Long-read sequencing of 945 Han individuals identifies structural variants associated with phenotypic diversity and disease susceptibility
Gong JPapers in this archive, Sun HPapers in this archive, Wang KPapers in this archive, Zhao YPapers in this archive, Huang YPapers in this archive, Chen QPapers in this archive, Qiao HPapers in this archive, Gao YPapers in this archive, Zhao JPapers in this archive, Ling YPapers in this archive, Cao RPapers in this archive, Tan JPapers in this archive, Wang QPapers in this archive, Ma YPapers in this archive, Li JPapers in this archive, Luo JPapers in this archive, Wang SPapers in this archive, Wang JPapers in this archive, Zhang GPapers in this archive, Xu SPapers in this archive, Qian FPapers in this archive, Zhou FPapers in this archive, Tang HPapers in this archive, Li DPapers in this archive, Chinese Pangenome Consortium (CPC), Sedlazeck FJPapers in this archive, Jin LPapers in this archive, Guan YPapers in this archive, Fan SPapers in this archive
Abstract
Genomic structural variants (SVs) are a major source of genetic diversity in humans. Here, through long-read sequencing of 945 Han Chinese genomes, we identify 111,288 SVs, including 24.56% unreported variants, many with predicted functional importance. By integrating human population-level phenotypic and multi-omics data as well as two humanized mouse models, we demonstrate the causal roles of two SVs: one SV that emerges at the common ancestor of modern humans, Neanderthals, and Denisovans in GSDMD for bone mineral density and one modern-human-specific SV in WWP2 impacting height, weight, fat, craniofacial phenotypes and immunity. Our results suggest that the GSDMD SV could serve as a rapid and cost-effective biomarker for assessing the risk of cisplatin-induced acute kidney injury. The functional conservation from human to mouse and widespread signals of positive natural selection suggest that both SVs likely influence local adaptation, phenotypic diversity, and disease susceptibility across diverse human populations. Subject terms: Functional genomics, Structural variation, Evolutionary genetics
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