Understanding the functional consequences of genetic variation, and how it affects complex human disease and quantitative traits, remains a critical challenge for biomedicine. We present an analysis of RNA sequencing data from 1641 samples across 43 tissues from 175 individuals, generated as part of the pilot phase of the Genotype-Tissue Expression (GTEx) project. We describe the landscape of gene expression across tissues, catalog thousands of tissue-specific and shared regulatory expression quantitative trait loci (eQTL) variants, describe complex network relationships, and identify signals from genome-wide association studies explained by eQTLs. These findings provide a systematic understanding of the cellular and biological consequences of human genetic variation and of the heterogeneity of such effects among a diverse set of human tissues.

Transcriptional regulation and posttranscriptional processing underlie many cellular and organismal phenotypes. We used RNA sequence data generated by Genotype-Tissue Expression (GTEx) project to investigate the patterns of transcriptome variation across individuals and tissues. Tissues exhibit characteristic transcriptional signatures that show stability in postmortem samples. These signatures are dominated by a relatively small number of genes—which is most clearly seen in blood—though few are exclusive to a particular tissue and vary more across tissues than individuals. Genes exhibiting high interindividual expression variation include disease candidates associated with sex, ethnicity, and age. Primary transcription is the major driver of cellular specificity, with splicing playing mostly a complementary role; except for the brain, which exhibits a more divergent splicing program. Variation in splicing, despite its stochasticity, may play in contrast a comparatively greater role in defining individual phenotypes.

Better methods are needed to assess mast-cell activation in vivo and to distinguish the activation of mast cells from that of basophils. Tryptase, a neutral protease selectively concentrated in the secretory granules of human mast cells (but not basophils), is released by mast cells together with histamine and serves as a marker of mast-cell activation. In 17 patients with systemic mastocytosis, concentrations of tryptase in plasma were linearly related to those of histamine (P less than 0.01). Eleven of the 17 patients had tryptase levels of 4 to 88 ng per milliliter, indicating ongoing mast-cell activation. In each of six patients who experienced corresponding anaphylactic reactions after penicillin, aspirin, or melon ingestion, a wasp sting, exercise, or antilymphocyte globulin injection, tryptase levels in serum ranged from 9 to 75 ng per milliliter, indicating mast-cell activation during each of these events. In contrast, serum tryptase levels were less than 5 ng per milliliter in all patients presenting with myocardial disease (n = 8, 6 with hypotension) or sepsis (n = 6, 3 with hypotension) and in the controls (n = 20). One patient had a myocardial infarction after anaphylaxis in response to a wasp sting and an elevated tryptase level of 25 ng per milliliter. Thus, the plasma or serum tryptase level is a diagnostic correlate of mast-cell-related events.

There is a striking and unexplained male predominance across many cancer types. A subset of X chromosome (chrX) genes can escape X-inactivation, which would protect females from complete functional loss by a single mutation. To identify putative “Escape from X-Inactivation Tumor Suppressor” (EXITS) genes, we compared somatic alterations from >4100 cancers across 21 tumor types for sex bias. Six of 783 non-pseudoautosomal region (PAR) chrX genes (ATRX, CNKSR2, DDX3X, KDM5C, KDM6A, and MAGEC3) more frequently harbored loss-of-function mutations in males (based on false discovery rate <0.1), compared to zero of 18,055 autosomal and PAR genes (P<0.0001). Male-biased mutations in genes that escape X-inactivation were observed in combined analysis across many cancers and in several individual tumor types, suggesting a generalized phenomenon. We conclude that biallelic expression of EXITS genes in females explains a portion of the reduced cancer incidence compared to males across a variety of tumor types.

Accurate prediction of the functional impact of genetic variation is critical for clinical genome interpretation. We systematically characterized the transcriptome effects of protein-truncating variants (PTVs), a class of variants expected to have profound impacts on gene function, using data from the Genotype-Tissue Expression (GTEx) and Geuvadis projects. We quantitate tissue-specific and positional effects on nonsense-mediated transcript decay, and present an improved predictive model for this decay. We directly measure the impact of variants both proximal and distal to splice junctions. Furthermore, we find that robustness to heterozygous gene inactivation is not due to dosage compensation. Our results illustrate the value of transcriptome data in the functional interpretation of genetic variants.