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.

Summary: Genotype imputation is a key step in the analysis of genome-wide association studies. Upcoming very large reference panels, such as those from The 1000 Genomes Project and the Haplotype Consortium, will improve imputation quality of rare and less common variants, but will also increase the computational burden. Here, we demonstrate how the application of software engineering techniques can help to keep imputation broadly accessible. Overall, these improvements speed up imputation by an order of magnitude compared with our previous implementation. Availability and implementation: minimac2, including source code, documentation, and examples is available at http://genome.sph.umich.edu/wiki/Minimac2 Contact:cfuchsb@umich.edu, goncalo@umich.edu

Background—: C-reactive protein (CRP) is a heritable marker of chronic inflammation that is strongly associated with cardiovascular disease. We sought to identify genetic variants that are associated with CRP levels. Methods and Results—: We performed a genome-wide association analysis of CRP in 66 185 participants from 15 population-based studies. We sought replication for the genome-wide significant and suggestive loci in a replication panel comprising 16 540 individuals from 10 independent studies. We found 18 genome-wide significant loci, and we provided evidence of replication for 8 of them. Our results confirm 7 previously known loci and introduce 11 novel loci that are implicated in pathways related to the metabolic syndrome ( APOC1 , HNF1A , LEPR , GCKR , HNF4A , and PTPN2 ) or the immune system ( CRP , IL6R , NLRP3 , IL1F10 , and IRF1 ) or that reside in regions previously not known to play a role in chronic inflammation ( PPP1R3B , SALL1 , PABPC4 , ASCL1 , RORA , and BCL7B ). We found a significant interaction of body mass index with LEPR ( P <2.9×10 ⁻⁶ ). A weighted genetic risk score that was developed to summarize the effect of risk alleles was strongly associated with CRP levels and explained ≈5% of the trait variance; however, there was no evidence for these genetic variants explaining the association of CRP with coronary heart disease. Conclusions—: We identified 18 loci that were associated with CRP levels. Our study highlights immune response and metabolic regulatory pathways involved in the regulation of chronic inflammation.