An HMM-based comparative genomic framework for detecting introgression in eukaryotes
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 hybridizati...
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description | 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. |
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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.</description><identifier>ISSN: 1553-7358</identifier><identifier>ISSN: 1553-734X</identifier><identifier>EISSN: 1553-7358</identifier><identifier>DOI: 10.1371/journal.pcbi.1003649</identifier><identifier>PMID: 24922281</identifier><language>eng</language><publisher>United States: Public Library of Science</publisher><subject>Algorithms ; Animals ; Biology and Life Sciences ; Chromosome Mapping ; Chromosomes ; Comparative Genomic Hybridization ; Computational Biology ; Computer Simulation ; Databases, Genetic ; Evolution ; Evolution, Molecular ; Genetic engineering ; Genetics, Population ; Genomes ; Genomics ; Hybridization ; Markov Chains ; Mice ; Models, Genetic ; Mutation ; Phylogenetics ; Phylogeny ; Population ; Scholarships & fellowships</subject><ispartof>PLoS computational biology, 2014-06, Vol.10 (6), p.e1003649</ispartof><rights>2014 Liu et al 2014 Liu et al</rights><rights>2014 Liu et al. 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: Liu KJ, Dai J, Truong K, Song Y, Kohn MH, et al. (2014) An HMM-Based Comparative Genomic Framework for Detecting Introgression in Eukaryotes. 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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.</description><subject>Algorithms</subject><subject>Animals</subject><subject>Biology and Life Sciences</subject><subject>Chromosome Mapping</subject><subject>Chromosomes</subject><subject>Comparative Genomic Hybridization</subject><subject>Computational Biology</subject><subject>Computer Simulation</subject><subject>Databases, Genetic</subject><subject>Evolution</subject><subject>Evolution, Molecular</subject><subject>Genetic engineering</subject><subject>Genetics, Population</subject><subject>Genomes</subject><subject>Genomics</subject><subject>Hybridization</subject><subject>Markov Chains</subject><subject>Mice</subject><subject>Models, Genetic</subject><subject>Mutation</subject><subject>Phylogenetics</subject><subject>Phylogeny</subject><subject>Population</subject><subject>Scholarships & fellowships</subject><issn>1553-7358</issn><issn>1553-734X</issn><issn>1553-7358</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2014</creationdate><recordtype>article</recordtype><sourceid>EIF</sourceid><sourceid>DOA</sourceid><recordid>eNpVkdFu1DAQRSMEoqXwBwjyA1nseGzHL0hVBbRSK17KszV2xsHbJF7Z2SL-npTdVu2T7fG9Z-y5VfWRsw0Xmn_Zpn2ecdzsvIsbzphQYF5Vp1xK0Wghu9fP9ifVu1K2q0Z2Rr2tTlowbdt2_LS6PZ_ry5ubxmGhvvZp2mHGJd5TPdCcpujrkHGiPynf1SHluqeF_BLnoY7zktOQqZSY5vVU0_4O89-0UHlfvQk4FvpwXM-qX9-_3V5cNtc_f1xdnF83XipYmtYZrbQxSjquAHqlgpGGO4PgELTuwVMbDGqAllgHhgAYc84bJToKTpxVnw_c3ZiKPQ6kWC5BS2WA6VVxdVD0Cbd2l-O0PtEmjPZ_IeXBYl6iH8kKNNSq0BuhCFzXIRpO5LUCicb3YWV9PXbbu4l6T-sAcHwBfXkzx992SPcWmJRSixUAB4DPqZRM4cnLmX3I9PEL9iFTe8x0tX163vfJ9Bii-AcAV6IM</recordid><startdate>20140601</startdate><enddate>20140601</enddate><creator>Liu, Kevin J</creator><creator>Dai, Jingxuan</creator><creator>Truong, Kathy</creator><creator>Song, Ying</creator><creator>Kohn, Michael H</creator><creator>Nakhleh, Luay</creator><general>Public Library of Science</general><general>Public Library of Science (PLoS)</general><scope>CGR</scope><scope>CUY</scope><scope>CVF</scope><scope>ECM</scope><scope>EIF</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>5PM</scope><scope>DOA</scope></search><sort><creationdate>20140601</creationdate><title>An HMM-based comparative genomic framework for detecting introgression in eukaryotes</title><author>Liu, Kevin J ; Dai, Jingxuan ; Truong, Kathy ; Song, Ying ; Kohn, Michael H ; Nakhleh, Luay</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c564t-2b97679965b1644d66f9591b9a4ba477d4ce2f9a7442e0849e4400bbc9638efb3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2014</creationdate><topic>Algorithms</topic><topic>Animals</topic><topic>Biology and Life Sciences</topic><topic>Chromosome Mapping</topic><topic>Chromosomes</topic><topic>Comparative Genomic Hybridization</topic><topic>Computational Biology</topic><topic>Computer Simulation</topic><topic>Databases, Genetic</topic><topic>Evolution</topic><topic>Evolution, Molecular</topic><topic>Genetic engineering</topic><topic>Genetics, Population</topic><topic>Genomes</topic><topic>Genomics</topic><topic>Hybridization</topic><topic>Markov Chains</topic><topic>Mice</topic><topic>Models, Genetic</topic><topic>Mutation</topic><topic>Phylogenetics</topic><topic>Phylogeny</topic><topic>Population</topic><topic>Scholarships & fellowships</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Liu, Kevin J</creatorcontrib><creatorcontrib>Dai, Jingxuan</creatorcontrib><creatorcontrib>Truong, Kathy</creatorcontrib><creatorcontrib>Song, Ying</creatorcontrib><creatorcontrib>Kohn, Michael H</creatorcontrib><creatorcontrib>Nakhleh, Luay</creatorcontrib><collection>Medline</collection><collection>MEDLINE</collection><collection>MEDLINE (Ovid)</collection><collection>MEDLINE</collection><collection>MEDLINE</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>PubMed Central (Full Participant titles)</collection><collection>DOAJ Directory of Open Access Journals</collection><jtitle>PLoS computational biology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Liu, Kevin J</au><au>Dai, Jingxuan</au><au>Truong, Kathy</au><au>Song, Ying</au><au>Kohn, Michael H</au><au>Nakhleh, Luay</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An HMM-based comparative genomic framework for detecting introgression in eukaryotes</atitle><jtitle>PLoS computational biology</jtitle><addtitle>PLoS Comput Biol</addtitle><date>2014-06-01</date><risdate>2014</risdate><volume>10</volume><issue>6</issue><spage>e1003649</spage><pages>e1003649-</pages><issn>1553-7358</issn><issn>1553-734X</issn><eissn>1553-7358</eissn><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.</abstract><cop>United States</cop><pub>Public Library of Science</pub><pmid>24922281</pmid><doi>10.1371/journal.pcbi.1003649</doi><oa>free_for_read</oa></addata></record> |
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subjects | Algorithms Animals Biology and Life Sciences Chromosome Mapping Chromosomes Comparative Genomic Hybridization Computational Biology Computer Simulation Databases, Genetic Evolution Evolution, Molecular Genetic engineering Genetics, Population Genomes Genomics Hybridization Markov Chains Mice Models, Genetic Mutation Phylogenetics Phylogeny Population Scholarships & fellowships |
title | An HMM-based comparative genomic framework for detecting introgression in eukaryotes |
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