Título : Boosting INIA’s Rice Breeding Program with Molecular and Quantitative Genetics Approaches
Autor(es) : Rosas, Juan Eduardo
Ale, Lucas
Rebollo, Inés
Scheffel, Sheila
Aguilar, Ignacio
Molina, Federico
Pérez, Fernando
Fecha de publicación : 9-feb-2020
Tipo de publicación: Otro
Areas del conocimiento : Ciencias Naturales y Exactas
Ciencias Biológicas
Genética y Herencia
Ciencias Agrícolas
Biotecnología Agropecuaria
Tecnología GM, clonación de ganado, selección asistida, diagnósticos, etc.
Agricultura, Silvicultura y Pesca
Agronomía, reproducción y protección de plantas
Otros descriptores : breeding
MAS
GWAS
Genomic selection
Resumen : As a major rice exporter, Uruguay must maximize its competitivity with higher yield, quality and innocuity, and lower inputs, in an increasingly instable environment. To timely meet these needs, INIA’s public rice breeding program (IRBP) is optimizing its cultivar development pipeline by incorporating molecular and quantitative genetics approaches that will enable to increase the selection accuracy and intensity, and to shorten the breeding cycle. Different strategies are applied depending on the complexity of the target trait in the breeding germplasm: 1) molecular assisted selection (MAS) for screening and introgression of valuable alleles for oligogenic traits, for increasing selection intensity and reducing population size for field trials; 2) genome-wide association studies (GWAS) for traits with unknow genetic architecture in our germplasm; and 3) mixed models integrating pedigree, genomic, and weather data for prediction complex traits under favorable and unfavorable environments for increasing selection accuracy. For MAS, SNP markers have been validated and applied for blast resistance, herbicide tolerance, amylose content and fragrance. GWAS were performed in indica and tropical japonica advanced breeding germplasm for arsenic grain content, tolerance to low temperature at vegetative and reproductive stages, and quantitative blast resistance. Several new and known QTL were discovered in the IRBP germplasm, and the usefulness of MAS for these traits was assessed. Finally, prediction of breeding value for yield is being implemented combining historic phenotypic and pedigree records with environmental data. First analyses of multi-year and multi-location analyses are showing promising results for increasing selection accuracy and characterizing genotype by environment interactions. Combined, these molecular and quantitative approaches are contributing to optimize the IRBP, and will accelerate the delivery of best cultivars for Uruguayan rice farmers.
URI / Handle: https://hdl.handle.net/20.500.12381/451
ISBN: 978-65-00-00331-4
URL : http://www.ainfo.inia.uy/digital/bitstream/item/14248/1/IRTC-2020-Rosas-1-Abstract.pdf
Institución responsable del proyecto: INIA
Financiadores: Instituto Nacional de Investigación Agropecuaria
Agencia Nacional de Investigación e Innovación
Identificador ANII: FSDA_1_2018_1_154120
Nivel de Acceso: Acceso abierto
Licencia CC: Reconocimiento 4.0 Internacional. (CC BY)
Aparece en las colecciones: Publicaciones de ANII

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