Performance assessment of Nanopore sequencing tools for transcriptome analysis.

Ikking, K.*, Gentle, N. L.

School of Molecular and Cell Biology, University of the Witwatersrand

Alternative splicing plays a pivotal role in cellular differentiation and disease. However, the technical challenges of accurately reconstructing and quantifying transcripts using short-read sequencing platforms have hindered comprehensive studies of mRNA isoforms. Recent innovations in long-read sequencing technologies, particularly those developed by Oxford Nanopore Technologies (ONT), offer promising opportunities to delve deeper into the additional biological complexity introduced by alternative splicing. Nevertheless, working with ONT data poses unique challenges, demanding more sophisticated base-calling methods and error-correction algorithms. In this study, we assessed the performance of six ONT-specific tools, namely Bambu, StringTie2, IsoQuant, Espresso, TALON, and Flair—in, to identify and quantify mRNA transcripts. By generating a dataset of 27 simulated cDNA samples, we examined how variables such as read accuracy, sequencing depth, transcript length, and transcript number affect isoform detection. Our results indicate that some tools are better suited to handle lower-quality data, underscoring the importance of choosing the appropriate tool based on data quality. Additionally, our findings showed that the number of reads per transcript had a negligible impact on quantification accuracy across all tools. These insights are invaluable for researchers navigating the complexities of transcriptome analysis with ONT technology. By understanding the strengths and limitations of each tool, researchers can make informed choices that enhance the accuracy and reliability of their studies.