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单细胞全长总RNA测序揭示了递归剪接和增强子RNA的动态变化。

Single-cell full-length total RNA sequencing uncovers dynamics of recursive splicing and enhancer RNAs.

作者信息

Hayashi Tetsutaro, Ozaki Haruka, Sasagawa Yohei, Umeda Mana, Danno Hiroki, Nikaido Itoshi

机构信息

Bioinformatics Research Unit, Advanced Center for Computing and Communication, RIKEN, 2-1 Hirosawa Wako, Saitama, 351-0198, Japan.

Single-cell Omics Research Unit, Center for RIKEN Center for Developmental Biology, RIKEN, 2-1 Hirosawa Wako, Saitama, 351-0198, Japan.

出版信息

Nat Commun. 2018 Feb 12;9(1):619. doi: 10.1038/s41467-018-02866-0.

Abstract

Total RNA sequencing has been used to reveal poly(A) and non-poly(A) RNA expression, RNA processing and enhancer activity. To date, no method for full-length total RNA sequencing of single cells has been developed despite the potential of this technology for single-cell biology. Here we describe random displacement amplification sequencing (RamDA-seq), the first full-length total RNA-sequencing method for single cells. Compared with other methods, RamDA-seq shows high sensitivity to non-poly(A) RNA and near-complete full-length transcript coverage. Using RamDA-seq with differentiation time course samples of mouse embryonic stem cells, we reveal hundreds of dynamically regulated non-poly(A) transcripts, including histone transcripts and long noncoding RNA Neat1. Moreover, RamDA-seq profiles recursive splicing in >300-kb introns. RamDA-seq also detects enhancer RNAs and their cell type-specific activity in single cells. Taken together, we demonstrate that RamDA-seq could help investigate the dynamics of gene expression, RNA-processing events and transcriptional regulation in single cells.

摘要

全转录组RNA测序已被用于揭示聚腺苷酸(poly(A))和非聚腺苷酸(non-poly(A))RNA的表达、RNA加工及增强子活性。尽管单细胞全转录组RNA测序技术在单细胞生物学领域具有潜在应用价值,但迄今为止尚未开发出相关方法。在此,我们描述了随机位移扩增测序(RamDA-seq),这是首个用于单细胞的全转录组RNA测序方法。与其他方法相比,RamDA-seq对非聚腺苷酸RNA具有高灵敏度,且转录本全长覆盖率近乎完整。利用RamDA-seq对小鼠胚胎干细胞分化时间进程样本进行分析,我们发现了数百个动态调控的非聚腺苷酸转录本,包括组蛋白转录本和长链非编码RNA Neat1。此外,RamDA-seq还能分析超过300 kb内含子中的递归剪接。RamDA-seq还可在单细胞中检测增强子RNA及其细胞类型特异性活性。综上所述,我们证明RamDA-seq有助于研究单细胞中基因表达、RNA加工事件及转录调控的动态变化。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bc2b/5809388/f50308936fef/41467_2018_2866_Fig1_HTML.jpg

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