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The Genotype-Tissue Expression (GTEx) pilot analysis: Multitissue gene regulation in humans
Open accessAbstract
Expression, genetic variation, and tissues: Human genomes show extensive genetic variation across individuals, but we have only just started documenting the effects of this variation on the regulation of gene expression. Furthermore, only a few tissues have been examined per genetic variant. In order to examine how genetic expression varies among tissues within individuals, the Genotype-Tissue Expression (GTEx) Consortium collected 1641 postmortem samples covering 54 body sites from 175 individuals. They identified quantitative genetic traits that affect gene expression and determined which of these exhibit tissue-specific expression patterns. Melé et al. measured how transcription varies among tissues, and Rivas et al. looked at how truncated protein variants affect expression across tissues. Science , this issue p. 648 , p. 660 , p. 666 ; see also p. 640
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“For the second stage of vision-language alignment (stage 3 of TITAN), we curated a dataset of 182,862 slide-report pairs from a combination of in-house clinical reports and pathology notes from the GTEx consortium129.”
From A multimodal whole-slide foundation model for pathology (2025) · cites this paper as [129]
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“Projects from large consortia like GTEx [156], the Epigenome Roadmap [176] and ENCODE [15] are already generating data from multiple-omics levels that facilitate these integrated analyses.”
From Gene co-expression analysis for functional classification and gene–disease predictions (2017) · cites this paper as [156]
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“NaV1.2 is widely expressed throughout the human central nervous system, but not in peripheral tissues [7,8].”
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“Such regulatory relationships show substantial heterogeneity across human cell types, tissues, and developmental stages (10), and are often highly species-specific (11).”
From Transcriptome-wide isoform-level dysregulation in ASD, schizophrenia, and bipolar disorder (2018) · cites this paper as [10]
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“Corroborating this hypothesis, GTEx data show multiple eQTLs within these enhancers that are associated with alterations in SCN1A expression in humans49.”
From Viral manipulation of functionally distinct interneurons in mice, non-human primates and humans (2020) · cites this paper as [49]
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“We found strong significant associations (false discovery rate (FDR)<0.05) between a SNP and expression of nearby genes in subcutaneous adipose tissues (Supplementary Data 13).”
From Meta-analysis identifies five novel loci associated with endometriosis highlighting key genes involved in hormone metabolism (2017) · cites this paper as [29]
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CFAP70 mutations lead to male infertility due to severe astheno-teratozoospermia. A case report
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Carella, A., Tejedor, J. R., García, M. G., Urdinguio, R. G., Bayón, G. F., Sierra, M., López, V., Toraño, E. G., Santamarina‐Ojeda, P., Pérez, R. F., et al. (2019) · International Journal of Cancer · doi:10.1002/ijc.32520 · Cited by 77
A sequence-based, deep learning model accurately predicts RNA splicing branchpoints
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Exome Genotyping Identifies Pleiotropic Variants Associated with Red Blood Cell Traits
Chami, N., Chen, M., Slater, A. J., Eicher, J. D., Εvangelou, Ε., Tajuddin, S. M., Love-Gregory, L. D., Kacprowski, T., Schick, U. M., Nomura, A., et al. (2016) · The American Journal of Human Genetics · doi:10.1016/j.ajhg.2016.05.007 · Cited by 77
Self-citationPonnaluri, V. K. C., Ehrlich, K. C., Zhang, G., Lacey, M. R., Johnston, D. A., Pradhan, S., & Ehrlich, M. (2016) · Epigenetics · doi:10.1080/15592294.2016.1265713 · Cited by 77
Nuclear Factor I/B: A Master Regulator of Cell Differentiation with Paradoxical Roles in Cancer
Becker‐Santos, D. D., Lonergan, K. M., Gronostajski, R. M., & Lam, W. L. (2017) · EBioMedicine · doi:10.1016/j.ebiom.2017.05.027 · Cited by 77
Human pain genetics database: a resource dedicated to human pain genetics research
Meloto, C. B., Benavides, R., Lichtenwalter, R. N., Wen, X., Tugarinov, N., Zorina-Lichtenwalter, K., Chabot‐Doré, A., Piltonen, M., Cattaneo, S., Verma, V., et al. (2017) · Pain · doi:10.1097/j.pain.0000000000001135 · Cited by 77
Self-citationBiallelic mutations of CFAP251 cause sperm flagellar defects and human male infertility
Li, W., He, X., Yang, S., Liu, C., Wu, H., Liu, W., Lv, M., Tang, D., Tan, J. Y., Tang, S., et al. (2018) · Journal of Human Genetics · doi:10.1038/s10038-018-0520-1 · Cited by 77
Defining the genetic and evolutionary architecture of alternative splicing in response to infection
Rotival, M., Quach, H., & Quintana‐Murci, L. (2019) · Nature Communications · doi:10.1038/s41467-019-09689-7 · Cited by 77
Choudhury, S., Huang, A. Y., Kim, J., Zhou, Z., Morillo, K. S., Maury, E. A., Tsai, J. W., Miller, M. B., Lodato, M. A., Araten, S., et al. (2022) · Nature Aging · doi:10.1038/s43587-022-00261-5 · Cited by 76
Cosentino, J., Behsaz, B., Alipanahi, B., McCaw, Z. R., Hill, D., Schwantes-An, T.-H. L., Lai, D., Carroll, A. W., Hobbs, B. D., Cho, M. H., et al. (2023) · Nature Genetics · doi:10.1038/s41588-023-01372-4 · Cited by 76
Expression quantitative trait locus analysis for translational medicine
Gibson, G. C., Powell, J. E., & Marigorta, U. M. (2015) · Genome Medicine · doi:10.1186/s13073-015-0186-7 · Cited by 77
Regulation of T Cell Receptor Signaling by DENND1B in T H 2 Cells and Allergic Disease
Yang, C.-W., Hojer, C. D., Zhou, M., Wu, X., Wüster, A., Lee, W. P., Yaspan, B. L., & Chan, A. C. (2016) · Cell · doi:10.1016/j.cell.2015.11.052 · Cited by 76
Genetics of autoimmune diseases: perspectives from genome-wide association studies
Kochi, Y. (2016) · International Immunology · doi:10.1093/intimm/dxw002 · Cited by 76
The importance of cohort studies in the post-GWAS era
Wijmenga, C., & Zhernakova, A. (2018) · Nature Genetics · doi:10.1038/s41588-018-0066-3 · Cited by 76
Hait, T. A., Amar, D., Ron Shamir, A., & Elkon, R. (2018) · Genome biology · doi:10.1186/s13059-018-1432-2 · Cited by 77
A Comparison of mRNA Sequencing with Random Primed and 3′-Directed Libraries
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Decreased sphingolipid synthesis in children with 17q21 asthma–risk genotypes
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Consistent RNA sequencing contamination in GTEx and other data sets
Nieuwenhuis, T. O., Yang, S. Y., Verma, R., Pillalamarri, V., Arking, D. E., Rosenberg, A. Z., McCall, M. N., & Halushka, M. K. (2020) · Nature Communications · doi:10.1038/s41467-020-15821-9 · Cited by 75
ATP-Binding and Hydrolysis in Inflammasome Activation
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Genetic architecture of heart failure with preserved versus reduced ejection fraction
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Self-citationModeling epigenetic lesions that cause gliomas
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GPR133 (ADGRD1), an adhesion G-protein-coupled receptor, is necessary for glioblastoma growth
Bayin, N. S., Frenster, J. D., KANE, J. R., Rubenstein, J. A., Modrek, A. S., Baitalmal, R., Dolgalev, I., Rudzenski, K., Scarabottolo, L., Crespi, D., et al. (2016) · Oncogenesis · doi:10.1038/oncsis.2016.63 · Cited by 75
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Metadata
- Authors
- The GTEx Consortium, Ardlie, K. G., Deluca, D. S., Segrè, A. V., Sullivan, T. J., Young, T. R., Gelfand, E. T., Trowbridge, C. A., Maller, J. B., Tukiainen, T., Lek, M., Ward, L. D., Kheradpour, P., Iriarte, B., Meng, Y., Palmer, C. D., Esko, T., Winckler, W., Hirschhorn, J. N., Kellis, M., MacArthur, D. G., Getz, G., Shabalin, A. A., Li, G., Zhou, Y.-H., Nobel, A. B., Rusyn, I., Wright, F. A., Lappalainen, T., Ferreira, P. G., Ongen, H., Rivas, M. A., Battle, A., Mostafavi, S., Monlong, J., Sammeth, M., Mele, M., Reverter, F., Goldmann, J. M., Koller, D., Guigó, R., McCarthy, M. I., Dermitzakis, E. T., Gamazon, E. R., Im, H. K., Konkashbaev, A., Nicolae, D. L., Cox, N. J., Flutre, T., Wen, X., Stephens, M., Pritchard, J. K., Tu, Z., Zhang, B., Huang, T., Long, Q., Lin, L., Yang, J., Zhu, J., Liu, J., Brown, A., Mestichelli, B., Tidwell, D., Lo, E., Salvatore, M., Shad, S., Thomas, J. A., Lonsdale, J. T., Moser, M. T., Gillard, B. M., Karasik, E., Ramsey, K., Choi, C., Foster, B. A., Syron, J., Fleming, J., Magazine, H., Hasz, R., Walters, G. D., Bridge, J. P., Miklos, M., Sullivan, S., Barker, L. K., Traino, H. M., Mosavel, M., Siminoff, L. A., Valley, D. R., Rohrer, D. C., Jewell, S. D., Branton, P. A., Sobin, L. H., Barcus, M., Qi, L., McLean, J., Hariharan, P., Um, K. S., Wu, S., Tabor, D., Shive, C., Smith, A. M., Buia, S. A., Undale, A. H., Robinson, K. L., Roche, N., Valentino, K. M., Britton, A., Burges, R., Bradbury, D., Hambright, K. W., Seleski, J., Korzeniewski, G. E., Erickson, K., Marcus, Y., Tejada, J., Taherian, M., Lu, C., Basile, M., Mash, D. C., Volpi, S., Struewing, J. P., Temple, G. F., Boyer, J., Colantuoni, D., Little, R., Koester, S., Carithers, L. J., Moore, H. M., Guan, P., Compton, C., Sawyer, S. J., Demchok, J. P., Vaught, J. B., Rabiner, C. A., Lockhart, N. C., Ardlie, K. G., Getz, G., Wright, F. A., Kellis, M., Volpi, S., & Dermitzakis, E. T.
- Affiliations
- Amélioration Génétique et Adaptation des Plantes méditerranéennes et tropicales (FR)
- ORCID
- Deluca, David S.
- Segrè, Ayellet V.
- Young, Taylor R.
- Maller, Julian B.
- Tukiainen, Taru
- Lek, Monkol
- Ward, Lucas D.
- Meng, Yan
- Palmer, Cameron D.
- Esko, Tõnu
- Winckler, Wendy
- Hirschhorn, Joel N.
- MacArthur, Daniel G.
- Shabalin, Andrey A.
- Li, Gen
- Zhou, Yi-Hui
- Nobel, Andrew B.
- Rusyn, Ivan
- Lappalainen, Tuuli
- Ferreira, Pedro G.
- Ongen, Halit
- Rivas, Manuel A.
- Battle, Alexis
- Mostafavi, Sara
- Monlong, Jean
- Sammeth, Michael
- Goldmann, Jakob M.
- Guigó, Roderic
- McCarthy, Mark I.
- Gamazon, Eric R.
- Im, Hae Kyung
- Konkashbaev, Anuar
- Nicolae, Dan L.
- Cox, Nancy J.
- Flutre, Timothée
- Wen, Xiaoquan
- Stephens, Matthew
- Pritchard, Jonathan K.
- Tu, Zhidong
- Zhang, Bin
- Huang, Tao
- Long, Quan
- Lin, Luan
- Yang, Jialiang
- Zhu, Jun
- Moser, Michael T.
- Gillard, Bryan M.
- Choi, Christopher
- Foster, Barbara A.
- Mosavel, Maghboeba
- Siminoff, Laura A.
- Rohrer, Daniel C.
- Jewell, Scott D.
- Branton, Philip A.
- Tabor, David
- Lu, Chunrong
- Mash, Deborah C.
- Struewing, Jeffery P.
- Moore, Helen M.
- Compton, Carolyn
- Sawyer, Sherilyn J.
- Venue
- Science
- Published
- 2015-05-08
- Volume
- 348
- Issue
- 6235
- Pages
- 648-660
- ISSN
- 0036-8075 (ISSN-L)
- 1095-9203
- PMC
- PMC4547484
- OpenAlex
- W1533942137
- Cited by
- 5,062
- References
- 82
- Citations by year
- 2026: 171 · 2025: 315 · 2024: 417 · 2023: 385 · 2022: 417 · 2021: 621 · 2020: 587 · 2019: 516 · 2018: 610 · 2017: 516 · 2016: 398 · 2015: 103
- FWCI
- 371.27
- Type
- journal article
- Language
- en
- Open access
- green
- www.ncbi.nlm.nih.gov
- Locations
- Science (publishedVersion)
- PubMed (publishedVersion)
- PubMed Central (acceptedVersion)
- Carolina Digital Repository (University of North Carolina at Chapel Hill) (submittedVersion)
- HAL (submittedVersion)
- UNC Libraries
- Funders
- U.S. National Institutes of Health
- NIH (HHSN261200800001E, R01 DA006227-17, R01 MH090941, R01 MH090951, R01 MH090937, R01 MH090936, R01 MH090948, R01 GM104371, R01AG046170, R01CA163772, U01AI111598-01)
- NIMH
- NIDA
- NIA
- NHLBI
- NHGRI
- NCI
- NIAID
- NINDS
- Office of the Director
- Roswell Park Cancer Institute (10XS171)
- Wellcome Trust (98381)
- European Research Council
- Louis-Jeantet Foundation
- Swiss National Science Foundation
- NDRI (10XS170)
- Science Care Inc. (10X172)
- IDOX (12ST1039)
- Van Andel Institute (10ST1035)
- Broad Institute (HHSN268201000029C)
- Clarendon Scholarship
- NDM Studentship
- Univ. of Oxford Green Templeton College Award
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Genetics › Genetic Associations and Epidemiology
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA Research and Splicing
- Keywords
- gene expression, tissue-specific gene regulation, expression quantitative trait loci, human genetic variation, regulatory networks, genome-wide association study, GTEx, RNA sequencing, tissue heterogeneity
- MeSH terms
- Alleles, Blood Pressure, Disease, Gene Expression Regulation, Multigene Family, Genotype, Humans, Organ Specificity, Pilot Projects, RNA Splicing, Genetic Variation, Genome, Human, Tibial Arteries, Sequence Analysis, RNA, GTPase-Activating Proteins, RNA, Untranslated, Quantitative Trait Loci, Gene Regulatory Networks, Genome-Wide Association Study, Transcriptome
About these checks
Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
Statistics and arithmetic are recomputed, not judged.
Confidence bands are shown only for fields calibrated on our annotated test set. None is calibrated yet, so no band is shown.
What counts as a claim ›How we measure confidence ›How we check this ›
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