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DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features

BACKGROUND: Pathogenic mutations in genes that control chromatin function have been implicated in rare genetic syndromes. These chromatin modifiers exhibit extraordinary diversity in the scale of the epigenetic changes they affect, from single basepair modifications by DNMT1 to whole genome structur...

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Autores principales: Bondhus, Leroy, Wei, Angela, Arboleda, Valerie A.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9447346/
https://www.ncbi.nlm.nih.gov/pubmed/36064314
http://dx.doi.org/10.1186/s12859-022-04899-1
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author Bondhus, Leroy
Wei, Angela
Arboleda, Valerie A.
author_facet Bondhus, Leroy
Wei, Angela
Arboleda, Valerie A.
author_sort Bondhus, Leroy
collection PubMed
description BACKGROUND: Pathogenic mutations in genes that control chromatin function have been implicated in rare genetic syndromes. These chromatin modifiers exhibit extraordinary diversity in the scale of the epigenetic changes they affect, from single basepair modifications by DNMT1 to whole genome structural changes by PRM1/2. Patterns of DNA methylation are related to a diverse set of epigenetic features across this full range of epigenetic scale, making DNA methylation valuable for mapping regions of general epigenetic dysregulation. However, existing methods are unable to accurately identify regions of differential methylation across this full range of epigenetic scale directly from DNA methylation data. RESULTS: To address this, we developed DMRscaler, a novel method that uses an iterative windowing procedure to capture regions of differential DNA methylation (DMRs) ranging in size from single basepairs to whole chromosomes. We benchmarked DMRscaler against several DMR callers in simulated and natural data comparing XX and XY peripheral blood samples. DMRscaler was the only method that accurately called DMRs ranging in size from 100 bp to 1 Mb (pearson's r = 0.94) and up to 152 Mb on the X-chromosome. We then analyzed methylation data from rare-disease cohorts that harbor chromatin modifier gene mutations in NSD1, EZH2, and KAT6A where DMRscaler identified novel DMRs spanning gene clusters involved in development. CONCLUSION: Taken together, our results show DMRscaler is uniquely able to capture the size of DMR features across the full range of epigenetic scale and identify novel, co-regulated regions that drive epigenetic dysregulation in human disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04899-1.
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spelling pubmed-94473462022-09-07 DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features Bondhus, Leroy Wei, Angela Arboleda, Valerie A. BMC Bioinformatics Software BACKGROUND: Pathogenic mutations in genes that control chromatin function have been implicated in rare genetic syndromes. These chromatin modifiers exhibit extraordinary diversity in the scale of the epigenetic changes they affect, from single basepair modifications by DNMT1 to whole genome structural changes by PRM1/2. Patterns of DNA methylation are related to a diverse set of epigenetic features across this full range of epigenetic scale, making DNA methylation valuable for mapping regions of general epigenetic dysregulation. However, existing methods are unable to accurately identify regions of differential methylation across this full range of epigenetic scale directly from DNA methylation data. RESULTS: To address this, we developed DMRscaler, a novel method that uses an iterative windowing procedure to capture regions of differential DNA methylation (DMRs) ranging in size from single basepairs to whole chromosomes. We benchmarked DMRscaler against several DMR callers in simulated and natural data comparing XX and XY peripheral blood samples. DMRscaler was the only method that accurately called DMRs ranging in size from 100 bp to 1 Mb (pearson's r = 0.94) and up to 152 Mb on the X-chromosome. We then analyzed methylation data from rare-disease cohorts that harbor chromatin modifier gene mutations in NSD1, EZH2, and KAT6A where DMRscaler identified novel DMRs spanning gene clusters involved in development. CONCLUSION: Taken together, our results show DMRscaler is uniquely able to capture the size of DMR features across the full range of epigenetic scale and identify novel, co-regulated regions that drive epigenetic dysregulation in human disease. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12859-022-04899-1. BioMed Central 2022-09-05 /pmc/articles/PMC9447346/ /pubmed/36064314 http://dx.doi.org/10.1186/s12859-022-04899-1 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis 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 Software
Bondhus, Leroy
Wei, Angela
Arboleda, Valerie A.
DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title_full DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title_fullStr DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title_full_unstemmed DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title_short DMRscaler: a scale-aware method to identify regions of differential DNA methylation spanning basepair to multi-megabase features
title_sort dmrscaler: a scale-aware method to identify regions of differential dna methylation spanning basepair to multi-megabase features
topic Software
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9447346/
https://www.ncbi.nlm.nih.gov/pubmed/36064314
http://dx.doi.org/10.1186/s12859-022-04899-1
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