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Cell-type-specific genetic regulation of gene expression in human tissues

The Genotype-Tissue Expression (GTEx) project (1) and other studies (25) demonstrated that genetic regulation of the transcriptome is widespread. The GTEx Consortium, in particular, has constructed a large catalog of loci of quantitative cis expression and splicing traits (cis-eQTL and cis-sQTL, respectively) in a wide range of tissues, demonstrating that these cis-eQTL and cis- sQTLs (collectively referred to herein as QTL) are generally highly tissue specific or widely shared, even between dissimilar tissues and organs (1, 6). However, most of these studies were performed using heterogeneous bulk tissue samples comprising different cell types. This limits the power, interpretation, and downstream applications of QTL studies. Genetic effects that are active only in rare cell types within a sampled tissue may not be detected, a mechanistic interpretation of QTL sharing between tissues and other contexts is complicated without understanding the differences in cell type composition and the inference of downstream molecular effects of regulatory variants without the cell-type-specific context is challenging Efforts to map eQTLs to individual cell types have largely been limited to blood, using purified cell types (7̵

1;11) or single cell sequencing (12).

Although many efforts are underway to optimize sequencing of single cells and single nuclei of human tissues (13, 14), included as part of the Human Cell Atlas (15), these methods are not yet scalable for sufficient sample size and coverage to achieve power comparable to that of bulk eQTL studies (1618). However, cell type-specific eQTLs can be computationally deduced from bulk tissue measurements using estimated proportions or enrichments of relevant cell types to test interactions with the genotype. To date, such approaches have only been applied to a limited range of cell types, such as blood cells (19, 20) and adipocytes (21). These studies identified thousands of cell-type interactions in eQTLs discovered in whole blood samples from large cohorts.[5683samples([5683samples([5683campioni([5683samples(19); 2116 samples, (20)], indicating that a large number of interactions are likely to be identified by expanding this type of assay to other tissues and cell types.

GTEx Consortium

Laboratory and Data Analysis Coordination Center (LDACC): François Aguet1, Shankara Anand1, Kristin G. Ardlie1, Stacey Gabriel1, Gad A. Getz1,2,3, Aaron Graubert1, Kane Hadley1, Robert E. Handsaker4.5.6, Katherine H. Huang1, Seva Kashin4.5.6, Xiao Li1, Daniel G. MacArthur5.7, Samuel R. Meier1, Jared L. Nedzel1, Duyen T. Nguyen1, Ayellet V. Segrè1.8, Ellen Todres1

Analysis Working Group (funded by GTEx project grants): François Aguet1, Shankara Anand1, Kristin G. Ardlie1, Brunilda Balliu9, Alvaro N. Barbeira10, Alexis Battle11.12, Rodrigo Bonazzola10, Andrew Brown13.14, Christopher D. Brown15, Stephane E. Castel16.17, Donald F. Conrad18.19, Daniel J. Cotter20, Nancy Cox21, Sayantan Das22, Olivia M. de Goede20, Emmanouil T. Dermitzakis13,23,24, Jonah Einson16.25, Barbara E. Engelhardt26.27, Eleazar Eskin28, Tiffany Y. Eulalio29, Nicole M. Ferraro29, Elise D. Flynn16.17, Laure Fresard30, Eric R. Gamazon21,31,32,33, Diego Garrido-Martín34, Nicole R. Gay20, Gad A. Getz1,2,3, Michael J. Gloudemans29, Aaron Graubert1, Roderic Guigó34.35, Kane Hadley1, Andrew R. Hame18.1, Robert E. Handsaker4.5.6, Yuan He11, Paul J. Hoffman16, Farhad Hormozdiari1.36, Lei Hou1.37, Katherine H. Huang1, Hae Kyung Im10, Brian Jo26.27, Silva Kasela16.17, Seva Kashin4.5.6, Manolis Kellis1.37, Sarah Kim-Hellmuth16,17,38, Alan Kwong22, Tuuli Lappalainen16.17, Xiao Li1, Xin Li30, Yanyu Liang10, Daniel G. MacArthur5.7, Serghei Mangul28.39, Samuel R. Meier1, Pejman Mohammadi16,17,40,41, Stephen B. Montgomery20.30, Manuel Muñoz-Aguirre34.42, Daniel C. Nachun30, Jared L. Nedzel1, Duyen T. Nguyen1, Andrew B. Nobel43, Meritxell Oliva10.44, YoSon Park15.45, Yongjin Park1.37, Princy Parsana12, Abhiram S. Rao46, Ferran Reverter47, John M. Rouhana1.8, Chiara Sabatti48, Ashis Saha12, Ayellet V. Segrè1.8, Andrew D. Skol10.49, Matthew Stephens50, Barbara E. Stranger10.51, Benjamin J. Strober11, Nicole A. Teran30, Ellen Todres1, Ana Viñuela13,23,24,52, Gao Wang50, Xiaoquan Wen22, Fred Wright53, Valentin Wucher34, Yuxin Zou54

Analysis Working Group (not funded by GTEx project grants): Pedro G. Ferreira55.56.57.58, Gen Li59, Marta Melé60, Esti Yeger-Lotem61.62

Leidos Biomedical – project management: Mary E. Barcus63, Debra Bradbury63, Tanya Krubit63, Jeffrey A. McLean63, Liqun Qi63, Karna Robinson63, Nancy V. Roche63, Anna M. Smith63, Leslie Sobin63, David E. Tabor63, Anita Undale63

Sites of origin of biological sample collection: Jason Bridge64, Lori E. Brigham65, Barbara A. Foster66, Bryan M. Gillard66, Richard Hasz67, Marcus Hunter68, Christopher Johns69, Mark Johnson70, Ellen Karasik66, Gene Kopen71, William F. Leinweber71, Alisa McDonald71, Michael T. Moser66, Kevin Myer68, Kimberley D. Ramsey66, Brian Roe68, Saboor Shad71, Jeffrey A. Thomas71.70, Gary Walters70, Michael Washington70, Joseph Wheeler69

Main resource of the biospecimen: Scott D. Jewell72, Daniel C. Rohrer72, Dana R. Valley72

Brain Bank Archive: David A. Davis73, Deborah C. Mash73

Pathology: Mary E. Barcus63, Philip A. Branton74, Leslie Sobin63

ELSI study: Laura K. Barker75, Heather M. Gardiner75, Maghboeba Mosavel76, Laura A. Siminoff75

Genome Browser Data Integration and Visualization: Paul Flicek77, Maximilian Haeussler78, Thomas Juettemann77, W. James Kent78, Christopher M. Lee78, Conner C. Powell78, Kate R. Rosenbloom78, Magali Ruffier77, Dan Sheppard77, Kieron Taylor77, Stephen J. Trevanion77, Daniel R. Zerbino77

EGTEx groups: Nathan S. Abell20, Joshua Akey79, Lin Chen44, Kathryn Demanelis44, Jennifer A. Doherty80, Andrew P. Feinberg81, Kasper D. Hansen82, Peter F. Hickey83, Lei Hou1.37, Farzana Jasmine44, Lihua Jiang20, Rajinder Kaul84.85, Manolis Kellis1.37, Muhammad G. Kibriya44, Jin Billy Li20, Qin Li20, Shin Lin86, Sandra E. Linder20, Stephen B. Montgomery20.30, Meritxell Oliva10.44, Yongjin Park1.37, Brandon L. Pierce44, Lindsay F. Rizzardi87, Andrew D. Skol10.49, Kevin S. Smith30, Michael Snyder20, John Stamatoyannopoulos84.88, Barbara E. Stranger10.51, Hua Tang20, Meng Wang20

NIH Program Management: Philip A. Branton74, Latarsha J. Carithers74.89, Ping Guan74, Susan E. Koester90, A. Roger Little91, Helen M. Moore74, Concepcion R. Nierrasninety two, Abhi K. Rao74, Jimmie B. Vaught74, Simona Volpi93

1Broad Institute of MIT and Harvard, Cambridge, MA, USA. 2Cancer Center and Department of Pathology, Massachusetts General Hospital, Boston, MA, USA. 3Harvard Medical School, Boston, MA, USA. 4Department of Genetics, Harvard Medical School, Boston, MA, USA. 5Medical and Population Genetics Program, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 6Stanley Center for Psychiatric Research, Broad Institute of MIT and Harvard, Cambridge, MA, USA. 7Analytical and Translational Genetics Unit, Massachusetts General Hospital, Boston, MA, USA. 8Ocular Genomics Institute, Massachusetts Eye and Ear, Harvard Medical School, Boston, MA, USA. 9Department of Biomathematics, University of California, Los Angeles, CA, USA. 10Section of Genetic Medicine, Department of Medicine, University of Chicago, Chicago, IL, USA. 11Department of Biomedical Engineering, Johns Hopkins University, Baltimore, MD, USA. 12Department of Computer Science, Johns Hopkins University, Baltimore, MD, USA. 13Department of Genetic and Developmental Medicine, Faculty of Medicine of the University of Geneva, Geneva, Switzerland. 14Population Health and Genomics, University of Dundee, Dundee, Scotland, UK. 15Department of Genetics, University of Pennsylvania, Perelman School of Medicine, Philadelphia, PA, USA. 16New York Genome Center, New York, NY, USA. 17Department of Systems Biology, Columbia University, New York, NY, USA. 18Department of Genetics, Washington University School of Medicine, St. Louis, MO, USA. 19Division of Genetics, Oregon National Primate Research Center, Oregon Health & Science University, Portland, OR, USA. 20Department of Genetics, Stanford University, Stanford, CA, USA. 21Division of Genetic Medicine, Department of Medicine, Vanderbilt University Medical Center, Nashville, TN, USA. 22Department of Biostatistics, University of Michigan, Ann Arbor, MI, USA. 23Institute of Genetics and Genomics in Geneva (iGE3), University of Geneva, Geneva, Switzerland. 24Swiss Institute of Bioinformatics, Geneva, Switzerland. 25Department of Biomedical Computer Science, Columbia University, New York, NY, USA. 26Department of Computer Science, Princeton University, Princeton, NJ, USA. 27Center for Statistics and Machine Learning, Princeton University, Princeton, NJ, USA. 28Department of Computer Science, University of California, Los Angeles, CA, USA. 29Program in Biomedical Informatics, Stanford University School of Medicine, Stanford, CA, USA. 30Department of Pathology, Stanford University, Stanford, CA, USA. 31Data Science Institute, Vanderbilt University, Nashville, TN, USA. 32Clare Hall, Cambridge University, Cambridge, UK. 33MRC Epidemiology Unit, University of Cambridge, Cambridge, UK. 34Center for Genomic Regulation (CRG), The Barcelona Institute for Science and Technology, Barcelona, ​​Catalonia, Spain. 35Universitat Pompeu Fabra (UPF), Barcelona, ​​Catalonia, Spain. 36Department of Epidemiology, Harvard T.H. Chan School of Public Health, Boston, MA, USA. 37Computer Science and Artificial Intelligence Laboratory, Massachusetts Institute of Technology, Cambridge, MA, USA. 38Statistical Genetics, Max Planck Institute of Psychiatry, Munich, Germany. 39Department of Clinical Pharmacy, School of Pharmacy, University of Southern California, Los Angeles, CA, USA. 40Scripps Research Translational Institute, La Jolla, CA, USA. 41Department of Structural and Computational Integrative Biology, The Scripps Research Institute, La Jolla, CA, USA. 42Department of Statistics and Operations Research, Universitat Politècnica de Catalunya (UPC), Barcelona, ​​Catalonia, Spain. 43Department of Statistics and Operations Research and Department of Biostatistics, University of North Carolina, Chapel Hill, NC, USA. 44Department of Public Health Sciences, University of Chicago, Chicago, IL, USA. 45Department of Systems Pharmacology and Translational Therapy, Perelman School of Medicine, University of Pennsylvania, Philadelphia, PA, USA. 46Department of Bioengineering, Stanford University, Stanford, CA, USA. 47Department of Genetics, Microbiology and Statistics, University of Barcelona, ​​Barcelona, ​​Spain. 48Departments of Biomedical Data Science and Statistics, Stanford University, Stanford, CA, USA. 49Department of Pathology and Laboratory Medicine, Ann & Robert H. Lurie Children’s Hospital of Chicago, Chicago, IL, USA. 50Department of Human Genetics, University of Chicago, Chicago, IL, USA. 51Center for Genetic Medicine, Department of Pharmacology, Northwestern University, Feinberg School of Medicine, Chicago, IL, USA. 52Department of Twin Research and Genetic Epidemiology, King’s College London, London, UK. 53Bioinformatics Research Center and Departments of Statistics and Life Sciences, North Carolina State University, Raleigh, NC, USA. 54Department of Statistics, University of Chicago, Chicago, IL, USA. 55Department of Computer Science, Faculty of Science, University of Porto, Porto, Portugal. 56Instituto de Investigação e Inovação em Saúde, University of Porto, Porto, Portugal. 57Institute of Molecular Pathology and Immunology, University of Porto, Porto, Portugal. 58Artificial Intelligence and Decision Support Laboratory, Institute for Systems and Computer Engineering, Technology and Science, Porto, Portugal. 59Mailman School of Public Health, Columbia University, New York, NY, USA. 60Department of Life Sciences, Barcelona Supercomputing Center, Barcelona, ​​Spain. 61Department of Clinical Biochemistry and Pharmacology, Ben-Gurion University of the Negev, Beer-Sheva, Israel. 62National Institute of Biotechnology in the Negev, Beer-Sheva, Israel. 63Leidos Biomedical, Rockville, MD, USA. 64Upstate New York Transplant Services, Buffalo, NY, USA. 65Washington Regional Transplant Community, Annandale, VA, USA. 66Therapeutics, Roswell Park Comprehensive Cancer Center, Buffalo, NY, USA. 67Gift of Life Donor Program, Philadelphia, PA, USA. 68LifeGift, Houston, TX, United States. 69Center for Organ Recovery and Education, Pittsburgh, PA, USA. 70LifeNet Health, Virginia Beach, Virginia. UNITED STATES OF AMERICA. 71National Disease Research Interchange, Philadelphia, PA, USA. 72Van Andel Research Institute, Grand Rapids, MI, USA. 73Department of Neurology, University of Miami Miller School of Medicine, Miami, FL, USA. 74Biorepository and Biospecimen Research Branch, Division of Cancer Treatment and Diagnosis, National Cancer Institute, National Institutes of Health, Bethesda, MD, USA. 75College of Public Health, Temple University, Philadelphia, PA, USA. 76Virginia Commonwealth University, Richmond, VA, USA. 77European Molecular Biology Laboratory, European Institute of Bioinformatics, Hinxton, United Kingdom. 78Genomics Institute, University of California, Santa Cruz, CA, USA. 79Carl Icahn Laboratory, Princeton University, Princeton, NJ, USA. 80Department of Population Health Sciences, University of Utah, Salt Lake City, UT, USA. 81Departments of Medicine, Biomedical Engineering and Mental Health, Johns Hopkins University, Baltimore, MD, USA. 82Department of Biostatistics, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, USA. 83Department of Medical Biology, The Walter and Eliza Hall Institute of Medical Research, Parkville, Victoria, Australia. 84Altius Institute for Biomedical Sciences, Seattle, WA, USA. 85Division of Genetics, University of Washington, Seattle, WA, USA. 86Department of Cardiology, University of Washington, Seattle, WA, USA. 87HudsonAlpha Institute for Biotechnology, Huntsville, AL, USA. 88Genome Sciences, University of Washington, Seattle, WA, USA. 89National Institute of Dental and Craniofacial Research, National Institutes of Health, Bethesda, MD, USA. 90Division of Neuroscience and Basic Behavioral Science, National Institute of Mental Health, National Institutes of Health, Bethesda, MD, USA. 91National Institute on Drug Abuse, Bethesda, MD, USA. ninety twoOffice of Strategic Coordination, Division of Program Coordination, Planning and Strategic Initiatives, Office of the Director, National Institutes of Health, Rockville, MD, USA. 93Division of Genomics Medicine, National Human Genome Research Institute, Bethesda, MD, USA.

Acknowledgments: We thank the donors and their families for their generous donation of organs for transplantation and tissue donations for the GTEx research project; we thank M. Khan for the illustrations in Fig. 1A. Financing: This work was funded by the following funding sources: Marie-Skłodowska Curie H2020 grant 706636 (S.K.-H.); Grant NIH 1K99HG009916-01 (S.E.C.); NIH Scholarship R01HG002585 (G.W. and M.S.); BIO2015-70777-P, Ministerio de Economia y Competitividad and FEDER funds (M.M.-A., V.W., R.G. and D.G.-M.); FPU15 / 03635, Ministerio de Educación, Cultura y Deporte (M.M-A.); “La Caixa” Foundation Agreement (ID 100010434) LCF / BQ / SO15 / 52260001 (D.G.-M.); EU IMI program (UE7-DIRECT-115317-1) (A.V. and E.T.D.); RNA1 project funded by FNS (31003A_149984) (A.V. and E.T.D.); Massachusetts Lions Eye Research Fund (A.R.H.) grant; MRC grants MR / R023131 / 1 and MR / M004422 / 1 (K.S.S.); and Biomedical Big Data Training Grant 5T32LM012424-03 (B.N.). The TwinsUK study was funded by the Wellcome Trust and the European Community’s Seventh Framework Program (FP7 / 2007-2013). The TwinsUK study also receives support from the National Institute for Health Research (NIHR), BioResource, Clinical Research Facility and Biomedical Research Center based at Guy’s and St Thomas’ NHS Foundation Trust in partnership with King’s College London. This work was further supported by the Director’s Office Common Fund, United States National Institute of Health (NIH), and by NCI, NHGRI, NHLBI, NIDA, NIMH, NIA, NIAID and NINDS through NIH contracts HHSN261200800001E (Leidos Prime contract with NCI: AMS, DET, NVR, JAM, LS, MEB, LQ, TK, DB, KR and AU), 10XS170 (NDRI: WFL, JAT, GK, AM, SS, RH, G.Wa., MJ, M.Wa., LEB, CJ, JW, BR, M.Hu., KM, LAS, HMG, M.Mo. and LKB), 10XS171 (Roswell Park Cancer Institute: BAF, MTM, EK, BMG, KDR and JB ), 10X172 (Science Care), 12ST1039 (IDOX), 10ST1035 (Van Andel Institute: SDJ, DCR and DRV), HHSN268201000029C (Broad Institute: FA, GG, KGA, AVS, X.Li., ET, SG, AG, SA, KHH, DTN, KH, SRM and JLN), 5U41HG009494 (FA, GG and KGA), and through NIH grants R01 DA006227-17 (University of Miami Brain Bank: DCM and DAD), University Scholarship Supplement of Miami DA006227 (DC M. and DAD), R01 MH090941 (University of Geneva), R01 MH090951 and R01 MH090937 (University of Chicago), R01 MH090936 ( University of North Carolina – Chapel Hill), R01MH101814 (MM-A., VW, SBM, RG, ETD, DG-M. E AV), U01HG007593 (SBM), R01MH101822 (CDB), U01HG007598 (MO and BES), U01MH104393 (APF). Extension from H002371 to 5U41HG002371 (WJK) and other funding sources: R01MH106842 (TL, PM, EF and PJH), R01HL142028 (TL, Si.Ka. and PJH), R01GM122924 (TL and SEC), R01MH107666 (HKD09530), PJH (HKI), UM1HG008901 (TL), R01GM124486 (TL), R01HG010067 (Y.Pa.), R01HG002585 (G.Wa. and M.St.), Gordon and Betty Moore Foundation GBMF 4559 (G.Wa. and M. St.), R01HG006855 (Se.Ka., REH), NIH CTSA grant UL1TR002550-01 (PM), R35HG010718 (ERG), R01MH109905, 1R01HG010480 (A.Ba.), Searle Scholar Program (A.Ba.), R01HG008150 (SBM), 5T32HG000044-22, NHGRI Institutional Training Grant in Genome Science (NRG) and F32HG009987 (FH). Contributions of the author: S.K.-H., F.A. and T.L. conceived the study. S.K.-H. and makes. he led the writing, generation of figures and editing of the manuscript and supplementary materials. S.K.-H. coordinated analyzes of all participating authors; S.K.-H. and makes. they generated pipelines and performed iQTL mapping; S.K.-H., F.A., M.O., M.M.-A., V.W., D.G.-M., S.M., B.N. and J.Q. performed cellular benchmarking analyzes; S.K. performed ieQTL validation with ASE data using the validation pipeline and ASE data generated by S.E.C.; F.A., A.V. and A.L.R. performed replication analysis; S.E.C. performed prediction analysis of QTL tissue activity; S.K.-H. and S.E.C. generated tissue sharing data (MASH); S.K.-H. performed tissue specificity, multi-tissue analysis and colocalization analysis; A.R.H. performed the QTLEnrich analysis; G.W. and Y.Z. provided software support for multi-tissue eQTL analysis; X.W. and H.K.I. provided advice on the analysis of colocation; A.B., A.M.-P. and J.M.-S. contributed to replication analysis; DOES. and K.G.A. generated and supervised the generation of GTEx v8, LDACC, pipeline data; A.N.B. and R.B. they generated GWAS data; K.S.S., M.S., H.S.X., G.G., E.T.D., H.K.I., R.G., A.V.S., B.E.S., K.G.A. and T.L. supervised the work of the trainees in their workshops; and M.O. and T.L. contributed to the drafting of the manuscript. All authors have read and approved the final manuscript. Conflicting interests: DOES. is an inventor of a patent application relating to TensorQTL; S.E.C. he is co-founder, chief technology officer and shareholder at Variant Bio; J.Q. is a Pfizer employee; H.S.X. is an employee of AbbVie; H.K.I. received speaker fees from GSK and AbbVie; E.T.D. is chairman and board member of Hybridstat; G.G. receives research funding from IBM and Pharmacyclics and is an inventor of patent applications relating to MuTect, ABSOLUTE, MutSig, MSMuTect, MSMutSig, POLYSOLVER and TensorQTL. G.G. is a founder, consultant and private equity interest in Scorpion Therapeutics; T.L. is a member of the scientific advisory board of Variant Bio with equity and Goldfinch Bio. GTEx consortium members: P.F. he is a member of the Scientific Advisory Committees of Fabric Genomics and Eagle Genomes. P.G.F. is partner of Bioinf2Bio. ERG. is a member of the Editorial Board of Circulation Research and advises the City of Hope / Beckman Research Institute; BEE. is on the scientific advisory boards of Celsius Therapeutics and Freenome; S.B.M. is a member of the Prime Genomics Scientific Advisory Board; D.G.M. is co-founder with participation in Goldfinch Bio and has received research support from AbbVie, Astellas, Biogen, BioMarin, Eisai, Merck, Pfizer, and Sanofi-Genzym. Availability of data and materials: All GTEx open access data, including summary statistics and cellular iQTL views, are available on the GTEx portal (https://gtexportal.org/home/datasets). All data protected by GTEx are available via dbGaP (accession phs000424.v8). Access to raw sequence data is now provided via the AnVIL platform (https://gtexportal.org/home/protectedDataAccess). Eighty-seven harmonized and imputed GWAS summary statistics described in Table S3 are available and linked to https://github.com/hakyimlab/gtex-gwas-analysis and https://zenodo.org/record/3629742#.XxYGoy1h0Ux. The original GWAS studies are cited in (1). The QTL mapping pipeline is available at https://github.com/broadinstitute/gtex-pipeline and https://doi.org/10.5281/zenodo.3727189, and tensorQTL is available at https://github.com/broadinstitute / tensorqtl and https://doi.org/10.5281/zenodo.3726360. The remaining GTEx biological samples have been archived and remain available as a resource for further studies (access can be requested on the GTEx portal at www.gtexportal.org/home/samplesPage).

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