• Medientyp: E-Artikel
  • Titel: TAGET: a toolkit for analyzing full-length transcripts from long-read sequencing
  • Beteiligte: Xia, Yuchao; Jin, Zijie; Zhang, Chengsheng; Ouyang, Linkun; Dong, Yuhao; Li, Juan; Guo, Lvze; Jing, Biyang; Shi, Yang; Miao, Susheng; Xi, Ruibin
  • Erschienen: Springer Science and Business Media LLC, 2023
  • Erschienen in: Nature Communications
  • Sprache: Englisch
  • DOI: 10.1038/s41467-023-41649-0
  • ISSN: 2041-1723
  • Schlagwörter: General Physics and Astronomy ; General Biochemistry, Genetics and Molecular Biology ; General Chemistry ; Multidisciplinary
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  • Beschreibung: <jats:title>Abstract</jats:title><jats:p>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 <jats:italic>ECM1</jats:italic>, 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.</jats:p>
  • Zugangsstatus: Freier Zugang