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dc.creatorMikić, Sanja
dc.creatorKondić-Špika, Ankica
dc.creatorBrbaklić, Ljiljana
dc.creatorStanisavljević, Dušan
dc.creatorTrkulja, Dragana
dc.creatorTomičić, Marina
dc.creatorNastasić, Aleksandra
dc.creatorKobiljski, Borislav
dc.creatorProdanović, Slaven
dc.creatorŠurlan-Momirović, Gordana
dc.date.accessioned2021-04-26T19:27:32Z
dc.date.available2021-04-26T19:27:32Z
dc.date.issued2016
dc.identifier.issn0718-5839
dc.identifier.urihttp://fiver.ifvcns.rs/handle/123456789/1587
dc.description.abstractAssociation analysis is a relatively novel approach in quantitative traits studies that allows high resolution mapping and time efficient and direct application on breeding material. Since the markers, which are close to the quantitative trait loci stable across environments and genetic backgrounds, may be valuable for marker assisted selection, we chose microsatellite markers previously linked to traits of interest in various mapping studies. A set of 36 microsatellite markers positioned near important maize (Zea mays L.) agronomic loci was used to evaluate genetic diversity and determine population structure. To verify the associations between the markers and traits, a panel of diverse maize inbred lines was genotyped with microsatellites and phenotyped for flowering time, yield and yield components. A relatively high level of polymorphism detected in number of alleles per locus (8.2), average polymorphic information content value (0.64), and average gene diversity (0.684) lines showed the analyzed panel of maize inbred contained significant genetic diversity and was suitable for association mapping. The population structure estimated by model-based clustering method grouped maize inbred lines into three clusters. The association analysis using the general linear and mixed linear models determined significant correlations between several agronomic traits and three microsatellites on chromosomes 3, 5, and 8, namely umc1025, bnlg1237, and bnlg162 consistent across the environments, explaining from 4.7% to 18.2% of total phenotypic variations. The results suggest that the chromosome regions containing quantitative trait loci (QTLs) associated with multiple yield-related traits consistently across environments are potentially important targets for selection.en
dc.publisherInst Investigaciones Agropecuarias, Chillan
dc.relationinfo:eu-repo/grantAgreement/MESTD/Technological Development (TD or TR)/31073/RS//
dc.rightsopenAccess
dc.sourceChilean Journal of Agricultural Research
dc.subjectAssociation analysisen
dc.subjectinbred linesen
dc.subjectlinkageen
dc.subjectpleiotropyen
dc.subjectSSR markersen
dc.subjectZea maysen
dc.titleMultiple marker-traits associations for maize agronomic traitsen
dc.typearticle
dc.rights.licensePublisher's own license
dc.citation.epage306
dc.citation.issue3
dc.citation.other76(3): 300-306
dc.citation.rankM22
dc.citation.spage300
dc.citation.volume76
dc.identifier.doi10.4067/S0718-58392016000300006
dc.identifier.fulltexthttp://fiver.ifvcns.rs/bitstream/id/521/1584.pdf
dc.identifier.scopus2-s2.0-84995679645
dc.identifier.wos000387021600006
dc.type.versionpublishedVersion


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