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对来自17000名个体的全基因组数据集进行的计算机功能分析,确定了在疟疾致病途径中富集的候选抗疟疾基因。

Insilico Functional Analysis of Genome-Wide Dataset From 17,000 Individuals Identifies Candidate Malaria Resistance Genes Enriched in Malaria Pathogenic Pathways.

作者信息

Damena Delesa, Agamah Francis E, Kimathi Peter O, Kabongo Ntumba E, Girma Hundaol, Choga Wonderful T, Golassa Lemu, Chimusa Emile R

机构信息

Division of Human Genetics, Department of Pathology, University of Cape Town, Cape Town, South Africa.

Aklilu Lema Institute of Pathobiology, Addis Ababa University, Addis Ababa, Ethiopia.

出版信息

Front Genet. 2021 Nov 18;12:676960. doi: 10.3389/fgene.2021.676960. eCollection 2021.

Abstract

Recent genome-wide association studies (GWASs) of severe malaria have identified several association variants. However, much about the underlying biological functions are yet to be discovered. Here, we systematically predicted plausible candidate genes and pathways from functional analysis of severe malaria resistance GWAS summary statistics ( = 17,000) meta-analysed across 11 populations in malaria endemic regions. We applied positional mapping, expression quantitative trait locus (eQTL), chromatin interaction mapping, and gene-based association analyses to identify candidate severe malaria resistance genes. We further applied rare variant analysis to raw GWAS datasets ( = 11,000) of three malaria endemic populations including Kenya, Malawi, and Gambia and performed various population genetic structures of the identified genes in the three populations and global populations. We performed network and pathway analyses to investigate their shared biological functions. Our functional mapping analysis identified 57 genes located in the known malaria genomic loci, while our gene-based GWAS analysis identified additional 125 genes across the genome. The identified genes were significantly enriched in malaria pathogenic pathways including multiple overlapping pathways in erythrocyte-related functions, blood coagulations, ion channels, adhesion molecules, membrane signalling elements, and neuronal systems. Our population genetic analysis revealed that the minor allele frequencies (MAF) of the single nucleotide polymorphisms (SNPs) residing in the identified genes are generally higher in the three malaria endemic populations compared to global populations. Overall, our results suggest that severe malaria resistance trait is attributed to multiple genes, highlighting the possibility of harnessing new malaria therapeutics that can simultaneously target multiple malaria protective host molecular pathways.

摘要

近期针对重症疟疾的全基因组关联研究(GWAS)已鉴定出多个关联变异。然而,其潜在生物学功能仍有许多有待发现。在此,我们通过对疟疾流行地区11个群体进行荟萃分析的重症疟疾抗性GWAS汇总统计数据(n = 17,000)进行功能分析,系统地预测了合理的候选基因和途径。我们应用定位映射、表达定量性状基因座(eQTL)、染色质相互作用映射和基于基因的关联分析来鉴定重症疟疾抗性候选基因。我们进一步对包括肯尼亚、马拉维和冈比亚在内的三个疟疾流行群体的原始GWAS数据集(n = 11,000)进行罕见变异分析,并对这三个群体以及全球群体中已鉴定基因的各种群体遗传结构进行了研究。我们进行了网络和途径分析以研究它们共有的生物学功能。我们的功能映射分析确定了位于已知疟疾基因组位点的57个基因,而基于基因的GWAS分析在全基因组中又鉴定出另外125个基因。所鉴定的基因在疟疾致病途径中显著富集,包括与红细胞相关功能、血液凝固、离子通道、黏附分子、膜信号元件和神经系统中的多个重叠途径。我们的群体遗传分析表明,与全球群体相比,三个疟疾流行群体中位于已鉴定基因中的单核苷酸多态性(SNP)的次要等位基因频率(MAF)普遍更高。总体而言,我们的结果表明重症疟疾抗性性状归因于多个基因,这突出了开发能够同时靶向多种疟疾保护性宿主分子途径的新型疟疾治疗方法的可能性。

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