithologist, they sometimes desolate and lay waste a tract of country 40 or 50 miles long, and 5 or 6 broad, by making it their breeding-place. While in the state of Ohio, Mr. Wilson saw a flock of these birds which extended, he judged, more than a mile in breadth, and continued to pass over his head at the rate of one mile in a minute, during four hours — thus making its whole length about 240 miles. According to his moderate estimate, this flock contained two thousand two hundred and thirty millions, two hundred and seventy-two pigeons.

A flock of passenger pigeons being hunted in Louisiana, The Illustrated Shooting and Dramatic News, 1875 (public domain)

It seems inconceivable that less than a century after the above report had been published the passenger pigeon had been completely exterminated, but this is precisely what happened.

As a result of an unutterably ruthless, relentless programme of persecution (on a scale unparalleled even in man’s nefarious history of wildlife destruction), perpetrated by trigger-happy gun-toters attracted by the awesome spectacle of the birds’ mass migrations, by 1 September 1914 only one solitary specimen remained alive. This was a 29-year-old hen bird named ‘Martha Washington’, exhibited at Cincinnati Zoo. And shortly after noonon that fateful September day, this last humble survivor of an ostensibly indomitable, indestructible species died. The unthinkable had happened - the passenger pigeon, whose vast migrating flocks had virtually eclipsed the sun in the time of the great American painter John James Audubon, was no more.

Martha Washington, the last known passenger pigeon, pictured alive on left, and as a taxiderm specimen at Washington DC's Smithsonian Institution on right (public domain)

Officially, that is. For at least another decade, alleged sightings of passenger pigeons were frequently reported, but scientists tended to dismiss these as mistaken observations of the smaller but superficially similar mourning dove Zenaida macroura, still a common species today. In September 1929, however, a remarkable report emerged that could not be discarded so readily. This was the month in which Michigan University bacteriologist Prof. Philip Hadley, in the company of a Mr Foard, an old friend familiar with the land, had been hunting in a virtually uninhabited wilderness nestling within Michigan’s northern peninsula.

They had been hunting there for some time when Foard drew Hadley’s attention to a bird perched close by, and declared that it was a passenger pigeon - which he had observed in enormous numbers when younger. Needless to say, Hadley turned at once to spy this exceedingly unexpected specimen, but just as he caught sight of it the bird took flight. Nevertheless, it did seem to him to be pigeon-like in form, with a pointed tail, and he clearly believed the incident to be of significance, because he sent details to the eminent US journal Science, which in turn judged it to be important enough to warrant publication in its issue of 14 February 1930.

Passenger pigeon, from Pigeons, Sir William Jardine, 1835 (public domain)

Within his letter, Hadley also referred to a couple of other recent sightings, documented a month earlier by Kendrick Kimball in the Detroit News (5 January). One of these sightings had been made on 10 June 1929, by Robert H. Wright of Munissing, Michigan. Wright was convinced that the pair of birds that he saw at close range on Highway M-28, about 16 miles from Munissing, were passenger pigeons. In the other sighting, made between Indianapolis and Kokomo while driving from Florida, Dr Samuel R. Landes spotted a flock of approximately 15 birds that he readily identified as passenger pigeons. Both Wright and Landes were familiar with this species’ appearance — like so many others, they had shot hundreds of them during the late 1870s.

Nonetheless, the last confirmed wild specimen was shot in 1899, at Babcock, Wisconsin, so is it really possible that the birds reported three decades later by the eyewitnesses above were truly passenger pigeons? It seems rather unlikely, at least at first, because after the last major flocks had been slaughtered (in 1878), stragglers did not survive long, and matings became ever fewer. It seemed as if the species could only persist and reproduce when present in huge flocks. At the same time, of course, the familiarity of the eyewitnesses with the species makes their testimony all that more difficult to discount.

A pair of taxiderm passenger pigeons at San Antonio, Texas (© Jonathan Downes/CFZ)

Perhaps certain fairly secluded localities did house a last few specimens, which existed undetected beyond the date of Martha’s death, and possibly even mated every now and then, and which were encountered only when their flights traversed areas frequented by humans, or when humans occasionally passed by their hideaways. Yet without the immense congregations necessary to provide the stimulus for normal, full-scale reproduction, they could surely do no more than extend their species’ survival by a few years. Long before the last individual had died, whether in 1914 or in the 1930s, the passenger pigeon’s descent into extinction had already begun, irrevocably and inevitably, with the disappearance of its vast flocks. After that, it could only be a matter of time.

Surely, then, the ‘passenger pigeon’ spied in March 1965 at Homer, Michigan, by Irene Llewellyn (Fate, September 1965) and another spied the same year by Stella Fenell at New Jersey’s Park Ridge (Fate, January 1966), not to mention an intriguing series of recently-claimed passenger pigeon sightings chronicled online in 2014, 2015, and 2016 by the website HoriconBirds.com, were only mourning doves ... weren’t they?

John James Audubon's famous painting of a pair of passenger pigeons, from his spectacular tome The Birds of America, 1827-1838 (public domain)

An Antipodean equivalent of sorts is the flock pigeon Phaps (=Histriophaps)histrionica, also known as the flock bronzewing. In the 1800s, huge flocks, containing millions of birds, lived on the grass plains of New South Wales and Queensland. Today, though, it is a relatively rare species (it was once thought to be extinct), categorised as Threatened by the IUCN.

This time, however, the cause is not man himself but his animals. The flock pigeon is a seed-eater, but generations of grazing cattle and sheep have prevented the plains’ grass from seeding adequately.

A flock pigeon (© Christopher Walker/Wikipedia – CC BY-SA 3.0 licence)

Of course, courtesy of the extraordinary technological advances taking place daily in the modern-day world that we all inhabit, perhaps we should never say never in relation to the prospect of one day seeing bona fide passenger pigeons alive and well again. On 8 February 2012, a meeting was convened at Harvard Medical School in Boston, Massachusetts, by a group of interested researchers from the non-profit genetic research organisation Revive & Restore, to explore the technical plausibility of resurrecting this iconic species via genomic engineering, as well as to examine the potential cultural, social, political, and ecological ramifications of restoring it to life and perhaps even reintroducing it into the wild. After presentations by a range of participants and discussions concerning their contributions, the group concluded that the genetic technique proposed should be tested to see how effective it may be, and how it could be improved, with this goal in mind.

So who knows? Maybe one day the passenger pigeon will indeed return, if no longer to darken the skies with vast flocks as in former times but at least to live again in the land where it rightfully belongs and where it would certainly have remained had its existence not been wilfully extinguished by our own species.

Passenger pigeons, frontispiece to The Passenger Pigeon, 1907 (public domain)

Finally: by an extraordinary quirk of fate, one of the last passenger pigeon individuals whose demise in the wild state was formally documented was actually shot not anywhere in the New World but, remarkably, in the English countryside instead. An escapee from captivity, it was shot in Yorkshire during 1876, as recorded in  T.A. Coward's book The Birds of the British Isles and Their Eggs - Second Series (1920). Moreover, this was just one of at least eight passenger pigeon specimens recorded from the wild in Great Britain.

Were all of them merely captive escapees, or might one or more have been genuine transatlantic vagrants? Sadly, it is highly unlikely that we shall ever know the answer to this intriguing question. My grateful thanks to correspondent Philip Jensen for kindly bringing this fascinating snippet of information to my attention.

Passenger pigeon, Plate 23 in Vol 1 of The Natural History of Carolina, Florida and Bahamas by Mark Catesby, George Edwards, 1754 (public domain)

For my tribute in verse to the passenger pigeon, please click here; and for its philatelic prominence, please click here.

This ShukerNature blog article is excerpted and expanded from my book Extraordinary Animals Revisited.







          EACR17 Cancer Genomics Day 3   
Churchill College, Cambridge: Yesterday heralded the 4th and final day of the EACR Cancer Genomics conference with some invited speakers…
          English speaking customer support engineer night shift AK munkakörbe keresünk munkatársat. | Fe...   
English speaking customer support engineer night shift AK munkakörbe keresünk munkatársat. | Feladatok: Triage level response to all technical support questions mainly for our US customers within 48 hours • Log Support Cases with Jira • Work as part of the Global Support Team • Work closely and collaborate with the other teams including Quality Management Team, Research & Development Team, including product testing • Assist with Workshops, on-site installation • Additional duties as required. | Elvárások: Bachelors or Masters degree in IT - Bio-IT field molecular biology, genomics or similar will be advantageous • 3+ years in a Technical Support role at a company with a scientific focus • Fluent English is a must • Experience with networking and command line tools • Technical/analytical mindset - strong troubleshooting skills • Ability to prioritize and work under pressure • Self-motivated, works well under minimal supervision • Confident strong communicator • High energy level; positive attitude; works well in a rapidly evolving business environment | További elvárások: Familiarity with Salesforce, MS Office products, Google-Docs, Jira, Java, SQL • Experience with remote support e.g. TeamViewer, GoToMeeting, Skype • Experience with configuration and troubleshooting on Windows or Linux or OS X the rest can be learned on the job • Active collaboration with key stakeholders in the Europe and US offices • Willingness to learn in all fields connected to the role. | További infó és jelentkezés itt: www.profession.hu/allas/1036303
          Genetic Testing Raises New Questions About Race -- A Conversation with Dr. Charmaine Royal   
'With the rise of a competitive market for personal gene testing, the tool is becoming more available and affordable to the public. People can now swab their cheek, send the sample off to a lab, and wait patiently for a private company with a massive gene database to tell them where in the world their genes are from. But what do these tests reveal about personal identity and what do they imply about race? State of Things host Frank Stasio talks with Glen Fisher, financial aid advisor at Durham Technical Community College, who took a DNA ancestry test, and Charmaine Royal, associate professor in the department of African and African-American studies at Duke and the founding director of the Duke Center on Genomics, Race, Identity, Difference.' -- WUNC 91.5






          Sr. / Research Technician / Research Assistant - Oklahoma Medical Research Foundation - Oklahoma City, OK   
We utilize both animal and cellular models, and cutting edge technologies in functional genomics, bioinformatics, genetics, molecular and cell biology, and...
From Indeed - Fri, 26 May 2017 13:59:53 GMT - View all Oklahoma City, OK jobs
          Software Developer 2 - Lawrence Berkeley National Laboratory - Berkeley, CA   
HTML/CSS, Javascript, or work with native UI API’s. Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Software Developer 2....
From Lawrence Berkeley National Laboratory - Tue, 13 Jun 2017 22:58:55 GMT - View all Berkeley, CA jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Experience with UI testing and user-centered design. Demonstrated experience to write high-performance, readable/reusable code for UI components which work...
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Precision Medicine and Biomarkers Leaders Summit   

The 4th Global Precision Medicine & Biomarkers Leaders Summit Examining ground breaking Biomarker, Companion Diagnostic, Immuno-Oncology, Genomic & Big Data and AI research to facilitate the development of impactful personalized treatments for patients.This expanding international event attracts the leading authorities worldwide working in companion diagnostics, big data, genomics, biomarkers, immuno-oncology and other facets of precision medicine. … Continue reading Precision Medicine and Biomarkers Leaders Summit

The post Precision Medicine and Biomarkers Leaders Summit appeared first on Almac.


          Tri-D Dynamics Aspires to Print Rocket Components for New Space Age   
In tech circles, amid the chatter about terrestrial innovations such as artificial intelligence, machine learning, and genomics, there’s excitement building around another important emerging sector: private space travel. Tesla’s Elon Musk, Amazon’s Jeff Bezos, Virgin’s Richard Branson, and Microsoft co-founder Paul Allen all have private space ventures underway. NASA is once again ramping up its […]
          June 2014 Highlights   

Editor-in-chief Shawn Kennedy and Clinical Managing Editor Karen Roush present the highlights of the June issue of the American Journal of Nursing. A newborn appears on our cover this month, relating to our first CE, “Genomic Breakthroughs in the Diagnosis and Treatment of Cystic Fibrosis.” Our second CE (with podcast) discusses the health care disparities faced by the LGBT population.

We have the fourth installment of our systematic reviews series focusing on study selection and critical appraisal. Our Mental Health Matters column provides an overview of clinical depression and a new treatment: transcranial direct current stimulation. And an Ethical Issues column addresses the implications of denying smokers employment in health care, and Shawn Kennedy speaks with the author in a podcast this month. In addition, there’s an AJN Reports column on whether nurses are ready for retirement, News, Reflections, Viewpoint, Drug Watch, Art of Nursing, and more.

          2nd DNA Replication as a Source of DNA Damage Conference   
The maintenance of genome integrity is critical for the suppression of cancer and premature ageing. Only recently has it become appreciated that DNA replication stress is a crucial driver of genomic instability. The timely progression of replisomes can be disrupted by lesions and secondary structure...
          CRISPR Platform Scans DNA to Predict Off-Target Effects   
If you’re reworking a genome, you might want to heed the old saying, “Measure twice, cut once.” Otherwise, your attempts to right the genome or modify it for special purposes could end in genomic wrongs—off-target effects. For example, the popular gene-editing tool known as CRISPR could go astray, altering genes other than the ones it was meant to alter. If only CRISPR’s potential slips could be foreseen! Then, perhaps, they could be avoided, and CRISPR would realize its potential not only in research, but also in medicine. Scientists from The University of Texas at Austin took an important step toward safer gene-editing cures for life-threatening disorders, from cancer to HIV to Huntington's disease, by developing CHAMP, which stands for chip-hybridized association-mapping platform. It repurposes next-generation sequencing chips to enable the massively parallel profiling of protein–nucleic acid interactions. The scientists used CHAMP to provide the first comprehensive survey ...
          Inhibition of Polyunsaturated Fatty Acids Synthesis Decreases Growth Rate and Membrane Fluidity of Rhodosporidium kratochvilovae at Low Temperature.   
Related Articles

Inhibition of Polyunsaturated Fatty Acids Synthesis Decreases Growth Rate and Membrane Fluidity of Rhodosporidium kratochvilovae at Low Temperature.

Lipids. 2017 Jun 28;:

Authors: Wang J, Chen W, Nian H, Ji X, Lin L, Wei Y, Zhang Q

Abstract
The intention of this study was to investigate the role of polyunsaturated fatty acids (PUFA) in the cold adaptation of Rhodosporidium kratochvilovae YM25235 by knockout of the Δ(12)/Δ(15)-fatty acid desaturase gene (RKD12) to inactivate Δ(12)/Δ(15)-fatty acid desaturase. Polymerase chain reaction (PCR) amplification was used to detect the genomic structure of RKD12 gene in YM25235. The RKD12 gene was knocked out by DNA homologous recombination to inhibit the biosynthesis of PUFA. Then, the contents of linoleic acid (LNA) and α-linolenic acid (ALA) after gene knockout were investigated using a gas chromatography-mass spectrometer, followed by determination of the growth rate and membrane fluidity of YM25235 at low temperature. After PCR amplification, a 1611 bp genomic fragment was amplified from YM25235. When the RKD12 gene was knocked out, the contents of LNA and ALA in YM25235 significantly decreased. The growth rate and membrane fluidity of YM25235 decreased significantly at low temperature. Inhibition of PUFA biosynthesis by RKD12 gene knockout influenced cold adaptation of YM25235 by decreasing the PUFA content in cell membranes and reducing the growth rate and membrane fluidity of YM25235 at low temperature.

PMID: 28660529 [PubMed - as supplied by publisher]


          IT Deskside Support - Bilingual - Eurofins Canada - Toronto, ON   
We are also number one in the field of environmental laboratory services and one of the global market leaders in agroscience, genomics, discovery pharmacology,...
From Indeed - Fri, 09 Jun 2017 12:58:51 GMT - View all Toronto, ON jobs
          Transformation and Growth Opportunities in the US Next-Generation Sequencing Informatics Market, 2021 - Research and Markets   
...the author expects a significant growth in mergers, acquisitions, and partnerships. At the same time, given the growing applications of healthcare Big Data tools in genomics data interpretation, the market is expected to witness the entry of several healthcare information technology ...

          We Can Now Build Biomolecules From Computer Code — No Humans Necessary - Futurism   

Futurism

We Can Now Build Biomolecules From Computer Code — No Humans Necessary
Futurism
Synthetic Genomics has created a digital-to-biological converter that uses digital code to create biologics like DNA, RNA, proteins, and viral particles. This may have major implications for space colonization, fighting disease outbreaks, and ...


          The messenger in Huntington's disease   
A research effort at the Centre for Genomic Regulation in Barcelona, Spain, reveals new molecular mechanisms of Huntington's disease.
          Everything is genetic, isn't it?   
There is hardly a trait, physical or behavioral, for which there is not at least some familial resemblance, especially among close relatives.  And I'm talking about what is meant when someone scolds you saying, "You're just like your mother!"  The more distant the relatives in terms of generations of separation, the less the similarity.  So you really can resist when told, "You're just like your great-grandmother!" The genetic effects decline in a systematic way with more distant kinship.

The 'heritability' of a trait refers to the relative degree to which its variation is the result of variation in genes, the rest being due to variation in non-genetic factors we call 'environment'.  Heritability is a ratio that ranges from zero when genes have nothing to do with the trait, to 1.0 when all the variation is genetic.  The measure applies to a sample or population and cannot automatically be extended to other samples or populations, where both genetic and environmental variation will be different, often to an unknown extent.

Most quantitative traits, like stature or blood pressure or IQ scores show some amount, often quite substantial, of genetic influence.  It often happens that we are interested in some trait that we think must be produced or affected by genes, but that no relevant factor, like a protein, is known.  The idea arose decades ago that if we could scan the genome, and compare those with different manifestations of the trait, using mapping techniques like GWAS (genomewide association studies), we could identify those sites, genomewide, whose variation in our chosen sample may affect the trait's variation.  Qualitative traits like the presence or absence of a disease (say, diabetes or hypertension), may often be due to the presence of some set of genetic variants whose joint impact exceeds some diagnostic threshold, and mapping studies can compare genotypes in affected cases to unaffected controls to identify those sites.

Genes are involved in everything. . . . .
Many things can affect the amount of similarity among relatives, so one has to try to think carefully about attributing ideas of similarity and cause.  Some traits, like stature (height) have very high heritability, sometimes estimated to be about 0.9, that is, 90% of the variation being due to the effects of genetic variation.  Other traits have much lower heritability, but there's generally familial similarity.  And, that's because we each develop from a single fertilized egg cell, which includes transmission of each of our parent's genomes, plus ingredients provided by the egg (and perhaps to a tiny degree sperm), much of which were the result of gene action in our parents when they produced that sperm or egg (e.g., RNA, proteins).  This is why traits can usually be found to have some heritability--some contribution due to genetic variation among the sampled individuals.  In that sense, we can say that genes are involved in everything.

Understanding the genetic factors involved in disease can be important and laudatory, even if tracking them down is a frustrating challenge.  But because genes are involved in everything, our society also seems to have an unending lust for investigators to overstate the value of their findings or, in particular, to estimate or declaim on the heritability, and hence genetic determination, of the most societally sensitive traits, like sexuality, criminality, race, intelligence, physical abuse and the like.

. . . . . but not everything is 'genetic'!

If the estimated heritability for a trait we care about is substantial, then this does suggest the obvious: genes are contributing to the mechanisms of the trait and so it is reasonable to acknowledge that genetic variation contributes to variation in the trait.  However, the mapping industry implies a somewhat different claim: it is that genes are a major factor in the sense that individual variants can be identified that are useful predictors of the trait of interest (NIH's lobbying machine has been saying we'll be able to predict future disease with 'precision').  There has been little constraint on the types of trait for which this approach, sometimes little more than belief or wishful-thinking, is appropriate.

It is important to understand that our standard measures of genes' relative effect are affected both by genetic variation and environmental lifestyle factors.  That means that if environments were to change, the relative genetic effects, even in the very same individuals, would also change.  But it isn't just environments that change; genotypes change, too, when mutations occur, and as with environmental factors, these change in ways that we cannot  predict even in principle.  That means that we cannot legitimately extrapolate, to a knowable extent, the genetic or environmental factors we observe in a given sample or population, to other, much less to future samples or populations.  This is not a secret problem, but it doesn't seem to temper claims of dramatic discoveries, in regard to disease or perhaps even more for societally sensitive traits.

But let's assume, correctly, that genetic variation affects a trait.  How does it work?  The usual finding is that tens or even hundreds of genome locations affect variation in the test trait.  Yet most of the effects of individual genes are very small or rare in the sample.  At least as important is that the bulk of the estimated heritability remains unaccounted for, and unless we're far off base somehow, the unaccounted fraction is due to the leaf-litter of variants individually too weak or too rare to reach significance.

Often it's also asserted that all the effects are additive, which makes things tractable: for every new person, not part of the study, just identify their variants and add up their estimated individual effects to get the total effect on the new person for whatever publishable trait you're interested in.  That's the predictive objective of the mapping studies.  However, I think that for many reasons one cannot accept that these variable sites' actions are truly additive. The reasons have to with actual biology, not the statistical convenience of using the results to diagnose or predict traits.  Cells and their compounds vary in concentrations per volume (3D), binding properties (multiple dimensions), surface areas (2D) and some in various ways that affect how how proteins are assembled and work, and so on.  In aggregate, additivity may come out in the wash, but the usual goal of applied measures is to extrapolate these average results to prediction in individuals.  There are many reasons to wish that were true, but few to believe it very strongly.

Even if they were really additive, the clearly very different leaf-litter background that together accounts for the bulk of the heritability can obscure the numerical amount of that additivity from sample to sample and person to person.  That is, what you estimated from this sample, may not apply, to an unknowable extent, to the next sample.  If and when it does works, we're lucky that our assumptions weren't too far off.

Of course, the focus and promises from the genetics interests assume that environment has nothing serious to do with the genetic effects.  But it's a major, often by far the major, factor, and it may even in principle be far more changeable than genetic variation.  One would have to say that environmental rather than genetic measures are likely to be, by far, the most important things to change in society's interest.

We regularly write these things here not just to be nay-sayers, but to try to stress what the issues are, hoping that someone, by luck or insight, finds better solutions or different ways to approach the problem that a century of genetics, despite its incredibly huge progress, has not yet done.  What it has done is in exquisite detail to show us what the problems are.

A friend and himself a good scientist in relevant areas, Michael Joyner, has passed on a rather apt suggestion to me, that he says he saw in work by Denis Noble.  We might be better off if we thought of the genome as a keyboard rather than as a code or program.  That is a good way to think about the subtle point that, in the end, yes, Virginia, there really are genomic effects: genes affect every trait....but not every trait is 'genetic'!
          More thoughts, and just plain provocateuring, on genomic causal complexity. . . .    
Here are some follow-up reflections on my recent post about GWAS and kindred methods and claims.  I know I'm being contentious, but science has always been contentious.  However, socioeconomic issues (careers, salaries, etc) also enter the picture in a way that is relevant to the inertial nature of our profession.  Readers who haven't read Ludwik Fleck's 1930's volume on 'thought collectives', one preceding Kuhn's 'normal science/paradigm' discussion, should do that, because it's relevant to where we stand now.

The causal complexity of genetic control of quantitative traits was in principle understood by Fisher and others almost exactly century ago.  The development of mapping tools opened the door to seeing what that meant more specifically, at the genome level.

Some key facts about this, I think, are that when there is a strong single signal, we see segregation in families (when there are enough families, as there were in Utah for BRCA mapping), or some other indicator (detectable deletion chromosome detection in Wilm's tumor and perhaps something similar in Retinoblastoma).  Those were families and mainly monogenic in the Mendelian sense (that is, of the traits Mendel carefully chose to study for their simple states).

But BRCA and I think for different reasons, retinitis pigmentosa, mapping by association rather than families doesn't find these genes 'for' the trait.  They're individually strong, but relatively minor on a population and hence association-mapping sense.  And, in nearly all cases, even with 'single locus' diseases, once the gene is known, we see genotypic complexity, including often very low 'penetrance' (showing that 'the' gene isn't a single-locus cause by itself).

BRCA-associated breast cancer risk, once the gene was known and could specifically be typed, is very different even among women carrying known high-risk BRCA1/2 alleles, depend on cohort and the study.  The purported single-locus Hemochromatosis gene (HFE) mutations are associated with high risk in the original sample, in Utah if my recollection is correct, but the mutation does not cause the disease in other samples.  Even the classic PKU is not always caused by PAH alleles, not all pathogenic PAH alleles cause PKU.  Ditto for CF and the CFTR gene.  In some cases, at least, it is likely other interacting genes that in particular populations lead the target gene to seem causal in a Mendelian-like sense.

And of course there is now a substantial literature showing that individuals carrying dead (non-activated) disease-causing genes are walking around without the disease.  I think estimates have shown that each of us carries many (100 or so?) such genes, at least some if not all of which are diploid-negative.  If this doesn't suggest pervasive redundancy and the mappability problems I and others have written about, what does it suggest?

I will once again utter the apparently off-color factor that few want to acknowledge or say in mixed company: somatic mutation. Enough said on that black-box subject.

And while invoking the Truth's name in vain, I'll just whisper here another off-color word: environment.  Enough said on that black-box subject, too.

And there is the non-reductionistic 4th dimension of genetic causation in cells, which is being studied by chromosomal conformation methods (3C and its variants).  What this will lead to is unclear, to me anyway, but clearly there are extensive trans phenomena that methods for sequence parsing and enumerating methods, par for the course now for many decades, are not solving.  If they were working, we wouldn't need a plethora of new terms, and gilded promises from on high (i.e., NIH).

I've often mentioned that much of what we do relies on statistical inference.  That's been getting a well-deserved bad name, but rest assure that the SAS and SPSS people will guarantee you that their packages or use-instructions have been fixed so they won't lead you astray any further.  Nonetheless, there is this third little secret: statistical methods in this arena assume various aspects of replicability while adaptive evolution is fundamentally about non-replicability.

In any case, estimating risk-factor (causal SNP) effects retrospectively is data-fitting and not, in itself, related to cause or prediction, much less doing so with 'precision'.  Such extrapolation rests on the assumption that past fractions mean future probability, which is critical here (especially when sampling, environment, mutation, somatic mutation etc. are inherently unpredictable and essentially non-replicable).

And is it too identity-political to mention that there is the unseemly fact that most of this intensive mapping work has been done on Europeans for the sometimes even openly acknowledged rationale that Europeans have the moolah to pay for the gene-targeted drugs that Pharma has been promising for decades of the genome era? In any case, that's mere racism relative to the deeper genetic-causal issues themselves.  Even restrictive sampling doesn't guarantee replicability; a point I won't mention again lest I be accused of being as repetitive as someone doing GWAS on obesity.

These are just the simple issues one can conjure up without even doing any PubMed searching.  What amount of hammering does it take to get the message to sink in?  By sinking in I mean not just being noted, briefly and in passing, but to force some change of approach beyond enumerating, random sampling, and cachet marketing words (like gene regulatory networks, precision genomic medicine, omingenic, and all the 'omics'-du-jour, etc.).

I would want to be clear even for those who wish to trash all my thoughts: Go ahead!  But at least acknowledge, as I acknowledged in my previous post, that the mapping era did do us great service by providing, for the first time, some specific sense of the genomic details underlying life's causal complexity and showing that in a general sense the original polygenic model was basically right.  Family studies are better when some really meaningfully single strong factor is at work, but the use of IBD assumptions to do association mapping cast, like a flashlight in the dark, light upon what had perforce remained dark to our understanding.  But it's now been quite a while that we have had the understanding we need to know that we should think of different ways to approach the subject of life's causation.  The flashlight's batteries are fading.

And here's my bit of sympathy for what is going on.  Complementing the complexity landscape that is the obvious reality are the key facts underlying all of this: scientists are people and, including yours truly, have limited abilities and can't just facilely be slammed for their not accounting for everything perfectly and immediately.  We're people who, mainly, need salaries, facilities in which to work, and employers like universities who these days have to operate in the black.  These are the deeply socioeconomic underlying problems that serve to encourage or even to force safe science, big science, and oversold science.  That the news media and other vested interests compound the felony is simply one of the problems of our type of imperfect society.

Moving the Big Money that has been locked up by the current haves, to redistribute to more important-payoff kinds of research would inevitably meet resistance, including from NIH's head office, which has been a sloganeering center that makes PT Barnum look like an amateur.  Whether or how or how much redirection of funding, which is what's actually at the unstated core of much of the controversy, is obviously not predictable.  But the importance of trying is what motivates my perhaps too-often and too-cranky posts:  Somebody has to speak of the Emperor's clothes!

Until we fix these underlying issues, whatever mess our current thrust is embedding us in, they will persist until some lucky day when an actually better idea stumbles upon the stage.
          The GWAS hoax....or was it a hoax? Is it a hoax?   
A long time ago, in 2000, in Nature Genetics, Joe Terwilliger and I critiqued the idea then being pushed by the powers-that-be, that the genomewide mapping of complex diseases was going to be straightforward, because of the 'theory' (that is, rationale) then being proposed that common variants caused common disease.  At one point, the idea was that only about 50,000 markers would be needed to map any such trait in any global populations.  I and collaborators can claim that in several papers in prominent journals, in a 1992 Cambridge Press book, Genetic Variation and Human Disease, and many times on this blog we have pointed out numerous reasons, based on what we know about evolution, why this was going to be a largely empty promise.  It has been inconvenient for this message to be heard, much less heeded, for reasons we've also discussed in many blog posts.

Before we get into that, it's important to note that unlike me, Joe has moved on to other things, like helping Dennis Rodman's diplomatic efforts in North Korea (here, Joe's shaking hands as he arrives in his most recent trip).  Well, I'm more boring by far, so I guess I'll carry on with my message for today.....




There's now a new paper, coining a new catch-word (omnigenic), to proclaim the major finding that complex traits are genetically complex.  The paper seems solid and clearly worthy of note.  The authors examine the chromosomal distribution of sites that seem to affect a trait, in various ways including chromosomal conformation.  They argue, convincingly, that mapping shows that complex traits are affected by sites strewn across the genome, and they provide a discussion of the pattern and findings.

The authors claim an 'expanded' view of complex traits, and as far as that goes it is justified in detail. What they are adding to the current picture is the idea that mapped traits are affected by 'core' genes but that other regions spread across the genome also contribute. In my view the idea of core genes is largely either obvious (as a toy example, the levels of insulin will relate to the insulin gene) or the concept will be shown to be unclear.  I say this because one can probably always retroactively identify mapped locations and proclaim 'core' elements, but why should any genome region that affects a trait be considered 'non-core'?

In any case, that would be just a semantic point if it were not predictably the phrase that launched a thousand grant applications.  I think neither the basic claim of conceptual novelty, nor the breathless exploitive treatment of it by the news media, are warranted: we've known these basic facts about genomic complexity for a long time, even if the new analysis provides other ways to find or characterize the multiplicity of contributing genome regions.  This assumes that mapping markers are close enough to functionally relevant sites that the latter can be found, and that the unmappable fraction of the heritability isn't leading to over-interpretation of what is 'mapped' (reached significance) or that what isn't won't change the picture.

However, I think the first thing we really need to do is understand the futility of thinking of complex traits as genetic in the 'precision genomic medicine' sense, and the last thing we need is yet another slogan by which hands can remain clasped around billions of dollars for Big Data resting on false promises.  Yet even the new paper itself ends with the ritual ploy, the assertion of the essential need for more information--this time, on gene regulatory networks.  I think it's already safe to assure any reader that these, too, will prove to be as obvious and as elusively ephemeral as genome wide association studies (GWAS) have been.

So was GWAS a hoax on the public?
No!  We've had a theory of complex (quantitative) traits since the early 1900s.  Other authors argued similarly, but RA Fisher's famous 1918 paper is the typical landmark paper.  His theory was, simply put, that infinitely many genome sites contribute to quantitative (what we now call polygenic) traits.  The general model has jibed with the age-old experience of breeders who have used empirical strategies to improve crop, or pets species.  Since association mapping (GWAS) became practicable, they have used mapping-related genotypes to help select animals for breeding; but genomic causation is so complex and changeable that they've recognized even this will have to be regularly updated.

But when genomewide mapping of complex traits was first really done (a prime example being BRCA genes and breast cancer) it seemed that apparently complex traits might, after all, have mappable genetic causes. BRCA1 was found by linkage mapping in multiply affected families (an important point!), in which a strong-effect allele was segregating.  The use of association mapping  was a tool of convenience: it used random samples (like cases vs controls) because one could hardly get sufficient multiply affected families for every trait one wanted to study.  GWAS rested on the assumption that genetic variants were identical by descent from common ancestral mutations, so that a current-day sample captured the latest descendants of an implied deep family: quite a conceptual coup based on the ability to identify association marker alleles across the genome identical by descent from the un-studied shared remote ancestors.

Until it was tried, we really didn't know how tractable such mapping of complex traits might be. Perhaps heritability estimates based on quantitative statistical models was hiding what really could be enumerable, replicable causes, in which case mapping could lead us to functionally relevant genes. It was certainly worth a try!

But it was quickly clear that this was in important ways a fool's errand.  Yes, some good things were to be found here and there, but the hoped-for miracle findings generally weren't there to be found. This, however, was a success not a failure!  It showed us what the genomic causal landscape looked like, in real data rather than just Fisher's theoretical imagination.  It was real science.  It was in the public interest.

But that was then.  It taught us its lessons, in clear terms (of which the new paper provides some detailed aspects).  But it long ago reached the point of diminishing returns.  In that sense, it's time to move on.

So, then, is GWAS a hoax?
Here, the answer must now be 'yes'!  Once the lesson is learned, bluntly speaking, continuing on is more a matter of keeping the funds flowing than profound new insights.  Anyone paying attention should by now know very well what the GWAS etc. lessons have been: complex traits are not genetic in the usual sense of being due to tractable, replicable genetic causation.  Omnigenic traits, the new catchword, will prove the same.

There may not literally be infinitely many contributing sites as in the original statistical models, be they core or peripheral, but infinitely many isn't so far off.  Hundreds or thousands of sites, and accounting for only a fraction of the heritability means essentially infinitely many contributors, for any practical purposes.  This is particularly so since the set is not a closed one:  new mutations are always arising and current variants dying away, and along with somatic mutation, the number of contributing sites is open ended, and not enumerable within or among samples.

The problem is actually worse.  All these data are retrospective statistical fits to samples of past outcomes (e.g., sampled individuals' blood pressures, or cases' vs controls' genotypes).  Past experience is not an automatic prediction of future risk.  Future mutations are not predicable, not even in principle.  Future environments and lifestyles, including major climatic dislocations, wars, epidemics and the like are not predictable, not even in principle.  Future somatic mutations are not predictable, not even in principle.

GWAS almost uniformly have found (1) different mapping results in different samples or populations, (2) only a fraction of heritability is accounted for by tens, hundreds, or even thousands of genome locations and (3) even relatively replicable 'major' contributors, themselves usually (though not always) small in their absolute effect, have widely varying risk effects among samples.

These facts are all entirely expectable based on evolutionary considerations, and they have long been known, both in principle, indirectly, and from detailed mapping of complex traits.  There are other well-known reasons why, based on evolutionary considerations, among other things, this kind of picture should be expected.  They involve the blatantly obvious redundancy in genetic causation, which is the result of the origin of genes by duplication and the highly complex pathways to our traits, among other things.  We've written about them here in the past.  So, given what we now know, more of this kind of Big Data is a hoax, and as such, a drain on public resources and, perhaps worse, on the public trust in science.

What 'omnigenic' might really mean is interesting.  It could mean that we're pressing up ever more intensely against the log-jam of understanding based on an enumerative gestalt about genetics.  Ever more detail, always promising that if we just enumerate and catalog just a bit (in this case, the authors say we need to study gene regulatory networks) more we'll understand.  But that is a failure to ask the right question: why and how could every trait be affected by every part of the genome?  Until someone starts looking at the deeper mysteries we've been identifying, we won't have the transormative insight that seems to be called for, in my view.

To use Kuhn's term, this really is normal science pressing up against a conceptual barrier, in my view. The authors work the details, but there's scant hint they recognize we need something more than more of the same.  What is called for, I think is young people who haven't already been propagandized about the current way of thinking, the current grantsmanship path to careers.

Perhaps more importantly, I think the situation is at present an especially cruel hoax, because there are real health problems, and real, tragic, truly genetic diseases that a major shift in public funding could enable real science to address.
          The (bad) luck of the draw; more evidence   
A while back, Vogelstein and Tomasetti (V-T) published a paper in Science in which it was argued that most cancers cannot be attributed to known environmental factors, but instead were due simply to the errors in DNA replication that occur throughout life when cells divide.  See our earlier 2-part series on this.

Essentially the argument is that knowledge of the approximate number of at-risk cell divisions per unit of age could account for the age-related pattern of increase in cancers of different organs, if one ignored some obviously environmental causes like smoking.  Cigarette smoke is a mutagen and if cancer is a mutagenic disease, as it certainly largely is, then that will account for the dose-related pattern of lung and oral cancers.

This got enraged responses from environmental epidemiologists whose careers are vested in the idea that if people would avoid carcinogens they'd reduce their cancer risk.  Of course, this is partly just the environmental epidemiologists' natural reaction to their ox being gored--threats to their grant largesse and so on.  But it is also true that environmental factors of various kinds, in addition to smoking, have been associated with cancer; some dietary components, viruses, sunlight, even diagnostic x-rays if done early and often enough, and other factors.

Most associated risks from agents like these are small, compared to smoking, but not zero and an at least legitimate objection to V-T's paper might be that the suggestion that environmental pollution, dietary excess, and so on don't matter when it comes to cancer is wrong.  I think V-T are saying no such thing.  Clearly some environmental exposures are mutagens and it would be a really hard-core reactionary to deny that mutations are unrelated to cancer.  Other external or lifestyle agents are mitogens; they stimulate cell division, and it would be silly not to think they could have a role in cancer.  If and when they do, it is not by causing mutations per se.  Instead mitogenic exposures in themselves just stimulate cell division, which is dangerous if the cell is already transformed into a cancer cell.  But it is also a way to increase cancer by just what V-T stress: the natural occurrence of mutations when cells divide.

There are a few who argue that cancer is due to transposable elements moving around and/or inserting into the genome where they can cause cells to misbehave, or other perhaps unknown factors such as of tissue organization, which can lead cells to 'misbehave', rather than mutations.

These alternatives are, currently, a rather minor cause of cancer.  In response to their critics, V-T have just published a new multi-national analysis that they suggest supports their theory.  They attempted to correct for the number of at-risk cells and so on, and found a convincing pattern that supports the intrinsic-mutation viewpoint.  They did this to rebut their critics.

This is at least in part an unnecessary food-fight.  When cells divide, DNA replication errors occur.  This seems well-documented (indeed, Vogelstein did some work years ago that showed evidence for somatic mutation--that is, DNA changes that are not inherited--and genomes of cancer cells compared to normal cells of the same individual.  Indeed, for decades this has been known in various levels of detail.  Of course, showing that this is causal rather than coincidental is a separate problem, because the fact of mutations occurring during cell division doesn't necessarily mean that the mutations are causal. However, for several cancers the repeated involvement of specific genes, and the demonstration of mutations in the same gene or genes in many different individuals, or of the same effect in experimental mice and so on, is persuasive evidence that mutational change is important in cancer.

The specifics of that importance are in a sense somewhat separate from the assertion that environmental epidemiologists are complaining about.  Unfortunately, to a great extent this is a silly debate. In essence, besides professional pride and careerism, the debate should not be about whether mutations are involved in cancer causation but whether specific environmental sources of mutation are identifiable and individually strong enough, as x-rays and tobacco smoke are, to be identified and avoided.  Smoking targets particular cells in the oral cavity and lungs.  But exposures that are more generic, but individually rare or not associated with a specific item like smoking, and can't be avoided, might raise the rate of somatic mutation generally.  Just having a body temperature may be one such factor, for example.

I would say that we are inevitably exposed to chemicals and so on that will potentially damage cells, mutation being one such effect.  V-T are substantially correct, from what the data look like, in saying that (in our words) namable, specific, and avoidable environmental mutations are not the major systematic, organ-targeting cause of cancer.  Vague and/or generic exposure to mutagens will lead to mutations more or less randomly among our cells (maybe, depending on the agent, differently depending on how deep in our bodies the cells are relative to the outside world or other means of exposure).  The more at-risk cells, the longer they're at risk, and so on, the greater the chance that some cell will experience a transforming set of changes.

Most of us probably inherit mutations in some of these genes from conception, and have to await other events to occur (whether these are mutational or of another nature as mentioned above).  The age patterns of cancers seem very convincingly to show that.  The real key factor here is the degree to which specific, identifiable, avoidable mutational agents can be identified.  It seems silly or, perhaps as likely, mere professional jealousy, to resist that idea.

These statements apply even if cancers are not all, or not entirely, due to mutational effects.  And, remember, not all of the mutations required to transform a cell need be of somatic origin.  Since cancer is mostly, and obviously, a multi-factor disease genetically (not a single mutation as a rule), we should not have our hackles raised if we find what seems obvious, that mutations are part of cell division, part of life.

There are curious things about cancer, such as our large body size but delayed onset ages relative to the occurrence of cancer in smaller, and younger animals like mice.  And different animals of different lifespans and body sizes, even different rodents, have different lifetime cancer risks (some may be the result of details of their inbreeding history or of inbreeding itself).  Mouse cancer rates increase with age and hence the number of at-risk cell divisions, but the overall risk at very young ages despite many fewer cell divisions (yet similar genome sizes) shows that even the spontaneous mutation idea of V-T has problems.  After all, elephants are huge and live very long lives; why don't they get cancer much earlier?

Overall, if if correct, V-T's view should not give too much comfort to our 'Precision' genomic medicine sloganeers, another aspect of budget protection, because the bad luck mutations are generally somatic, not germline, and hence not susceptible to Big Data epidemiology, genetic or otherwise, that depends on germ-line variation as the predictor.

Related to this are the numerous reports of changes in life expectancy among various segments of society and how they are changing based on behaviors, most recently, for example, the opiod epidemic among whites in depressed areas of the US.  Such environmental changes are not predictable specifically, not even in principle, and can't be built into genome-based Big Data, or the budget-promoting promises coming out of NIH about such 'precision'.  Even estimated lifetime cancer risks associated with mutations in clear-cut risk-affecting genes like BRCA1 mutations and breast cancer, vary greatly from population to population and study to study.  The V-T debate, and their obviously valid point, regardless of the details, is only part of the lifetime cancer risk story.

ADDENDUM 1
Just after posting this, I learned of a new story on this 'controversy' in The Atlantic.  It is really a silly debate, as noted in my original version.  It tacitly makes many different assumptions about whether this or that tinkering with our lifestyles will add to or reduce the risk of cancer and hence support the anti-V-T lobby.  If we're going to get into the nitty-gritty and typically very minor details about, for example, whether the statistical colon-cancer-protective effect of aspirin shows that V-T were wrong, then this really does smell of academic territory defense.

Why do I say that?  Because if we go down that road, we'll have to say that statins are cancer-causing, and so is exercise, and kidney transplants and who knows what else.  They cause cancer by allowing people to live longer, and accumulate more mutational damage to their cells.  And the supposedly serious opioid epidemic among Trump supporters actually is protective, because those people are dying earlier and not getting cancer!

The main point is that mutations are clearly involved in carcinogenesis, cell division life-history is clearly involved in carcinogenesis, environmental mutagens are clearly involved in carcinogenesis, and inherited mutations are clearly contributory to the additional effects of life-history events.  The silly extremism to which the objectors to V-T would take us would be to say that, obviously, if we avoided any interaction whatsoever with our environment, we'd never get cancer.  Of course, we'd all be so demented and immobilized with diverse organ-system failures that we wouldn't realize our good fortune in not getting cancer.

The story and much of the discussion on all sides is also rather naive even about the nature of cancer (and how many or of which mutations etc it takes to get cancer); but that's for another post sometime.

ADDENDUM 2
I'll add another new bit to my post, that I hadn't thought of when I wrote the original.  We have many ways to estimate mutation rates, in nature and in the laboratory.  They include parent-offspring comparison in genomewide sequencing samples, and there have been sperm-to-sperm comparisons.  I'm sure there are many other sets of data (see Michael Lynch in Trends in Genetics 2010 Aug; 26(8): 345–352.  These give a consistent picture and one can say, if one wants to, that the inherent mutation rate is due to identifiable environmental factors, but given the breadth of the data that's not much different than saying that mutations are 'in the air'.  There are even sex-specific differences.

The numerous mutation detection and repair mechanisms, built into genomes, adds to the idea that mutations are part of life, for example that they are not related to modern human lifestyles.  Of course, evolution depends on mutation, so it cannot and never has been reduced to zero--a species that couldn't change doesn't last.  Mutations occur in plants and animals and prokaryotes, in all environments and I believe, generally at rather similar species-specific rates.

If you want to argue that every mutation has an external (environmental) cause rather than an internal molecular one, that is merely saying there's no randomness in life or imperfection in molecular processes.  That is as much a philosophical as an empirical assertion (as perhaps any quantum physicist can tell you!).  The key, as  asserted in the post here, is that for the environmentalists' claim to make sense, to be a mutational cause in the meaningful sense, the force or factor must be systematic and identifiable and tissue-specific, and it must be shown how it gets to the internal tissue in question and not to other tissues on the way in, etc.

Given how difficult it has been to chase down most environmental carcinogenic factors, to which exposure is more than very rare, and that the search has been going on for a very long time, and only a few have been found that are, in themselves, clearly causal (ultraviolet radiation, Human Papilloma Virus, ionizing radiation, the ones mentioned in the post), whatever is left over must be very weak, non tissue-specific, rare, and the like.  Even radiation-induced lung cancer in uranium minors has been challenging to prove (for example, because miners also largely were smokers).

It is not much of a stretch to simply say that even if, in principle, all mutations in our body's lifetime were due to external exposures, and the relevant mutagens could be identified and shown in some convincing way to be specifically carcinogenic in specific tissues, in practice if not ultra-reality, then the aggregate exposures to such mutations are unavoidable and epistemically random with respect to tissue and gene.  That I would say is the essence of the V-T finding.

Quibbling about that aspect of carcinogenesis is for those who have already determined how many angels dance on the head of a pin.
          Relatedness is relative: How can I be 85% genetically similar to my mom, but only related to her by half?   
First of all, no. I am not the lovechild of star-crossed siblings, or even cousins, or even second cousins. 

This is a gee-whiz kind of post. But the issues are not insignificant.

Hear me out with the background, first, before I get to the part where my eyes bug out of my head and I pull out my kid's Crayola box and start drawing.

If you've learned about sociobiology, or evolutionary psychology, or inclusive fitness, or kin selection, or the evolution of cooperation and even "altruism," or if you've read The Selfish Gene, or if you've been able to follow the debate about levels of selection (which you can peek at here)...

... then you've heard that you're related to your parents by 1/2, to your siblings by 1/2 as well, to your grandparents and grandchildren by 1/4, to your aunts and uncles and nieces and nephews by 1/4 as well, and to your first cousins by 1/8 and so on and so forth.  (Here's some more information.)

So, for example. For evolution (read: adaptationism) to explain how cooperative social behavior could be adaptive in the genetic sense, we use the following logic provided by Bill Hamilton, which became known as "Hamilton's Rule": 

The cost to your cooperation or your prosocial behavior (C) must be less than its benefit to you (B), reproductively speaking, relative to how genetically related (r) you are to the individual with whom you're cooperating. That could have come out smoother. Oh, here you go:

C < rB, or B > C/r

If you're helping out your identical genetic twin (r=1.0), then as long as the benefit to you is greater than the cost, it's adaptive.

C < B, or B > C

If you're helping out your daughter (r = 0.5) then as long as the benefit to you is greater than twice the cost, it's adaptive.

C < (1/2)B, or B > 2C

So already, the adaptive risk to helping out your daughter or your brother is quite higher. And it's even harder to justify the cooperation between individuals and their sibs' kids, and grandkids, especially ESPECIALLY non-kin. But, of course creatures do it! And so do we.

As relatedness gets more distant and distant, we go from 2 times the cost, to 4 times, 8 times, 16, 32, 64 etc... You can see why people like to say "the math falls away" or "drops off" at first or second cousins when they're explaining where the arbitrary line of genetic "kin" is drawn.  If you offer up a curious, "we're all related, we're all kin," someone out of this school of thought that's focused on explaining the evolution of and genes for social behavior may clue you in by circumscribing "kin" as the members of a group that are r = 1/8 or r = 1/16 but usually not less related than that.

This has long bothered me because we're all genetically related and so much cooperation beyond close kin is happening. And it's been hard for me, as someone who sees everything as connected, to read text after text supporting "kin selection" and "kin recognition" (knowing who to be kind to and who to avoid bleeping), to get past the fact that we're arbitrarily deciding what is "kin" and it seems to be for convenience. I'm not doubting that cooperation is important for evolutionary reasons. Quite the contrary! It's just that why is there so much math, based in so many potentially unnecessary assumptions about genes for behavior, gracing so many pages of scientific literature for explaining it or underscoring its importance? 

(It could just be that as an outsider and a non-expert I just don't understand enough of it and if I only did, I wouldn't be gracing this blog with my questions. But let's get back to my reason for posting anyway because it's potentially useful.)

Right. So. Even for folks who aren't part of evolution's academic endeavor, it's obvious to most that we're one half dad and one half mom. The sperm carries one half of a genome, the egg another, and together they make a whole genome which becomes the kid. Voila!

There's even an adorable "Biologist's Mother's Day" song about how we've got half our moms' genome... 


... but there's biology above and beyond the genes we get from mom (and not from dad). And that song is great for teaching us that the rest of the egg and the gestational experience in utero provide so much more to the development of the soon-to-be new human. So "slightly more than half of everything" is thanks to our mothers. Aw!

But, genetically, the mainstream idea is still that we're 50% our mom. 

I teach very basic genetics because I teach evolution and anthropology.And I'm not (usually) a dummy.* I get it. It's a fact! I'm half, genetically, my mom and I'm also half my dad. 

r = 0.5

Okay! But, given these facts about relatedness and how it's imagined in evolutionary biology, facts that I never ever questioned, I hope you can see why this report from 23andMe (personal genomics enterprise) blew my mind:

Percent similarity to Holly Dunsworth over 536070 SNPs (single nucleotide polymorphisms or, effectively/rather, a subset of known variants in the genome; Click on the image to enlarge).
I am 85% like my mom and I am at least 76% like my students and friends who are sharing with me on 23andMe. Names of comparisons have been redacted. As far as I know, this kind of report is no longer offered by 23andMe. I spat back in 2011/12 and the platform has evolved since.

Okay, first of all, it is a huge relief that, of all the people I'm sharing with on 23andMe, the one who squeezed me out of her body is the most genetically similar to me. Science works.

But that number there, with my mother, it is not 50%. It's quite a bit bigger than that. It says I'm over 85% the same as her.

What's more, I am also very similar to every single person I'm sharing with on the site, including example accounts from halfway around the world. Everyone is at least 60-ish% genetically similar to me, according to 23andMe. I know we're all "cousins," but my actual cousins are supposed to be 1/8th according to evolutionary biology. How can my mom be related to me by only one half? How can my actual cousins be only an eighth (which is 12.5%)? 

What is up with evolutionary biology and this whole "r" thing?

Hi. Here is where, if they weren't already, people just got really annoyed with me. Evolutionary biology's "relatedness" or "r" is not the same as genetic similarity like that reported by 23andMe.

Okay!

But why not? 

Let me help unpack the 85% genetic similarity with my mom. Remember, it's not because I'm inbred (which you have to take my word for, but notice that most everyone on there is over 70% genetically similar to me so...).

It's because my mom and dad, just like any two humans, share a lot in common genetically. Some of the alleles that I inherited from my dad are alleles that my mom inherited from her parents. So, not only is everything I got from her (50%) similar to her, but so are many of the parts that I got from my dad. 

Let me get out my kid's arts supplies.

Here is a pretty common view of relatedness, genetically. In our imagination, parents are not related (r = 0) which can lead our imagination to think that their alleles are distinct. Here there are four distinct alleles/variants that could be passed onto offspring, with each offspring only getting one from mom and one from dad. In this case, the sperm carrying the orange variant and the egg with the blue variant made the baby.


1. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
But few genes have four known alleles, at least not four that exist at an appreciable frequency. Some could have three. What does that look like? 

The green allele doesn't exist in the next example. As a result of there being only three variants for this gene or locus, mom and dad must share at least one allele, minimum. That means, they look related and that means that, depending on which egg and sperm make the kid, the kid could be more related to mom than to dad. 


2. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
Now here's where people who know more than I do about these things say that the kid is not more related to mom than dad because she got only one allele from mom and that keeps her at r = 0.5. 

Well, that's just insane. What does it matter whether she got the allele from mom or dad? I thought genes were selfish? (Sorry, for the outburst.)

Again, I realize I'm annoying people and probably much worse--like stomping all over theory and knowledge and science--by mixing up the different concepts of genetic similarity (e.g. 50%) with "r" (e.g. 0.5) and horribly misunderstanding all the nuance (and debate) about "r," but I'm doing it because I'm desperately trying to know why these two related ideas are, in fact, distinct. 

One last pathetic cartoon. 

In this third example, as is common in the genome, there are only two alleles/variants in existence (at an appreciable frequency, so not accounting for constant accumulation of de novo variation). An example of such a gene with only two known alleles is the "earwax gene" ABCC11 (there's a wet/waxy allele and dry/crumbly one). Here, the two alleles are orange and blue. Most humans in the species will have at least one allele in common with their mate for a gene with two alleles, and it's not because most humans are inbred, unless we want to redefine inbreeding to include very distant relatives (aside: which may be how the term is used by experts). 


3. (Please, if you're horrified by the "r" business in these figures, read the post for explanation.)
But as a result of the chance segregation of either the blue or orange allele into each of the gametes, two people with the same genotype can make a kid with the same genotype. 

And of course, making a kid with your same genotype is the only possible outcome if you and your mate are both homozygous (i.e. where both copies are of the same variant so that leaves no chance for variation in offspring unless there is a new mutation). 

So, I wandered a little bit away from my point with these drawings, but I had to because I wanted to get down from where my imagination has me (us?) with "r" versus how things really are with reproduction. We are baby-making with vastly similar genomes to ours, so we are making babies with vastly similar genomes to ours. 

So, I do see why biology says I'm related to my mom by one half. But, on the other hand, what does it matter if I got the thing I have in common with my mom from my mom or whether I got it from my dad? Because I got it. Period. It lives. Period. 

[Inserted graf January 20, '17] Saying it matters where I got the similarity to my mom keeps us at r = 0.5. Saying it matters only that I inherited DNA like hers keeps us always, all of us, at r > 0.5 with our parents and our kids because any two babymakers share much of their genome.

And the fact that this (see 2 and 3) happens so often is why I'm a lot more than 50% genetically like my mom, and the same can be said about my genetic similarity to my dad without him even spitting for 23andMe. 

So, here we are. I don't understand why our relatedness to one another, based on genetic similarity, is not "r."

I hope it's for really beautifully logical reasons and not something political. 

Because...

If "r" was defined by genetic similarity, then would cooperating with my 76% genetically similar students and friends be more adaptive than the credit I currently get from evolutionary biology for cooperating with my own flesh and blood son? 

If "r" was defined by genetic similarity, then could we use the power of math and theoretical biology to encourage broader cooperation among humans beyond their close kin? 

So many questions.

Maybe I should re-learn the math and learn all the other math.

Nah. Not myself. At least, it wouldn't come fast enough for my appetite. Maybe someone who already knows the math could leave a comment and we could go from there... 

And it would be worth it, you know, because despite my relatively weaker math skills, I bet we're more than 50% genetically similar.





*from 23andMe: "You have 321 Neanderthal variants. You have more Neanderthal variants than 96% of 23andMe customers."
          Post-truth science?   
This year was one that shook normal politics to its core.  Our belief in free and fair elections, in the idea that politicians strive to tell the truth and are ashamed to be caught lying, in real news vs fake, in the importance of tradition and precedent, indeed in the importance of science in shaping our world, have all been challenged.  This has served to remind us that we can't take progress, world view, or even truth and the importance of truth themselves for granted.  The world is changing, like it or not.  And, as scientists who assume that truth actually exists and whose lives are devoted to searching for it, the changes are not in familiar directions.  We can disagree with our neighbors about many things, but when we can't even agree on what's true, this is not the 'normal' world we know.

To great fanfare, Oxford Dictionaries chose "post-truth" as its international word of the year.
The use of “post-truth” — defined as “relating to or denoting circumstances in which objective facts are less influential in shaping public opinion than appeals to emotion and personal belief” — increased by 2,000 percent over last year, according to analysis of the Oxford English Corpus, which collects roughly 150 million words of spoken and written English from various sources each month.  New York Times
I introduce this into a science blog because, well, I see some parallels with science.  As most of us know, Thomas Kuhn, in his iconic book, The Structure of Scientific Revolutions, wrote about "normal science", how scientists go about their work on a daily basis, theorizing, experimenting, and synthesizing based on a paradigm, a world view that is agreed upon by the majority of scientists.  (Although not well recognized, Kuhn was preceded in this by Ludwik Fleck, Polish and Israeli physician and biologist who, way back in the 1930s, used the term 'thought collective' for the same basic idea.)

When thoughtful observers recognize that an unwieldy number of facts no longer fit the prevailing paradigm, and develop a new synthesis of current knowledge, a 'scientific revolution' occurs and matures into a new normal science.  In the 5th post in Ken's recent thought-provoking series on genetics as metaphysics, he reminded us of some major 'paradigm shifts' in the history of science -- plate tectonics, relativity and the theory of evolution itself.

We have learned a lot in the last century, but there are 'facts' that don't fit into the prevailing gene-centered, enumerative, reductive approach to understanding prediction and causation, our current paradigm.  If you've read the MT for a while, you know that this is an idea we've often kicked around.  In 2013 Ken made a list of 'strange facts' in a post he called "Are we there yet or do strange things about life require new thinking?" I repost that list below because I think it's worth considering again the kinds of facts that should challenge our current paradigm.

As scientists, our world view is supposed to be based on truth.  We know that climate change is happening, that it's automation not immigration that's threatening jobs in the US, that fossil fuels are in many places now more costly than wind or solar.  But by and large, we know these things not because we personally do research into them all -- we can't -- but because we believe the scientists who do carry out the research and who tell us what they find.  In that sense, our world views are faith-based.  Scientists are human, and have vested interests and personal world views, and seek credit, and so on, but generally they are trustworthy about reporting facts and the nature of actual evidence, even if they advocate their preferred interpretation of the facts, and even if scientists, like anyone else, do their best to support their views and even their biases.

Closer to home, as geneticists, our world view is also faith-based in that we interpret our observations based on a theory or paradigm that we can't possibly test every time we invoke it, but that we simply accept.  The current 'normal' biology is couched in the evolutionary paradigm often based on ideas of strongly specific natural selection, and genetics in the primacy of the gene.

The US Congress just passed a massive bill in support of normal science, the "21st Century Cures Act", with funding for the blatant marketing ploys of the brain connectome project, the push for "Precision Medicine" (first "Personalized Medicine, this endeavor has been, rebranded -- cynically? --yet again to "All of Us") and the new war on cancer.  These projects are nothing if not born of our current paradigm in the life sciences; reductive enumeration of causation and the ability to predict disease.  But the many well-known challenges to this paradigm lead us to predict that, like the Human Genome Project which among other things was supposed to lead to the cure of all disease by 2020, these endeavors can't fulfill their promise.

To a great if not even fundamental extent, this branding is about securing societal resources, for projects too big and costly to kill, in a way similar to any advertising or even to the way churches promise heaven when they pass the plate. But it relies on wide-spread acceptance of contemporary 'normal science', despite the unwieldy number of well-known, misfitting facts.  Even science is now perilously close to 'post-truth' science. This sort of dissembling is deeply built into our culture at present.

We've got brilliant scientists doing excellent work, turning out interesting results every day, and brilliant science journalists who describe and publicize their new findings. But it's almost all done within, and accepting, the working paradigm. Too few scientists, and even fewer writers who communicate their science, are challenging that paradigm and pushing our understanding forward. Scientists, insecure and scrambling not just for insight but for their very jobs, are pressed explicitly or implicitly to toe the current party line. In a very real sense, we're becoming more dedicated to faith-based science than we are to truth.

Neither Ken nor I are certain that a new paradigm is necessary, or that it's right around the corner. How could we know? But, there are enough 'strange facts', that don't fit the current paradigm centered around genes as discrete, independent causal units, that we think it's worth thinking about whether a new synthesis, that can incorporate these facts, might be necessary. It's possible, as we've often said, that we already know everything we need to know: that biology is complex, genetics is interactive not iterative, every genome is unique and interacts with unique individual histories of exposures to environmental risk factors, evolution generates difference rather than replicability, and we will never be able to predict complex disease 'precisely'.

But it's also possible that there are new ways to think about what we know, beyond statistics and population-based observations, to better understand causation.  There are many facts that don't fit the current paradigm, and more smart scientists should be thinking about this as they carry on with their normal science.



---------------------------------
Do strange things about life require new concepts?
1.  The linear view of genetic causation (cis effects of gene function, for the cognoscenti) is clearly inaccurate.  Gene regulation and usage are largely, if not mainly, not just local to a given chromosome region (they are trans);
2.  Chromosomal usage is 4-dimensional within the nucleus, not even 3-dimensional, because arrangements are changing with circumstances, that is, with time;
3.  There is a large amount of inter-genic and inter-chromosomal communication leading to selective expression and non-expression at individual locations and across the genome (e.g., monoallelic expression).  Thousands of local areas of chromosomes wrap and unwrap dynamically depending on species, cell type,  environmental conditions, and the state of other parts of the genome at a given time; 
4.  There is all sorts of post-transcription modification (e.g., RNA editing, chaperoning) that is a further part of 4-D causation;
5.  There is environmental feedback in terms of gene usage, some of which is inherited (epigenetic marking) that can be inherited and borders on being 'lamarckian';
6.  There are dynamic symbioses as a fundamental and pervasive rather than just incidental and occasional part of life (e.g., microbes in humans);
7.  There is no such thing as 'the' human genome from which deviations are measured.  Likewise, there is no evolution of 'the' human and chimpanzee genome from 'the' genome of a common ancestor.  Instead, perhaps conceptually like event cones in physics, where the speed of light constrains what has happened or can happen, there are descent cones of genomic variation descending from individual sequences--time-dependent spreading of variation, with time-dependent limitations.  They intertwine among individuals though each individual's is unique.  There is a past cone leading of ancestry to each current instance of a genome sequence, from an ever-widening set of ancestors (as one goes back in time) and a future cone of descendants and their variation that's affected by mutations.  There are descent cones in the genomes among organisms, and among organisms in a species, and between species. This is of course just a heuristic, not an attempt at a literal simile or to steal ideas from physics! 
Light cone: Wikipedia

8.  Descent cones exist among the cells and tissues within each organism, because of somatic mutation, but the metaphor breaks down because they have strange singular rather than complex ancestry because in individuals the go back to a point, a single fertilized egg, and of individuals to life's Big Bang;
9.  For the previous reasons, all genomes represent 'point' variations (instances) around a non-existent core  that we conceptually refer to as 'species' or 'organs', etc.('the' human genome, 'the' giraffe, etc.);
10.  Enumerating causation by statistical sampling methods is often impossible (literally) because rare variants don't have enough copies to generate 'significance', significance criteria are subjective, and/or because many variants have effects too small to generate significance;
11.  Natural selection, that generates current variation along with chance (drift) is usually so weak that it cannot be demonstrated, often in principle, for similar statistical reasons:  if cause of a trait is too weak to show, cause of fitness is too weak to show; there is not just one way to be 'adapted'.
12.  Alleles and genotypes have effects that are inherently relativistic.  They depend upon context, and each organism's context is different;
13.  Perhaps analogously with the ideal gas law and its like, phenotypes seem to have coherence.  We each have a height or blood pressure, despite all the variation noted above.  In populations of people, or organs, we find ordinary (e.g., 'bell-shaped') distributions, that may be the result of a 'law' of large numbers: just as human genomes are variation around a 'platonic' core, so blood pressure is the net result of individual action of many cells.  And biological traits are typically always changing;
14. 'Environment' (itself a vague catch-all term) has very unclear effects on traits.  Genomic-based risks are retrospectively assessed but future environments cannot, in principle, be known, so that genomic-based prediction is an illusion of unclear precision; 
15.  The typical picture is of many-to-many genomic (and other) causation for which many causes can lead to the same result (polygenic equivalence), and many results can be due to the same cause (pleiotropy);
16. Our reductionist models, even those that deal with networks, badly under-include interactions and complementarity.  We are prisoners of single-cause thinking, which is only reinforced by strongly adaptationist Darwinism that, to this day, makes us think deterministically and in terms of competition, even though life is manifestly a phenomenon of molecular cooperation (interaction).  We have no theory for the form of these interactions (simple multiplicative? geometric?).
17.  In a sense all molecular reactions are about entropy, energy, and interaction among different molecules or whatever.  But while ordinary nonliving molecular reactions converge on some result, life is generally about increasing difference, because life is an evolutionary phenomenon.
18. DNA is itself a quasi-random, inert sequence. Its properties come entirely from spatial, temporal, combinatorial ('Boolean'-like) relationships. This context works only because of what else is in (and on the immediate outside) of the cell at the given time, a regress back to the origin of life.

          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Dna: 1 persona sana su 5 ha mutazioni   
Il corpo umano è una macchina perfetta, ma forse il Dna potrebbe non esserlo al 100% Secondo quanto evidenziato da due ricerche destinate a riaccendere il dibattito sui test genetici e presentate dalla rivista Science sul suo sito, in un individuo sano su cinque sono presenti mutazioni genetiche legate a malattie rare o associate a tumori La prima ricerca, pubblicata sulla rivista The Annals of Internal Medicine, è stata condotta su 50 individui dal gruppo di Jason Vassy, del Veteran Affairs Boston Healthcare System. Dei 50, 11 avevano alterazioni associate a malattie rare ma solo due di essi mostravano i sintomi. La seconda ricerca è anticipata sul sito bioRxiv, che pubblica ricerche che non hanno ancora superato la fase della revisione da parte della comunità scientifica. Condotta da Michael Snyder, nel Centro di Genomica e Medicina personalizzata dell’università di Stanford, indica
          Auburn University scientists make breakthrough discovery on the evolution of the innate immune system   

The laboratory of Kenneth Halanych, the Schneller Endowed Chair in the Department of Biological Sciences at Auburn University, has made a discovery that could have widespread implications for how scientists study the function of the human immune system. Led by doctoral student Michael Tassia, the team’s research revealed that humans and their closest invertebrate relatives share core components of their innate immune systems, components that date back more than 500 million years.

“Humans belong to a group called ‘Deuterostomes’ that include vertebrate animals as well as invertebrate animals like sea stars, sea urchins, sea squirts and acorn worms,” said Tassia.

“All of these groups had gill slits, much like fish, early in their history,” added Halanych.

Tassia and the team in the Halanych lab studied genetic datasets of more than 40 different deuterostome species including human and invertebrate. The research showed evidence that humans and other deuterostomes share a common evolutionary history of their innate immune systems.

“Humans and other vertebrates possess two types of immune systems–innate and adaptive,” said Tassia. “The adaptive immune system is the one we are more familiar with. It contains components such as antibodies that allow for ‘immunological memory,’ which is why immunizations are an effective tool against diseases and pathogens. Whereas the adaptive immune system must ‘learn’ to recognize a pathogen, the innate immune system is prepared from the get-go. The innate immune system relies on a suite of molecules called ‘pattern-recognition receptors’ which, over long periods of evolution, have adapted to recognize common molecular patterns associated with bacteria, fungi and viruses. So, if bacteria like E. coli get into somewhere they shouldn’t, such as a really nasty paper cut, cells in your body sporting these pattern-recognition receptors are ready to mount a rapid immune response, causing inflammation, recruiting more immune cells and destroying those bacteria.”

Tassia explained that the adaptive immune system is exclusive to vertebrates. Components of the innate immune system, on the other hand, predate vertebrates and are present in groups as old as jellies, whose last common ancestor with vertebrates existed more than 500 million years ago. As a result, he began his work by comparing the most well-known pattern-recognition receptors, “Toll-like receptors,” or TLRs, from more than 40 different invertebrate and vertebrate species.

“In our research, we looked at the much bigger system, starting with the diversity of TLRs in each of our species and continuing further by examining whether or not all the other important components required for the system to work are present across deuterostomes,” said Tassia. “Our findings indicate that nearly all the components are present across all the major deuterostome groups, suggesting their innate immune system was present in the last common ancestor more than 500 million years ago and was expanded upon in vertebrates and other groups. Our study also used phylogenetic methods to evaluate the similarity of TLRs between major animal lineages. Interestingly, we were able to identify a group of TLRs very closely related to a mammalian TLR that is critical for recognizing viruses, suggesting this particular method for antiviral defense may be more evolutionarily ancient than previously expected and could predate the origin of vertebrates.”

The realization that the innate immune system of vertebrates and their close invertebrate relatives is similar opens the door to developing more controllable laboratory experiments to understand immune system evolution.

“Often the generation time and ability to keep invertebrates in the laboratory can make them logistically favorable for studying vertebrate systems,” said Halanych.

The research findings are the result of years of study, beginning with Halanych’s dissertation and long-standing interest in the evolution of hemichordates and echinoderms–marine invertebrates–and continuing with the work of doctoral students in the Halanych lab, as well as publically available information from the National Institutes of Health. Tassia gathered several terabytes of genetic data from the previous research efforts and spent approximately two years developing a bioinformatic, computational framework that allowed him to confidently identify and perform analysis on specific genes.

“This work is a great example of how bioinformatics tools can help answer important questions of organismal biology,” said Halanych. “The Tassia et al. paper has helped push the laboratory, and Auburn University, further into the forefront of marine invertebrate genomics.”

The research results were published in the prestigious scientific journal, Proceedings of the National Academy of Sciences, or PNAS, in a paper titled, “Toll-like receptor pathway evolution in deuterostomes”.

PNAS is one of the top scientific journals and is run by the National Academy of Sciences, an association of the world’s top scientists across many disciplines. Intellectual and scientific standards for the journal are very high, signifying that work published in PNAS is likely to have a significant impact on the field of study.


          Ryan Waples Final Exam   
Ryan will be presenting his MS thesis entitled: Population genomics of Salish Sea chum salmon: The legacy of the salmonid whole genome duplication WHEN: Monday, December 14th at 10:00 AM WHERE: FSH 203 FACULTY ADVISER(S): Lisa and Jim Seeb All are welcome to attend. Continue reading
          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Wellcome Trust Sanger Institute: Postdoctoral Fellow - Experimental Malaria    
GBP31115 - GBP39004 per annum + excellent benefits: Wellcome Trust Sanger Institute: The Sanger Institute Malaria Programme integrates genomic and experimental genetic approaches to tackle fundamental questions in malaria biology, and to identify new targets for drug and vaccine development. Cambridgeshire, England
          Maximizing the Clinical Benefit of Anthracyclines in Addition to Taxanes in the Adjuvant Treatment of Early Breast Cancer.   

Maximizing the Clinical Benefit of Anthracyclines in Addition to Taxanes in the Adjuvant Treatment of Early Breast Cancer.

J Clin Oncol. 2017 Jun 29;:JCO2017725960

Authors: Curigliano G, Criscitiello C

Abstract
The Oncology Grand Rounds series is designed to place original reports published in the Journal into clinical context. A case presentation is followed by a description of diagnostic and management challenges, a review of the relevant literature, and a summary of the authors' suggested management approaches. The goal of this series is to help readers better understand how to apply the results of key studies, including those published in Journal of Clinical Oncology, to patients seen in their own clinical practice. A healthy 56-year-old postmenopausal woman discovered a palpable mass at the one o'clock position of the left breast. After an initial biopsy confirmed breast cancer, she underwent mastectomy and axillary node dissection for a left-sided breast cancer that measured 3.5 cm. There was extensive lymphovascular invasion. Pathology review indicated a poorly differentiated, grade 3 invasive ductal carcinoma and ductal carcinoma in situ (largest focus, 3.5 cm). The margins were negative. Two of the 11 axillary lymph nodes contained metastatic carcinoma. Immunohistochemical studies previously obtained on the core biopsy indicated that the tumor was positive for estrogen receptor expression (50%), negative for progesterone receptor expression, and had a Ki-67 score of 60%. There was no amplification of the human epidermal growth factor receptor 2/ neu gene. Staging scans were negative for metastatic disease. Our multidisciplinary tumor board recommended adjuvant chemotherapy, postmastectomy radiation therapy, and endocrine therapy. A 52-year-old postmenopausal woman presented with a palpable mass of the right breast. An initial core biopsy confirmed carcinoma in the breast. She underwent quadrantectomy and axillary node dissection. The final pathology report disclosed a moderately differentiated invasive ductal carcinoma (diameter, 2.5 cm). The margins were negative. None of the three sentinel lymph nodes contained metastatic carcinoma. Immunohistochemical studies showed that the tumor was positive for estrogen receptor expression (90%) and for progesterone receptor expression (40%) and had a Ki-67 score of 20%. There was no amplification of the human epidermal growth factor receptor 2/ neu gene. Staging scans were negative for metastatic disease. A genomic assay was obtained and suggested an intermediate to high risk of recurrence. Her past medical history was notable for hypertension and moderately overweight status (body mass index, 39 kg/m(2)). Our multidisciplinary tumor board recommended adjuvant chemotherapy, postsurgical radiation therapy, and endocrine therapy.

PMID: 28661760 [PubMed - as supplied by publisher]


          Annotation of the Domestic Pig Genome by Quantitative Proteogenomics   

TOC Graphic

Journal of Proteome Research
DOI: 10.1021/acs.jproteome.7b00184

          Hadoop e Cloudera aiutano a indagare fra i segreti del Dna   
Il centro di ricerca genomica dell'Inova Translational Medicine Institute ha adottato Cloudera Enterprise in sostituzione del precedente sistema di data warehouse. Ha così migliorato le proprie capacità di raccolta e analisi dei dati, finalizzate alla medicina di precisione.
          Director - Clinical Genomic Core   
Organizational ProfileSidra Medical and Research Center is a state of the art academic medical center that will function to the level of the highest international standards Its clinical focus is on the specialty care of women and childrenSidra&rsquos Vision is &ldquoSidra Medical and Research Center will be a beacon of learning
          2016 Brings Big News for NaviNet   

On the very first business day of 2016, NaviNet was aquired by NantHealth, a transformative provider of genomic and clinical information technology.  NaviNet’s huge network is an asset shared and used heavily by health plans, health systems, small practices, ancillaries and many other participants  --  many of whom have been asking how and where NaviNet fits in NantHealth’s plans for the future.


          บรรพบุรุษสัตว์มีรกอาจมีหน้าตาคล้ายหนูผี และไม่เคยอยู่ร่วมกับไดโนเสาร์   

บรรพบุรุษสัตว์มีรกอาจมีหน้าตาคล้ายหนูผี และไม่เคยอยู่ร่วมกับไดโนเสาร์


เป็นเวลานานกว่าสองทศวรรษที่นักชีววิทยาหาทางลงไม่ได้ว่าบรรพบุรุษของสัตว์เลี้ยงลูกด้วยนมกลุ่ม Placentalia (สัตว์เลี้ยงลูกด้วยนมที่เลี้ยงตัวอ่อนในครรภ์ด้วยรกที่สมบูรณ์ สัตว์เลี้ยงลูกด้วยนมปัจจุบันเกือบทุกชนิดรวมทั้งมนุษย์จัดอยู่ในกลุ่มนี้) เริ่มต้นสายวิวัฒนาการขึ้นมาเมื่อไรกันแน่ เพราะหลักฐานทางชีวโมเลกุลที่เรียกว่า molecular clock ระบุว่า Placentalia เริ่มโผล่ขึ้นมาบนโลกเมื่อประมาณ 100 ล้านปีที่แล้ว นั่นแปลว่าบรรพบุรุษ Placentalia จะต้องเคยมีชีวิตช่วงหนึ่งกับไดโนเสาร์ที่สูญพันธุ์ไปในรอยต่อยุค Cretaceous-Paleogene (K-Pg boundary) เมื่อประมาณ 65 ล้านปีที่แล้ว แต่นักวิทยาศาสตร์กลับไม่เคยเจอหลักฐานฟอสซิลของ Placentalia ที่มีอายุเกิน K-Pg boundary เลย อีกทั้งนักชีววิทยาหลายคนก็ยังเชื่อว่าสัตว์เลี้ยงลูกด้วยนมตัวเล็กๆ ไม่น่าจะแก่งแย่งแข่งขันกับไดโนเสาร์เจ้าโลกในขณะนั้นได้ การแตกกระจายของสายวิวัฒนาการ (radiation) ของสัตว์เลี้ยงลูกด้วยนมจึงควรเกิดหลังจากที่ไดโนเสาร์สูญพันธุ์ไปแล้วจนหมดสิ้น

หลักฐาน molecular clock นั้นมาจากการประมาณหาอายุของบรรพบุรุษร่วม (common ancestor) ของยีนหนึ่งๆ โดยมีสมมติฐานว่าอัตราการกลายพันธุ์คงที่สม่ำเสมอ นักวิทยาศาสตร์จะดูว่ายีนตัวเดียวกันในสิ่งมีชีวิตสองชนิด (หรือมากกว่า) แตกต่างกันขนาดไหน และคำนวณกลับว่าต้องใช้เวลานานเท่าไรจึงจะเกิดความแตกต่างเท่านั้นได้จากการกลายพันธุ์ จุดอ่อนของ molecular clock คือ ยีนหนึ่งๆ ไม่จำเป็นต้องมีการกลายพันธุ์คงที่สม่ำเสมอตลอดเวลา และ ยีนแตกต่างกันก็มีอัตราการกลายพันธุ์ต่างกันด้วย นักชีววิทยาที่เชื่อว่าวิวัฒนาการสัตว์เลี้ยงลูกด้วยนมเพิ่งจะแตกกระจายหลังการสูญพันธุ์ของไดโนเสาร์ก็เอาจุดอ่อนข้อนี้ขึ้นมาเถียง ส่วนนักชีววิทยาที่ฝักใฝ่หลักฐานชีวโมเลกุลก็โต้กลับว่าการที่พวกชอบขุดยังไม่เจอฟอสซิลก็ไม่ได้แปลว่าไม่มีฟอสซิลอยู่จริงๆ

ทีมวิจัยของนักวิทยาศาสตร์ 23 คนที่นำโดย Maureen O'Leary แห่ง Stony Brook University เห็นว่าไหนๆ ทั้งสองทางก็มีจุดอ่อนของตัวมันเองทั้งคู่ ทำไมไม่ลองเอาสองทางมาผสมผสานรวมกันหละ พวกเขาเริ่มต้นด้วยการเอาข้อมูลทางสัณฐานวิทยาและพันธุกรรมของสัตว์เลี้ยงลูกด้วยนมที่ยังมีชีวิตอยู่ในปัจจุบัน 46 สปีชีส์ ครอบคลุมทั้งกลุ่ม Monotremata (สัตว์เลี้ยงลูกด้วยนมที่ออกลูกเป็นไข่ เช่น ตุ่นปากเป็ด ตัวกินมดหนาม เป็นต้น), กลุ่ม Marsupial (พวกที่เลี้ยงดูตัวอ่อนด้วยรกเป็นระยะสั้นๆ แล้วก็คลอดมาเลี้ยงต่อในกระเป๋าหน้าท้อง เช่น จิงโจ้ เป็นต้น), และกลุ่ม Placentalia รายการข้อมูลทางสัณฐานวิทยาที่ใช้ในงานวิจัยนี้ยาวเหยียดถึง 4,541 รายการ มากกว่างานวิจัยก่อนๆ หน้าเกือบสิบเท่า แค่ระบุรายการที่ต้องใช้ก็กินเวลาปาเข้าไป 2 ปีแล้ว (เพราะนักวิทยาศาสตร์ที่ศึกษาสัตว์แต่ละกลุ่มใช้คำศัพท์แตกต่างกนออกไป ตามประเพณีที่สืบๆ กันมา) ส่วนข้อมูลทางพันธุกรรมนั้นเปรียบเทียบความแตกต่างของยีนจำนวน 27 ยีน

ขั้นต่อไป นักวิจัยก็นำข้อมูลทางสัณฐานวิทยาที่พบในฟอสซิลของสัตว์เลี้ยงลูกด้วยนมที่สูญพันธุ์ไปแล้วอีก 40 สปีชีส์เข้ามารวม ขั้นตอนการรวบรวมข้อมูลทั้งหมดกินเวลา 3 ปี จากนั้นก็นำข้อมูลเปรียบเทียบทั้งหมดขึ้นไปอยู่บนซอฟท์แวร์ฐานข้อมูลกลุ่มเมฆที่ชื่อว่า"Morphobank" http://mammaltree.informatics.sunysb.edu/ สัตว์เลี้ยงลูกด้วยนมแต่ละตัวจะถูกจัดตำแหน่งลงบนกิ่งก้านของวิวัฒนาการตามลักษณะของสัณฐานวิทยาประกอบกับข้อมูลทางพันธุกรรม และจากลำดับของสายกิ่งก้านเหล่านั้น นักวิจัยก็สามารถที่จะประเมินระยะห่างทางวิวัฒนาการของสัตว์เลี้ยงลูกด้วยนมแต่ละสาย ซึ่งเอามาคำนวณย้อนหาตำแหน่งจุดเวลาที่บรรพบุรุษของสัตว์เลี้ยงลูกด้วยนมกลุ่ม Placentalia กำเนิดขึ้นมาได้ นักวิจัยเรียกวิธีการนี้ว่า "Phylophenomics" เพื่อให้สอดคล้องกับศาสตร์ "Phylogenomics" ที่ใช้ข้อมูลทางพันธุกรรมในการลำดับสายวิวัฒนาการสิ่งมีชีวิต

ผลได้ออกมาว่า บรรพบุรุษของ Placentalia เกิดขึ้นประมาณ 200,000 - 400,000 ปีหลังจาก K-Pg boundary และภายในเวลาเพียงสองแสนปี สาย Placentalia ก็แยกออกเป็น 10 สายหลักแพร่เผ่าพันธุ์มาถึงยุคปัจจุบัน ดังนั้นจึงสนับสนุนทฤษฎีที่ว่าวิวัฒนาการของสัตว์เลี้ยงลูกด้วยนมแตกกระจายสายหลังจากการสูญพันธุ์ของไดโนเสาร์

ภาพจาก PhysOrg; Credit: Stony Brook University/ Luci Betti Nash

ในเมื่อการวิเคราะห์ครั้งนี้ใช้ข้อมูลทางสัณฐานวิทยาเป็นหลัก นักวิจัยจึงสามารถที่จะสร้างภาพจำลองของบรรพบุรุษต้นตระกูล Placentalia ขึ้นมาได้ด้วยการอนุมานจากลักษณะทางสัณฐานวิทยาที่มีอยู่ บรรพบุรุษในจินตนาการนี้มีหน้าตาคล้ายสัตว์ฟันแทะพวกหนูผี จมูกยื่นนาว หางยาวเป็นพวง ปีนต้นไม้เก่ง กินแมลงเป็นอาหาร หนักประมาณ 6-245 กรัม ตัวใหญ่ประมาณหนูหรือลูกแมวตัวเขื่องๆ สมองส่วนรับสัมผัสกลิ่นและ corpus callosum (มัดเส้นประสาทที่เชื่อมสมองซีกซ้ายและขวา) เจริญดี

ภาพจาก PhysOrg; Credit: Carl Buell

นอกจากนี้นักวิจัยยังพบเรื่องน่าประหลาดใจที่ขัดกับความเชื่อเดิมๆ อีกหลายอย่าง เช่น ค้นพบว่าสัตว์เลี้ยงลูกด้วยนมกลุ่ม Afrotherian (ได้แก่ ตัว aardvark, ช้าง, หมูน้ำ เป็นต้น) ไม่ได้ถือกำเนิดขึ้นในดินแดนแอฟริกาอย่างที่เคยเชื่อกัน มันเริ่มวิวัฒนาการในดินแดนทวีปอเมริกาใต้ ซึ่งตอนนั้นทั้งสองทวีปแยกห่างกันเป็นพันๆ กิโลเมตร ต้นตระกูลของ Afrotheria ส่วนหนึ่งน่าจะพลัดหลงมาไม่ทางใดก็ทางหนึ่ง แล้วมาแพร่พันธุ์ในแอฟริกา ขณะที่เพื่อนร่วมรุ่นของมันในอเมริกาใต้สูญพันธุ์ไปจนหมด

โครงการวิจัยนี้เป็นส่วนหนึ่งของโครงการ Assembling the Tree of Life (ATOL) ซึ่งได้รับเงินทุนสนับสนุนจาก National Science Foundation

อย่างไรก็ตาม นักวิทยาศาสตร์ที่ยังไม่อยากรีบฟันธงสรุปอะไร เช่น Mark Springer แห่ง University of California, Riverside ก็ติงว่างานวิจัยนี้ไม่ได้คำนึงถึงปรากฏการณ์ที่สัตว์ต่างกลุ่มจะเกิดวิวัฒนาการแบบ Convergent evolution (หมายถึงสิ่งมีชีวิตที่อยู่คนละสายมีวิวัฒนาการสร้างลักษณะที่คล้ายๆ กันขึ้นมาเพราะมีวิถีชีวิตคล้ายกัน) ข้อสรุปและผลที่ได้จึงอาจจะคลาดเคลื่อนผิดไปจากความเป็นจริง นอกจากนี้นักวิทยาศาสตร์บางคน เช่น Olaf Bininda-Emonds แห่ง Oldenburg University ก็ไม่เห็นว่า Phylophenomics จะมาช่วยหาทางลงอะไรได้ให้กับข้อถกเถียงเกี่ยวกับจุดกำเนิดของ Placentalia

งานวิจัยตีพิมพ์ใน Science DOI: 10.1126/science.1229237


          We Can Now Build Biomolecules From Computer Code — No Humans Necessary - Futurism   

Futurism

We Can Now Build Biomolecules From Computer Code — No Humans Necessary
Futurism
Synthetic Genomics has created a digital-to-biological converter that uses digital code to create biologics like DNA, RNA, proteins, and viral particles. This may have major implications for space colonization, fighting disease outbreaks, and ...


          Genetic and epigenetic inactivation of SESTRIN1 controls mTORC1 and response to EZH2 inhibition in follicular lymphoma.   
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Genetic and epigenetic inactivation of SESTRIN1 controls mTORC1 and response to EZH2 inhibition in follicular lymphoma.

Sci Transl Med. 2017 Jun 28;9(396):

Authors: Oricchio E, Katanayeva N, Donaldson MC, Sungalee S, Joyce PP, Béguelin W, Battistello E, Sanghvi VR, Jiang M, Jiang Y, Teater M, Parmigiani A, Budanov AV, Chan FC, Shah SP, Kridel R, Melnick AM, Ciriello G, Wendel HG

Abstract
Follicular lymphoma (FL) is an incurable form of B cell lymphoma. Genomic studies have cataloged common genetic lesions in FL such as translocation t(14;18), frequent losses of chromosome 6q, and mutations in epigenetic regulators such as EZH2 Using a focused genetic screen, we identified SESTRIN1 as a relevant target of the 6q deletion and demonstrate tumor suppression by SESTRIN1 in vivo. Moreover, SESTRIN1 is a direct target of the lymphoma-specific EZH2 gain-of-function mutation (EZH2(Y641X) ). SESTRIN1 inactivation disrupts p53-mediated control of mammalian target of rapamycin complex 1 (mTORC1) and enables mRNA translation under genotoxic stress. SESTRIN1 loss represents an alternative to RRAGC mutations that maintain mTORC1 activity under nutrient starvation. The antitumor efficacy of pharmacological EZH2 inhibition depends on SESTRIN1, indicating that mTORC1 control is a critical function of EZH2 in lymphoma. Conversely, EZH2(Y641X) mutant lymphomas show increased sensitivity to RapaLink-1, a bifunctional mTOR inhibitor. Hence, SESTRIN1 contributes to the genetic and epigenetic control of mTORC1 in lymphoma and influences responses to targeted therapies.

PMID: 28659443 [PubMed - in process]


          Genomic Analyses of Dominant US Clonal Lineages of Phytophthora infestans Reveals a Shared Common Ancestry for Clonal Lineages US11 and US18 and a Lack of Recently Shared Ancestry Among All Other US Lineages   
none
          Population Genomics of Fungal and Oomycete Pathogens   
none
          Human Cytosolic Sulfotransferase SULT1C3: Genomic Analysis and Functional Characterization of Splice Variant SULT1C3a and SULT1C3d   
Abstract
Summary: The cytosolic sulfotransferase SULT1C3 remained the most poorly understood human SULT. The SULT1C3 gene has been shown to contain alternative exons 7 and 8, raising the question concerning their evolutionary origin and implying the generation of multiple SULT1C3 variants. Two SULT1C3 splice variants, SULT1C3a and SULT1C3d, were investigated to verify the impact of alternative C-terminal sequences on their sulfating activity. Sequence homology and gene location analyses were performed to verify the orthology of the SULT1C3 gene. The SULT1C3 gene appears to be present only in humans and other primates, but alternative exons 7b and 8b share high degrees of homology with corresponding regions of rodent SULT1C1 genes, implying their evolutionary origin being from a defunct human SULT1C1 gene. Purified recombinant SULT1C3a and SULT1C3d were analyzed for sulfating activities toward a variety of endogenous and xenobiotic compounds. While SULT1C3a displayed weaker activities and strict substrate specificity toward hydroxyl chlorinated biphenyls, SULT1C3d exhibited broader substrate specificity toward bile acids and thyroid hormones as well as hydroxyl chlorinated biphenyls. Molecular docking simulation suggested that Tyr249 and Met257 may play an important role in substrate recognition by SULT1C3d. Alternative splicing of exons 7 and 8 sequences resulted in differential catalytic properties of SULT1C3 variants.

          Systematic discovery of novel eukaryotic transcriptional regulators using sequence homology independent prediction.   
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Systematic discovery of novel eukaryotic transcriptional regulators using sequence homology independent prediction.

BMC Genomics. 2017 Jun 26;18(1):480

Authors: Bossi F, Fan J, Xiao J, Chandra L, Shen M, Dorone Y, Wagner D, Rhee SY

Abstract
BACKGROUND: The molecular function of a gene is most commonly inferred by sequence similarity. Therefore, genes that lack sufficient sequence similarity to characterized genes (such as certain classes of transcriptional regulators) are difficult to classify using most function prediction algorithms and have remained uncharacterized.
RESULTS: To identify novel transcriptional regulators systematically, we used a feature-based pipeline to screen protein families of unknown function. This method predicted 43 transcriptional regulator families in Arabidopsis thaliana, 7 families in Drosophila melanogaster, and 9 families in Homo sapiens. Literature curation validated 12 of the predicted families to be involved in transcriptional regulation. We tested 33 out of the 195 Arabidopsis putative transcriptional regulators for their ability to activate transcription of a reporter gene in planta and found twelve coactivators, five of which had no prior literature support. To investigate mechanisms of action in which the predicted regulators might work, we looked for interactors of an Arabidopsis candidate that did not show transactivation activity in planta and found that it might work with other members of its own family and a subunit of the Polycomb Repressive Complex 2 to regulate transcription.
CONCLUSIONS: Our results demonstrate the feasibility of assigning molecular function to proteins of unknown function without depending on sequence similarity. In particular, we identified novel transcriptional regulators using biological features enriched in transcription factors. The predictions reported here should accelerate the characterization of novel regulators.

PMID: 28651538 [PubMed - in process]


          Routine DNA Sequencing May Be Helpful And Not As Scary As Feared   
Advances in technology have made it much easier, faster and less expensive to do whole genome sequencing — to spell out all three billion letters in a person's genetic code. Falling costs have given rise to speculation that it could soon become a routine part of medical care, perhaps as routine as checking your blood pressure. But will such tests, which can be done for as little as $1,000, prove useful, or needlessly scary? The first closely-controlled study aimed at answering that question suggests that doctors and their patients can handle the flood of information the tests would produce. The study was published Monday in Annals of Internal Medicine. "We can actually do genome sequencing in normal, healthy individuals without adverse consequences — and actually with identification of some important findings," says Teri Manolio , director of the division of genomic medicine at the National Human Genome Institute, which funded the study. Manolio wrote an editorial accompanying the
          Sep 20, 2017: PPPMB Seminar - Jim Bradeen at Plant Science Building   

Jim Bradeen
University of Minnesota

Areas of Interest

Genomics of Disease Resistance in Plants

Our research focuses on the genetics and genomics of plant resistance to major pathogens. We conduct research in the Solanaceae (potato, tomato, tobacco) and Rosaceae (apple, peach, strawberry, rose) families. Our aim is sustainable and durable genetic solutions to important crop diseases, resulting in reduced grower and environmental costs associated with frequent pesticide applications. Using molecular and applied research techniques, we are identifying, characterizing, isolating, and deploying previously unknown or under-utilized sources of natural genetic resistance. Current research includes structural genomics (genome mapping, whole genome sequencing) of wild relatives of potato, comparative genomics of disease resistance genes across Solanaceous and Rosaceous species, and functional regulation of potato disease resistance genes throughout plant developmental stages and in different plant organs.

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          Sep 27, 2017: PPPMB Seminar - Kathryn Bushley at Plant Science Building   

Kathryn Bushley
University of Minnesota

Expertise:

Fungal metabolism

Research Interests:

Fungi are one of the most biochemically diverse kingdoms of life, producing a diverse array of bioactive natural products, many of which have medicinal properties or function in maintaining pathogenesis or symbiosis. Research in my lab focuses on how fungal metabolism shapes the interaction of fungi with plants and other organisms. Using a combination of next generation sequencing technologies, natural products chemistry, molecular genetics, and metabolomics, we examine the evolution, diversity, and functions of fungal secondary metabolites, particularly nonribosomal peptide synthetases (NRPSs) and polyketide synthetases (PKSs). Current research in the lab is focused on fungi that parasitize insects and includes several projects: 1) a population genomic study of fine-scale evolution of secondary metabolites among isolates of the beetle pathogen Tolypocladium inflatum, 2) a comparative genomic and transcriptomic approach to identify genes and regulatory networks that allow fungi in the genera Fusarium and Beauveria to interact with distinct hosts (insects, plants, and other fungi), and 3) the impact of mating biology on the population genetic structure of insect pathogenic fungi.

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          Oct 4, 2017: “Cross-Kingdom RNAi and RNA trafficking in plant pathogen interactions“ - Hailing Jin at Plant Science Building   

Hailing Jin

Professor, & Cy Mouradick Endowed Chair
Director of Genetics,Genomics and Bioinformatics Graduate Program
Department of Plant Pathology and Microbiology
Center for Plant Cell Biology
Institute for Integrative Genome Biology, University of California, Riverside

Biography & Research Interests

My lab studies the molecular mechanisms of plant immunity and pathogen virulence, with an overall goal to develop effective and environmentally friendly strategies to control plant diseases and to ensure sufficient food production.

Our research projects include:

Small RNAs and Cross-Kingdom RNAi in Plant - Pathogen InteractionsSmall RNAs, including microRNAs (miRNAs) and small interfering RNAs (siRNAs), are important regulators of eukaryotic gene expression by guiding mRNA cleavage, translational inhibition or chromatin modification. We utilize genomics, genetics, molecular and biochemical approaches to identify and functionally characterize infection-regulated small RNAs, including those from plant hosts and from eukaryotic pathogens. My lab provided the first example of a plant endogenous siRNA that regulates plant immune responses. We further discovered that some small RNAs from aggressive fungal pathogens are delivered into host cells to hijack host RNAi machinery to suppress host immunity genes. These studies have added small RNAs to the list of pathogen effectors, which unveiled a novel virulence mechanism in aggressive eukaryotic pathogens. The transport of small RNAs from fungal pathogens to plant hosts also represents a naturally occurring cross-kingdom RNAi event. We recently show that such cross-kingdom RNAi is bi-directional, plants are also capable of delivery small RNAs into fungal pathogens to attenuate their virulence.

Regulatory mechanisms of RNAi machinery in plant - pathogen interactionsMy lab also studies the function and regulation of RNAi pathway components, mostly Argonaute (AGO) proteins in plant immunity. AGO proteins are the core components of RNAi complexes, which selectively bind with small RNAs and silence target genes with complementary sequences. We discovered that Arabidopsis AGO2 positively regulates antibacterial immunity by associating with miR393*, which targets a Golgi-localized SNARE gene MEMB12 and leads to increased secretion of antimicrobial peptide and confers resistance. Since miR393 also contributes to antibacterial immunity by suppressing auxin receptors, miR393*/miR393 represent a novel example of a miRNA*/miRNA pair that functions in the same cellular pathway (host immunity) through two distinct AGOs. We further demonstrated that small RNA duplex structures and AGO PIWI domain contribute to the selective loading of small RNAs in different AGO proteins, AGO1 and AGO2. We currently focus on the regulation and modification of AGO proteins in responses to pathogen attacks.

Epigenetic regulation of plant immune responses Surveillance of pathogen infection is mediated by intracellular NOD-like nucleotide-binding/leucine-rich-repeat receptors (NLRs) in both plants and animals. We recently discovered that some NBS-LRR genes, are under the control of specific plant chromatin remodeling proteins, as well as RNA-directed DNA methylation (RdDM) pathway. Such epigenetic regulation ensures precise expression of these resistance genes to avoid autoimmune responses or disease.

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          Oct 18, 2017: PPPMB Seminar - Harrison at Plant Science Building   

Maria Harrison
Adjunct Professor, Section of Plant Pathology & Plant-Microbe Biology
School of Integrative Plant Science, Cornell University

Research Overview

Most vascular flowering plants are able to form symbiotic associations with arbuscular mycorrhizal (AM) fungi. These associations, named ‘arbuscular mycorrhizas’, develop in the roots, where the fungus colonizes the cortex to access carbon supplied by the plant. The fungal contribution to the symbiosis includes the transfer of mineral nutrients, particularly phosphorus, from the soil to the plant. In many soils, phosphate exists at levels that are limiting for plant growth. Consequently, additional phosphate supplied via AM fungi can have a significant impact on plant development, and this symbiosis influences the structure of plant communities in ecosystems worldwide.

The long-term goals of our research are to understand the mechanisms underlying development of the AM symbiosis and phosphate transfer between the symbionts. A model legume, Medicago truncatula, and arbuscular mycorrhizal fungi, Glomus versiforme, Glomus intraradices and Gigaspora gigantea are used for these analyses. Currently, a combination of molecular, cell biology, genetic and genomics approaches are being used to obtain insights into development of the symbiosis, communication between the plant and fungal symbionts, and symbiotic phosphate transport.

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          Oct 25, 2017: "Trichoderma, the phytobiome and the challenge of translating science to the field" - Molly Cadle-Davidson at Plant Science Building   

Molly Cadle-Davidson, Ph.D.
Chief Science Officer, Advanced Biological Marketing

Dr. Cadle-Davidson started with ABM as a consultant in 2013 and became the assistant chief scientific officer in January 2014. Her role is to work to enhance existing ABM genomics strategies and to foster next-generation product development for ABM.

Cadle-Davidson is an expert in the field of genetics and is well versed in the application of genomics and nextgeneration sequencing techniques for trait-based research and development. She has done extensive work with both plant and human-based genomic research and has collaborated with individuals from institutions throughout the world, including Cornell University, Imperial College and the United States Department of Agriculture Agricultural Research Service.

Prior to joining ABM, Cadle-Davidson was highly involved in government work with SRC, Inc. and aided other government-funded programs with the Departments of Homeland Security, State, Defense and Justice. While at SRC, Inc. her work resulted in one Trade Secret, two patents pending and one patent application currently being prepared for the company.

Dr. Cadle-Davidson holds a Bachelor of Science in Genetics from the University of California, as well as a Master of Science in Plant Pathology from Washington State University and a Ph.D. in Plant Breeding and Genetics from Cornell University. She has also contributed to 13 published journal articles in many highly regarded scientific journals.

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          Dec 5, 2017: PPPMB Seminar - Jason Stajich at Plant Science Building   

Jason Stajich
Professor, Department of Plant Pathology and Microbiology and Institute for Integrative Genome Biology, UC Riverside

I am interested in the process and mechanisms of evolution. I study this primarily in fungi using comparative, computational, and experimental tools. We utilize genome and RNA sequencing, sequence analysis, molecular evolution, and phylogenetics, and molecular biology tools to explore the functions of genes or genomic regions identified by analyses to be involved in processes we study.

Most of our work is focused in the zygomycete and zoosporic chytrid fungi (fungi that move!). We also have collaborative projects and interests in Aspergillus, Fusarium, Coccidioides, and Clavispora lusitaniae. The lab is increasingly moving towards questions that relate to symbioses with new projects on fungal-bacteria antagonism and on the biological symbioses that occur among fungi, algae, bacteria in desert Biological crusts. I also have a new interest in extremophile fungi and working on projects to understand the halophilic Hortaea werneckii and endolithic Antarctic fungi through genome sequencing and laboratory experiments.

I am involved in many fungal genome projects including co-leading the 1000 fungal genomes project with the JGI and the zygolife project.

In the broader scope I am interested in the evolution of multicellular forms and regulation of development in fungi. I think understanding how differential gene regulation is established can help learn more about the mechanisms of cell type differentiation. We are also studying the cell wall to understand how innovations in the cell wall and dimorphism impact interactions between pathogenic fungi and hosts they infect. These different projects seek to provide new insight into the big picture of how the complexity of life evolved and how host and pathogen interactions co-evolved.

To address this work we also need tools to sift and mine the gigantic datasets that genomics can produce. I have focused on building tools for comparative and computational analyses of genomes including work on the BioPerl and Gbrowse projects and the development of open source software for bioinformatics and life sciences research through the Open Bioinformatics Foundation.

The lab is also focused on the development of databases for fungal genome data to make the genome and functional information more available. I also blog about interesting findings in fungal, microbial, and genome research and share protocols and coordinate projects through a wiki site.

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          AACR Publishes First Set of Screening Recommendations Emerging from Childhood Cancer Predisposition Workshop   

​PHILADELPHIA — The American Association for Cancer Research (AACR) has published its first set of consensus screening recommendations for children with common cancer predisposition syndromes in Clinical Cancer Research, a journal of the AACR. These recommendations emerged from the Childhood Cancer Predisposition Workshop held by the AACR Pediatric Cancer Working Group in October 2016.

These recommendations serve to highlight the genetic nuances associated with childhood cancer predisposition syndromes as well as provide primary and specialty pediatric clinicians with standardized approaches to facilitate appropriate surveillance of children affected by such syndromes.

“We are at an evolving time, and in the current era with widespread use of genomic sequencing, several studies indicate that at least 10 percent of childhood cancers arise as a result of genetic predisposition,” said chairperson of the Childhood Cancer Predisposition Workshop, Garrett M. Brodeur, MD. Garrett M. Brodeur, MD

Brodeur, a professor of pediatrics; Audrey E. Evans Chair in Molecular Oncology; associate director of Abramson Cancer Center; and director of the Cancer Predisposition Program at the Children’s Hospital of Philadelphia, added, “Given that in children, the overall risk for developing cancer is low, surveillance in the general population is probably not feasible or economically warranted. However, surveillance seems a sound strategy if target populations with an increased risk for developing cancer can be identified.”

The Pediatric Cancer Working Group of the AACR convened a workshop that included 65 professionals from 11 countries, including 51 physician directors or co-directors of cancer predisposition programs (pediatric oncologists or medical geneticists), seven genetic counselors, three radiologists, three directors of adult cancer predisposition programs, and a pediatric endocrinologist.

The panel reviewed existing data and practices, and established international consensus recommendations for cancer surveillance for the 50 most common syndromes that predispose children to the development of cancer. These syndromes were then clustered into nine major groups based on the major cancer types with which they are associated: Li-Fraumeni syndrome, neurofibromatoses, overgrowth syndromes and Wilms tumor, neural tumors, GI cancer predisposition, neuroendocrine syndromes, leukemia predisposition, DNA instability syndromes, and miscellaneous syndromes.

“The consensus was that a less than 1 percent prevalence of a particular type of cancer in those 20 years of age or younger is too low and, therefore, not worthy of surveillance, and that if the prevalence is 5 percent or more, then we really should screen,” Brodeur noted. “Surveillance for cancers with prevalence between 1 and 5 percent would depend on specific factors and be considered on an individual basis.”

A major outcome of this workshop is the development of 18 position papers that provide recommendations for surveillance, focusing on when to initiate and/or discontinue specific screening measures, which modalities to use, and how frequent to screen patients.

“We needed to start somewhere for a number of these diseases for which there were no existing protocols. We now have the recommendations for the 50 most common syndromes that predispose children to the development of cancer in their first 20 years of life. The publications will be made freely available online so that anyone in the world—patients, doctors, anybody interested—will be able to read and download them,” Brodeur said. “After we gather some experience in following these surveillance protocols, we hope to meet again and combine our experiences to see how they are working and if they should be modified,” he added.

An overview of the initiative and the first five position papers, published on June 1, 2017, are freely available to readers online:

For details regarding the institutions with established centers dedicated to determining and managing hereditary cancer risk that were represented at the AACR Childhood Cancer Predisposition Workshop, click here.

Press Release Published Date: 6/1/2017 8:00 AM
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          First Analysis of AACR Project GENIE Data Published   

​PHILADELPHIA — The first analysis of nearly 19,000 de-identified genomic records from the American Association for Cancer Research (AACR) international data-sharing initiative known as AACR Project Genomics Evidence Neoplasia Information Exchange (GENIE) was published today in Cancer Discovery, a journal of the AACR.

In addition to the genomic analysis, the report includes examples of how the AACR Project GENIE genomic data can be used to facilitate clinical research, including:

  • Analysis showing that more than 30 percent of the samples had mutations that are clinically actionable, meaning that they are suggestive of a specific treatment that is either already approved by the U.S. Food and Drug Administration or is being tested in clinical trials.
  • Analysis showing that the rate at which patients with samples in the AACR Project GENIE registry would match with arms of the NCI-MATCH trial reflected the actual accrual rates for the trial.
  • Details of two additional studies underway that are linking certain genetic characteristics of metastatic breast cancer with clinical and pathological features of the tumors, as well as with patient outcomes.

“There has been a lot of discussion about the potential of data-sharing initiatives to accelerate the pace of progress against cancer,” said Charles L. Sawyers, MD, FAACR, who is the AACR Project GENIE Steering Committee chairperson and an author on the paper. “This paper shows that AACR Project GENIE has made the first steps to delivering on this promise.

“We are particularly excited by the clinical actionability analysis,” continued Sawyers, who is also chairperson of the Human Oncology and Pathogenesis Program at Memorial Sloan Kettering Cancer Center in New York, and a Howard Hughes Medical Institute investigator. “Prior studies looking at how often tumor genome sequencing identifies a clinically actionable mutation have yielded variable results, leading some to question its clinical utility. The huge number of samples in our study and the high rate of clinical actionability give us confidence that tumor genome sequencing can have an important role in clinical care.”

AACR Project GENIE is a multi-phase, multi-year, international data-sharing project that was launched by the AACR in partnership with eight global academic leaders in clinical cancer genomics in November 2015. Just over a year later, in January 2017, the AACR Project GENIE consortium made public nearly 19,000 de-identified genomic records collected from patients who were treated at the eight international institutions participating in the first phase of the project.

“This paper describes the AACR Project GENIE consortium and provides a landscape overview of the first public GENIE data release,” said Ethan Cerami, PhD, director of the Knowledge Systems Group and lead scientist in the Department of Biostatistics and Computational Biology at the Dana-Farber Cancer Institute in Boston, and an author on the paper. “By showing that we can share data across multiple institutions in the United States, Canada, and Europe to obtain results none of the institutions could have obtained alone, we have put AACR Project GENIE at the forefront of data-sharing efforts to accelerate scientific discovery and ultimately improve patient care.”

The paper provides detailed information about the data collected at the different institutions, highlighting that even though the types of sequencing and size of the gene panels used at the individual institutions differ and are evolving over time, the data can be compared across institutions. The high-level analysis of the nearly 19,000 de-identified genomic records made public by the consortium also shows many similarities with the data in The Cancer Genome Atlas (TCGA). The paper also highlights several differences with TCGA data, which the authors speculate are a result of a greater proportion of the AACR Project GENIE records coming from patients with recurrent or relapsing disease.

The eight institutions who participated in AACR Project GENIE phase 1 are: Dana-Farber Cancer Institute, Boston; Gustave Roussy Cancer Campus, Paris-Villejuif, France; The Netherlands Cancer Institute, Amsterdam, on behalf of the Center for Personalized Cancer Treatment, Utrecht, The Netherlands; Sidney Kimmel Comprehensive Cancer Center at Johns Hopkins, Baltimore; Memorial Sloan Kettering Cancer Center, New York; Princess Margaret Cancer Centre, Toronto; University of Texas MD Anderson Cancer Center, Houston; and Vanderbilt-Ingram Cancer Center, Nashville, Tennessee.

This study was supported by funds from the AACR, Genentech, Boehringer Ingelheim, Pfizer, Eli Lilly, the Howard Hughes Medical Institute, the National Institutes of Health, the National Cancer Institute, the Princess Margaret Cancer Foundation, the Ontario Ministry of Health, Susan G. Komen, the Dr. Miriam and Sheldon G. Adelson Medical Research Foundation, the T.J. Martell Foundation, the Commonwealth Foundation, the Cancer Prevention and Research Institute of Texas, the Dutch Ministry of Health, and the Dutch Cancer Society. Sawyers serves on the board of directors of Novartis. Cerami declares no conflicts of interest.


Press Release Published Date: 6/1/2017 4:30 AM
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          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Genetics roadmap to develop more resilient farmed fish   
In Scotland, researchers at WorldFish will embark on new research to create more resilient fish with characteristics such as disease resistance and more effective feed utilization, using advanced techniques such as genomic selection to introduce these characteristics into its improved … Continue reading
          The software also provides gender information (Electronic Supplem   
The software also provides gender information (Electronic Supplementary Material Fig. 3). The sensitivity and precision of the DNA Detection and Gender Identification functions were assessed by analysing five purified extracted genomic DNA samples over a range of DNA input amounts … Continue reading
          Science Signaling Podcast, 20 May 2014   
Renate Pilz discusses an alternative form of the thyroid hormone receptor that mediates nongenomic signaling at the plasma membrane.
          Bioinformatics Specialist-Metagenomics/Proteomics - Signature Science, LLC - Austin, TX   
The Bioinformatics Specialist will work within a team of molecular biologists, forensic scientists, biochemists, bioinformaticians, database managers,... $90,000 a year
From Signature Science, LLC - Tue, 06 Jun 2017 09:05:50 GMT - View all Austin, TX jobs
          Sr. / Research Technician / Research Assistant - Oklahoma Medical Research Foundation - Oklahoma City, OK   
We utilize both animal and cellular models, and cutting edge technologies in functional genomics, bioinformatics, genetics, molecular and cell biology, and...
From Indeed - Fri, 26 May 2017 13:59:53 GMT - View all Oklahoma City, OK jobs
          We Can Now Build Biomolecules From Computer Code — No Humans Necessary - Futurism   

Futurism

We Can Now Build Biomolecules From Computer Code — No Humans Necessary
Futurism
Synthetic Genomics has created a digital-to-biological converter that uses digital code to create biologics like DNA, RNA, proteins, and viral particles. This may have major implications for space colonization, fighting disease outbreaks, and ...


          Unchained Labs Gets $13M, Buys Trinean   
Pleasanton-based Unchained Labs, a developer of tools used in the life sciences industry, said today that it has acquired Trinean, a developer of systems that measure protein, DNA and RNA concentration in biologics and genomics samples. Financial terms of the buy were not disclosed.... (more)
          Paramount Recruitment: Bioinformatics Consultant - London   
Negotiable: Paramount Recruitment: Bioinformatics Engagement Specialist/ Consultant London The post holder is responsible for supporting Genomics England's external partners with their genomics projects working with the data and insight that we provide to them through their world leading London, England
          Genomic fossils reveal adaptation of non-autonomous pararetroviruses driven by concerted evolution of noncoding regulatory sequences   
- Source: journals.plos.org
          Osr1 functions downstream of Hedgehog pathway to regulate foregut development   
Publication date: Available online 10 May 2017
Source:Developmental Biology

Author(s): Lu Han, Jingyue Xu, Emily Grigg, Megan Slack, Praneet Chaturvedi, Rulang Jiang, Aaron M. Zorn

During early fetal development, paracrine Hedgehog (HH) ligands secreted from the foregut epithelium activate Gli transcription factors in the surrounding mesenchyme to coordinate formation of the respiratory system, digestive track and the cardiovascular network. Although disruptions to this process can lead to devastating congenital defects, the underlying mechanisms and downstream targets, are poorly understood. We show that the zinc finger transcription factor Osr1 is a novel HH target as Osr1 expression in the foregut mesenchyme depends on HH signaling and the effector of HH pathway Gli3 binds to a conserved genomic loci near Osr1 promoter region. Molecular analysis of mouse germline Osr1 mutants reveals multiple functions of Osr1 during foregut development. Osr1 mutants exhibit fewer lung progenitors in the ventral foregut. Osr is then required for the proper branching of the primary lung buds, with mutants exhibiting miss-located lung lobes. Finally, Osr1 is essential for proper mesenchymal differentiation including pulmonary arteries, esophageal and tracheal smooth muscle as well as tracheal cartilage rings. Tissue specific conditional knockouts in combination with lineage tracing indicate that Osr1 is required cell autonomously in the foregut mesenchyme. We conclude that Osr1 is a novel downstream target of HH pathway, required for lung specification, branching morphogenesis and foregut mesenchymal differentiation.






          Woolly Mammoth Resurrection Project: Paypal Founder Peter Thiel Funds Effort To Bring Back Extinct Ice Age Animal   
Paypal founder Peter Thiel gave a fund of $100,000 to a Harvard genomic professor who is working to resurrect the extinct woolly mammoth. Why do some scientists want to bring back the Ice Age animal?
          Genome Wide Analysis of Drug-Induced Torsades de Pointes: Lack of Common Variants with Large Effect Sizes   
Marked prolongation of the QT interval on the electrocardiogram associated with the polymorphic ventricular tachycardia Torsades de Pointes is a serious adverse event during treatment with antiarrhythmic drugs and other culprit medications, and is a common cause for drug relabeling and withdrawal. Although clinical risk factors have been identified, the syndrome remains unpredictable in an individual patient. Here we used genome-wide association analysis to search for common predisposing genetic variants. Cases of drug-induced Torsades de Pointes (diTdP), treatment tolerant controls, and general population controls were ascertained across multiple sites using common definitions, and genotyped on the Illumina 610k or 1M-Duo BeadChips. Principal Components Analysis was used to select 216 Northwestern European diTdP cases and 771 ancestry-matched controls, including treatment-tolerant and general population subjects. With these sample sizes, there is 80% power to detect a variant at genome-wide significance with minor allele frequency of 10% and conferring an odds ratio of ≥2.7. Tests of association were carried out for each single nucleotide polymorphism (SNP) by logistic regression adjusting for gender and population structure. No SNP reached genome wide-significance; the variant with the lowest P value was rs2276314, a non-synonymous coding variant in C18orf21 (p  =  3×10−7, odds ratio = 2, 95% confidence intervals: 1.5–2.6). The haplotype formed by rs2276314 and a second SNP, rs767531, was significantly more frequent in controls than cases (p  =  3×10−9). Expanding the number of controls and a gene-based analysis did not yield significant associations. This study argues that common genomic variants do not contribute importantly to risk for drug-induced Torsades de Pointes across multiple drugs.
          An Integrated Model of Multiple-Condition ChIP-Seq Data Reveals Predeterminants of Cdx2 Binding   
Regulatory proteins can bind to different sets of genomic targets in various cell types or conditions. To reliably characterize such condition-specific regulatory binding we introduce MultiGPS, an integrated machine learning approach for the analysis of multiple related ChIP-seq experiments. MultiGPS is based on a generalized Expectation Maximization framework that shares information across multiple experiments for binding event discovery. We demonstrate that our framework enables the simultaneous modeling of sparse condition-specific binding changes, sequence dependence, and replicate-specific noise sources. MultiGPS encourages consistency in reported binding event locations across multiple-condition ChIP-seq datasets and provides accurate estimation of ChIP enrichment levels at each event. MultiGPS's multi-experiment modeling approach thus provides a reliable platform for detecting differential binding enrichment across experimental conditions. We demonstrate the advantages of MultiGPS with an analysis of Cdx2 binding in three distinct developmental contexts. By accurately characterizing condition-specific Cdx2 binding, MultiGPS enables novel insight into the mechanistic basis of Cdx2 site selectivity. Specifically, the condition-specific Cdx2 sites characterized by MultiGPS are highly associated with pre-existing genomic context, suggesting that such sites are pre-determined by cell-specific regulatory architecture. However, MultiGPS-defined condition-independent sites are not predicted by pre-existing regulatory signals, suggesting that Cdx2 can bind to a subset of locations regardless of genomic environment. A summary of this paper appears in the proceedings of the RECOMB 2014 conference, April 2–5.
          Genome-Wide and Differential Proteomic Analysis of Hepatitis B Virus and Aflatoxin B1 Related Hepatocellular Carcinoma in Guangxi, China   
Both hepatitis B virus (HBV) and aflatoxin B1 (AFB1) exposure can cause liver damage as well as increase the probability of hepatocellular carcinoma (HCC). To investigate the underlying genetic changes that may influence development of HCC associated with HBV infection and AFB1 exposure, HCC patients were subdivided into 4 groups depending upon HBV and AFB1 exposure status: (HBV(+)/AFB1(+), HBV(+)/AFB1(-), HBV(-)/AFB1(+), HBV(-)/AFB1(-)). Genetic abnormalities and protein expression profiles were analyzed by array-based comparative genomic hybridization and isobaric tagging for quantitation. A total of 573 chromosomal aberrations (CNAs) including 184 increased and 389 decreased were detected in our study population. Twenty-five recurrently altered regions (RARs; chromosomal alterations observed in ≥10 patients) in chromosomes were identified. Loss of 4q13.3-q35.2, 13q12.1-q21.2 and gain of 7q11.2-q35 were observed with a higher frequency in the HBV(+)/AFB1(+), HBV(+)/AFB1(-) and HBV(-)/AFB1(+) groups compared to the HBV(-)/AFB(-) group. Loss of 8p12-p23.2 was associated with high TNM stage tumors (P = 0.038) and was an unfavorable prognostic factor for tumor-free survival (P =0.045). A total of 133 differentially expressed proteins were identified in iTRAQ proteomics analysis, 69 (51.8%) of which mapped within identified RARs. The most common biological processes affected by HBV and AFB1 status in HCC tumorigenesis were detoxification and drug metabolism pathways, antigen processing and anti-apoptosis pathways. Expression of AKR1B10 was increased significantly in the HBV(+)/AFB1(+) and HBV(-)/AFB1(+) groups. A significant correlation between the expression of AKR1B10 mRNA and protein levels as well as AKR1B10 copy number was observered, which suggest that AKR1B10 may play a role in AFB1-related hepatocarcinogenesis. In summary, a number of genetic and gene expression alterations were found to be associated with HBV and AFB1- related HCC. The possible synergistic effects of HBV and AFB1 in hepatocarcinogenesis warrant further investigations.
          Co-regulated Transcripts Associated to Cooperating eSNPs Define Bi-fan Motifs in Human Gene Networks   
Associations between the level of single transcripts and single corresponding genetic variants, expression single nucleotide polymorphisms (eSNPs), have been extensively studied and reported. However, most expression traits are complex, involving the cooperative action of multiple SNPs at different loci affecting multiple genes. Finding these cooperating eSNPs by exhaustive search has proven to be statistically challenging. In this paper we utilized availability of sequencing data with transcriptional profiles in the same cohorts to identify two kinds of usual suspects: eSNPs that alter coding sequences or eSNPs within the span of transcription factors (TFs). We utilize a computational framework for considering triplets, each comprised of a SNP and two associated genes. We examine pairs of triplets with such cooperating source eSNPs that are both associated with the same pair of target genes. We characterize such quartets through their genomic, topological and functional properties. We establish that this regulatory structure of cooperating quartets is frequent in real data, but is rarely observed in permutations. eSNP sources are mostly located on different chromosomes and away from their targets. In the majority of quartets, SNPs affect the expression of the two gene targets independently of one another, suggesting a mutually independent rather than a directionally dependent effect. Furthermore, the directions in which the minor allele count of the SNP affects gene expression within quartets are consistent, so that the two source eSNPs either both have the same effect on the target genes or both affect one gene in the opposite direction to the other. Same-effect eSNPs are observed more often than expected by chance. Cooperating quartets reported here in a human system might correspond to bi-fans, a known network motif of four nodes previously described in model organisms. Overall, our analysis offers insights regarding the fine motif structure of human regulatory networks.
          STORMSeq: An Open-Source, User-Friendly Pipeline for Processing Personal Genomics Data in the Cloud   
The increasing public availability of personal complete genome sequencing data has ushered in an era of democratized genomics. However, read mapping and variant calling software is constantly improving and individuals with personal genomic data may prefer to customize and update their variant calls. Here, we describe STORMSeq (Scalable Tools for Open-Source Read Mapping), a graphical interface cloud computing solution that does not require a parallel computing environment or extensive technical experience. This customizable and modular system performs read mapping, read cleaning, and variant calling and annotation. At present, STORMSeq costs approximately $2 and 5–10 hours to process a full exome sequence and $30 and 3–8 days to process a whole genome sequence. We provide this open-access and open-source resource as a user-friendly interface in Amazon EC2.
          The Marine Microbial Eukaryote Transcriptome Sequencing Project (MMETSP): Illuminating the Functional Diversity of Eukaryotic Life in the Oceans through Transcriptome Sequencing   
Microbial ecology is plagued by problems of an abstract nature. Cell sizes are so small and population sizes so large that both are virtually incomprehensible. Niches are so far from our everyday experience as to make their very definition elusive. Organisms that may be abundant and critical to our survival are little understood, seldom described and/or cultured, and sometimes yet to be even seen. One way to confront these problems is to use data of an even more abstract nature: molecular sequence data. Massive environmental nucleic acid sequencing, such as metagenomics or metatranscriptomics, promises functional analysis of microbial communities as a whole, without prior knowledge of which organisms are in the environment or exactly how they are interacting. But sequence-based ecological studies nearly always use a comparative approach, and that requires relevant reference sequences, which are an extremely limited resource when it comes to microbial eukaryotes [1]. In practice, this means sequence databases need to be populated with enormous quantities of data for which we have some certainties about the source. Most important is the taxonomic identity of the organism from which a sequence is derived and as much functional identification of the encoded proteins as possible. In an ideal world, such information would be available as a large set of complete, well-curated, and annotated genomes for all the major organisms from the environment in question. Reality substantially diverges from this ideal, but at least for bacterial molecular ecology, there is a database consisting of thousands of complete genomes from a wide range of taxa, supplemented by a phylogeny-driven approach to diversifying genomics [2]. For eukaryotes, the number of available genomes is far, far fewer, and we have relied much more heavily on random growth of sequence databases [3],[4], raising the question as to whether this is fit for purpose.
          ATM Regulates Insulin-Like Growth Factor 1-Secretory Clusterin (IGF-1-sCLU) Expression that Protects Cells against Senescence   
Downstream factors that regulate the decision between senescence and cell death have not been elucidated. Cells undergo senescence through three pathways, replicative senescence (RS), stress-induced premature senescence (SIPS) and oncogene-induced senescence. Recent studies suggest that the ataxia telangiectasia mutant (ATM) kinase is not only a key protein mediating cellular responses to DNA damage, but also regulates cellular senescence induced by telomere end exposure (in RS) or persistent DNA damage (in SIPS). Here, we show that expression of secretory clusterin (sCLU), a known pro-survival extracellular chaperone, is transcriptionally up-regulated during both RS and SIPS, but not in oncogene-induced senescence, consistent with a DNA damage-inducible mechanism. We demonstrate that ATM plays an important role in insulin-like growth factor 1 (IGF-1) expression, that in turn, regulates downstream sCLU induction during senescence. Loss of ATM activity, either by genomic mutation (ATM-deficient fibroblasts from an ataxia telangiectasia patient) or by administration of a chemical inhibitor (AAI, an inhibitor of ATM and ATR), blocks IGF-1-sCLU expression in senescent cells. Downstream, sCLU induction during senescence is mediated by IGF-1R/MAPK/Egr-1 signaling, identical to its induction after DNA damage. In contrast, administration of an IGF-1 inhibitor caused apoptosis of senescent cells. Thus, IGF-1 signaling is required for survival, whereas sCLU appears to protect cells from premature senescence, as IMR-90 cells with sCLU knockdown undergo senescence faster than control cells. Thus, the ATM-IGF-1-sCLU pathway protects cells from lethality and suspends senescence.
          Israeli Acute Paralysis Virus: Epidemiology, Pathogenesis and Implications for Honey Bee Health   
Israeli acute paralysis virus (IAPV) is a widespread RNA virus of honey bees that has been linked with colony losses. Here we describe the transmission, prevalence, and genetic traits of this virus, along with host transcriptional responses to infections. Further, we present RNAi-based strategies for limiting an important mechanism used by IAPV to subvert host defenses. Our study shows that IAPV is established as a persistent infection in honey bee populations, likely enabled by both horizontal and vertical transmission pathways. The phenotypic differences in pathology among different strains of IAPV found globally may be due to high levels of standing genetic variation. Microarray profiles of host responses to IAPV infection revealed that mitochondrial function is the most significantly affected biological process, suggesting that viral infection causes significant disturbance in energy-related host processes. The expression of genes involved in immune pathways in adult bees indicates that IAPV infection triggers active immune responses. The evidence that silencing an IAPV-encoded putative suppressor of RNAi reduces IAPV replication suggests a functional assignment for a particular genomic region of IAPV and closely related viruses from the Family Dicistroviridae, and indicates a novel therapeutic strategy for limiting multiple honey bee viruses simultaneously and reducing colony losses due to viral diseases. We believe that the knowledge and insights gained from this study will provide a new platform for continuing studies of the IAPV–host interactions and have positive implications for disease management that will lead to mitigation of escalating honey bee colony losses worldwide.
          Gene-Wide Analysis Detects Two New Susceptibility Genes for Alzheimer's Disease   
Background: Alzheimer's disease is a common debilitating dementia with known heritability, for which 20 late onset susceptibility loci have been identified, but more remain to be discovered. This study sought to identify new susceptibility genes, using an alternative gene-wide analytical approach which tests for patterns of association within genes, in the powerful genome-wide association dataset of the International Genomics of Alzheimer's Project Consortium, comprising over 7 m genotypes from 25,580 Alzheimer's cases and 48,466 controls. Principal Findings: In addition to earlier reported genes, we detected genome-wide significant loci on chromosomes 8 (TP53INP1, p = 1.4×10−6) and 14 (IGHV1-67 p = 7.9×10−8) which indexed novel susceptibility loci. Significance: The additional genes identified in this study, have an array of functions previously implicated in Alzheimer's disease, including aspects of energy metabolism, protein degradation and the immune system and add further weight to these pathways as potential therapeutic targets in Alzheimer's disease.
          Inference of Ancestral Recombination Graphs through Topological Data Analysis   
The recent explosion of genomic data has underscored the need for interpretable and comprehensive analyses that can capture complex phylogenetic relationships within and across species. Recombination, reassortment and horizontal gene transfer constitute examples of pervasive biological phenomena that cannot be captured by tree-like representations. Starting from hundreds of genomes, we are interested in the reconstruction of potential evolutionary histories leading to the observed data. Ancestral recombination graphs represent potential histories that explicitly accommodate recombination and mutation events across orthologous genomes. However, they are computationally costly to reconstruct, usually being infeasible for more than few tens of genomes. Recently, Topological Data Analysis (TDA) methods have been proposed as robust and scalable methods that can capture the genetic scale and frequency of recombination. We build upon previous TDA developments for detecting and quantifying recombination, and present a novel framework that can be applied to hundreds of genomes and can be interpreted in terms of minimal histories of mutation and recombination events, quantifying the scales and identifying the genomic locations of recombinations. We implement this framework in a software package, called TARGet, and apply it to several examples, including small migration between different populations, human recombination, and horizontal evolution in finches inhabiting the Galápagos Islands.
          Vectors as Epidemiological Sentinels: Patterns of Within-Tick Borrelia burgdorferi Diversity   
Hosts including humans, other vertebrates, and arthropods, are frequently infected with heterogeneous populations of pathogens. Within-host pathogen diversity has major implications for human health, epidemiology, and pathogen evolution. However, pathogen diversity within-hosts is difficult to characterize and little is known about the levels and sources of within-host diversity maintained in natural populations of disease vectors. Here, we examine genomic variation of the Lyme disease bacteria, Borrelia burgdorferi (Bb), in 98 individual field-collected tick vectors as a model for study of within-host processes. Deep population sequencing reveals extensive and previously undocumented levels of Bb variation: the majority (~70%) of ticks harbor mixed strain infections, which we define as levels Bb diversity pre-existing in a diverse inoculum. Within-tick diversity is thus a sample of the variation present within vertebrate hosts. Within individual ticks, we detect signatures of positive selection. Genes most commonly under positive selection across ticks include those involved in dissemination in vertebrate hosts and evasion of the vertebrate immune complement. By focusing on tick-borne Bb, we show that vectors can serve as epidemiological and evolutionary sentinels: within-vector pathogen diversity can be a useful and unbiased way to survey circulating pathogen diversity and identify evolutionary processes occurring in natural transmission cycles.
          Developmental Pathway of the MPER-Directed HIV-1-Neutralizing Antibody 10E8   
Antibody 10E8 targets the membrane-proximal external region (MPER) of HIV-1 gp41, neutralizes >97% of HIV-1 isolates, and lacks the auto-reactivity often associated with MPER-directed antibodies. The developmental pathway of 10E8 might therefore serve as a promising template for vaccine design, but samples from time-of-infection—often used to infer the B cell record—are unavailable. In this study, we used crystallography, next-generation sequencing (NGS), and functional assessments to infer the 10E8 developmental pathway from a single time point. Mutational analysis indicated somatic hypermutation of the 2nd-heavy chain-complementarity determining region (CDR H2) to be critical for neutralization, and structures of 10E8 variants with V-gene regions reverted to genomic origin for heavy-and-light chains or heavy chain-only showed structural differences >2 Å relative to mature 10E8 in the CDR H2 and H3. To understand these developmental changes, we used bioinformatic sieving, maximum likelihood, and parsimony analyses of immunoglobulin transcripts to identify 10E8-lineage members, to infer the 10E8-unmutated common ancestor (UCA), and to calculate 10E8-developmental intermediates. We were assisted in this analysis by the preservation of a critical D-gene segment, which was unmutated in most 10E8-lineage sequences. UCA and early intermediates weakly bound a 26-residue-MPER peptide, whereas HIV-1 neutralization and epitope recognition in liposomes were only observed with late intermediates. Antibody 10E8 thus develops from a UCA with weak MPER affinity and substantial differences in CDR H2 and H3 from the mature 10E8; only after extensive somatic hypermutation do 10E8-lineage members gain recognition in the context of membrane and HIV-1 neutralization.
          A Genomic Map of the Effects of Linked Selection in Drosophila   
Natural selection at one site shapes patterns of genetic variation at linked sites. Quantifying the effects of “linked selection” on levels of genetic diversity is key to making reliable inference about demography, building a null model in scans for targets of adaptation, and learning about the dynamics of natural selection. Here, we introduce the first method that jointly infers parameters of distinct modes of linked selection, notably background selection and selective sweeps, from genome-wide diversity data, functional annotations and genetic maps. The central idea is to calculate the probability that a neutral site is polymorphic given local annotations, substitution patterns, and recombination rates. Information is then combined across sites and samples using composite likelihood in order to estimate genome-wide parameters of distinct modes of selection. In addition to parameter estimation, this approach yields a map of the expected neutral diversity levels along the genome. To illustrate the utility of our approach, we apply it to genome-wide resequencing data from 125 lines in Drosophila melanogaster and reliably predict diversity levels at the 1Mb scale. Our results corroborate estimates of a high fraction of beneficial substitutions in proteins and untranslated regions (UTR). They allow us to distinguish between the contribution of sweeps and other modes of selection around amino acid substitutions and to uncover evidence for pervasive sweeps in untranslated regions (UTRs). Our inference further suggests a substantial effect of other modes of linked selection and of adaptation in particular. More generally, we demonstrate that linked selection has had a larger effect in reducing diversity levels and increasing their variance in D. melanogaster than previously appreciated.
          What Is a Genome?   
The genome is often described as the information repository of an organism. Whether millions or billions of letters of DNA, its transmission across generations confers the principal medium for inheritance of organismal traits. Several emerging areas of research demonstrate that this definition is an oversimplification. Here, we explore ways in which a deeper understanding of genomic diversity and cell physiology is challenging the concepts of physical permanence attached to the genome as well as its role as the sole information source for an organism.
          XRN2 Links Transcription Termination to DNA Damage and Replication Stress   
XRN2 is a 5’-3’ exoribonuclease implicated in transcription termination. Here we demonstrate an unexpected role for XRN2 in the DNA damage response involving resolution of R-loop structures and prevention of DNA double-strand breaks (DSBs). We show that XRN2 undergoes DNA damage-inducible nuclear re-localization, co-localizing with 53BP1 and R loops, in a transcription and R-loop-dependent process. XRN2 loss leads to increased R loops, genomic instability, replication stress, DSBs and hypersensitivity of cells to various DNA damaging agents. We demonstrate that the DSBs that arise with XRN2 loss occur at transcriptional pause sites. XRN2-deficient cells also exhibited an R-loop- and transcription-dependent delay in DSB repair after ionizing radiation, suggesting a novel role for XRN2 in R-loop resolution, suppression of replication stress, and maintenance of genomic stability. Our study highlights the importance of regulating transcription-related activities as a critical component in maintaining genetic stability.
          Apprendimento automatico per capire il genoma   

L'Inova Translational Medicine Institute (ITMI), importante istituto di ricerca medica mondiale, ha implementato Cloudera Enterprise per analizzare in modo sicuro un’ampia raccolta di dati Sup genoma in modo rapido e su scala senza precedenti al fine di innovare più velocemente nell’ambito della ricerca della medicina traslazionale.

Come parte del Centro Inova per la Salute Personalizzata (ICPH), il team di scienziati, ricercatori, analisti e collaboratori di ITMI utilizza algoritmi di apprendimento automatico su terabyte di informazioni cliniche e genomiche con l’obiettivo di identificare i legami genetici con le malattie.

Realizzano scoperte dalle informazioni sui dati e, in collaborazione con il medico curante, sviluppano piani di trattamento personalizzati per i pazienti. Questo approccio è anche conosciuto come medicina di precisione e ha il potere di aiutare i pazienti a vivere più a lungo e ad avere una vita più sana.

La genetica svolge un ruolo importante nella maggior parte delle principali cause di morte negli Stati Uniti, tra cui malattie cardiache, cancro e diabete. L’Istituto raccoglie dati clinici da migliaia di pazienti di Inova di oltre 110 Paesi. Il DNA unico di una sola persona contiene sei miliardi di bit di informazioni.

La mappatura dei DNA degli individui nelle sequenze genomiche aiuta gli scienziati a determinare la causa delle malattie e scoprire le terapie trasformative. Come parte di questo processo, l’ITMI sta assemblando quello che si prevede sarà uno dei più grandi database di sequenze di genomi di tutto il mondo collegato alle informazioni sui pazienti in un sistema sanitario.

La piattaforma di Cloudera ha permesso a ITMI di ottimizzare l’analisi dei dati genomici a fini diagnostici. Questa analisi dei dati genomici consente a uno scienziato di bioinformatica di studiare le correlazioni genomiche di persone con condizioni come l’artrite, le malattie autoimmuni o il cancro.

In passato, data l’enorme dimensione di genoma completi, il completamento di questo processo poteva richiedere a ITMI fino a due mesi. Utilizzando Cloudera, ITMI è in grado di eseguire l’analisi end-to-end dei dati in una settimana. Per il futuro ITMI prevede di eseguire queste analisi dei dati in poche ore.

ITMI ha creato un’infrastruttura bioinformatica globale per la raccolta di dati dei genomi dell’Istituto - sempre più consistente –contrapposta agli archivi clinici. L’infrastruttura è stata progettata per archiviare ed elaborare questa convergenza di dati biologici, in velocità e in modo scalabile, oggi e anche in futuro.

Considerando che un genoma è pari a più di tre miliardi di coppie di base di DNA, ITMI attualmente tiene traccia di circa 9.000 genomi completi sequenziati, con una previsione di crescere a 15.000 in futuro. Il moderno database analitico di Cloudera, alimentato da Apache Impala (in fase di progettazione), fornisce analisi SQL ad elevate prestazioni.

Il team ITMI applica la contemporaneità multiutente e analisi ad alte prestazioni dei dati genomici acquisiti da madri, padri e bambini partecipanti a diversi studi familiari di base. Per esempio, ITMI è stata in grado di sfruttare la sua esperienza nell’analisi clinica e genomica per aiutare a individuare anomalie congenite precedentemente non diagnosticate nei bambini. Si tratta di un processo iterativo che richiede tempo ma, grazie a strumenti come Cloudera, ITMI prevede di accelerare ancora di più il processo di diagnosi per aiutare le famiglie.

L'articolo Apprendimento automatico per capire il genoma è un contenuto originale di 01net.


          Post-doctoral Fellow - Functional & Chemical Genomics - Oklahoma Medical Research Foundation - Oklahoma City, OK   
A postdoctoral fellow position is available immediately in the laboratory of Dr. Functional &amp; Chemical Genomics - Yoon....
From Indeed - Tue, 27 Jun 2017 19:39:34 GMT - View all Oklahoma City, OK jobs
          Research Scientist (Environmental Genomics and Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Mentor graduate students and postdoctoral fellows, by devising projects based on original analysis, maximizing their skills and abilities addressing these...
From Lawrence Berkeley National Laboratory - Thu, 20 Apr 2017 02:51:08 GMT - View all Berkeley, CA jobs
          Bioinformatics Specialist-Metagenomics/Proteomics - Signature Science, LLC - Austin, TX   
One year of postdoctoral research in a demonstrably relevant area. Preferably one year of postdoctoral research in a demonstrably relevant area;... $90,000 a year
From Signature Science, LLC - Tue, 06 Jun 2017 09:05:50 GMT - View all Austin, TX jobs
          HGVA: the Human Genome Variation Archive   
Abstract
High-profile genomic variation projects like the 1000 Genomes project or the Exome Aggregation Consortium, are generating a wealth of human genomic variation knowledge which can be used as an essential reference for identifying disease-causing genotypes. However, accessing these data, contrasting the various studies and integrating those data in downstream analyses remains cumbersome. The Human Genome Variation Archive (HGVA) tackles these challenges and facilitates access to genomic data for key reference projects in a clean, fast and integrated fashion. HGVA provides an efficient and intuitive web-interface for easy data mining, a comprehensive RESTful API and client libraries in Python, Java and JavaScript for fast programmatic access to its knowledge base. HGVA calculates population frequencies for these projects and enriches their data with variant annotation provided by CellBase, a rich and fast annotation solution. HGVA serves as a proof-of-concept of the genome analysis developments being carried out by the University of Cambridge together with UK's 100 000 genomes project and the National Institute for Health Research BioResource Rare-Diseases, in particular, deploying open-source for Computational Biology (OpenCB) software platform for storing and analyzing massive genomic datasets.

          DEOGEN2: prediction and interactive visualization of single amino acid variant deleteriousness in human proteins   
Abstract
High-throughput sequencing methods are generating enormous amounts of genomic data, giving unprecedented insights into human genetic variation and its relation to disease. An individual human genome contains millions of Single Nucleotide Variants: to discriminate the deleterious from the benign ones, a variety of methods have been developed that predict whether a protein-coding variant likely affects the carrier individual's health. We present such a method, DEOGEN2, which incorporates heterogeneous information about the molecular effects of the variants, the domains involved, the relevance of the gene and the interactions in which it participates. This extensive contextual information is non-linearly mapped into one single deleteriousness score for each variant. Since for the non-expert user it is sometimes still difficult to assess what this score means, how it relates to the encoded protein, and where it originates from, we developed an interactive online framework (http://deogen2.mutaframe.com/) to better present the DEOGEN2 deleteriousness predictions of all possible variants in all human proteins. The prediction is visualized so both expert and non-expert users can gain insights into the meaning, protein context and origins of each prediction.

          GeSeq – versatile and accurate annotation of organelle genomes   
Abstract
We have developed the web application GeSeq (https://chlorobox.mpimp-golm.mpg.de/geseq.html) for the rapid and accurate annotation of organellar genome sequences, in particular chloroplast genomes. In contrast to existing tools, GeSeq combines batch processing with a fully customizable reference sequence selection of organellar genome records from NCBI and/or references uploaded by the user. For the annotation of chloroplast genomes, the application additionally provides an integrated database of manually curated reference sequences. GeSeq identifies genes or other feature-encoding regions by BLAT-based homology searches and additionally, by profile HMM searches for protein and rRNA coding genes and two de novo predictors for tRNA genes. These unique features enable the user to conveniently compare the annotations of different state-of-the-art methods, thus supporting high-quality annotations. The main output of GeSeq is a GenBank file that usually requires only little curation and is instantly visualized by OGDRAW. GeSeq also offers a variety of optional additional outputs that facilitate downstream analyzes, for example comparative genomic or phylogenetic studies.

          mTCTScan: a comprehensive platform for annotation and prioritization of mutations affecting drug sensitivity in cancers   
Abstract
Cancer therapies have experienced rapid progress in recent years, with a number of novel small-molecule kinase inhibitors and monoclonal antibodies now being widely used to treat various types of human cancers. During cancer treatments, mutations can have important effects on drug sensitivity. However, the relationship between tumor genomic profiles and the effectiveness of cancer drugs remains elusive. We introduce Mutation To Cancer Therapy Scan (mTCTScan) web server (http://jjwanglab.org/mTCTScan) that can systematically analyze mutations affecting cancer drug sensitivity based on individual genomic profiles. The platform was developed by leveraging the latest knowledge on mutation-cancer drug sensitivity associations and the results from large-scale chemical screening using human cancer cell lines. Using an evidence-based scoring scheme based on current integrative evidences, mTCTScan is able to prioritize mutations according to their associations with cancer drugs and preclinical compounds. It can also show related drugs/compounds with sensitivity classification by considering the context of the entire genomic profile. In addition, mTCTScan incorporates comprehensive filtering functions and cancer-related annotations to better interpret mutation effects and their association with cancer drugs. This platform will greatly benefit both researchers and clinicians for interrogating mechanisms of mutation-dependent drug response, which will have a significant impact on cancer precision medicine.

          ConTra v3: a tool to identify transcription factor binding sites across species, update 2017   
Abstract
Transcription factors are important gene regulators with distinctive roles in development, cell signaling and cell cycling, and they have been associated with many diseases. The ConTra v3 web server allows easy visualization and exploration of predicted transcription factor binding sites (TFBSs) in any genomic region surrounding coding or non-coding genes. In this updated version, with a completely re-implemented user interface using latest web technologies, users can choose from nine reference organisms ranging from human to yeast. ConTra v3 can analyze promoter regions, 5΄-UTRs, 3΄-UTRs and introns or any other genomic region of interest. Thousands of position weight matrices are available to choose from for detecting specific binding sites. Besides this visualization option, additional new exploration functionality is added to the tool that will automatically detect TFBSs having at the same time the highest regulatory potential, the highest conservation scores of the genomic regions covered by the predicted TFBSs and strongest co-localizations with genomic regions exhibiting regulatory activity. The ConTra v3 web server is freely available at http://bioit2.irc.ugent.be/contra/v3.

          RegulatorTrail: a web service for the identification of key transcriptional regulators   
Abstract
Transcriptional regulators such as transcription factors and chromatin modifiers play a central role in most biological processes. Alterations in their activities have been observed in many diseases, e.g. cancer. Hence, it is of utmost importance to evaluate and assess the effects of transcriptional regulators on natural and pathogenic processes. Here, we present RegulatorTrail, a web service that provides rich functionality for the identification and prioritization of key transcriptional regulators that have a strong impact on, e.g. pathological processes. RegulatorTrail offers eight methods that use regulator binding information in combination with transcriptomic or epigenomic data to infer the most influential regulators. Our web service not only provides an intuitive web interface, but also a well-documented RESTful API that allows for a straightforward integration into third-party workflows. The presented case studies highlight the capabilities of our web service and demonstrate its potential for the identification of influential regulators: we successfully identified regulators that might explain the increased malignancy in metastatic melanoma compared to primary tumors, as well as important regulators in macrophages. RegulatorTrail is freely accessible at: https://regulatortrail.bioinf.uni-sb.de/.

          BusyBee Web: metagenomic data analysis by bootstrapped supervised binning and annotation   
Abstract
Metagenomics-based studies of mixed microbial communities are impacting biotechnology, life sciences and medicine. Computational binning of metagenomic data is a powerful approach for the culture-independent recovery of population-resolved genomic sequences, i.e. from individual or closely related, constituent microorganisms. Existing binning solutions often require a priori characterized reference genomes and/or dedicated compute resources. Extending currently available reference-independent binning tools, we developed the BusyBee Web server for the automated deconvolution of metagenomic data into population-level genomic bins using assembled contigs (Illumina) or long reads (Pacific Biosciences, Oxford Nanopore Technologies). A reversible compression step as well as bootstrapped supervised binning enable quick turnaround times. The binning results are represented in interactive 2D scatterplots. Moreover, bin quality estimates, taxonomic annotations and annotations of antibiotic resistance genes are computed and visualized. Ground truth-based benchmarks of BusyBee Web demonstrate comparably high performance to state-of-the-art binning solutions for assembled contigs and markedly improved performance for long reads (median F1 scores: 70.02–95.21%). Furthermore, the applicability to real-world metagenomic datasets is shown. In conclusion, our reference-independent approach automatically bins assembled contigs or long reads, exhibits high sensitivity and precision, enables intuitive inspection of the results, and only requires FASTA-formatted input. The web-based application is freely accessible at: https://ccb-microbe.cs.uni-saarland.de/busybee.

          IslandViewer 4: expanded prediction of genomic islands for larger-scale datasets   
Abstract
IslandViewer (http://www.pathogenomics.sfu.ca/islandviewer/) is a widely-used webserver for the prediction and interactive visualization of genomic islands (GIs, regions of probable horizontal origin) in bacterial and archaeal genomes. GIs disproportionately encode factors that enhance the adaptability and competitiveness of the microbe within a niche, including virulence factors and other medically or environmentally important adaptations. We report here the release of IslandViewer 4, with novel features to accommodate the needs of larger-scale microbial genomics analysis, while expanding GI predictions and improving its flexible visualization interface. A user management web interface as well as an HTTP API for batch analyses are now provided with a secured authentication to facilitate the submission of larger numbers of genomes and the retrieval of results. In addition, IslandViewer's integrated GI predictions from multiple methods have been improved and expanded by integrating the precise Islander method for pre-computed genomes, as well as an updated IslandPath-DIMOB for both pre-computed and user-supplied custom genome analysis. Finally, pre-computed predictions including virulence factors and antimicrobial resistance are now available for 6193 complete bacterial and archaeal strains publicly available in RefSeq. IslandViewer 4 provides key enhancements to facilitate the analysis of GIs and better understand their role in the evolution of successful environmental microbes and pathogens.

          WoPPER: Web server for Position Related data analysis of gene Expression in Prokaryotes   
Abstract
The structural and conformational organization of chromosomes is crucial for gene expression regulation in eukaryotes and prokaryotes as well. Up to date, gene expression data generated using either microarray or RNA-sequencing are available for many bacterial genomes. However, differential gene expression is usually investigated with methods considering each gene independently, thus not taking into account the physical localization of genes along a bacterial chromosome. Here, we present WoPPER, a web tool integrating gene expression and genomic annotations to identify differentially expressed chromosomal regions in bacteria. RNA-sequencing or microarray-based gene expression data are provided as input, along with gene annotations. The user can select genomic annotations from an internal database including 2780 bacterial strains, or provide custom genomic annotations. The analysis produces as output the lists of positionally related genes showing a coordinated trend of differential expression. Graphical representations, including a circular plot of the analyzed chromosome, allow intuitive browsing of the results. The analysis procedure is based on our previously published R-package PREDA. The release of this tool is timely and relevant for the scientific community, as WoPPER will fill an existing gap in prokaryotic gene expression data analysis and visualization tools. WoPPER is open to all users and can be reached at the following URL: https://WoPPER.ba.itb.cnr.it

          A PanorOmic view of personal cancer genomes   
Abstract
The massive molecular profiling of thousands of cancer patients has led to the identification of many tumor type specific driver genes. However, only a few (or none) of them are present in each individual tumor and, to enable precision oncology, we need to interpret the alterations found in a single patient. Cancer PanorOmics (http://panoromics.irbbarcelona.org) is a web-based resource to contextualize genomic variations detected in a personal cancer genome within the body of clinical and scientific evidence available for 26 tumor types, offering complementary cohort- and patient-centric views. Additionally, it explores the cellular environment of mutations by mapping them on the human interactome and providing quasi-atomic structural details, whenever available. This ‘PanorOmic’ molecular view of individual tumors, together with the appropriate genetic counselling and medical advice, should contribute to the identification of actionable alterations ultimately guiding the clinical decision-making process.

          TraitRateProp: a web server for the detection of trait-dependent evolutionary rate shifts in sequence sites   
Abstract
Understanding species adaptation at the molecular level has been a central goal of evolutionary biology and genomics research. This important task becomes increasingly relevant with the constant rise in both genotypic and phenotypic data availabilities. The TraitRateProp web server offers a unique perspective into this task by allowing the detection of associations between sequence evolution rate and whole-organism phenotypes. By analyzing sequences and phenotypes of extant species in the context of their phylogeny, it identifies sequence sites in a gene/protein whose evolutionary rate is associated with shifts in the phenotype. To this end, it considers alternative histories of whole-organism phenotypic changes, which result in the extant phenotypic states. Its joint likelihood framework that combines models of sequence and phenotype evolution allows testing whether an association between these processes exists. In addition to predicting sequence sites most likely to be associated with the phenotypic trait, the server can optionally integrate structural 3D information. This integration allows a visual detection of trait-associated sequence sites that are juxtapose in 3D space, thereby suggesting a common functional role. We used TraitRateProp to study the shifts in sequence evolution rate of the RPS8 protein upon transitions into heterotrophy in Orchidaceae. TraitRateProp is available at http://traitrate.tau.ac.il/prop.

          plantiSMASH: automated identification, annotation and expression analysis of plant biosynthetic gene clusters   
Abstract
Plant specialized metabolites are chemically highly diverse, play key roles in host–microbe interactions, have important nutritional value in crops and are frequently applied as medicines. It has recently become clear that plant biosynthetic pathway-encoding genes are sometimes densely clustered in specific genomic loci: biosynthetic gene clusters (BGCs). Here, we introduce plantiSMASH, a versatile online analysis platform that automates the identification of candidate plant BGCs. Moreover, it allows integration of transcriptomic data to prioritize candidate BGCs based on the coexpression patterns of predicted biosynthetic enzyme-coding genes, and facilitates comparative genomic analysis to study the evolutionary conservation of each cluster. Applied on 48 high-quality plant genomes, plantiSMASH identifies a rich diversity of candidate plant BGCs. These results will guide further experimental exploration of the nature and dynamics of gene clustering in plant metabolism. Moreover, spurred by the continuing decrease in costs of plant genome sequencing, they will allow genome mining technologies to be applied to plant natural product discovery. The plantiSMASH web server, precalculated results and source code are freely available from http://plantismash.secondarymetabolites.org.

          SeMPI: a genome-based secondary metabolite prediction and identification web server   
Abstract
The secondary metabolism of bacteria, fungi and plants yields a vast number of bioactive substances. The constantly increasing amount of published genomic data provides the opportunity for an efficient identification of gene clusters by genome mining. Conversely, for many natural products with resolved structures, the encoding gene clusters have not been identified yet. Even though genome mining tools have become significantly more efficient in the identification of biosynthetic gene clusters, structural elucidation of the actual secondary metabolite is still challenging, especially due to as yet unpredictable post-modifications. Here, we introduce SeMPI, a web server providing a prediction and identification pipeline for natural products synthesized by polyketide synthases of type I modular. In order to limit the possible structures of PKS products and to include putative tailoring reactions, a structural comparison with annotated natural products was introduced. Furthermore, a benchmark was designed based on 40 gene clusters with annotated PKS products. The web server of the pipeline (SeMPI) is freely available at: http://www.pharmaceutical-bioinformatics.de/sempi.

          MicrobiomeAnalyst: a web-based tool for comprehensive statistical, visual and meta-analysis of microbiome data   
Abstract
The widespread application of next-generation sequencing technologies has revolutionized microbiome research by enabling high-throughput profiling of the genetic contents of microbial communities. How to analyze the resulting large complex datasets remains a key challenge in current microbiome studies. Over the past decade, powerful computational pipelines and robust protocols have been established to enable efficient raw data processing and annotation. The focus has shifted toward downstream statistical analysis and functional interpretation. Here, we introduce MicrobiomeAnalyst, a user-friendly tool that integrates recent progress in statistics and visualization techniques, coupled with novel knowledge bases, to enable comprehensive analysis of common data outputs produced from microbiome studies. MicrobiomeAnalyst contains four modules - the Marker Data Profiling module offers various options for community profiling, comparative analysis and functional prediction based on 16S rRNA marker gene data; the Shotgun Data Profiling module supports exploratory data analysis, functional profiling and metabolic network visualization of shotgun metagenomics or metatranscriptomics data; the Taxon Set Enrichment Analysis module helps interpret taxonomic signatures via enrichment analysis against >300 taxon sets manually curated from literature and public databases; finally, the Projection with Public Data module allows users to visually explore their data with a public reference data for pattern discovery and biological insights. MicrobiomeAnalyst is freely available at http://www.microbiomeanalyst.ca.

          Programmatic access to bioinformatics tools from EMBL-EBI update: 2017   
Abstract
Since 2009 the EMBL-EBI provides free and unrestricted access to several bioinformatics tools via the user's browser as well as programmatically via Web Services APIs. Programmatic access to these tools, which is fundamental to bioinformatics, is increasingly important as more high-throughput data is generated, e.g. from proteomics and metagenomic experiments. Access is available using both the SOAP and RESTful approaches and their usage is reviewed regularly in order to ensure that the best, supported tools are available to all users. We present here an update describing the latest enhancement to the Job Dispatcher APIs as well as the governance under it.

          GEPIA: a web server for cancer and normal gene expression profiling and interactive analyses   
Abstract
Tremendous amount of RNA sequencing data have been produced by large consortium projects such as TCGA and GTEx, creating new opportunities for data mining and deeper understanding of gene functions. While certain existing web servers are valuable and widely used, many expression analysis functions needed by experimental biologists are still not adequately addressed by these tools. We introduce GEPIA (Gene Expression Profiling Interactive Analysis), a web-based tool to deliver fast and customizable functionalities based on TCGA and GTEx data. GEPIA provides key interactive and customizable functions including differential expression analysis, profiling plotting, correlation analysis, patient survival analysis, similar gene detection and dimensionality reduction analysis. The comprehensive expression analyses with simple clicking through GEPIA greatly facilitate data mining in wide research areas, scientific discussion and the therapeutic discovery process. GEPIA fills in the gap between cancer genomics big data and the delivery of integrated information to end users, thus helping unleash the value of the current data resources. GEPIA is available at http://gepia.cancer-pku.cn/.

          Omicseq: a web-based search engine for exploring omics datasets   
Abstract
The development and application of high-throughput genomics technologies has resulted in massive quantities of diverse omics data that continue to accumulate rapidly. These rich datasets offer unprecedented and exciting opportunities to address long standing questions in biomedical research. However, our ability to explore and query the content of diverse omics data is very limited. Existing dataset search tools rely almost exclusively on the metadata. A text-based query for gene name(s) does not work well on datasets wherein the vast majority of their content is numeric. To overcome this barrier, we have developed Omicseq, a novel web-based platform that facilitates the easy interrogation of omics datasets holistically to improve ‘findability’ of relevant data. The core component of Omicseq is trackRank, a novel algorithm for ranking omics datasets that fully uses the numerical content of the dataset to determine relevance to the query entity. The Omicseq system is supported by a scalable and elastic, NoSQL database that hosts a large collection of processed omics datasets. In the front end, a simple, web-based interface allows users to enter queries and instantly receive search results as a list of ranked datasets deemed to be the most relevant. Omicseq is freely available at http://www.omicseq.org.

          The Proteins API: accessing key integrated protein and genome information   
Abstract
The Proteins API provides searching and programmatic access to protein and associated genomics data such as curated protein sequence positional annotations from UniProtKB, as well as mapped variation and proteomics data from large scale data sources (LSS). Using the coordinates service, researchers are able to retrieve the genomic sequence coordinates for proteins in UniProtKB. This, the LSS genomics and proteomics data for UniProt proteins is programmatically only available through this service. A Swagger UI has been implemented to provide documentation, an interface for users, with little or no programming experience, to ‘talk’ to the services to quickly and easily formulate queries with the services and obtain dynamically generated source code for popular programming languages, such as Java, Perl, Python and Ruby. Search results are returned as standard JSON, XML or GFF data objects. The Proteins API is a scalable, reliable, fast, easy to use RESTful services that provides a broad protein information resource for users to ask questions based upon their field of expertise and allowing them to gain an integrated overview of protein annotations available to aid their knowledge gain on proteins in biological processes. The Proteins API is available at (http://www.ebi.ac.uk/proteins/api/doc).

          Reply by Anonymous Coward (UID 20479168)   
King Tut Related to Half of European Men? Maybe Not A personal genomics company in Switzerland says they've reconstructed a DNA profile of King Tutankhamen by watching the Discovery Channel, claiming the results suggest more than half of Western European men are related to the boy...
          Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum   
The burden of falciparum malaria is especially high in sub-Saharan Africa. Differences in pressure from host immunity and antimalarial drugs lead to adaptive changes responsible for high level of genetic varia...
           NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases.    
Blauwendraat, C; Faghri, F; Pihlstrom, L; Geiger, JT; Elbaz, A; Lesage, S; Corvol, J-C; Blauwendraat, C; Faghri, F; Pihlstrom, L; Geiger, JT; Elbaz, A; Lesage, S; Corvol, J-C; May, P; Nicolas, A; Abramzon, Y; Murphy, NA; Gibbs, JR; Ryten, M; Ferrari, R; Bras, J; Guerreiro, R; Williams, J; Sims, R; Lubbe, S; Hernandez, DG; Mok, KY; Robak, L; Campbell, RH; Rogaeva, E; Traynor, BJ; Chia, R; Chung, SJ; International Parkinson's Disease Genomics Consortium (IPDGC), ; COURAGE-PD Consortium, ; Hardy, JA; Brice, A; Wood, NW; Houlden, H; Shulman, JM; Morris, HR; Gasser, T; Krüger, R; Heutink, P; Sharma, M; Simón-Sánchez, J; Nalls, MA; Singleton, AB; Scholz, SW; - view fewer <#> (2017) NeuroChip, an updated version of the NeuroX genotyping platform to rapidly screen for variants associated with neurological diseases. Neurobiol Aging 10.1016/j.neurobiolaging.2017.05.009 .
          Genomic analysis clarifies subtypes of gastric cancer   
In a massive effort to catalog the molecular causes of stomach cancer, scientists have identified four subtypes of tumors based on shared mutations and other molecular abnormalities. They say the new classification promises to advance clinical research to develop improved therapies for the third-leading cancer killer worldwide.
          Genomics Is Not Magic, There Is No Magic   
MIT Technology Review has an article up, Do Your Family Members Have a Right to Your Genetic Code?, which is now part of the genomics-human-interest-piece genre you see regularly. Here you have the exemplar of this sort of narrative: what do you do when one twin gets a test and the other does not, and...
          Comment on ImaGenomic Portraiture 2.3 Plugin Serial Key Full Download by vivekpatil   
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          Synthetic Genomics Inc. Announces Breakthrough In Algae Biofuel Research   

By Lauren M. Graham, Ph.D.

On June 19, 2017, Synthetic Genomics Inc. announced a breakthrough in its collaboration with ExxonMobil involving the modification of an algae strain that more than doubled its oil content to 40 percent without significantly inhibiting the strain’s growth.  Synthetic Genomics researchers identified a genetic switch that could be fine-tuned to regulate the conversion of carbon to oil in the algae species, Nannochloropsis gaditana, and established a proof-of-concept approach for the new process.  The achievement is a key milestone in the partnership that aims to demonstrate that algae can be incredibly productive as a renewable energy source with a corresponding positive contribution to our environment.  Additional research, testing, and analysis is required to ensure the process is commercially viable. 


          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Advancements in genetic testing: should we be concerned?   

Recently, the International Herald Tribune published an article describing the initiatives of Complete Genomics, a firm in Silicon Valley that has performed significant research on genomic sequencing technology.

Complete Genomics aims to lower the cost of human genome sequencing in order to make this service more readily available to the general population. On the company’s website, Dr. Reid predicted that the cost for gene sequencing could one day be as low as that of a blood test.

I believe that the impact on the medical community of whole human genome sequencing at a cost comparable to a comprehensive blood test will be profound, and it will raise a host of public policy issues (privacy, security, disclosure, reimbursement, interpretation, counseling, etc.), all important topics for future discussions.

Yes, and there is another vital issue that will be impacted by the potential widespread availability of genomic testing: bioethics.

I would like to make it clear that I completely support scientific advancement and research that does not injure human life from conception to natural death. I am frequently amazed by what science can do in assisting people with serious diseases. We are lucky to live in a time where many illnesses are understood and treated, though there is still a lot of work to be done.  

My concern with this news on gene sequencing is that too much information can cause great damage when it comes to medical testing and the diagnosis of genetic disorders. How many people, after going through genetic testing, may find out that they are “at risk” for certain genetic disorders and thus choose to euthanize themselves? Furthermore, how many mothers, after finding out that their unborn child has a genetic anomaly, will choose to abort their child?

We have already seen a rise in the number of abortions of female children since parents became able to know the sex of their child. This phenomenon will repeat itself if access to gene sequencing becomes commonplace- only it will be worse, because then the medical community will thoroughly defend the parents’ ‘choice’ on the grounds that the child’s quality of life would be lower, and that the child would have some life-threatening illness.

It can seem inconsistent on God’s behalf to give us access to so much information, and yet to also ask that we respect human life under all circumstances. However, the inconsistency is really within the medical community. God gives us information to help us, not to hurt us. In the same way, doctors and scientific researchers have a duty to help others and protect their lives.

Let us suppose, for example, that a mother has just recently found out that her baby has a genetic defect. Under such conditions, what can the doctor do? He can either advise her to abort her child, which would likely leave her with scars of suffering and guilt…or he could offer her resources to better prepare for the arrival of her newborn child. The woman could educate herself on the genetic disease, talk to families who have experienced raising children with genetic disease, and maybe even immerse herself in prayer (or companionship with friends and family) to develop the strength to accept the uncertainty that awaits her, and her child.

Also, let us not forget that genetic testing could help us perform surgeries in the womb, before the child is born, in order to replace a defective gene. As long as such surgeries pose no harm to the child, they would be ethically approvable and could even cure the child of his genetic anomaly. Dr. Jérôme Lejeune, a pro-life pediatrician and geneticist, always dreamed that one day a cure for Down’s Syndrome would be discovered. Given the rapid development taking place in the scientific field, let us hope that workers in the medical and scientific community orient their efforts towards initiatives that respect all human life.


          Bioinformatics Specialist-Metagenomics/Proteomics - Signature Science, LLC - Austin, TX   
Travel to project and business development meetings as needed. Familiarity with machine learning, Git, and agile software development is a plus;... $90,000 a year
From Signature Science, LLC - Tue, 06 Jun 2017 09:05:50 GMT - View all Austin, TX jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Genomic DNA Interactions Mechanize Peptidotoxin-Mediated Anticancer Nanotherapy   

TOC Graphic

Molecular Pharmaceutics
DOI: 10.1021/acs.molpharmaceut.7b00083

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          Uncovering the transcriptomic and epigenomic landscape of nicotinic receptor genes in non-neuronal tissues   
Bo Zhang, Pamela Madden, Junchen Gu, Xiaoyun Xing, Savita Sankar, Jennifer Flynn, Kristen Kroll and Ting Wang: 2017 BMC Genomics Volume 18, Issue 1, Article number 439 Read More
          Front End Web Engineer   
San Carlos, We are a Biotech software and services company focused on the development, refinement and advancement of genomic diagnostic technologies. We are a fully integrated organization that owns our methods; from early scientific research all the way through the execution/analysis of diagnostic tests in physicians’ offices. While we consider ourselves a leader in the DNA mapping industry, we cannot contin
          Senior Systems Engineer - Linux/Virtualization/RAID   
San Diego, Located in beautiful San Diego, CA, we deliver on the promise of precision medicine today. Through daily re-computation of individual member clinical and full-sequence genomic data, our analytics provides a prospective clinical interpretation that enables true personalization of therapy, and prevents clinical gaps before they occur. Top Reasons to Work with Us - HUGE Room for Growth - Great Work/L
          Senior Systems Engineer - Linux/Virtualization/RAID   
San Diego, Located in beautiful San Diego, CA, we deliver on the promise of precision medicine today. Through daily re-computation of individual member clinical and full-sequence genomic data, our analytics provides a prospective clinical interpretation that enables true personalization of therapy, and prevents clinical gaps before they occur. Top Reasons to Work with Us - HUGE Room for Growth - Great Work/L
          Malignant Peripheral Nerve Sheath Tumors State of the Science: Leveraging Clinical and Biological Insights into Effective Therapies   
Malignant peripheral nerve sheath tumor (MPNST) is the leading cause of mortality in patients with neurofibromatosis type 1. In 2002, an MPNST consensus statement reviewed the current knowledge and provided guidance for the diagnosis and management of MPNST. Although the improvement in clinical outcome has not changed, substantial progress has been made in understanding the natural history and biology of MPNST through imaging and genomic advances since 2002. Genetically engineered mouse models that develop MPNST spontaneously have greatly facilitated preclinical evaluation of novel drugs for translation into clinical trials led by consortia efforts. Continued work in identifying alterations that contribute to the transformation, progression, and metastasis of MPNST coupled with longitudinal follow-up, biobanking, and data sharing is needed to develop prognostic biomarkers and effective prevention and therapeutic strategies for MPNST.
          (USA-WA-Seattle) Bioinformaticist - Genomics, Amazon Web Services   
Do you want to be a key part of a team focused on increasing the reach of cloud computing across stakeholders in the Genomics industry? Do you have the industry background, technical depth, and communication skills needed to help further establish Amazon as the leader in the industry? The Genomics industry is accelerating the development of novel diagnostics, treatments and is the cornerstone of personalized medicine. AWS is looking for a Business Development leader who understands business and technical trends impacting the industry, and is passionate and capable of driving market development across the sector globally for AWS, leveraging the richness of the AWS cloud computing platform to position and drive the right technology solutions, enable the ecosystem, and address changing industry needs. Your responsibilities will include recommending and implementing systems and processes that will optimize use of AWS service in genomics, working with business development and solution architects to enable and deploy solutions and keeping abreast of scientific and technical approaches in the realm of bioinformatics. You will work with key customers and prospects to understand optimized tooling and approaches to genetic analysis, processing and data storage. You will work closely with AWS Solutions Architects to develop and promote cloud patterns and solutions for the genomics industry, including high performance computing, storage optimization and partner based solutions etc. You will also work closely with the AWS product and services teams to help evolve AWS offerings for more rapid adoption by customers. The ideal candidate will have both a scientific and business background, with experience working with Genomics customers, with demonstrated experience interacting at the CxO/VP level, with a good understanding of genomic science and technology. He/she should have a demonstrated ability to think strategically and analytically about business, product, and technical challenges, with the ability to build and convey compelling value propositions, and work cross-organizationally to build consensus. A keen sense of ownership, drive, and scrappiness is a must. Roles & Responsibilities: + Serve as a key member of the Business Development team to drive overall AWS market and technical strategy for the Genomics industry. + Define and execute on a product development plan and ensure they are in line with the AWS strategic direction, in partnership with key internal stakeholders (e.g. sales teams, service teams, legal, support, etc.). + Define and identify and key technologies and patterns that are used in bioinformatics processing and identify and engage key partners including ISVs and research associations. + Understand the technical requirements of our customers and work closely with the internal development teams to guide the direction of our product offerings for developers. + Present technical and scientific reviews to the senior management team regarding progress and roadblocks to expanding our reach in the industry. + Develop and build new informatics processing pipelines for industry use that leverage various AWS services and programs + Handle a high volume of engagements and interactions in the fast pace of the cloud computing market. + The right person will be scientific and technical, and possess at least 5-10 years of bioinformatics experience supplying technical solutions to the Genomics industry. + Strong leadership skills are key, with proven verbal and written communications skills with demonstrated ability to work effectively across internal and external organizations. + Relevant technical knowledge is helpful, such as R, RStudio, algorithmic development with Python or PERL and an understanding of the required supporting infrastructure. + Experience with genomic pipeline development, analysis and tooling as well as database systems, core distributed computing concepts, storage systems, fundamentals of cloud computing and virtualization, etc. with ability to go deep enough on relevant technologies key to the industry. + Education- a PhD is desired; technical background with Computer Science, and/or Biochemistry/Genomics background is highly desired; working knowledge of software development practices and data center / infrastructure / networking technologies highly desired. + The right person will be scientific and technical, and possess at least 10 years of bioinformatics experience supplying technical solutions to the Genomics industry. + Relevant technical knowledge such as R, RStudio, algorithmic development with Python or PERL and an understanding of the required supporting infrastructure. + Experience with genomic pipeline development, analysis and tooling as well as database systems, core distributed computing concepts, storage systems, fundamentals of cloud computing and virtualization, etc. with ability to go deep enough on relevant technologies key to the industry. + Education- a PhD in bioinformatics; technical background with Computer Science, and/or Biochemistry/Genomics background is highly desired; working knowledge of software development practices and data center / infrastructure / networking technologies highly desired. AMZR Req ID: 554335 External Company URL: www.amazon.com
          Senior Enterprise Applications Engineering Manager   
San Carlos, We are a Biotech software and services company focused on the development, refinement and advancement of genomic diagnostic technologies. We are a fully integrated organization that owns our methods; from early scientific research all the way through the execution/analysis of diagnostic tests in physicians’ offices. While we consider ourselves a leader in the DNA mapping industry, we cannot contin
          Kommentar zu Epigenomics: Wie lange kann das so weitergehen? von CharlesFak   
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          Unchained Labs Raises $13M in Series C Financing; Acquires Trinean   
Unchained Labs, a Pleasanton, CA–based life sciences company, raised $13M in Series C financing. Backers included Novo Ventures, Canaan Partners and TPG. Unchained Labs also made its 5th acquisition in just over 2 years by purchasing Trinean, whose DropSense systems measure protein, DNA and RNA concentration in biologics and genomics samples. The acquired company is […]
          Genomic Vaccines Fight Disease in Ways Not Possible Before   
Vaccines composed of DNA or RNA, instead of protein, could enable rapid development of preventives for infectious diseases

-- Read more on ScientificAmerican.com

          Multiple Tests of Association with Biological Annotation Metadata   
We propose a general and formal statistical framework for the multiple tests of associations between known fixed features of a genome and unknown parameters of the distribution of variable features of this genome in a population of interest. The known fixed gene-annotation profiles, corresponding to the fixed features of the genome, may concern Gene Ontology (GO) annotation, pathway membership, regulation by particular transcription factors, nucleotide sequences, or protein sequences. The unknown gene-parameter profiles, corresponding to the variable features of the genome, may be, for example, regression coefficients relating genome-wide transcript levels or DNA copy numbers to possibly censored biological and clinical outcomes and covariates. A generic question of great interest in current genomic research, regarding the detection of associations between biological annotation metadata and genome-wide expression measures, may then be translated into the multiple tests of hypotheses concerning association measures between gene-annotation and gene-parameter profiles. A general and rigorous formulation of the statistical inference question allows us to apply the multiple testing methodology developed in Dudoit and van der Laan (2006) and related articles, to control a broad class of Type I error rates, in testing problems involving general data generating distributions (with arbitrary dependence structures among variables), null hypotheses, and test statistics. Resampling-based single-step and stepwise multiple testing procedures, that take into account the joint distribution of the test statistics, are provided to control Type I error rates defined as tail probabilities for arbitrary functions of the numbers of false positives and rejected hypotheses. The proposed statistical and computational methods are illustrated using the acute lymphoblastic leukemia (ALL) microarray dataset of Chiaretti et al. (2004), with the aim of relating GO annotation to differential gene expression between B-cell ALL with the BCR/ABL fusion and cytogenetically normal NEG B-cell ALL. The sensitivity of the identified lists of GO terms to the choice of association parameter between GO annotation and differential gene expression demonstrates the importance of translating the biological question in terms of suitable gene-annotation profiles, gene-parameter profiles, and association measures. In particular, the results show the limitations of binary gene-parameter profiles of differential expression indicators, which are still the norm for combined GO annotation and microarray data analyses. Procedures based on such binary gene-parameter profiles tend to be conservative and lack robustness with respect to the estimator for the set of differentially expressed genes. WWW companion: www.stat.berkeley.edu/~sandrine/Docs/Papers/DFF06/DFF.html
          Using metagenomics to investigate human and environmental resistomes   
Abstract
Antibiotic resistance is a global health concern declared by the WHO as one of the largest threats to modern healthcare. In recent years, metagenomic DNA sequencing has started to be applied as a tool to study antibiotic resistance in different environments, including the human microbiota. However, a multitude of methods exist for metagenomic data analysis, and not all methods are suitable for the investigation of resistance genes, particularly if the desired outcome is an assessment of risks to human health. In this review, we outline the current state of methods for sequence handling, mapping to databases of resistance genes, statistical analysis and metagenomic assembly. In addition, we provide an overview of important considerations related to the analysis of resistance genes, and recommend some of the currently used tools and methods that are best equipped to inform research and clinical practice related to antibiotic resistance.

          Fine Mapping, Transcriptome Analysis, and Marker Development for Y2 , the Gene that Conditions Beta-Carotene Accumulation in Carrot (Daucus carota L.).   

Fine Mapping, Transcriptome Analysis, and Marker Development for Y2 , the Gene that Conditions Beta-Carotene Accumulation in Carrot (Daucus carota L.).

G3 (Bethesda). 2017 Jun 29;:

Authors: Ellison S, Senalik D, Bostan H, Iorizzo M, Simon P

Abstract
Domesticated carrots, Daucus carota subsp. sativus, are the richest source of beta-carotene in the US diet, which when consumed is converted into vitamin A, an essential component of eye health and immunity. The Y2 locus plays a significant role in beta-carotene accumulation in carrot roots, but a candidate gene has not been identified. To advance our understanding of this locus, the genetic basis of beta-carotene accumulation was explored by utilizing an advanced mapping population, transcriptome analysis, and nucleotide diversity in diverse carrot accessions with varying levels of beta-carotene. A single large effect Quantitative Trait Locus (QTL) on the distal arm of chromosome 7 overlapped with the previously identified beta-carotene accumulation QTL, Y2 Fine mapping efforts reduced the genomic region of interest to 650 kb including 72 genes. Transcriptome analysis within this fine mapped region identified four genes differentially expressed at two developmental time points and 13 genes differentially expressed at one time point. These differentially expressed genes included transcription factors and genes involved in light signaling and carotenoid flux, including a member of the Di19 gene family involved in Arabidopsis photomorphogenesis, and a homolog of the bHLH36 transcription factor involved in maize carotenoid metabolism. Analysis of nucleotide diversity in 25 resequenced carrot accessions revealed a drastic decrease in diversity of this fine-mapped region in orange cultivated accessions as compared to white and yellow cultivated and to white wild samples. The results presented in this study provide a foundation to identify and characterize the gene underlying beta-carotene accumulation in carrot.

PMID: 28663343 [PubMed - as supplied by publisher]


          Lab member heading to Michigan State for summer internship in plant genomics   

One of my undergraduate research students, Josh Allman, was recently accepted into a summer research program at Michigan State University in plant genomics funded by the National Science Foundation. Josh is doing his independent research in my lab on the regulation of alpha crystallin expression in zebrafish. Last summer he worked with me to genotype [...]

          Announcing the TEDMED 2017 Editorial Advisory Board   

Blockchain in healthcare; Synthetic genomics; Healthcare reform; The opioid epidemic; Drones for good; The effect of social determinants on health; Cost of drug innovation; Impact of climate change on health. These are just a few of the topics that we … Continue reading

The post Announcing the TEDMED 2017 Editorial Advisory Board appeared first on TEDMED Blog.


          Software Developer 2 - Lawrence Berkeley National Laboratory - Berkeley, CA   
HTML/CSS, Javascript, or work with native UI API’s. Berkeley Lab’s Environmental Genomics &amp; Systems Biology Division has an opening for a Software Developer 2....
From Lawrence Berkeley National Laboratory - Tue, 13 Jun 2017 22:58:55 GMT - View all Berkeley, CA jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Experience with UI testing and user-centered design. Demonstrated experience to write high-performance, readable/reusable code for UI components which work...
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Predictive Analytics Sector Leader - Life Science - Genomics - Capgemini - Jersey City, NJ   
Together with its clients, Capgemini creates and delivers business, technology and digital. The Collaborative Business ExperienceTM....
From Capgemini - Fri, 16 Jun 2017 19:53:18 GMT - View all Jersey City, NJ jobs
          Blockchain for Secure Health Data Exchange Being Explored by FDA   
Blockchain for Secure Health Data Exchange Being Explored by FDA

Blockchain technology is being leveraged by IBM and the FDA to improve public health.

ARMONK, N.Y., Jan. 13, 2017 (Block512) — IBM Watson Health (NYSE: IBM) has signed a research initiative with the U.S. Food and Drug Administration (FDA) aimed at defining a secure, efficient and scalable exchange of health data using blockchain technology. IBM and the FDA will explore the exchange of owner mediated data from several sources, such as Electronic Medical Records, clinical trials, genomic data, and health data from mobile devices, wearables and the “Internet of Things.” The initial focus will be on oncology-related data.

Continue reading Blockchain for Secure Health Data Exchange Being Explored by FDA at insights365.


          Software Developer 2 - Lawrence Berkeley National Laboratory - Berkeley, CA   
Experience with developing applications to display/visualize scientific (preferably biological) data. Berkeley Lab’s Environmental Genomics &amp; Systems Biology...
From Lawrence Berkeley National Laboratory - Tue, 13 Jun 2017 22:58:55 GMT - View all Berkeley, CA jobs
          Exhibit: Discover Utah Genomics   
Discover Utah Genomics September 9 – November 2, 2016 EHSL Upper Level University of Utah scientists have been tracking down the genetic cause of disease for over 50 years. They’ve discovered over 30 genes that cause major diseases resulting in new tests and treatments that have saved thousands of lives. Now U of U scientists […]
          Sr. / Research Technician / Research Assistant - Oklahoma Medical Research Foundation - Oklahoma City, OK   
We utilize both animal and cellular models, and cutting edge technologies in functional genomics, bioinformatics, genetics, molecular and cell biology, and...
From Indeed - Fri, 26 May 2017 13:59:53 GMT - View all Oklahoma City, OK jobs
          Alignment-free inference of hierarchical and reticulate phylogenomic relationships   
Abstract
We are amidst an ongoing flood of sequence data arising from the application of high-throughput technologies, and a concomitant fundamental revision in our understanding of how genomes evolve individually and within the biosphere. Workflows for phylogenomic inference must accommodate data that are not only much larger than before, but often more error prone and perhaps misassembled, or not assembled in the first place. Moreover, genomes of microbes, viruses and plasmids evolve not only by tree-like descent with modification but also by incorporating stretches of exogenous DNA. Thus, next-generation phylogenomics must address computational scalability while rethinking the nature of orthogroups, the alignment of multiple sequences and the inference and comparison of trees. New phylogenomic workflows have begun to take shape based on so-called alignment-free (AF) approaches. Here, we review the conceptual foundations of AF phylogenetics for the hierarchical (vertical) and reticulate (lateral) components of genome evolution, focusing on methods based on k-mers. We reflect on what seems to be successful, and on where further development is needed.

          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Global Diet and Nutrition Meeting 2018 (Bella Clarke)   
Human Nutrition, Pediatric Nutrition, Maternal Nutrition, Clinical Nutrition, Animal Nutrition, Sports Nutrition, Food Allergies and Intolerances, Eating Disorders, Nutrigenomics, Functional Food, Artificial Sweeteners and its Effects, Obesity and Diet, Cancer and Diet, Diabetes Friendly Diet, Nutrition Security, Gastro-intestinal Disorders and Diet, Food Borne Illnesses,...
          Comparison of Alternative Splicing Junction Detection Tools Using RNA-Seq Data.   
Related Articles

Comparison of Alternative Splicing Junction Detection Tools Using RNA-Seq Data.

Curr Genomics. 2017 Jun;18(3):268-277

Authors: Ding L, Rath E, Bai Y

Abstract
BACKGROUND: Alternative splicing (AS) is a posttranscriptional process that produces differ-ent transcripts from the same gene and is important to produce diverse protein products in response to environmental stimuli. AS occurs at specific sites on the mRNA sequence, some of which have been de-fined. Multiple bioinformatics tools have been developed to detect AS from experimental data.
OBJECTIVES: The goal of this review is to help researchers use specific tools to aid their research and to develop new AS detection tools based on these previously established tools.
METHOD: We selected 15 AS detection tools that were recently published; we classified and delineated them on several aspects. Also, a performance comparison of these tools with the same starting input was conducted.
RESULT: We reviewed the following categorized features of the tools: Publication information, working principles, generic and distinct workflows, running platform, input data requirement, sequencing depth dependency, reads mapped to multiple locations, isoform annotation basis, precise detected AS types, and performance benchmarks.
CONCLUSION: Through comparisons of these tools, we provide a panorama of the advantages and short-comings of each tool and their scopes of application.

PMID: 28659722 [PubMed - in process]


          Next Generation Sequencing Data and Proteogenomics.   
Related Articles

Next Generation Sequencing Data and Proteogenomics.

Adv Exp Med Biol. 2016;926:11-19

Authors: Ruggles KV, Fenyö D

Abstract
The field of proteogenomics has been driven by combined advances in next-generation sequencing (NGS) and proteomic methods. NGS technologies are now both rapid and affordable, making it feasible to include sequencing in the clinic and academic research setting. Alongside the improvements in sequencing technologies, methods in high throughput proteomics have increased the depth of coverage and the speed of analysis. The integration of these data types using continuously evolving bioinformatics methods allows for improvements in gene and protein annotation, and a more comprehensive understanding of biological systems.

PMID: 27686803 [PubMed - indexed for MEDLINE]


           More than one way to build a flagellum: comparative genomics of parasitic protozoa    
Briggs, Laura J, Davidge, Jacqueline A, Wickstead, Bill, Ginger, Michael L. and Gull, Keith (2004) More than one way to build a flagellum: comparative genomics of parasitic protozoa. Current Biology, 14 (15). R611-R612. ISSN 0960-9822
           Biological and Clinical Significance of Polymorphisms in NAD(P)H: Quinone Oxidoreductase 1 (NQO1)    
Phillips, Roger M. and Basu, S. (2004) Biological and Clinical Significance of Polymorphisms in NAD(P)H: Quinone Oxidoreductase 1 (NQO1). Current Pharmacogenomics and Personalized Medicine, 2 (1). pp. 75-82. ISSN 1570-1603
           Embryonic stem cell-derived neurons : a model for antidepressant pharmacogenomics    
McHugh, Patrick C, Rogers, G.R., Joyce, P.R. and Kennedy, M.A. (2004) Embryonic stem cell-derived neurons : a model for antidepressant pharmacogenomics. American Journal of Medical Genetics. Part B: Neuropsychiatric Genetics, 130B (1). p. 158. ISSN 1552-4841
           Post-genomic applications of tissue microarrays: basic research, prognostic oncology, clinical genomics and drug discovery    
Mobasheri, A., Airley, Rachel, Foster, C.S., Schulze-Tanzil, G. and Shakibaei, M. (2004) Post-genomic applications of tissue microarrays: basic research, prognostic oncology, clinical genomics and drug discovery. Histology and Histopathology, 19 (1). pp. 325-335. ISSN 0213-3911
          Caltech Professor Drills Down on Developing Genomic Tools   
Research Professor Carlos Lois is one of 10 recipients of an EDGE (Enabling Discovery through Genomic Tools) grant from the National Science Foundation (NSF). The newly formed NSF EDGE program will enable biologists to develop enhanced genomic tools that could one day reveal insights into why organisms are structured the way they are and function [...]
          Precipio Diagnostics And Transgenomic, Inc. Complete Merger    
...
  Life Sciences Jobs  
          France to invest €670 million euros for Genomics and Personalized Medicine   
Government of France Announce plans to invest €670 million euros or ($760.8 million) for Genomics and Personalized Medicine which will see it establish 12 genome sequencing centers and two national centers for genomic expertise and data analysis. The program would initially focus on cancer, diabetes and rare diseases but after 2020 would expand to include common […]
           Multiple Autisms: Spectrums of Advocacy and Genomic Science. By Jennifer S. Singh   
<span class="paragraphSection"><span style="font-style:italic;">Multiple Autisms: Spectrums of Advocacy and Genomic Science.</span> By SinghJennifer S.. Minneapolis: University of Minnesota Press, 2015. xv, 284 pages. Paperback, $27.00.</span>
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Familiarity with UNIX. Professor McCombie is seeking highly motivated Postdoctoral Fellows in Statistical Genomics and Human Genetics for his group at the...
From Cold Spring Harbor Laboratory - Wed, 12 Apr 2017 05:15:08 GMT - View all Cold Spring Harbor, NY jobs
          Post-doctoral Fellow - Functional & Chemical Genomics - Oklahoma Medical Research Foundation - Oklahoma City, OK   
*Posting Number: * 0001040 *Working Title: * Post-doctoral Fellow *Classification* : On-going *Status* : Full-Time *Department: * Functional &...
From Indeed - Tue, 27 Jun 2017 19:39:34 GMT - View all Oklahoma City, OK jobs
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Gronau I, Arbiza L, Mohammed J, Siepel A. Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, et al. Postdoctoral Positions in Computational Genomics....
From Cold Spring Harbor Laboratory - Wed, 29 Mar 2017 17:25:11 GMT - View all Cold Spring Harbor, NY jobs
          Post-doctoral Fellow - Functional & Chemical Genomics - Oklahoma Medical Research Foundation - Oklahoma City, OK   
A postdoctoral fellow position is available immediately in the laboratory of Dr. Functional &amp; Chemical Genomics - Yoon....
From Indeed - Tue, 27 Jun 2017 19:39:34 GMT - View all Oklahoma City, OK jobs
          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          Dorsal Forebrain-Specific Deficiency of Reelin-Dab1 Signal Causes Behavioral Abnormalities Related to Psychiatric Disorders   
Abstract
Reelin-Dab1 signaling is involved in brain development and neuronal functions. The abnormalities in the signaling through either reduction of Reelin and Dab1 gene expressions or the genomic mutations in the brain have been reported to be associated with psychiatric disorders. However, it has not been clear if the deficiency in Reelin-Dab1 signaling is responsible for symptoms of the disorders. Here, to examine the function of Reelin-Dab1 signaling in the forebrain, we generated dorsal forebrain-specific Dab1 conditional knockout mouse (Dab1 cKO) and performed a behavioral test battery on the Dab1 cKO mice. Although conventional Dab1 null mutant mice exhibit cerebellar atrophy and cerebellar ataxia, the Dab1 cKO mice had normal cerebellum and showed no motor dysfunction. Dab1 cKO mice exhibited behavioral abnormalities, including hyperactivity, decreased anxiety-like behavior, and impairment of working memory, which are reminiscent of symptoms observed in patients with psychiatric disorders such as schizophrenia and bipolar disorder. These results suggest that deficiency of Reelin-Dab1 signal in the dorsal forebrain is involved in the pathogenesis of some symptoms of human psychiatric disorders.

          Mother Cells Pass on DNA Damage to Offspring   
Some dividing human cells pass on low-level DNA damage to offspring, causing daughter cells to pause in a quiescent, or dormant, state previously thought to be random in origin.

          Gene Mutations Linked to Early-Onset of Pancreatitis in Children   
Genetic mutations and a family history of pancreatitis are often associated with an early-onset of the disease in children. The research study was published in iThe Journal of Pediatrics.

          Identifying Genes that Influence the Timing of Puberty   
A genomic analysis that influences the timing of puberty in men and women was conducted to date and about 389 genetic signals were associated with puberty timing.

          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Familiarity with UNIX. Professor McCombie is seeking highly motivated Postdoctoral Fellows in Statistical Genomics and Human Genetics for his group at the...
From Cold Spring Harbor Laboratory - Wed, 12 Apr 2017 05:15:08 GMT - View all Cold Spring Harbor, NY jobs
          IT Deskside Support - Bilingual - Eurofins Canada - Toronto, ON   
We are also number one in the field of environmental laboratory services and one of the global market leaders in agroscience, genomics, discovery pharmacology,...
From Indeed - Fri, 09 Jun 2017 12:58:51 GMT - View all Toronto, ON jobs
          Laboratory Analyst I - Food Microbiology - Eurofins-Experchem Inc. - Toronto, ON   
It is also number one in the field of environmental laboratory services and one of the global market leaders in agro science, genomics, discovery pharmacology,...
From Indeed - Thu, 11 May 2017 23:32:46 GMT - View all Toronto, ON jobs
          Could studying deaf horses shed light on treatment in humans?   

Over the years, Chemistry Prof. Koren Lipsett has owned and rescued horses. Today, they are a focus of her research on deafness in humans.

“My research lab focuses on genomic studies so we can understand human disease,” said Lipsett.

Prof. LipsettSo far, Lipsett and her students have looked at blind cats, fibroblast growth factor (hair length) in cattle, and for the past seven years, deafness in horses. They hope by researching these issues and genetic diseases in large mammals, it will help researchers better understand how to treat human genetic disorders, like congenital blindness and deafness.

Suzanne E. DiNello-Schleicher ’10, a biology and chemistry double major who is today a veterinarian, was the inspiration behind the horse project. One day in Lipsett’s lab, she was doing some preliminary research on the Internet and came across a story about a deaf colt.

“Because she’s a horse person and a vet person, she said, ‘maybe we can pursue this,’” said Lipsett. “Well it turns out the family that owned that particular horse also had the parents and siblings in this pedigree of Spanish Mustangs. Not just one offspring was deaf. There were two deaf offspring that came from the same stallion and two different mares. So that started the project.”

Working with larger mammals has its benefits, Lipsett says. For one, large mammals, as opposed to mice and rats, live longer. If, during transitional research, researchers are completing a treatment study, this allows scientists to study long-term implications. It’s humane: Lipsett uses hair plucked from the horse’s mane. It’s convenient: she uses her own horse and horses from the SPCA as experimental controls. She is currently working with a family from Virginia who owned deaf horses with white coats and blue eyes—the phenotype that studies have shown to correlate with deafness in other animals, like the Siberian Husky.

This knowledge helped Lipsett’s lab narrow down their focus to a candidate gene called the KIT gene.

Prof. Lipsett in the lab

“In [other cases of mammals] that had deafness, white pigmentation, and blue eyes, it has come down to the KIT gene,” said Lipsett. “That particular gene is complex, but that’s not the only one that has been found—there are 5 or 6 genes that we identified as candidate genes. And our job is to methodically go through, sequencing those genes, to see if we can find the mutation.”

The process involves examining the gene’s exons, the segments of the DNA that contain the coding information, or set of instructions, that translate to the protein of interest, for example.

Benjamin Gantz ’16 was responsible for examining exon-21 in the KIT gene. They ran into several issues with designing primers, which is the first step to sequencing a gene.

“Ben got to a point where we understood where the problem was, and by the time he graduated we a had a good understanding of what to do next,” said Lipsett.

“Ben would say, ‘wow, I’m doing real science,’ and I’d say, ‘You've been doing real science the whole time!’ Because you need to think outside the box. There’s no canned answer.”

“Many students have worked on this project before me. It was amazing to be able to pick up where they left off and continue this research,” echoed Gantz. “In independent research labs like Dr. Lipsett's, you are determining the answers to questions that no one on the planet knows. Other scientists may use our research to further their own understanding or study, but our findings will be a starting point for them.”

Over the years, several students have worked on pieces of the project that have been published, like Kaytie Innamorati ’14, who is currently conducting research on Alzheimer’s Disease as a Ph.D. candidate at Drexel University. She is listed as a co-author on the abstract, “Determining the genetic basis of equine deafness via candidate gene studies.” Also, Alecia Achimovich ’16, a Ph.D. candidate at The University of Virginia, is a co-author with Kaytie on a recent abstract.

Prof. Koren Lipsett working in the lab

Today, Lipsett says the research is at the point where they have narrowed down which genes to focus on, and now it’s about consolidating the data order to identify a putative gene mutation. As with the blind cat study, the next step will be to explore the mechanism of pathology that will help define how the gene mutation translated to disease symptoms like blindness or deafness.

“We care about this because we can directly correlate it to human studies,” said Lipsett. “The more we understand the gene function in a mammal model, the more likely we can understand the equivalent function in humans. Then, we can apply that knowledge to characterize and potentially treat the genetic disorder.”

A biological career pathway

Lipsett didn’t start working with DNA until she came to Gettysburg. But looking at her journey, the path to that research seemed inevitable.

“I loved biochemistry in college,” she said. “I didn’t do genomics, I did protein studies. It’s related to the biological system, and that’s what’s exciting to me. My work evolved slowly, as in any research career. You don’t necessarily stay in the same track, but your research takes you down new tracks and lets you solve cool new problems.”

Prof. Koren LipsettDuring Lipsett’s postdoctoral research at Johns Hopkins University, she studied metabolic pathways at the genomic level and how specific genes, and the gene products, participate in a given biological pathway. She and her colleagues worked on identifying the gene corresponding to an enzyme involved in the aflatoxin biosynthetic pathway in fungus, furthering their understanding of the pathways in natural product biosynthesis. For example, aflatoxins are a family of carcinogenic toxins that are produced by fungi and can be found contaminating grain and peanuts (peanut butter). Aflatoxin can cause liver cancer. In the United States, we screen our crops for the contaminant, but other countries might not.

“My interest is studying these pathways,” she said. Because nature produces antifungal, anticancer and antibacterial agents, she asks questions like, What structural features of the molecule inhibit growth, and How can we modify and make a better antifungal [agent]?

“By applying knowledge gained from understanding the biosynthetic pathway, and the genes involved in that pathway, one can learn from nature and perhaps make the next new therapeutic drug based on that knowledge,” she said. “Learning from nature is really cool!”

Lipsett describes herself as “jumping” into mitochondrial DNA. Her mitochondrial genomic studies began with looking at genomic variations in mitochondrial DNA, some of which have been identified as causing mitochondrial myopathies.

Plucking Patent

This past January, Lipsett received some exciting news: A letter notifying her that she was issued a United States patent for the “Isolation and Characterization of a Single Mitochondron.”

Lipsett explained that one characteristic of mitochondria is that it contains multiple copies of the mitochondrial genome, and each cell can contain many mitochondria.

“If there is a mutation in one copy of the genome, and there are 100 copies total, the other 99 copies are fine,” she said. “So why should one copy interfere with the cell?” Her questions led to studies to learn more about how that one modified copy becomes the predominant version, and therefore, causative of mitochondrial disease symptoms.

She and her colleagues at the National Institute of Standards and Technology designed a technique using what is described as “optical tweezers” that can trap and then isolate a single mitochodrion using an infrared laser.  

Lipsett decided to apply for the patent after speaking with one of her former research students.

“Christian Bauer ’97, a biochemistry and molecular biology major, went to get his master’s in forensic science,” said Lipsett. Bauer continued his education and became a patent attorney. “He was visiting to speak with students for a career panel, and he said, ‘apply for a patent—that’s intellectual property!’”

Lipsett switched gears and began examining nuclear—as opposed to the mitochondrial—genomic variations. During a sabbatical at the National Cancer Institute in Frederick, her research path transitioned to examining pedigrees of large mammals in order to identify the gene responsible for a specific disease.

“I like learning new tools for finding that needle in the haystack, that Eureka moment,” she said. “We haven’t found it yet in the deafness project, but we’ve gathered enough information from this deaf horse study to think it’s more complex than just one gene.”


          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          Rethink Big and Europe?s Position in Big Data   

I will here take a break from core database and talk a bit about EU policies for research funding.

I had lunch with Stefan Manegold of CWI last week, where we talked about where European research should go. Stefan is involved in RETHINK big, a European research project for compiling policy advice regarding big data for EC funding agencies. As part of this, he is interviewing various stakeholders such as end user organizations and developers of technology.

RETHINK big wants to come up with a research agenda primarily for hardware, anything from faster networks to greener data centers. CWI represents software expertise in the consortium.

So, we went through a regular questionnaire about how we see the landscape. I will summarize this below, as this is anyway informative.

Core competence

My own core competence is in core database functionality, specifically in high performance query processing, scale-out, and managing schema-less data. Most of the Virtuoso installed base is in the RDF space, but most potential applications are in fact outside of this niche.

User challenges

The life sciences vertical is the one in which I have the most application insight, from going to Open PHACTS meetings and holding extensive conversations with domain specialists. We have users in many other verticals, from manufacturing to financial services, but there I do not have as much exposure to the actual applications.

Having said this, the challenges throughout tend to be in diversity of data. Every researcher has their MySQL database or spreadsheet, and there may not even be a top level catalogue of everything. Data formats are diverse. Some people use linked data (most commonly RDF) as a top level metadata format. The application data, such as gene sequences or microarray assays, reside in their native file formats and there is little point in RDF-izing these.

There are also public data resources that are published in RDF serializations as vendor-neutral, self-describing format. Having everything as triples, without a priori schema, makes things easier to integrate and in some cases easier to describe and query.

So, the challenge is in the labor intensive nature of data integration. Data comes with different levels of quantity and quality, from hand-curated to NLP extractions. Querying in the single- or double-digit terabyte range with RDF is quite possible, as we have shown many times on this blog, but most use cases do not even go that far. Anyway, what we see on the field is primarily a data diversity game. The scenario is data integration; the technology we provide is database. The data transformation proper, data cleansing, units of measure, entity de-duplication, and such core data-integration functions are performed using diverse, user-specific means.

Jerven Bolleman of the Swiss Institute of Bioinformatics is a user of ours with whom we have long standing discussions on the virtues of federated data and querying. I advised Stefan to go talk to him; he has fresh views about the volume challenges with unexpected usage patterns. Designing for performance is tough if the usage pattern is out of the blue, like correlating air humidity on the day of measurement with the presence of some genomic patterns. Building a warehouse just for that might not be the preferred choice, so the problem field is not exhausted. Generally, I’d go for warehousing though.

What technology would you like to have? Network or power efficiency?

OK. Even a fast network is a network. A set of processes on a single shared-memory box is also a kind of network. InfiniBand is maybe half the throughput and 3x the latency of single threaded interprocess communication within one box. The operative word is latency. Making large systems always involves a network or something very much like one in large scale-up scenarios.

On the software side, next to nobody understands latency and contention; yet these are the one core factor in any pursuit of scalability. Because of this situation, paradigms like MapReduce and bulk synchronous parallel (BSP) processing have become popular because these take the communication out of the program flow, so the programmer cannot muck this up, as otherwise would happen with the inevitability of destiny. Of course, our beloved SQL or declarative query in general does give scalability in many tasks without programmer participation. Datalog has also been used as a means of shipping computation around, as in the the work of Hellerstein.

There are no easy solutions. We have built scale-out conscious, vectorized extensions to SQL procedures where one can express complex parallel, distributed flows, but people do not use or understand these. These are very useful, even indispensable, but only on the inside, not as a programmer-facing construct. MapReduce and BSP are the limit of what a development culture will absorb. MapReduce and BSP do not hide the fact of distributed processing. What about things that do? Parallel, partitioned extensions to Fortran arrays? Functional languages? I think that all the obvious aids to parallel/distributed programming have been conceived of. No silver bullet; just hard work. And above all the discernment of what paradigm fits what problem. Since these are always changing, there is no finite set of rules, and no substitute for understanding and insight, and the latter are vanishingly scarce. "Paradigmatism," i.e., the belief that one particular programming model is a panacea outside of its original niche, is a common source of complexity and inefficiency. This is a common form of enthusiastic naïveté.

If you look at power efficiency, the clusters that are the easiest to program consist of relatively few high power machines and a fast network. A typical node size is 16+ cores and 256G or more RAM. Amazon has these in entirely workable configurations, as documented earlier on this blog. The leading edge in power efficiency is in larger number of smaller units, which makes life again harder. This exacerbates latency and forces one to partition the data more often, whereas one can play with replication of key parts of data more freely if the node size is larger.

One very specific item where research might help without having to rebuild the hardware stack would be better, lower-latency exposure of networks to software. Lightweight threads and user-space access, bypassing slow protocol stacks, etc. MPI has some of this, but maybe more could be done.

So, I will take a cluster of such 16-core, 256GB machines on a faster network, over a cluster of 1024 x 4G mobile phones connected via USB. Very selfish and unecological, but one has to stay alive and life is tough enough as is.

Are there pressures to adapt business models based on big data?

The transition from capex to opex may be approaching maturity, as there have been workable cloud configurations for the past couple of years. The EC2 from way back, with at best a 4 core 16G VM and a horrible network for $2/hr, is long gone. It remains the case that 4 months of 24x7 rent in the cloud equals the purchase price of physical hardware. So, for this to be economical long-term at scale, the average utilization should be about 10% of the peak, and peaks should not be on for more than 10% of the time.

So, database software should be rented by the hour. A 100-150% markup for the $2.80 a large EC2 instance costs would be reasonable. Consider that 70% of the cost in TPC benchmarks is database software.

There will be different pricing models combining different up-front and per-usage costs, just as there are for clouds now. If the platform business goes that way and the market accepts this, then systems software will follow. Price/performance quotes should probably be expressed as speed/price/hour instead of speed/price.

The above is rather uncontroversial but there is no harm restating these facts. Reinforce often.

Well, the question is raised, what should Europe do that would have tangible impact in the next 5 years?

This is a harder question. There is some European business in wide area and mobile infrastructures. Competing against Huawei will keep them busy. Intel and Mellanox will continue making faster networks regardless of European policies. Intel will continue building denser compute nodes, e.g., integrated Knight’s Corner with dual IB network and 16G fast RAM on chip. Clouds will continue making these available on demand once the technology is in mass production.

What’s the next big innovation? Neuromorphic computing? Quantum computing? Maybe. For now, I’d just do more engineering along the core competence discussed above, with emphasis on good marketing and scalable execution. By this I mean trained people who know something about deployment. There is a huge training gap. In the would-be "Age of Data," knowledge of how things actually work and scale is near-absent. I have offered to do some courses on this to partners and public alike, but I need somebody to drive this show; I have other things to do.

I have been to many, many project review meetings, mostly as a project partner but also as reviewer. For the past year, the EC has used an innovation questionnaire at the end of the meetings. It is quite vague, and I don’t think it delivers much actionable intelligence.

What would deliver this would be a venture capital type activity, with well-developed networks and active participation in developing a business. The EC is not now set up to perform this role, though. But the EC is a fairly large and wealthy entity, so it could invest some money via this type of channel. Also there should be higher individual incentives and rewards for speed and excellence. Getting the next Horizon 2020 research grant may be good, but better exists. The grants are competitive enough and the calls are not bad; they follow the times.

In the projects I have seen, productization does get some attention, e.g., the LOD2 stack, but it is not something that is really ongoing or with dedicated commercial backing. It may also be that there is no market to justify such dedicated backing. Much of the RDF work has been "me, too" — let’s do what the real database and data integration people do, but let’s just do this with triples. Innovation? Well, I took the best of the real DB world and adapted this to RDF, which did produce a competent piece of work with broad applicability, extending outside RDF. Is there better than this? Well, some of the data integration work (e.g., LIMES) is not bad, and it might be picked up by some of the players that do this sort of thing in the broader world, e.g., Informatica, the DI suites of big DB vendors, Tamr, etc. I would not know if this in fact adds value to the non-RDF equivalents; I do not know the field well enough, but there could be a possibility.

The recent emphasis for benchmarking, spearheaded by Stefano Bertolo is good, as exemplified by the LDBC FP7. There should probably be one or two projects of this sort going at all times. These make challenges known and are an effective means of guiding research, with a large multiplier: Once a benchmark gets adopted, infinitely more work goes into solving the problem than in stating it in the first place.

The aims and calls are good. The execution by projects is variable. For 1% of excellence, there apparently must be 99% of so-and-so, but this is just a fact of life and not specific to this context. The projects are rather diffuse. There is not a single outcome that gets all the effort. In this, the level of engagement of participants is less and focus is much more scattered than in startups. A really hungry, go-getter mood is mostly absent. I am a believer in core competence. Well, most people will agree that core competence is nice. But the projects I have seen do not drive for it hard enough.

It is hard to say exactly what kinds of incentives could be offered to encourage truly exceptional work. The American startup scene does offer high rewards and something of this could be transplanted into the EC project world. I would not know exactly what form this could take, though.


          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          IT Deskside Support - Bilingual - Eurofins Canada - Toronto, ON   
We are also number one in the field of environmental laboratory services and one of the global market leaders in agroscience, genomics, discovery pharmacology,...
From Indeed - Fri, 09 Jun 2017 12:58:51 GMT - View all Toronto, ON jobs
          Laboratory Analyst I - Food Microbiology - Eurofins-Experchem Inc. - Toronto, ON   
It is also number one in the field of environmental laboratory services and one of the global market leaders in agro science, genomics, discovery pharmacology,...
From Indeed - Thu, 11 May 2017 23:32:46 GMT - View all Toronto, ON jobs
          Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum.   

Pooled-DNA sequencing identifies genomic regions of selection in Nigerian isolates of Plasmodium falciparum.

Parasit Vectors. 2017 Jun 29;10(1):320

Authors: Oyebola KM, Idowu ET, Olukosi YA, Awolola TS, Amambua-Ngwa A

Abstract
BACKGROUND: The burden of falciparum malaria is especially high in sub-Saharan Africa. Differences in pressure from host immunity and antimalarial drugs lead to adaptive changes responsible for high level of genetic variations within and between the parasite populations. Population-specific genetic studies to survey for genes under positive or balancing selection resulting from drug pressure or host immunity will allow for refinement of interventions.
METHODS: We performed a pooled sequencing (pool-seq) of the genomes of 100 Plasmodium falciparum isolates from Nigeria. We explored allele-frequency based neutrality test (Tajima's D) and integrated haplotype score (iHS) to identify genes under selection.
RESULTS: Fourteen shared iHS regions that had at least 2 SNPs with a score > 2.5 were identified. These regions code for genes that were likely to have been under strong directional selection. Two of these genes were the chloroquine resistance transporter (CRT) on chromosome 7 and the multidrug resistance 1 (MDR1) on chromosome 5. There was a weak signature of selection in the dihydrofolate reductase (DHFR) gene on chromosome 4 and MDR5 genes on chromosome 13, with only 2 and 3 SNPs respectively identified within the iHS window. We observed strong selection pressure attributable to continued chloroquine and sulfadoxine-pyrimethamine use despite their official proscription for the treatment of uncomplicated malaria. There was also a major selective sweep on chromosome 6 which had 32 SNPs within the shared iHS region. Tajima's D of circumsporozoite protein (CSP), erythrocyte-binding antigen (EBA-175), merozoite surface proteins - MSP3 and MSP7, merozoite surface protein duffy binding-like (MSPDBL2) and serine repeat antigen (SERA-5) were 1.38, 1.29, 0.73, 0.84 and 0.21, respectively.
CONCLUSION: We have demonstrated the use of pool-seq to understand genomic patterns of selection and variability in P. falciparum from Nigeria, which bears the highest burden of infections. This investigation identified known genomic signatures of selection from drug pressure and host immunity. This is evidence that P. falciparum populations explore common adaptive strategies that can be targeted for the development of new interventions.

PMID: 28662682 [PubMed - in process]


          Stage-Specific Transcriptome and Proteome Analyses of the Filarial Parasite Onchocerca volvulus and Its Wolbachia Endosymbiont.   
Related Articles

Stage-Specific Transcriptome and Proteome Analyses of the Filarial Parasite Onchocerca volvulus and Its Wolbachia Endosymbiont.

MBio. 2016 Nov 23;7(6):

Authors: Bennuru S, Cotton JA, Ribeiro JM, Grote A, Harsha B, Holroyd N, Mhashilkar A, Molina DM, Randall AZ, Shandling AD, Unnasch TR, Ghedin E, Berriman M, Lustigman S, Nutman TB

Abstract
Onchocerciasis (river blindness) is a neglected tropical disease that has been successfully targeted by mass drug treatment programs in the Americas and small parts of Africa. Achieving the long-term goal of elimination of onchocerciasis, however, requires additional tools, including drugs, vaccines, and biomarkers of infection. Here, we describe the transcriptome and proteome profiles of the major vector and the human host stages (L1, L2, L3, molting L3, L4, adult male, and adult female) of Onchocerca volvulus along with the proteome of each parasitic stage and of its Wolbachia endosymbiont (wOv). In so doing, we have identified stage-specific pathways important to the parasite's adaptation to its human host during its early development. Further, we generated a protein array that, when screened with well-characterized human samples, identified novel diagnostic biomarkers of O. volvulus infection and new potential vaccine candidates. This immunomic approach not only demonstrates the power of this postgenomic discovery platform but also provides additional tools for onchocerciasis control programs.
IMPORTANCE: The global onchocerciasis (river blindness) elimination program will have to rely on the development of new tools (drugs, vaccines, biomarkers) to achieve its goals by 2025. As an adjunct to the completed genomic sequencing of O. volvulus, we used a comprehensive proteomic and transcriptomic profiling strategy to gain a comprehensive understanding of both the vector-derived and human host-derived parasite stages. In so doing, we have identified proteins and pathways that enable novel drug targeting studies and the discovery of novel vaccine candidates, as well as useful biomarkers of active infection.

PMID: 27881553 [PubMed - indexed for MEDLINE]


          Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth   
Recurrent hormone-binding domain truncated ESR1 amplifications in primary endometrial cancers suggest their implication in hormone independent growth Holst, Frederik; Hoivik, Erling A.; Taylor-Weiner, Amaro; Schumacher, Steven E.; Asmann, Yan W.; Grossmann, Patrick; Trovik, Jone; Necela, Brian M.; Thompson, E. Aubrey; Salvesen, Helga B.; Cherniack, Andrew D.; Gibson, William J; Meyerson, Matthew L; Beroukhim, Rameen The estrogen receptor alpha (ERα) is highly expressed in both endometrial and breast cancers, and represents the most prevalent therapeutic target in breast cancer. However, anti-estrogen therapy has not been shown to be effective in endometrial cancer. Recently it has been shown that hormone-binding domain alterations of ERα in breast cancer contribute to acquired resistance to anti-estrogen therapy. In analyses of genomic data from The Cancer Genome Atlas (TCGA), we observe that endometrial carcinomas manifest recurrent ESR1 gene amplifications that truncate the hormone-binding domain encoding region of ESR1 and are associated with reduced mRNA expression of exons encoding the hormone-binding domain. These findings support a role for hormone-binding alterations of ERα in primary endometrial cancer, with potentially important therapeutic implications.
          Project Interlinking Blockchain and Genomics Raises $824k Ahead of ICO Closure   

A blockchain project aiming to push the perimeters of ownership and protection of genomics data has raised around $824,000 in an ongoing ICO round. Gene-Chain, as the project is titled, demonstrates a blockchain which a) secures personal genomic data from cloud breaches, and b) enables the sharing of genomic data among researchers and medical practitioners. […]

The post Project Interlinking Blockchain and Genomics Raises $824k Ahead of ICO Closure appeared first on The Bitcoin News - Leading Bitcoin and Crypto News since 2012.


          Encrypgen Announces New Bonus Structure for Its Ongoing ICO   

Encrypgen, the company behind Gene Chain, a blockchain solution for the genomics industry has announced a new bonus structure for its ongoing ICO. With another 17 days, the Gene Chain Coin ICO will now have weekly bonus slabs starting June 29, 2017. As per the new bonus structure, investors purchasing the Gene-Chain tokens during this […]

The post Encrypgen Announces New Bonus Structure for Its Ongoing ICO appeared first on The Bitcoin News - Leading Bitcoin and Crypto News since 2012.


          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          Precipio Diagnostics And Transgenomic, Inc. Complete Merger    
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          Genoptix, Inc. And BioNano Genomics Announce Strategic Alliance    
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          Veracyte Announces Publication Of Study Supporting The Development Of Envisia Genomic Classifier For IPF In    
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          FDA, NCI to study cancer proteogenomics together   
The FDA and the National Cancer Institute will collaborate on clinical proteogenomics cancer research, including "statistical -More

          Mammoth task: billionaire Peter Thiel funded effort to resurrect woolly beast   

Mammoth task: billionaire Peter Thiel funded effort to resurrect woolly beastPayPal billionaire and Gawker war-wager Peter Thiel has invested $100,000 in a research effort to resurrect the woolly mammoth. Thiel, who believes that viewing death as inevitable is a sign of “complacency of the western world”, gave the money to Harvard University genomics professor George Church, whose laboratory is attempting to revive the extinct pachyderm. The donation, detailed for the first time in a new book by Ben Mezrich called Woolly: The True Story of the Quest to Revive One of History’s Most Iconic Extinct Creatures, was made in 2015.



          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          EDITORIALE: Pensiero forestale   
Negli ultimi decenni la capacità di crescita scientifica del settore forestale appare del tutto straordinaria, in grado di cambiare rapidamente qualsiasi quadro di riferimento e di aprirsi concretamente ai temi emergenti collegati alla genomica, alle biotecnologie, alle nanotecnologie, alle tecnologie spaziali e a quelle informatiche. Al contempo, da più parti viene, però, spesso evidenziata una certa carenza di cultura selvicolturale, condizione non di rado ostativa per una diffusione realmente efficace dei risultati della ricerca e per un adeguato trasferimento delle conoscenze scientifiche anche laddove è possibile fare riferimento a soluzioni innovative.
          alikhan4312 posted a blog post   
alikhan4312 posted a blog post

Ni-NTA resin column

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          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          CPTS Program   
The major objectives of this Master's Degree program are to provide training in conceptual/theoretical frameworks, research methodologies, and statistical methods essential to the design and conduct of clinical and epidemiologic research; to provide training in the fundamentals of molecular biology, genetics/genomics and genetic epidemiology; and to provide training in the basic skills of grant and manuscript preparation.
          Bioinformatics Specialist-Metagenomics/Proteomics - Signature Science, LLC - Austin, TX   
Travel to project and business development meetings as needed. Familiarity with machine learning, Git, and agile software development is a plus;... $90,000 a year
From Signature Science, LLC - Tue, 06 Jun 2017 09:05:50 GMT - View all Austin, TX jobs
          Il futuro della ricerca oncologica nei sei progetti tra Cro e imprese regionali finanziati con 900 mila euro   
L’Istituto Nazionale Tumori di Aviano è l’assegnatario di sei progetti inseriti nei bandi di finanziamento Por-Fesr 2016. I coordinatori dei gruppi di lavoro sono Roberta Maestro e Alessandra Viel (Oncogenetica e Oncogenomica Funzionale), Federico Polo ed Erika Cecchin (Farmacologia Sperimentale e Clinica) e Vincenzo Canzonieri di Anatomia Patologica a indirizzo Oncologico
          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
           Characterization of drug-resistant neuroblastoma cell lines by comparative genomic hybridization.    
Bedrnicek, J. and Vicha, A. and Jarosova, M. and Holzerova, M. and Cinatl, Jindrich and Michaelis, Martin and Cinatl, Jaroslav and Eckschlager, T. (2005) Characterization of drug-resistant neuroblastoma cell lines by comparative genomic hybridization. Neoplasma, 52 (5). pp. 415-9. ISSN 0028-2685. (The full text of this publication is not currently available from this repository. You may be able to access a copy if URLs are provided)
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Ancient gene flow from early modern humans into Eastern Neanderthals. Postdoctoral Positions in Computational Genomics....
From Cold Spring Harbor Laboratory - Wed, 29 Mar 2017 17:25:11 GMT - View all Cold Spring Harbor, NY jobs
          Envisioning the scientific community as One Big Lab   
The blogosphere has been abuzz recently, or, at least, it seems that way if you've only been checking up on it sporadically the last few weeks. Jennifer Rohn's post about lab notebooks has spurred over 100 lively comments spanning electronic lab notebooks, peer-review, openness in science, and the reward system in science, making for an engrossing peek at the social science of science. Cameron's own musings on that discussion. Pawel Szczesny writes about what it means to be a freelancing scientist. All of this is fascinating and it is exciting to contemplate both what the future of science holds and the obstacles we will need to overcome; the fact that there are indeed stubborn obstacles (technological as well as cultural) and potentially tremendous rewards makes the anticipation of that future all the more heightened.

Emboldened by the collective fervor, I would like to propose an idea - an idea with the same name as this blog. But first, the back story.

About 8 months ago, one of my lab mates was writing up a short paper for submission to a translational bioinformatics conference. The work she was submitting revolved around a powerful literature-search tool tailored for pharmacogenomics called Pharmspresso. Although Pharmspresso had features lacking in existing search methods and was thus useful, the intent was for it to recognize genes, drugs and polymorphisms in free text, and so she needed a way to evaluate its performance. The evaluation task would be straightforward: given a set of pharmacogenomics papers, what percentage of the mentions of genes, drugs, and polymorphisms does Pharmspresso capture? Getting the list of recognized entities from Pharmspresso would be easy, just give it the documents and set it running. But what would be the gold standard?

Typically, gold standards are created by humans. In this case, it would be the list of entities recognized by human readers with the appropriate knowledge to make the distinctions, in the same set of papers. To get her gold standard then, she essentially asked favors of her colleagues in the lab and the department, which translated to a number of them reading papers and doing data entry during free time (or during faculty talks) at a departmental retreat in early fall - not exactly fun, but done out of a sense of duty to science and the goodness of their hearts.

Afterwards, while socializing during one of the poster sessions, this task came up, and the discussion (in which Samuel Flores, Magda Jonikas, Yael Garten, Alain Laederach, and Bernie Daigle all participated) quickly turned to alternative solutions for tackling this and similar problems in science - those requiring knowledge and resources external to your own. As another example, many bioinformaticians work on problems that produce predictions of functions which would benefit from experimental tests of their validity. Conversely, a wet lab may benefit greatly from someone with computational expertise guiding or leading the data analysis, or even providing the hypotheses for experimental studies (in the form of predictions). This is the stuff from which many collaborations are born, but it may be difficult to find the right people in the first place, or the task at hand might seem not quite collaboration-worthy.

In essence, the problem boils down to this: you or your lab possesses a certain collection of skills, knowledge, and resources (hereafter referred to as simply resources), but your needs may not be fully addressed by what you possess. The solution lies in this simple proposition: some other person or lab has what you're looking for.

While it makes sense for a lab or individual to grow their resources and be mostly self-sufficient, at some point it becomes more economical to outsource certain tasks - to companies for antibody development, software for data analysis, supercomputers for high-throughput computing, etc. In some cases, the exchange takes place directly at the academic level, for example, with some labs maintaining and sharing specific cell lines or mouse strains for use by other researchers, or less directly through the use of published and available tools for all sorts of tasks in bioinformatics. So it would seem that outsourcing is common and accepted. But aside from these sorts of established avenues, what other needs do scientists have in conducting their research that are not easily solved? How often is a line of inquiry abandoned or slowed because of a lack of necessary skills, knowledge, or material resources?

The idea behind One Big Lab is that the scientific community should act as, well, one big lab, sharing resources when it makes sense, and everyone, especially the community as a whole, benefits.

During that discussion at the departmental retreat, the solution boiled down to some form of online transaction service built around a credit system. Scientist X would like 5 gold standard outputs for a certain task, so she posts a description of the task along with some credit attached. Other users can then sign up to complete the task, after which they receive the stated number of credits. Of course, in order to post tasks, you need to have a balance of credits you can draw from - which you earn by doing other people's tasks. Getting credits into the system to start needs to be figured out (give everyone N credits? Money for credits?), but assuming there's some baseline of credit floating around amongst the various users, an equilibrium should eventually be reached (at least, that's the hope).

Variations on this theme are natural - have a peer rating system, have the final credit payment be subject to a bidding system (based somehow on user ratings, e.g. highly rated users can ask for more credits to complete a task and the task-poster may select which user to "hire" based on the user ratings as well as how much each user is asking), have some kind of mechanism for taking transactions "offline" into serious collaborations, etc. Tasks may run the gamut from routine and rote to intellectually stimulating and scientifically rewarding. Obviously, guidelines will have to be set for what transactions may be appropriate for this forum and which ones might be more suited for formal, collaborative relationships - but even here, a forum such as this could be very useful for finding collaborators.

In addition to the scientific transaction system, there could be other features that build on the community aspect, such as journal clubs, informal manuscript review, resources for students, and discussion forums. There could be repositories for knowledge or links to existing ones, informal or formal consulting, and casual exchange of ideas which could stimulate research or professional development. All of this should reinforce the idea that science is strengthened by community and the scientific community should not be held back by insufficient allocation of resources.

Although there are a number of websites out there that tackle some of these aspects, especially the community-building ones, I haven't really seen much resembling the transaction system, which is really the core of the idea. Pawel's freelance science comes close, and what I'd like to see is a formalized community-wide online service for essentially that. Maybe this is technically infeasible right now right the way grants work (it may be difficult to justify spending time or resources on other people's research) or with the way scientists work, but I would like to think that the basic premise - bringing together people with complementary skills and resources - makes sense and balances out in everyone's favor. (Whether this premise actually pans out in practice is up for debate - if we offered credits for cash, would anyone ever do someone else's tasks, or would demand outpace supply? By the same token, there could be "freelance" scientists like Pawel who primarily complete tasks, and could then have the option of "cashing out".) I'm sure there are a ton of tricky legal, IP, financial, organizational, etc not to mention social and cultural issues (would you trust someone you don't know to do work for you?), but I think the idea of having One Big Lab is worth exploring.

If I had the time, skills, and business acumen I would throw together a prototype and work out a business plan, but at the moment the most I can do is outsource it to the closest thing we have to One Big Lab - the blogosphere. ;)

Incidentally, Alain Laederach had come up with a similar idea about a year earlier and we thought about naming it "Experitrade" - an online system for trading experiments, essentially, but the name sounded too corporate and the grant he wrote never got off the ground. But the idea has persisted and inspired One Big Lab.

So, I'd welcome any thoughts, logical extensions, deal-makers or deal-breakers, important issues to consider, "prior art"... does anyone think this idea has legs? Will it work if it is completely altruistic? Does adding money into the equation detract from its mission or the science? What sorts of technical and organizational roadblocks are there? Clearly it makes the most sense, if any prototype is developed, to start small - with a couple participating labs or within a school or university, which helps with the trust issue as well. But I'd like to make sure I'm not completely missing the picture!
          AMIA Summit on Translational Bioinformatics   





Hundreds of clinical scientists, biologists, bioinformaticians, and policy gurus descended on the swanky Intercontinental Mark Hopkins hotel for the first AMIA-sponsored Summit on Translational Bioinformatics last week. Stanford's Atul Butte rallied impressive troops for this inaugural meeting, including the leaders of all of the National Centers for Biomedical Computation (NCBCs, 7 or so total). Since translational bioinformatics is not simply about research, but about translating research into tangible benefits (clinical diagnostics, therapeutics, and standard of care), this meant a many faceted conversation involving basic researchers, large-scale integrative projects (e.g. caBIG, the NCBCs), clinical scientists, informaticians, and government agencies. This was reflected by the structure of the meeting, which consisted of tutorials; policy, technology, and organization panels; primary paper sessions; and posters covering topics ranging from how to establish collaborative projects to ontologies and phenomics.

Given the breadth of the audience, I'm sure the highlights of the conference vary from person to person. Below are some of mine:

Eitan Rubin from Ben Gurion University, Israel (Talk highlight). "Reverse translational bioinformatics: a bioinformatics assay of age, gender and clinical biomarker." A self-proclaimed biologist, Eitan presented some intriguing work in what he called "reverse translational bioinformatics" - using clinical/medical data to make useful discoveries about biology. As an additional aim, he strove to show that existing bioinformatics tools could be applied to clinical data with little modification. To do this, he took an immense data set - thousands of variables collected for tens of thousands of individuals (part of a nutrition and lifestyle survey that was epidemiological in nature), including laboratory tests, questionnaire answers, and medication data - and essentially turned it into a microarray after binning by age. Note that this was a proxy for clinical data since no such data is currently publicly available. He then subjected this array to the same kinds of analyses one would perform on an array of molecular biological data: normalization, calculation of median values, clustering by age and variable. The results encompassed both the expected and the surprising. For example, when he clustered by age, he found distinct boundaries between somewhat intuitive ages - at 12 yrs and 16 yrs for both sexes, at 40 yrs for women and again around 49, and around 45 for men; these could point to interesting biological changes going on at these age boundaries. He also plotted the median values for variables like serum lead level vs age and found distinct patterns. At this point, he has only begun to analyze the enormous amounts of data, and more interesting patterns are sure to emerge. In the meantime, it helps drive home the potential behind open data and data (and methods!) re-use.

Yael Garten from Stanford University (talk highlight). "Pharmspresso: a text analysis tool for linking pharmacogenomic concepts." [Disclaimer: Yael and I are colleagues in the same lab and I helped to critique her presentation.] Yael's work on a semantic, scoped search engine for pharmacogenomics is worth mentioning because of its immediate and potential utility. Pharmspresso allows a user to query a corpus of documents (currently about a thousand pharmacogenomic-related articles previously curated by the PharmGKB team) for keywords, genes, drugs, and/or polymorphisms occurring in the same sentences. Based on the Textpresso ontology created for mining the C.elegans literature, Pharmspresso includes semantic support for human genes, drugs, and genetic polymorphisms and additionally improves upon more general search engines such as Google and PubMed by limiting the scope of the hits to the sentence-level and returning hits color-coded within each sentence for easy evaluation of search results. Pharmspresso has already helped the PharmGKB curators and in the future will be incorporated into an automatic curation pipeline.

Selected papers to be published in BMC Bioinformatics. At the close of the conference, the surprise announcement was made that 15 of the 27 presented papers had been selected to be published in a summer issue of BMC Bioinformatics as a joint agreement between the Open Access journal and AMIA, who would foot the bill. The papers would need to be expanded and updated for submission but the peer review process had happened for the conference and so they were already considered accepted for the journal. A couple of big conferences already do something similar - ISMB/ECCB and RECOMB - but it would be great if every major conference had some kind of arrangement like this with a journal. It seems like it would be a win-win for everyone - peer-review already taken care of, an increased audience for that issue of the journal, and a nice CV boost for the authors (and no more hard decisions between presenting at a conference vs publishing in a journal). Given the fact that this was the very first meeting for this conference, it was a very nice surprise indeed.

Thoughtful A/V setup. This is simply a logistical highlight. We've all sat through our share of technical difficulties, but this conference (at least in the main room) was astonishingly free of them. A large part of this was due to the presence of dedicated A/V staff who knew just when to dim and raise the lights, cue mood music, and put up the "transition screen" - a screen blank except for the AMIA logo. This screen went up whenever a presenter's slides were NOT up, and prevented those awkward moments when the audience could see the desktop of the presenter's laptop or the view of the Powerpoint application. It was also nice not to have to see the blue or black screens when video input was changed. All in all, it imparted a much-appreciated professional touch to the conference which other meetings would do well to emulate.

In summary, there were some informative panels on various policies and the NCBCs, interesting research, and nice extras that made this first Summit on Translational Bioinformatics a big success!
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Bacteria Laden Meat in Question, But Don't Eat Fish Instead   

A study conducted by the Arizona-based Translational Genomics Research Institute (TGRI) and released last Friday found that nearly half of all meat products sampled contained high levels of bacteria and some strains were resistant to multiple types of antibiotics. The research team examined 136 meat samples from 26 grocery stores in Illinois, Florida, California, Arizona […]

The post Bacteria Laden Meat in Question, But Don't Eat Fish Instead appeared first on Organic Authority.


          17-0031 Bioanalytical Scientist - USA-CA-La Jolla   
At Synthetic Genomics, Inc., we are dedicated to developing and commercializing genomic-driven solutions to address global challenges. We are currently seeking a Bioanalytical Scientist within our Ana...
          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Familiarity with UNIX. Professor McCombie is seeking highly motivated Postdoctoral Fellows in Statistical Genomics and Human Genetics for his group at the...
From Cold Spring Harbor Laboratory - Wed, 12 Apr 2017 05:15:08 GMT - View all Cold Spring Harbor, NY jobs
          Post-doctoral Fellow - Functional & Chemical Genomics - Oklahoma Medical Research Foundation - Oklahoma City, OK   
*Posting Number: * 0001040 *Working Title: * Post-doctoral Fellow *Classification* : On-going *Status* : Full-Time *Department: * Functional &...
From Indeed - Tue, 27 Jun 2017 19:39:34 GMT - View all Oklahoma City, OK jobs
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Gronau I, Arbiza L, Mohammed J, Siepel A. Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, et al. Postdoctoral Positions in Computational Genomics....
From Cold Spring Harbor Laboratory - Wed, 29 Mar 2017 17:25:11 GMT - View all Cold Spring Harbor, NY jobs
          Front End Developer SD2 (Environmental Genomics & Systems Biology) - Lawrence Berkeley National Laboratory - Berkeley, CA   
Berkeley Lab’s Environmental Genomics & Systems Biology Division has an opening for a Front End Developer. As part of the KBase implementation team, you will
From Lawrence Berkeley National Laboratory - Tue, 30 May 2017 19:54:31 GMT - View all Berkeley, CA jobs
          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Ancient gene flow from early modern humans into Eastern Neanderthals. Postdoctoral Positions in Computational Genomics....
From Cold Spring Harbor Laboratory - Wed, 29 Mar 2017 17:25:11 GMT - View all Cold Spring Harbor, NY jobs
          Technical Officer   
NSW-Dubbo, Working for NSW Health Pathology NSW Health Pathology is a government agency that operates for the good of NSW's health and justice systems and the well-being of the community. The organisation invests in its people as well as the technologies that ensure staff can deliver the answers customers need when they need them. NSW Health Pathology is at the forefront of emerging fields such as genomics,
          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Master Grower - Horticulture - Fox D Consulting - Greater Toronto Area, ON   
Understanding of biotechnology, molecular biology and genomics preferred. NIAGARA ONTARIO, CHATHAM ONTARIO, MUSKOKA REGION, BRANT REGION, GTA.... $50,000 - $100,000 a year
From Indeed - Wed, 28 Jun 2017 12:14:28 GMT - View all Greater Toronto Area, ON jobs
          Molecular and FISH analyses of a 53-kbp intact DNA fragment inserted by biolistics in wheat (Triticum aestivum L.) genome.   

Molecular and FISH analyses of a 53-kbp intact DNA fragment inserted by biolistics in wheat (Triticum aestivum L.) genome.

Plant Cell Rep. 2017 Jun 30;:

Authors: Partier A, Gay G, Tassy C, Beckert M, Feuillet C, Barret P

Abstract
KEY MESSAGE: A large, 53-kbp, intact DNA fragment was inserted into the wheat ( Triticum aestivum L.) genome. FISH analyses of individual transgenic events revealed multiple insertions of intact fragments. Transferring large intact DNA fragments containing clusters of resistance genes or complete metabolic pathways into the wheat genome remains a challenge. In a previous work, we showed that the use of dephosphorylated cassettes for wheat transformation enabled the production of simple integration patterns. Here, we used the same technology to produce a cassette containing a 44-kb Arabidopsis thaliana BAC, flanked by one selection gene and one reporter gene. This 53-kb linear cassette was integrated in the bread wheat (Triticum aestivum L.) genome by biolistic transformation. Our results showed that transgenic plants harboring the entire cassette were generated. The inheritability of the cassette was demonstrated in the T1 and T2 generation. Surprisingly, FISH analysis performed on T1 progeny of independent events identified double genomic insertions of intact fragments in non-homoeologous positions. Inheritability of these double insertions was demonstrated by FISH analysis of the T1 generation. Relative conclusions that can be drawn from molecular or FISH analysis are discussed along with future prospects of the engineering of large fragments for wheat transformation or genome editing.

PMID: 28667403 [PubMed - as supplied by publisher]


          Data Scientist   
San Francisco, Data Scientist Company: Ancestry DNA Location: San Francisco, CA Position Type: Full Time Experience: 1 year Education: Master's Degree Data Scientist: Dvlp comp. methods/models to analyze genomic data from genomic samples. Anlze big data from high-throughput sequencing tech platforms. Dvlp & validate machine learning. Req: MSCS & 1 yr. exp. w/ sequencing data, predictive modeling, visualization,
          Second-generation PLINK: rising to the challenge of larger and richer datasets.   

PLINK 1 is a widely used open-source C/C++ toolset for genome-wide association studies and research in population genetics. However, the steady accumulation of data from imputation and whole-genome sequencing studies has exposed a strong need for faster and scalable implementations of key functions, such as logistic regression, linkage disequilibrium estimation, and genomic distance evaluation.


          Research Technician I - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
The core will collaborate with CSHL and other regional investigators to design, execute, and interpret single-cell genomics experiments, as well as develop...
From Cold Spring Harbor Laboratory - Wed, 21 Jun 2017 19:55:00 GMT - View all Cold Spring Harbor, NY jobs
          Senior Systems Engineer - Linux/Virtualization/RAID   
San Diego, Located in beautiful San Diego, CA, we deliver on the promise of precision medicine today. Through daily re-computation of individual member clinical and full-sequence genomic data, our analytics provides a prospective clinical interpretation that enables true personalization of therapy, and prevents clinical gaps before they occur. Top Reasons to Work with Us - HUGE Room for Growth - Great Work/L
          Senior Systems Engineer - Linux/Virtualization/RAID   
San Diego, Located in beautiful San Diego, CA, we deliver on the promise of precision medicine today. Through daily re-computation of individual member clinical and full-sequence genomic data, our analytics provides a prospective clinical interpretation that enables true personalization of therapy, and prevents clinical gaps before they occur. Top Reasons to Work with Us - HUGE Room for Growth - Great Work/L
          Manager of Software Development   
Bellevue, If you are a "Hands On" Manager of Software Development with experience, please read on! Located in beautiful Bellevue, WA, we are a rapidly growing SaaS company that is making precision medicine a reality for thousands of physicians every day. We are looking for a Director of Software Development to build the team that will make genomic medicine an integral part of the global health systems. The
          Epigenomics » Übernahmefrist für China-Offerte läuft Freitag ab   
von Klaus Schachinger, €uro am Sonntag

Das Unternehmen hat auf Anfrage von €uro am Sonntag noch einmal für die Annahme der Offerte geworben, wollte aber keine weiteren Details nennen.

Aktionäre halten die ...
          Genomic Signal Processing   

          Introduction to Computational Genomics: A Case Studies Approach   

          ‘Biological Teleportation’ Edges Closer With Craig Venter’s Digital-to-Biological Converter   
The year is 2030. In a high-security containment lab, scientists gathered around a towering machine, eagerly awaiting the first look at a newly discovered bacterium on Mars. With a series of beeps, the machine—a digital-to-biological converter, or DBC—signaled that it had successfully received the bacterium’s digitized genomic file. Using a chemical cocktail comprised of the […]
          Post-doctoral Fellow - Functional & Chemical Genomics - Oklahoma Medical Research Foundation - Oklahoma City, OK   
*Posting Number: * 0001040 *Working Title: * Post-doctoral Fellow *Classification* : On-going *Status* : Full-Time *Department: * Functional &...
From Indeed - Tue, 27 Jun 2017 19:39:34 GMT - View all Oklahoma City, OK jobs
          Post Doc Computational - Cold Spring Harbor Laboratory - Cold Spring Harbor, NY   
Gronau I, Arbiza L, Mohammed J, Siepel A. Kuhlwilm M, Gronau I, Hubisz MJ, de Filippo C, Prado J, et al. Postdoctoral Positions in Computational Genomics....
From Cold Spring Harbor Laboratory - Wed, 29 Mar 2017 17:25:11 GMT - View all Cold Spring Harbor, NY jobs
          Fulltime tenure-track position in the field of nutrition and human intestinal microbiome   
Universite Laval - School of Nutrition - Laval, QC - Quebec City, QC - nutrition or biochemistry or microbiology or a related discipline; 2) Have a recognized expertise in the field of the human intestinal microbiome; 3..., grants or awards; 4) Have demonstrated skills for laboratory work in microbiology, metagenomics, molecular biology and nutritional biochemistry...