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.

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 v8 data, based on 17,382 RNA-sequencing samples from 54 tissues of 948 post-mortem 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.

“Orangutan” is derived from the Malay term “man of the forest” and aptly describes the Southeast Asian great apes native to Sumatra and Borneo. The orangutan species, Pongo abelii (Sumatran) and Pongo pygmaeus (Bornean), are the most phylogenetically distant great apes from humans, thereby providing an informative perspective on hominid evolution. Here we present a Sumatran orangutan draft genome assembly and short read sequence data from five Sumatran and five Bornean orangutan genomes. Our analyses reveal that, compared to other primates, the orangutan genome has many unique features. Structural evolution of the orangutan genome has proceeded much more slowly than other great apes, evidenced by fewer rearrangements, less segmental duplication, a lower rate of gene family turnover and surprisingly quiescent Alu repeats, which have played a major role in restructuring other primate genomes. We also describe the first primate polymorphic neocentromere, found in both Pongo species, emphasizing the gradual evolution of orangutan genome structure. Orangutans have extremely low energy usage for a eutherian mammal1, far lower than their hominid relatives. Adding their genome to the repertoire of sequenced primates illuminates new signals of positive selection in several pathways including glycolipid metabolism. From the population perspective, both Pongo species are deeply diverse; however, Sumatran individuals possess greater diversity than their Bornean counterparts, and more species-specific variation. Our estimate of Bornean/Sumatran speciation time, 400k years ago (ya), is more recent than most previous studies and underscores the complexity of the orangutan speciation process. Despite a smaller modern census population size, the Sumatran effective population size (Ne) expanded exponentially relative to the ancestral Ne after the split, while Bornean Ne declined over the same period. Overall, the resources and analyses presented here offer new opportunities in evolutionary genomics, insights into hominid biology, and an extensive database of variation for conservation efforts.

Many complex human phenotypes exhibit sex-differentiated characteristics. However, the molecular mechanisms underlying these differences remain largely unknown. We generated a catalog of sex differences in gene expression and in the genetic regulation of gene expression across 44 human tissue sources surveyed by the Genotype-Tissue Expression project (GTEx, v8 release). We demonstrate that sex influences gene expression levels and cellular composition of tissue samples across the human body. A total of 37% of all genes exhibit sex-biased expression in at least one tissue. We identify cis expression quantitative trait loci (eQTLs) with sex-differentiated effects and characterize their cellular origin. By integrating sex-biased eQTLs with genome-wide association study data, we identify 58 gene-trait associations that are driven by genetic regulation of gene expression in a single sex. These findings provide an extensive characterization of sex differences in the human transcriptome and its genetic regulation.

Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in non-blood, disease-relevant tissue types. Here we characterize variability in TL measurements for 6,391 tissue samples, representing >20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) Project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation impacts TL in multiple tissue types, and that TL can mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health. ONE SENTENCE SUMMARYTelomere length varies by tissue type but is generally correlated among tissue types (positively) and with age (negatively). MAIN TEXTTelomeres are DNA-protein complexes located at the end of chromosomes that protect chromosome ends from degradation and fusion (1). The length of the DNA component of telomeres shortens as cells divide (2) with short telomeres eventually triggering cellular senescence (3,4). In most human tissues, TL gradually shortens over the life course, and TL shortening is considered a hallmark (and a potential underlying cause) of human aging (5). In human studies, short TL measured in leukocytes is associated with increased risk of aging-related diseases including cardiovascular disease (6) and type II diabetes (7) as well as all-cause mortality (8). However, long TL may increase risk for some types of cancer (9-11). Leukocyte TL is influenced by inherited genetic variation (single nucleotide polymorphisms [SNPs]), some of which reside near genes with roles in telomere maintenance (12)(13)(14)(15). Leukocyte TL is also associated with lifestyle factors (e.g., obesity) and exposures (e.g., cigarette smoking) (16,17).Epidemiologic studies of TL predominantly use blood (occasionally saliva) as a DNA source. Thus, our understanding of variation in TL, its determinants (e.g., demographic, lifestyle, and genetic factors), and its associations with disease phenotypes is based almost entirely on TL measured in leukocytes from whole blood. Few prior studies have compared TL in leukocytes to TL in other human tissue types; these prior studies are relatively small (<100 participants; <5 tissue types) but provide evidence that TL differs across tissue types and that TL measurements from different tissue types are correlated (18,19). However, larger studies of many additional tissue types are needed to gain a comprehensive understanding of variation in TL and its determinants within and across a wide range of human tissues and cell types. In order to address these gaps in our understanding of TL and its role as a biomarker of aging and disease risk, we measured TL in > 6,000 unique tissue samples, representing >20 distinct tissue types and > 950 individual don...

Telomere shortening is a hallmark of aging. Telomere length (TL) in blood cells has been studied extensively as a biomarker of human aging and disease; however, little is known regarding variability in TL in nonblood, disease-relevant tissue types. Here, we characterize variability in TLs from 6391 tissue samples, representing >20 tissue types and 952 individuals from the Genotype-Tissue Expression (GTEx) project. We describe differences across tissue types, positive correlation among tissue types, and associations with age and ancestry. We show that genetic variation affects TL in multiple tissue types and that TL may mediate the effect of age on gene expression. Our results provide the foundational knowledge regarding TL in healthy tissues that is needed to interpret epidemiological studies of TL and human health.

The Genotype-Tissue Expression (GTEx) project has identified expression and splicing quantitative trait loci in cis (QTLs) for the majority of genes across a wide range of human tissues. However, the functional characterization of these QTLs has been limited by the heterogeneous cellular composition of GTEx tissue samples. We mapped interactions between computational estimates of cell type abundance and genotype to identify cell type–interaction QTLs for seven cell types and show that cell type–interaction expression QTLs (eQTLs) provide finer resolution to tissue specificity than bulk tissue cis-eQTLs. Analyses of genetic associations with 87 complex traits show a contribution from cell type–interaction QTLs and enables the discovery of hundreds of previously unidentified colocalized loci that are masked in bulk tissue.

Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each of a diverse set of tissues. We used the Genotype-Tissue Expression (GTEx) project v6 RNA sequencing data across 50 tissues and 449 individuals. First, we developed a framework called Transcriptome-Wide Networks (TWNs) for combining total expression and relative isoform levels into a single sparse network, capturing the interplay between the regulation of splicing and transcription. We built TWNs for 16 tissues and found that hubs in these networks were strongly enriched for splicing and RNA binding genes, demonstrating their utility in unraveling regulation of splicing in the human transcriptome. Next, we used a Bayesian biclustering model that identifies network edges unique to a single tissue to reconstruct Tissue-Specific Networks (TSNs) for 26 distinct tissues and 10 groups of related tissues. Finally, we found genetic variants associated with pairs of adjacent nodes in our networks, supporting the estimated network structures and identifying 20 genetic variants with distant regulatory impact on transcription and splicing. Our networks provide an improved understanding of the complex relationships of the human transcriptome across tissues.