Transcript assembly is the effort to distill information from RNA-seq experiments into a comprehensive annotation of the transcript isoforms present in the corresponding samples. In parallel, advances have been made for profiling RNA on “third-generation” long-read sequencing platforms such as PacBio and Oxford Nanopore single-molecule sequencers that can read continuous DNA and/or RNA molecules and yield end-to-end complete transcript sequences. Major recent advances have enabled the amplification of full-length transcripts from single cells or 3′ end capture from millions of cells. Ī wide array of RNA-seq protocols have been developed to profile different aspects of the transcriptome, from strand-specific coverage of gene bodies to selective amplification of RNA 5′ ends, 3′ ends or simultaneous capture of both ends. Accordingly, many computational tools have been developed for genome annotation including software that utilizes the massive and growing diversity of RNA sequencing (RNA-seq) technologies. To understand how transcriptome architecture varies during development and in response to disease, it is therefore valuable to have an automated method that accurately identifies transcript isoforms. The completeness and accuracy of a reference annotation can considerably impact all downstream data analyses, from gene expression to predictions of gene function. Moreover, multicellular organisms have difficult-to-access cell types that will inevitably be overlooked by even the most comprehensive annotation projects. Large-scale projects dedicated to the manual curation of gene annotations are extremely valuable, but are labor-intensive and thus limited in scope to the most well-studied organisms. Variation in transcript initiation, splicing, and polyadenylation can generate an array of RNA isoforms, and cataloging how these RNA variants change across development and disease provides insights into corresponding gene functions. The functions of genes depend on the amount and types of RNA molecules that they produce.
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