Hu Youjin, An Qin, Guo Ying, Zhong Jiawei, Fan Shuxin, Rao Pinhong, Liu Xialin, Liu Yizhi, Fan Guoping
Zhongshan Ophthalmic Center, State Key Laboratory of Ophthalmology, Sun Yat-Sen University, Guangzhou, China.
Department of Human Genetics, David Geffen School of Medicine, UCLA, Los Angeles, CA, USA.
Methods Mol Biol. 2019;1979:363-377. doi: 10.1007/978-1-4939-9240-9_21.
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.
单细胞转录组和单细胞甲基化组分析已成功揭示了单细胞之间转录组和DNA甲基化组的异质性，并成为理解转录组和DNA甲基化组在分化和癌变等复杂生物学过程中动态变化的有力工具。受这些单细胞组学方法在理解特定“组”调控方面取得成功的启发，人们对在单细胞分辨率下阐明多组学之间的调控关系产生了更多兴趣。从同一个单细胞同时进行多组学分析将为我们理解不同“组”之间的关系提供终极力量，但由于在单个细胞中检测极微量的DNA或RNA存在困难，这一想法几十年来一直未能实现。为应对这一技术挑战，我们最近开发了一种名为scMT-seq的新方法，该方法可以同时从同一个细胞中分析DNA甲基化组和RNA转录组。这种方法使我们能够从单个细胞中测量最具信息性的50万至100万个CpG位点的DNA甲基化状态以及10000个基因的mRNA水平，其中3200个基因可以同时进行启动子DNA甲基化和RNA转录分析。利用scMT-seq数据，我们成功地展示了单个背根神经节神经元中DNA甲基化与转录水平之间的调控关系（Hu等人，《基因组生物学》17:88，2016）。我们相信scMT-seq将成为揭示转录与DNA甲基化之间调控机制的有力技术，并将引起表观遗传学领域之外的广泛关注。
