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    Reconstructing phylogenetic relationships based on repeat sequence similarities

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    Authors
    Vitales, Daniel
    Garcia, Sonia
    Dodsworth, Steven
    Affiliation
    Institut Botànic de Barcelona
    Universitat de Barcelona
    University of Bedfordshire
    Issue Date
    2020-02-28
    Subjects
    phylogenetics
    phylogenetic relationships
    Subject Categories::C410 Applied Genetics
    
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    Abstract
    A recent phylogenetic method based on genome-wide abundance of different repeat types proved to be useful in reconstructing the evolutionary history of several plant and animal groups. Here, we demonstrate that an alternative information source from the repeatome can also be employed to infer phylogenetic relationships among taxa. Specifically, this novel approach makes use of the repeat sequence similarity matrices obtained from the comparative clustering analyses of RepeatExplorer 2, which are subsequently transformed to between-taxa distance matrices. These pairwise matrices are used to construct neighbour-joining trees for each of the top most-abundant clusters and they are finally summarized in a consensus network. This methodology was tested on three groups of angiosperms and one group of insects, resulting in congruent evolutionary hypotheses compared to more standard systematic analyses based on commonly used DNA markers. We propose that the combined application of these phylogenetic approaches based on repeat abundances and repeat sequence similarities could be helpful to understand mechanisms governing genome and repeatome evolution.
    Citation
    Vitales D, Garcia S, Dodsworth S (2020) 'Reconstructing phylogenetic relationships based on repeat sequence similarities', Molecular Phylogenetics and Evolution, 147, pp.106766.
    Publisher
    Elsevier
    Journal
    Molecular Phylogenetics and Evolution
    URI
    http://hdl.handle.net/10547/624050
    DOI
    10.1016/j.ympev.2020.106766
    PubMed ID
    32119996
    Additional Links
    https://www.sciencedirect.com/science/article/pii/S1055790320300385
    Type
    Article
    Language
    en
    ISSN
    1055-7903
    EISSN
    1095-9513
    ae974a485f413a2113503eed53cd6c53
    10.1016/j.ympev.2020.106766
    Scopus Count
    Collections
    Biomedical and biological science

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