Alfalfa genomic selection for different stress-prone growing regions

Alfalfa (Medicago sativa L.) selection for stress-prone regions has high priority for sustainable crop–livestock systems. This study assessed the genomic selection (GS) ability to predict alfalfa breeding values for drought-prone agricultural sites of Algeria, Morocco, and Argentina; managed-stress...

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Main Authors: Annicchiarico, Paolo, Nazzicari, Nelson, Bouizgaren, Abdelaziz, Hayek, Taoufik, Laouar, Meriem, Cornacchione, Monica, Basigalup, Daniel Horacio, Monterrubio Martin, Cristina, Brummer, Edward Charles, Pecetti, Luciano
Format: info:ar-repo/semantics/artículo
Language:Inglés
Published: Wiley 2022
Subjects:
Online Access:http://hdl.handle.net/20.500.12123/13132
https://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20264
https://doi.org/10.1002/tpg2.20264
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author Annicchiarico, Paolo
Nazzicari, Nelson
Bouizgaren, Abdelaziz
Hayek, Taoufik
Laouar, Meriem
Cornacchione, Monica
Basigalup, Daniel Horacio
Monterrubio Martin, Cristina
Brummer, Edward Charles
Pecetti, Luciano
author_browse Annicchiarico, Paolo
Basigalup, Daniel Horacio
Bouizgaren, Abdelaziz
Brummer, Edward Charles
Cornacchione, Monica
Hayek, Taoufik
Laouar, Meriem
Monterrubio Martin, Cristina
Nazzicari, Nelson
Pecetti, Luciano
author_facet Annicchiarico, Paolo
Nazzicari, Nelson
Bouizgaren, Abdelaziz
Hayek, Taoufik
Laouar, Meriem
Cornacchione, Monica
Basigalup, Daniel Horacio
Monterrubio Martin, Cristina
Brummer, Edward Charles
Pecetti, Luciano
author_sort Annicchiarico, Paolo
collection INTA Digital
description Alfalfa (Medicago sativa L.) selection for stress-prone regions has high priority for sustainable crop–livestock systems. This study assessed the genomic selection (GS) ability to predict alfalfa breeding values for drought-prone agricultural sites of Algeria, Morocco, and Argentina; managed-stress (MS) environments of Italy featuring moderate or intense drought; and one Tunisian site irrigated with moderately saline water. Additional aims were to investigate genotype × environment interaction (GEI) patterns and the effect on GS predictions of three single-nucleotide polymorphism (SNP) calling procedures, 12 statistical models that exclude or incorporate GEI, and allele dosage information. Our study included 127 genotypes from a Mediterranean reference population originated from three geographically contrasting populations, genotyped via genotyping-by-sequencing and phenotyped based on multi-year biomass dry matter yield of their dense-planted half-sib progenies. The GEI was very large, as shown by 27-fold greater additive genetic variance × environment interaction relative to the additive genetic variance and low genetic correlation for progeny yield responses across environments. The predictive ability of GS (using at least 37,969 SNP markers) exceeded 0.20 for moderate MS (representing Italian stress-prone sites) and the sites of Algeria and Argentina while being quite low for the Tunisian site and intense MS. Predictions of GS were complicated by rapid linkage disequilibrium decay. The weighted GBLUP model, GEI incorporation into GS models, and SNP calling based on a mock reference genome exhibited a predictive ability advantage for some environments. Our results support the specific breeding for each target region and suggest a positive role for GS in most regions when considering the challenges associated with phenotypic selection.
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institution Instituto Nacional de Tecnología Agropecuaria (INTA -Argentina)
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spelling INTA131322022-10-17T14:08:36Z Alfalfa genomic selection for different stress-prone growing regions Annicchiarico, Paolo Nazzicari, Nelson Bouizgaren, Abdelaziz Hayek, Taoufik Laouar, Meriem Cornacchione, Monica Basigalup, Daniel Horacio Monterrubio Martin, Cristina Brummer, Edward Charles Pecetti, Luciano Medicago sativa Selección Asistida por Marcadores Valor Genético Estres Estrés de Sequia Marker-assisted Selection Breeding Value Stress Drought Stress Alfalfa Selección Genómica Lucerne Genomic Selection Alfalfa (Medicago sativa L.) selection for stress-prone regions has high priority for sustainable crop–livestock systems. This study assessed the genomic selection (GS) ability to predict alfalfa breeding values for drought-prone agricultural sites of Algeria, Morocco, and Argentina; managed-stress (MS) environments of Italy featuring moderate or intense drought; and one Tunisian site irrigated with moderately saline water. Additional aims were to investigate genotype × environment interaction (GEI) patterns and the effect on GS predictions of three single-nucleotide polymorphism (SNP) calling procedures, 12 statistical models that exclude or incorporate GEI, and allele dosage information. Our study included 127 genotypes from a Mediterranean reference population originated from three geographically contrasting populations, genotyped via genotyping-by-sequencing and phenotyped based on multi-year biomass dry matter yield of their dense-planted half-sib progenies. The GEI was very large, as shown by 27-fold greater additive genetic variance × environment interaction relative to the additive genetic variance and low genetic correlation for progeny yield responses across environments. The predictive ability of GS (using at least 37,969 SNP markers) exceeded 0.20 for moderate MS (representing Italian stress-prone sites) and the sites of Algeria and Argentina while being quite low for the Tunisian site and intense MS. Predictions of GS were complicated by rapid linkage disequilibrium decay. The weighted GBLUP model, GEI incorporation into GS models, and SNP calling based on a mock reference genome exhibited a predictive ability advantage for some environments. Our results support the specific breeding for each target region and suggest a positive role for GS in most regions when considering the challenges associated with phenotypic selection. EEA Santiago del Estero Fil: Annicchiarico, Paolo. Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria. Centro di Ricerca Zootecnia e Acquacoltura; Italia Fil: Nazzicari, Nelson. Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria. Centro di Ricerca Zootecnia e Acquacoltura; Italia Fil: Bouizgaren, Abdelaziz. Institut National de la Recherche Agronomique du Maroc. Centres Régionaux de Marrakech et de Rabat; Marruecos Fil: Hayek, Taoufik. Institut des Régions Arides de Médenine; Tunez Fil: Laouar, Meriem. Ecole Nationale Supérieure Agronomique. Dép. de Productions Végétales. Laboratoire d’Amélioration Intégrative des Productions Végétales; Argelia Fil: Cornacchione, Monica. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Santiago del Estero; Argentina Fil: Basigalup, Daniel Horacio. Instituto Nacional de Tecnología Agropecuaria (INTA). Estación Experimental Agropecuaria Manfredi. Grupo de Mejoramiento Genético de Alfalfa; Argentina Fil: Monterrubio Martin, Cristina. Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria. Centro di Ricerca Zootecnia e Acquacoltura; Italia Fil: Brummer, E. Charles. University of California at Davies. Depeparment of Plant Sciences. Plant Breeding Center,; Estados Unidos Fil: Pecetti, Luciano. Consiglio per la Ricerca in Agricoltura e l’Analisi dell’Economia Agraria. Centro di Ricerca Zootecnia e Acquacoltura; Italia 2022-10-17T14:04:18Z 2022-10-17T14:04:18Z 2022-10 info:ar-repo/semantics/artículo info:eu-repo/semantics/article info:eu-repo/semantics/publishedVersion http://hdl.handle.net/20.500.12123/13132 https://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20264 1940-3372 https://doi.org/10.1002/tpg2.20264 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 Wiley The Plant Genome : e20264 (First published: 12 October 2022)
spellingShingle Medicago sativa
Selección Asistida por Marcadores
Valor Genético
Estres
Estrés de Sequia
Marker-assisted Selection
Breeding Value
Stress
Drought Stress
Alfalfa
Selección Genómica
Lucerne
Genomic Selection
Annicchiarico, Paolo
Nazzicari, Nelson
Bouizgaren, Abdelaziz
Hayek, Taoufik
Laouar, Meriem
Cornacchione, Monica
Basigalup, Daniel Horacio
Monterrubio Martin, Cristina
Brummer, Edward Charles
Pecetti, Luciano
Alfalfa genomic selection for different stress-prone growing regions
title Alfalfa genomic selection for different stress-prone growing regions
title_full Alfalfa genomic selection for different stress-prone growing regions
title_fullStr Alfalfa genomic selection for different stress-prone growing regions
title_full_unstemmed Alfalfa genomic selection for different stress-prone growing regions
title_short Alfalfa genomic selection for different stress-prone growing regions
title_sort alfalfa genomic selection for different stress prone growing regions
topic Medicago sativa
Selección Asistida por Marcadores
Valor Genético
Estres
Estrés de Sequia
Marker-assisted Selection
Breeding Value
Stress
Drought Stress
Alfalfa
Selección Genómica
Lucerne
Genomic Selection
url http://hdl.handle.net/20.500.12123/13132
https://acsess.onlinelibrary.wiley.com/doi/10.1002/tpg2.20264
https://doi.org/10.1002/tpg2.20264
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AT laouarmeriem alfalfagenomicselectionfordifferentstresspronegrowingregions
AT cornacchionemonica alfalfagenomicselectionfordifferentstresspronegrowingregions
AT basigalupdanielhoracio alfalfagenomicselectionfordifferentstresspronegrowingregions
AT monterrubiomartincristina alfalfagenomicselectionfordifferentstresspronegrowingregions
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