Skip to main content
bioRxiv
  • Home
  • About
  • Submit
  • ALERTS / RSS
Advanced Search
New Results

JAFFAL: Detecting fusion genes with long read transcriptome sequencing

View ORCID ProfileNadia M. Davidson, View ORCID ProfileYing Chen, View ORCID ProfileGeorgina L. Ryland, Piers Blombery, View ORCID ProfileJonathan Göke, View ORCID ProfileAlicia Oshlack
doi: https://doi.org/10.1101/2021.04.26.441398
Nadia M. Davidson
1Peter MacCallum Cancer Centre, Victoria, Australia
2School of BioSciences, University of Melbourne, Victoria, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Nadia M. Davidson
  • For correspondence: nadia.davidson@petermac.org alicia.oshlack@petermac.org
Ying Chen
3Genome Institute of Singapore, Singapore, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Ying Chen
Georgina L. Ryland
1Peter MacCallum Cancer Centre, Victoria, Australia
4Centre for Cancer Research, University of Melbourne, Victoria, Australia
5Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Georgina L. Ryland
Piers Blombery
1Peter MacCallum Cancer Centre, Victoria, Australia
5Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
Jonathan Göke
3Genome Institute of Singapore, Singapore, Singapore
6National Cancer Centre Singapore, Singapore, Singapore
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Jonathan Göke
Alicia Oshlack
1Peter MacCallum Cancer Centre, Victoria, Australia
2School of BioSciences, University of Melbourne, Victoria, Australia
5Sir Peter MacCallum Department of Oncology, University of Melbourne, Victoria, Australia
  • Find this author on Google Scholar
  • Find this author on PubMed
  • Search for this author on this site
  • ORCID record for Alicia Oshlack
  • For correspondence: nadia.davidson@petermac.org alicia.oshlack@petermac.org
  • Abstract
  • Full Text
  • Info/History
  • Metrics
  • Supplementary material
  • Preview PDF
Loading

Abstract

Massively parallel short read transcriptome sequencing has greatly expanded our knowledge of fusion genes which are drivers of tumor initiation and progression. In cancer, many fusions are also important diagnostic markers and targets for therapy. Long read transcriptome sequencing allows the full length of fusion transcripts to be discovered, however, this data has a high rate of errors and fusion finding algorithms designed for short reads do not work. While numerous fusion finding algorithms now exist for short read RNA sequencing data, methods to detect fusions using third generation or long read sequencing data are lacking.

Here we present JAFFAL a method to identify fusions from long-read transcriptome sequencing. We validated JAFFAL using simulation, cell line and patient data from Nanopore and PacBio. We show that fusions can be accurately detected in long read data with JAFFAL, providing better accuracy than other long read fusion finders and within the range of a state-of-the-art method applied to short read data. By comparing Nanopore transcriptome sequencing protocols we find that numerous chimeric molecules are generated during cDNA library preparation that are absent when RNA is sequenced directly. Finally, we demonstrate that JAFFAL enables fusions to be detected at the level of individual cells, when applied to long read single cell sequencing. JAFFAL is open source and available as part of the JAFFA package at https://github.com/Oshlack/JAFFA/wiki.

Competing Interest Statement

The authors have declared no competing interest.

  • Abbreviations

    ONT
    Oxford Nanopore Technologies
    ALL
    acute lymphoblastic leukemia
    AML
    acute myeloid leukemia
    SRA
    Sequence Read Archive
    CCLE
    Cancer Cell Line Encyclopedia
  • Copyright 
    The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-ND 4.0 International license.
    Back to top
    PreviousNext
    Posted April 26, 2021.
    Download PDF

    Supplementary Material

    Email

    Thank you for your interest in spreading the word about bioRxiv.

    NOTE: Your email address is requested solely to identify you as the sender of this article.

    Enter multiple addresses on separate lines or separate them with commas.
    JAFFAL: Detecting fusion genes with long read transcriptome sequencing
    (Your Name) has forwarded a page to you from bioRxiv
    (Your Name) thought you would like to see this page from the bioRxiv website.
    CAPTCHA
    This question is for testing whether or not you are a human visitor and to prevent automated spam submissions.
    Share
    JAFFAL: Detecting fusion genes with long read transcriptome sequencing
    Nadia M. Davidson, Ying Chen, Georgina L. Ryland, Piers Blombery, Jonathan Göke, Alicia Oshlack
    bioRxiv 2021.04.26.441398; doi: https://doi.org/10.1101/2021.04.26.441398
    Reddit logo Twitter logo Facebook logo LinkedIn logo Mendeley logo
    Citation Tools
    JAFFAL: Detecting fusion genes with long read transcriptome sequencing
    Nadia M. Davidson, Ying Chen, Georgina L. Ryland, Piers Blombery, Jonathan Göke, Alicia Oshlack
    bioRxiv 2021.04.26.441398; doi: https://doi.org/10.1101/2021.04.26.441398

    Citation Manager Formats

    • BibTeX
    • Bookends
    • EasyBib
    • EndNote (tagged)
    • EndNote 8 (xml)
    • Medlars
    • Mendeley
    • Papers
    • RefWorks Tagged
    • Ref Manager
    • RIS
    • Zotero
    • Tweet Widget
    • Facebook Like
    • Google Plus One

    Subject Area

    • Bioinformatics
    Subject Areas
    All Articles
    • Animal Behavior and Cognition (4395)
    • Biochemistry (9613)
    • Bioengineering (7110)
    • Bioinformatics (24914)
    • Biophysics (12642)
    • Cancer Biology (9978)
    • Cell Biology (14377)
    • Clinical Trials (138)
    • Developmental Biology (7967)
    • Ecology (12132)
    • Epidemiology (2067)
    • Evolutionary Biology (16008)
    • Genetics (10937)
    • Genomics (14764)
    • Immunology (9889)
    • Microbiology (23712)
    • Molecular Biology (9492)
    • Neuroscience (50963)
    • Paleontology (370)
    • Pathology (1544)
    • Pharmacology and Toxicology (2688)
    • Physiology (4031)
    • Plant Biology (8677)
    • Scientific Communication and Education (1512)
    • Synthetic Biology (2403)
    • Systems Biology (6446)
    • Zoology (1346)