Please use this identifier to cite or link to this item: https://doi.org/10.1371/journal.pone.0004721
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dc.titleDissecting nucleosome free regions by a segmental semi-Markov model
dc.contributor.authorSun W.
dc.contributor.authorXie W.
dc.contributor.authorXu F.
dc.contributor.authorGrunstein M.
dc.contributor.authorLi K.-C.
dc.date.accessioned2019-11-08T00:53:35Z
dc.date.available2019-11-08T00:53:35Z
dc.date.issued2009
dc.identifier.citationSun W., Xie W., Xu F., Grunstein M., Li K.-C. (2009). Dissecting nucleosome free regions by a segmental semi-Markov model. PLoS ONE 4 (3) : e4721. ScholarBank@NUS Repository. https://doi.org/10.1371/journal.pone.0004721
dc.identifier.issn19326203
dc.identifier.urihttps://scholarbank.nus.edu.sg/handle/10635/161840
dc.description.abstractBackground: Nucleosome free regions (NFRs) play important roles in diverse biological processes including gene regulation. A genome-wide quantitative portrait of each individual NFR, with their starting and ending positions, lengths, and degrees of nucleosome depletion is critical for revealing the heterogeneity of gene regulation and chromatin organization. By averaging nucleosome occupancy levels, previous studies have identified the presence of NFRs in the promoter regions across many genes. However, evaluation of the quantitative characteristics of individual NFRs requires an NFR calling method. Methodology: In this study, we propose a statistical method to identify the patterns of NFRs from a genome-wide measurement of nucleosome occupancy. This method is based on an appropriately designed segmental semi-Markov model, which can capture each NFR pattern and output its quantitative characterizations. Our results show that the majority of the NFRs are located in intergenic regions or promoters with a length of about 400-600bp and varying degrees of nucleosome depletion. Our quantitative NFR mapping allows for an investigation of the relative impacts of transcription machinery and DNA sequence in evicting histones from NFRs. We show that while both factors have significant overall effects, their specific contributions vary across different subtypes of NFRs. Conclusion: The emphasis of our approach on the variation rather than the consensus of nucleosome free regions sets the tone for enabling the exploration of many subtler dynamic aspects of chromatin biology. � 2009 Sun et al.
dc.rightsAttribution 4.0 International
dc.rights.urihttp://creativecommons.org/licenses/by/4.0/
dc.sourceUnpaywall 20191101
dc.subjecthistone
dc.subjectspacer DNA
dc.subjectanalytic method
dc.subjectarticle
dc.subjectchromatin
dc.subjectconsensus
dc.subjectcontrolled study
dc.subjectDNA sequence
dc.subjectgene mapping
dc.subjectgenetic transcription
dc.subjectgenome analysis
dc.subjectmolecular biology
dc.subjectnucleosome
dc.subjectpromoter region
dc.subjectquantitative analysis
dc.subjectstatistical model
dc.subjectanimal
dc.subjectchromosome map
dc.subjectgenetics
dc.subjectgenomics
dc.subjecthuman
dc.subjectmethodology
dc.subjectprobability
dc.subjectAnimals
dc.subjectChromosome Mapping
dc.subjectDNA, Intergenic
dc.subjectGenomics
dc.subjectHistones
dc.subjectHumans
dc.subjectMarkov Chains
dc.subjectNucleosomes
dc.typeArticle
dc.contributor.departmentBIOCHEMISTRY
dc.description.doi10.1371/journal.pone.0004721
dc.description.sourcetitlePLoS ONE
dc.description.volume4
dc.description.issue3
dc.description.pagee4721
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