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.

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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

Genetic analysis of a mouse model of major histocompatability complex (MHC)-associated autoimmune type 1 (insulin-dependent) diabetes mellitus (IDDM) has shown that the disease is caused by a combination of a major effect at the MHC and at least ten other susceptibility loci elsewhere in the genome. A genome-wide scan of 93 affected sibpair families (ASP) from the UK (UK93) indicated a similar genetic basis for human type 1 diabetes, with the major genetic component at the MHC locus (IDDM1) explaining 34% of the familial clustering of the disease (lambda(s)=2.5; refs 3,4). In the present report, we have analysed a further 263 multiplex families from the same population (UK263) to provide a total UK data set of 356 ASP families (UK356). Only four regions of the genome outside IDDM1/MHC, which was still the only major locus detected, were not excluded at lambda(s)=3 and lod=-2, of which two showed evidence of linkage: chromosome 10p13-p11 (maximum lod score (MLS)=4.7, P=3x10(-6), lambda(s)=1.56) and chromosome 16q22-16q24 (MLS=3.4, P=6.5x10(-5), lambda(s)=1.6). These and other novel regions, including chromosome 14q12-q21 and chromosome 19p13-19q13, could potentially harbour disease loci but confirmation and fine mapping cannot be pursued effectively using conventional linkage analysis. Instead, more powerful linkage disequilibrium-based and haplotype mapping approaches must be used; such data is already emerging for several type 1 diabetes loci detected initially by linkage.