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dc.contributor.authorVetö, N.M.
dc.contributor.authorPostolache, D.
dc.contributor.authorGuzman Escudero, F.L.
dc.contributor.authorVajana, E.
dc.contributor.authorBraga, R.B.
dc.contributor.authorSalgueiro, F.
dc.contributor.authorMargis, R.
dc.contributor.authorVendramin, G.G.
dc.contributor.authorTurchetto-Zolet, A.C.
dc.date.accessioned2025-10-31T18:33:35Z
dc.date.available2025-10-31T18:33:35Z
dc.date.issued2023
dc.identifier.urihttps://hdl.handle.net/20.500.12805/4971
dc.description.abstractEvolutionary diversity in species can arise in many ways, including local adaptation. Despite the global importance of tropical forest ecosystems, few studies have explored patterns of local adaptation in tropical tree species. We investigated population genetic structure and adaptive genetic diversity in Eugenia uniflora, a widely distributed tree species across the Atlantic Forest Domain (AFD). We sampled E. uniflora in distinct environments from the AFD and genotyped 523 single-nucleotide polymorphisms (SNPs) using a candidate gene approach. We studied neutral population structure and used two outlier methods based on population differentiation (Bayescan and LEA) and one gene-environment association analysis (LFMM) to detect putative SNPs under divergent selection. We detected spatial population structuring between the northern and southern range of the species distribution and higher genetic diversity in southern populations from the riparian forest. We found 18 candidate loci potentially involved in local adaptation, among which LEA and LFMM both detected seven loci. Overall, precipitation-related variables were more represented in statistically significant genotype-climate associations (c. 60%). Our study provides a first insight into the distribution of adaptive genetic variation in E. uniflora, highlighting how tropical tree species may adapt over time and across the AFD.en_US
dc.description.sponsorshipThis work was financially supported by Conselho Nacional de Desenvolvimento Cient\u00EDfico e Tecnol\u00F3gico (CNPq;grantnumbers:306202/2016-6 and 308135/2020-2), Coordena\u00E7\u00E3o de Aperfei\u00E7oamento de Pessoal de N\u00EDvel Superior (CAPES; grant numbers: 88881.064988/2014-01 and 2806/2014), Funda\u00E7\u00E3o de Amparo \u00E0 Pesquisa do Estado do Rio Grande do Sul (FAPERGS; grant numbers: 16/0491-9 and 19/2551-0001677-8), Instituto Nacional de Ci\u00EAncia e Tecnologia (INCT) Plant Stress Biotech grant from Minist\u00E9rio da Ci\u00EAncia e Tecnologia (MCT) of the Brazilian Government and Postgraduate Program in Genetics and Molecular Biology (PPGMB).
dc.formatapplication/pdf
dc.language.isoeng
dc.publisherOxford University Press
dc.relation.ispartofurn:issn:1095-8339
dc.rightshttps://purl.org/coar/access_right/c_abf2
dc.rights.urihttps://creativecommons.org/licenses/by-nc-sa/4.0/
dc.subjectGenetic Diversity and Evolutionary Insights Across Speciesen_US
dc.subjectGenomic Insights into Population Adaptation and Structureen_US
dc.titlePopulation structure and signals of local adaptation in Eugenia uniflora (Myrtaceae), a widely distributed species in the Atlantic Foresten_US
dc.typehttps://purl.org/coar/resource_type/c_2df8fbb1
dc.identifier.doihttps://doi.org/10.1093/botlinnean/boac012
dc.subject.ocdehttps://purl.org/pe-repo/ocde/ford#1.06.10
dc.type.otherResearch article
dc.identifier.journalBotanical Journal of the Linnean Society
dc.type.versionhttps://purl.org/coar/version/c_970fb48d4fbd8a85


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