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Single-cell RNA-seq analysis of mouse preimplantation embryos by third-generation sequencing
Xiaoying Fan1,2, Dong Tang3, Yuhan Liao1
1Beijing Advanced Innovation Center for Genomics, Biomedical Pioneering Innovation Center, School of Life Sciences, Peking University, Beijing, China.
Plos Biology
|December 30, 2020
Summary
We developed SCAN-seq, a novel single-cell RNA sequencing technology using Nanopore. This method captures full-length RNA transcripts with high accuracy, advancing single-cell transcriptome analysis.
Area of Science:
- Genomics
- Molecular Biology
- Developmental Biology
Background:
- Next-generation sequencing (NGS) based single-cell RNA sequencing (scRNA-seq) has revolutionized biological research.
- Limitations in read length of current scRNA-seq methods hinder comprehensive transcriptome analysis.
- Unannotated transcripts and allele-specific expression remain challenging areas.
Purpose of the Study:
- To develop a novel scRNA-seq technology capable of capturing full-length RNA transcripts.
- To assess the sensitivity, accuracy, and capabilities of the new technology in analyzing complex biological samples.
- To identify unannotated transcripts and analyze gene expression patterns at single-cell resolution.
Main Methods:
- Development of SCAN-seq (single-cell amplification and sequencing of full-length RNAs by Nanopore platform), a third-generation sequencing (TGS) based scRNA-seq technology.
- Application of SCAN-seq to mouse embryonic stem cells (mESCs) and mouse preimplantation embryos.
- Verification of identified transcripts using reverse transcription PCR (RT-PCR)-coupled Sanger sequencing.
Main Results:
- SCAN-seq demonstrated high sensitivity and accuracy comparable to existing NGS-based scRNA-seq methods.
- Thousands of unannotated transcripts were identified in mESCs with a high verification rate.
- Analysis of mouse preimplantation embryos revealed distinct cell populations at different developmental stages.
- A total of 27,250 unannotated transcripts from 9,338 genes were identified, many with stage-specific expression.
- SCAN-seq accurately determined allele-specific gene expression patterns within individual cells.
Conclusions:
- SCAN-seq represents a significant advancement in single-cell transcriptome analysis by enabling full-length RNA sequencing.
- The technology facilitates the discovery of novel transcripts and provides deeper insights into developmental processes.
- SCAN-seq offers high accuracy for analyzing allele-specific expression at the single-cell level, overcoming limitations of previous methods.
