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Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross
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 o...
Autores principales: | , , , , , , , , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Public Library of Science
2013
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3585141/ https://www.ncbi.nlm.nih.gov/pubmed/23468633 http://dx.doi.org/10.1371/journal.ppat.1003196 |
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author | Ferris, Martin T. Aylor, David L. Bottomly, Daniel Whitmore, Alan C. Aicher, Lauri D. Bell, Timothy A. Bradel-Tretheway, Birgit Bryan, Janine T. Buus, Ryan J. Gralinski, Lisa E. Haagmans, Bart L. McMillan, Leonard Miller, Darla R. Rosenzweig, Elizabeth Valdar, William Wang, Jeremy Churchill, Gary A. Threadgill, David W. McWeeney, Shannon K. Katze, Michael G. Pardo-Manuel de Villena, Fernando Baric, Ralph S. Heise, Mark T. |
author_facet | Ferris, Martin T. Aylor, David L. Bottomly, Daniel Whitmore, Alan C. Aicher, Lauri D. Bell, Timothy A. Bradel-Tretheway, Birgit Bryan, Janine T. Buus, Ryan J. Gralinski, Lisa E. Haagmans, Bart L. McMillan, Leonard Miller, Darla R. Rosenzweig, Elizabeth Valdar, William Wang, Jeremy Churchill, Gary A. Threadgill, David W. McWeeney, Shannon K. Katze, Michael G. Pardo-Manuel de Villena, Fernando Baric, Ralph S. Heise, Mark T. |
author_sort | Ferris, Martin T. |
collection | PubMed |
description | 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. |
format | Online Article Text |
id | pubmed-3585141 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2013 |
publisher | Public Library of Science |
record_format | MEDLINE/PubMed |
spelling | pubmed-35851412013-03-06 Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross Ferris, Martin T. Aylor, David L. Bottomly, Daniel Whitmore, Alan C. Aicher, Lauri D. Bell, Timothy A. Bradel-Tretheway, Birgit Bryan, Janine T. Buus, Ryan J. Gralinski, Lisa E. Haagmans, Bart L. McMillan, Leonard Miller, Darla R. Rosenzweig, Elizabeth Valdar, William Wang, Jeremy Churchill, Gary A. Threadgill, David W. McWeeney, Shannon K. Katze, Michael G. Pardo-Manuel de Villena, Fernando Baric, Ralph S. Heise, Mark T. PLoS Pathog Research Article 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. Public Library of Science 2013-02-28 /pmc/articles/PMC3585141/ /pubmed/23468633 http://dx.doi.org/10.1371/journal.ppat.1003196 Text en © 2013 Ferris et al http://creativecommons.org/licenses/by/4.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are properly credited. |
spellingShingle | Research Article Ferris, Martin T. Aylor, David L. Bottomly, Daniel Whitmore, Alan C. Aicher, Lauri D. Bell, Timothy A. Bradel-Tretheway, Birgit Bryan, Janine T. Buus, Ryan J. Gralinski, Lisa E. Haagmans, Bart L. McMillan, Leonard Miller, Darla R. Rosenzweig, Elizabeth Valdar, William Wang, Jeremy Churchill, Gary A. Threadgill, David W. McWeeney, Shannon K. Katze, Michael G. Pardo-Manuel de Villena, Fernando Baric, Ralph S. Heise, Mark T. Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title | Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title_full | Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title_fullStr | Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title_full_unstemmed | Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title_short | Modeling Host Genetic Regulation of Influenza Pathogenesis in the Collaborative Cross |
title_sort | modeling host genetic regulation of influenza pathogenesis in the collaborative cross |
topic | Research Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3585141/ https://www.ncbi.nlm.nih.gov/pubmed/23468633 http://dx.doi.org/10.1371/journal.ppat.1003196 |
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