Gupta Ishaan, Collier Paul G, Haase Bettina, Mahfouz Ahmed, Joglekar Anoushka, Floyd Taylor, Koopmans Frank, Barres Ben, Smit August B, Sloan Steven A, Luo Wenjie, Fedrigo Olivier, Ross M Elizabeth, Tilgner Hagen U
Brain and Mind Research Institute and Center for Neurogenetics, Weill Cornell Medicine, New York, New York, USA.
The Rockefeller University, New York, New York, USA.
Nat Biotechnol. 2018 Oct 15. doi: 10.1038/nbt.4259.
Full-length RNA sequencing (RNA-Seq) has been applied to bulk tissue, cell lines and sorted cells to characterize transcriptomes, but applying this technology to single cells has proven to be difficult, with less than ten single-cell transcriptomes having been analyzed thus far. Although single splicing events have been described for ≤200 single cells with statistical confidence, full-length mRNA analyses for hundreds of cells have not been reported. Single-cell short-read 3' sequencing enables the identification of cellular subtypes, but full-length mRNA isoforms for these cell types cannot be profiled. We developed a method that starts with bulk tissue and identifies single-cell types and their full-length RNA isoforms without fluorescence-activated cell sorting. Using single-cell isoform RNA-Seq (ScISOr-Seq), we identified RNA isoforms in neurons, astrocytes, microglia, and cell subtypes such as Purkinje and Granule cells, and cell-type-specific combination patterns of distant splice sites. We used ScISOr-Seq to improve genome annotation in mouse Gencode version 10 by determining the cell-type-specific expression of 18,173 known and 16,872 novel isoforms.
全长RNA测序（RNA-Seq）已应用于大块组织、细胞系和分选细胞以表征转录组，但将该技术应用于单细胞已被证明是困难的，到目前为止，分析的单细胞转录组不到十个。尽管已以统计学置信度描述了≤200个单细胞的单个剪接事件，但尚未报道对数百个细胞进行全长mRNA分析。单细胞短读3'测序能够识别细胞亚型，但无法对这些细胞类型的全长mRNA异构体进行分析。我们开发了一种方法，该方法从大块组织开始，无需荧光激活细胞分选即可识别单细胞类型及其全长RNA异构体。使用单细胞异构体RNA-Seq（ScISOr-Seq），我们在神经元、星形胶质细胞、小胶质细胞以及浦肯野细胞和颗粒细胞等细胞亚型中鉴定了RNA异构体，以及远距离剪接位点的细胞类型特异性组合模式。我们使用ScISOr-Seq通过确定18,173个已知异构体和16,872个新异构体的细胞类型特异性表达来改进小鼠Gencode版本10中的基因组注释。
