背景:基于下一代测序(NGS)的单细胞RNA测序(scRNA-seq)的快速发展允许以高通量方式检测和定量基因表达,为全面了解各种生物过程中的细胞功能提供了强大的工具。然而,基于NGS的scRNA-seq仅定量基因表达,并且由于有限的读取长度,无法揭示每个基因的确切转录物结构(亚型)。另一方面,第三代测序(TGS)技术的长读取长度,包括牛津纳米孔技术(ONT)和太平洋生物科学(PacBio),能够直接读取完整的cDNA分子。
目的:ONT和PacBio均已与scRNA-seq结合使用,但是它们在单细胞分析中的性能尚未得到系统评估。
方法:要解决这个问题,我们从包含不同数量细胞的相同单细胞cDNA文库中产生了ONT和PacBio数据。
结果:使用NGS作为对照,我们评估了每个平台在细胞类型识别方面的性能.此外,验证了通过两个平台识别新亚型和等位基因特异性基因/亚型表达的可靠性,为设计单细胞转录组研究中的测序策略提供系统评估。
结论:除了基因表达分析,基于NGS的scRNA-seq只能提供,基于TGS的scRNA-seq实现了基因剪接分析,鉴定新的同工型。PacBio的测序质量更高,它在新转录本鉴定和等位基因特异性基因/同工型表达的准确性方面优于ONT。
BACKGROUND: The rapid development of next-generation sequencing (NGS)-based single-cell RNA sequencing (scRNA-seq) allows for detecting and quantifying gene expression in a high-throughput manner, providing a powerful tool for comprehensively understanding cellular function in various biological processes. However, the NGS-based scRNA-seq only quantifies gene expression and cannot reveal the exact transcript structures (isoforms) of each gene due to the limited read length. On the other hand, the long read length of third-generation sequencing (TGS) technologies, including Oxford Nanopore Technologies (ONT) and Pacific Biosciences (PacBio), enable direct reading of intact cDNA molecules.
OBJECTIVE: Both ONT and PacBio have been used in conjunction with scRNA-seq, but their performance in single-cell analyses has not been systematically evaluated.
METHODS: To address this, we generated ONT and PacBio data from the same single-cell cDNA libraries containing different amount of cells.
RESULTS: Using NGS as a control, we assessed the performance of each platform in cell type identification. Additionally, the reliability in identifying novel isoforms and allele-specific gene/isoform expression by both platforms was verified, providing a systematic evaluation to design the sequencing strategies in single-cell transcriptome studies.
CONCLUSIONS: Beyond gene expression analysis, which the NGS-based scRNA-seq only affords, TGS-based scRNA-seq achieved gene splicing analyses, identifying novel isoforms. Attribute to higher sequencing quality of PacBio, it outperforms ONT in accuracy of novel transcripts identification and allele-specific gene/isoform expression.