What's new for 'JKB_daily1' in PubMed

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

Sent on Tuesday, 2015 January 27
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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Items 1 - 4 of 4

1.	Science. 2015 Jan 16;347(6219):250-4. doi: 10.1126/science.1258732. The roller coaster flight strategy of bar-headed geese conserves energy during Himalayan migrations. Bishop CM1, Spivey RJ1, Hawkes LA2, Batbayar N3, Chua B4, Frappell PB5, Milsom WK4, Natsagdorj T6, Newman SH7, Scott GR8, Takekawa JY9, Wikelski M10, Butler PJ11. Abstract The physiological and biomechanical requirements of flight at high altitude have been the subject of much interest. Here, we uncover a steep relation between heart rate and wingbeat frequency (raised to the exponent 3.5) and estimated metabolic power and wingbeat frequency (exponent 7) of migratory bar-headed geese. Flight costs increase more rapidly than anticipated as air density declines, which overturns prevailing expectations that this species should maintain high-altitude flight when traversing the Himalayas. Instead, a "roller coaster" strategy, of tracking the underlying terrain and discarding large altitude gains only to recoup them later in the flight with occasional benefits from orographic lift, is shown to be energetically advantageous for flights over the Himalayas. Copyright © 2015, American Association for the Advancement of Science.
	PMID: 25593180 [PubMed - indexed for MEDLINE]
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2.	Science. 2015 Jan 16;347(6219):248-50. doi: 10.1126/science.1259172. Epub 2014 Nov 20. Agriculture facilitated permanent human occupation of the Tibetan Plateau after 3600 B.P. Chen FH1, Dong GH1, Zhang DJ2, Liu XY3, Jia X2, An CB2, Ma MM2, Xie YW2, Barton L4, Ren XY5, Zhao ZJ6, Wu XH7, Jones MK8. Abstract Our understanding of when and how humans adapted to living on the Tibetan Plateau at altitudes above 2000 to 3000 meters has been constrained by a paucity of archaeological data. Here we report data sets from the northeastern Tibetan Plateau indicating that the first villages were established only by 5200 calendar years before the present (cal yr B.P.). Using these data, we tested the hypothesis that a novel agropastoral economy facilitated year-round living at higher altitudes since 3600 cal yr B.P. This successful subsistence strategy facilitated the adaptation of farmers-herders to the challenges of global temperature decline during the late Holocene. Copyright © 2015, American Association for the Advancement of Science.
	PMID: 25593179 [PubMed - indexed for MEDLINE]
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3.	Nature. 2014 Dec 11;516(7530):198-206. doi: 10.1038/nature14046. Genome-wide characterization of the routes to pluripotency. Hussein SM1, Puri MC2, Tonge PD1, Benevento M3, Corso AJ4, Clancy JL5, Mosbergen R6, Li M1, Lee DS7, Cloonan N8, Wood DL8, Munoz J3, Middleton R9, Korn O6, Patel HR10, White CA11, Shin JY12, Gauthier ME8, Lê Cao KA8, Kim JI7, Mar JC13, Shakiba N14, Ritchie W9, Rasko JE15, Grimmond SM8, Zandstra PW11, Wells CA16, Preiss T17, Seo JS18, Heck AJ3, Rogers IM19, Nagy A20. Comment in Stem cells: A designer's guide to pluripotency. [Nature. 2014] Stem cells: A designer's guide to pluripotency.Wu J, Izpisua Belmonte JC. Nature. 2014 Dec 11; 516(7530):172-3. Abstract Somatic cell reprogramming to a pluripotent state continues to challenge many of our assumptions about cellular specification, and despite major efforts, we lack a complete molecular characterization of the reprograming process. To address this gap in knowledge, we generated extensive transcriptomic, epigenomic and proteomic data sets describing the reprogramming routes leading from mouse embryonic fibroblasts to induced pluripotency. Through integrative analysis, we reveal that cells transition through distinct gene expression and epigenetic signatures and bifurcate towards reprogramming transgene-dependent and -independent stable pluripotent states. Early transcriptional events, driven by high levels of reprogramming transcription factor expression, are associated with widespread loss of histone H3 lysine 27 (H3K27me3) trimethylation, representing a general opening of the chromatin state. Maintenance of high transgene levels leads to re-acquisition of H3K27me3 and a stable pluripotent state that is alternative to the embryonic stem cell (ESC)-like fate. Lowering transgene levels at an intermediate phase, however, guides the process to the acquisition of ESC-like chromatin and DNA methylation signature. Our data provide a comprehensive molecular description of the reprogramming routes and is accessible through the Project Grandiose portal at http://www.stemformatics.org.
	PMID: 25503233 [PubMed - indexed for MEDLINE]
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4.	Nature. 2014 Dec 11;516(7530):242-5. doi: 10.1038/nature13760. Epub 2014 Sep 28. An evolutionary arms race between KRAB zinc-finger genes ZNF91/93 and SVA/L1 retrotransposons. Jacobs FM1, Greenberg D2, Nguyen N3, Haeussler M4, Ewing AD5, Katzman S4, Paten B4, Salama SR6, Haussler D6. Comment in As time goes by: KRABs evolve to KAP endogenous retroelements. [Dev Cell. 2014] As time goes by: KRABs evolve to KAP endogenous retroelements.Imbeault M, Trono D. Dev Cell. 2014 Nov 10; 31(3):257-8. Epub 2014 Nov 10. Abstract Throughout evolution primate genomes have been modified by waves of retrotransposon insertions. For each wave, the host eventually finds a way to repress retrotransposon transcription and prevent further insertions. In mouse embryonic stem cells, transcriptional silencing of retrotransposons requires KAP1 (also known as TRIM28) and its repressive complex, which can be recruited to target sites by KRAB zinc-finger (KZNF) proteins such as murine-specific ZFP809 which binds to integrated murine leukaemia virus DNA elements and recruits KAP1 to repress them. KZNF genes are one of the fastest growing gene families in primates and this expansion is hypothesized to enable primates to respond to newly emerged retrotransposons. However, the identity of KZNF genes battling retrotransposons currently active in the human genome, such as SINE-VNTR-Alu (SVA) and long interspersed nuclear element 1 (L1), is unknown. Here we show that two primate-specific KZNF genes rapidly evolved to repress these two distinct retrotransposon families shortly after they began to spread in our ancestral genome. ZNF91 underwent a series of structural changes 8-12 million years ago that enabled it to repress SVA elements. ZNF93 evolved earlier to repress the primate L1 lineage until ∼12.5 million years ago when the L1PA3-subfamily of retrotransposons escaped ZNF93's restriction through the removal of the ZNF93-binding site. Our data support a model where KZNF gene expansion limits the activity of newly emerged retrotransposon classes, and this is followed by mutations in these retrotransposons to evade repression, a cycle of events that could explain the rapid expansion of lineage-specific KZNF genes. PMCID: PMC4268317 [Available on 2015/6/11]
	PMID: 25274305 [PubMed - indexed for MEDLINE]
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What's new for 'JKB_daily1' in PubMed

This message contains My NCBI what's new results from the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM).
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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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What's new for 'JKB_daily1' in PubMed

This message contains My NCBI what's new results from the National Center for Biotechnology Information (NCBI) at the U.S. National Library of Medicine (NLM).
Do not reply directly to this message.

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

Sent on Wednesday, 2015 January 21
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 - 6 of 6

1.	Science. 2015 Jan 2;347(6217):1258524. doi: 10.1126/science.1258524. Epub 2014 Nov 27. Mosquito genomics. Extensive introgression in a malaria vector species complex revealed by phylogenomics. Fontaine MC1, Pease JB2, Steele A3, Waterhouse RM4, Neafsey DE5, Sharakhov IV6, Jiang X7, Hall AB7, Catteruccia F8, Kakani E8, Mitchell SN9, Wu YC10, Smith HA1, Love RR1, Lawniczak MK11, Slotman MA12, Emrich SJ13, Hahn MW14, Besansky NJ15. Comment in Evolutionary genomics. Conundrum of jumbled mosquito genomes. [Science. 2015] Evolutionary genomics. Conundrum of jumbled mosquito genomes.Clark AG, Messer PW. Science. 2015 Jan 2; 347(6217):27-8. Abstract Introgressive hybridization is now recognized as a widespread phenomenon, but its role in evolution remains contested. Here, we use newly available reference genome assemblies to investigate phylogenetic relationships and introgression in a medically important group of Afrotropical mosquito sibling species. We have identified the correct species branching order to resolve a contentious phylogeny and show that lineages leading to the principal vectors of human malaria were among the first to split. Pervasive autosomal introgression between these malaria vectors means that only a small fraction of the genome, mainly on the X chromosome, has not crossed species boundaries. Our results suggest that traits enhancing vectorial capacity may be gained through interspecific gene flow, including between nonsister species. Copyright © 2015, American Association for the Advancement of Science.
	PMID: 25431491 [PubMed - indexed for MEDLINE]
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2.	Nat Genet. 2014 Nov;46(11):1220-6. doi: 10.1038/ng.3117. Epub 2014 Oct 12. Genomic analyses provide insights into the history of tomato breeding. Lin T1, Zhu G2, Zhang J3, Xu X4, Yu Q5, Zheng Z2, Zhang Z2, Lun Y2, Li S2, Wang X2, Huang Z2, Li J2, Zhang C2, Wang T3, Zhang Y3, Wang A4, Zhang Y6, Lin K6, Li C7, Xiong G8, Xue Y9, Mazzucato A10, Causse M11, Fei Z12, Giovannoni JJ12, Chetelat RT13, Zamir D14, Städler T15, Li J4, Ye Z3, Du Y2, Huang S1. Abstract The histories of crop domestication and breeding are recorded in genomes. Although tomato is a model species for plant biology and breeding, the nature of human selection that altered its genome remains largely unknown. Here we report a comprehensive analysis of tomato evolution based on the genome sequences of 360 accessions. We provide evidence that domestication and improvement focused on two independent sets of quantitative trait loci (QTLs), resulting in modern tomato fruit ∼100 times larger than its ancestor. Furthermore, we discovered a major genomic signature for modern processing tomatoes, identified the causative variants that confer pink fruit color and precisely visualized the linkage drag associated with wild introgressions. This study outlines the accomplishments as well as the costs of historical selection and provides molecular insights toward further improvement.
	PMID: 25305757 [PubMed - indexed for MEDLINE]
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3.	Nat Genet. 2014 Nov;46(11):1173-86. doi: 10.1038/ng.3097. Epub 2014 Oct 5. Defining the role of common variation in the genomic and biological architecture of adult human height. Wood AR1, Esko T2, Yang J3, Vedantam S4, Pers TH5, Gustafsson S6, Chu AY7, Estrada K8, Luan J9, Kutalik Z10, Amin N11, Buchkovich ML12, Croteau-Chonka DC13, Day FR9, Duan Y14, Fall T15, Fehrmann R16, Ferreira T17, Jackson AU18, Karjalainen J16, Lo KS19, Locke AE18, Mägi R20, Mihailov E21, Porcu E22, Randall JC23, Scherag A24, Vinkhuyzen AA25, Westra HJ16, Winkler TW26, Workalemahu T27, Zhao JH9, Absher D28, Albrecht E29, Anderson D30, Baron J31, Beekman M32, Demirkan A33, Ehret GB34, Feenstra B35, Feitosa MF36, Fischer K37, Fraser RM38, Goel A39, Gong J40, Justice AE41, Kanoni S42, Kleber ME43, Kristiansson K44, Lim U45, Lotay V46, Lui JC31, Mangino M47, Mateo Leach I48, Medina-Gomez C49, Nalls MA50, Nyholt DR51, Palmer CD4, Pasko D1, Pechlivanis S52, Prokopenko I53, Ried JS29, Ripke S54, Shungin D55, Stancáková A56, Strawbridge RJ57, Sung YJ58, Tanaka T59, Teumer A60, Trompet S61, van der Laan SW62, van Setten J63, Van Vliet-Ostaptchouk JV64, Wang Z65, Yengo L66, Zhang W 67, Afzal U67, Arnlöv J68, Arscott GM69, Bandinelli S70, Barrett A71, Bellis C72, Bennett AJ71, Berne C73, Blüher M74, Bolton JL38, Böttcher Y75, Boyd HA35, Bruinenberg M76, Buckley BM77, Buyske S78, Caspersen IH79, Chines PS80, Clarke R81, Claudi-Boehm S82, Cooper M30, Daw EW36, De Jong PA83, Deelen J32, Delgado G84, Denny JC85, Dhonukshe-Rutten R86, Dimitriou M87, Doney AS88, Dörr M89, Eklund N90, Eury E66, Folkersen L57, Garcia ME91, Geller F35, Giedraitis V92, Go AS93, Grallert H94, Grammer TB84, Gräßler J95, Grönberg H96, de Groot LC86, Groves CJ71, Haessler J40, Hall P96, Haller T37, Hallmans G97, Hannemann A98, Hartman CA99, Hassinen M100, Hayward C101, Heard-Costa NL102, Helmer Q103, Hemani G3, Henders AK51, Hillege HL104, Hlatky MA105, Hoffmann W106, Hoffmann P107, Holmen O108, Houwing-Duistermaat JJ 109, Illig T110, Isaacs A111, James AL112, Jeff J46, Johansen B79, Johansson Å113, Jolley J114, Juliusdottir T17, Junttila J115, Kho AN116, Kinnunen L44, Klopp N110, Kocher T117, Kratzer W118, Lichtner P119, Lind L120, Lindström J44, Lobbens S66, Lorentzon M121, Lu Y122, Lyssenko V123, Magnusson PK96, Mahajan A17, Maillard M124, McArdle WL125, McKenzie CA126, McLachlan S38, McLaren PJ127, Menni C47, Merger S82, Milani L37, Moayyeri A47, Monda KL128, Morken MA80, Müller G129, Müller-Nurasyid M130, Musk AW131, Narisu N80, Nauck M132, Nolte IM133, Nöthen MM134, Oozageer L135, Pilz S136, Rayner NW137, Renstrom F138, Robertson NR139, Rose LM7, Roussel R140, Sanna S22, Scharnagl H141, Scholtens S133, Schumacher FR142, Schunkert H143, Scott RA9, Sehmi J67, Seufferlein T118, Shi J144, Silventoinen K145, Smit JH146, Smith AV147, Smolonska J148, Stanton AV149, Stirrups K150, Stott DJ151, Stringham HM18, Sundström J120, Swertz MA16, Syvänen AC152, Tayo BO153, Thorleifsson G154, Tyrer JP155, van Dijk S156, van Schoor NM157, van der Velde N158, van Heemst D159, van Oort FV160, Vermeulen SH161, Verweij N48, Vonk JM133, Waite LL28, Waldenberger M162, Wennauer R163, Wilkens LR45, Willenborg C 164, Wilsgaard T165, Wojczynski MK36, Wong A166, Wright AF101, Zhang Q36, Arveiler D167, Bakker SJ168, Beilby J169, Bergman RN170, Bergmann S171, Biffar R172, Blangero J72, Boomsma DI173, Bornstein SR95, Bovet P174, Brambilla P175, Brown MJ176, Campbell H38, Caulfield MJ177, Chakravarti A178, Collins R81, Collins FS80, Crawford DC179, Cupples LA180, Danesh J181, de Faire U182, den Ruijter HM183, Erbel R184, Erdmann J164, Eriksson JG185, Farrall M39, Ferrannini E186, Ferrières J187, Ford I188, Forouhi NG9, Forrester T126, Gansevoort RT168, Gejman PV189, Gieger C29, Golay A190, Gottesman O46, Gudnason V147, Gyllensten U113, Haas DW191, Hall AS192, Harris TB91, Hattersley AT193, Heath AC194, Hengstenberg C143, Hicks AA195, Hindorff LA196, Hingorani AD197, Hofman A198, Hovingh GK199, Humphries SE200, Hunt SC201, Hypponen E202, Jacobs KB203, Jarvelin MR204, Jousilahti P44, Jula AM44, Kaprio J205, Kastelein JJ199, Kayser M206, Kee F207, Keinanen-Kiukaanniemi SM208, Kiemeney LA209, Kooner JS210, Kooperberg C40, Koskinen S44, Kovacs P74, Kraja AT36, Kumari M211, Kuusisto J212, Lakka TA213, Langenberg C214, Le Marchand L45, Lehtimäki T215, Lupoli S216, Madden PA194, Männistö S44, Manunta P217, Marette A218, Matise TC219, McKnight B220, Meitinger T221, Moll FL222, Montgomery GW51, Morris AD88, Morris AP223, Murray JC224, Nelis M37, Ohlsson C121, Oldehinkel AJ99, Ong KK225, Ouwehand WH114, Pasterkamp G62, Peters A226, Pramstaller PP227, Price JF38, Qi L228, Raitakari OT229, Rankinen T230, Rao DC231, Rice TK232, Ritchie M233, Rudan I234, Salomaa V44, Samani NJ235, Saramies J236, Sarzynski MA230, Schwarz PE237, Sebert S238, Sever P239, Shuldiner AR240, Sinisalo J241, Steinthorsdottir V154, Stolk RP133, Tardif JC242, Tönjes A74 , Tremblay A243, Tremoli E244, Virtamo J44, Vohl MC245; Electronic Medical Records and Genomics (eMEMERGEGE) Consortium; MIGen Consortium; PAGEGE Consortium; LifeLines Cohort Study, Amouyel P246, Asselbergs FW247, Assimes TL105, Bochud M174, Boehm BO248, Boerwinkle E249, Bottinger EP46, Bouchard C230, Cauchi S66, Chambers JC250, Chanock SJ251, Cooper RS153, de Bakker PI252, Dedoussis G87, Ferrucci L59, Franks PW253, Froguel P254, Groop LC255, Haiman CA142, Hamsten A57, Hayes MG116, Hui J256, Hunter DJ257, Hveem K108, Jukema JW258, Kaplan RC259, Kivimaki M211, Kuh D166, Laakso M212, Liu Y260, Martin NG51, März W261, Melbye M262, Moebus S52, Munroe PB177, Njølstad I165, Oostra BA263, Palmer CN88, Pedersen NL96, Perola M264, Pérusse L265, Peters U40, Powell JE3, Power C266, Quertermous T105, Rauramaa R267, Reinmaa E37, Ridker PM268, Rivadeneira F49, Rotter JI269, Saaristo TE270, Saleheen D271, Schlessinger D272, Slagboom PE32, Snieder H133, Spector TD47, Strauch K273, Stumvoll M74, Tuomilehto J274, Uusitupa M275, van der Harst P276, Völzke H106, Walker M277, Wareham NJ9, Watkins H39, Wichmann HE278, Wilson JF38, Zanen P279, Deloukas P280, Heid IM281, Lindgren CM282, Mohlke KL12, Speliotes EK283, Thorsteinsdottir U284, Barroso I285, Fox CS286, North KE287, Strachan DP288, Beckmann JS289, Berndt SI251, Boehnke M18, Borecki IB36, McCarthy MI290, Metspalu A21, Stefansson K284, Uitterlinden AG49, van Duijn CM291, Franke L16 , Willer CJ292, Price AL293, Lettre G242, Loos RJ294, Weedon MN1, Ingelsson E295, O'Connell JR296, Abecasis GR18, Chasman DI268, Goddard ME297, Visscher PM3, Hirschhorn JN298, Frayling TM1. Collaborators: McCarty CA, Starren J, Peissig P, Berg R, Rasmussen L, Linneman J, Miller A, Choudary V, Chen L, Waudby C, Kitchner T, Reeser J, Fost N, Ritchie M, Wilke RA, Chisholm RL, Avila PC, Greenland P, Hayes M, Kho A, Kibbe WA, Lemke AA, Lowe WL, Smith ME, Wolf WA, Pacheco JA, Thompson WK, Humowiecki J, Law M, Chute C, Kullo I, Koenig B, de Andrade M, Bielinski S, Pathak J, Savova G, Wu J, Henriksen J, Ding K, Hart L, Palbicki J, Larson EB, Newton K, Ludman E, Spangler L, Hart G, Carrell D, Jarvik G, Crane P, Burke W, Fullerton SM, Trinidad SB, Carlson C, Hutchinson F, McDavid A, Roden DM, Clayton E, Haines JL, Masys DR, Churchill LR, Cornfield D, Crawford D, Darbar D, Denny JC, Malin BA, Ritchie MD, Schildcrout JS, Xu H, Ramirez AH, Basford M, Pulley J, Alizadeh B, de Boer RA, Boezen HM, Bruinenberg M, Franke L, van der Harst P, Hillege HL, van der Klauw MM, Navis G, Ormel J, Postma DS, Rosmalen JG, Slaets JP, Snieder H, Stolk RP, Wolffenbuttel BH, Wijmenga C, Kathiresan S, Voight BF, Purcell S, Musunuru K, Ardissino D, Mannucci PM, Anand S, Engert JC, Samani NJ, Schunkert H, Erdmann J, Reilly MP, Rader DJ, Morgan T, Spertus JA, Stoll M, Girelli D, McKeown PP, Patterson CC, Siscovick DS, O'Donnell CJ, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Melander O, Altshuler D, Ardissino D, Merlini PA, Berzuini C, Bernardinelli L, Peyvandi F, Tubaro M, Celli P, Ferrario M, Fetiveau R, Marziliano N, Casari G, Galli M, Ribichini F, Rossi M, Bernardi F, Zonzin P, Piazza A, Mannucci PM, Schwartz SM, Siscovick DS, Yee J, Friedlander Y, Elosua R, Marrugat J, Lucas G, Subirana I, Sala J, Ramos R, Kathiresan S, Meigs JB, Williams G, Nathan DM, MacRae CA, O'Donnell CJ, Salomaa V, Havulinna AS, Peltonen L, Melander O, Berglund G, Voight B, Kathiresan S, Hirschhorn JN, Asselta R, Duga S, Spreafico M, Musunuru K, Daly MJ, Purcell S, Voight BF, Purcell S, Nemesh J, Korn JM, McCarroll SA, Schwartz SM, Yee J, Kathiresan S, Lucas G, Subirana I, Elosua R, Surti A, Guiducci C, Gianniny L, Mirel D, Parkin M, Burtt N, Gabriel SB, Samani NJ, Thompson JR, Braund PS, Wright BJ, Balmforth AJ, Ball SG, Hall AS, Schunkert I, Erdmann J, Linsel-Nitschke P, Lieb W, Ziegler A, König IR, Hengstenberg C, Fischer M, Stark K, Grosshennig A, Preuss M, Wichmann HE, Schreiber S, Schunkert H, Samani NJ, Erdmann J, Ouwehand W, Hengstenberg C, Deloukas P, Scholz M, Cambien F, Goodall A, Reilly MP, Li M, Chen Z, Wilensky R, Matthai W, Qasim A, Hakonarson HH, Devaney J, Burnett MS, Pichard AD, Kent KM, Satler L, Lindsay JM, Waksman R, Knouff CW, Waterworth DM, Walker MC, Mooser V, Epstein SE, Rader DJ, Scheffold T, Berger K, Stoll M, Huge A, Girelli D, Martinelli N, Olivieri O, Corrocher R, Morgan T, Spertus JA, McKeown PP, Patterson CC, Schunkert H, Erdmann J, Linsel-Nitschke P, Lieb W, Ziegler A, König I, Hengstenberg C, Fischer M, Stark K, Grosshennig A, Preuss M, Wichmann HE, Schreiber S, Hólm H, Thorleifsson G, Thorsteinsdottir U, Stefansson K, Engert JC, Do R, Xie C, Anand S, Kathiresan S, Ardissino D, Mannucci PM, Siscovick D, O'Donnell CJ, Samani NJ, Melander O, Elosua R, Peltonen L, Salomaa V, Schwartz SM, Altshuler D, Matise T, Buyske S, Higashio J, Williams R, Nato A, Ambite JL, Deelman E, Manolio T, Hindorff L, North KE, Heiss G, Taylor K, Franceschini N, Avery C, Graff M, Lin D, Quibrera M, Cochran B, Kao L, Umans J, Cole S, MacCluer J, Person S, Pankow J, Gross M, Boerwinkle E, Fornage M, Durda P, Jenny N, Patsy B, Arnold A, Buzkova P, Crawford D, Haines J, Murdock D, Glenn K, Brown-Gentry K, Thornton-Wells T, Dumitrescu L, Jeff J, Bush WS, Mitchell SL, Goodloe R, Wilson S, Boston J, Malinowski J, Restrepo N, Oetjens M, Fowke J, Zheng W, Spencer K, Ritchie M, Pendergrass S, Le Marchand L, Wilkens L, Park L, Tiirikainen M, Kolonel L, Lim U, Cheng I, Wang H, Shohet R, Haiman C, Stram D, Henderson B, Monroe K, Schumacher F, Kooperberg C, Peters U, Anderson G, Carlson C, Prentice R, LaCroix A, Wu C, Carty C, Gong J, Rosse S, Young A, Haessler J, Kocarnik J, Lin Y, Jackson R, Duggan D, Kuller L. Abstract Using genome-wide data from 253,288 individuals, we identified 697 variants at genome-wide significance that together explained one-fifth of the heritability for adult height. By testing different numbers of variants in independent studies, we show that the most strongly associated ∼2,000, ∼3,700 and ∼9,500 SNPs explained ∼21%, ∼24% and ∼29% of phenotypic variance. Furthermore, all common variants together captured 60% of heritability. The 697 variants clustered in 423 loci were enriched for genes, pathways and tissue types known to be involved in growth and together implicated genes and pathways not highlighted in earlier efforts, such as signaling by fibroblast growth factors, WNT/β-catenin and chondroitin sulfate-related genes. We identified several genes and pathways not previously connected with human skeletal growth, including mTOR, osteoglycin and binding of hyaluronic acid. Our results indicate a genetic architecture for human height that is characterized by a very large but finite number (thousands) of causal variants. PMCID: PMC4250049 [Available on 2015/5/1]
	PMID: 25282103 [PubMed - indexed for MEDLINE]
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4.	Nat Genet. 2014 Nov;46(11):1205-11. doi: 10.1038/ng.3114. Epub 2014 Oct 5. Recombination drives genome evolution in outbreak-related Legionella pneumophila isolates. Sánchez-Busó L1, Comas I1, Jorques G2, González-Candelas F1. Abstract Legionella pneumophila is a strictly environmental pathogen and the etiological agent of legionellosis. It is known that non-vertical processes have a major role in the short-term evolution of pathogens, but little is known about the relevance of these and other processes in environmental bacteria. We report the whole-genome sequencing of 69 L. pneumophila strains linked to recurrent outbreaks in a single location (Alcoy, Spain) over 11 years. We found some examples where the genome sequences of isolates of the same sequence type and outbreak did not cluster together and were more closely related to sequences from different outbreaks. Our analyses identify 16 recombination events responsible for almost 98% of the SNPs detected in the core genome and an apparent acceleration in the evolutionary rate. These results have profound implications for the understanding of microbial populations and for public health interventions in Legionella outbreak investigations.
	PMID: 25282102 [PubMed - indexed for MEDLINE]
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5.	Nat Genet. 2014 Nov;46(11):1160-5. doi: 10.1038/ng.3101. Epub 2014 Sep 28. Genome-wide analysis of noncoding regulatory mutations in cancer. Weinhold N1, Jacobsen A2, Schultz N1, Sander C1, Lee W3. Comment in Second call for pan-cancer analysis. [Nat Genet. 2014] Second call for pan-cancer analysis.[No authors listed]Nat Genet. 2014 Dec; 46(12):1251. Abstract Cancer primarily develops because of somatic alterations in the genome. Advances in sequencing have enabled large-scale sequencing studies across many tumor types, emphasizing the discovery of alterations in protein-coding genes. However, the protein-coding exome comprises less than 2% of the human genome. Here we analyze the complete genome sequences of 863 human tumors from The Cancer Genome Atlas and other sources to systematically identify noncoding regions that are recurrently mutated in cancer. We use new frequency- and sequence-based approaches to comprehensively scan the genome for noncoding mutations with potential regulatory impact. These methods identify recurrent mutations in regulatory elements upstream of PLEKHS1, WDR74 and SDHD, as well as previously identified mutations in the TERT promoter. SDHD promoter mutations are frequent in melanoma and are associated with reduced gene expression and poor prognosis. The non-protein-coding cancer genome remains widely unexplored, and our findings represent a step toward targeting the entire genome for clinical purposes. PMCID: PMC4217527 [Available on 2015/5/1]
	PMID: 25261935 [PubMed - indexed for MEDLINE]
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6.	Nat Genet. 2014 Nov;46(11):1227-32. doi: 10.1038/ng.3095. Epub 2014 Sep 21. PRC2 is recurrently inactivated through EED or SUZ12 loss in malignant peripheral nerve sheath tumors. Lee W1, Teckie S2, Wiesner T3, Ran L3, Prieto Granada CN4, Lin M5, Zhu S3, Cao Z3, Liang Y3, Sboner A6, Tap WD7, Fletcher JA8, Huberman KH9, Qin LX10, Viale A9, Singer S11, Zheng D12, Berger MF13, Chen Y14, Antonescu CR4, Chi P14. Abstract Malignant peripheral nerve sheath tumors (MPNSTs) represent a group of highly aggressive soft-tissue sarcomas that may occur sporadically, in association with neurofibromatosis type I (NF1 associated) or after radiotherapy. Using comprehensive genomic approaches, we identified loss-of-function somatic alterations of the Polycomb repressive complex 2 (PRC2) components (EED or SUZ12) in 92% of sporadic, 70% of NF1-associated and 90% of radiotherapy-associated MPNSTs. MPNSTs with PRC2 loss showed complete loss of trimethylation at lysine 27 of histone H3 (H3K27me3) and aberrant transcriptional activation of multiple PRC2-repressed homeobox master regulators and their regulated developmental pathways. Introduction of the lost PRC2 component in a PRC2-deficient MPNST cell line restored H3K27me3 levels and decreased cell growth. Additionally, we identified frequent somatic alterations of CDKN2A (81% of all MPNSTs) and NF1 (72% of non-NF1-associated MPNSTs), both of which significantly co-occur with PRC2 alterations. The highly recurrent and specific inactivation of PRC2 components, NF1 and CDKN2A highlights their critical and potentially cooperative roles in MPNST pathogenesis. PMCID: PMC4249650 [Available on 2015/5/1]
	PMID: 25240281 [PubMed - indexed for MEDLINE]
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