Single-cell RNA-seq analysis of mouse preimplantation embryos by third-generation sequencing

• Published in: PLoS biology Vol. 18; no. 12; p. e3001017
• Main Authors: Fan, Xiaoying, Tang, Dong, Liao, Yuhan, Li, Pidong, Zhang, Yu, Wang, Minxia, Liang, Fan, Wang, Xiao, Gao, Yun, Wen, Lu, Wang, Depeng, Wang, Yang, Tang, Fuchou
• Format: Journal Article
• Language: English
• Published: United States Public Library of Science 30.12.2020; Public Library of Science (PLoS)
• Subjects: Accuracy; Alleles; Alternative splicing; Analysis; Animals; Annotations; Biology and Life Sciences; Blastocyst; Blastocyst - metabolism; Cell cycle; Construction; Embryonic stem cells; Embryos; Female; Forecasts and trends; Gene expression; Gene Expression Profiling - methods; Genetic aspects; Genetic transcription; High-Throughput Nucleotide Sequencing - methods; Male; Mammalian cells; Methods; Methods and Resources; Mice; Mice, Inbred C57BL; Mice, Inbred DBA; Mouse Embryonic Stem Cells - metabolism; Oocytes - metabolism; Polymerase chain reaction; Research and analysis methods; Reverse transcription; Ribonucleic acid; RNA; RNA - metabolism; RNA sequencing; Sequence Analysis, RNA - methods; Single-Cell Analysis - methods; Splicing; Stem cells; Transcriptome - genetics; Unicellular organisms; China
• ISSN: 1545-7885; 1544-9173; 1545-7885
• DOI: 10.1371/journal.pbio.3001017

The development of next generation sequencing (NGS) platform-based single-cell RNA sequencing (scRNA-seq) techniques has tremendously changed biological researches, while there are still many questions that cannot be addressed by them due to their short read lengths. We developed a novel scRNA-seq technology based on third-generation sequencing (TGS) platform (single-cell amplification and sequencing of full-length RNAs by Nanopore platform, SCAN-seq). SCAN-seq exhibited high sensitivity and accuracy comparable to NGS platform-based scRNA-seq methods. Moreover, we captured thousands of unannotated transcripts of diverse types, with high verification rate by reverse transcription PCR (RT-PCR)–coupled Sanger sequencing in mouse embryonic stem cells (mESCs). Then, we used SCAN-seq to analyze the mouse preimplantation embryos. We could clearly distinguish cells at different developmental stages, and a total of 27,250 unannotated transcripts from 9,338 genes were identified, with many of which showed developmental stage-specific expression patterns. Finally, we showed that SCAN-seq exhibited high accuracy on determining allele-specific gene expression patterns within an individual cell. SCAN-seq makes a major breakthrough for single-cell transcriptome analysis field.