Literature DB >> 31028648

Simultaneous Profiling of mRNA Transcriptome and DNA Methylome from a Single Cell.

Youjin Hu1, Qin An2, Ying Guo3, Jiawei Zhong4, Shuxin Fan4, Pinhong Rao4, Xialin Liu4, Yizhi Liu4, Guoping Fan2.   

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.

Keywords:  Multi-omics profiling; Single-cell DNA methylome; Single-cell sequencing; Single-cell transcriptome

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Year:  2019        PMID: 31028648     DOI: 10.1007/978-1-4939-9240-9_21

Source DB:  PubMed          Journal:  Methods Mol Biol        ISSN: 1064-3745


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