Abstract

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.

Highlights

  • The development of generation sequencing (NGS) platform-based single-cell RNA sequencing techniques has made great advances during the past decade, and these techniques have accelerated researches in many biological fields

  • We further evaluated the reproducibility of SCAN-seq by calculating the correlations on global gene expressions between each pair of individual mouse embryonic stem cell (mESC)

  • SCAN-seq got the results obtained using the current next generation sequencing (NGS) platform-based scRNA-seq methods, and captured the intact cDNA molecules directly, which is convenient and accurate for RNA isoform analysis

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Summary

Introduction

The development of generation sequencing (NGS) platform-based single-cell RNA sequencing (scRNA-seq) techniques has made great advances during the past decade, and these techniques have accelerated researches in many biological fields. It helped to overcome the challenges in studying rare biological materials and illustrated the heterogeneity within a biological sample [1,2]. The highly parallel scRNA-seq methods such as Drop-seq [3,4] and Microwell-seq [5] have made it feasible to analyze human cell atlas (HCA).

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