No abstract

The 1000 Genomes Project (1kGP), launched in 2008, is the largest fully open resource of whole genome sequencing (WGS) data consented for public distribution of raw sequence data without access or use restrictions. The final (phase 3) 2015 release of 1kGP included 2,504 unrelated samples from 26 populations, representing five continental regions of the world and was based on a combination of technologies including low coverage WGS (mean depth 7.4X), high coverage whole exome sequencing (mean depth 65.7X), and microarray genotyping. Here, we present a new, high coverage WGS resource encompassing the original 2,504 1kGP samples, as well as an additional 698 related samples that result in 602 complete trios in the 1kGP cohort. We sequenced this expanded 1kGP cohort of 3,202 samples to a targeted depth of 30X using Illumina NovaSeq 6000 instruments. We performed SNV/INDEL calling against the GRCh38 reference using GATK HaplotypeCaller, and generated a comprehensive set of SVs by integrating multiple analytic methods through a sophisticated machine learning model, upgrading the 1kGP dataset to current state-of-the-art standards. Using this strategy, we defined over 111 million SNVs, 14 million INDELs, and ~170 thousand SVs across the entire cohort of 3,202 samples with estimated false discovery rate (FDR) of 0.3%, 1.0%, and 1.8%, respectively. By comparison to the low-coverage phase 3 callset, we observed substantial improvements in variant discovery and estimated FDR that were facilitated by high coverage re-sequencing and expansion of the cohort. Specifically, we called 7% more SNVs, 59% more INDELs, and 170% more SVs per genome than the phase 3 callset. Moreover, we leveraged the presence of families in the cohort to achieve superior haplotype phasing accuracy and we demonstrate improvements that the high coverage panel brings especially for INDEL imputation. We make all the data generated as part of this project publicly available and we envision this updated version of the 1kGP callset to become the new de facto public resource for the worldwide scientific community working on genomics and genetics.

Identifying large expansions of short tandem repeats (STRs), such as those that cause amyotrophic lateral sclerosis (ALS) and fragile X syndrome, is challenging for short-read whole-genome sequencing (WGS) data. A solution to this problem is an important step toward integrating WGS into precision medicine. We developed a software tool called ExpansionHunter that, using PCR-free WGS short-read data, can genotype repeats at the locus of interest, even if the expanded repeat is larger than the read length. We applied our algorithm to WGS data from 3001 ALS patients who have been tested for the presence of the C9orf72 repeat expansion with repeat-primed PCR (RP-PCR). Compared against this truth data, ExpansionHunter correctly classified all (212/212, 95% CI [0.98, 1.00]) of the expanded samples as either expansions (208) or potential expansions (4). Additionally, 99.9% (2786/2789, 95% CI [0.997, 1.00]) of the wild-type samples were correctly classified as wild type by this method with the remaining three samples identified as possible expansions. We further applied our algorithm to a set of 152 samples in which every sample had one of eight different pathogenic repeat expansions, including those associated with fragile X syndrome, Friedreich's ataxia, and Huntington's disease, and correctly flagged all but one of the known repeat expansions. Thus, ExpansionHunter can be used to accurately detect known pathogenic repeat expansions and provides researchers with a tool that can be used to identify new pathogenic repeat expansions.

Heritability, the proportion of phenotypic variance explained by genetic factors, can be estimated from pedigree data 1 , but such estimates are uninformative with respect to the underlying genetic architecture. Analyses of data from genome-wide association studies (GWAS) on unrelated individuals have shown that for human traits and disease, approximately one-third to two-thirds of heritability is captured by common SNPs 2-5 . It is not known whether the remaining heritability is due to the imperfect tagging of causal variants by common SNPs, in particular if the causal variants are rare, or other reasons such as overestimation of heritability from pedigree data. Here we show that pedigree heritability for height and body mass index (BMI) appears to be fully recovered from whole-genome sequence (WGS) data on 21,620 unrelated individuals of European ancestry. We assigned 47.1 million genetic variants to groups based upon their minor allele frequencies (MAF) and linkage disequilibrium (LD) with variants nearby, and estimated and partitioned variation accordingly. The estimated heritability was 0.79 (SE 0.09) for height and 0.40 (SE 0.09) for BMI, consistent with pedigree estimates. Low-MAF variants in low LD with neighbouring variants were enriched for heritability, to a greater extent for protein altering variants, consistent with negative selection thereon. Cumulatively variants in the MAF range of 0.0001 to 0.1 explained 0.54 (SE 0.05) and 0.51 (SE 0.11) of heritability for height and BMI, respectively. Our results imply that the still missing heritability of complex traits and disease is accounted for by rare variants, in particular those in regions of low LD.

In Caenorhabditis elegans, the dosage compensation complex (DCC) specifically binds to and represses transcription from both X chromosomes in hermaphrodites. The DCC is composed of an X-specific condensin complex that interacts with several proteins. During embryogenesis, DCC starts localizing to the X chromosomes around the 40-cell stage, and is followed by X-enrichment of H4K20me1 between 100-cell to comma stage. Here, we analyzed dosage compensation of the X chromosome between sexes, and the roles of dpy-27 (condensin subunit), dpy-21 (non-condensin DCC member), set-1 (H4K20 monomethylase) and set-4 (H4K20 di-/tri-methylase) in X chromosome repression using mRNA-seq and ChIP-seq analyses across several developmental time points. We found that the DCC starts repressing the X chromosomes by the 40-cell stage, but X-linked transcript levels remain significantly higher in hermaphrodites compared to males through the comma stage of embryogenesis. Dpy-27 and dpy-21 are required for X chromosome repression throughout development, but particularly in early embryos dpy-27 and dpy-21 mutations produced distinct expression changes, suggesting a DCC independent role for dpy-21. We previously hypothesized that the DCC increases H4K20me1 by reducing set-4 activity on the X chromosomes. Accordingly, in the set-4 mutant, H4K20me1 increased more from the autosomes compared to the X, equalizing H4K20me1 level between X and autosomes. H4K20me1 increase on the autosomes led to a slight repression, resulting in a relative effect of X derepression. H4K20me1 depletion in the set-1 mutant showed greater X derepression compared to equalization of H4K20me1 levels between X and autosomes in the set-4 mutant, indicating that H4K20me1 level is important, but X to autosomal balance of H4K20me1 contributes only slightly to X-repression. Thus H4K20me1 by itself is not a downstream effector of the DCC. In summary, X chromosome dosage compensation starts in early embryos as the DCC localizes to the X, and is strengthened in later embryogenesis by H4K20me1.