Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross

Abstract

Genetic variation contributes to host responses and outcomes following infection by influenza A virus or other viral infections. Yet narrow windows of disease symptoms and confounding environmental factors have made it difficult to identify polymorphic genes that contribute to differential disease outcomes in human populations. Therefore, to control for these confounding environmental variables in a system that models the levels of genetic diversity found in outbred populations such as humans, we used incipient lines of the highly genetically diverse Collaborative Cross (CC) recombinant inbred (RI) panel (the pre-CC population) to study how genetic variation impacts influenza associated disease across a genetically diverse population. A wide range of variation in influenza disease related phenotypes including virus replication, virus-induced inflammation, and weight loss was observed. Many of the disease associated phenotypes were correlated, with viral replication and virus-induced inflammation being predictors of virus-induced weight loss. Despite these correlations, pre-CC mice with unique and novel disease phenotype combinations were observed. We also identified sets of transcripts (modules) that were correlated with aspects of disease. In order to identify how host genetic polymorphisms contribute to the observed variation in disease, we conducted quantitative trait loci (QTL) mapping. We identified several QTL contributing to specific aspects of the host response including virus-induced weight loss, titer, pulmonary edema, neutrophil recruitment to the airways, and transcriptional expression. Existing whole-genome sequence data was applied to identify high priority candidate genes within QTL regions. A key host response QTL was located at the site of the known anti-influenza Mx1 gene. We sequenced the coding regions of Mx1 in the eight CC founder strains, and identified a novel Mx1 allele that showed reduced ability to inhibit viral replication, while maintaining protection from weight loss.

Contrasting genetic architectures in different mouse reference populations used for studying complex traits

“…A similar result was found with the CC, including a QTL (Chr 16) for wheel running distance that accounted for 17.0% of the variance, a QTL (Chr 12) for food intake during exercise that accounted for 17.6% of the variance, and a QTL (Chr 4) for body weight that explained 18.6% of the variance Foulds Mathes et al 2011). Somewhat larger QTL effects, ranging from 10% to 49%, were detected for influenza-associated phenotypes and hematological measures (Kelada et al 2012;Ferris et al 2013). The largest effects among these individual QTLs explained 42% of the variance in influenza-associated weight loss and 49% of the variance in mean corpuscular volume (MCV).…”

“…However, considerable breeding difficulties were encountered (Philip et al 2011); and as of January 1, 2015, only 69 strains are listed as available on the CC website (Table 1) with a current goal of about 100 strains. Despite these difficulties, investigators have used these 69 completed strains and other incipient lines to study the genetics of infection, body weight, food intake, cancer, albuminuria, and other traits Durrant et al 2011;Foulds Mathes et al 2011;Philip et al 2011;Kelada et al 2012Thaisz et al 2012;Ferris et al 2013; Phillippi et al 2014;Rogala et al 2014;Rutledge et al 2014;Vered et al 2014).…”

“…Gene expression data generated from the HMDP was similarly combined with expression data from other RI lines and studies of KO mice to identify a role for Bicc1 in determining bone mineral density (Mesner et al 2014). The CC was used to show that resistance to influenza A virus infection was largely due to variants in Mx1 (Ferris et al 2013). The CC-RIX mice were used to identify an association between Tek and susceptibility to Ebola infection (Rasmussen et al 2014).…”

Genetic Regulation ofZfp30, CXCL1, and Neutrophilic Inflammation in Murine Lung

“…The genomes of the CC founder strains Yalcin et al 2011) and the features of the CC population have been described recently (Collaborative Cross Consortium 2012). Results obtained using incipient CC lines that were partially inbred (referred to as "preCC" mice) have been notable in terms of phenotypic diversity and identification of new QTL (Aylor et al 2011;Bottomly et al 2012;Kelada et al 2012;Ferris et al 2013;Kelada et al 2014).…”

Les populations génétiques de référence de souris de laboratoire : une nouvelle génération de modèles animaux pour les maladies humaines

“…Il est ainsi possible d'évaluer l'influence du fonds génétique sur le phéno-mène étudié. En explorant des fonds génétiques très différents, on obtient alors une gamme de réponses qui peut refléter la diversité des situations rencontrées chez l'homme (Nadeau, 2001 (Bailey, 1971;Taylor, 1989 (Ferris et al 2013).…”