Archive for the 'SciLit' Category

promoter/enhancer categorization and Encyclopedia

July 1, 2017

Genome-wide characterization of..promoters w…enhancer functions http://www.Nature.com/ng/journal/v49/n7/full/ng.3884.html Blurs distinction betw these, suggests flexibility

Genome-wide characterization of mammalian promoters with distal enhancer functions

Lan T M Dao,
Ariel O Galindo-Albarrán,
Jaime A Castro-Mondragon,
Charlotte Andrieu-Soler,
Alejandra Medina-Rivera,
Charbel Souaid,
Guillaume Charbonnier,
Aurélien Griffon,
Laurent Vanhille,
Tharshana Stephen,
Jaafar Alomairi,
David Martin,
Magali Torres,
Nicolas Fernandez,
Eric Soler,
Jacques van Helden,
Denis Puthier
& Salvatore Spicuglia

Promoting transcription over long distances

Rui R Catarino,
Christoph Neumayr
& Alexander Stark

Nature Genetics 49, 972–973 (2017) doi:10.1038/ng.3904
28 June 2017

http://www.nature.com/ng/journal/v49/n7/full/ng.3884.html

http://www.nature.com/ng/journal/v49/n7/full/ng.3904.html

QT:{{”
“Should we be surprised that promoters can function as enhancers—or better—that enhancers and promoter regions can overlap? Probably not: the habit of annotating different genomic regions with distinct labels ignores the fact that DNA sequences typically encode different genetic functions in a rather flexible manner. Enhancers and promoters are determined by the presence of short degenerate motifs, and even protein-coding regions display flexibility due to the degeneracy of the genetic code. Therefore, a single DNA sequence can encode different types of functions, including enhancer function of protein-coding regions or—as shown now—enhancer function of
promoters.”
“}}

Single Cell Analysis paper

June 30, 2017

http://genome-tech.ucsd.edu/public/Lake_Science_2016/
https://twitter.com/mikejg84/status/880240608144531456

16 Neuronal subtypes & [inter-regional] diversity revealed by [#singlecell]-nucleus RNAseq of…the brain
http://science.sciencemag.org/content/352/6293/1586.long

Neuronal subtypes and diversity revealed by single-nucleus RNA sequencing of the human brain.
Lake BB, Ai R, Kaeser GE, Salathia NS, Yung YC, Liu R, Wildberg A, Gao D, Fung HL, Chen S, Vijayaraghavan R, Wong J, Chen A, Sheng X, Kaper F, Shen R, Ronaghi M, Fan JB, Wang W, Chun J, Zhang K.
Science. 2016 Jun 24;352(6293):1586-90. doi: 10.1126/science.aaf1204.

A survey of human brain transcriptome diversity at the single cell level

June 27, 2017

Brain #transcriptome diversity at the single cell level
http://www.PNAS.org/content/112/23/7285 Has useful gene-exp. profiles of specific neural cell types

has profiles for 185 biomarker genes for 6 cell types

Zika virus evolution and spread in the Americas : Nature : Nature Research

June 25, 2017

http://www.nature.com/nature/journal/v546/n7658/full/nature22402.html

#Zika virus evolution & spread in the Americas, by @sabeti_lab http://www.Nature.com/nature/journal/v546/n7658/full/nature22402.html #Phylogeny reconstruction of 110 new + 64 known seqs.

First, design for data sharing : Nature Biotechnology : Nature Research

June 20, 2017

Design for data sharing
http://www.Nature.com/nbt/journal/v34/n4/full/nbt.3516.html Issues in distributing mPower mobile dataset – no DAC, allowing donors to change preferences

QT:{{”
“This March, Sage Bionetworks (Seattle) began sharing curated data collected from >9,000 participants of mPower, a smartphone-enabled health research study for Parkinson’s disease. The mPower study is notable as one of the first observational assessments of human health to rapidly achieve scale as a result of its design and execution purely through a smartphone interface. To support this unique study design, we developed a novel electronic informed consent process that includes participant-determined data-sharing preferences. It is through these preferences that the new data—including self-reported outcomes and quantitative sensor data—are shared broadly for secondary analysis. Our hope is that by sharing these data immediately, prior even to our own complete analysis, we will shorten the time to harnessing any utility that this study’s data may hold to improve the condition of patients who suffer from this disease.

Turbulent times for data sharing

Our release of mPower comes at a turbulent time in data sharing. The power of data for secondary research is top of mind for many these days. Vice President Joe Biden, in heading President Barack Obama’s ambitious cancer ‘moonshot’, describes data sharing as second only to funding to the success of the effort. However, this powerful support for data sharing stands in opposition to the opinions of many within the research establishment. To wit, the august New England Journal of Medicine (NEJM)’s recent editorial suggesting that those who wish to reuse clinical trial data without the direct participation and approval of the original study team are “research parasites”. In the wake of colliding perspectives on data sharing, we must not lose sight of the scientific and societal ends served by such efforts.” “}}

A comprehensive transcriptional map of primate brain development

June 19, 2017

A…transcriptional map of primate (macaque) #brain development http://www.Nature.com/nature/journal/vaop/ncurrent/full/nature18637.html Gene expression changes more rapidly before birth
Nature (2016) doi:10.1038/nature18637

An Expanded View of Complex Traits: From Polygenic to Omnigenic: Cell

June 19, 2017

Thought-provoking calculations, perhaps suggesting that ever bigger association studies won’t yield useful results
https://twitter.com/joe_pickrell/status/875406448716632064

http://www.cell.com/cell/abstract/S0092-8674(17)30629-3

An Expanded View of Complex Traits: From Polygenic to Omnigenic

Evan A. Boyle
Yang I. Li
Jonathan K. Pritchard
DOI: http://dx.doi.org/10.1016/j.cell.2017.05.038

Journal Club Paper

June 18, 2017

Zhou, J. and Troyanskaya, O.G. (2015). Predicting effects of noncoding variants with deep learning–based sequence model. Nature Methods, 12, 931–934.

Predicting (& prioritizing) effects of noncoding variants w. [DeepSEA] #DeepLearning…model
https://www.Nature.com/nmeth/journal/v12/n10/full/nmeth.3547.html Trained w #ENCODE data

Proportionality: A Valid Alternative to Correlation for Relative Data

June 12, 2017

A Valid Alternative to #Correlation for Rel. Data
http://journals.PLoS.org/ploscompbiol/article?id=10.1371/journal.pcbi.1004075 Illustrates how r fails on simple expression expts HT @mason_lab

https://twitter.com/mason_lab/status/870643989246074881

A Big Bang model of human colorectal tumor growth : Nature Genetics : Nature Research

June 7, 2017

https://www.nature.com/ng/journal/v47/n3/full/ng.3214.html

Big Bang model of…tumor growth, v. slow #evolution under selection https://www.Nature.com/ng/journal/v47/n3/full/ng.3214.html #Cancer is born w/ key mutations all there

Andrea Sottoriva,
Haeyoun Kang,
Zhicheng Ma,
Trevor A Graham,
Matthew P Salomon,
Junsong Zhao,
Paul Marjoram,
Kimberly Siegmund,
Michael F Press,
Darryl Shibata
& Christina Curtis

Nature Genetics 47, 209–216 (2015) doi:10.1038/ng.3214