国家神经系统疾病临床医学研究中心数据管理与共享系统

发表杂志：Cell Discovery

发表类型: Original Contributions

影响因子(IF): 33.5

PMID: 37479695 Pubmed原文链接 全文下载

中国人群大规模全基因组测序研究是开展我国人群精准医疗、提升新药研发能力的重要先决条件。截至目前，有两项中国人群全基因组测序研究已经发表，分别为上海瑞金医院宁光院士主持的ChinaMAP（N=10588，发表于Cell Research，IF=25.617）(1)，中国科学院生物物理研究所徐涛院士主持的女娲项目（N=2999，发表于Cell Reports，IF=9.423）(2)。目前尚没有针对卒中人群的大规模全基因组测序研究发表。归纳和注释CNSR3的全基因组测序项目得到的各种遗传变异（包括SNV、indel），是开展基因功能研究和多组学研究的重要基础，也是中国人群卒中基因图谱的主要内容。 Our previous analyses on 48 ischaemic stroke (IS)-associated single nucleotide variants (SNVs) showed potential genetic heterogeneity in IS susceptibility between Chinese and Europeans (in submission). Therefore, a comprehensive study on the whole genome sequencing (WGS) data was needed to fully portray the genetic architecture of IS across different regions of China and construct a WGS-based genetic variation profile for Chinese IS patients (1, 2). 【Purpose】 Here, we aimed to describe the genomic landscape on SNVs and insertion-deletions (InDels) of 10241 WGS data from the Third China National Stroke Registry (CNSR-Ⅲ). The main purposes included: 1. Summarizing the genetic variants obtained from WGS; 2. Describing pathogenic and loss of function (LoF) variants for the stroke patients in five subtypes; 3. Demonstrating genetic diversity and the population structure for IS patients across different provinces of China; 4. Investigating the population-specific association between genetic variants and common traits under linkage disequilibrium (LD) block pattern among Chinese. The genetic architecture for Chinese IS patients would be resolved by this analysis, and it could promote the discovery of novel drug targets and the development of new therapeutic measures for IS (3). 此篇为全基因组分析的基础，进行整个基因数据描述。

Variant quality score recalibration (VQSR) and hard filters (depth ≥ 9, genotype quality ≥ 20, maximum number of alternative alleles at the same position ≤ 10, and maximum length of indel ≤ 10 bp) would be applied first. All qualified SNVs and indels would be annotated by InterVar(4), and then they would be classified based on their function in protein-coding and gene expression regulation. Pathogenic and LoF variants would be summarized for each patient, and their contribution to different IS subtypes and susceptibility across provinces of China would be investigated and compared by t-tests. Allele frequencies of genetic variants would be compared with those in 1000 Genome Project (5), TopMed (6), and gnomAD project (7). Population structure of CNSR-Ⅲ samples would be investigated by principal component analysis (PCA) and admixture analysis (8, 9). The association of genetic variants with common qualitative and quantitative traits would be explored using logistic regression and linear regression, respectively. The LD structure would be constructed by HaploView under default parameters (10).