Deng Enze, Shen Qingmei, Zhang Jingna, Fang Yaowei, Chang Lei, Luo Guanzheng, Fan Xiaoying
MOE Key Laboratory of Gene Function and Regulation, Guangdong Province Key Laboratory of Pharmaceutical Functional Genes, State Key Laboratory of Biocontrol, School of Life Sciences, Sun Yat-sen University, Guangzhou 510275, China; Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China.
Guangzhou National Laboratory, No. 9 XingDaoHuanBei Road, Guangzhou International Bio Island, Guangzhou 510005, Guangdong Province, China; GMU-GIBH Joint School of Life Sciences, The Fifth Affiliated Hospital of Guangzhou Medical University, Guangzhou Medical University, Guangzhou 510005, China.
J Adv Res. 2025 May;71:141-153. doi: 10.1016/j.jare.2024.05.020. Epub 2024 May 22.
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.
Both ONT and PacBio have been used in conjunction with scRNA-seq, but their performance in single-cell analyses has not been systematically evaluated.
To address this, we generated ONT and PacBio data from the same single-cell cDNA libraries containing different amount of cells.
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.
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.
基于新一代测序（NGS）的单细胞RNA测序（scRNA-seq）的快速发展使得能够以高通量方式检测和定量基因表达，为全面理解各种生物过程中的细胞功能提供了强大工具。然而，基于NGS的scRNA-seq仅对基因表达进行定量，由于读长有限，无法揭示每个基因的确切转录本结构（异构体）。另一方面，包括牛津纳米孔技术（ONT）和太平洋生物科学公司（PacBio）在内的第三代测序（TGS）技术的长读长能够直接读取完整的cDNA分子。
ONT和PacBio都已与scRNA-seq结合使用，但其在单细胞分析中的性能尚未得到系统评估。
为了解决这个问题，我们从包含不同数量细胞的同一单细胞cDNA文库中生成了ONT和PacBio数据。
以NGS作为对照，我们评估了每个平台在细胞类型识别中的性能。此外，还验证了两个平台在识别新异构体以及等位基因特异性基因/异构体表达方面的可靠性，为单细胞转录组研究中的测序策略设计提供了系统评估。
除了基于NGS的scRNA-seq仅能提供的基因表达分析之外，基于TGS的scRNA-seq还实现了基因剪接分析，识别出新的异构体。由于PacBio的测序质量更高，它在新转录本识别和等位基因特异性基因/异构体表达的准确性方面优于ONT。
