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dc.contributor.authorWiberg, R. A. W.
dc.contributor.authorTyukmaeva, V.
dc.contributor.authorHoikkala, A.
dc.contributor.authorRitchie, M. G.
dc.contributor.authorKankare, M.
dc.date.accessioned2021-08-10T08:08:28Z
dc.date.available2021-08-10T08:08:28Z
dc.date.issued2021
dc.identifier.citationWiberg, R. A. W., Tyukmaeva, V., Hoikkala, A., Ritchie, M. G., & Kankare, M. (2021). Cold adaptation drives population genomic divergence in the ecological specialist, Drosophila montana. <i>Molecular Ecology</i>, <i>30</i>(15), 3783-3796. <a href="https://doi.org/10.1111/mec.16003" target="_blank">https://doi.org/10.1111/mec.16003</a>
dc.identifier.otherCONVID_97806138
dc.identifier.urihttps://jyx.jyu.fi/handle/123456789/77307
dc.description.abstractDetecting signatures of ecological adaptation in comparative genomics is challenging, but analysing population samples with characterised geographic distributions, such as clinal variation, can help identify genes showing covariation with important ecological variation. Here we analysed patterns of geographic variation in the cold-adapted species Drosophila montana across phenotypes, genotypes and environmental conditions and tested for signatures of cold adaptation in population genomic divergence. We first derived the climatic variables associated with the geographic distribution of 24 populations across two continents to trace the scale of environmental variation experienced by the species, and measured variation in the cold tolerance of the flies of six populations from different geographic contexts. We then performed pooled whole genome sequencing of these six populations, and used Bayesian methods to identify SNPs where genetic differentiation is associated with both climatic variables and the population phenotypic measurements, while controlling for effects of demography and population structure. The top candidate SNPs were enriched on the X and 4th chromosomes, and they also lay near genes implicated in other studies of cold tolerance and population divergence in this species and its close relatives. We conclude that ecological adaptation has contributed to the divergence of D. montana populations throughout the genome and in particular on the X and 4th chromosomes, which also showed highest interpopulation FST. This study demonstrates that ecological selection can drive genomic divergence at different scales, from candidate genes to chromosome-wide effects.en
dc.format.mimetypeapplication/pdf
dc.language.isoeng
dc.publisherWiley
dc.relation.ispartofseriesMolecular Ecology
dc.rightsCC BY 4.0
dc.subject.otherCCRT
dc.subject.othercline populations
dc.subject.othercold tolerance
dc.subject.otherCTmin
dc.subject.otherD. montana
dc.subject.otherenvironmental adaptation
dc.subject.othergenomic divergence
dc.titleCold adaptation drives population genomic divergence in the ecological specialist, Drosophila montana
dc.typearticle
dc.identifier.urnURN:NBN:fi:jyu-202108104472
dc.contributor.laitosBio- ja ympäristötieteiden laitosfi
dc.contributor.laitosDepartment of Biological and Environmental Scienceen
dc.contributor.oppiaineEvoluutiotutkimus (huippuyksikkö)fi
dc.contributor.oppiaineEkologia ja evoluutiobiologiafi
dc.contributor.oppiaineCentre of Excellence in Evolutionary Researchen
dc.contributor.oppiaineEcology and Evolutionary Biologyen
dc.type.urihttp://purl.org/eprint/type/JournalArticle
dc.description.reviewstatuspeerReviewed
dc.format.pagerange3783-3796
dc.relation.issn0962-1083
dc.relation.numberinseries15
dc.relation.volume30
dc.type.versionpublishedVersion
dc.rights.copyright© 2021 the Authors
dc.rights.accesslevelopenAccessfi
dc.relation.grantnumber267244
dc.relation.grantnumber322980
dc.relation.grantnumber268214
dc.subject.ysokylmänkestävyys
dc.subject.ysogeneettinen muuntelu
dc.subject.ysogenomiikka
dc.subject.ysopopulaatiogenetiikka
dc.subject.ysosopeutuminen
dc.subject.ysomuuntelu (biologia)
dc.subject.ysomahlakärpäset
dc.format.contentfulltext
jyx.subject.urihttp://www.yso.fi/onto/yso/p3062
jyx.subject.urihttp://www.yso.fi/onto/yso/p23916
jyx.subject.urihttp://www.yso.fi/onto/yso/p5146
jyx.subject.urihttp://www.yso.fi/onto/yso/p9005
jyx.subject.urihttp://www.yso.fi/onto/yso/p6137
jyx.subject.urihttp://www.yso.fi/onto/yso/p8280
jyx.subject.urihttp://www.yso.fi/onto/yso/p12159
dc.rights.urlhttps://creativecommons.org/licenses/by/4.0/
dc.relation.doi10.1111/mec.16003
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
dc.relation.funderSuomen Akatemiafi
dc.relation.funderAcademy of Finlanden
dc.relation.funderAcademy of Finlanden
dc.relation.funderAcademy of Finlanden
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramAkatemiahanke, SAfi
jyx.fundingprogramAkatemiatutkijan tehtävä, SAfi
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramAcademy Project, AoFen
jyx.fundingprogramResearch post as Academy Research Fellow, AoFen
jyx.fundinginformationThis work was supported by a combined Natural Environment Research Council and St Andrews 600th Anniversary PhD Studentship grant (NE/L501852/1) to RAWW, The Ella and Georg Ehrnrooth Fellowship to VT, NERC grant (NE/P000592/1) to MGR, and Academy of Finland project 267244 to AH and projects 268214 and 322980 to MK. Bioinformatics and Computational Biology analyses were supported by the University of St Andrews Bioinformatics Unit which is funded by a Wellcome Trust ISSF award (grant 105621/Z/14/Z).


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