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Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice
Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirrorin...
Autores principales: | , , , , , , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Genetics Society of America
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3284329/ https://www.ncbi.nlm.nih.gov/pubmed/22384400 http://dx.doi.org/10.1534/g3.111.001800 |
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author | Bottomly, Daniel Ferris, Martin T. Aicher, Lauri D. Rosenzweig, Elizabeth Whitmore, Alan Aylor, David L. Haagmans, Bart L. Gralinski, Lisa E. Bradel-Tretheway, Birgit G. Bryan, Janine T. Threadgill, David W. de Villena, Fernando Pardo-Manuel Baric, Ralph S. Katze, Michael G. Heise, Mark McWeeney, Shannon K. |
author_facet | Bottomly, Daniel Ferris, Martin T. Aicher, Lauri D. Rosenzweig, Elizabeth Whitmore, Alan Aylor, David L. Haagmans, Bart L. Gralinski, Lisa E. Bradel-Tretheway, Birgit G. Bryan, Janine T. Threadgill, David W. de Villena, Fernando Pardo-Manuel Baric, Ralph S. Katze, Michael G. Heise, Mark McWeeney, Shannon K. |
author_sort | Bottomly, Daniel |
collection | PubMed |
description | Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe (“high”) and mild (“low”) response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative regulatory regions potentially controlling their expression. Twenty-one significant expression quantitative trait loci were identified, which allowed direct examination of genes associated with regulation of host response to infection. To perform initial validation of our findings, quantitative polymerase chain reaction was performed in the infected founder strains, and we were able to confirm or partially confirm more than 70% of those tested. In addition, we explored putative causal and reactive (downstream) relationships between the significantly regulated genes and others in the high or low response groups using structural equation modeling. By using systems approaches and a genetically diverse population, we were able to develop a novel framework for identifying the underlying biological subnetworks under host genetic control during influenza virus infection. |
format | Online Article Text |
id | pubmed-3284329 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | Genetics Society of America |
record_format | MEDLINE/PubMed |
spelling | pubmed-32843292012-03-01 Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice Bottomly, Daniel Ferris, Martin T. Aicher, Lauri D. Rosenzweig, Elizabeth Whitmore, Alan Aylor, David L. Haagmans, Bart L. Gralinski, Lisa E. Bradel-Tretheway, Birgit G. Bryan, Janine T. Threadgill, David W. de Villena, Fernando Pardo-Manuel Baric, Ralph S. Katze, Michael G. Heise, Mark McWeeney, Shannon K. G3 (Bethesda) Mouse Genetic Resources Outbreaks of influenza occur on a yearly basis, causing a wide range of symptoms across the human population. Although evidence exists that the host response to influenza infection is influenced by genetic differences in the host, this has not been studied in a system with genetic diversity mirroring that of the human population. Here we used mice from 44 influenza-infected pre-Collaborative Cross lines determined to have extreme phenotypes with regard to the host response to influenza A virus infection. Global transcriptome profiling identified 2671 transcripts that were significantly differentially expressed between mice that showed a severe (“high”) and mild (“low”) response to infection. Expression quantitative trait loci mapping was performed on those transcripts that were differentially expressed because of differences in host response phenotype to identify putative regulatory regions potentially controlling their expression. Twenty-one significant expression quantitative trait loci were identified, which allowed direct examination of genes associated with regulation of host response to infection. To perform initial validation of our findings, quantitative polymerase chain reaction was performed in the infected founder strains, and we were able to confirm or partially confirm more than 70% of those tested. In addition, we explored putative causal and reactive (downstream) relationships between the significantly regulated genes and others in the high or low response groups using structural equation modeling. By using systems approaches and a genetically diverse population, we were able to develop a novel framework for identifying the underlying biological subnetworks under host genetic control during influenza virus infection. Genetics Society of America 2012-02-01 /pmc/articles/PMC3284329/ /pubmed/22384400 http://dx.doi.org/10.1534/g3.111.001800 Text en Copyright © 2012 Bottomly et al http://creativecommons.org/licenses/by/3.0/ This is an open-access article distributed under the terms of the Creative Commons Attribution Unported License (http://creativecommons.org/licenses/by/3.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Mouse Genetic Resources Bottomly, Daniel Ferris, Martin T. Aicher, Lauri D. Rosenzweig, Elizabeth Whitmore, Alan Aylor, David L. Haagmans, Bart L. Gralinski, Lisa E. Bradel-Tretheway, Birgit G. Bryan, Janine T. Threadgill, David W. de Villena, Fernando Pardo-Manuel Baric, Ralph S. Katze, Michael G. Heise, Mark McWeeney, Shannon K. Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title | Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title_full | Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title_fullStr | Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title_full_unstemmed | Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title_short | Expression Quantitative Trait Loci for Extreme Host Response to Influenza A in Pre-Collaborative Cross Mice |
title_sort | expression quantitative trait loci for extreme host response to influenza a in pre-collaborative cross mice |
topic | Mouse Genetic Resources |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3284329/ https://www.ncbi.nlm.nih.gov/pubmed/22384400 http://dx.doi.org/10.1534/g3.111.001800 |
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