Genomics, Proteomics & Bioinformatics
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.
| 论文编号: | DOI:10.1016/j.gpb.2018.07.002 |
| 论文题目: | HeteroMeth: A Database of Cell-to-cell Heterogeneity in DNA Methylation |
| 英文论文题目: | HeteroMeth: A Database of Cell-to-cell Heterogeneity in DNA Methylation |
| 第一作者: | Qing Huan, Yuliang Zhang, Shaohuan Wu, and WenfengQian |
| 英文第一作者: | Qing Huan, Yuliang Zhang, Shaohuan Wu, and WenfengQian |
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| 发表年度: | 2018-09-13 |
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| 摘要: | 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. |
| 英文摘要: | 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. |
| 刊物名称: | Genomics, Proteomics & Bioinformatics |
| 英文刊物名称: | Genomics, Proteomics & Bioinformatics |
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| 其它备注: | Qing Huan, Yuliang Zhang, Shaohuan Wu, and WenfengQian. HeteroMeth: A Database of Cell-to-cell Heterogeneity in DNA Methylation. Genomics, Proteomics & Bioinformatics. DOI:10.1016/j.gpb.2018.07.002 |
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