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Published on: January 9, 2020
Genome-wide associations of structural variants with human traits through imputation from long-read assemblies
Wei-Yang Bai1,2, Shuli Liu1,2, Zhongqu Duan1,2
1New Cornerstone Science Laboratory, School of Life Sciences, Westlake University, Hangzhou, China.
Structural variants (SVs) significantly impact human traits, but are hard to study. This research developed a tool to impute SVs from common genetic data, revealing their substantial role in complex traits.
Area of Science:
- Genomics
- Human Genetics
- Bioinformatics
Background:
- Structural variants (SVs) are a major source of genetic variation, yet their contribution to human traits is poorly understood due to genotyping challenges in large populations.
- Previous methods struggled to analyze SVs comprehensively across the genome in large cohorts.
Purpose of the Study:
- To develop a method for imputing structural variants (SVs) from single-nucleotide polymorphism (SNP) data to enable large-scale analysis.
- To investigate the role of SVs in complex human traits using genome-wide association studies (GWAS).
Main Methods:
- Generated a comprehensive catalog of 171,233 high-quality genome-wide SVs using PacBio HiFi long-read sequencing from 241 individuals.
- Developed ImputeSV, a reference panel and web application, to impute SVs from SNP data.
- Imputed 54,578 common SVs in 456,643 UK Biobank participants and performed GWAS for 2,624 traits.
Main Results:
- Demonstrated high accuracy for SV imputation at both individual and cohort levels.
- Estimated that SVs account for at least 4.7% of common genetic variation influencing complex traits.
- Identified 17,335 significant SV-trait associations, including 958 potentially driven by SVs rather than small variants.
Conclusions:
- Long-read sequencing data combined with imputation methods effectively enables large-scale SV analysis.
- Structural variants play a significant, previously underestimated role in the genetic architecture of complex human traits.
- The study provides a valuable resource of SVs and their associations within the UK Biobank cohort.
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