Mapping and characterization of structural variation in 17,795 human genomes.

Mapping and characterization of structural variation in 17,795 human genomes.
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DOI:
10.1038/s41586-020-2371-0
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发表时间:
2020-07
期刊:
影响因子:
64.8
通讯作者:
Hall IM
Hall IM
中科院分区:
综合性期刊1区
文献类型:
--
作者:
Abel HJ;Larson DE;Regier AA;Chiang C;Das I;Kanchi KL;Layer RM;Neale BM;Salerno WJ;Reeves C;Buyske S;NHGRI Centers for Common Disease Genomics;Matise TC;Muzny DM;Zody MC;Lander ES;Dutcher SK;Stitziel NO;Hall IM

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全基因组测序(WGS)用于人类遗传学研究的一个关键目标是询问所有形式的变异,包括单核苷酸变异(SNV)、小插入/缺失(indel)变异和结构变异(SV)。然而,SV研究的工具和资源已经落后于较小的变异。在这里,我们使用了一个可扩展的管道来映射和表征17,795个深度测序的人类基因组中的SV。我们公开发布站点频率数据,以创建迄今为止最大的基于WGS的SV资源。平均而言,个体携带2.9个改变编码区的罕见SV,影响4.2个基因的剂量或结构,占罕见高影响编码等位基因的4.0-11.2%。基于计算模型,我们估计SV占全基因组罕见等位基因的17.2%,预测的有害影响相当于功能丧失的编码等位基因;约90%的此类SV为非编码缺失(平均每个基因组19.1个)。我们报告了158,991例超罕见SV,并表明约2%的个体携带超罕见的兆碱基规模SV,其中近一半是平衡或复杂的重排。最后,我们推断了基因和非编码元件的剂量敏感性,揭示了与元素类别和保守性相关的趋势。这项工作将有助于指导SV分析和解释在WGS时代。
A key goal of whole genome sequencing (WGS) for human genetics studies is to interrogate all forms of variation, including single nucleotide variants (SNV), small insertion/deletion (indel) variants and structural variants (SV). However, tools and resources for the study of SV have lagged behind those for smaller variants. Here, we used a scalable pipeline to map and characterize SV in 17,795 deeply sequenced human genomes. We publicly release site-frequency data to create the largest WGS-based SV resource to date. On average, individuals carry 2.9 rare SVs that alter coding regions, affecting the dosage or structure of 4.2 genes and accounting for 4.0-11.2% of rare high-impact coding alleles. Based on a computational model, we estimate that SVs account for 17.2% of rare alleles genome-wide with predicted deleterious effects equivalent to loss-of-function coding alleles; ~90% of such SVs are non-coding deletions (mean 19.1 per genome). We report 158,991 ultra-rare SVs and show that ~2% of individuals carry ultra-rare megabase-scale SVs, nearly half of which are balanced or complex rearrangements. Finally, we infer the dosage sensitivity of genes and non-coding elements, revealing trends related to element class and conservation. This work will help guide SV analysis and interpretation in the era of WGS.
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