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ASAPA: a bioinformatic pipeline based on Iso-Seq that identifies the links among alternative splicing, alternative transcription initiation and alternative polyadenylation.
Functional & Integrative Genomics 2024 March 27
BACKGROUND: Although the events associated with alternative splicing (AS), alternative polyadenylation (APA) and alternative transcription initiation (ATI) can be identified by many approaches based on isoform sequencing (Iso-Seq), these analyses are generally independent of each other and the links between these events are still rarely mentioned. However, an interdependency analysis can be achieved because the transcriptional start site, splice sites and polyA site could be simultaneously included in a long, full-length read from Iso-Seq.
RESULTS: We create ASAPA pipeline that enables streamlined analysis for a robust detection of potential links among AS, ATI and APA using Iso-Seq data. We tested this pipeline using Arabidopsis data and found some interesting results: some adjacent introns tend to be simultaneously spliced or retained; coupling between AS and ATI or APA is limited to the initial or terminal intron; and ATI and APA are potentially linked in some special cases.
CONCLUSION: Our pipeline enables streamlined analysis for a robust detection of potential links among AS, ATI and APA using Iso-Seq data, which is conducive to a better understanding of transcription landscape generation.
RESULTS: We create ASAPA pipeline that enables streamlined analysis for a robust detection of potential links among AS, ATI and APA using Iso-Seq data. We tested this pipeline using Arabidopsis data and found some interesting results: some adjacent introns tend to be simultaneously spliced or retained; coupling between AS and ATI or APA is limited to the initial or terminal intron; and ATI and APA are potentially linked in some special cases.
CONCLUSION: Our pipeline enables streamlined analysis for a robust detection of potential links among AS, ATI and APA using Iso-Seq data, which is conducive to a better understanding of transcription landscape generation.
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