%0 Journal Article
%T Detection of trait-associated structural variations using short-read sequencing.
%A Kosugi S
%A Kamatani Y
%A Harada K
%A Tomizuka K
%A Momozawa Y
%A Morisaki T
%A  
%A Terao C
%J Cell Genom
%V 3
%N 6
%D 2023 Jun 14
%M 37388916
暂无%R 10.1016/j.xgen.2023.100328
%X Genomic structural variation (SV) affects genetic and phenotypic characteristics in diverse organisms, but the lack of reliable methods to detect SV has hindered genetic analysis. We developed a computational algorithm (MOPline) that includes missing call recovery combined with high-confidence SV call selection and genotyping using short-read whole-genome sequencing (WGS) data. Using 3,672 high-coverage WGS datasets, MOPline stably detected ∼16,000 SVs per individual, which is over ∼1.7-3.3-fold higher than previous large-scale projects while exhibiting a comparable level of statistical quality metrics. We imputed SVs from 181,622 Japanese individuals for 42 diseases and 60 quantitative traits. A genome-wide association study with the imputed SVs revealed 41 top-ranked or nearly top-ranked genome-wide significant SVs, including 8 exonic SVs with 5 novel associations and enriched mobile element insertions. This study demonstrates that short-read WGS data can be used to identify rare and common SVs associated with a variety of traits.