PLoS Pathogens | |
Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross | |
Birgit Bradel-Tretheway1  Martin T. Ferris1  Jeremy Wang1  Shannon K. McWeeney2  Gary A. Churchill3  Michael G. Katze4  Alan C. Whitmore4  William Valdar4  David L. Aylor4  Mark T. Heise4  Lisa E. Gralinski4  Elizabeth Rosenzweig5  Ralph S. Baric5  Ryan J. Buus5  Leonard McMillan5  David W. Threadgill6  Timothy A. Bell7  Janine T. Bryan8  Bart L. Haagmans8  Fernando Pardo-Manuel de Villena8  Darla R. Miller8  Daniel Bottomly8  Lauri D. Aicher8  | |
[1] Carolina Vaccine Institute, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, United States of America;Department of Computer Science, University of North Carolina–Chapel Hill, Chapel Hill, North Carolina, United States of America;Department of Epidemiology, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, United States of America;Department of Genetics, University of North Carolina-Chapel Hill, Chapel Hill, North Carolina, United States of America;Department of Microbiology, School of Medicine, University of Washington, Seattle, Washington, United States of America;Erasmus Medical Center, Rotterdam, the Netherlands;Oregon Clinical and Translational Research Institute, Oregon Health & Science University, Portland, Oregon, United States of America;Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research, Portland, Oregon, United States of America | |
关键词: Quantitative trait loci; Influenza A virus; Genetics of disease; Inflammatory diseases; Population genetics; Alleles; Genetic polymorphism; Influenza; | |
DOI : 10.1371/journal.ppat.1003196 | |
学科分类:生物科学(综合) | |
来源: Public Library of Science | |
【 摘 要 】
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.
【 授权许可】
CC BY
【 预 览 】
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