A systematic benchmark of Nanopore long-read RNA sequencing for transcript-level analysis in human cell lines
- Author(s)
- Chen, Y; Davidson, NM; Wan, YK; Yao, F; Su, Y; Gamaarachchi, H; Sim, A; Patel, H; Low, HM; Hendra, C; Wratten, L; Hakkaart, C; Sawyer, C; Iakovleva, V; Lee, PL; Xin, L; Ng, HEV; Loo, JM; Ong, X; Ng, HQA; Wang, J; Koh, WQC; Poon, SYP; Stanojevic, D; Tran, HD; Lim, KHE; Toh, SY; Ewels, PA; Ng, HH; Iyer, NG; Thiery, A; Chng, WJ; Chen, L; DasGupta, R; Sikic, M; Chan, YS; Tan, BOP; Wan, Y; Tam, WL; Yu, Q; Khor, CC; Wüstefeld, T; Lezhava, A; Pratanwanich, PN; Love, MI; Goh, WSS; Ng, SB; Oshlack, A; Göke, J;
- Details
- Publication Year 2025-04,Volume 22,Issue #4,Page 801-812
- Journal Title
- Nature Methods
- Publication Type
- Research article
- Abstract
- The human genome contains instructions to transcribe more than 200,000 RNAs. However, many RNA transcripts are generated from the same gene, resulting in alternative isoforms that are highly similar and that remain difficult to quantify. To evaluate the ability to study RNA transcript expression, we profiled seven human cell lines with five different RNA-sequencing protocols, including short-read cDNA, Nanopore long-read direct RNA, amplification-free direct cDNA and PCR-amplified cDNA sequencing, and PacBio IsoSeq, with multiple spike-in controls, and additional transcriptome-wide N(6)-methyladenosine profiling data. We describe differences in read length, coverage, throughput and transcript expression, reporting that long-read RNA sequencing more robustly identifies major isoforms. We illustrate the value of the SG-NEx data to identify alternative isoforms, novel transcripts, fusion transcripts and N(6)-methyladenosine RNA modifications. Together, the SG-NEx data provide a comprehensive resource enabling the development and benchmarking of computational methods for profiling complex transcriptional events at isoform-level resolution.
- Publisher
- Springer Nature
- Keywords
- Humans; *Sequence Analysis, RNA/methods; *Gene Expression Profiling/methods; Transcriptome; *Nanopore Sequencing/methods; Cell Line; Benchmarking; Genome, Human; *Nanopores
- Department(s)
- Laboratory Research
- Publisher's Version
- https://doi.org/10.1038/s41592-025-02623-4
- Open Access at Publisher's Site
https://doi.org/10.1038/s41592-025-02623-4- Terms of Use/Rights Notice
- Refer to copyright notice on published article.
Creation Date: 2025-04-02 06:40:58
Last Modified: 2025-04-10 03:35:23