Cohort-wide deep whole genome sequencing and the allelic architecture of complex traits

Abstract

The role of rare variants in complex traits remains uncharted. Here, we conduct deep whole genome sequencing of 1,457 individuals from an isolated population, and test for rare variant burdens across six cardiometabolic traits. We identify a role for rare regulatory variation, which has hitherto been missed. We find evidence of rare variant burdens overlapping with, and mostly independent of established common variant signals (ADIPOQ and adiponectin, P=4.2x10 -8 ; APOC3 and triglyceride levels, P=1.58×10 -26 ; GGT1 and gamma-glutamyltransferase, P=2.3x10 -6 ; UGT1A9 and bilirubin, P=1.9×10 -8 ), and identify replicating evidence for a burden associated with triglyceride levels in FAM189A (P=2.26x10 -8 ), indicating a role for this gene in lipid metabolism.The role of rare sequence variants in the genetic architecture of medically-relevant complex traits is not well-understood. Population-scale deep whole genome sequencing can capture genetic variation across the entire allele frequency spectrum traversing the coding and noncoding genome. Here, to improve our understanding of the role of rare variants, we perform cohort-wide deep whole genome sequencing of 1,457 individuals from a deeplyphenotyped, isolated population from Crete, Greece (the HELIC-MANOLIS cohort 1-3 ) at an average depth of 22.5x ( Supplementary Figure 1), capturing 98% of true single nucleotide variants (SNVs) (Online Methods and Supplementary Figure 2). We address open questions on whole genome sequencing study design, analysis and interpretation, and identify burdens of coding and regulatory rare variants associated with cardiometabolic traits. RESULTS Effect of sequencing depthComparing whole genome sequencing at various depths ranging from 15x to 30x (Online Methods), we find that 96.4% of singletons, 97.9% of doubletons and 97.6% of variants called using 30x sequencing are recapitulated at 22.5x depth. Genotype accuracy (as measured by r 2 ) is 99.7% for 22.5x depth and 98.5% for 15x depth, suggesting that increases between 15x and 30x translate into marginal improvements in both call rate and quality of very rare SNVs (Figure 1, Supplementary Figure 3 and Methods). We find that false discovery rates and genotype accuracy are substantially more dependent on sequencing depth for INDELs than for SNVs (Figure 1). Landscape of sequence variationFollowing quality control (QC), we call 24,163,896 non-monomorphic SNVs and INDELs, 97.9% of which are biallelic. 14,281,180 (60.31%) of the biallelic SNVs are rare (minor allele frequency [MAF]<0.01); 3,103,273 (13.1%) are low-frequency (MAF 0.01-0.05); and 6,292,726 (26.57%) are common (MAF>0.05). We call 8,294 non-monomorphic variants annotated as loss-of-function (LoF) with low-confidence (LC) 4 , and 438 variants annotated as LoF with high-confidence (HC) ( Supplementary Figure 4). On average, each individual carries 405 (s=19) LC LoF variants and 31 (s=6) HC LoF variants, compared to 149 LoF variants per sample in a whole genome sequencing study of 2,636 Icelanders 5 . 0.6% and 1% of HC and LC LoF c...

Very low-depth whole-genome sequencing in complex trait association studies

“…We then compared independent suggestively associated signals at P < 5×10 −7 (Supplementary Table S2). These signals were then cross-referenced with a larger ( n = 1457) study based on 22× WGS on the same traits in the same cohort (Gilly et al , 2018). We only considered signals to be true if they displayed evidence for association with at most a two order of magnitude attenuation compared to our suggestive significance threshold ( P < 5 ×10 −5 ).…”

Long Non-coding RNA TDRKH-AS1 Promotes Colorectal Cancer Cell Proliferation and Invasion Through the β-Catenin Activated Wnt Signaling Pathway

“…Specifically, the RNA-sequencing (RNAseq) data from TCGA focused on exon sequences ( 28 ). Further population-scale deep whole-genome sequencing would help to detect the signal more accurate and robust ( 29 ). In our experiment, we emphasized the differential gene expressions between patients in different stages.…”

Medium-coverage DNA sequencing in the design of the genetic association study

“…Different from the study of SNP, the detection of structural variations (SVs) using NGS mostly relies on the sequencing depth, such as the copy number variations (CNVs) and indels. Gilly et al found that genotype accuracy is substantially more dependent on sequencing depth for indels than for SNPs [ 13 ]. In a recent study, the performance of several CNV detection tools varied with the sequencing depth, with high-coverage resulted in high sensitivity and specificity [ 20 ].…”

“…Xu et al [ 11 ] specified a similar trend that the medium depth may be the optimal design in real application by comparing low-, high-coverage, and two-stage sequencing in NGS study. Recently, Gilly et al [ 13 ] compared the genotype accuracy at depths 15×, 22.5×, and 30× by downsampling reads from a cohort of 100 samples. Their result demonstrated that the 15× was possible to achieve near-perfect sensitivity and quality for rare SNP calling and genotyping compared with 30× sequencing.…”