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    An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes

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    Author
    Liu, Kevin J.; Dai, Jingxuan; Truong, Kathy; Song, Ying; Kohn, Michael H.; More... Nakhleh, Luay Less...
    Date
    2014
    Abstract
    One outcome of interspecific hybridization and subsequent effects of evolutionary forces is introgression, which is the integration of genetic material from one species into the genome of an individual in another species. The evolution of several groups of eukaryotic species has involved hybridization, and cases of adaptation through introgression have been already established. In this work, we report on PhyloNet-HMM?a new comparative genomic framework for detecting introgression in genomes. PhyloNet-HMM combines phylogenetic networks with hidden Markov models (HMMs) to simultaneously capture the (potentially reticulate) evolutionary history of the genomes and dependencies within genomes. A novel aspect of our work is that it also accounts for incomplete lineage sorting and dependence across loci. Application of our model to variation data from chromosome 7 in the mouse (Mus musculus domesticus) genome detected a recently reported adaptive introgression event involving the rodent poison resistance gene Vkorc1, in addition to other newly detected introgressed genomic regions. Based on our analysis, it is estimated that about 9% of all sites within chromosome 7 are of introgressive origin (these cover about 13 Mbp of chromosome 7, and over 300 genes). Further, our model detected no introgression in a negative control data set. We also found that our model accurately detected introgression and other evolutionary processes from synthetic data sets simulated under the coalescent model with recombination, isolation, and migration. Our work provides a powerful framework for systematic analysis of introgression while simultaneously accounting for dependence across sites, point mutations, recombination, and ancestral polymorphism.
    Citation
    Liu, Kevin J., Dai, Jingxuan, Truong, Kathy, et al.. "An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes." PLoS Computational Biology, 10, no. 6 (2014) Public Library of Science: e1003649. http://dx.doi.org/10.1371/journal.pcbi.1003649.
    Published Version
    http://dx.doi.org/10.1371/journal.pcbi.1003649
    Type
    Journal article
    Publisher
    Public Library of Science
    Citable link to this page
    https://hdl.handle.net/1911/77461
    Rights
    This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
    Link to License
    https://creativecommons.org/licenses/by/4.0/
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    • Computer Science Publications [134]
    • EEB Faculty Publications [67]
    • Faculty Publications [4990]

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    Managed by the Digital Scholarship Services at Fondren Library, Rice University
    Physical Address: 6100 Main Street, Houston, Texas 77005
    Mailing Address: MS-44, P.O.BOX 1892, Houston, Texas 77251-1892
    Site Map