Distinct gene loci control the host response to influenza H1N1 virus infection in a time-dependent manner

Abstract

BackgroundThere is strong but mostly circumstantial evidence that genetic factors modulate the severity of influenza infection in humans. Using genetically diverse but fully inbred strains of mice it has been shown that host sequence variants have a strong influence on the severity of influenza A disease progression. In particular, C57BL/6J, the most widely used mouse strain in biomedical research, is comparatively resistant. In contrast, DBA/2J is highly susceptible.ResultsTo map regions of the genome responsible for differences in influenza susceptibility, we infected a family of 53 BXD-type lines derived from a cross between C57BL/6J and DBA/2J strains with influenza A virus (PR8, H1N1). We monitored body weight, survival, and mean time to death for 13 days after infection. Qivr5 (quantitative trait for influenza virus resistance on chromosome 5) was the largest and most significant QTL for weight loss. The effect of Qivr5 was detectable on day 2 post infection, but was most pronounced on days 5 and 6. Survival rate mapped to Qivr5, but additionally revealed a second significant locus on chromosome 19 (Qivr19). Analysis of mean time to death affirmed both Qivr5 and Qivr19. In addition, we observed several regions of the genome with suggestive linkage. There are potentially complex combinatorial interactions of the parental alleles among loci. Analysis of multiple gene expression data sets and sequence variants in these strains highlights about 30 strong candidate genes across all loci that may control influenza A susceptibility and resistance.ConclusionsWe have mapped influenza susceptibility loci to chromosomes 2, 5, 16, 17, and 19. Body weight and survival loci have a time-dependent profile that presumably reflects the temporal dynamic of the response to infection. We highlight candidate genes in the respective intervals and review their possible biological function during infection.

Genetic Control of Survival and Weight Loss during Pneumonic Burkholderia pseudomallei (Bp) Infection

“…These findings suggest that weight loss following Bp infection may be a dynamic phenotype that involves different host genes over the course of infection/disease. Interestingly, a recently reported genome wide study of host response to H1N1 influenza infection also identified multiple QTLs (different from those identified here) that appear to control weight loss kinetics in a time-dependent fashion [73]. The H1N1 study identified a QTL on Chr 10 that was linked only with the day 1 weight loss trait, and they concluded that much of the weight loss was transient and associated with the stress of anesthesia prior to intranasal instillation.…”

“…Most often, mapping populations are used to understand the relationship between phenotype and genotype relative to complex traits. The phenotypic and genotypic data that is generated is compiled into complex networks, which are then used to discriminate genetic variation among the mapping population [55,72,73]. This approach provides an informative view into the general framework of complex traits and the flow of biological information [69].…”

“…The BXD strain set is fully genotyped and each line is genetically distinct with a defined and fixed genetic architecture [73]. There are currently over 100 BXD strains for which genotype data is publically available.…”

“…Furthermore, an additional advantage to identifying QTLs are the insights gained into the development and physiology of complex traits on a molecular level [96]. QTL mapping has been used to successfully identify genomic regions underlying a variety of human diseases such as chlamydial infections [100], Influenza [73] and alcoholism [101].…”

“…Published findings have identified host genetic factors that are critical for variable susceptibility to intracellular parasites [115], viruses [116][117][118][119][120], and both intracellular [74,100,121] and extracellular [122] bacterial pathogens. Moreover, recent genome-wide studies have established novel associations between common polymorphisms and susceptibility to several infectious diseases that are responsible for significant morbidity and/or mortality in humans [73,100,123,124].…”