Description
An invading pathogen will trigger specific host responses, which can be explored to identify genes functioning in pathogen recognition and elimination. Here we performed trans-species expression quantitative trait locus (ts-eQTL) analysis using genotypes of the Plasmodium yoelii malaria parasite and phenotypes of mouse gene expression. We significantly (LOD score3.0) linked 1,054 host genes to many parasite genetic loci. Clustering genome-wide pattern of LOD scores (GPLSs), which produced results different from those of direct expression level clustering, grouped host genes functioning in related pathways together, allowing accurate functional prediction of unknown genes. As proof of principle, 14 of 15 randomly selected genes unknown, but predicted to function in type I interferon (IFN-I) responses, were experimentally verified using gene over expression, shRNA knockdown, viral infection, and/or infection of KO mice. This study demonstrates an effective strategy for studying gene function, establishes a functional gene database, and identifies regulators in IFN-I pathways.