Evidence map›Paper›PMID 26303911›Full record

ArticleBMC genomics2015

Identification of microRNAs associated with allergic airway disease using a genetically diverse mouse population.

Holly Rutledge, Jeanette Baran-Gale, Fernando Pardo-Manuel de Villena, Elissa J Chesler, Gary A Churchill, Praveen Sethupathy, Samir N P Kelada

Open access · goldAbstract read
In one paragraph

Article in BMC genomics, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 15 papers.

0numbers the graph read from it
0cells of the map it votes in
15citing papers in PubMed
1.1field-weighted citation impact, top 24% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

15 citing papers in PubMed, 24 citations in OpenAlex.

  1. Trial
  2. Article
  3. Human pancreatic islet microRNAs implicated in diabetes and related traits by large-scale genetic analysis.Proceedings of the National Academy of Sciences of the United States of America · 2023
    Article
  4. Review
  5. Article
  6. Article
  7. Article
  8. Article
  9. Review
  10. Article
  11. Article
  12. Article
  13. The microRNA miR-31 inhibits CD8Nature immunology · 2017
    Article
  14. Function and regulation of microRNA-31 in development and disease.Molecular reproduction and development · 2016
    Review
  15. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

7 authors at 2 institutions in 1 country.

Holly RutledgeDepartment of Genetics, University of North Carolina, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA. hrutledg@email.unc.edu.
Jeanette Baran-GaleDepartment of Genetics, University of North Carolina, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA. jtbaran@email.unc.edu.
Fernando Pardo-Manuel de VillenaDepartment of Genetics, University of North Carolina, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA. fernando@med.unc.edu.
Elissa J CheslerThe Jackson Laboratory, Bar Harbor, ME, USA. Elissa.Chesler@jax.org.
Gary A ChurchillThe Jackson Laboratory, Bar Harbor, ME, USA. Gary.Churchill@jax.org.
Praveen SethupathyDepartment of Genetics, University of North Carolina, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA. praveen_sethupathy@med.unc.edu.
Samir N P KeladaDepartment of Genetics, University of North Carolina, 120 Mason Farm Road, Chapel Hill, NC, 27599, USA. samir_kelada@med.unc.edu.
University of North Carolina at Chapel Hill · USJackson Laboratory · US

Funding

Shared Resource ManagementP30CA034196 · NCI · JACKSON LABORATORY · PI William Carl Skarnes · 1985 to 2026
$61.9M
UNC and PERLEGEN, IncP50GM076468 · NIGMS · JACKSON LABORATORY · PI PETKOV, PETKO M · 2006 to 2015
$31.0M
Systems Genetic Analysis of Multi-parent CrossesR01GM070683 · NIGMS · JACKSON LABORATORY · PI BROMAN, KARL W, CHURCHILL, GARY A · 2004 to 2022
$6.8M
Modeling heterogeneity for safe cancer prevention and detectionU01CA105417 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THREADGILL, DAVID W. · 2004 to 2013
$6.7M
Systems Genetics Resource ConsortiumU01CA134240 · NCI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI THREADGILL, DAVID W. · 2007 to 2011
$5.4M
An Interdisciplinary program for systems genomics of complex behaviorsP50HG006582 · NHGRI · UNIV OF NORTH CAROLINA CHAPEL HILL · PI PARDO-MANUEL DE VILLENA, FERNANDO · 2011 to 2013
$2.6M
UNC Predoc Training Progr in Bioinformatics/Comp BiologyT32GM067553 · NIGMS · UNIV OF NORTH CAROLINA CHAPEL HILL · PI ELSTON, TIMOTHY C · 2005 to 2019
$2.5M
Discovery of microRNA regulatory modules controlling human pancreatic islet functR00DK091318 · NIDDK · UNIV OF NORTH CAROLINA CHAPEL HILL · PI SETHUPATHY, PRAVEEN · 2012 to 2014
$737k
NCI NIH HHS P30 CA034196NCI NIH HHS U01 CA105417NCI NIH HHS U01CA105417NCI NIH HHS U01 CA134240NCI NIH HHS U01CA134240NHGRI NIH HHS P50 HG006582NHGRI NIH HHS P50HG006582NIDDK NIH HHS R00 DK091318NIDDK NIH HHS R00DK091318NIGMS NIH HHS 2T32GM067553NIGMS NIH HHS GM070683NIGMS NIH HHS GM076468NIGMS NIH HHS P50 GM076468NIGMS NIH HHS R01 GM070683NIGMS NIH HHS T32 GM067553
6 · The paper itself

Abstract

backgroundAllergic airway diseases (AADs) such as asthma are characterized in part by granulocytic airway inflammation. The gene regulatory networks that govern granulocyte recruitment are poorly understood, but evidence is accruing that microRNAs (miRNAs) play an important role. To identify miRNAs that may underlie AADs, we used two complementary approaches that leveraged the genotypic and phenotypic diversity of the Collaborative Cross (CC) mouse population. In the first approach, we sought to identify miRNA expression quantitative trait loci (eQTL) that overlap QTL for AAD-related phenotypes. Specifically, CC founder strains and incipient lines of the CC were sensitized and challenged with house dust mite allergen followed by measurement of granulocyte recruitment to the lung. Total lung RNA was isolated and miRNA was measured using arrays for CC founders and qRT-PCR for incipient CC lines.

resultsAmong CC founders, 92 miRNAs were differentially expressed. We measured the expression of 40 of the most highly expressed of these 92 miRNAs in the incipient lines of the CC and identified 18 eQTL corresponding to 14 different miRNAs. Surprisingly, half of these eQTL were distal to the corresponding miRNAs, and even on different chromosomes. One of the largest-effect local miRNA eQTL was for miR-342-3p, for which we identified putative causal variants by bioinformatic analysis of the effects of single nucleotide polymorphisms on RNA structure. None of the miRNA eQTL co-localized with QTL for eosinophil or neutrophil recruitment. In the second approach, we constructed putative miRNA/mRNA regulatory networks and identified three miRNAs (miR-497, miR-351 and miR-31) as candidate master regulators of genes associated with neutrophil recruitment. Analysis of a dataset from human keratinocytes transfected with a miR-31 inhibitor revealed two target genes in common with miR-31 targets correlated with neutrophils, namely Oxsr1 and Nsf.

conclusionsmiRNA expression in the allergically inflamed murine lung is regulated by genetic loci that are smaller in effect size compared to mRNA eQTL and often act in trans. Thus our results indicate that the genetic architecture of miRNA expression is different from mRNA expression. We identified three miRNAs, miR-497, miR-351 and miR-31, that are candidate master regulators of genes associated with neutrophil recruitment. Because miR-31 is expressed in airway epithelia and is predicted to target genes with known links to neutrophilic inflammation, we suggest that miR-31 is a potentially novel regulator of airway inflammation.

Indexed as

MiceAnimalsAsthmaFounder EffectGene Expression RegulationGranulocytesLungMaleMicroRNAsPhylogenyPolymorphism, Single NucleotidePyroglyphidaeQuantitative Trait LociRodent DiseasesMicroRNAsMirn31 microRNA, mouseMIRN351 microRNA, 351mirn497 microRNA, mouse

Identifiers

PMID26303911
PMCPMC4548451
OpenAlexW1898158636

What OpenQuestion holds

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LicenceCC BY
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.