Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts.
Identifieur interne : 000F82 ( PubMed/Corpus ); précédent : 000F81; suivant : 000F83Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts.
Auteurs : Laurence Josset ; Nicolas Tchitchek ; Lisa E. Gralinski ; Martin T. Ferris ; Amie J. Eisfeld ; Richard R. Green ; Matthew J. Thomas ; Jennifer Tisoncik-Go ; Gary P. Schroth ; Yoshihiro Kawaoka ; Fernando Pardo Manuel De Villena ; Ralph S. Baric ; Mark T. Heise ; Xinxia Peng ; Michael G. KatzeSource :
- RNA biology [ 1555-8584 ] ; 2014.
English descriptors
- KwdEn :
- Animals, Antiviral Agents (administration & dosage), Antiviral Agents (pharmacology), Cell Line, Female, Gene Expression Profiling, Gene Expression Regulation (drug effects), Influenza A virus (drug effects), Influenza A virus (physiology), Interferon-alpha (administration & dosage), Interferon-alpha (pharmacology), Lung (metabolism), Lung (virology), Mice, Mice, Inbred C57BL, Molecular Sequence Annotation, RNA Virus Infections (drug therapy), RNA Virus Infections (genetics), RNA Virus Infections (virology), RNA, Long Noncoding (genetics), SARS Virus (drug effects), SARS Virus (physiology), Sequence Analysis, RNA.
- MESH :
- chemical , administration & dosage : Antiviral Agents, Interferon-alpha.
- chemical , genetics : RNA, Long Noncoding.
- chemical , pharmacology : Antiviral Agents, Interferon-alpha.
- drug effects : Gene Expression Regulation, Influenza A virus, SARS Virus.
- drug therapy : RNA Virus Infections.
- genetics : RNA Virus Infections.
- metabolism : Lung.
- physiology : Influenza A virus, SARS Virus.
- virology : Lung, RNA Virus Infections.
- Animals, Cell Line, Female, Gene Expression Profiling, Mice, Mice, Inbred C57BL, Molecular Sequence Annotation, Sequence Analysis, RNA.
Abstract
The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb).
DOI: 10.4161/rna.29442
PubMed: 24922324
Links to Exploration step
pubmed:24922324Le document en format XML
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<term>Female</term>
<term>Gene Expression Profiling</term>
<term>Gene Expression Regulation (drug effects)</term>
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<front><div type="abstract" xml:lang="en">The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb). </div>
</front>
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<Month>06</Month>
<Day>19</Day>
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<DateRevised><Year>2020</Year>
<Month>04</Month>
<Day>04</Day>
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<Issue>7</Issue>
<PubDate><Year>2014</Year>
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<Title>RNA biology</Title>
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<ArticleTitle>Annotation of long non-coding RNAs expressed in collaborative cross founder mice in response to respiratory virus infection reveals a new class of interferon-stimulated transcripts.</ArticleTitle>
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<Abstract><AbstractText>The outcome of respiratory virus infection is determined by a complex interplay of viral and host factors. Some potentially important host factors for the antiviral response, whose functions remain largely unexplored, are long non-coding RNAs (lncRNAs). Here we systematically inferred the regulatory functions of host lncRNAs in response to influenza A virus and severe acute respiratory syndrome coronavirus (SARS-CoV) based on their similarity in expression with genes of known function. We performed total RNA-Seq on viral-infected lungs from eight mouse strains, yielding a large data set of transcriptional responses. Overall 5,329 lncRNAs were differentially expressed after infection. Most of the lncRNAs were co-expressed with coding genes in modules enriched in genes associated with lung homeostasis pathways or immune response processes. Each lncRNA was further individually annotated using a rank-based method, enabling us to associate 5,295 lncRNAs to at least one gene set and to predict their potential cis effects. We validated the lncRNAs predicted to be interferon-stimulated by profiling mouse responses after interferon-α treatment. Altogether, these results provide a broad categorization of potential lncRNA functions and identify subsets of lncRNAs with likely key roles in respiratory virus pathogenesis. These data are fully accessible through the MOuse NOn-Code Lung interactive database (MONOCLdb). </AbstractText>
</Abstract>
<AuthorList CompleteYN="Y"><Author ValidYN="Y"><LastName>Josset</LastName>
<ForeName>Laurence</ForeName>
<Initials>L</Initials>
<AffiliationInfo><Affiliation>Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA; Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA.</Affiliation>
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<Author ValidYN="Y"><LastName>Tchitchek</LastName>
<ForeName>Nicolas</ForeName>
<Initials>N</Initials>
<AffiliationInfo><Affiliation>Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA; Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA.</Affiliation>
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<Author ValidYN="Y"><LastName>Gralinski</LastName>
<ForeName>Lisa E</ForeName>
<Initials>LE</Initials>
<AffiliationInfo><Affiliation>Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA; Department of Epidemiology; University of North Carolina-Chapel Hill; Chapel Hill, NC USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Ferris</LastName>
<ForeName>Martin T</ForeName>
<Initials>MT</Initials>
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</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Eisfeld</LastName>
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<AffiliationInfo><Affiliation>Department of Pathobiological Sciences; Influenza Research Institute; University of Wisconsin-Madison; Madison, WI USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Green</LastName>
<ForeName>Richard R</ForeName>
<Initials>RR</Initials>
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<Author ValidYN="Y"><LastName>Thomas</LastName>
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<ForeName>Gary P</ForeName>
<Initials>GP</Initials>
<AffiliationInfo><Affiliation>Illumina, Inc.; San Diego, CA USA.</Affiliation>
</AffiliationInfo>
</Author>
<Author ValidYN="Y"><LastName>Kawaoka</LastName>
<ForeName>Yoshihiro</ForeName>
<Initials>Y</Initials>
<AffiliationInfo><Affiliation>Department of Pathobiological Sciences; Influenza Research Institute; University of Wisconsin-Madison; Madison, WI USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Manuel de Villena</LastName>
<ForeName>Fernando Pardo</ForeName>
<Initials>FP</Initials>
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<Author ValidYN="Y"><LastName>Baric</LastName>
<ForeName>Ralph S</ForeName>
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<Initials>MT</Initials>
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<Author ValidYN="Y"><LastName>Peng</LastName>
<ForeName>Xinxia</ForeName>
<Initials>X</Initials>
<AffiliationInfo><Affiliation>Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA; Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA.</Affiliation>
</AffiliationInfo>
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<Author ValidYN="Y"><LastName>Katze</LastName>
<ForeName>Michael G</ForeName>
<Initials>MG</Initials>
<AffiliationInfo><Affiliation>Department of Microbiology; School of Medicine; University of Washington; Seattle, WA USA; Pacific Northwest Regional Center of Excellence for Biodefense and Emerging Infectious Diseases Research; Portland, OR USA.</Affiliation>
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<Country>United States</Country>
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