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    Orthonome - a new pipeline for predicting high quality orthologue gene sets applicable to complete and draft genomes

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    Author
    Rane, RV; Oakeshott, JG; Nguyen, T; Hoffmann, AA; Lee, SF
    Date
    2017-08-31
    Source Title
    BMC Genomics
    Publisher
    BMC
    University of Melbourne Author/s
    Hoffmann, Ary
    Affiliation
    School of BioSciences
    Metadata
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    Document Type
    Journal Article
    Citations
    Rane, R. V., Oakeshott, J. G., Nguyen, T., Hoffmann, A. A. & Lee, S. F. (2017). Orthonome - a new pipeline for predicting high quality orthologue gene sets applicable to complete and draft genomes. BMC GENOMICS, 18 (1), https://doi.org/10.1186/s12864-017-4079-6.
    Access Status
    Open Access
    URI
    http://hdl.handle.net/11343/256896
    DOI
    10.1186/s12864-017-4079-6
    Abstract
    BACKGROUND: Distinguishing orthologous and paralogous relationships between genes across multiple species is essential for comparative genomic analyses. Various computational approaches have been developed to resolve these evolutionary relationships, but strong trade-offs between precision and recall of orthologue prediction remains an ongoing challenge. RESULTS: Here we present Orthonome, an orthologue prediction pipeline, designed to reduce the trade-off between orthologue capture rates (recall) and accuracy of multi-species orthologue prediction. The pipeline compares sequence domains and then forms sequence-similar clusters before using phylogenetic comparisons to identify inparalogues. It then corrects sequence similarity metrics for fragment and gene length bias using a novel scoring metric capturing relationships between full length as well as fragmented genes. The remaining genes are then brought together for the identification of orthologues within a phylogenetic framework. The orthologue predictions are further calibrated along with inparalogues and gene births, using synteny, to identify novel orthologous relationships. We use 12 high quality Drosophila genomes to show that, compared to other orthologue prediction pipelines, Orthonome provides orthogroups with minimal error but high recall. Furthermore, Orthonome is resilient to suboptimal assembly/annotation quality, with the inclusion of draft genomes from eight additional Drosophila species still providing >6500 1:1 orthologues across all twenty species while retaining a better combination of accuracy and recall than other pipelines. Orthonome is implemented as a searchable database and query tool along with multiple-sequence alignment browsers for all sets of orthologues. The underlying documentation and database are accessible at http://www.orthonome.com . CONCLUSION: We demonstrate that Orthonome provides a superior combination of orthologue capture rates and accuracy on complete and draft drosophilid genomes when tested alongside previously published pipelines. The study also highlights a greater degree of evolutionary conservation across drosophilid species than earlier thought.

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