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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
27/04/2021 |
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Actualizado : |
10/08/2021 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
QUERO, G.; SIMONDI, S.; CERETTA, S.; OTERO, A.; GARAYCOCHEA, S.; FERNANDEZ, S.; BORSANI, O.; BONNECARRERE, V. |
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Afiliación : |
GASTÓN QUERO CORRALLO, Dep. de Biología Vegetal, Facultad de Agronomía, Univ. de la República, Montevideo, Uruguay; SEBASTIÁN SIMONDI, Area de Matemática, Facultad de Ciencias Exactas y Naturales, Univ. Nacional de Cuyo (FCEN-UNCuyo), Mendoza, Argentina; SERGIO EDUARDO CERETTA SORIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ALVARO RICARDO OTERO CAMA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SILVIA RAQUEL GARAYCOCHEA SOLSONA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SCHUBERT DANIEL FERNANDEZ REGGIARDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; OMAR BORSANI, Dep. de Biología Vegetal, Facultad de Agronomía, Univ. de la República, Montevideo, Uruguay; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
An integrative analysis of yield stability for a GWAS in a small soybean breeding population. |
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Fecha de publicación : |
2021 |
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Fuente / Imprenta : |
Crop Science, May 2021, volume 61, issue 3, pages 19003-1914. Doi: https://doi.org/10.1002/csc2.20490 |
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ISSN : |
0011-183X |
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DOI : |
10.1002/csc2.20490 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received, 3 November 2020; Accepted, 11 February 2021; Published online, 14 April 2021.
Associate Editor: Junping Chen.
The authors thank Edgardo Rey and Wanda Iriarte for technical assistance in field experiment and laboratory works, respectively. They also thank Monika Kavanova for her contribution to data interpretation and discussion. This work was financially supported by the following projects: Innovagro FSA_1_2013_1_12924, funded by ANII (Agencia Nacional de Investigación e Innovación), and Red Nacional de Biotecnología Agrícola RTS_1_2014_1, funded by ANII, INIA (Instituto Nacional de Investigación Agropecuaria), Barraca Erro S.A., Lebu SRL, Fadisol SA, CALMER, and COPAGRAN.
Author Contributions: Gastón Quero: Conceptualization, Formal analysis, Investigation, Methodology, Writing‐original draft, Writing‐review & editing. Sebastián Simondi: Data curation, Formal analysis. Sergio Ceretta: Investigation, Methodology. Álvaro Otero: Methodology. Silvia Garaycochea: Methodology, Software. Schubert Fernández: Software. Omar Borsani: Supervision. Victoria Bonnecarrère: Conceptualization, Funding acquisition, Project administration, Supervision, Writing‐original draft, Writing‐review & editing.
Corresponding author: Victoria Bonnecarrère, Instituto Nacional de InvestigaciónAgropecuaria (INIA),Unidad de Biotecnología y Programa de Cultivo de Secano, Estación Experimental INIA Las Brujas,Ruta 48 km10, Canelones,Uruguay. Email: vbonnecarrere@inia.org.uy |
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Contenido : |
ABSTRACT.
Drought stress is one of the most important factors limiting soybean [Glycine max (L.) Merr.] productivity and reducing yield stability. Soybean breeders need phenotypic and genotypic tools to improve drought stress tolerance, but most of available strategies are expensive and unaffordable for small-scale public breeding programs. In this study, elite germplasm of a locally adapted breeding population was used to estimate a yield stability index as an indicator of drought response. In order to associate yield stability of analyzed genotypes to drought response, water deficit scenarios related to the crop cycle group were defined. Four groups of genotypes were identified in relation to yield stability: two groups showed stables yield (without interaction with water deficit scenarios), and two groups showed unstable yield (with crossover interaction with water deficit scenarios). This phenotypic information was used to identify genomic regions and candidate genes associated with yield stability index. A new method for the definition of a quantitative trait loci (QTL) region was developed based on the probability of marker pairwise of belonging to four linkage disequilibrium (LD) categories. Seven QTL were found and their implication on drought tolerance was further supported by linkage to previously reported QTL for water use efficiency trait. © 2021 The Authors. Crop Science © 2021 Crop Science Society of America |
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Palabras claves : |
Drought stress; GBS - Genotyping by sequencing; GWAS - Genome-wide association study. |
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Asunto categoría : |
F30 Genética vegetal y fitomejoramiento |
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Marc : |
LEADER 03833naa a2200277 a 4500
001 1061997
005 2021-08-10
008 2021 bl uuuu u00u1 u #d
022 $a0011-183X
024 7 $a10.1002/csc2.20490$2DOI
100 1 $aQUERO, G.
245 $aAn integrative analysis of yield stability for a GWAS in a small soybean breeding population.$h[electronic resource]
260 $c2021
500 $aArticle history: Received, 3 November 2020; Accepted, 11 February 2021; Published online, 14 April 2021. Associate Editor: Junping Chen. The authors thank Edgardo Rey and Wanda Iriarte for technical assistance in field experiment and laboratory works, respectively. They also thank Monika Kavanova for her contribution to data interpretation and discussion. This work was financially supported by the following projects: Innovagro FSA_1_2013_1_12924, funded by ANII (Agencia Nacional de Investigación e Innovación), and Red Nacional de Biotecnología Agrícola RTS_1_2014_1, funded by ANII, INIA (Instituto Nacional de Investigación Agropecuaria), Barraca Erro S.A., Lebu SRL, Fadisol SA, CALMER, and COPAGRAN. Author Contributions: Gastón Quero: Conceptualization, Formal analysis, Investigation, Methodology, Writing‐original draft, Writing‐review & editing. Sebastián Simondi: Data curation, Formal analysis. Sergio Ceretta: Investigation, Methodology. Álvaro Otero: Methodology. Silvia Garaycochea: Methodology, Software. Schubert Fernández: Software. Omar Borsani: Supervision. Victoria Bonnecarrère: Conceptualization, Funding acquisition, Project administration, Supervision, Writing‐original draft, Writing‐review & editing. Corresponding author: Victoria Bonnecarrère, Instituto Nacional de InvestigaciónAgropecuaria (INIA),Unidad de Biotecnología y Programa de Cultivo de Secano, Estación Experimental INIA Las Brujas,Ruta 48 km10, Canelones,Uruguay. Email: vbonnecarrere@inia.org.uy
520 $aABSTRACT. Drought stress is one of the most important factors limiting soybean [Glycine max (L.) Merr.] productivity and reducing yield stability. Soybean breeders need phenotypic and genotypic tools to improve drought stress tolerance, but most of available strategies are expensive and unaffordable for small-scale public breeding programs. In this study, elite germplasm of a locally adapted breeding population was used to estimate a yield stability index as an indicator of drought response. In order to associate yield stability of analyzed genotypes to drought response, water deficit scenarios related to the crop cycle group were defined. Four groups of genotypes were identified in relation to yield stability: two groups showed stables yield (without interaction with water deficit scenarios), and two groups showed unstable yield (with crossover interaction with water deficit scenarios). This phenotypic information was used to identify genomic regions and candidate genes associated with yield stability index. A new method for the definition of a quantitative trait loci (QTL) region was developed based on the probability of marker pairwise of belonging to four linkage disequilibrium (LD) categories. Seven QTL were found and their implication on drought tolerance was further supported by linkage to previously reported QTL for water use efficiency trait. © 2021 The Authors. Crop Science © 2021 Crop Science Society of America
653 $aDrought stress
653 $aGBS - Genotyping by sequencing
653 $aGWAS - Genome-wide association study
700 1 $aSIMONDI, S.
700 1 $aCERETTA, S.
700 1 $aOTERO, A.
700 1 $aGARAYCOCHEA, S.
700 1 $aFERNANDEZ, S.
700 1 $aBORSANI, O.
700 1 $aBONNECARRERE, V.
773 $tCrop Science, May 2021, volume 61, issue 3, pages 19003-1914. Doi: https://doi.org/10.1002/csc2.20490
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