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Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species

DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily ap...

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Autores principales: Huh, Iksoo, Wu, Xin, Park, Taesung, Yi, Soojin V
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357555/
https://www.ncbi.nlm.nih.gov/pubmed/28981571
http://dx.doi.org/10.1093/bib/bbx077
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author Huh, Iksoo
Wu, Xin
Park, Taesung
Yi, Soojin V
author_facet Huh, Iksoo
Wu, Xin
Park, Taesung
Yi, Soojin V
author_sort Huh, Iksoo
collection PubMed
description DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation.
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spelling pubmed-63575552019-02-08 Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species Huh, Iksoo Wu, Xin Park, Taesung Yi, Soojin V Brief Bioinform Paper DNA methylation is one of the most extensively studied epigenetic modifications of genomic DNA. In recent years, sequencing of bisulfite-converted DNA, particularly via next-generation sequencing technologies, has become a widely popular method to study DNA methylation. This method can be readily applied to a variety of species, dramatically expanding the scope of DNA methylation studies beyond the traditionally studied human and mouse systems. In parallel to the increasing wealth of genomic methylation profiles, many statistical tools have been developed to detect differentially methylated loci (DMLs) or differentially methylated regions (DMRs) between biological conditions. We discuss and summarize several key properties of currently available tools to detect DMLs and DMRs from sequencing of bisulfite-converted DNA. However, the majority of the statistical tools developed for DML/DMR analyses have been validated using only mammalian data sets, and less priority has been placed on the analyses of invertebrate or plant DNA methylation data. We demonstrate that genomic methylation profiles of non-mammalian species are often highly distinct from those of mammalian species using examples of honey bees and humans. We then discuss how such differences in data properties may affect statistical analyses. Based on these differences, we provide three specific recommendations to improve the power and accuracy of DML and DMR analyses of invertebrate data when using currently available statistical tools. These considerations should facilitate systematic and robust analyses of DNA methylation from diverse species, thus advancing our understanding of DNA methylation. Oxford University Press 2017-07-21 /pmc/articles/PMC6357555/ /pubmed/28981571 http://dx.doi.org/10.1093/bib/bbx077 Text en © The Author 2017. Published by Oxford University Press. http://creativecommons.org/licenses/by-nc/4.0/ This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/4.0/), which permits non-commercial re-use, distribution, and reproduction in any medium, provided the original work is properly cited. For commercial re-use, please contact journals.permissions@oup.com
spellingShingle Paper
Huh, Iksoo
Wu, Xin
Park, Taesung
Yi, Soojin V
Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title_full Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title_fullStr Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title_full_unstemmed Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title_short Detecting differential DNA methylation from sequencing of bisulfite converted DNA of diverse species
title_sort detecting differential dna methylation from sequencing of bisulfite converted dna of diverse species
topic Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6357555/
https://www.ncbi.nlm.nih.gov/pubmed/28981571
http://dx.doi.org/10.1093/bib/bbx077
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