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Registros recuperados : 25 | |
3. | | GUTIERREZ, L.; BORGES, A.; QUERO, G.; GONZALEZ-REYMUNDEZ, A.; BERRO, I.; LADO, B.; CASTRO, A. Biostatistical tools for plant breeding in the genomics era. In: German, S.; Quincke, M.; Vázquez, D.; Castro, M.; Pereyra, S.; Silva, P.; García, A. (Eds.). Seminario Internacional "1914-2014: Un siglo de mejoramiento de trigo en La Estanzuela". Montevideo (UY): INIA, 2018. p.46-57. (INIA Serie Técnica; 241).Biblioteca(s): INIA La Estanzuela. |
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4. | | QUERO, G.; BONNECARRERE, V.; FERNÁNDEZ, S.; SILVA, P.; SIMONDI, S.; BORSANI, O. La eficiencia del uso de luz y la partición energética en arroz es genotipo dependiente. [resumen] In: INIA (Instituto Nacional de Investigación Agropecuaria); INIA Las Brujas; Biotecnología. Jornada de Agrobiotecnología, XI. Encuentro Nacional de REDBIO, III. Jornada técnica. Las Brujas, Canelones (UY): INIA, 2018. p.8-9 (Serie Actividades de Difusión; 786)Biblioteca(s): INIA Las Brujas. |
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8. | | LARZABAL, J.; BONNECARRERE, V.; QUERO, G.; BENTOS, D.; RODRIGUEZ, M.; STEWART, S. P13. Agresividad de aislamientos de Diaporthe caulivora, principal agente causal del cancro del tallo de la soja en Uruguay. [Poster]. Posters. In: Sociedad Uruguaya de Fitopatología (SUFIT). Jornada Uruguaya de Fitopatología, 7., Jornada Uruguaya de Protección Vegetal, 5., 10 noviembre 2023, Montevideo, Uruguay. Libro de resúmenes. 30 años SUFIT, 1993-2023. Montevideo (UY): Sociedad Uruguay de Fitopatología (SUFIT), 2023. p. 40. Fuente de financiamiento: ANII Beca de Doctorado POS_NAC_2020_1_164264. -- Autor correspondencia: e-mail: larzabaljc@gmail.comBiblioteca(s): INIA Las Brujas. |
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9. | | QUERO, G.; SIMONDI, S.; CERETTA, S.; OTERO, A.; GARAYCOCHEA, S.; FERNANDEZ, S.; BORSANI, O.; BONNECARRERE, V. An integrative analysis of yield stability for a GWAS in a small soybean breeding population. Crop Science, May 2021, volume 61, issue 3, pages 19003-1914. Doi: https://doi.org/10.1002/csc2.20490 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...Biblioteca(s): INIA Las Brujas. |
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11. | | ROSAS, J.E.; ESCOBAR, M.; MARTÍNEZ, S.; BLANCO, P.H.; PÉREZ DE VIDA, F.; QUERO, G.; GUTIÉRREZ, L.; BONNECARRERE, V. Epistasis and quantitative resistance to Pyricularia oryzae revealed by GWAS in advanced rice breeding populations. Agriculture 2020, 10(12), 622. Open Access. DOI: https://doi.org/10.3390/agriculture10120622 Article history: Received: 30 October 2020 / Revised: 23 November 2020 / Accepted: 24 November 2020 / Published: 11 December 2020.Biblioteca(s): INIA Treinta y Tres. |
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12. | | REBUFFO, M.; MONZA, J.; CASTILLO, A.; SANJUÁN, J.; REYNO, R.; BATISTA, L.; QUERO, G.; CUITIÑO, M.J. Multidisciplinary approaches to improve forage legume species for stressing environments in South America. In: INTERNATIONAL SYMPOSIUM ON THE MOLECULAR BREEDING OF FORAGE AND TURF, 7., 2012, Salt Lake City, UT, US. Proceedings: other invited oral presentation abstracts. Salt Lake City, UT: MBFT, 2012. p. 62.Biblioteca(s): INIA La Estanzuela. |
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13. | | MONTEVERDE, E.; ROSAS, J.E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; BONNECARRERE, V.; QUERO, G.; GUTIERREZ, L.; MCCOUCH, S. Multienvironment models increase prediction accuracy of complex traits in advanced breeding lines of rice (O. sativa). Crop Science, 2018, 58:1519-1530. Article history: Accepted on May 09, 2018. Published online June 21, 2018.Biblioteca(s): INIA Treinta y Tres. |
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14. | | MONTEVERDE, E.; GUTIERREZ, L.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; BONNECARRERE, V.; QUERO, G.; MCCOUCH, SUSAN Integrating molecular markers and environmental covariates to interpret genotype by environment interaction in rice (Oryza sativa L.) grown in subtropical areas. G3: GENES, GENOMES, GENETICS May 1, 2019, v.9 (5), p. 1519-1531. OPEN ACCESS. Article history: Manuscript received February 6, 2019 // Accepted for publication March 5, 2019// Published Early Online March 15, 2019.
Supplemental material available at Figshare: https://doi.org/10.25387/g3.7685636Biblioteca(s): INIA Treinta y Tres. |
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16. | | BONNECARRERE, V.; QUERO, G.; MONTEVERDE, E.; ROSAS, J.E.; PÉREZ DE VIDA, F.; CRUZ, M.; CORREDOR, E.; GARAYCOCHEA, S.; MONZA, J.; BORSANI, O. Candidate gene markers associated with cold tolerance in vegetative stage of rice (Oryza sativa L.). Euphytica, 2015, v. 203 no. 2, p. 385-398. p. 385-398. Received: 17 June 2014 / Accepted: 23 October 2014 / Published online: 2 November 2014Biblioteca(s): INIA Las Brujas; INIA Treinta y Tres. |
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17. | | ROSAS, J.E.; BONNECARRERE, V.; MARTÍNEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; QUERO, G.; FERNANDEZ, S.; GARAYCOCHEA, S.; JANNINK, J.L.; GUTIÉRREZ, L. GWAS for resistance to stem rot and aggregated sheath spot in advanced temperate rice (Oryza sativa L.) germplasm. [Poster]. In: International Conference on Quantitative Genetics, (5o., 2016, Madison)Biblioteca(s): INIA Treinta y Tres. |
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18. | | QUERO, G.; GUTIÉRREZ, L.; FERNANDEZ, S.; BLANCO, P.H.; PÉREZ DE VIDA, F.; GARAYCOCHEA, S.; MONTEVERDE, E.; MCCOUCH, M.; ROSAS, J.E.; BERBERIAN, N.; SIMONDIS, S.; BONNECARRERE, V. Genome wide association (GWAS) discovers rice granin quality genes in the starch metabolism, grain size and cell wall synthesis pathways. MV 24 - COMUNICACIONES LIBRES - MV. MEJORAMIENTO VEGETAL In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 292Biblioteca(s): INIA Las Brujas. |
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19. | | ROSAS, J.E.; BONNECARRERE, V.; MARTÍNEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; QUERO, G.; FERNANDEZ, S.; GARAYCOCHEA, S.; JANNINK, J.; GUTIERREZ, L. Mapeo asociativo de la resistencia a enfermedades del tallo y la vaina en germoplasma avanzado de arroz. 2 - SIMPOSIOS "MEJORAMIENTO GENÉTICO POR RESISTENCIA A ENFERMEDADES E INTERACCIONES PLANTA-PATÓGENO" In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 61Biblioteca(s): INIA Las Brujas. |
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20. | | BONNECARRERE, M.; QUERO, G.; ROSAS, J.E.; FERNANDEZ, S.; GARAYCOCHEA, S.; MARTÍNEZ, S.; PÉREZ DE VIDA, F.; BLANCO, P.H.; BERBERIAN, N.; GUTIERREZ, L. Marcadores moleculares identificados en el Proyecto "Mapeo asociativo para asistir el mejoramiento genético de arroz". In: JORNADA TÉCNICA, VIII JORNADA DE AGROBIOTECNOLOGÍA. INIA LAS BRUJAS, 30 DE OCTUBRE DE 2014. UNIDAD DE BIOTECNOLOGÍA. Montevideo (Uruguay): INIA, 2014. 5-6 (Actividades de Difusión; 741)Biblioteca(s): INIA Las Brujas. |
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Registros recuperados : 25 | |
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Registro completo
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Biblioteca (s) : |
INIA Treinta y Tres. |
Fecha actual : |
15/12/2020 |
Actualizado : |
08/02/2021 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
-- - -- |
Autor : |
ROSAS, J.E.; ESCOBAR, M.; MARTÍNEZ, S.; BLANCO, P.H.; PÉREZ DE VIDA, F.; QUERO, G.; GUTIÉRREZ, L.; BONNECARRERE, V. |
Afiliación : |
JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; MAIA ESCOBAR BONORA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SEBASTIÁN MARTÍNEZ KOPP, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GASTÓN QUERO CORRALLO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Facultad de Agronomía, UDELAR; University of Wisconsin-Madison, USA.; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
Título : |
Epistasis and quantitative resistance to Pyricularia oryzae revealed by GWAS in advanced rice breeding populations. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Agriculture 2020, 10(12), 622. Open Access. DOI: https://doi.org/10.3390/agriculture10120622 |
DOI : |
10.3390/agriculture10120622 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 30 October 2020 / Revised: 23 November 2020 / Accepted: 24 November 2020 / Published: 11 December 2020. |
Contenido : |
Rice blast caused by Pyricularia oryzae is a major rice disease worldwide. Despite the detailed knowledge on major resistance genes available to date, little is known about how these genes interact with quantitative blast resistance loci and with the genetic background. Knowledge on these interactions is crucial for assessing the usefulness of introgressed resistance loci in breeding germplasm. Our goal was to identify quantitative trait loci (QTL) for blast resistance in rice breeding populations and to describe how they interact among each other and with the genetic background. To that end, resistance to blast was mapped by genome-wide association study (GWAS) in two advanced rice breeding subpopulations, one made of 305 indica type inbred lines, and the other of 245 tropical japonica inbred lines. The interactions and main effects of blast resistance loci were assessed in a multilocus model. Well known, major effect blast resistance gene clusters were detected in both tropical japonica (Pii/Pi3/Pi5) and indica (Piz/Pi2/Pi9) subpopulations with the GWAS scan 1. When these major effect loci were included as fixed cofactors in subsequent GWAS scans 2 and 3, additional QTL and more complex genetic architectures were revealed. The multilocus model for the tropical japonica subpopulation showed that Pii/Pi3/Pi5 had significant interaction with two QTL in chromosome 1 and one QTL in chromosome 8, together explaining 64% of the phenotypic variance. In the indica subpopulation a significant interaction among the QTL in chromosomes 6 and 4 and the genetic background, together with Piz/Pi2/Pi9 and QTL in chromosomes 1, 4 and 7, explained 35% of the phenotypic variance. Our results suggest that epistatic interactions can play a major role modulating the response mediated by major effect blast resistance loci such as Pii/Pi3/Pi5. Furthermore, the additive and epistatic effects of multiple QTL bring additional layers of quantitative resistance with a magnitude comparable to that of major effect loci. These findings highlight the need of genetic background-specific validation of markers for molecular assisted blast resistance breeding and provide insights for developing quantitative resistance to blast disease in rice. MenosRice blast caused by Pyricularia oryzae is a major rice disease worldwide. Despite the detailed knowledge on major resistance genes available to date, little is known about how these genes interact with quantitative blast resistance loci and with the genetic background. Knowledge on these interactions is crucial for assessing the usefulness of introgressed resistance loci in breeding germplasm. Our goal was to identify quantitative trait loci (QTL) for blast resistance in rice breeding populations and to describe how they interact among each other and with the genetic background. To that end, resistance to blast was mapped by genome-wide association study (GWAS) in two advanced rice breeding subpopulations, one made of 305 indica type inbred lines, and the other of 245 tropical japonica inbred lines. The interactions and main effects of blast resistance loci were assessed in a multilocus model. Well known, major effect blast resistance gene clusters were detected in both tropical japonica (Pii/Pi3/Pi5) and indica (Piz/Pi2/Pi9) subpopulations with the GWAS scan 1. When these major effect loci were included as fixed cofactors in subsequent GWAS scans 2 and 3, additional QTL and more complex genetic architectures were revealed. The multilocus model for the tropical japonica subpopulation showed that Pii/Pi3/Pi5 had significant interaction with two QTL in chromosome 1 and one QTL in chromosome 8, together explaining 64% of the phenotypic variance. In the indica subpopulation a s... Presentar Todo |
Palabras claves : |
DISEASE RESISTANCE; GWAS; LEAF BLAST; MAGNAPORTHE ORYZAE; PYRICULARIA ORYZAE; QTL BY GENETIC BACKGROUND INTERACTION; QTL by QTL INTERACTION; RESISTENCIA A ENFERMEDADES. |
Asunto categoría : |
H20 Enfermedades de las plantas |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/14870/1/agriculture-10-00622.pdf
https://www.mdpi.com/2077-0472/10/12/622
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Marc : |
LEADER 03395naa a2200325 a 4500 001 1061583 005 2021-02-08 008 2020 bl uuuu u00u1 u #d 024 7 $a10.3390/agriculture10120622$2DOI 100 1 $aROSAS, J.E. 245 $aEpistasis and quantitative resistance to Pyricularia oryzae revealed by GWAS in advanced rice breeding populations.$h[electronic resource] 260 $c2020 500 $aArticle history: Received: 30 October 2020 / Revised: 23 November 2020 / Accepted: 24 November 2020 / Published: 11 December 2020. 520 $aRice blast caused by Pyricularia oryzae is a major rice disease worldwide. Despite the detailed knowledge on major resistance genes available to date, little is known about how these genes interact with quantitative blast resistance loci and with the genetic background. Knowledge on these interactions is crucial for assessing the usefulness of introgressed resistance loci in breeding germplasm. Our goal was to identify quantitative trait loci (QTL) for blast resistance in rice breeding populations and to describe how they interact among each other and with the genetic background. To that end, resistance to blast was mapped by genome-wide association study (GWAS) in two advanced rice breeding subpopulations, one made of 305 indica type inbred lines, and the other of 245 tropical japonica inbred lines. The interactions and main effects of blast resistance loci were assessed in a multilocus model. Well known, major effect blast resistance gene clusters were detected in both tropical japonica (Pii/Pi3/Pi5) and indica (Piz/Pi2/Pi9) subpopulations with the GWAS scan 1. When these major effect loci were included as fixed cofactors in subsequent GWAS scans 2 and 3, additional QTL and more complex genetic architectures were revealed. The multilocus model for the tropical japonica subpopulation showed that Pii/Pi3/Pi5 had significant interaction with two QTL in chromosome 1 and one QTL in chromosome 8, together explaining 64% of the phenotypic variance. In the indica subpopulation a significant interaction among the QTL in chromosomes 6 and 4 and the genetic background, together with Piz/Pi2/Pi9 and QTL in chromosomes 1, 4 and 7, explained 35% of the phenotypic variance. Our results suggest that epistatic interactions can play a major role modulating the response mediated by major effect blast resistance loci such as Pii/Pi3/Pi5. Furthermore, the additive and epistatic effects of multiple QTL bring additional layers of quantitative resistance with a magnitude comparable to that of major effect loci. These findings highlight the need of genetic background-specific validation of markers for molecular assisted blast resistance breeding and provide insights for developing quantitative resistance to blast disease in rice. 653 $aDISEASE RESISTANCE 653 $aGWAS 653 $aLEAF BLAST 653 $aMAGNAPORTHE ORYZAE 653 $aPYRICULARIA ORYZAE 653 $aQTL BY GENETIC BACKGROUND INTERACTION 653 $aQTL by QTL INTERACTION 653 $aRESISTENCIA A ENFERMEDADES 700 1 $aESCOBAR, M. 700 1 $aMARTÍNEZ, S. 700 1 $aBLANCO, P.H. 700 1 $aPÉREZ DE VIDA, F. 700 1 $aQUERO, G. 700 1 $aGUTIÉRREZ, L. 700 1 $aBONNECARRERE, V. 773 $tAgriculture 2020, 10(12), 622. Open Access. DOI: https://doi.org/10.3390/agriculture10120622
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