What's new for 'JKB_daily1' in PubMed

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Sender's message: Sepsis or genomics or altitude: JKB_daily1

Sent on Saturday, 2015 January 24
Search: (sepsis[MeSH Terms] OR septic shock[MeSH Terms] OR altitude[MeSH Terms] OR genomics[MeSH Terms] OR genetics[MeSH Terms] OR retrotransposons[MeSH Terms] OR macrophage[MeSH Terms]) AND ("2009/8/8"[Publication Date] : "3000"[Publication Date]) AND (("Science"[Journal] OR "Nature"[Journal] OR "The New England journal of medicine"[Journal] OR "Lancet"[Journal] OR "Nature genetics"[Journal] OR "Nature medicine"[Journal]) OR (Hume DA[Author] OR Baillie JK[Author] OR Faulkner, Geoffrey J[Author]))

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PubMed Results

Items 1 - 4 of 4

1.	Nat Genet. 2014 Dec;46(12):1251. doi: 10.1038/ng.3155. Second call for pan-cancer analysis. [No authors listed] Comment on Genome-wide analysis of noncoding regulatory mutations in cancer. [Nat Genet. 2014] Genome-wide analysis of noncoding regulatory mutations in cancer.Weinhold N, Jacobsen A, Schultz N, Sander C, Lee W. Nat Genet. 2014 Nov; 46(11):1160-5. Epub 2014 Sep 28.
	PMID: 25418742 [PubMed - indexed for MEDLINE]
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2.	Nat Genet. 2014 Dec;46(12):1356-62. doi: 10.1038/ng.3139. Epub 2014 Nov 10. Leveraging population admixture to characterize the heritability of complex traits. Zaitlen N1, Pasaniuc B2, Sankararaman S3, Bhatia G4, Zhang J5, Gusev A4, Young T6, Tandon A3, Pollack S4, Vilhjálmsson BJ4, Assimes TL7, Berndt SI8, Blot WJ9, Chanock S8, Franceschini N10, Goodman PG11, He J5, Hennis AJ12, Hsing A13, Ingles SA5, Isaacs W14, Kittles RA15, Klein EA16, Lange LA17, Nemesure B18, Patterson N6, Reich D19, Rybicki BA20, Stanford JL21, Stevens VL22, Strom SS23, Whitsel EA10, Witte JS24, Xu J25, Haiman C26, Wilson JG27, Kooperberg C21, Stram D5, Reiner AP28, Tang H29, Price AL4. Abstract Despite recent progress on estimating the heritability explained by genotyped SNPs (h(2)g), a large gap between h(2)g and estimates of total narrow-sense heritability (h(2)) remains. Explanations for this gap include rare variants or upward bias in family-based estimates of h(2) due to shared environment or epistasis. We estimate h(2) from unrelated individuals in admixed populations by first estimating the heritability explained by local ancestry (h(2)γ). We show that h(2)γ = 2FSTCθ(1 - θ)h(2), where FSTC measures frequency differences between populations at causal loci and θ is the genome-wide ancestry proportion. Our approach is not susceptible to biases caused by epistasis or shared environment. We applied this approach to the analysis of 13 phenotypes in 21,497 African-American individuals from 3 cohorts. For height and body mass index (BMI), we obtained h(2) estimates of 0.55 ± 0.09 and 0.23 ± 0.06, respectively, which are larger than estimates of h(2)g in these and other data but smaller than family-based estimates of h(2). PMCID: PMC4244251 [Available on 2015/6/1]
	PMID: 25383972 [PubMed - indexed for MEDLINE]
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3.	Nat Genet. 2014 Dec;46(12):1363-71. doi: 10.1038/ng.3138. Epub 2014 Nov 2. A multiscale statistical mechanical framework integrates biophysical and genomic data to assemble cancer networks. AlQuraishi M1, Koytiger G2, Jenney A2, MacBeath G3, Sorger PK2. Comment in Predicting protein networks in cancer. [Nat Genet. 2014] Predicting protein networks in cancer.Califano A. Nat Genet. 2014 Dec; 46(12):1252-3. Abstract Functional interpretation of genomic variation is critical to understanding human disease, but it remains difficult to predict the effects of specific mutations on protein interaction networks and the phenotypes they regulate. We describe an analytical framework based on multiscale statistical mechanics that integrates genomic and biophysical data to model the human SH2-phosphoprotein network in normal and cancer cells. We apply our approach to data in The Cancer Genome Atlas (TCGA) and test model predictions experimentally. We find that mutations mapping to phosphoproteins often create new interactions but that mutations altering SH2 domains result almost exclusively in loss of interactions. Some of these mutations eliminate all interactions, but many cause more selective loss, thereby rewiring specific edges in highly connected subnetworks. Moreover, idiosyncratic mutations appear to be as functionally consequential as recurrent mutations. By synthesizing genomic, structural and biochemical data, our framework represents a new approach to the interpretation of genetic variation. PMCID: PMC4244270 [Available on 2015/6/1]
	PMID: 25362484 [PubMed - indexed for MEDLINE]
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4.	Nat Genet. 2014 Dec;46(12):1343-9. doi: 10.1038/ng.3119. Epub 2014 Oct 19. Haplotype-resolved whole-genome sequencing by contiguity-preserving transposition and combinatorial indexing. Amini S1, Pushkarev D1, Christiansen L1, Kostem E1, Royce T1, Turk C1, Pignatelli N1, Adey A2, Kitzman JO2, Vijayan K1, Ronaghi M1, Shendure J2, Gunderson KL1, Steemers FJ1. Abstract Haplotype-resolved genome sequencing enables the accurate interpretation of medically relevant genetic variation, deep inferences regarding population history and non-invasive prediction of fetal genomes. We describe an approach for genome-wide haplotyping based on contiguity-preserving transposition (CPT-seq) and combinatorial indexing. Tn5 transposition is used to modify DNA with adaptor and index sequences while preserving contiguity. After DNA dilution and compartmentalization, the transposase is removed, resolving the DNA into individually indexed libraries. The libraries in each compartment, enriched for neighboring genomic elements, are further indexed via PCR. Combinatorial 96-plex indexing at both the transposition and PCR stage enables the construction of phased synthetic reads from each of the nearly 10,000 'virtual compartments'. We demonstrate the feasibility of this method by assembling >95% of the heterozygous variants in a human genome into long, accurate haplotype blocks (N50 = 1.4-2.3 Mb). The rapid, scalable and cost-effective workflow could enable haplotype resolution to become routine in human genome sequencing.
	PMID: 25326703 [PubMed - indexed for MEDLINE]
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