Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics
Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human...
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| Published in: | Nature genetics Vol. 53; no. 3; pp. 313 - 321 |
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| Main Authors: | , , , , , , , , , , , , , , , , , , , , , , , |
| Format: | Journal Article |
| Language: | English |
| Published: |
New York
Nature Publishing Group US
01.03.2021
Nature Publishing Group |
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| ISSN: | 1061-4036, 1546-1718, 1546-1718 |
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| Abstract | Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.
Integrative data analysis of 1,367 human iPSC lines maps common and rare regulatory variants that colocalize with loci associated with human traits and diseases. |
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| AbstractList | Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases.Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases. Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases. Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of novel colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases. Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases. Integrative data analysis of 1,367 human iPSC lines maps common and rare regulatory variants that colocalize with loci associated with human traits and diseases. Induced pluripotent stem cells (iPSCs) are an established cellular system to study the impact of genetic variants in derived cell types and developmental contexts. However, in their pluripotent state, the disease impact of genetic variants is less well known. Here, we integrate data from 1,367 human iPSC lines to comprehensively map common and rare regulatory variants in human pluripotent cells. Using this population-scale resource, we report hundreds of new colocalization events for human traits specific to iPSCs, and find increased power to identify rare regulatory variants compared with somatic tissues. Finally, we demonstrate how iPSCs enable the identification of causal genes for rare diseases. Integrative data analysis of 1,367 human iPSC lines maps common and rare regulatory variants that colocalize with loci associated with human traits and diseases. |
| Audience | Academic |
| Author | Jakubosky, David Bonner, Devon E. Mirauta, Bogdan Smith, Erin N. Gloudemans, Michael J. Seaton, Daniel D. Stegle, Oliver Li, Xin Ferraro, Nicole M. Cai, Na Wheeler, Matthew T. Frésard, Laure Zastrow, Diane B. Bonder, Marc Jan D’Antonio, Matteo Carcamo-Orive, Ivan Kilpinen, Helena Montgomery, Stephen B. Zhao, Chunli Vakili, Dara Horta, Danilo Frazer, Kelly A. Smail, Craig Knowles, Joshua W. |
| AuthorAffiliation | 1 European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Cambridge, UK 5 Genomic Medicine Center, Children’s Mercy Research Institute and Children’s Mercy Kansas City, Kansas City, MO 64108, USA 17 Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland 9 Department of Pediatrics and Rady Children’s Hospital, University of California, San Diego, La Jolla, CA 92093, USA 11 Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA 12 Wellcome Sanger Institute, Wellcome Trust Genome Campus, CB10 1SA Cambridge, UK 15 Faculty of Medicine, Imperial College London, London, UK 16 Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA 94305, USA 19 Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA 92093 USA 20 Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA 7 Biomedical Science |
| AuthorAffiliation_xml | – name: 4 Department of Biomedical Data Science, Stanford University School of Medicine, Stanford, CA 94305, USA – name: 7 Biomedical Sciences Graduate Program, University of California, San Diego, La Jolla, CA 92093, USA – name: 19 Institute for Genomic Medicine, University of California, San Diego, La Jolla, CA 92093 USA – name: 18 Helsinki Institute of Life Science (HiLIFE), University of Helsinki, Finland – name: 16 Stanford Center for Undiagnosed Diseases, Stanford University, Stanford, CA 94305, USA – name: 13 Helmholtz Pioneer Campus, Helmholtz Zentrum München, Ingolstaedter Landstraße 1, D-85764 Neuherberg, Germany – name: 17 Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki, Finland – name: 14 UCL Great Ormond Street Institute of Child Health, University College London, UK – name: 11 Division of Cardiovascular Medicine, Stanford University School of Medicine, Stanford, CA 94305, USA – name: 20 Department of Genetics, Stanford University School of Medicine, Stanford, CA, 94305, USA – name: 12 Wellcome Sanger Institute, Wellcome Trust Genome Campus, CB10 1SA Cambridge, UK – name: 6 Department of Pathology, Stanford University School of Medicine, Stanford, CA 94305, USA – name: 5 Genomic Medicine Center, Children’s Mercy Research Institute and Children’s Mercy Kansas City, Kansas City, MO 64108, USA – name: 10 CAS Key Laboratory of Computational Biology, CAS-MPG Partner Institute for Computational Biology, Shanghai Institute of Nutrition and Health, Chinese Academy of Sciences, Shanghai, 200031, China – name: 9 Department of Pediatrics and Rady Children’s Hospital, University of California, San Diego, La Jolla, CA 92093, USA – name: 8 Department of Biomedical Informatics, University of California, San Diego, La Jolla, CA 92093, USA – name: 2 European Molecular Biology Laboratory, Genome Biology Unit, 69117 Heidelberg, Germany – name: 1 European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, CB10 1SD Cambridge, UK – name: 3 Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), 69120 Heidelberg, Germany – name: 15 Faculty of Medicine, Imperial College London, London, UK |
| Author_xml | – sequence: 1 givenname: Marc Jan orcidid: 0000-0002-8431-3180 surname: Bonder fullname: Bonder, Marc Jan email: bondermj@gmail.com organization: European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, European Molecular Biology Laboratory, Genome Biology Unit, Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ) – sequence: 2 givenname: Craig orcidid: 0000-0001-8045-6021 surname: Smail fullname: Smail, Craig email: csmail@stanford.edu organization: Department of Biomedical Data Science, Stanford University School of Medicine, Genomic Medicine Center, Children’s Mercy Research Institute and Children’s Mercy Kansas City – sequence: 3 givenname: Michael J. orcidid: 0000-0002-9924-9943 surname: Gloudemans fullname: Gloudemans, Michael J. organization: Department of Biomedical Data Science, Stanford University School of Medicine – sequence: 4 givenname: Laure surname: Frésard fullname: 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for Undiagnosed Diseases, Stanford University – sequence: 23 givenname: Helena surname: Kilpinen fullname: Kilpinen, Helena organization: Wellcome Sanger Institute, Wellcome Trust Genome Campus, UCL Great Ormond Street Institute of Child Health, University College London, Faculty of Biological and Environmental Sciences, University of Helsinki, Helsinki Institute of Life Science (HiLIFE), University of Helsinki – sequence: 24 givenname: Joshua W. orcidid: 0000-0003-1922-7240 surname: Knowles fullname: Knowles, Joshua W. organization: Division of Cardiovascular Medicine, Stanford University School of Medicine – sequence: 25 givenname: Erin N. surname: Smith fullname: Smith, Erin N. organization: Institute for Genomic Medicine, University of California, San Diego – sequence: 26 givenname: Kelly A. orcidid: 0000-0002-6060-8902 surname: Frazer fullname: Frazer, Kelly A. organization: Department of Pediatrics and Rady Children’s Hospital, University of California, San Diego, Institute for Genomic Medicine, University of California, San Diego – sequence: 27 givenname: Stephen B. orcidid: 0000-0002-5200-3903 surname: Montgomery fullname: Montgomery, Stephen B. email: smontgom@stanford.edu organization: Department of Pathology, Stanford University School of Medicine, Department of Genetics, Stanford University School of Medicine – sequence: 28 givenname: Oliver orcidid: 0000-0002-8818-7193 surname: Stegle fullname: Stegle, Oliver email: oliver.stegle@embl.de organization: European Molecular Biology Laboratory, European Bioinformatics Institute, Wellcome Trust Genome Campus, European Molecular Biology Laboratory, Genome Biology Unit, Division of Computational Genomics and Systems Genetics, German Cancer Research Center (DKFZ), Wellcome Sanger Institute, Wellcome Trust Genome Campus |
| BackLink | https://www.ncbi.nlm.nih.gov/pubmed/33664507$$D View this record in MEDLINE/PubMed |
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| Contributor | Jakubosky, David A Brown, Christopher D Park, YoSon Jan Bonder, Marc Seaton, Daniel |
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| Copyright | The Author(s), under exclusive licence to Springer Nature America, Inc. 2021 COPYRIGHT 2021 Nature Publishing Group Copyright Nature Publishing Group Mar 2021 |
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| DOI | 10.1038/s41588-021-00800-7 |
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| Notes | ObjectType-Article-1 SourceType-Scholarly Journals-1 ObjectType-Feature-2 content type line 14 content type line 23 Shared first authors, contributed equally to this work Shared last authors, contributed equally to this work The main analyses and data preparations were performed by M.J.B. and C.S.; D.J. and M.D. performed structural variant calling and analysis; N.M.F. performed GTEx v7 data processing; L.F. and X.L. performed rare variant annotation and interpretation; H.K. and D.V. annotated and validated the rare disease variants and genes for the HipSci rare disease samples; M.J.G. performed the colocalization analysis; M.J.B., D.S., B.M. and D.H. developed the eQTL software; C.Z. generated iPSC lines for UDN rare disease samples; N.C., I.C.-O., Y.P. assisted with data processing and analysis; M.J.B., C.S., M.J.G., S.B.M., O.S. wrote the manuscript; I.C.-O., N.C., N.M.F., K.A.F., L.F., M.J.G., D.J., M.T.W., D.B.Z., B.M. assisted in editing the manuscript; M.J.B., C.S., E.S., K.A.F., O.S., S.B.M. conceived and oversaw the study. Author contributions |
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| Title | Identification of rare and common regulatory variants in pluripotent cells using population-scale transcriptomics |
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