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Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming

BACKGROUND: Human induced pluripotent stem cells (iPSCs) have a wide range of applications throughout the fields of basic research, disease modeling and drug screening. Epigenetic instable iPSCs with aberrant DNA methylation may divide and differentiate into cancer cells. Unfortunately, little effor...

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Autores principales: Shao, Xiaojian, Zhang, Cuiyun, Sun, Ming-An, Lu, Xuemei, Xie, Hehuang
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2014
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4242552/
https://www.ncbi.nlm.nih.gov/pubmed/25404570
http://dx.doi.org/10.1186/1471-2164-15-978
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author Shao, Xiaojian
Zhang, Cuiyun
Sun, Ming-An
Lu, Xuemei
Xie, Hehuang
author_facet Shao, Xiaojian
Zhang, Cuiyun
Sun, Ming-An
Lu, Xuemei
Xie, Hehuang
author_sort Shao, Xiaojian
collection PubMed
description BACKGROUND: Human induced pluripotent stem cells (iPSCs) have a wide range of applications throughout the fields of basic research, disease modeling and drug screening. Epigenetic instable iPSCs with aberrant DNA methylation may divide and differentiate into cancer cells. Unfortunately, little effort has been taken to compare the epigenetic variation in iPSCs with that in differentiated cells. Here, we developed an analytical procedure to decipher the DNA methylation heterogeneity of mixed cells and further exploited it to quantitatively assess the DNA methylation variation in the methylomes of adipose-derived stem cells (ADS), mature adipocytes differentiated from ADS cells (ADS-adipose) and iPSCs reprogrammed from ADS cells (ADS-iPSCs). RESULTS: We observed that the degree of DNA methylation variation varies across distinct genomic regions with promoter and 5’UTR regions exhibiting low methylation variation and Satellite showing high methylation variation. Compared with differentiated cells, ADS-iPSCs possess globally decreased methylation variation, in particular in repetitive elements. Interestingly, DNA methylation variation decreases in promoter regions during differentiation but increases during reprogramming. Methylation variation in promoter regions is negatively correlated with gene expression. In addition, genes showing a bipolar methylation pattern, with both completely methylated and completely unmethylated reads, are related to the carbohydrate metabolic process, cellular development, cellular growth, proliferation, etc. CONCLUSIONS: This study delivers a way to detect cell-subset specific methylation genes in a mixed cell population and provides a better understanding of methylation dynamics during stem cell differentiation and reprogramming. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-978) contains supplementary material, which is available to authorized users.
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spelling pubmed-42425522014-11-25 Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming Shao, Xiaojian Zhang, Cuiyun Sun, Ming-An Lu, Xuemei Xie, Hehuang BMC Genomics Research Article BACKGROUND: Human induced pluripotent stem cells (iPSCs) have a wide range of applications throughout the fields of basic research, disease modeling and drug screening. Epigenetic instable iPSCs with aberrant DNA methylation may divide and differentiate into cancer cells. Unfortunately, little effort has been taken to compare the epigenetic variation in iPSCs with that in differentiated cells. Here, we developed an analytical procedure to decipher the DNA methylation heterogeneity of mixed cells and further exploited it to quantitatively assess the DNA methylation variation in the methylomes of adipose-derived stem cells (ADS), mature adipocytes differentiated from ADS cells (ADS-adipose) and iPSCs reprogrammed from ADS cells (ADS-iPSCs). RESULTS: We observed that the degree of DNA methylation variation varies across distinct genomic regions with promoter and 5’UTR regions exhibiting low methylation variation and Satellite showing high methylation variation. Compared with differentiated cells, ADS-iPSCs possess globally decreased methylation variation, in particular in repetitive elements. Interestingly, DNA methylation variation decreases in promoter regions during differentiation but increases during reprogramming. Methylation variation in promoter regions is negatively correlated with gene expression. In addition, genes showing a bipolar methylation pattern, with both completely methylated and completely unmethylated reads, are related to the carbohydrate metabolic process, cellular development, cellular growth, proliferation, etc. CONCLUSIONS: This study delivers a way to detect cell-subset specific methylation genes in a mixed cell population and provides a better understanding of methylation dynamics during stem cell differentiation and reprogramming. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (doi:10.1186/1471-2164-15-978) contains supplementary material, which is available to authorized users. BioMed Central 2014-11-18 /pmc/articles/PMC4242552/ /pubmed/25404570 http://dx.doi.org/10.1186/1471-2164-15-978 Text en © Shao et al.; licensee BioMed Central Ltd. 2014 This article is published under license to BioMed Central Ltd. 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 work is properly credited. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Shao, Xiaojian
Zhang, Cuiyun
Sun, Ming-An
Lu, Xuemei
Xie, Hehuang
Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title_full Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title_fullStr Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title_full_unstemmed Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title_short Deciphering the heterogeneity in DNA methylation patterns during stem cell differentiation and reprogramming
title_sort deciphering the heterogeneity in dna methylation patterns during stem cell differentiation and reprogramming
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4242552/
https://www.ncbi.nlm.nih.gov/pubmed/25404570
http://dx.doi.org/10.1186/1471-2164-15-978
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