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

Author

Listed:
  • Yuchao Xia

    (Beijing Information Science and Technology University
    Beijing GeneX Health Co.,Ltd)

  • Zijie Jin

    (Health Science Center, Peking University
    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
    Peking University
    Peking University)

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.

Suggested Citation

  • Yuchao Xia & Zijie Jin & Chengsheng Zhang & Linkun Ouyang & Yuhao Dong & Juan Li & Lvze Guo & Biyang Jing & Yang Shi & Susheng Miao & Ruibin Xi, 2023. "TAGET: a toolkit for analyzing full-length transcripts from long-read sequencing," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
  • Handle: RePEc:nat:natcom:v:14:y:2023:i:1:d:10.1038_s41467-023-41649-0
    DOI: 10.1038/s41467-023-41649-0
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    1. Yaqi Su & Zhejian Yu & Siqian Jin & Zhipeng Ai & Ruihong Yuan & Xinyi Chen & Ziwei Xue & Yixin Guo & Di Chen & Hongqing Liang & Zuozhu Liu & Wanlu Liu, 2024. "Comprehensive assessment of mRNA isoform detection methods for long-read sequencing data," Nature Communications, Nature, vol. 15(1), pages 1-19, December.

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