GTEx

Large stable releases (notably v6p and v8) distributing expression matrices, covariates, and variant calls; default inputs for TWAS, colocalization, and enrichment after GWAS.

Cell-type-specific eQTL analysis using computational deconvolution of bulk GTEx RNA-seq data across multiple tissues.

Single-cell pilots, additional molecular assays, and integration with other consortia complement the core bulk RNA-seq atlas and support finer-resolution interpretation of regulatory variation.

Analysis of genetic effects on gene expression using 7,051 RNA-seq samples from 449 donors across 44 tissues. Identified thousands of cis- and trans-eQTLs.

Description of the novel approach to high-quality postmortem tissue procurement for the GTEx project.

Comprehensive analysis of transcriptome variation across tissues and individuals, revealing that tissue identity is the primary driver of expression variation.

First comprehensive description of the GTEx project design, including tissue collection protocols, RNA-seq and genotyping methods, and the initial data release strategy.

Pilot analysis of RNA-seq data from ~175 donors across 43 tissues, demonstrating tissue-specific and shared cis-eQTL architecture.

Multitissue RNA-seq and genotyping in ~175 donors across 43 tissues; defined tissue-specific and shared cis-eQTL architecture and established GTEx as the reference expression resource.

Increased donor count, read depth, and tissue coverage with harmonized QC; broadened power for splicing QTLs, ASE, and cross-tissue meta-analysis.

Identification and analysis of splicing QTLs across 49 tissues in GTEx v8. sQTLs were less tissue-shared than eQTLs and enriched at GWAS loci.

Long-read RNA sequencing across GTEx tissues revealed extensive transcriptome variation including novel isoforms, fusion transcripts, and full-length isoform structures.

v8 flagship paper: comprehensive atlas of genetic regulatory effects across 49 human tissues from 838 donors. Includes cis-eQTL, trans-eQTL, sQTL, and expression correlation networks.

Landscape analysis of X chromosome inactivation across 29 tissues, identifying genes that escape XCI and demonstrating tissue-specific patterns with implications for sex-differences in complex traits.

rhyQTL (rhythmic QTL) — maps genetic determinants of 24-hour rhythmic gene expression across 45 GTEx tissues (838 individuals). Defines a new QTL class: rhyQTLs regulate gene rhythmicity (amplitude/phase/presence of daily cycle), distinct from eQTLs which regulate overall expression level. 63.8% of rhythmic genes show differential rhythmicity across genotypes; rhyQTLs explain median 15.8% of SNP heritability for 15 lipid traits. Only 3-37% of rhyQTLs overlap with eQTLs; rhyQTLs enriched in enhancer regions. Reveals ~4× more rhythmic genes than whole-population analyses.

24-hour biological rhythms are essential to maintain physiological homeostasis. Disruption of these rhythms increases the risks of multiple diseases. The biological rhythms are known to have a genetic basis formed by core clock genes, but how individual genetic variation shapes the oscillating transcriptome and contributes to human chronophysiology and disease risk is largely unknown. Here, we mapped interactions between temporal gene expression and genotype to identify quantitative trait loci (QTLs) contributing to rhythmic gene expression. These newly identified QTLs were termed as rhythmic QTLs (rhyQTLs), which determine previously unappreciated rhythmic genes in human subpopulations with specific genotypes. Our analyses of 45 human tissues from the Genotype-Tissue Expression (GTEx) project revealed thousands of rhythmic genes that would be otherwise obscured without stratifying by genetic variation. rhyQTLs and their associated rhythmic genes contribute extensively to essential chronophysiological processes, including bile acid and lipid metabolism. The identification of rhyQTLs sheds light on the genetic mechanisms of gene rhythmicity, offers mechanistic insights into variations in human disease risk, and enables precision chronotherapeutic approaches for patients.