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Abstract
This study was aimed to identify quantitative trait loci (QTL) for nitrogen use efficiency (NUE) and related traits in a maize population derived from a cross between two lines with different genetic background (B100 and LP2). Recombinant inbred lines (181) from this population were evaluated under field conditions during two growing seasons, and significant (P < 0.01) phenotypic and genotypic variability was detected for most evaluated traits. Two [ver mas...]
dc.contributor.authorMandolino, Cecilia Ines
dc.contributor.authorD'Andrea, Karina Elizabeth
dc.contributor.authorOlmos, Sofía Eugenia
dc.contributor.authorOtegui, María Elena
dc.contributor.authorEyherabide, Guillermo
dc.date.accessioned2018-08-15T17:17:56Z
dc.date.available2018-08-15T17:17:56Z
dc.date.issued2018-04
dc.identifier.issn2279-8013
dc.identifier.urihttps://journals-crea.4science.it/index.php/maydica/article/view/1594/1097
dc.identifier.urihttp://hdl.handle.net/20.500.12123/3088
dc.description.abstractThis study was aimed to identify quantitative trait loci (QTL) for nitrogen use efficiency (NUE) and related traits in a maize population derived from a cross between two lines with different genetic background (B100 and LP2). Recombinant inbred lines (181) from this population were evaluated under field conditions during two growing seasons, and significant (P < 0.01) phenotypic and genotypic variability was detected for most evaluated traits. Two different mapping methods were applied for detecting QTLs. Firstly, a trait by trait approach was performed on across environments, and 19 QTLs were identified. Secondly, a multi-trait multi-environment analysis detected seven joint QTLs. Almost all joint QTLs had inconsistent additive effects from one environment to another, which would reflect presence of QTL × Environment interaction. Most joint QTLs co-localized with QTLs detected by individual mapping. We detected consistent additive effects for grain yield per plant and NUE, as well as for biomass and nitrogen harvest index in some joint QTLs, especially QTL-1 and QTL-6. These QTLs had positive and stable effects across environments, and presence of some genes within these QTL intervals could be relevant for selecting for both NUE and grain yield simultaneously. Up today, this is a first report on the co-localization of QTLs for enhanced allocation of biomass allocation to grains with NUE, and NUE candidate gene identification. Fine mapping of these regions could allow to detect additional markers more closely linked to these QTLs that could be used for marker assisted selection for NUE.es_AR
dc.formatapplication/pdfes_AR
dc.language.isoenges_AR
dc.rightsinfo:eu-repo/semantics/openAccesses_AR
dc.sourceMaydica : a journal devoted to maize and allied species 63 (1) : 1-16. (2018)es_AR
dc.subjectMaízes_AR
dc.subjectMaizees_AR
dc.subjectNitrógenoes_AR
dc.subjectNitrogenes_AR
dc.subjectGenéticaes_AR
dc.subjectGeneticses_AR
dc.subjectLoci de Rasgos Cuantitativos
dc.subjectQuantitative Trait Locieng
dc.subject.otherEficiencia de uso de nitrógenoes_AR
dc.subject.otherQTL
dc.subject.otherEstados Unidos
dc.titleMaize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs populationes_AR
dc.typeinfo:ar-repo/semantics/artículoes_AR
dc.typeinfo:eu-repo/semantics/articleeng
dc.typeinfo:eu-repo/semantics/publishedVersioneng
dc.description.origenEEA Pergaminoes_AR
dc.description.filFil: Mandolino, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Laboratorio Biotecnología; Argentina. Universidad Nacional Noroeste de Buenos Aires. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CIT NOBA); Argentina.es_AR
dc.description.filFil: D'Andrea, Karina Elizabeth. Consejo Nacional de Investigaciones, Científicas y Técnicas - Universidad de Buenos Aires. Facultad de Agronomía (CONICET- FAUBA); Argentina.es_AR
dc.description.filFil: Olmos, Sofía. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento Agronomía; Argentina.es_AR
dc.description.filFil: Mandolino, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Laboratorio Biotecnología; Argentina.es_AR
dc.description.filFil: Otegui, María. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Ecofisiología; Argentina. Consejo Nacional de Investigaciones, Científicas y Técnicas - Universidad de Buenos Aires. Facultad de Agronomía (CONICET- FAUBA); Argentina.es_AR
dc.description.filFil: Eyhérabide, Guillermo. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Laboratorio Biotecnología; Argentina. Universidad Nacional Noroeste de Buenos Aires. Centro de Investigaciones y Transferencia del Noroeste de la Provincia de Buenos Aires (CIT NOBA); Argentina.es_AR
dc.subtypecientifico


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