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.

To better understand the molecular and cellular differences in brain organization between human and non-human primates, we performed transcriptome sequencing of sixteen regions of adult human, chimpanzee, and macaque brains. Integration with human single-cell transcriptomic data revealed global, regional, and cell-type specific species expression differences in genes representing distinct functional categories. We validated and further characterized the human specificity of genes enriched in distinct cell types through histological and functional analyses, including rare subpallial-derived interneurons expressing dopamine biosynthesis genes enriched in the human striatum and absent in the non-human African ape neocortex. Our integrated analysis of the generated data revealed diverse molecular and cellular features of the phylogenetic reorganization of the human brain across multiple levels of organization, with relevance for brain function and disease.

Aging is one of the most important biological processes and is a known risk factor for many age-related diseases in human. Studying age-related transcriptomic changes in tissues across the whole body can provide valuable information for a holistic understanding of this fundamental process. In this work, we catalogue age-related gene expression changes in nine tissues from nearly two hundred individuals collected by the Genotype-Tissue Expression (GTEx) project. In general, we find the aging gene expression signatures are very tissue specific. However, enrichment for some well-known aging components such as mitochondria biology is observed in many tissues. Different levels of cross-tissue synchronization of age-related gene expression changes are observed, and some essential tissues (e.g., heart and lung) show much stronger “co-aging” than other tissues based on a principal component analysis. The aging gene signatures and complex disease genes show a complex overlapping pattern and only in some cases, we see that they are significantly overlapped in the tissues affected by the corresponding diseases. In summary, our analyses provide novel insights to the co-regulation of age-related gene expression in multiple tissues; it also presents a tissue-specific view of the link between aging and age-related diseases.

Puerto Rico and the surrounding islands rest on the eastern fringe of the Caribbean's Greater Antilles, located less than 100 miles northwest of the Lesser Antilles. Puerto Ricans are genetic descendants of pre-Columbian peoples, as well as peoples of European and African descent through 500 years of migration to the island. To infer these patterns of pre-Columbian and historic peopling of the Caribbean, we characterized genetic diversity in 326 individuals from the southeastern region of Puerto Rico and the island municipality of Vieques. We sequenced the mitochondrial DNA (mtDNA) control region of all of the samples and the complete mitogenomes of 12 of them to infer their putative place of origin. In addition, we genotyped 121 male samples for 25 Y-chromosome single nucleotide polymorphism and 17 STR loci. Approximately 60% of the participants had indigenous mtDNA haplotypes (mostly from haplogroups A2 and C1), while 25% had African and 15% European haplotypes. Three A2 sublineages were unique to the Greater Antilles, one of which was similar to Mesoamerican types, while C1b haplogroups showed links to South America, suggesting that people reached the island from the two distinct continental source areas. However, none of the male participants had indigenous Y-chromosomes, with 85% of them instead being European/Mediterranean and 15% sub-Saharan African in origin. West Eurasian Y-chromosome short tandem repeat haplotypes were quite diverse and showed similarities to those observed in southern Europe, North Africa and the Middle East. These results attest to the distinct, yet equally complex, pasts for the male and female ancestors of modern day Puerto Ricans.

No abstract

Cardiomyopathy (CMP) is a heritable disorder. Over 50% of cases are gene-elusive on clinical gene panel testing. The contribution of variants in non-coding DNA elements that result in cryptic splicing and regulate gene expression has not been explored. We analyzed whole-genome sequencing (WGS) data in a discovery cohort of 209 pediatric CMP patients and 1953 independent replication genomes and exomes. We searched for protein-coding variants, and non-coding variants predicted to affect the function or expression of genes. Thirty-nine percent of cases harbored pathogenic coding variants in known CMP genes, and 5% harbored high-risk loss-of-function (LoF) variants in additional candidate CMP genes. Fifteen percent harbored high-risk regulatory variants in promoters and enhancers of CMP genes (odds ratio 2.25, p = 6.70 × 10−7 versus controls). Genes involved in α-dystroglycan glycosylation (FKTN, DTNA) and desmosomal signaling (DSC2, DSG2) were most highly enriched for regulatory variants (odds ratio 6.7–58.1). Functional effects were confirmed in patient myocardium and reporter assays in human cardiomyocytes, and in zebrafish CRISPR knockouts. We provide strong evidence for the genomic contribution of functionally active variants in new genes and in regulatory elements of known CMP genes to early onset CMP.