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A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome

Central questions to epigenome evolution include whether interspecies changes of histone modifications are independent of evolutionary changes of DNA, and if there is dependence whether they depend on any specific types of DNA sequence changes. Here, we present a likelihood approach for testing hypo...

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Detalles Bibliográficos
Autores principales: Lu, Jia, Cao, Xiaoyi, Zhong, Sheng
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2018
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324829/
https://www.ncbi.nlm.nih.gov/pubmed/30586383
http://dx.doi.org/10.1371/journal.pcbi.1006673
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author Lu, Jia
Cao, Xiaoyi
Zhong, Sheng
author_facet Lu, Jia
Cao, Xiaoyi
Zhong, Sheng
author_sort Lu, Jia
collection PubMed
description Central questions to epigenome evolution include whether interspecies changes of histone modifications are independent of evolutionary changes of DNA, and if there is dependence whether they depend on any specific types of DNA sequence changes. Here, we present a likelihood approach for testing hypotheses on the co-evolution of genome and histone modifications. The gist of this approach is to convert evolutionary biology hypotheses into probabilistic forms, by explicitly expressing the joint probability of multispecies DNA sequences and histone modifications, which we refer to as a class of Joint Evolutionary Model for the Genome and the Epigenome (JEMGE). JEMGE can be summarized as a mixture model of four components representing four evolutionary hypotheses, namely dependence and independence of interspecies epigenomic variations to underlying sequence substitutions and to underlying sequence insertions and deletions (indels). We implemented a maximum likelihood method to fit the models to the data. Based on comparison of likelihoods, we inferred whether interspecies epigenomic variations depended on substitution or indels in local genomic sequences based on DNase hypersensitivity and spermatid H3K4me3 ChIP-seq data from human and rhesus macaque. Approximately 5.5% of homologous regions in the genomes exhibited H3K4me3 modification in either species, among which approximately 67% homologous regions exhibited local-sequence-dependent interspecies H3K4me3 variations. Substitutions accounted for less local-sequence-dependent H3K4me3 variations than indels. Among transposon-mediated indels, ERV1 insertions and L1 insertions were most strongly associated with H3K4me3 gains and losses, respectively. By initiating probabilistic formulation on the co-evolution of genomes and epigenomes, JEMGE helps to bring evolutionary biology principles to comparative epigenomic studies.
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spelling pubmed-63248292019-01-19 A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome Lu, Jia Cao, Xiaoyi Zhong, Sheng PLoS Comput Biol Research Article Central questions to epigenome evolution include whether interspecies changes of histone modifications are independent of evolutionary changes of DNA, and if there is dependence whether they depend on any specific types of DNA sequence changes. Here, we present a likelihood approach for testing hypotheses on the co-evolution of genome and histone modifications. The gist of this approach is to convert evolutionary biology hypotheses into probabilistic forms, by explicitly expressing the joint probability of multispecies DNA sequences and histone modifications, which we refer to as a class of Joint Evolutionary Model for the Genome and the Epigenome (JEMGE). JEMGE can be summarized as a mixture model of four components representing four evolutionary hypotheses, namely dependence and independence of interspecies epigenomic variations to underlying sequence substitutions and to underlying sequence insertions and deletions (indels). We implemented a maximum likelihood method to fit the models to the data. Based on comparison of likelihoods, we inferred whether interspecies epigenomic variations depended on substitution or indels in local genomic sequences based on DNase hypersensitivity and spermatid H3K4me3 ChIP-seq data from human and rhesus macaque. Approximately 5.5% of homologous regions in the genomes exhibited H3K4me3 modification in either species, among which approximately 67% homologous regions exhibited local-sequence-dependent interspecies H3K4me3 variations. Substitutions accounted for less local-sequence-dependent H3K4me3 variations than indels. Among transposon-mediated indels, ERV1 insertions and L1 insertions were most strongly associated with H3K4me3 gains and losses, respectively. By initiating probabilistic formulation on the co-evolution of genomes and epigenomes, JEMGE helps to bring evolutionary biology principles to comparative epigenomic studies. Public Library of Science 2018-12-26 /pmc/articles/PMC6324829/ /pubmed/30586383 http://dx.doi.org/10.1371/journal.pcbi.1006673 Text en © 2018 Lu et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Lu, Jia
Cao, Xiaoyi
Zhong, Sheng
A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title_full A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title_fullStr A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title_full_unstemmed A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title_short A likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
title_sort likelihood approach to testing hypotheses on the co-evolution of epigenome and genome
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6324829/
https://www.ncbi.nlm.nih.gov/pubmed/30586383
http://dx.doi.org/10.1371/journal.pcbi.1006673
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