美国哈佛医学院Po-Ru Loh研究组揭示罕见拷贝数变异对人类复杂性状的影响。这一研究成果于2022年10月27日发表在国际学术期刊《细胞》上。

研究人员开发了一种计算方法，利用生物库队列中的单倍型共享来更敏感地检测拷贝数变异（CNV）。应用于英国生物库，这种方法占了由基因组结构变异产生的所有罕见基因失活事件的大约一半。这个CNV调用集能够详细分析CNV和56个定量性状之间的关联，并确定269个独立的关联（p<5×10^-8）可能是由CNV引起的。近一半的基因位点可识别出推测的靶标基因，使人们能够了解这些基因的剂量敏感性，并发现一些基因与性状的关系。这些结果证明了单倍型的分析能够提供对人类复杂性状遗传基础的了解。

据悉，人类基因组包含数十万个含有CNV的区域。然而，大多数此类多态性的表型效应是未知的，因为只有较大的CNV可以从大型生物库产生的SNP阵列数据中确定。

附：英文原文

Title: Influences of rare copy-number variation on human complex traits

Author: Margaux L.A. Hujoel, Maxwell A. Sherman, Alison R. Barton, Ronen E. Mukamel, Vijay G. Sankaran, Chikashi Terao, Po-Ru Loh

Issue&Volume: 2022/10/27

Abstract: The human genome contains hundreds of thousands of regions harboring copy-number variants (CNV). However, the phenotypic effects of most such polymorphisms are unknown because only larger CNVs have been ascertainable from SNP-array data generated by large biobanks. We developed a computational approach leveraging haplotype sharing in biobank cohorts to more sensitively detect CNVs. Applied to UK Biobank, this approach accounted for approximately half of all rare gene inactivation events produced by genomic structural variation. This CNV call set enabled a detailed analysis of associations between CNVs and 56 quantitative traits, identifying 269 independent associations (p < 5 × 108) likely to be causally driven by CNVs. Putative target genes were identifiable for nearly half of the loci, enabling insights into dosage sensitivity of these genes and uncovering several gene-trait relationships. These results demonstrate the ability of haplotype-informed analysis to provide insights into the genetic basis of human complex traits.

DOI: 10.1016/j.cell.2022.09.028

Source: https://www.cell.com/cell/fulltext/S0092-8674(22)01247-8