TAGET: a toolkit for analyzing full-length transcripts from long-read sequencing

Yuchao Xia, Zijie Jin, Chengsheng Zhang, Linkun Ouyang, Yuhao Dong, Juan Li, Lvze Guo, Biyang Jing, Yang Shi, Susheng Miao () and Ruibin Xi ()
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Yuchao Xia: Beijing Information Science and Technology University
Zijie Jin: Health Science Center, Peking University
Chengsheng Zhang: Beijing GeneX Health Co.,Ltd
Linkun Ouyang: Peking University
Yuhao Dong: Beijing GeneX Health Co.,Ltd
Juan Li: College of Future Technology, Peking University
Lvze Guo: Beijing GeneX Health Co.,Ltd
Biyang Jing: Beijing GeneX Health Co.,Ltd
Yang Shi: BeiGene (Beijing) Co., Ltd.
Susheng Miao: Harbin Medical University Cancer Hospital
Ruibin Xi: Peking University

Nature Communications, 2023, vol. 14, issue 1, 1-12

Abstract: Abstract Single-molecule Real-time Isoform Sequencing (Iso-seq) of transcriptomes by PacBio can generate very long and accurate reads, thus providing an ideal platform for full-length transcriptome analysis. We present an integrated computational toolkit named TAGET for Iso-seq full-length transcript data analyses, including transcript alignment, annotation, gene fusion detection, and quantification analyses such as differential expression gene analysis and differential isoform usage analysis. We evaluate the performance of TAGET using a public Iso-seq dataset and newly sequenced Iso-seq datasets from tumor patients. TAGET gives significantly more precise novel splice site prediction and enables more accurate novel isoform and gene fusion discoveries, as validated by experimental validations and comparisons with RNA-seq data. We identify and experimentally validate a differential isoform usage gene ECM1, and further show that its isoform ECM1b may be a tumor-suppressor in laryngocarcinoma. Our results demonstrate that TAGET provides a valuable computational toolkit and can be applied to many full-length transcriptome studies.

Date: 2023
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DOI: 10.1038/s41467-023-41649-0

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