Posts Tagged ‘#genomics’

Analysis of noncoding regulatory mutations in cancer

Monday, September 29th, 2014

http://www.nature.com/ng/journal/vaop/ncurrent/full/ng.3101.html

An interesting report of potential non-coding drivers without actually doing any wet lab work.

“These methods identify recurrent mutations in regulatory elements upstream of PLEKHS1, WDR74 and SDHD, as well as previously identified mutations in the TERT promoter”. In the text they mention “Khurana et al. also reported WDR74 promoter mutations in 2 of the 20 prostate cancer genomes analyzed”.

The genomic and transcriptomic architecture of 2,000 breast tumours reveals novel subgroups : Nature : Nature Publishing Group

Sunday, August 31st, 2014

metabric consortium

gene expression & copy number data available and survival data (on request) for the 4 main breast cancer types (basal, her2 , luma, lumb)

similar to TCGA but from the UK

Allows construction of discovery & validation sets to compare segregation of survival with mRNA level

compare segreg. of survival with inferred protein activity v mRNA level

PacBio Blog: Data Release: ~54x Long-Read Coverage for PacBio-only De Novo Human Genome Assembly

Sunday, August 31st, 2014

http://blog.pacificbiosciences.com/2014/02/data-release-54x-long-read-coverage-for.html

QT:{{”
We are pleased to make publicly available a new shotgun sequence dataset of long PacBio® reads from a human DNA sample. We previously released sequence data using Single Molecule, Real-Time (SMRT®) Sequencing of ~10x coverage of this sample, sufficient for
reference-based detection of structural variation. Today we expand on that release with additional data that increases the total sequencing coverage to ~54x. This long-read data has enabled the generation of the first de novohuman genome assembly from PacBio-only sequence reads. Download the 54x long-read coverage dataset.

The dataset was generated from sequencing a well-studied human cell line (CHM1htert), which is being utilized as part of a National Institutes of Health project to sequence and assemble an alternate reference genome (the “platinum genome”). This NIH project is being led by Rick Wilson from Washington University at St. Louis and Evan Eichler from the University of Washington in collaboration with investigators from the National Center for Biotechnology Information. “}}

Single-cell RNA-seq highlights intratumoral heterogeneity in primary glioblastoma

Saturday, August 30th, 2014

#Singlecell #RNAseq highlights intratumoral heterogeneity http://www.sciencemag.org/content/344/6190/1396.abs Subtype classifiers variably expressed across indiv. cells

Patel AP(1), Tirosh I(2), Trombetta JJ(2), Shalek AK(2), Gillespie SM(3),
Wakimoto H(4), Cahill DP(4), Nahed BV(4), Curry WT(4), Martuza RL(4), Louis
DN(5), Rozenblatt-Rosen O(2), Suvà ML(6), Regev A(7), Bernstein BE(8).

Published Online June 12 2014
Science 20 June 2014:
Vol. 344 no. 6190 pp. 1396-1401
DOI: 10.1126/science.1254257

Extensive transduction of nonrepetitive DNA mediated by L1 retrotransposition in cancer genomes

Monday, August 11th, 2014

Transduction of nonrepetitive DNA mediated by L1 retrotransposition in #cancer #genomes
http://www.sciencemag.org/content/345/6196/1251343.abs associated w/ hypomethylation

Jose M. C. Tubio1,
Yilong Li1,*,
Young Seok Ju1,*,
Inigo Martincorena1,
Susanna L. Cooke1,

Adrienne M. Flanagan30,31,
P. Andrew Futreal1,32,
Sam M. Janes3,
G. Steven Bova12,
Michael R. Stratton1,
Ultan McDermott1,
Peter J. Campbell1,10,33,‡

QT:{{”
Retrotransposons are DNA repeat sequences that are constantly on the move. By poaching certain cellular enzymes, they copy and insert themselves at new sites in the genome. Sometimes they carry along adjacent DNA sequences, a process called 3′ transduction. Tubio et al. found that 3′ transduction is a common event in human tumors. Because this process can scatter genes and regulatory sequences across the genome, it may represent yet another mechanism by which tumor cells acquire new mutations that help them survive and grow.
“}}

Activating Mutations Cluster in the “Molecular Brake” Regions of Protein Kinases and Do Not Associate w ith Conserved or Catalytic Residues

Thursday, August 7th, 2014

Activating Mutations Cluster in… Regions of… #Kinases & Do Not Associate with Conserved or Catalytic Residues
http://onlinelibrary.wiley.com/doi/10.1002/humu.22493/abstract

related to Kin-Driver – a database of driver mutations, which can be used as a gold std in driver predictions

Evolution at Two Levels: On Genes and Form

Wednesday, July 23rd, 2014

Evolution at 2 Levels: Genes &
Formhttp://www.plosbiology.org/article/info%3Adoi%2F10.1371%2Fjournal.pbio.0030245 Reg evol likely for genes in mult tissues, w. pleiotropic coding SNPs & mult CRMs

QT:{{”

One critical parameter that affects the relative contribution of different genetic mechanisms to anatomical variation is the pleiotropy of mutations []. In general, it is expected that mutations with greater pleiotropic effects will have more deleterious effects on organismal fitness and will be a less common source of variation in form than mutations with less widespread effects.

Over the past 30 years, several key features of gene structure, function, and regulation in multicellular organisms have emerged that govern the pleiotropy of mutations and thus shape the capacity of species to generate anatomical variation and to evolve (see ). Because of these features, mutations in different genes and different parts of genes (that is, non-coding and coding sequences) can differ
dramatically in their degree of pleiotropy. For example, a mutation in the coding region of a transcription factor that functions in multiple tissues may directly affect all of the genes the protein regulates. In contrast, a mutation in a single cis-regulatory element will affect gene expression only in the domain governed by that element.

The most influential single publication of this era, however, was Susumu Ohno’s book Evolution by Gene Duplication []. Ohno focused on the importance of gene redundancy in allowing “forbidden” mutations to occur that could impart new functions to proteins. His opening motto, “natural selection merely modified, while redundancy created,” reflected a view of natural selection as a largely purifying, conservative process. Ohno insisted that “allelic mutations of already existing gene loci cannot account for major changes in evolution.”

…the estimated rate of gene duplication is about once per gene per 100 million years []. This figure suggests that gene duplication can contribute to genome evolution over longer spans of evolutionary time (for example, greater than 50 million years)….

The human FOXP2 gene encodes a transcription factor, and mutations at the locus were discovered to be associated with a speech and language disorder…. While it would certainly be convenient if the two changes in the FOXP2 protein were functional, the additional hypothesis must be considered that functional regulatory changes might have occurred at theFOXP2 locus. In weighing alternative hypotheses of FOXP2 or any gene’s potential involvement in the evolution of form (or neural circuitry), we should ask the following questions. (i) Is the gene product used in multiple tissues? (ii) Are mutations in the coding sequence known or likely to be pleiotropic? (iii) Does the locus contain multiple cis-regulatory elements?

If the answers are yes to all of these questions, then regulatory sequence evolution is the more likely mode of evolution than coding sequence evolution.

“}}

chinese cancer data

Friday, July 18th, 2014

http://www.ncbi.nlm.nih.gov/pmc/articles/PMC3759719/

Annotated somatic variants and interactive variant analysis results are available online atwww.ingenuity.com/acrg2012.

Eighty-eight primary HCC tumors and matched adjacent nontumor liver tissues were analyzed by whole-genome DNA sequencing to identify somatic mutations and HBV integration sites. The vast majority (92%,n = 81) of patients in this cohort were HBV carriers (i.e., HBsAg seropositive) suffering from chronic hepatitis B or cirrhosis. None of the patients were hepatitis C virus (HCV) positive

the data:

http://gigadb.org/dataset/100034

The original paper is here: http://www.ncbi.nlm.nih.gov/pubmed/23788652

chinese cancer data

Thursday, July 17th, 2014

the data:

http://gigadb.org/dataset/100034

The original paper is here: http://www.ncbi.nlm.nih.gov/pubmed/23788652

PAWG-WGL Links for PCAWG upload status

Friday, July 4th, 2014

PanCancer.info has fantastic #viz of the progress & int’l effort in the Pan-#Cancer Analysis of Whole #Genomes (#PCAWG) project