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| Registros recuperados : 6 | |
| 2. |  | ESTEVES, P.; MASTROPIERRO, M.M.; CASTILLO, A.; DALLA RIZZA, M.; BELZILE, F.; HERNANDEZ, L.; QUINCKE, M. Métodos para aumentar la eficiencia del mejoramiento de trigo. In: CONGRESO NACIONAL DE TRIGO, 8o. ; SIMPOSIO DE CEREALES DE SIEMBRA OTOÑO INVERNAL, 6o. ; ENCUENTRO DEL MERCOSUR, 2º, Pergamino, Argentina: AIANBA, 14-16 setiembre,2016.| Biblioteca(s): INIA La Estanzuela. |
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| 3. | | ESTEVES, P.; MURCHIO, S.; CEPPA, M.; BONILLA, B.; DIEPPA, D.; CASTILLO, A.; DALLA RIZZA, M. Puesta en marcha del Proyecto: Producción de Haploides-duplicados de arroz, trigo y cebada. In: INIA (Instituto Nacional de Investigación Agropecuaria); Inia Las Brujas; Biotecnología. Apostando a la investigación para un futuro innovador. Jornada de Agrobiotecnología, IX. Jornada Técnica. Canelones (Uruguay): INIA , 2015. p. 17-19 (Actividades de Difusión; 755)| Biblioteca(s): INIA Las Brujas. |
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| 4. | | GALLINO, J. P.; CASTILLO, A.; CERETTA, S.; ESTEVES, P.; BONNECARRERE, V. A simple and inexpensive procedure to more quickly obtain new varieties in soybean. Crop Breeding and Applied Biotechnology, 2022, volume 22, Issue 1, e38212216. OPEN ACCESS. doi: https://doi.org/10.1590/1984-70332022v22n1a06 Article history: Received 24 May 2021; Accepted 12 Aug 2021; Published 30 Mar 2022; Publication in this collection 04 May 2022; Date of issue 2022.
Corresponding author: Gallino, J.P.; INIA, Estación Experimental "Wilson Ferreira...| Biblioteca(s): INIA Las Brujas. |
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| 5. | | ESTEVES, P.; HERNANDEZ, L.; CASTILLO, A.; DALLA RIZZA, M.; QUINCKE, M. Tecnologías para el desarrollo de líneas recombinantes de trigo. MV 20 - 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. 290| Biblioteca(s): INIA Las Brujas. |
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| 6. | | ESTEVES, P.; MASTROPIERRO, M.; CASTILLO, A.; HERNANDEZ, L.; RODRIGUEZ, M.; DE LEON, W.; PEREIRA, F.; QUINCKE, M. Herramientas biotecnológicas para el mejoramiento genético de cultivos. Revista INIA Uruguay, 2017, no.48, p. 62-66. (Revista INIA; 48)| Biblioteca(s): INIA Las Brujas; INIA Tacuarembó. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
15/11/2015 |
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Actualizado : |
09/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
B - 2 |
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Autor : |
FRAGOMENI, B.O.; MISZTAL, I.; LOURENCO, D.L.; AGUILAR, I.; OKIMOTO, R.; MUIR, W.M. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Changes in variance explained by top SNP windows over generations for three traits in broiler chicken |
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Fecha de publicación : |
2014 |
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Fuente / Imprenta : |
Frontiers in Genetics, 2014, v.5, no.Oct., Article number 332. OPEN ACCESS. |
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ISSN : |
1664-8021 |
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DOI : |
10.3389/fgene.2014.00332 |
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Idioma : |
Inglés |
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Notas : |
Article history: Published 01 October 2014. |
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Contenido : |
ABSTRACT.
The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.
© 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and Muir. MenosABSTRACT.
The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated.
© 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and... Presentar Todo |
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Palabras claves : |
Gene identification; Genome-wide association study; Genomic selection; QTL; SsGBLUP. |
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Thesagro : |
MEJORAMIENTO GENETICO ANIMAL; POLLO DE ENGORDE. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/5195/1/Aguilar-I.-2014.-Frontiers-in-Genetics.pdf
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Marc : |
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100 1 $aFRAGOMENI, B.O.
245 $aChanges in variance explained by top SNP windows over generations for three traits in broiler chicken$h[electronic resource]
260 $c2014
500 $aArticle history: Published 01 October 2014.
520 $aABSTRACT. The purpose of this study was to determine if the set of genomic regions inferred as accounting for the majority of genetic variation in quantitative traits remain stable over multiple generations of selection. The data set contained phenotypes for five generations of broiler chicken for body weight, breast meat, and leg score. The population consisted of 294,632 animals over five generations and also included genotypes of 41,036 single nucleotide polymorphism (SNP) for 4,866 animals, after quality control. The SNP effects were calculated by a GWAS type analysis using single step genomic BLUP approach for generations 1-3, 2-4, 3-5, and 1-5. Variances were calculated for windows of 20 SNP. The top ten windows for each trait that explained the largest fraction of the genetic variance across generations were examined. Across generations, the top 10 windows explained more than 0.5% but less than 1% of the total variance. Also, the pattern of the windows was not consistent across generations. The windows that explained the greatest variance changed greatly among the combinations of generations, with a few exceptions. In many cases, a window identified as top for one combination, explained less than 0.1% for the other combinations. We conclude that identification of top SNP windows for a population may have little predictive power for genetic selection in the following generations for the traits here evaluated. © 2014 Fragomeni, Misztal, Lourenco, Aguilar, Okimoto and Muir.
650 $aMEJORAMIENTO GENETICO ANIMAL
650 $aPOLLO DE ENGORDE
653 $aGene identification
653 $aGenome-wide association study
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653 $aSsGBLUP
700 1 $aMISZTAL, I.
700 1 $aLOURENCO, D.L.
700 1 $aAGUILAR, I.
700 1 $aOKIMOTO, R.
700 1 $aMUIR, W.M.
773 $tFrontiers in Genetics, 2014$gv.5, no.Oct., Article number 332. OPEN ACCESS.
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