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Genetic impacts on DNA methylation help elucidate regulatory genomic processes

BACKGROUND: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium Methylati...

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Autores principales: Villicaña, Sergio, Castillo-Fernandez, Juan, Hannon, Eilis, Christiansen, Colette, Tsai, Pei-Chien, Maddock, Jane, Kuh, Diana, Suderman, Matthew, Power, Christine, Relton, Caroline, Ploubidis, George, Wong, Andrew, Hardy, Rebecca, Goodman, Alissa, Ong, Ken K., Bell, Jordana T.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391992/
https://www.ncbi.nlm.nih.gov/pubmed/37525248
http://dx.doi.org/10.1186/s13059-023-03011-x
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author Villicaña, Sergio
Castillo-Fernandez, Juan
Hannon, Eilis
Christiansen, Colette
Tsai, Pei-Chien
Maddock, Jane
Kuh, Diana
Suderman, Matthew
Power, Christine
Relton, Caroline
Ploubidis, George
Wong, Andrew
Hardy, Rebecca
Goodman, Alissa
Ong, Ken K.
Bell, Jordana T.
author_facet Villicaña, Sergio
Castillo-Fernandez, Juan
Hannon, Eilis
Christiansen, Colette
Tsai, Pei-Chien
Maddock, Jane
Kuh, Diana
Suderman, Matthew
Power, Christine
Relton, Caroline
Ploubidis, George
Wong, Andrew
Hardy, Rebecca
Goodman, Alissa
Ong, Ken K.
Bell, Jordana T.
author_sort Villicaña, Sergio
collection PubMed
description BACKGROUND: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03011-x.
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spelling pubmed-103919922023-08-02 Genetic impacts on DNA methylation help elucidate regulatory genomic processes Villicaña, Sergio Castillo-Fernandez, Juan Hannon, Eilis Christiansen, Colette Tsai, Pei-Chien Maddock, Jane Kuh, Diana Suderman, Matthew Power, Christine Relton, Caroline Ploubidis, George Wong, Andrew Hardy, Rebecca Goodman, Alissa Ong, Ken K. Bell, Jordana T. Genome Biol Research BACKGROUND: Pinpointing genetic impacts on DNA methylation can improve our understanding of pathways that underlie gene regulation and disease risk. RESULTS: We report heritability and methylation quantitative trait locus (meQTL) analysis at 724,499 CpGs profiled with the Illumina Infinium MethylationEPIC array in 2358 blood samples from three UK cohorts. Methylation levels at 34.2% of CpGs are affected by SNPs, and 98% of effects are cis-acting or within 1 Mbp of the tested CpG. Our results are consistent with meQTL analyses based on the former Illumina Infinium HumanMethylation450 array. Both SNPs and CpGs with meQTLs are overrepresented in enhancers, which have improved coverage on this platform compared to previous approaches. Co-localisation analyses across genetic effects on DNA methylation and 56 human traits identify 1520 co-localisations across 1325 unique CpGs and 34 phenotypes, including in disease-relevant genes, such as USP1 and DOCK7 (total cholesterol levels), and ICOSLG (inflammatory bowel disease). Enrichment analysis of meQTLs and integration with expression QTLs give insights into mechanisms underlying cis-meQTLs (e.g. through disruption of transcription factor binding sites for CTCF and SMC3) and trans-meQTLs (e.g. through regulating the expression of ACD and SENP7 which can modulate DNA methylation at distal sites). CONCLUSIONS: Our findings improve the characterisation of the mechanisms underlying DNA methylation variability and are informative for prioritisation of GWAS variants for functional follow-ups. The MeQTL EPIC Database and viewer are available online at https://epicmeqtl.kcl.ac.uk. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s13059-023-03011-x. BioMed Central 2023-07-31 /pmc/articles/PMC10391992/ /pubmed/37525248 http://dx.doi.org/10.1186/s13059-023-03011-x Text en © The Author(s) 2023 https://creativecommons.org/licenses/by/4.0/Open Access This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Villicaña, Sergio
Castillo-Fernandez, Juan
Hannon, Eilis
Christiansen, Colette
Tsai, Pei-Chien
Maddock, Jane
Kuh, Diana
Suderman, Matthew
Power, Christine
Relton, Caroline
Ploubidis, George
Wong, Andrew
Hardy, Rebecca
Goodman, Alissa
Ong, Ken K.
Bell, Jordana T.
Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title_full Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title_fullStr Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title_full_unstemmed Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title_short Genetic impacts on DNA methylation help elucidate regulatory genomic processes
title_sort genetic impacts on dna methylation help elucidate regulatory genomic processes
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10391992/
https://www.ncbi.nlm.nih.gov/pubmed/37525248
http://dx.doi.org/10.1186/s13059-023-03011-x
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