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Registro completo
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Biblioteca (s) : |
INIA Las Brujas; INIA Treinta y Tres. |
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Fecha : |
12/03/2019 |
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Actualizado : |
12/03/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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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. |
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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. |
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Título : |
Genome-wide association study using historical breeding populations discovers genomic regions involved in high-quality rice. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Plant Genome, 2018, Volume 11, Article number 170076. Open Access. |
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ISSN : |
1940-3372 |
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DOI : |
10.3835/plantgenome2017.08.0076 |
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Idioma : |
Inglés |
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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. |
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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 |
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Palabras claves : |
FOOD GRAIN; GENETIC SELECTION; GENETIC VARIATION; GENETICS; MILLED RICE; PLANT BREEDING. |
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Thesagro : |
ORYZA SATIVA; RICE. |
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Asunto categoría : |
F01 Cultivo |
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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
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Marc : |
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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.
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