Literature DB >> 25954028

Systematic DNA methylation analysis of multiple cell lines reveals common and specific patterns within and across tissues of origin.

Xiaofei Yang1, Xiaojian Shao2, Lin Gao3, Shihua Zhang4.   

Abstract

DNA methylation is a key functional regulatory mechanism in human genome, which plays critical roles in development, differentiation and many diseases. With rapid progress of large-scale projects (e.g. ENCODE), many DNA methylation data across diverse cell lines have been produced. However, common methylation patterns, cell lineage- and cell line-specific DNA methylation patterns across multiple cell lines have not yet been explored completely. Using the DNA methylation data across 54 human cell lines, we identified 35 276 local DNA methylation regions called local clusters of CpG sites (LCCSs). We constructed an LCCS co-methylation network and investigated the common DNA methylation patterns across all cell lines, which reveal two distinct groups in terms of their methylation level and genomic characteristics. We further detected diverse sets of cell lineage-specific high- and low-methylation patterns, which were depleted in promoter, CpG island (CGI) and repeat regions but enriched in gene body and non-CGI regions, especially the CGI shore regions. We discovered that the cell lineage-specific low-methylated LCCSs were enriched with functional transcriptional factor binding motif regions. Moreover, the detected cell line-specific high- and low-methylated patterns show distinct enrichments in cell line-specific chromatin states and functional relevance with the corresponding cell lines.
© The Author 2015. Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com.

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Year:  2015        PMID: 25954028     DOI: 10.1093/hmg/ddv172

Source DB:  PubMed          Journal:  Hum Mol Genet        ISSN: 0964-6906            Impact factor:   6.150


  16 in total

1.  Variability in DNA methylation at the serotonin transporter gene promoter: epigenetic mechanism or cell-type artifact?

Authors:  Sarah R Moore; Michael S Kobor
Journal:  Mol Psychiatry       Date:  2018-08-06       Impact factor: 15.992

2.  Understanding the role of the chromosome 15q25.1 in COPD through epigenetics and transcriptomics.

Authors:  Ivana Nedeljkovic; Elena Carnero-Montoro; Lies Lahousse; Diana A van der Plaat; Kim de Jong; Judith M Vonk; Cleo C van Diemen; Alen Faiz; Maarten van den Berge; Ma'en Obeidat; Yohan Bossé; David C Nickle; Bios Consortium; Andre G Uitterlinden; Joyce J B van Meurs; Bruno C H Stricker; Guy G Brusselle; Dirkje S Postma; H Marike Boezen; Cornelia M van Duijn; Najaf Amin
Journal:  Eur J Hum Genet       Date:  2018-02-08       Impact factor: 4.246

3.  Systematic identification and annotation of human methylation marks based on bisulfite sequencing methylomes reveals distinct roles of cell type-specific hypomethylation in the regulation of cell identity genes.

Authors:  Hongbo Liu; Xiaojuan Liu; Shumei Zhang; Jie Lv; Song Li; Shipeng Shang; Shanshan Jia; Yanjun Wei; Fang Wang; Jianzhong Su; Qiong Wu; Yan Zhang
Journal:  Nucleic Acids Res       Date:  2015-12-03       Impact factor: 16.971

4.  CD47 is a direct target of SNAI1 and ZEB1 and its blockade activates the phagocytosis of breast cancer cells undergoing EMT.

Authors:  Muhammad Zaeem Noman; Kris Van Moer; Vanessa Marani; Robert M Gemmill; Léon-Charles Tranchevent; Francisco Azuaje; Arnaud Muller; Salem Chouaib; Jean Paul Thiery; Guy Berchem; Bassam Janji
Journal:  Oncoimmunology       Date:  2018-02-15       Impact factor: 8.110

5.  Whole-genome bisulfite sequencing maps from multiple human tissues reveal novel CpG islands associated with tissue-specific regulation.

Authors:  Isabel Mendizabal; Soojin V Yi
Journal:  Hum Mol Genet       Date:  2015-10-28       Impact factor: 6.150

6.  Multiple network algorithm for epigenetic modules via the integration of genome-wide DNA methylation and gene expression data.

Authors:  Xiaoke Ma; Zaiyi Liu; Zhongyuan Zhang; Xiaotai Huang; Wanxin Tang
Journal:  BMC Bioinformatics       Date:  2017-01-31       Impact factor: 3.169

7.  BNDF methylation in mothers and newborns is associated with maternal exposure to war trauma.

Authors:  Darlene A Kertes; Samarth S Bhatt; Hayley S Kamin; David A Hughes; Nicole C Rodney; Connie J Mulligan
Journal:  Clin Epigenetics       Date:  2017-06-30       Impact factor: 6.551

8.  Pan-cancer analysis of frequent DNA co-methylation patterns reveals consistent epigenetic landscape changes in multiple cancers.

Authors:  Jie Zhang; Kun Huang
Journal:  BMC Genomics       Date:  2017-01-25       Impact factor: 3.969

9.  The dynamic DNA methylation landscape of the mutL homolog 1 shore is altered by MLH1-93G>A polymorphism in normal tissues and colorectal cancer.

Authors:  Andrea J Savio; Miralem Mrkonjic; Mathieu Lemire; Steven Gallinger; Julia A Knight; Bharat Bapat
Journal:  Clin Epigenetics       Date:  2017-03-09       Impact factor: 6.551

10.  Differential analysis of biological networks.

Authors:  Da Ruan; Alastair Young; Giovanni Montana
Journal:  BMC Bioinformatics       Date:  2015-10-09       Impact factor: 3.169

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