Read-depth CNV genotyping method identifies 501 copy-number variants associated with 1,537 human traits in UK Biobank
By
Andrew J. Sharp Send email to [email protected]
Summary
This study presents a novel read-depth-based method for genotyping copy-number variants (CNVs) from genome sequencing data, including challenging types like mosaic, recurrent, and multiallelic CNVs. Applied to the UK Biobank cohort, the method genotyped each 5-kb segment across the genome and conducted phenome-wide association studies (PheWASs) across 13,215 traits. The analysis identified 501 CNVs associated with 1,537 traits, with nearly 75% of these associations not detectable by comparable single-nucleotide variant (SNV)-based approaches, providing significant new insights into how CNVs influence human traits and disease.
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bskyRead-depth CNV genotyping method identifies 501 copy-number variants associated with 1,537 human traits in UK Biobankcell.comKey quotes
· 3 pulledWe developed a read-depth-based approach that allows accurate and scalable copy-number genotyping from genome sequencing data, including mosaic, recurrent, and multiallelic copy-number variants (CNVs) that are difficult to genotype using other methods.
We genotyped each 5-kb segment throughout the genome in the UK Biobank cohort and performed phenome-wide association studies (PheWASs) using 13,215 traits under three different association models, identifying 501 CNVs associated with 1,537 traits.
Of these, almost 75% were not found by comparable single-nucleotide variant (SNV)-based PheWAS.
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