ALBERT

Description: DNA sequence variation has been associated with quantitative changes in molecular phenotypes such as gene expression, but its impact on chromatin states is poorly characterized. To understand the interplay between chromatin and genetic control of gene regulation, we quantified allelic variability in transcription factor binding, histone modifications, and gene expression within humans. We found abundant allelic specificity in chromatin and extensive local, short-range, and long-range allelic coordination among the studied molecular phenotypes. We observed genetic influence on most of these phenotypes, with histone modifications exhibiting strong context-dependent behavior. Our results implicate transcription factors as primary mediators of sequence-specific regulation of gene expression programs, with histone modifications frequently reflecting the primary regulatory event.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kilpinen, Helena -- Waszak, Sebastian M -- Gschwind, Andreas R -- Raghav, Sunil K -- Witwicki, Robert M -- Orioli, Andrea -- Migliavacca, Eugenia -- Wiederkehr, Michael -- Gutierrez-Arcelus, Maria -- Panousis, Nikolaos I -- Yurovsky, Alisa -- Lappalainen, Tuuli -- Romano-Palumbo, Luciana -- Planchon, Alexandra -- Bielser, Deborah -- Bryois, Julien -- Padioleau, Ismael -- Udin, Gilles -- Thurnheer, Sarah -- Hacker, David -- Core, Leighton J -- Lis, John T -- Hernandez, Nouria -- Reymond, Alexandre -- Deplancke, Bart -- Dermitzakis, Emmanouil T -- GM25232/GM/NIGMS NIH HHS/ -- HG004845/HG/NHGRI NIH HHS/ -- R01 HG004845/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2013 Nov 8;342(6159):744-7. doi: 10.1126/science.1242463. Epub 2013 Oct 17.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24136355" target="_blank"〉PubMed〈/a〉

Description: Gorillas are humans' closest living relatives after chimpanzees, and are of comparable importance for the study of human origins and evolution. Here we present the assembly and analysis of a genome sequence for the western lowland gorilla, and compare the whole genomes of all extant great ape genera. We propose a synthesis of genetic and fossil evidence consistent with placing the human-chimpanzee and human-chimpanzee-gorilla speciation events at approximately 6 and 10 million years ago. In 30% of the genome, gorilla is closer to human or chimpanzee than the latter are to each other; this is rarer around coding genes, indicating pervasive selection throughout great ape evolution, and has functional consequences in gene expression. A comparison of protein coding genes reveals approximately 500 genes showing accelerated evolution on each of the gorilla, human and chimpanzee lineages, and evidence for parallel acceleration, particularly of genes involved in hearing. We also compare the western and eastern gorilla species, estimating an average sequence divergence time 1.75 million years ago, but with evidence for more recent genetic exchange and a population bottleneck in the eastern species. The use of the genome sequence in these and future analyses will promote a deeper understanding of great ape biology and evolution.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303130/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3303130/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Scally, Aylwyn -- Dutheil, Julien Y -- Hillier, LaDeana W -- Jordan, Gregory E -- Goodhead, Ian -- Herrero, Javier -- Hobolth, Asger -- Lappalainen, Tuuli -- Mailund, Thomas -- Marques-Bonet, Tomas -- McCarthy, Shane -- Montgomery, Stephen H -- Schwalie, Petra C -- Tang, Y Amy -- Ward, Michelle C -- Xue, Yali -- Yngvadottir, Bryndis -- Alkan, Can -- Andersen, Lars N -- Ayub, Qasim -- Ball, Edward V -- Beal, Kathryn -- Bradley, Brenda J -- Chen, Yuan -- Clee, Chris M -- Fitzgerald, Stephen -- Graves, Tina A -- Gu, Yong -- Heath, Paul -- Heger, Andreas -- Karakoc, Emre -- Kolb-Kokocinski, Anja -- Laird, Gavin K -- Lunter, Gerton -- Meader, Stephen -- Mort, Matthew -- Mullikin, James C -- Munch, Kasper -- O'Connor, Timothy D -- Phillips, Andrew D -- Prado-Martinez, Javier -- Rogers, Anthony S -- Sajjadian, Saba -- Schmidt, Dominic -- Shaw, Katy -- Simpson, Jared T -- Stenson, Peter D -- Turner, Daniel J -- Vigilant, Linda -- Vilella, Albert J -- Whitener, Weldon -- Zhu, Baoli -- Cooper, David N -- de Jong, Pieter -- Dermitzakis, Emmanouil T -- Eichler, Evan E -- Flicek, Paul -- Goldman, Nick -- Mundy, Nicholas I -- Ning, Zemin -- Odom, Duncan T -- Ponting, Chris P -- Quail, Michael A -- Ryder, Oliver A -- Searle, Stephen M -- Warren, Wesley C -- Wilson, Richard K -- Schierup, Mikkel H -- Rogers, Jane -- Tyler-Smith, Chris -- Durbin, Richard -- 062023/Wellcome Trust/United Kingdom -- 075491/Z/04/Wellcome Trust/United Kingdom -- 077009/Wellcome Trust/United Kingdom -- 077192/Wellcome Trust/United Kingdom -- 077198/Wellcome Trust/United Kingdom -- 089066/Wellcome Trust/United Kingdom -- 090532/Wellcome Trust/United Kingdom -- 095908/Wellcome Trust/United Kingdom -- 15603/Cancer Research UK/United Kingdom -- 202218/European Research Council/International -- A15603/Cancer Research UK/United Kingdom -- G0501331/Medical Research Council/United Kingdom -- G0701805/Medical Research Council/United Kingdom -- HG002385/HG/NHGRI NIH HHS/ -- U54 HG003079/HG/NHGRI NIH HHS/ -- WT062023/Wellcome Trust/United Kingdom -- WT077009/Wellcome Trust/United Kingdom -- WT077192/Wellcome Trust/United Kingdom -- WT077198/Wellcome Trust/United Kingdom -- WT089066/Wellcome Trust/United Kingdom -- Medical Research Council/United Kingdom -- Biotechnology and Biological Sciences Research Council/United Kingdom -- Howard Hughes Medical Institute/ -- Intramural NIH HHS/ -- England -- Nature. 2012 Mar 7;483(7388):169-75. doi: 10.1038/nature10842.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Sanger Institute, Wellcome Trust Genome Campus, Hinxton CB10 1SA, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/22398555" target="_blank"〉PubMed〈/a〉

Description: Genome sequencing projects are discovering millions of genetic variants in humans, and interpretation of their functional effects is essential for understanding the genetic basis of variation in human traits. Here we report sequencing and deep analysis of messenger RNA and microRNA from lymphoblastoid cell lines of 462 individuals from the 1000 Genomes Project--the first uniformly processed high-throughput RNA-sequencing data from multiple human populations with high-quality genome sequences. We discover extremely widespread genetic variation affecting the regulation of most genes, with transcript structure and expression level variation being equally common but genetically largely independent. Our characterization of causal regulatory variation sheds light on the cellular mechanisms of regulatory and loss-of-function variation, and allows us to infer putative causal variants for dozens of disease-associated loci. Altogether, this study provides a deep understanding of the cellular mechanisms of transcriptome variation and of the landscape of functional variants in the human genome.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918453/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3918453/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Lappalainen, Tuuli -- Sammeth, Michael -- Friedlander, Marc R -- 't Hoen, Peter A C -- Monlong, Jean -- Rivas, Manuel A -- Gonzalez-Porta, Mar -- Kurbatova, Natalja -- Griebel, Thasso -- Ferreira, Pedro G -- Barann, Matthias -- Wieland, Thomas -- Greger, Liliana -- van Iterson, Maarten -- Almlof, Jonas -- Ribeca, Paolo -- Pulyakhina, Irina -- Esser, Daniela -- Giger, Thomas -- Tikhonov, Andrew -- Sultan, Marc -- Bertier, Gabrielle -- MacArthur, Daniel G -- Lek, Monkol -- Lizano, Esther -- Buermans, Henk P J -- Padioleau, Ismael -- Schwarzmayr, Thomas -- Karlberg, Olof -- Ongen, Halit -- Kilpinen, Helena -- Beltran, Sergi -- Gut, Marta -- Kahlem, Katja -- Amstislavskiy, Vyacheslav -- Stegle, Oliver -- Pirinen, Matti -- Montgomery, Stephen B -- Donnelly, Peter -- McCarthy, Mark I -- Flicek, Paul -- Strom, Tim M -- Geuvadis Consortium -- Lehrach, Hans -- Schreiber, Stefan -- Sudbrak, Ralf -- Carracedo, Angel -- Antonarakis, Stylianos E -- Hasler, Robert -- Syvanen, Ann-Christine -- van Ommen, Gert-Jan -- Brazma, Alvis -- Meitinger, Thomas -- Rosenstiel, Philip -- Guigo, Roderic -- Gut, Ivo G -- Estivill, Xavier -- Dermitzakis, Emmanouil T -- 075491/Z/04/B/Wellcome Trust/United Kingdom -- 076113/Wellcome Trust/United Kingdom -- 081917/Wellcome Trust/United Kingdom -- 083270/Wellcome Trust/United Kingdom -- 085475/B/08/Z/Wellcome Trust/United Kingdom -- 085475/Z/08/Z/Wellcome Trust/United Kingdom -- 085532/Wellcome Trust/United Kingdom -- 090367/Wellcome Trust/United Kingdom -- 090532/Wellcome Trust/United Kingdom -- 090532/Z/09/Z/Wellcome Trust/United Kingdom -- 095552/Wellcome Trust/United Kingdom -- 095552/Z/11/Z/Wellcome Trust/United Kingdom -- 098381/Wellcome Trust/United Kingdom -- G0601261/Medical Research Council/United Kingdom -- MH090941/MH/NIMH NIH HHS/ -- R01 GM104371/GM/NIGMS NIH HHS/ -- R01 MH090941/MH/NIMH NIH HHS/ -- WT085532/Wellcome Trust/United Kingdom -- England -- Nature. 2013 Sep 26;501(7468):506-11. doi: 10.1038/nature12531. Epub 2013 Sep 15.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Department of Genetic Medicine and Development, University of Geneva Medical School, 1211 Geneva, Switzerland. tuuli.e.lappalainen@gmail.com〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24037378" target="_blank"〉PubMed〈/a〉

Description: Interpreting variants, especially noncoding ones, in the increasing number of personal genomes is challenging. We used patterns of polymorphisms in functionally annotated regions in 1092 humans to identify deleterious variants; then we experimentally validated candidates. We analyzed both coding and noncoding regions, with the former corroborating the latter. We found regions particularly sensitive to mutations ("ultrasensitive") and variants that are disruptive because of mechanistic effects on transcription-factor binding (that is, "motif-breakers"). We also found variants in regions with higher network centrality tend to be deleterious. Insertions and deletions followed a similar pattern to single-nucleotide variants, with some notable exceptions (e.g., certain deletions and enhancers). On the basis of these patterns, we developed a computational tool (FunSeq), whose application to ~90 cancer genomes reveals nearly a hundred candidate noncoding drivers.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947637/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3947637/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Khurana, Ekta -- Fu, Yao -- Colonna, Vincenza -- Mu, Xinmeng Jasmine -- Kang, Hyun Min -- Lappalainen, Tuuli -- Sboner, Andrea -- Lochovsky, Lucas -- Chen, Jieming -- Harmanci, Arif -- Das, Jishnu -- Abyzov, Alexej -- Balasubramanian, Suganthi -- Beal, Kathryn -- Chakravarty, Dimple -- Challis, Daniel -- Chen, Yuan -- Clarke, Declan -- Clarke, Laura -- Cunningham, Fiona -- Evani, Uday S -- Flicek, Paul -- Fragoza, Robert -- Garrison, Erik -- Gibbs, Richard -- Gumus, Zeynep H -- Herrero, Javier -- Kitabayashi, Naoki -- Kong, Yong -- Lage, Kasper -- Liluashvili, Vaja -- Lipkin, Steven M -- MacArthur, Daniel G -- Marth, Gabor -- Muzny, Donna -- Pers, Tune H -- Ritchie, Graham R S -- Rosenfeld, Jeffrey A -- Sisu, Cristina -- Wei, Xiaomu -- Wilson, Michael -- Xue, Yali -- Yu, Fuli -- 1000 Genomes Project Consortium -- Dermitzakis, Emmanouil T -- Yu, Haiyuan -- Rubin, Mark A -- Tyler-Smith, Chris -- Gerstein, Mark -- 085532/Wellcome Trust/United Kingdom -- 090532/Wellcome Trust/United Kingdom -- 095908/Wellcome Trust/United Kingdom -- 098051/Wellcome Trust/United Kingdom -- CA167824/CA/NCI NIH HHS/ -- G12 MD007579/MD/NIMHD NIH HHS/ -- G12 RR003050/RR/NCRR NIH HHS/ -- GM104424/GM/NIGMS NIH HHS/ -- HG005718/HG/NHGRI NIH HHS/ -- HG007000/HG/NHGRI NIH HHS/ -- P20 MD006899/MD/NIMHD NIH HHS/ -- R01 CA166661/CA/NCI NIH HHS/ -- R01 HG002898/HG/NHGRI NIH HHS/ -- R01CA152057/CA/NCI NIH HHS/ -- R01HG4719/HG/NHGRI NIH HHS/ -- U01 CA111275/CA/NCI NIH HHS/ -- U01 HG005718/HG/NHGRI NIH HHS/ -- U01HG6513/HG/NHGRI NIH HHS/ -- U41 HG007000/HG/NHGRI NIH HHS/ -- U54 HG003079/HG/NHGRI NIH HHS/ -- UL1 TR000457/TR/NCATS NIH HHS/ -- WT085532/Wellcome Trust/United Kingdom -- WT095908/Wellcome Trust/United Kingdom -- New York, N.Y. -- Science. 2013 Oct 4;342(6154):1235587. doi: 10.1126/science.1235587.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Program in Computational Biology and Bioinformatics, Yale University, New Haven, CT 06520, USA.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/24092746" target="_blank"〉PubMed〈/a〉

Description: Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes-which is most clearly seen in blood-though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547472/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547472/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Mele, Marta -- Ferreira, Pedro G -- Reverter, Ferran -- DeLuca, David S -- Monlong, Jean -- Sammeth, Michael -- Young, Taylor R -- Goldmann, Jakob M -- Pervouchine, Dmitri D -- Sullivan, Timothy J -- Johnson, Rory -- Segre, Ayellet V -- Djebali, Sarah -- Niarchou, Anastasia -- GTEx Consortium -- Wright, Fred A -- Lappalainen, Tuuli -- Calvo, Miquel -- Getz, Gad -- Dermitzakis, Emmanouil T -- Ardlie, Kristin G -- Guigo, Roderic -- HHSN261200800001E/PHS HHS/ -- HHSN268201000029C/HL/NHLBI NIH HHS/ -- HHSN268201000029C/PHS HHS/ -- R01 DA006227-17/DA/NIDA NIH HHS/ -- R01 MH090936/MH/NIMH NIH HHS/ -- R01 MH090941/MH/NIMH NIH HHS/ -- New York, N.Y. -- Science. 2015 May 8;348(6235):660-5. doi: 10.1126/science.aaa0355.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Harvard Department of stem cell and regenerative biology, Harvard University, Cambridge, MA, USA. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. McGill University, Montreal, Canada. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. National Institute for Scientific Computing (LNCC), Petropolis, Rio de Janeiro, Brazil. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Radboud University, Nijmegen, Netherlands. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskie Gory 1-73, 119992 Moscow, Russia. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. ; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Harvard Department of stem cell and regenerative biology, Harvard University, Cambridge, MA, USA. Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Broad Institute of MIT and Harvard, Cambridge, MA, USA. McGill University, Montreal, Canada. National Institute for Scientific Computing (LNCC), Petropolis, Rio de Janeiro, Brazil. Radboud University, Nijmegen, Netherlands. Faculty of Bioengineering and Bioinformatics, Moscow State University, Leninskie Gory 1-73, 119992 Moscow, Russia. North Carolina State University, Raleigh, NC, USA. New York Genome Center, New York, NY, USA. Department of Systems Biology, Columbia University, New York, NY, USA. Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA. Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain. Joint CRG-Barcelona Super Computing Center (BSC)-Institut de Recerca Biomedica (IRB) Program in Computational Biology, Barcelona, Catalonia, Spain. ; North Carolina State University, Raleigh, NC, USA. ; Department of Genetic Medicine and Development, University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. New York Genome Center, New York, NY, USA. Department of Systems Biology, Columbia University, New York, NY, USA. ; Facultat de Biologia, Universitat de Barcelona (UB), Barcelona, Catalonia, Spain. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA 02114, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. kardlie@broadinstitute.org roderic.guigo@crg.cat. ; Center for Genomic Regulation (CRG), Barcelona, Catalonia, Spain. Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. Institut Hospital del Mar d'Investigacions Mediques (IMIM), Barcelona, Catalonia, Spain. Joint CRG-Barcelona Super Computing Center (BSC)-Institut de Recerca Biomedica (IRB) Program in Computational Biology, Barcelona, Catalonia, Spain. kardlie@broadinstitute.org roderic.guigo@crg.cat.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25954002" target="_blank"〉PubMed〈/a〉

Description: Accurate prediction of the functional effect of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants, a class of variants expected to have profound effects on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitated tissue-specific and positional effects on nonsense-mediated transcript decay and present an improved predictive model for this decay. We directly measured the effect of variants both proximal and distal to splice junctions. Furthermore, we found that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.〈br /〉〈br /〉〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537935/" target="_blank"〉〈img src="https://static.pubmed.gov/portal/portal3rc.fcgi/4089621/img/3977009" border="0"〉〈/a〉   〈a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4537935/" target="_blank"〉This paper as free author manuscript - peer-reviewed and accepted for publication〈/a〉〈br /〉〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Rivas, Manuel A -- Pirinen, Matti -- Conrad, Donald F -- Lek, Monkol -- Tsang, Emily K -- Karczewski, Konrad J -- Maller, Julian B -- Kukurba, Kimberly R -- DeLuca, David S -- Fromer, Menachem -- Ferreira, Pedro G -- Smith, Kevin S -- Zhang, Rui -- Zhao, Fengmei -- Banks, Eric -- Poplin, Ryan -- Ruderfer, Douglas M -- Purcell, Shaun M -- Tukiainen, Taru -- Minikel, Eric V -- Stenson, Peter D -- Cooper, David N -- Huang, Katharine H -- Sullivan, Timothy J -- Nedzel, Jared -- GTEx Consortium -- Geuvadis Consortium -- Bustamante, Carlos D -- Li, Jin Billy -- Daly, Mark J -- Guigo, Roderic -- Donnelly, Peter -- Ardlie, Kristin -- Sammeth, Michael -- Dermitzakis, Emmanouil T -- McCarthy, Mark I -- Montgomery, Stephen B -- Lappalainen, Tuuli -- MacArthur, Daniel G -- 090532/Wellcome Trust/United Kingdom -- 090532/Z/09/Z/Wellcome Trust/United Kingdom -- 095552/Wellcome Trust/United Kingdom -- 095552/Z/11/Z/Wellcome Trust/United Kingdom -- 098381/Wellcome Trust/United Kingdom -- DA006227/DA/NIDA NIH HHS/ -- HHSN261200800001E/CA/NCI NIH HHS/ -- HHSN261200800001E/PHS HHS/ -- HHSN268201000029C/HL/NHLBI NIH HHS/ -- HHSN268201000029C/PHS HHS/ -- MH090936/MH/NIMH NIH HHS/ -- MH090937/MH/NIMH NIH HHS/ -- MH090941/MH/NIMH NIH HHS/ -- MH090948/MH/NIMH NIH HHS/ -- MH090951/MH/NIMH NIH HHS/ -- P30 DK020595/DK/NIDDK NIH HHS/ -- R01 GM104371/GM/NIGMS NIH HHS/ -- R01 MH090941/MH/NIMH NIH HHS/ -- R01 MH101810/MH/NIMH NIH HHS/ -- R01 MH101814/MH/NIMH NIH HHS/ -- R01 MH101820/MH/NIMH NIH HHS/ -- R01GM104371/GM/NIGMS NIH HHS/ -- R01MH090941/MH/NIMH NIH HHS/ -- R01MH101810/MH/NIMH NIH HHS/ -- R01MH101814/MH/NIMH NIH HHS/ -- U01 HG007593/HG/NHGRI NIH HHS/ -- U01HG007593/HG/NHGRI NIH HHS/ -- New York, N.Y. -- Science. 2015 May 8;348(6235):666-9. doi: 10.1126/science.1261877.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Wellcome Trust Centre for Human Genetics, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. rivas@well.ox.ac.uk tlappalainen@nygenome.org macarthur@atgu.mgh.harvard.edu. ; FInstitute for Molecular Medicine Finland (FIMM), University of Helsinki, Helsinki, Finland. ; Washington University in St. Louis, St. Louis, MO, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. ; Department of Genetics, Stanford University, Stanford, CA, USA. Department of Pathology, Stanford University, Stanford, CA, USA. Biomedical Informatics Program, Stanford University, Stanford, CA, USA. ; Department of Genetics, Stanford University, Stanford, CA, USA. Department of Pathology, Stanford University, Stanford, CA, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. Department of Psychiatry, Mt. Sinai Hospital, NY, USA. ; Department of Genetic Medicine and Development,University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. ; Department of Genetics, Stanford University, Stanford, CA, USA. ; Department of Psychiatry, Mt. Sinai Hospital, NY, USA. Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY, USA. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. Department of Psychiatry, Mt. Sinai Hospital, NY, USA. Division of Psychiatric Genomics, Department of Psychiatry, Icahn School of Medicine at Mount Sinai, NY, USA. ; Institute of Medical Genetics, School of Medicine, Cardiff University, Heath Park, Cardiff, UK. ; Center for Genomic Regulation (CRG), Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. ; Wellcome Trust Centre for Human Genetics, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. Department of Statistics, University of Oxford, Oxford, UK. ; Center for Genomic Regulation (CRG), Universitat Pompeu Fabra (UPF), Barcelona, Catalonia, Spain. National Institute for Scientific Computing (LNCC), Petropolis, Rio de Janeiro, Brazil. ; Wellcome Trust Centre for Human Genetics, Nuffield Department of Clinical Medicine, University of Oxford, Oxford, UK. Oxford Center for Diabetes Endocrinology and Metabolism, University of Oxford, Oxford, UK. ; Department of Genetics, Stanford University, Stanford, CA, USA. Department of Genetic Medicine and Development,University of Geneva, Geneva, Switzerland. Institute for Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. Swiss Institute of Bioinformatics, Geneva, Switzerland. New York Genome Center, New York, NY, USA. Department of Systems Biology, Columbia University, New York, NY, USA. rivas@well.ox.ac.uk tlappalainen@nygenome.org macarthur@atgu.mgh.harvard.edu. ; Broad Institute of MIT and Harvard, Cambridge, MA, USA. Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. Department of Medicine, Harvard Medical School, Boston, MA, USA. rivas@well.ox.ac.uk tlappalainen@nygenome.org macarthur@atgu.mgh.harvard.edu.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25954003" target="_blank"〉PubMed〈/a〉

Description: 〈p〉Transcriptome data can facilitate the interpretation of the effects of rare genetic variants. Here, we introduce ANEVA (analysis of expression variation) to quantify genetic variation in gene dosage from allelic expression (AE) data in a population. Application of ANEVA to the Genotype-Tissues Expression (GTEx) data showed that this variance estimate is robust and correlated with selective constraint in a gene. Using these variance estimates in a dosage outlier test (ANEVA-DOT) applied to AE data from 70 Mendelian muscular disease patients showed accuracy in detecting genes with pathogenic variants in previously resolved cases and led to one confirmed and several potential new diagnoses. Using our reference estimates from GTEx data, ANEVA-DOT can be incorporated in rare disease diagnostic pipelines to use RNA-sequencing data more effectively.〈/p〉

Description: Motivation : High-throughput sequencing technologies enable the genome-wide analysis of the impact of genetic variation on molecular phenotypes at unprecedented resolution. However, although powerful, these technologies can also introduce unexpected artifacts. Results : We investigated the impact of library amplification bias on the identification of allele-specific (AS) molecular events from high-throughput sequencing data derived from chromatin immunoprecipitation assays (ChIP-seq). Putative AS DNA binding activity for RNA polymerase II was determined using ChIP-seq data derived from lymphoblastoid cell lines of two parent–daughter trios. We found that, at high-sequencing depth, many significant AS binding sites suffered from an amplification bias, as evidenced by a larger number of clonal reads representing one of the two alleles. To alleviate this bias, we devised an amplification bias detection strategy, which filters out sites with low read complexity and sites featuring a significant excess of clonal reads. This method will be useful for AS analyses involving ChIP-seq and other functional sequencing assays. Availability : The R package absfilter for library clonality simulations and detection of amplification-biased sites is available from http://updepla1srv1.epfl.ch/waszaks/absfilter Contact : sebastian.waszak@epfl.ch or bart.deplancke@epfl.ch Supplementary information: Supplementary data are available at Bioinformatics online.