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Precise Transcript Reconstruction with End-Guided Assembly

View ORCID ProfileMichael A. Schon, View ORCID ProfileStefan Lutzmayer, View ORCID ProfileFalko Hofmann, View ORCID ProfileMichael D. Nodine
doi: https://doi.org/10.1101/2022.01.12.476004
Michael A. Schon
1Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
2Laboratory of Molecular Biology, Wageningen University, Wageningen, 6708 PB, the Netherlands
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  • For correspondence: michael.nodine@wur.nl michael.schon@wur.nl
Stefan Lutzmayer
1Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
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Falko Hofmann
1Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
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Michael D. Nodine
1Gregor Mendel Institute (GMI), Austrian Academy of Sciences, Vienna Biocenter (VBC), Dr. Bohr-Gasse 3, 1030 Vienna, Austria
2Laboratory of Molecular Biology, Wageningen University, Wageningen, 6708 PB, the Netherlands
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  • For correspondence: michael.nodine@wur.nl michael.schon@wur.nl
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ABSTRACT

Accurate annotation of transcript isoforms is crucial to understand gene functions, but automated methods for reconstructing full-length transcripts from RNA sequencing (RNA-seq) data remain imprecise. We developed Bookend, a software package for transcript assembly that incorporates data from different RNA-seq techniques, with a focus on identifying and utilizing RNA 5′ and 3′ ends. Through end-guided assembly with Bookend we demonstrate that correct modeling of transcript start and end sites is essential for precise transcript assembly. Furthermore, we discovered that utilization of end-labeled reads present in full-length single-cell RNA-seq (scRNA-seq) datasets dramatically improves the precision of transcript assembly in single cells. Finally, we show that hybrid assembly across short-read, long-read, and end-capture RNA-seq datasets from Arabidopsis, as well as meta-assembly of RNA-seq from single mouse embryonic stem cells (mESCs) can produce end-to-end transcript annotations of comparable quality to reference annotations in these model organisms.

Summary statement Bookend is a generalized framework that utilizes RNA 5′ and 3′ end information hidden in RNA-seq datasets to accurately reconstruct transcriptomes including those from single cells.

Competing Interest Statement

The authors have declared no competing interest.

Footnotes

  • https://github.com/Gregor-Mendel-Institute/bookend

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. All rights reserved. No reuse allowed without permission.
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Posted January 13, 2022.
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Precise Transcript Reconstruction with End-Guided Assembly
Michael A. Schon, Stefan Lutzmayer, Falko Hofmann, Michael D. Nodine
bioRxiv 2022.01.12.476004; doi: https://doi.org/10.1101/2022.01.12.476004
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Precise Transcript Reconstruction with End-Guided Assembly
Michael A. Schon, Stefan Lutzmayer, Falko Hofmann, Michael D. Nodine
bioRxiv 2022.01.12.476004; doi: https://doi.org/10.1101/2022.01.12.476004

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