Scientific Institute IRCCS E. Medea, Bioinformatic Lab, Bosisio Parini (LC), Italy.
PLoS Genet. 2010 Feb 19;6(2):e1000849. doi: 10.1371/journal.pgen.1000849.
Viruses have exerted a constant and potent selective pressure on human genes throughout evolution. We utilized the marks left by selection on allele frequency to identify viral infection-associated allelic variants. Virus diversity (the number of different viruses in a geographic region) was used to measure virus-driven selective pressure. Results showed an excess of variants correlated with virus diversity in genes involved in immune response and in the biosynthesis of glycan structures functioning as viral receptors; a significantly higher than expected number of variants was also seen in genes encoding proteins that directly interact with viral components. Genome-wide analyses identified 441 variants significantly associated with virus-diversity; these are more frequently located within gene regions than expected, and they map to 139 human genes. Analysis of functional relationships among genes subjected to virus-driven selective pressure identified a complex network enriched in viral products-interacting proteins. The novel approach to the study of infectious disease epidemiology presented herein may represent an alternative to classic genome-wide association studies and provides a large set of candidate susceptibility variants for viral infections.
病毒在整个进化过程中对人类基因施加了持续而强大的选择压力。我们利用选择对等位基因频率留下的痕迹来识别与病毒感染相关的等位基因变异。病毒多样性(特定地理区域内存在的不同病毒数量)用于衡量病毒驱动的选择压力。结果表明,与免疫反应和糖蛋白结构生物合成基因中与病毒多样性相关的变异过多,这些基因作为病毒受体发挥作用;与直接与病毒成分相互作用的蛋白质编码基因中的变异数量也明显高于预期。全基因组分析确定了 441 个与病毒多样性显著相关的变异;这些变异比预期更频繁地位于基因区域内,它们映射到 139 个人类基因。对受病毒驱动的选择压力影响的基因之间的功能关系进行分析,确定了一个富含病毒产物相互作用蛋白的复杂网络。本文提出的研究传染病流行病学的新方法可能代表了对经典全基因组关联研究的一种替代方法,并为病毒感染提供了一组大量的候选易感性变异。