Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

GTEx Consortium

doi:10.1016/j.cell.2021.03.050

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

GTEx Consortium

Mailman School of Public Health

Research output: Contribution to journal › Article › peer-review

101 Citations (Scopus)

Abstract

Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

Original language	English
Pages (from-to)	2633-2648.e19
Journal	Cell
Volume	184
Issue number	10
DOIs	https://doi.org/10.1016/j.cell.2021.03.050
Publication status	Published - May 13 2021

Bibliographical note

Publisher Copyright:
© 2021 Elsevier Inc.

Funding

We thank the Montgomery and Kirkegaard labs for their feedback on this work. The GTEx project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (NIH) and by the National Cancer Institute , the National Human Genome Research Institute (NHGRI), the National Heart, Lung, and Blood Institute (NHLBI), the National Institute on Drug Abuse (NIDA), the National Institute of Mental Health , and the National Institute of Neurological Disorders and Stroke. We are thankful for support from a Stanford graduate fellowship and Bio-X Stanford interdisciplinary graduate fellowship (to O.M.d.G.); a National Science Foundation graduate research fellowship (to N.M.F.); NHLBI grant R01HL135313-01 (to A.S.R.); National Library of Medicine (NLM) training grant 5T15LM007033-36 (to T.Y.E.); NHLBI grant HHSN268201000029C and NHGRI grant 5U41HG009494 (to F.A. and K.G.A.); NIH grants R01GM122924 (to S.E.C. and T.L.) and 1K99HG009916-01 (to S.E.C.); Marie-Skłodowska Curie fellowship H2020 grant 706636 (to S.K.-H.); NIH grant R01HG010067 (to Y.P.); a Mr. and Mrs. Spencer T. Olin fellowship for women in graduate study (to A.J.S.); NIH grant R01MH109905 (to A.B.); the Searle Scholar Program (to A.B.); NIH grant R01MH101822 (to C.D.B.); NIH grants R01MH106842 , R01HL142028 , UM1HG008901 , and R01GM124486 (to T.L.); NIH grants R01MH107666 and P30DK020595 (H.K.I.); NIH grants R01HL109512 , R01HL134817 , R33HL120757 , and R01HL139478 (to T.Q.); the Chan Zuckerberg Foundation-Human Cell Atlas Initiative (to T.Q.); Stanford University School of Medicine (to K.K.); and NIH grants R01MH101814 (NIH Common Fund; GTEx Program) (to A.B. and S.B.M.), R01HG008150 (NHGRI; Non-Coding Variants Program) (to A.B. and S.B.M.), and R01AG066490 , R01HL142015 , U01HG009431 , and U01HG009080 (to S.B.M.). We thank the Montgomery and Kirkegaard labs for their feedback on this work. The GTEx project was supported by the Common Fund of the Office of the Director of the National Institutes of Health (NIH) and by the National Cancer Institute, the National Human Genome Research Institute (NHGRI), the National Heart, Lung, and Blood Institute (NHLBI), the National Institute on Drug Abuse (NIDA), the National Institute of Mental Health, and the National Institute of Neurological Disorders and Stroke. We are thankful for support from a Stanford graduate fellowship and Bio-X Stanford interdisciplinary graduate fellowship (to O.M.d.G.); a National Science Foundation graduate research fellowship (to N.M.F.); NHLBI grant R01HL135313-01 (to A.S.R.); National Library of Medicine (NLM) training grant 5T15LM007033-36 (to T.Y.E.); NHLBI grant HHSN268201000029C and NHGRI grant 5U41HG009494 (to F.A. and K.G.A.); NIH grants R01GM122924 (to S.E.C. and T.L.) and 1K99HG009916-01 (to S.E.C.); Marie-Sk?odowska Curie fellowship H2020 grant 706636 (to S.K.-H.); NIH grant R01HG010067 (to Y.P.); a Mr. and Mrs. Spencer T. Olin fellowship for women in graduate study (to A.J.S.); NIH grant R01MH109905 (to A.B.); the Searle Scholar Program (to A.B.); NIH grant R01MH101822 (to C.D.B.); NIH grants R01MH106842, R01HL142028, UM1HG008901, and R01GM124486 (to T.L.); NIH grants R01MH107666 and P30DK020595 (H.K.I.); NIH grants R01HL109512, R01HL134817, R33HL120757, and R01HL139478 (to T.Q.); the Chan Zuckerberg Foundation-Human Cell Atlas Initiative (to T.Q.); Stanford University School of Medicine (to K.K.); and NIH grants R01MH101814 (NIH Common Fund; GTEx Program) (to A.B. and S.B.M.), R01HG008150 (NHGRI; Non-Coding Variants Program) (to A.B. and S.B.M.), and R01AG066490, R01HL142015, U01HG009431, and U01HG009080 (to S.B.M.). O.M.d.G. designed the study, conducted analyses, visualized data, and co-wrote the manuscript; D.C.N. conducted co-expression and ASE analyses. N.M.F. conducted outlier analysis and contributed to writing. M.J.G. conducted colocalization analysis. A.S.R. contributed to colocalization analysis. C.S. contributed to outlier analysis. T.Y.E. contributed to ASE analysis. F.A. generated QTL and ASE data. B.N. and J.X. contributed to QTL replication analyses. A.N.B. contributed to GWAS and colocalization analysis. S.E.C. generated ASE and tissue-sharing data. S.K.-H. generated tissue sharing data. Y.P. contributed to colocalization analysis. A.J.S. generated structural variant data. B.J.S. contributed to outlier analysis. C.D.B. and X.W. led trainees and contributed to GWAS and colocalization analysis. I.M.H. led trainees and contributed to structural variant data. A.B. contributed to outlier analysis. T.L. led trainees. H.K.I. led trainees and led the GWAS analysis team. K.G.A. generated data and provided oversight of the LDACC and pipelines. S.M. led trainees and contributed to QTL replication analyses. T.Q. and K.K. helped with data interpretation. S.B.M. designed the study, led trainees, and co-wrote the manuscript. F.A. is an inventor on a patent application related to TensorQTL; S.E.C. is a co-founder and chief technology officer at Variant Bio and owns stock in Variant Bio; T.L. is on the scientific advisory board of Variant Bio, Goldfinch Bio, and GSK and owns stock in Variant Bio; and S.B.M. is on the scientific advisory board of MyOme. All other authors report no competing interests.

Funders	Funder number
LDACC
Marie-Skłodowska Curie fellowship H2020
National Science Foundation	R01HL135313-01
National Institutes of Health
National Institute of Mental Health	R01MH109905, R01MH101822, R01MH107666, R01MH106842
National Institute on Drug Abuse
National Heart, Lung, and Blood Institute	R01HL134817, R01HL139478, R01HL142028, R01HL142015, R33HL120757, R01HL109512
National Human Genome Research Institute	U01HG009080, R01HG008150, R01HG010067, U01HG009431, UM1HG008901
National Cancer Institute
National Institute of Neurological Disorders and Stroke
U.S. National Library of Medicine	HHSN268201000029C, 5U41HG009494, 1K99HG009916-01, R01GM122924, 5T15LM007033-36
School of Medicine, Stanford University	R01MH101814, R01AG066490
Horizon 2020 Framework Programme	706636
Searle Scholars Program	R01GM124486, P30DK020595

ASJC Scopus Subject Areas

General Biochemistry,Genetics and Molecular Biology

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

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10.1016/j.cell.2021.03.050

Cite this

@article{c1e97adb6afc47069cbb9b964bd7d2a2,

title = "Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease",

abstract = "Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.",

author = "{GTEx Consortium} and {de Goede}, {Olivia M.} and Nachun, {Daniel C.} and Ferraro, {Nicole M.} and Gloudemans, {Michael J.} and Rao, {Abhiram S.} and Craig Smail and Eulalio, {Tiffany Y.} and Fran{\c c}ois Aguet and Bernard Ng and Jishu Xu and Barbeira, {Alvaro N.} and Castel, {Stephane E.} and Sarah Kim-Hellmuth and Park, {Yo Son} and Scott, {Alexandra J.} and Strober, {Benjamin J.} and Shankara Anand and Stacey Gabriel and Getz, {Gad A.} and Aaron Graubert and Kane Hadley and Handsaker, {Robert E.} and Huang, {Katherine H.} and Xiao Li and MacArthur, {Daniel G.} and Meier, {Samuel R.} and Nedzel, {Jared L.} and Nguyen, {Duyen T.} and Segr{\`e}, {Ayellet V.} and Ellen Todres and Brunilda Balliu and Rodrigo Bonazzola and Andrew Brown and Conrad, {Donald F.} and Cotter, {Daniel J.} and Nancy Cox and Sayantan Das and Dermitzakis, {Emmanouil T.} and Jonah Einson and Engelhardt, {Barbara E.} and Eleazar Eskin and Flynn, {Elise D.} and Laure Fresard and Gamazon, {Eric R.} and Diego Garrido-Mart{\'i}n and Gay, {Nicole R.} and Roderic Guig{\'o} and Hamel, {Andrew R.} and Yuan He and Gen Li",

note = "Publisher Copyright: {\textcopyright} 2021 Elsevier Inc.",

year = "2021",

month = may,

day = "13",

doi = "10.1016/j.cell.2021.03.050",

language = "English",

volume = "184",

pages = "2633--2648.e19",

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AU - GTEx Consortium

AU - de Goede, Olivia M.

AU - Nachun, Daniel C.

AU - Ferraro, Nicole M.

AU - Gloudemans, Michael J.

AU - Rao, Abhiram S.

AU - Smail, Craig

AU - Eulalio, Tiffany Y.

AU - Aguet, François

AU - Ng, Bernard

AU - Xu, Jishu

AU - Barbeira, Alvaro N.

AU - Castel, Stephane E.

AU - Kim-Hellmuth, Sarah

AU - Park, Yo Son

AU - Scott, Alexandra J.

AU - Strober, Benjamin J.

AU - Anand, Shankara

AU - Gabriel, Stacey

AU - Getz, Gad A.

AU - Graubert, Aaron

AU - Hadley, Kane

AU - Handsaker, Robert E.

AU - Huang, Katherine H.

AU - Li, Xiao

AU - MacArthur, Daniel G.

AU - Meier, Samuel R.

AU - Nedzel, Jared L.

AU - Nguyen, Duyen T.

AU - Segrè, Ayellet V.

AU - Todres, Ellen

AU - Balliu, Brunilda

AU - Bonazzola, Rodrigo

AU - Brown, Andrew

AU - Conrad, Donald F.

AU - Cotter, Daniel J.

AU - Cox, Nancy

AU - Das, Sayantan

AU - Dermitzakis, Emmanouil T.

AU - Einson, Jonah

AU - Engelhardt, Barbara E.

AU - Eskin, Eleazar

AU - Flynn, Elise D.

AU - Fresard, Laure

AU - Gamazon, Eric R.

AU - Garrido-Martín, Diego

AU - Gay, Nicole R.

AU - Guigó, Roderic

AU - Hamel, Andrew R.

AU - He, Yuan

AU - Li, Gen

PY - 2021/5/13

Y1 - 2021/5/13

N2 - Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

AB - Long non-coding RNA (lncRNA) genes have well-established and important impacts on molecular and cellular functions. However, among the thousands of lncRNA genes, it is still a major challenge to identify the subset with disease or trait relevance. To systematically characterize these lncRNA genes, we used Genotype Tissue Expression (GTEx) project v8 genetic and multi-tissue transcriptomic data to profile the expression, genetic regulation, cellular contexts, and trait associations of 14,100 lncRNA genes across 49 tissues for 101 distinct complex genetic traits. Using these approaches, we identified 1,432 lncRNA gene-trait associations, 800 of which were not explained by stronger effects of neighboring protein-coding genes. This included associations between lncRNA quantitative trait loci and inflammatory bowel disease, type 1 and type 2 diabetes, and coronary artery disease, as well as rare variant associations to body mass index.

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ER -

Population-scale tissue transcriptomics maps long non-coding RNAs to complex disease

Abstract

Bibliographical note

Funding

ASJC Scopus Subject Areas

UN SDGs

Access to Document

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