期刊
GENOME BIOLOGY
卷 17, 期 -, 页码 -出版社
BMC
DOI: 10.1186/s13059-016-0950-z
关键词
Single-cell methylome; Single-cell transcriptome; Sensory neurons; Dorsal root ganglion; Gene regulation
资金
- CIRM CESCG CRP Grant Program
- NIH CTSI [UL1-TR000124]
- National Cancer Institute of the National Institutes of Health [P50CA092131]
- National Program on Key Basic Research Project (973 Program) [2015CB964702, 2015CB964601]
- Joint Research Fund for Overseas Chinese, Hong Kong and Macao Young Scholars [31428016]
- National Natural Science Foundation of China [81430026]
- Experimental Animal Research Fund, Science and Technology Commission of Shanghai Municipality [15140903900]
- Shanghai Municipal Commission of Health and Family Planning [XBR2013094]
- Jiangsu Science and Technology Planning Project [BM2014052]
- Chinese National Overseas Postdoc Scholarship [2013-057]
- National Institute of Arthritis and Musculoskeletal and Skin Diseases training grant [T32AR059033]
Background: Single-cell transcriptome and single-cell methylome technologies have become powerful tools to study RNA and DNA methylation profiles of single cells at a genome-wide scale. A major challenge has been to understand the direct correlation of DNA methylation and gene expression within single-cells. Due to large cell-to-cell variability and the lack of direct measurements of transcriptome and methylome of the same cell, the association is still unclear. Results: Here, we describe a novel method (scMT-seq) that simultaneously profiles both DNA methylome and transcriptome from the same cell. In sensory neurons, we consistently identify transcriptome and methylome heterogeneity among single cells but the majority of the expression variance is not explained by proximal promoter methylation, with the exception of genes that do not contain CpG islands. By contrast, gene body methylation is positively associated with gene expression for only those genes that contain a CpG island promoter. Furthermore, using single nucleotide polymorphism patterns from our hybrid mouse model, we also find positive correlation of allelic gene body methylation with allelic expression. Conclusions: Our method can be used to detect transcriptome, methylome, and single nucleotide polymorphism information within single cells to dissect the mechanisms of epigenetic gene regulation.
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