| |
|
|
| Registros recuperados : 85 | |
| 45. |  | GARCÍA, J.A.; ROSAS, J.E.; GARCÍA Y SANTOS, C.; STREITENBERGER, N.; FEIJOO, M.; DUTRA, F. Senecio spp. transboundary introduction and expansion affecting cattle in Uruguay: clinico-pathological, epidemiological and genetic survey, and experimental intoxication with Senecio oxyphyllus. Toxicon, 15 January 2020, Volume 173, Pages 68-74. OPEN ACCESS. Doi: https://doi.org/10.1016/j.toxicon.2019.11.013 Article history: Received Date: 08 September 2019 // Accepted Date: 26 November 2019 // Available online 27 November 2019.| Biblioteca(s): INIA Treinta y Tres. |
|    |
| 49. | | DÍAZ SOLÍS, S.; PÉREZ DE VIDA, F.; ROSAS, J.E.; MOREJÓN RIVERA, R. Respuesta de diferentes líneas y cultivares de arroz sometidos a bajas temperaturas en condiciones controladas. Biotecnología Vegetal, Enero-Marzo 2017, v. 17, no. 1, p. 57-65. Historia del artículo: Recibido el 7/10/2016, aceptado el 11/11/2016, publicado Enero 2017.| Biblioteca(s): INIA Treinta y Tres. |
| |
| 50. | | ROSAS, J.E.; ALE, L.; REBOLLO, I.; SCHEFFEL, S.; AGUILAR, I.; MOLINA, F.; PÉREZ DE VIDA, F. Boosting INIA's Rice Breeding Program with molecular quantitative genetics approaches. [Abstract]. In: International Temperate Rice Conference (7., 2020, Pelotas, RS), Science & Innovation: feeding a world of 10 billion people: proceedings. Pelotas RS, Brasil, February 9-12, 2020. Brasília, DF : Embrapa, 2020.| Biblioteca(s): INIA Treinta y Tres. |
| |
| 51. | | 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. |
| |
| 52. | | REBOLLO, I.; SCHEFFEL, S.; IRIARTE, W.; BLANCO, P.H.; MOLINA, F.; PÉREZ DE VIDA, F.; ROSAS, J.E. Consolidación de los datos históricos del Programa de Mejoramiento Genético de Arroz en una base de datos. In: Terra, J. A.; Martínez, S.; Saravia, H.; Mesones, B.; Álvarez, O. (Eds.) Arroz 2020. Montevideo (UY): INIA, 2020. p. 5-8. (INIA Serie Técnica; 257)| Biblioteca(s): INIA Treinta y Tres. |
| |
| 54. | | BERBERIAN, N.; BONNECARRERE, V.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; MARTÍNEZ, S.; GUTIÉRREZ, L. Model comparison and experimental design simulation including natural field variability in rice crop (Oryza sativa L.). In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo; FAGRO, 2019. p. 14 Trabajo originalmente presentado en: Berberian, N.; Bonecarrere, V.; Blaco, P.; Pérez de Vida, F.; Rosas, J.; Martínez, S.; Gutíerrez, L. 2018. International Biometric Conference, 29. Model comparison and experimental design simulation...| Biblioteca(s): INIA Treinta y Tres. |
| |
| 55. | | REBOLLO, I.; PÉREZ DE VIDA, F.; BLANCO, P.H.; MOLINA, F.; CRUZ, M.; BONNECARRERE, V.; GARAYCOCHEA, S.; ROSAS, J.E. Mapeo asociado de tolerancia a bajas temperaturas en germoplasma avanzado de arroz. [Poster]. En: Jornadas de Investigación, Facultad de Agronomía (UdelaR), 8-9, nov. 2018, Montevideo, UY.| Biblioteca(s): INIA Treinta y Tres. |
| |
| 56. | | REBOLLO, I.; CRUZ, M.; PÉREZ DE VIDA, F.; BLANCO, P.H.; MOLINA, F.; BONNECARRERE, V.; GARAYCOCHEA, S.; ROSAS, J.E. Mapeo asociativo de tolerancia a bajas temperaturas en germoplasma avanzado de arroz. In: UNIVERSIDAD DE LA REPÚBLICA (UDELAR). FACULTAD DE AGRONOMÍA. Resúmenes. Jornadas de Investigación, 8-9 nov., 2018, Montevideo, Uruguay. Montevideo; FAGRO, 2019. p. 18| Biblioteca(s): INIA Treinta y Tres. |
| |
| 57. | | 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. |
|  |
| 58. | | REBOLLO, I.; SCHEFFEL, S.; BLANCO, P.H.; MOLINA, F.; MARTÍNEZ, S.; CARRACELAS, G.; PÉREZ DE VIDA, F.; ROSAS, J.E. Instituto Nacional de Investigación Agropecuaria (INIA) Rice Breeding Program Historical Dataset. [Dataset]. DRYAD Dataset, 2024. https://doi.org/10.5061/dryad.x69p8czn8 Correspondence author: Juan E. Rosas, email: jrosas@inia.org.uy -- Publication date: February 16, 2024. -- This dataset is embargoed and will be released when the associated article is published. Lists of files and downloads will become...| Biblioteca(s): INIA Las Brujas. |
|  |
| 59. | | 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/g3.7685636| Biblioteca(s): INIA Treinta y Tres. |
| |
| Registros recuperados : 85 | |
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
|
Fecha actual : |
12/03/2019 |
|
Actualizado : |
12/03/2019 |
|
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
|
Circulación / Nivel : |
Internacional - -- |
|
Autor : |
QUERO, G.; GUTIÉRREZ, L.; MONTEVERDE, E.; BLANCO, P.H.; PÉREZ DE VIDA, F.; ROSAS, J.E.; FERNANDEZ, S.; GARAYCOCHEA, S.; MC COUCH, S.; BERBERIAN, N.; SIMONDI, S.; BONNECARRERE, V. |
|
Afiliación : |
GASTÓN QUERO CORRALLO, Universidad de la República (UdelaR)/ Facultad de Agronomía; INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; LUCÍA GUTIÉRREZ, Dep. of Agronomy, Univ. of Wisconsin-Madison, United States.; Universidad de la República (UdelaR)/ Facultad de Agronomía; ELIANA MONTEVERDE, Dep. of Plant Breeding and Genetics, Cornell Univ., United States; PEDRO HORACIO BLANCO BARRAL, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BLAS PEREZ DE VIDA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; JUAN EDUARDO ROSAS CAISSIOLS, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SCHUBERT DANIEL FERNANDEZ REGGIARDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SILVIA RAQUEL GARAYCOCHEA SOLSONA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; SUSAN MCCOUCH, Dep. of Plant Breeding and Genetics, Cornell Univ., United States; NATALIA BERBERIAN, Universidad de la República (UdelaR)/ Facultad de Agronomía; SEBASTIÁN SIMONDI, College of Natural and Exact Sciences, Univ. Nacional de Cuyo, Argentina; MARIA VICTORIA BONNECARRERE MARTINEZ, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
|
Título : |
Genome-wide association study using historical breeding populations discovers genomic regions involved in high-quality rice. |
|
Fecha de publicación : |
2018 |
|
Fuente / Imprenta : |
Plant Genome, 2018, Volume 11, Article number 170076. Open Access. |
|
ISSN : |
1940-3372 |
|
DOI : |
10.3835/plantgenome2017.08.0076 |
|
Idioma : |
Inglés |
|
Notas : |
Article history: Received: Aug 25, 2017 // Accepted: Apr 09, 2018 // Published: July 12, 2018.
Permissions: This is an open access article under the CC BY-NC-ND license. Proper attribution is required for reuse. No permissions are needed for reuse unless it is derivative or for commercial purposes. |
|
Contenido : |
Abstract.
Rice (Oryza sativa L.) is one of the most important staple food crops in the world; however, there has recently been a shift in consumer demand for higher grain quality. Therefore, understanding the genetic architecture of grain quality has become a key objective of rice breeding programs. Genomewide association studies (GWAS) using large diversity panels have successfully identified genomic regions associated with complex traits in diverse crop species. Our main objective was to identify genomic regions associated with grain quality and to identify and characterize favorable haplotypes for selection. We used two locally adapted rice breeding populations and historical phenotypic data for three rice quality traits: yield after milling, percentage of head rice recovery, and percentage of chalky grain. We detected 22 putative quantitative trait loci (QTL) in the same genomic regions as starch synthesis, starch metabolism, and cell wall synthesis-related genes are found. Additionally, we found a genomic region on chromosome 6 in the tropical japonica population that was associated with all quality traits and we identified favorable haplotypes. Furthermorethis region is linked to the OsBEI gene that codes for a starch branching enzyme I, which is implicated in starch granule formation. In tropical japonica, we also found two putative QTL linked to OsBEII, OsDEP1, and OsDEP2. Our study provides an insight into the genetic basis of rice grain chalkiness, yield after milling, and head rice, identifying favorable haplotypes and molecular markers for selection in breeding programs.
© 2018 Crop Science Society of America MenosAbstract.
Rice (Oryza sativa L.) is one of the most important staple food crops in the world; however, there has recently been a shift in consumer demand for higher grain quality. Therefore, understanding the genetic architecture of grain quality has become a key objective of rice breeding programs. Genomewide association studies (GWAS) using large diversity panels have successfully identified genomic regions associated with complex traits in diverse crop species. Our main objective was to identify genomic regions associated with grain quality and to identify and characterize favorable haplotypes for selection. We used two locally adapted rice breeding populations and historical phenotypic data for three rice quality traits: yield after milling, percentage of head rice recovery, and percentage of chalky grain. We detected 22 putative quantitative trait loci (QTL) in the same genomic regions as starch synthesis, starch metabolism, and cell wall synthesis-related genes are found. Additionally, we found a genomic region on chromosome 6 in the tropical japonica population that was associated with all quality traits and we identified favorable haplotypes. Furthermorethis region is linked to the OsBEI gene that codes for a starch branching enzyme I, which is implicated in starch granule formation. In tropical japonica, we also found two putative QTL linked to OsBEII, OsDEP1, and OsDEP2. Our study provides an insight into the genetic basis of rice grain chalkiness, yield after mil... Presentar Todo |
|
Palabras claves : |
FOOD GRAIN; GENETIC SELECTION; GENETIC VARIATION; GENETICS; MILLED RICE; PLANT BREEDING. |
|
Thesagro : |
ORYZA SATIVA; RICE. |
|
Asunto categoría : |
F01 Cultivo |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12507/1/tpg-11-3-170076.pdf
https://dl.sciencesocieties.org/publications/tpg/abstracts/11/3/170076
|
|
Marc : |
LEADER 03044naa a2200385 a 4500
001 1059613
005 2019-03-12
008 2018 bl uuuu u00u1 u #d
022 $a1940-3372
024 7 $a10.3835/plantgenome2017.08.0076$2DOI
100 1 $aQUERO, G.
245 $aGenome-wide association study using historical breeding populations discovers genomic regions involved in high-quality rice.$h[electronic resource]
260 $c2018
500 $aArticle history: Received: Aug 25, 2017 // Accepted: Apr 09, 2018 // Published: July 12, 2018. Permissions: This is an open access article under the CC BY-NC-ND license. Proper attribution is required for reuse. No permissions are needed for reuse unless it is derivative or for commercial purposes.
520 $aAbstract. Rice (Oryza sativa L.) is one of the most important staple food crops in the world; however, there has recently been a shift in consumer demand for higher grain quality. Therefore, understanding the genetic architecture of grain quality has become a key objective of rice breeding programs. Genomewide association studies (GWAS) using large diversity panels have successfully identified genomic regions associated with complex traits in diverse crop species. Our main objective was to identify genomic regions associated with grain quality and to identify and characterize favorable haplotypes for selection. We used two locally adapted rice breeding populations and historical phenotypic data for three rice quality traits: yield after milling, percentage of head rice recovery, and percentage of chalky grain. We detected 22 putative quantitative trait loci (QTL) in the same genomic regions as starch synthesis, starch metabolism, and cell wall synthesis-related genes are found. Additionally, we found a genomic region on chromosome 6 in the tropical japonica population that was associated with all quality traits and we identified favorable haplotypes. Furthermorethis region is linked to the OsBEI gene that codes for a starch branching enzyme I, which is implicated in starch granule formation. In tropical japonica, we also found two putative QTL linked to OsBEII, OsDEP1, and OsDEP2. Our study provides an insight into the genetic basis of rice grain chalkiness, yield after milling, and head rice, identifying favorable haplotypes and molecular markers for selection in breeding programs. © 2018 Crop Science Society of America
650 $aORYZA SATIVA
650 $aRICE
653 $aFOOD GRAIN
653 $aGENETIC SELECTION
653 $aGENETIC VARIATION
653 $aGENETICS
653 $aMILLED RICE
653 $aPLANT BREEDING
700 1 $aGUTIÉRREZ, L.
700 1 $aMONTEVERDE, E.
700 1 $aBLANCO, P.H.
700 1 $aPÉREZ DE VIDA, F.
700 1 $aROSAS, J.E.
700 1 $aFERNANDEZ, S.
700 1 $aGARAYCOCHEA, S.
700 1 $aMC COUCH, S.
700 1 $aBERBERIAN, N.
700 1 $aSIMONDI, S.
700 1 $aBONNECARRERE, V.
773 $tPlant Genome, 2018, Volume 11, Article number 170076. Open Access.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
