Bayesian Diallel analysis reveals MX1-dependent and MX1-independent effects on response to influenza a virus in mice

Paul L. Maurizio, Martin T. Ferris, Gregory R. Keele, Darla R. Miller, Ginger D. Shaw, Alan C. Whitmore, Ande West, Clayton R. Morrison, Kelsey E. Noll, Kenneth S. Plante, Adam S. Cockrell, David W. Threadgill, Fernando Pardo Manuel de Villena, Ralph S. Baric, Mark T. Heise, William Valdar

Research output: Contribution to journalArticlepeer-review

10 Scopus citations

Abstract

Influenza A virus (IAV) is a respiratory pathogen that causes substantial morbidity and mortality during both seasonal and pandemic outbreaks. Infection outcomes in unexposed populations are affected by host genetics, but the host genetic architecture is not well understood. Here, we obtain a broad view of how heritable factors affect a mouse model of response to IAV infection using an 8 · 8 diallel of the eight inbred founder strains of the Collaborative Cross (CC). Expanding on a prior statistical framework for modeling treatment response in diallels, we explore how a range of heritable effects modify acute host response to IAV through 4 d postinfection. Heritable effects in aggregate explained ~57% of the variance in IAV-induced weight loss. Much of this was attributable to a pattern of additive effects that became more prominent through day 4 postinfection and was consistent with previous reports of antiinfluenza myxovirus resistance 1 (Mx1) polymorphisms segregating between these strains; these additive effects largely recapitulated haplotype effects observed at the Mx1 locus in a previous study of the incipient CC, and are also replicated here in a CC recombinant intercross population. Genetic dominance of protective Mx1 haplotypes was observed to differ by subspecies of origin: relative to the domesticus null Mx1 allele, musculus acts dominantly whereas castaneus acts additively. After controlling for Mx1, heritable effects, though less distinct, accounted for ~34% of the phenotypic variance. Implications for future mapping studies are discussed.

Original languageEnglish (US)
Pages (from-to)427-445
Number of pages19
JournalG3: Genes, Genomes, Genetics
Volume8
Issue number2
DOIs
StatePublished - Feb 1 2018
Externally publishedYes

Keywords

  • Causal effect Bayesian mixed model
  • MPP
  • Multiparental populations
  • Multiple imputation
  • Treatment response

ASJC Scopus subject areas

  • Molecular Biology
  • Genetics
  • Genetics(clinical)

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