The DOI matches its Crossref record; 84 of the 84 references it cites were found in a registry or an index.
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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In the citing paper
“NaV1.2 is widely expressed throughout the human central nervous system, but not in peripheral tissues [7,8].”
From Progress in Understanding and Treating SCN2A-Mediated Disorders (2018) · cites this paper as [7]
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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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Cites
Controlling the False Discovery Rate: A Practical and Powerful Approach to Multiple Testing
Benjamini, Y., & Hochberg, Y. (1995) · Journal of the Royal Statistical Society Series B: Statistical Methodology · doi:10.1111/j.2517-6161.1995.tb02031.x · Cited by 109,482
PLINK: a tool set for whole-genome association and population-based linkage analyses.
Purcell, S., Neale, B., Todd-Brown, K., Thomas, L., Ferreira, M. A. R., Bender, D., Maller, J., Sklar, P., de Bakker, P. I. W., Daly, M. J., et al. (2007) · The American Journal of Human Genetics · doi:10.1086/519795 · Cited by 34,089
Self-citationBEDTools: a flexible suite of utilities for comparing genomic features
Quinlan, A. R., & Hall, I. M. (2010) · Bioinformatics · doi:10.1093/bioinformatics/btq033 · Cited by 27,437
vegan: Community Ecology Package
Oksanen, J., Simpson, G. L., Blanchet, F. G., Kindt, R., Legendre, P., Minchin, P. R., O’Hara, R. B., Sólymos, P., Stevens, M. H. H., Szöcs, E., et al. (2001) · doi:10.32614/cran.package.vegan · Cited by 27,099
An integrated encyclopedia of DNA elements in the human genome
The ENCODE Project Consortium (2012) · Nature · doi:10.1038/nature11247 · Cited by 18,072
A new method for non-parametric multivariate analysis of variance
Anderson, M. J. (2001) · Austral Ecology · doi:10.1111/j.1442-9993.2001.01070.pp.x · Cited by 13,828
Mapping and quantifying mammalian transcriptomes by RNA-Seq
Mortazavi, A., Williams, B. A., McCue, K., Schaeffer, L., & Wold, B. (2008) · Nature Methods · doi:10.1038/nmeth.1226 · Cited by 13,696
TopHat: discovering splice junctions with RNA-Seq
Trapnell, C., Pachter, L. S., & Salzberg, S. L. (2009) · Bioinformatics · doi:10.1093/bioinformatics/btp120 · Cited by 11,682
A framework for variation discovery and genotyping using next-generation DNA sequencing data
DePristo, M. A., Banks, E., Poplin, R. E., Garimella, K. V., Maguire, J., Hartl, C., Philippakis, A., del Angel, G., Rivas, M. A., Hanna, M., et al. (2011) · Nature Genetics · doi:10.1038/ng.806 · Cited by 11,457
Self-citationPrincipal components analysis corrects for stratification in genome-wide association studies
Price, A. L., Patterson, N. J., Plenge, R. M., Weinblatt, M. E., Shadick, N. A., & Reich, D. (2006) · Nature Genetics · doi:10.1038/ng1847 · Cited by 10,248
Research works printed but not linked: 1
- H. Ongen E.T. Dermitzakis http://biorxiv.org/content/early/2015/01/22/014126 (2015).
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Hemani, G., Zheng, J., Elsworth, B., Wade, K. H., Haberland, V., Baird, D., Laurin, C., Burgess, S., Bowden, J., Langdon, R., et al. (2018) · eLife · doi:10.7554/elife.34408 · Cited by 7,959
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
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