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White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction

White lupin is a high-protein crop requiring drought tolerance improvement. This study focused on a genetically-broad population of 138 lines to investigate the phenotypic variation and genotype × environment interaction (GEI) for grain yield and other traits across drought-prone and moisture-favour...

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Autores principales: Pecetti, Luciano, Annicchiarico, Paolo, Crosta, Margherita, Notario, Tommaso, Ferrari, Barbara, Nazzicari, Nelson
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916572/
https://www.ncbi.nlm.nih.gov/pubmed/36768674
http://dx.doi.org/10.3390/ijms24032351
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author Pecetti, Luciano
Annicchiarico, Paolo
Crosta, Margherita
Notario, Tommaso
Ferrari, Barbara
Nazzicari, Nelson
author_facet Pecetti, Luciano
Annicchiarico, Paolo
Crosta, Margherita
Notario, Tommaso
Ferrari, Barbara
Nazzicari, Nelson
author_sort Pecetti, Luciano
collection PubMed
description White lupin is a high-protein crop requiring drought tolerance improvement. This study focused on a genetically-broad population of 138 lines to investigate the phenotypic variation and genotype × environment interaction (GEI) for grain yield and other traits across drought-prone and moisture-favourable managed environments, the trait genetic architecture and relevant genomic regions by a GWAS using 9828 mapped SNP markers, and the predictive ability of genomic selection (GS) models. Water treatments across two late cropping months implied max. available soil water content of 60–80% for favourable conditions and from wilting point to 15% for severe drought. Line yield responses across environments featured a genetic correlation of 0.84. Relatively better line yield under drought was associated with an increased harvest index. Two significant QTLs emerged for yield in each condition that differed across conditions. Line yield under stress displayed an inverse linear relationship with the onset of flowering, confirmed genomically by a common major QTL. An adjusted grain yield computed as deviation from phenology-predicted yield acted as an indicator of intrinsic drought tolerance. On the whole, the yield in both conditions and the adjusted yield were polygenic, heritable, and exploitable by GS with a high predictive ability (0.62–0.78). Our results can support selection for climatically different drought-prone regions.
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spelling pubmed-99165722023-02-11 White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction Pecetti, Luciano Annicchiarico, Paolo Crosta, Margherita Notario, Tommaso Ferrari, Barbara Nazzicari, Nelson Int J Mol Sci Article White lupin is a high-protein crop requiring drought tolerance improvement. This study focused on a genetically-broad population of 138 lines to investigate the phenotypic variation and genotype × environment interaction (GEI) for grain yield and other traits across drought-prone and moisture-favourable managed environments, the trait genetic architecture and relevant genomic regions by a GWAS using 9828 mapped SNP markers, and the predictive ability of genomic selection (GS) models. Water treatments across two late cropping months implied max. available soil water content of 60–80% for favourable conditions and from wilting point to 15% for severe drought. Line yield responses across environments featured a genetic correlation of 0.84. Relatively better line yield under drought was associated with an increased harvest index. Two significant QTLs emerged for yield in each condition that differed across conditions. Line yield under stress displayed an inverse linear relationship with the onset of flowering, confirmed genomically by a common major QTL. An adjusted grain yield computed as deviation from phenology-predicted yield acted as an indicator of intrinsic drought tolerance. On the whole, the yield in both conditions and the adjusted yield were polygenic, heritable, and exploitable by GS with a high predictive ability (0.62–0.78). Our results can support selection for climatically different drought-prone regions. MDPI 2023-01-25 /pmc/articles/PMC9916572/ /pubmed/36768674 http://dx.doi.org/10.3390/ijms24032351 Text en © 2023 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Pecetti, Luciano
Annicchiarico, Paolo
Crosta, Margherita
Notario, Tommaso
Ferrari, Barbara
Nazzicari, Nelson
White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title_full White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title_fullStr White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title_full_unstemmed White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title_short White Lupin Drought Tolerance: Genetic Variation, Trait Genetic Architecture, and Genome-Enabled Prediction
title_sort white lupin drought tolerance: genetic variation, trait genetic architecture, and genome-enabled prediction
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9916572/
https://www.ncbi.nlm.nih.gov/pubmed/36768674
http://dx.doi.org/10.3390/ijms24032351
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