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Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells

Genetic variants have potential influence on DNA methylation and thereby regulate mRNA expression. This study aimed to comprehensively reveal the relationships among SNP, methylation and mRNA, and identify methylation‐mediated regulation patterns in human peripheral blood mononuclear cells (PBMCs)....

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Autores principales: Lu, Yi‐Hua, Wang, Bing‐Hua, Jiang, Fei, Mo, Xing‐Bo, Wu, Long‐Fei, He, Pei, Lu, Xin, Deng, Fei‐Yan, Lei, Shu‐Feng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: John Wiley and Sons Inc. 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584519/
https://www.ncbi.nlm.nih.gov/pubmed/31106970
http://dx.doi.org/10.1111/jcmm.14315
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author Lu, Yi‐Hua
Wang, Bing‐Hua
Jiang, Fei
Mo, Xing‐Bo
Wu, Long‐Fei
He, Pei
Lu, Xin
Deng, Fei‐Yan
Lei, Shu‐Feng
author_facet Lu, Yi‐Hua
Wang, Bing‐Hua
Jiang, Fei
Mo, Xing‐Bo
Wu, Long‐Fei
He, Pei
Lu, Xin
Deng, Fei‐Yan
Lei, Shu‐Feng
author_sort Lu, Yi‐Hua
collection PubMed
description Genetic variants have potential influence on DNA methylation and thereby regulate mRNA expression. This study aimed to comprehensively reveal the relationships among SNP, methylation and mRNA, and identify methylation‐mediated regulation patterns in human peripheral blood mononuclear cells (PBMCs). Based on in‐house multi‐omics datasets from 43 Chinese Han female subjects, genome‐wide association trios were constructed by simultaneously testing the following three association pairs: SNP‐methylation, methylation‐mRNA and SNP‐mRNA. Causal inference test (CIT) was used to identify methylation‐mediated genetic effects on mRNA. A total of 64,184 significant cis‐methylation quantitative trait loci (meQTLs) were identified (FDR < 0.05). Among the 745 constructed trios, 464 trios formed SNP‐methylation‐mRNA regulation chains (CIT). Network analysis (Cytoscape 3.3.0) constructed multiple complex regulation networks among SNP, methylation and mRNA (eg a total of 43 SNPs simultaneously connected to cg22517527 and further to PRMT2, DIP2A and YBEY). The regulation chains were supported by the evidence from 4DGenome database, relevant to immune or inflammatory related diseases/traits, and overlapped with previous eQTLs from dbGaP and GTEx. The results provide new insights into the regulation patterns among SNP, DNA methylation and mRNA expression, especially for the methylation‐mediated effects, and also increase our understanding of functional mechanisms underlying the established associations.
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spelling pubmed-65845192019-07-01 Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells Lu, Yi‐Hua Wang, Bing‐Hua Jiang, Fei Mo, Xing‐Bo Wu, Long‐Fei He, Pei Lu, Xin Deng, Fei‐Yan Lei, Shu‐Feng J Cell Mol Med Original Articles Genetic variants have potential influence on DNA methylation and thereby regulate mRNA expression. This study aimed to comprehensively reveal the relationships among SNP, methylation and mRNA, and identify methylation‐mediated regulation patterns in human peripheral blood mononuclear cells (PBMCs). Based on in‐house multi‐omics datasets from 43 Chinese Han female subjects, genome‐wide association trios were constructed by simultaneously testing the following three association pairs: SNP‐methylation, methylation‐mRNA and SNP‐mRNA. Causal inference test (CIT) was used to identify methylation‐mediated genetic effects on mRNA. A total of 64,184 significant cis‐methylation quantitative trait loci (meQTLs) were identified (FDR < 0.05). Among the 745 constructed trios, 464 trios formed SNP‐methylation‐mRNA regulation chains (CIT). Network analysis (Cytoscape 3.3.0) constructed multiple complex regulation networks among SNP, methylation and mRNA (eg a total of 43 SNPs simultaneously connected to cg22517527 and further to PRMT2, DIP2A and YBEY). The regulation chains were supported by the evidence from 4DGenome database, relevant to immune or inflammatory related diseases/traits, and overlapped with previous eQTLs from dbGaP and GTEx. The results provide new insights into the regulation patterns among SNP, DNA methylation and mRNA expression, especially for the methylation‐mediated effects, and also increase our understanding of functional mechanisms underlying the established associations. John Wiley and Sons Inc. 2019-05-20 2019-07 /pmc/articles/PMC6584519/ /pubmed/31106970 http://dx.doi.org/10.1111/jcmm.14315 Text en © 2019 The Authors. Journal of Cellular and Molecular Medicine published by John Wiley & Sons Ltd and Foundation for Cellular and Molecular Medicine. This is an open access article under the terms of the http://creativecommons.org/licenses/by/4.0/ License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
spellingShingle Original Articles
Lu, Yi‐Hua
Wang, Bing‐Hua
Jiang, Fei
Mo, Xing‐Bo
Wu, Long‐Fei
He, Pei
Lu, Xin
Deng, Fei‐Yan
Lei, Shu‐Feng
Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title_full Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title_fullStr Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title_full_unstemmed Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title_short Multi‐omics integrative analysis identified SNP‐methylation‐mRNA: Interaction in peripheral blood mononuclear cells
title_sort multi‐omics integrative analysis identified snp‐methylation‐mrna: interaction in peripheral blood mononuclear cells
topic Original Articles
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6584519/
https://www.ncbi.nlm.nih.gov/pubmed/31106970
http://dx.doi.org/10.1111/jcmm.14315
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