The contribution of rare and low-frequency variants to human traits is largely unexplored. Here we describe insights from sequencing whole genomes (low read depth, 7×) or exomes (high read depth, 80×) of nearly 10,000 individuals from population-based and disease collections. In extensively phenotyped cohorts we characterize over 24 million novel sequence variants, generate a highly accurate imputation reference panel and identify novel alleles associated with levels of triglycerides (APOB), adiponectin (ADIPOQ) and low-density lipoprotein cholesterol (LDLR and RGAG1) from single-marker and rare variant aggregation tests. We describe population structure and functional annotation of rare and low-frequency variants, use the data to estimate the benefits of sequencing for association studies, and summarize lessons from disease-specific collections. Finally, we make available an extensive resource, including individual-level genetic and phenotypic data and web-based tools to facilitate the exploration of association results.

Gonçalo Abecasis, Francesco Cucca, David Schlessinger, Serena Sanna and colleagues report ~17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians. They assess the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We report ∼17.6 million genetic variants from whole-genome sequencing of 2,120 Sardinians; 22% are absent from previous sequencing-based compilations and are enriched for predicted functional consequences. Furthermore, ∼76,000 variants common in our sample (frequency >5%) are rare elsewhere (<0.5% in the 1000 Genomes Project). We assessed the impact of these variants on circulating lipid levels and five inflammatory biomarkers. We observe 14 signals, including 2 major new loci, for lipid levels and 19 signals, including 2 new loci, for inflammatory markers. The new associations would have been missed in analyses based on 1000 Genomes Project data, underlining the advantages of large-scale sequencing in this founder population.

Imputing genotypes from reference panels created by whole-genome sequencing (WGS) provides a cost-effective strategy for augmenting the single-nucleotide polymorphism (SNP) content of genome-wide arrays. The UK10K Cohorts project has generated a data set of 3,781 whole genomes sequenced at low depth (average 7x), aiming to exhaustively characterize genetic variation down to 0.1% minor allele frequency in the British population. Here we demonstrate the value of this resource for improving imputation accuracy at rare and low-frequency variants in both a UK and an Italian population. We show that large increases in imputation accuracy can be achieved by re-phasing WGS reference panels after initial genotype calling. We also present a method for combining WGS panels to improve variant coverage and downstream imputation accuracy, which we illustrate by integrating 7,562 WGS haplotypes from the UK10K project with 2,184 haplotypes from the 1000 Genomes Project. Finally, we introduce a novel approximation that maintains speed without sacrificing imputation accuracy for rare variants.

The development of massively parallel sequencing technologies enables the sequencing of total cDNA (RNA-Seq) to derive accurate measure of individual gene expression, differential splicing activity, and to discover novel regions of transcription, dramatically changing the way that the functional complexity of transcriptomes can be studied. Here we report on the first use of RNA-Seq to gain insight into the wide range of transcriptional responses that are associated with berry development in Vitis vinifera 'Corvina'. More than 59 million sequence reads, 36 to 44 bp in length, were generated from three developmental stages: post setting, véraison, and ripening. The sequence reads were aligned onto the 8.4-fold draft sequence of the Pinot Noir 40024 genome and then analyzed to measure gene expression levels, to detect alternative splicing events, and expressed single nucleotide polymorphisms. We detected 17,324 genes expressed during berry development, 6,695 of which were expressed in a stage-specific manner, suggesting differences in expression for genes in numerous functional categories and a significant transcriptional complexity. This exhaustive overview of gene expression dynamics demonstrates the utility of RNA-Seq for identifying single nucleotide polymorphisms and splice variants and for describing how plant transcriptomes change during development.