Simultaneous Profiling of mRNA Transcriptome and DNA Methylome from a Single Cell
Abstract
Single-cell transcriptome and single-cell methylome analysis have successfully revealed the heterogeneity in transcriptome and DNA methylome between single cells, and have become powerful tools to understand the dynamics of transcriptome and DNA methylome during the complicated biological processes, such as differentiation and carcinogenesis.Inspired by the success of using these single-cell -omics methods to understand the regulation of a particular "-ome," more interests have been put on elucidating the regulatory relationship among multiple-omics at single-cell resolution. The simultaneous profiling of multiple-omics from the same single cell would provide us the ultimate power to understand the relationship among different "-omes," but this idea is not materialized for decades due to difficulties to assay extremely tiny amount of DNA or RNA in a single cell.To address this technical challenge, we have recently developed a novel method named scMT-seq that can simultaneously profile both DNA methylome and RNA transcriptome from the same cell. This method enabled us to measure, from a single cell, the DNA methylation status of the most informative 0.5-1 million CpG sites and mRNA level of 10,000 genes, of which 3200 genes can be further analyzed with both promoter DNA methylation and RNA transcription. Using the scMT-seq data, we have successfully shown the regulatory relationship between DNA methylation and transcriptional level in a single dorsal root ganglion neuron (Hu et al., Genome Biol 17:88, 2016). We believe the scMT-seq would be a powerful technique to uncover the regulatory mechanism between transcription and DNA methylation, and would be of wide interest beyond the epigenetics community.
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Multiple teams have created methods that jointly profile DNA methylation and RNA.
“Many groups have built from this foundation to develop technologies that co-profile the DNA methylome and transcriptome28–31.”
From The technological landscape and applications of single-cell multi-omics (2023) · cites this paper as [31]
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- Authors
- Hu, Y., An, Q., Guo, Y., Zhong, J., Fan, S., Rao, P., Liu, X., Liu, Y., & Fan, G.
- Affiliations
- Sun Yat-sen University (CN)
- University of California, Los Angeles (US)
- Central South University (CN)
- Corresponding author
- Hu, Youjin
- Venue
- Methods in Molecular Biology
- Publisher
- Springer New York
- Published
- 2019
- Volume
- 1979
- Pages
- 363-377
- ISSN
- 1064-3745 (ISSN-L)
- 1940-6029
- OpenAlex
- W2990443886
- Cited by
- 26
- References
- 19
- Citations by year
- 2026: 1 · 2025: 3 · 2024: 3 · 2023: 8 · 2022: 5 · 2021: 1 · 2020: 3 · 2019: 1
- FWCI
- 2.75
- Type
- book chapter
- Language
- en
- Open access
- closed
- Licence
- www.springer.com/tdm (tdm)
- Locations
- Methods in molecular biology (publishedVersion)
- PubMed (publishedVersion)
- The HKU Scholars Hub (University of Hong Kong) (submittedVersion)
- Funders
- National Science Foundation
- National Natural Science Foundation of China
- National Key Research and Development Program of China
- Topics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Single-cell and spatial transcriptomics
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
- Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Genomics and Chromatin Dynamics
- Keywords
- single-cell transcriptome, promoter methylation, dorsal root ganglion neurons, epigenetics, single-cell RNA sequencing
- MeSH terms
- Animals, DNA, Humans, RNA, Messenger, Software, Polymerase Chain Reaction, Sequence Analysis, RNA, CpG Islands, DNA Methylation, Gene Expression Profiling, Epigenesis, Genetic, Epigenomics, Single-Cell Analysis, Transcriptome
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