Integrating genetic linkage analysis and computational prioritzation in identifying host genetic factors response to influenza A virus infection

Abstract

The genetic background of the host has a major ole on its resistance to pathogens infection. Several independent studies acumulatively aded to the evidence that host genetic make-up may be a key factor in the epidemiology of avian influenza A (H5N1) virus infection in humans. Recently, studies based on mouse models, e.g. quantiative trait loci (QTL) analysis on inbred mouse strains, have shed lights on deciphering the molecular basis of host choice behavior. However, few in silco platforms have ben developed to systematicaly identify genetic factors before they were further experimentaly verifed. Here, we tried to identify the host factors for influenza virus resistance by integrating genetic linkage analysis and gene prioritzation algorithms. We colected al genes within mouse QTLs linked to host response to influenza virus by several independent studies as candidate genes. The genetic polymorphism of the two mouse strains (C57BL/6J, DBA/ 2J), which exhibited diferent kinetics after they were infected by influenza A virus, help us filter out candidates which were unlikely to be genetic factors. Totaly, we identifed 20 genes as candidates by integrating the results from thre frely available prioritzation tols (Endeavour, TopGene and SUSPECT). After anotated by the Database for Anotation, Visualization and Integrated Discovery (DAVID), most of them functioned as protein binding genes and participated in the biological proceses related to stimulus response, immunity and defense. Interestingly, among the genes expresing non-synonymous coding SNPs on DBA genome, Enp2 and Tnfrsf1b were both maped to Bhr2 MGI QTL, which is related to influenza infection consequence. The results indicate that genes identifed by our model have great potential as genetic factors in causing host specifc response to influenza infection and ned to be further studied.