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Sumstats Transcriptomics

Curation of Transcriptomics — listings under the Summary statistics tab.

Summary Table

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NAME Main citation YEAR
GTEx
GTEx Consortium, Science, 2020
2020
GTEx
GTEx Consortium, Science, 2020
2020
eQTLGen Phase II
eQTLGen Consortium
NA
eQTLGen Phase I
Võsa U et al., Nat Genet, 2021
2021

GTEx

Summary statistics
PUBMED_LINK
32913098
DESCRIPTION
V10
URL
https://gtexportal.org/home/
TITLE
The GTEx Consortium atlas of genetic regulatory effects across human tissues.
Main citation
GTEx Consortium. (2020) The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science, 369 (6509) 1318-1330. doi:10.1126/science.aaz1776. PMID 32913098
ABSTRACT
The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
DOI
10.1126/science.aaz1776

GTEx

Summary statistics
PUBMED_LINK
32913098
DESCRIPTION
V11 GTEx V11 updates the GTEx V10 data to use GENCODE 47 annotation. It contains no new samples or donors compared to V10.
URL
https://gtexportal.org/home/
TITLE
The GTEx Consortium atlas of genetic regulatory effects across human tissues.
Main citation
GTEx Consortium. (2020) The GTEx Consortium atlas of genetic regulatory effects across human tissues. Science, 369 (6509) 1318-1330. doi:10.1126/science.aaz1776. PMID 32913098
ABSTRACT
The Genotype-Tissue Expression (GTEx) project was established to characterize genetic effects on the transcriptome across human tissues and to link these regulatory mechanisms to trait and disease associations. Here, we present analyses of the version 8 data, examining 15,201 RNA-sequencing samples from 49 tissues of 838 postmortem donors. We comprehensively characterize genetic associations for gene expression and splicing in cis and trans, showing that regulatory associations are found for almost all genes, and describe the underlying molecular mechanisms and their contribution to allelic heterogeneity and pleiotropy of complex traits. Leveraging the large diversity of tissues, we provide insights into the tissue specificity of genetic effects and show that cell type composition is a key factor in understanding gene regulatory mechanisms in human tissues.
DOI
10.1126/science.aaz1776

eQTLGen Phase I

Summary statistics
PUBMED_LINK
34475573
URL
https://www.eqtlgen.org/
TITLE
Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression.
Main citation
Võsa U, Claringbould A, Westra HJ, Bonder MJ, ...&, Franke L. (2021) Large-scale cis- and trans-eQTL analyses identify thousands of genetic loci and polygenic scores that regulate blood gene expression. Nat Genet, 53 (9) 1300-1310. doi:10.1038/s41588-021-00913-z. PMID 34475573
ABSTRACT
Trait-associated genetic variants affect complex phenotypes primarily via regulatory mechanisms on the transcriptome. To investigate the genetics of gene expression, we performed cis- and trans-expression quantitative trait locus (eQTL) analyses using blood-derived expression from 31,684 individuals through the eQTLGen Consortium. We detected cis-eQTL for 88% of genes, and these were replicable in numerous tissues. Distal trans-eQTL (detected for 37% of 10,317 trait-associated variants tested) showed lower replication rates, partially due to low replication power and confounding by cell type composition. However, replication analyses in single-cell RNA-seq data prioritized intracellular trans-eQTL. Trans-eQTL exerted their effects via several mechanisms, primarily through regulation by transcription factors. Expression of 13% of the genes correlated with polygenic scores for 1,263 phenotypes, pinpointing potential drivers for those traits. In summary, this work represents a large eQTL resource, and its results serve as a starting point for in-depth interpretation of complex phenotypes.
DOI
10.1038/s41588-021-00913-z

eQTLGen Phase II

Summary statistics
DESCRIPTION
Expanded blood eQTL meta-analysis and genome-wide summary statistics across cohorts; consortium coordination, cookbook, and downloads via the Phase II portal.
URL
https://www.eqtlgen.org/
TITLE
eQTLGen Phase II (blood eQTL consortium resource).
Main citation
eQTLGen Consortium. eQTLGen Phase II (blood eQTL consortium resource).