Please use this identifier to cite or link to this item: http://hdl.handle.net/1893/23732
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dc.contributor.authorHearn, Jacken_UK
dc.contributor.authorStone, Graham Nen_UK
dc.contributor.authorBunnefeld, Lynseyen_UK
dc.contributor.authorNicholls, James Aen_UK
dc.contributor.authorBarton, Nicholas Hen_UK
dc.contributor.authorLohse, Konraden_UK
dc.date.accessioned2017-08-31T22:28:57Z-
dc.date.available2017-08-31T22:28:57Zen_UK
dc.date.issued2014-01en_UK
dc.identifier.urihttp://hdl.handle.net/1893/23732-
dc.description.abstractShort-read sequencing technologies have in principle made it feasible to draw detailed inferences about the recent history of any organism. In practice, however, this remains challenging due to the difficulty of genome assembly in most organisms and the lack of statistical methods powerful enough to discriminate between recent, nonequilibrium histories. We address both the assembly and inference challenges. We develop a bioinformatic pipeline for generating outgroup-rooted alignments of orthologous sequence blocks from de novo low-coverage short-read data for a small number of genomes, and show how such sequence blocks can be used to fit explicit models of population divergence and admixture in a likelihood framework. To illustrate our approach, we reconstruct the Pleistocene history of an oak-feeding insect (the oak gallwasp Biorhiza pallida), which, in common with many other taxa, was restricted during Pleistocene ice ages to a longitudinal series of southern refugia spanning the Western Palaearctic. Our analysis of sequence blocks sampled from a single genome from each of three major glacial refugia reveals support for an unexpected history dominated by recent admixture. Despite the fact that 80% of the genome is affected by admixture during the last glacial cycle, we are able to infer the deeper divergence history of these populations. These inferences are robust to variation in block length, mutation model and the sampling location of individual genomes within refugia. This combination of de novo assembly and numerical likelihood calculation provides a powerful framework for estimating recent population history that can be applied to any organism without the need for prior genetic resources.en_UK
dc.language.isoenen_UK
dc.publisherWiley-Blackwellen_UK
dc.relationHearn J, Stone GN, Bunnefeld L, Nicholls JA, Barton NH & Lohse K (2014) Likelihood-based inference of population history from low-coverage de novo genome assemblies. Molecular Ecology, 23 (1), pp. 198-211. https://doi.org/10.1111/mec.12578en_UK
dc.rightsThe publisher does not allow this work to be made publicly available in this Repository. Please use the Request a Copy feature at the foot of the Repository record to request a copy directly from the author. You can only request a copy if you wish to use this work for your own research or private study.en_UK
dc.rights.urihttp://www.rioxx.net/licenses/under-embargo-all-rights-reserveden_UK
dc.subjectadmixtureen_UK
dc.subjectmaximum likelihooden_UK
dc.subjectpopulation divergenceen_UK
dc.subjectstatistical phylogeographyen_UK
dc.titleLikelihood-based inference of population history from low-coverage de novo genome assembliesen_UK
dc.typeJournal Articleen_UK
dc.rights.embargodate2999-12-05en_UK
dc.rights.embargoreason[Hearn_et_al-2014-Molecular_Ecology.pdf] The publisher does not allow this work to be made publicly available in this Repository therefore there is an embargo on the full text of the work.en_UK
dc.identifier.doi10.1111/mec.12578en_UK
dc.identifier.pmid24188568en_UK
dc.citation.jtitleMolecular Ecologyen_UK
dc.citation.issn1365-294Xen_UK
dc.citation.issn0962-1083en_UK
dc.citation.volume23en_UK
dc.citation.issue1en_UK
dc.citation.spage198en_UK
dc.citation.epage211en_UK
dc.citation.publicationstatusPublisheden_UK
dc.citation.peerreviewedRefereeden_UK
dc.type.statusVoR - Version of Recorden_UK
dc.author.emaillynsey.bunnefeld@stir.ac.uken_UK
dc.citation.date04/11/2013en_UK
dc.contributor.affiliationUniversity of Edinburghen_UK
dc.contributor.affiliationUniversity of Edinburghen_UK
dc.contributor.affiliationBiological and Environmental Sciencesen_UK
dc.contributor.affiliationUniversity of Edinburghen_UK
dc.contributor.affiliationInstitute of Science and Technology Austriaen_UK
dc.contributor.affiliationUniversity of Edinburghen_UK
dc.identifier.isiWOS:000330950900017en_UK
dc.identifier.scopusid2-s2.0-84891529646en_UK
dc.identifier.wtid558597en_UK
dc.contributor.orcid0000-0002-9226-7153en_UK
dc.date.accepted2013-09-20en_UK
dcterms.dateAccepted2013-09-20en_UK
dc.date.filedepositdate2016-07-11en_UK
rioxxterms.typeJournal Article/Reviewen_UK
rioxxterms.versionVoRen_UK
local.rioxx.authorHearn, Jack|en_UK
local.rioxx.authorStone, Graham N|en_UK
local.rioxx.authorBunnefeld, Lynsey|0000-0002-9226-7153en_UK
local.rioxx.authorNicholls, James A|en_UK
local.rioxx.authorBarton, Nicholas H|en_UK
local.rioxx.authorLohse, Konrad|en_UK
local.rioxx.projectInternal Project|University of Stirling|https://isni.org/isni/0000000122484331en_UK
local.rioxx.freetoreaddate2999-12-05en_UK
local.rioxx.licencehttp://www.rioxx.net/licenses/under-embargo-all-rights-reserved||en_UK
local.rioxx.filenameHearn_et_al-2014-Molecular_Ecology.pdfen_UK
local.rioxx.filecount1en_UK
local.rioxx.source0962-1083en_UK
Appears in Collections:Biological and Environmental Sciences Journal Articles

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