The 1000 Genomes Project set out to provide a comprehensive description of common human genetic variation by applying whole-genome sequencing to a diverse set of individuals from multiple populations. Here we report completion of the project, having reconstructed the genomes of 2,504 individuals from 26 populations using a combination of low-coverage whole-genome sequencing, deep exome sequencing, and dense microarray genotyping. We characterized a broad spectrum of genetic variation, in total over 88 million variants (84.7 million single nucleotide polymorphisms (SNPs), 3.6 million short insertions/deletions (indels), and 60,000 structural variants), all phased onto high-quality haplotypes. This resource includes >99% of SNP variants with a frequency of >1% for a variety of ancestries. We describe the distribution of genetic variation across the global sample, and discuss the implications for common disease studies.
We describe the landscape of somatic genomic alterations based on multi-dimensional and comprehensive characterization of more than 500 glioblastoma tumors (GBMs). We identify several novel mutated genes as well as complex rearrangements of signature receptors including EGFR and PDGFRA. TERT promoter mutations are shown to correlate with elevated mRNA expression, supporting a role in telomerase reactivation. Correlative analyses confirm that the survival advantage of the proneural subtype is conferred by the G-CIMP phenotype, and MGMT DNA methylation may be a predictive biomarker for treatment response only in classical subtype GBM. Integrative analysis of genomic and proteomic profiles challenges the notion of therapeutic inhibition of a pathway as an alternative to inhibition of the target itself. These data will facilitate the discovery of therapeutic and diagnostic target candidates, the validation of research and clinical observations and the generation of unanticipated hypotheses that can advance our molecular understanding of this lethal cancer.
Summary Structural variants (SVs) are implicated in numerous diseases and make up the majority of varying nucleotides among human genomes. Here we describe an integrated set of eight SV classes comprising both balanced and unbalanced variants, which we constructed using short-read DNA sequencing data and statistically phased onto haplotype-blocks in 26 human populations. Analyzing this set, we identify numerous gene-intersecting SVs exhibiting population stratification and describe naturally occurring homozygous gene knockouts suggesting the dispensability of a variety of human genes. We demonstrate that SVs are enriched on haplotypes identified by genome-wide association studies and exhibit enrichment for expression quantitative trait loci. Additionally, we uncover appreciable levels of SV complexity at different scales, including genic loci subject to clusters of repeated rearrangement and complex SVs with multiple breakpoints likely formed through individual mutational events. Our catalog will enhance future studies into SV demography, functional impact and disease association.
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Summary Genomic structural variants (SVs) are abundant in humans, differing from other variation classes in extent, origin, and functional impact. Despite progress in SV characterization, the nucleotide resolution architecture of most SVs remains unknown. We constructed a map of unbalanced SVs (i.e., copy number variants) based on whole genome DNA sequencing data from 185 human genomes, integrating evidence from complementary SV discovery approaches with extensive experimental validations. Our map encompassed 22,025 deletions and 6,000 additional SVs, including insertions and tandem duplications. Most SVs (53%) were mapped to nucleotide resolution, which facilitated analyzing their origin and functional impact. We examined numerous whole and partial gene deletions with a genotyping approach and observed a depletion of gene disruptions amongst high frequency deletions. Furthermore, we observed differences in the size spectra of SVs originating from distinct formation mechanisms, and constructed a map constructed a map of SV hotspots formed by common mechanisms. Our analytical framework and SV map serves as a resource for sequencing-based association studies.
The pan-cancer analysis of whole genomes The expansion of whole-genome sequencing studies from individual ICGC and TCGA working groups presented the opportunity to undertake a meta-analysis of genomic features across tumour types. To achieve this, the PCAWG Consortium was established. A Technical Working Group implemented the informatics analyses by aggregating the raw sequencing data from different working groups that studied individual tumour types, aligning the sequences to the human genome and delivering a set of high-quality somatic mutation calls for downstream analysis (Extended Data Fig. 1). Given the recent meta-analysis
The INK4a gene encodes two distinct growth inhibitors--the cyclin-dependent kinase inhibitor p16Ink4a, which is a component of the Rb pathway, and the tumor suppressor p19Arf, which has been functionally linked to p53. Here we show that p19Arf potently suppresses oncogenic transformation in primary cells and that this function is abrogated when p53 is neutralized by viral oncoproteins and dominant-negative mutants but not by the p53 antagonist MDM2. This finding, coupled with the observations that p19Arf and MDM2 physically interact and that p19Rrf blocks MDM2-induced p53 degradation and transactivational silencing, suggests that p19Arf functions mechanistically to prevent MDM2's neutralization of p53. Together, our findings ascribe INK4a's potent tumor suppressor activity to the cooperative actions of its two protein products and their relation to the two central growth control pathways, Rb and p53.
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