Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population
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...
| Autores principales: | , , , , |
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| Formato: | Artículo |
| Lenguaje: | Inglés |
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2018
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| Materias: | |
| Acceso en línea: | https://journals-crea.4science.it/index.php/maydica/article/view/1594/1097 http://hdl.handle.net/20.500.12123/3088 |
| _version_ | 1855483176672034816 |
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| author | Mandolino, Cecilia Ines D'Andrea, Karina Elizabeth Olmos, Sofía Eugenia Otegui, María Elena Eyherabide, Guillermo |
| author_browse | D'Andrea, Karina Elizabeth Eyherabide, Guillermo Mandolino, Cecilia Ines Olmos, Sofía Eugenia Otegui, María Elena |
| author_facet | Mandolino, Cecilia Ines D'Andrea, Karina Elizabeth Olmos, Sofía Eugenia Otegui, María Elena Eyherabide, Guillermo |
| author_sort | Mandolino, Cecilia Ines |
| collection | INTA Digital |
| description | 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 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. |
| format | Artículo |
| id | INTA3088 |
| institution | Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina) |
| language | Inglés |
| publishDate | 2018 |
| publishDateRange | 2018 |
| publishDateSort | 2018 |
| record_format | dspace |
| spelling | INTA30882018-08-15T17:33:32Z Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population Mandolino, Cecilia Ines D'Andrea, Karina Elizabeth Olmos, Sofía Eugenia Otegui, María Elena Eyherabide, Guillermo Maíz Maize Nitrógeno Nitrogen Genética Genetics Loci de Rasgos Cuantitativos Quantitative Trait Loci Eficiencia de uso de nitrógeno QTL Estados Unidos 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 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. EEA Pergamino Fil: 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. Fil: D'Andrea, Karina Elizabeth. Consejo Nacional de Investigaciones, Científicas y Técnicas - Universidad de Buenos Aires. Facultad de Agronomía (CONICET- FAUBA); Argentina. Fil: Olmos, Sofía. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento Agronomía; Argentina. Fil: Mandolino, Cecilia. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Pergamino. Departamento de Laboratorio Biotecnología; Argentina. Fil: 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. Fil: 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. 2018-08-15T17:17:56Z 2018-08-15T17:17:56Z 2018-04 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion https://journals-crea.4science.it/index.php/maydica/article/view/1594/1097 http://hdl.handle.net/20.500.12123/3088 2279-8013 eng info:eu-repo/semantics/openAccess http://creativecommons.org/licenses/by-nc-sa/4.0/ Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International (CC BY-NC-SA 4.0) application/pdf Maydica : a journal devoted to maize and allied species 63 (1) : 1-16. (2018) |
| spellingShingle | Maíz Maize Nitrógeno Nitrogen Genética Genetics Loci de Rasgos Cuantitativos Quantitative Trait Loci Eficiencia de uso de nitrógeno QTL Estados Unidos Mandolino, Cecilia Ines D'Andrea, Karina Elizabeth Olmos, Sofía Eugenia Otegui, María Elena Eyherabide, Guillermo Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title | Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title_full | Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title_fullStr | Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title_full_unstemmed | Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title_short | Maize Nitrogen Use Efficiency: QTL Mapping in a U.S. Dent x Argentine-Caribbean Flint RILs population |
| title_sort | maize nitrogen use efficiency qtl mapping in a u s dent x argentine caribbean flint rils population |
| topic | Maíz Maize Nitrógeno Nitrogen Genética Genetics Loci de Rasgos Cuantitativos Quantitative Trait Loci Eficiencia de uso de nitrógeno QTL Estados Unidos |
| url | https://journals-crea.4science.it/index.php/maydica/article/view/1594/1097 http://hdl.handle.net/20.500.12123/3088 |
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