Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites

Genome-wide and fine mapping studies have shown that more than 90% of genetic variants associated with autoimmune diseases (AID) are located in non-coding regions of the human genome and especially in regulatory sequences, including microRNAs (miRNA) target sites. MiRNAs are small endogenous noncodi...

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Main Authors: Rodrigo C. de Almeida, Vinícius S. Chagas, Mauro A. A. Castro, Maria L. Petzl-Erler
Format: Article
Language:English
Published: Frontiers Media S.A. 2018-04-01
Series:Frontiers in Genetics
Subjects:
Online Access:http://journal.frontiersin.org/article/10.3389/fgene.2018.00139/full
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author Rodrigo C. de Almeida
Rodrigo C. de Almeida
Vinícius S. Chagas
Mauro A. A. Castro
Maria L. Petzl-Erler
author_facet Rodrigo C. de Almeida
Rodrigo C. de Almeida
Vinícius S. Chagas
Mauro A. A. Castro
Maria L. Petzl-Erler
author_sort Rodrigo C. de Almeida
collection DOAJ
description Genome-wide and fine mapping studies have shown that more than 90% of genetic variants associated with autoimmune diseases (AID) are located in non-coding regions of the human genome and especially in regulatory sequences, including microRNAs (miRNA) target sites. MiRNAs are small endogenous noncoding RNAs that modulate gene expression at the post-transcriptional level. Single nucleotide polymorphisms (SNPs) located within the 3′ untranslated region of their target mRNAs (miRSNP) can alter miRNA binding sites. Yet, little is known about their effect on regulation by miRNA and the consequences for AID. Conversely, it is well known that two or more AID may share part of their genetic background. Here, we hypothesized that miRSNPs could be associated with more than one AID. To identify miRSNPs associated with AID, we integrated results from three different prediction tools (Polymirts, miRSNP, and miRSNPscore) using a naïve Bayes classifier approach to identify miRSNPs predicted to affect binding sites of miRNAs. Further, to detect miRSNPs associated with two or more AID, we integrated predictions with summary statistics from 12 AID studies. In addition, to prioritize miRSNPs, miRNAs and AID-associated target genes, we used public expression quantitative trait locus (eQTL) data and mRNA-seq and small RNA-seq data. We identified 34 miRNSPs associated with at least two AID. Furthermore, we found 86 miRNAs predicted to target 18 of the associated gene's mRNAs. Our integrative approach revealed new insights into miRNAs and AID associated target genes. Thus, it helped to prioritize AID noncoding risk SNPs that might be involved in the causal mechanisms, providing valuable information for further functional studies.
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spelling doaj.art-a086b6372e514333918382f6b18c9b822022-12-21T19:37:40ZengFrontiers Media S.A.Frontiers in Genetics1664-80212018-04-01910.3389/fgene.2018.00139349768Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding SitesRodrigo C. de Almeida0Rodrigo C. de Almeida1Vinícius S. Chagas2Mauro A. A. Castro3Maria L. Petzl-Erler4Human Molecular Genetics Laboratory, Department of Genetics, Federal University of Paraná, Curitiba, BrazilMolecular Epidemiology, Department of Biomedical Data Sciences, Leiden University Medical Center, Leiden, NetherlandsBioinformatics and Systems Biology Laboratory, Federal University of Paraná, Curitiba, BrazilBioinformatics and Systems Biology Laboratory, Federal University of Paraná, Curitiba, BrazilHuman Molecular Genetics Laboratory, Department of Genetics, Federal University of Paraná, Curitiba, BrazilGenome-wide and fine mapping studies have shown that more than 90% of genetic variants associated with autoimmune diseases (AID) are located in non-coding regions of the human genome and especially in regulatory sequences, including microRNAs (miRNA) target sites. MiRNAs are small endogenous noncoding RNAs that modulate gene expression at the post-transcriptional level. Single nucleotide polymorphisms (SNPs) located within the 3′ untranslated region of their target mRNAs (miRSNP) can alter miRNA binding sites. Yet, little is known about their effect on regulation by miRNA and the consequences for AID. Conversely, it is well known that two or more AID may share part of their genetic background. Here, we hypothesized that miRSNPs could be associated with more than one AID. To identify miRSNPs associated with AID, we integrated results from three different prediction tools (Polymirts, miRSNP, and miRSNPscore) using a naïve Bayes classifier approach to identify miRSNPs predicted to affect binding sites of miRNAs. Further, to detect miRSNPs associated with two or more AID, we integrated predictions with summary statistics from 12 AID studies. In addition, to prioritize miRSNPs, miRNAs and AID-associated target genes, we used public expression quantitative trait locus (eQTL) data and mRNA-seq and small RNA-seq data. We identified 34 miRNSPs associated with at least two AID. Furthermore, we found 86 miRNAs predicted to target 18 of the associated gene's mRNAs. Our integrative approach revealed new insights into miRNAs and AID associated target genes. Thus, it helped to prioritize AID noncoding risk SNPs that might be involved in the causal mechanisms, providing valuable information for further functional studies.http://journal.frontiersin.org/article/10.3389/fgene.2018.00139/fullmicroRNASNPautoimmunityeQTLGWASdata integration
spellingShingle Rodrigo C. de Almeida
Rodrigo C. de Almeida
Vinícius S. Chagas
Mauro A. A. Castro
Maria L. Petzl-Erler
Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
Frontiers in Genetics
microRNA
SNP
autoimmunity
eQTL
GWAS
data integration
title Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
title_full Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
title_fullStr Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
title_full_unstemmed Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
title_short Integrative Analysis Identifies Genetic Variants Associated With Autoimmune Diseases Affecting Putative MicroRNA Binding Sites
title_sort integrative analysis identifies genetic variants associated with autoimmune diseases affecting putative microrna binding sites
topic microRNA
SNP
autoimmunity
eQTL
GWAS
data integration
url http://journal.frontiersin.org/article/10.3389/fgene.2018.00139/full
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