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Novel Sequence Discovery by Subtractive Genomics
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Exact Algorithms for Duplication-Transfer-Loss Reconciliation with Non-Binary Gene Trees.

Misagh Kordi, Mukul S Bansal

    IEEE/ACM Transactions on Computational Biology and Bioinformatics
    |June 17, 2017
    PubMed
    Summary
    This summary is machine-generated.

    This study introduces new algorithms for Duplication-Transfer-Loss (DTL) reconciliation with non-binary gene trees, improving evolutionary inference accuracy by addressing gene tree uncertainty.

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    Area of Science:

    • Computational Biology
    • Evolutionary Biology
    • Phylogenetics

    Background:

    • Duplication-Transfer-Loss (DTL) reconciliation is crucial for understanding gene family evolution, especially with horizontal gene transfer.
    • Existing efficient algorithms for DTL reconciliation require binary gene trees.
    • Non-binary gene trees, common due to topological uncertainty, make DTL reconciliation NP-hard.

    Purpose of the Study:

    • To develop the first exact algorithms for DTL reconciliation with non-binary gene trees.
    • To address the computational complexity of DTL reconciliation with uncertain gene tree topologies.
    • To improve the accuracy of evolutionary inferences by accounting for gene tree uncertainty.

    Main Methods:

    • Demonstrated fixed-parameter tractability of non-binary DTL reconciliation concerning the gene tree's maximum degree.
    • Developed an efficient algorithm to enumerate optimal binary resolutions for non-binary gene trees.
    • Applied the novel algorithms to a large empirical dataset of over 4,700 gene trees from 100 species.

    Main Results:

    • The DTL reconciliation problem for non-binary gene trees is shown to be fixed-parameter tractable.
    • An efficient algorithm for enumerating binary resolutions of non-binary gene trees was developed.
    • Analysis of a large empirical dataset revealed the impact of gene tree uncertainty on DTL reconciliation.

    Conclusions:

    • The developed algorithms provide exact solutions for DTL reconciliation with non-binary gene trees.
    • These methods enhance the reliability of evolutionary inferences by mitigating errors from gene tree uncertainty.
    • The study demonstrates the practical applicability and utility of the new algorithms in evolutionary biology research.