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High resolution annotation of zebrafish transcriptome using long-read sequencing

    • 1Department of Neurology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA;
    • 2Center for Advanced Research on Diagnostic Assays (CARDA), Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA;
    • 3Department of Pharmacological Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA;
    • 4Department of Development and Regenerative Biology, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA;
    • 5Program in Biology, New York University Abu Dhabi, Abu Dhabi, UAE;
    • 6Department of Genetics and Genomic Sciences, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA;
    • 7The Mount Sinai Center for RNA Biology and Medicine, Icahn School of Medicine at Mount Sinai, New York, New York 10029, USA
    • 8 These authors are joint first authors and contributed equally to this work.
Published July 30, 2018. Vol 28 Issue 9, pp. 1415-1425. https://doi.org/10.1101/gr.223586.117
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Abstract

With the emergence of zebrafish as an important model organism, a concerted effort has been made to study its transcriptome. This effort is limited, however, by gaps in zebrafish annotation, which are especially pronounced concerning transcripts dynamically expressed during zygotic genome activation (ZGA). To date, short-read sequencing has been the principal technology for zebrafish transcriptome annotation. In part because these sequence reads are too short for assembly methods to resolve the full complexity of the transcriptome, the current annotation is rudimentary. By providing direct observation of full-length transcripts, recently refined long-read sequencing platforms can dramatically improve annotation coverage and accuracy. Here, we leveraged the SMRT platform to study the transcriptome of zebrafish embryos before and after ZGA. Our analysis revealed additional novelty and complexity in the zebrafish transcriptome, identifying 2539 high-confidence novel transcripts that originated from previously unannotated loci and 1835 high-confidence new isoforms in previously annotated genes. We validated these findings using a suite of computational approaches including structural prediction, sequence homology, and functional conservation analyses, as well as by confirmatory transcript quantification with short-read sequencing data. Our analyses provided insight into new homologs and paralogs of functionally important proteins and noncoding RNAs, isoform switching occurrences, and different classes of novel splicing events. Several novel isoforms representing distinct splicing events were validated through PCR experiments, including the discovery and validation of a novel 8-kb transcript spanning multiple mir-430 elements, an important driver of early development. Our study provides a significantly improved zebrafish transcriptome annotation resource.

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