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qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data

In an isogenic cell population, phenotypic heterogeneity among individual cells is common and critical for survival of the population under different environment conditions. DNA modification is an important epigenetic factor that can regulate phenotypic heterogeneity. The single molecule real-time (...

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Detalles Bibliográficos
Autores principales: Feng, Zhixing, Li, Jing, Zhang, Jing-Ren, Zhang, Xuegong
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Oxford University Press 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267614/
https://www.ncbi.nlm.nih.gov/pubmed/25404133
http://dx.doi.org/10.1093/nar/gku1097
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author Feng, Zhixing
Li, Jing
Zhang, Jing-Ren
Zhang, Xuegong
author_facet Feng, Zhixing
Li, Jing
Zhang, Jing-Ren
Zhang, Xuegong
author_sort Feng, Zhixing
collection PubMed
description In an isogenic cell population, phenotypic heterogeneity among individual cells is common and critical for survival of the population under different environment conditions. DNA modification is an important epigenetic factor that can regulate phenotypic heterogeneity. The single molecule real-time (SMRT) sequencing technology provides a unique platform for detecting a wide range of DNA modifications, including N6-methyladenine (6-mA), N4-methylcytosine (4-mC) and 5-methylcytosine (5-mC). Here we present qDNAmod, a novel bioinformatic tool for genome-wide quantitative profiling of intercellular heterogeneity of DNA modification from SMRT sequencing data. It is capable of estimating proportion of isogenic haploid cells, in which the same loci of the genome are differentially modified. We tested the reliability of qDNAmod with the SMRT sequencing data of Streptococcus pneumoniae strain ST556. qDNAmod detected extensive intercellular heterogeneity of DNA methylation (6-mA) in a clonal population of ST556. Subsequent biochemical analyses revealed that the recognition sequences of two type I restriction–modification (R-M) systems are responsible for the intercellular heterogeneity of DNA methylation initially identified by qDNAmod. qDNAmod thus represents a valuable tool for studying intercellular phenotypic heterogeneity from genome-wide DNA modification.
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spelling pubmed-42676142014-12-23 qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data Feng, Zhixing Li, Jing Zhang, Jing-Ren Zhang, Xuegong Nucleic Acids Res Computational Biology In an isogenic cell population, phenotypic heterogeneity among individual cells is common and critical for survival of the population under different environment conditions. DNA modification is an important epigenetic factor that can regulate phenotypic heterogeneity. The single molecule real-time (SMRT) sequencing technology provides a unique platform for detecting a wide range of DNA modifications, including N6-methyladenine (6-mA), N4-methylcytosine (4-mC) and 5-methylcytosine (5-mC). Here we present qDNAmod, a novel bioinformatic tool for genome-wide quantitative profiling of intercellular heterogeneity of DNA modification from SMRT sequencing data. It is capable of estimating proportion of isogenic haploid cells, in which the same loci of the genome are differentially modified. We tested the reliability of qDNAmod with the SMRT sequencing data of Streptococcus pneumoniae strain ST556. qDNAmod detected extensive intercellular heterogeneity of DNA methylation (6-mA) in a clonal population of ST556. Subsequent biochemical analyses revealed that the recognition sequences of two type I restriction–modification (R-M) systems are responsible for the intercellular heterogeneity of DNA methylation initially identified by qDNAmod. qDNAmod thus represents a valuable tool for studying intercellular phenotypic heterogeneity from genome-wide DNA modification. Oxford University Press 2014-12-16 2014-11-17 /pmc/articles/PMC4267614/ /pubmed/25404133 http://dx.doi.org/10.1093/nar/gku1097 Text en © The Author(s) 2014. Published by Oxford University Press on behalf of Nucleic Acids Research. 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 reuse, distribution, and reproduction in any medium, provided the original work is properly cited.
spellingShingle Computational Biology
Feng, Zhixing
Li, Jing
Zhang, Jing-Ren
Zhang, Xuegong
qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title_full qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title_fullStr qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title_full_unstemmed qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title_short qDNAmod: a statistical model-based tool to reveal intercellular heterogeneity of DNA modification from SMRT sequencing data
title_sort qdnamod: a statistical model-based tool to reveal intercellular heterogeneity of dna modification from smrt sequencing data
topic Computational Biology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4267614/
https://www.ncbi.nlm.nih.gov/pubmed/25404133
http://dx.doi.org/10.1093/nar/gku1097
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