TY - JOUR
T1 - Genome-wide analysis of host-plasmodium yoelii interactions reveals regulators of the type i interferon response
AU - Wu, Jian
AU - Cai, Baowei
AU - Sun, Wenxiang
AU - Huang, Ruili
AU - Liu, Xueqiao
AU - Lin, Meng
AU - Pattaradilokrat, Sittiporn
AU - Martin, Scott
AU - Qi, Yanwei
AU - Nair, Sethu C.
AU - Bolland, Silvia
AU - Cohen, Jeffrey I.
AU - Austin, Christopher P.
AU - Long, Carole A.
AU - Myers, Timothy G.
AU - Wang, Rong Fu
AU - Su, Xin zhuan
PY - 2015
Y1 - 2015
N2 - Invading pathogens trigger specific host responses, an understanding of which might identify genes that function in pathogen recognition and elimination. In this study, 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 linked 1,054 host genes to parasite genetic loci (LOD score R 3.0). Using LOD score patterns, which produced results that differed from direct expression-level clustering, we grouped host genes that function in related pathways, allowing functional prediction of unknown genes. As a proof of principle, 14 of 15 randomly selected genes predicted to function in type I interferon (IFN-I) responses were experimentally validated using overexpression, small hairpin RNA knockdown, viral infection, and/or infection of knockout mice. This study demonstrates an effective strategy for studying gene function, establishes a functional gene database, and identifies regulators in IFN-I pathways.
AB - Invading pathogens trigger specific host responses, an understanding of which might identify genes that function in pathogen recognition and elimination. In this study, 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 linked 1,054 host genes to parasite genetic loci (LOD score R 3.0). Using LOD score patterns, which produced results that differed from direct expression-level clustering, we grouped host genes that function in related pathways, allowing functional prediction of unknown genes. As a proof of principle, 14 of 15 randomly selected genes predicted to function in type I interferon (IFN-I) responses were experimentally validated using overexpression, small hairpin RNA knockdown, viral infection, and/or infection of knockout mice. This study demonstrates an effective strategy for studying gene function, establishes a functional gene database, and identifies regulators in IFN-I pathways.
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U2 - 10.1016/j.celrep.2015.06.058
DO - 10.1016/j.celrep.2015.06.058
M3 - Article
C2 - 26190101
AN - SCOPUS:84947040852
VL - 12
SP - 661
EP - 672
JO - Cell Reports
JF - Cell Reports
SN - 2211-1247
IS - 4
ER -