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.

Most great ape genetic variation remains uncharacterized; however,\ud its study is critical for understanding population history, recombination,\ud selection and susceptibility to disease.Herewe sequence\ud to high coverage a total of 79 wild- and captive-born individuals\ud representing all six great ape species and seven subspecies and report\ud 88.8 million single nucleotide polymorphisms. Our analysis provides\ud support for genetically distinct populations within each species,\ud signals of gene flow, and the split of common chimpanzees\ud into two distinct groups: Nigeria–Cameroon/western and central/\ud eastern populations.We find extensive inbreeding in almost all wild\ud populations, with eastern gorillas being the most extreme. Inferred\ud effective population sizes have varied radically over timein different\ud lineages and this appears to have a profound effect on the genetic\ud diversity at, or close to, genes in almost all species. We discover and\ud assign 1,982 loss-of-function variants throughout the human and\ud great ape lineages, determining that the rate of gene loss has not\ud been different in the human branch compared to other internal\ud branches in the great ape phylogeny. This comprehensive catalogue\ud of great ape genomediversity provides a framework for understanding\ud evolution and a resource for more effective management of wild\ud and captive great ape populations

The search for a method that utilizes biological information to predict humans’ place of origin has occupied scientists for millennia. Over the past four decades, scientists have employed genetic data in an effort to achieve this goal but with limited success. While biogeographical algorithms using next-generation sequencing data have achieved an accuracy of 700 km in Europe, they were inaccurate elsewhere. Here we describe the Geographic Population Structure (GPS) algorithm and demonstrate its accuracy with three data sets using 40,000–130,000 SNPs. GPS placed 83% of worldwide individuals in their country of origin. Applied to over 200 Sardinians villagers, GPS placed a quarter of them in their villages and most of the rest within 50 km of their villages. GPS’s accuracy and power to infer the biogeography of worldwide individuals down to their country or, in some cases, village, of origin, underscores the promise of admixture-based methods for biogeography and has ramifications for genetic ancestry testing.