Influences of rare copy number variation on human complex traits

拷贝数变化 单倍型 生物 遗传学 生命银行 结构变异 数量性状位点 单核苷酸多态性 SNP公司 SNP阵列 基因 全基因组关联研究 遗传关联 等位基因 表型 人类基因组 计算生物学 基因组 基因型
作者
Margaux L. A. Hujoel,Maxwell A. Sherman,Alison R. Barton,Ronen E. Mukamel,Vijay G. Sankaran,Po-Ru Loh
出处
期刊:bioRxiv 被引量:1
标识
DOI:10.1101/2021.10.21.465308
摘要

Abstract The human genome contains hundreds of thousands of regions exhibiting copy number variation (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs (spanning tens of kilobases) have been ascertainable from the SNP-array data generated by large biobanks. We developed a new computational approach that leverages abundant haplotype-sharing in biobank cohorts to more sensitively detect CNVs co-inherited within extended SNP haplotypes. Applied to UK Biobank, this approach achieved 6-fold increased CNV detection sensitivity compared to previous analyses, accounting for approximately half of all rare gene inactivation events produced by genomic structural variation. This extensive CNV call set enabled the most comprehensive analysis to date of associations between CNVs and 56 quantitative traits, identifying 269 independent associations ( P < 5 × 10 −8 ) – involving 97 loci – that rigorous statistical fine-mapping analyses indicated were likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling new insights into dosage-sensitivity of these genes and implicating several novel gene-trait relationships. CNVs at several loci created extended allelic series including deletions or duplications of distal enhancers that associated with much stronger phenotypic effects than SNPs within these regulatory elements. These results demonstrate the ability of haplotype-informed analysis to empower structural variant detection and provide insights into the genetic basis of human complex traits.

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