HeteroMeth: A Database of Cell-to-cell Heterogeneity in DNA Methylation.
10.1016/j.gpb.2018.07.002
- Author:
Qing HUAN
1
,
2
;
Yuliang ZHANG
1
,
3
,
4
;
Shaohuan WU
1
,
3
,
4
;
Wenfeng QIAN
1
,
3
,
5
Author Information
1. State Key Laboratory of Plant Genomics, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
2. Key Laboratory of Genetic Network Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China.
3. Key Laboratory of Genetic Network Biology, Institute of Genetics and Developmental Biology, Chinese Academy of Sciences, Beijing 100101, China
4. University of Chinese Academy of Sciences, Beijing 100049, China.
5. University of Chinese Academy of Sciences, Beijing 100049, China. Electronic address: wfqian@genetics.ac.cn.
- Publication Type:Journal Article
- Keywords:
Bisulfite sequencing;
Cell-to-cell heterogeneity;
DNA methylation;
Shannon entropy;
Single cell
- MeSH:
Animals;
Arabidopsis;
genetics;
Cell Line;
Computer Simulation;
DNA Methylation;
genetics;
Databases, Genetic;
Entropy;
Genetic Heterogeneity;
Genome;
High-Throughput Nucleotide Sequencing;
Humans;
Mice;
Oryza;
genetics;
Reference Standards;
Reproducibility of Results;
Sequence Analysis, DNA;
Single-Cell Analysis;
User-Computer Interface
- From:
Genomics, Proteomics & Bioinformatics
2018;16(4):234-243
- CountryChina
- Language:English
-
Abstract:
DNA methylation is an important epigenetic mark that plays a vital role in gene expression and cell differentiation. The average DNA methylation level among a group of cells has been extensively documented. However, the cell-to-cell heterogeneity in DNA methylation, which reflects the differentiation of epigenetic status among cells, remains less investigated. Here we established a gold standard of the cell-to-cell heterogeneity in DNA methylation based on single-cell bisulfite sequencing (BS-seq) data. With that, we optimized a computational pipeline for estimating the heterogeneity in DNA methylation from bulk BS-seq data. We further built HeteroMeth, a database for searching, browsing, visualizing, and downloading the data for heterogeneity in DNA methylation for a total of 141 samples in humans, mice, Arabidopsis, and rice. Three genes are used as examples to illustrate the power of HeteroMeth in the identification of unique features in DNA methylation. The optimization of the computational strategy and the construction of the database in this study complement the recent experimental attempts on single-cell DNA methylomes and will facilitate the understanding of epigenetic mechanisms underlying cell differentiation and embryonic development. HeteroMeth is publicly available at http://qianlab.genetics.ac.cn/HeteroMeth.
