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Isoform-level discovery, quantification and fusion analysis from single-cell and spatial long-read RNA-seq data with Bambu-Clump


Sim et al. introduce Bambu-Clump — a new computational tool for transcript discovery and quantification in single-cell and spatial long-read RNA sequencing. Bambu-Clump can be applied to long- and short-read RNA datasets, and overcomes the challenge of low sequencing depth by leveraging information from both individual cells and cell clusters.

Key points:

  • The authors generated single-cell and spatial RNA sequencing datasets for cancer cell lines and mouse brain tissue using Oxford Nanopore reads of unrestricted length and other long- and short-read sequencing technologies.

  • Oxford Nanopore sequencing had comparable overall performance for transcript discovery, but had a higher median read length and was faster and more cost-effective than an alternative long-read sequencing platform.

  • The full-length RNA sequencing capabilities of Oxford Nanopore Technologies were essential for resolving transcript isoforms and detecting fusion events.

  • This work could potentially benefit cancer research in the future as many cancers involve fusion genes, structural mutations, and abnormal RNA splicing.

Sample type: human cancer cell lines and mouse brain tissue

Kit: Ligation Sequencing Kit

Authors: Andre Sim, Min Hao Ling, Ying Chen, Han Lu, Yi Xiang See, Arnaud Perrin, Ong Bee Leng Agnes, Elaine Yiqun Cao, Burton Chia, Jinyue Liu, Torsten Wüstefeld, Jay W. Shin, Jonathan Göke

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