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

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.Electronic supplementary materialThe online version of this article (doi:10.1186/s12864-015-1732-9) contains supplementary material, which is available to authorized users.

RETRACTED: Genetic Architecture Modulates Diet-Induced Hepatic mRNA and miRNA Expression Profiles in Diversity Outbred Mice

“…Unlike a recent report of eQTL in yeast, we do not observe that most eQTL are trans -acting in nature ( Albert et al 2018 ), but this could be due to differences in power or model organism of each study. While the functional consequences of this prominent difference in genetic architecture of mRNA and miRNA remains unclear, similar effects have been observed in studies utilizing CC mice ( Rutledge et al 2015 ), a genetically related population to the DO mice used in this study. Although speculative, these data from the CC and DO mouse populations suggest that individual miRNAs on average may be regulated by fewer transcription factors than individual genes.…”

The microRNA miR-31 inhibits CD8+ T cell function in chronic viral infection

“…Several of these ( Ppp6c , Lats2 , Oxsr1 , Elavl1 (ref. 19) and Stk40 ) 20–23 have been reported as targets of miR-31, while eight mRNAs ( Psd4 , Sh2d1a , Ilf3 , Coro7 , Rab1b , Stra13 , Cdkn1a and Ifi30 ) represented newly identified targets of miR-31 (Fig. 3c).…”

Transcriptomic Analysis of Chronic Hepatitis B and C and Liver Cancer Reveals MicroRNA-Mediated Control of Cholesterol Synthesis Programs

“…To identify miRNA candidate master regulators, we used a tool we developed previously ( 29 ), which we subsequently named “miRHub.” We have since used miRHub successfully in several follow-up studies ( 57 – 59 ), including one in which we provided a more detailed description of the methods ( 57 ). Briefly, miRHub uses the TargetScan algorithm to predicted target sites for miRNAs of interest in the 3′ UTRs of DE genes and then determines by Monte Carlo simulation for each miRNA whether the number and strength of predicted targets is significantly greater than expected by chance.…”