Complex Genetic Architecture Underlies Regulation of Influenza-A-Virus-Specific Antibody Responses in the Collaborative Cross
Year: 2020
Type: article
Abstract: Noll et al. use the Collaborative Cross, a mouse genetic reference population, to map genetic loci associated with variation in the humoral response to influenza virus infection. Cross-dataset comparison shows that mapped loci are important for antibody response to multiple pathogens, and candidate genes with likely translational relevance are identified. © 2020 The Author(s)Host genetic factors play a fundamental role in regulating humoral immunity to viral infection, including influenza A virus (IAV). Here, we utilize the Collaborative Cross (CC), a mouse genetic reference population, to study genetic regulation of variation in antibody response following IAV infection. CC mice show significant heritable variation in the magnitude, kinetics, and composition of IAV-specific antibody response. We map 23 genetic loci associated with this variation. Analysis of a subset of these loci finds that they broadly affect the antibody response to IAV as well as other viruses. Candidate genes are identified based on predicted variant consequences and haplotype-specific expression patterns, and several show overlap with genes identified in human mapping studies. These findings demonstrate that the host antibody response to IAV infection is under complex genetic control and highlight the utility of the CC in modeling and identifying genetic factors with translational relevance to human health and disease.
DOI: 10.17615/dh3c-xp88
Authors: West, Ande, Hampton, Brea K., Noll, Kelsey E., Ferris, Martin T., Morrison, Thomas E., McCarthy, Mary K., de Villena, Fernando Pardo-Manuel, Morrison, Clayton R., Kollmus, Heike, Whitmore, Alan C., Heise, Mark T., Schughart, Klaus, Mooney, Michael, Pilzner, Carolin, Leist, Sarah R., Miller, Darla, Baric, Ralph S., McWeeney, Shannon, Shaw, Ginger, Plante, Kenneth S., Schaefer, Alexandra, Menachery, Vineet D., Gralinski, Lisa E.
Institution: University of North Carolina at Chapel Hill
Language: English
Subfield: Epidemiology
Field: Medicine
Domain: Health Sciences
Open Access status: green
OpenAlex ID: W4287940560