期刊
CURRENT BIOINFORMATICS
卷 14, 期 7, 页码 566-573出版社
BENTHAM SCIENCE PUBL LTD
DOI: 10.2174/1574893614666190204151746
关键词
Pacific Bioscience (PacBio); SMRT Isoform Sequencing (Iso-Seq); Next-Generation Sequencing (NGS); Alternative Splicing (AS); Alternative Polyadenylation (APA); genome annotation; novel genes
资金
- National Key Research and Development Program of China [2018YFD0600101, 2016YFD0600106]
- National Natural Science Foundation of China [31570674, 31800566]
- International Science and Technology Cooperation and Exchange Fund from Fujian Agriculture and Forestry University [KXGH17016]
- Natural Science Foundation of Fujian Province [2018J01608]
- Department of Energy Office of Science, Office of Biological and Environmental Research [DE-SC0010733]
- U.S. Department of Energy (DOE) [DE-SC0010733] Funding Source: U.S. Department of Energy (DOE)
Background: The advent of the Single-Molecule Real-time (SMRT) Isoform Sequencing (Iso-Seq) has paved the way to obtain longer full-length transcripts. This method was found to be much superior in identifying full-length splice variants and other post-transcriptional events as compared to the Next Generation Sequencing (NGS)-based short read sequencing (RNA-Scq). Several different bioinformatics tools to analyze the Iso-Seq data have been developed and some of them are still being refined to address different aspects of transcriptome complexity. However, a comprehensive summary of the available tools and their utility is still lacking. Objective: Here, we summarized the existing Iso-Seq analysis tools and presented an integrated bioinformatics pipeline for Iso-Seq analysis, which overcomes the limitations of NGS and generates long contiguous Full-Length Non-Chimeric (FLNC) reads for the analysis of post-transcriptional events. Results: In this review, we summarized recent applications of Iso-Seq in plants, which include improved genome annotations, identification of novel genes and lncRNAs, identification of full-length splice isoforms, detection of novel Alternative Splicing (AS) and Alternative Polyadenylation (APA) events. In addition, we also discussed the bioinformatics pipeline for comprehensive Iso-Seq data analysis, including how to reduce the error rate in the reads and how to identify and quantify post-transcriptional events. Furthermore, the visualization approach of Iso-Seq was discussed as well. Finally, we discussed methods to combine Iso-Seq data with RNA-Seq for transcriptomc quantification. Conclusion: Overall, this review demonstrates that the Iso-Seq is pivotal for analyzing transcriptome complexity and this new method offers unprecedented opportunities to comprehensively understand transcripts diversity.
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