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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha : |
21/02/2014 |
Actualizado : |
15/10/2019 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Autor : |
AGUILAR, I.; MISZTAL, I.; JOHNSON, D.L.; LEGARRA, A.; TSURUTA, S.; LAWLOR, T.J. |
Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; I. MISZTAL, University of Georgia (US); D.L. JOHNSON, Livestock Improvement Corp. (NZ); A. LEGARRA, INRA (FR); S. TSURUTA, University of Georgia (US); T.J. LAWLOR, Holstein Association USA Inc. (US). |
Título : |
Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. |
Fecha de publicación : |
2010 |
Fuente / Imprenta : |
Journal of Dairy Science, 2010, v. 93, no. 2, p. 743-752. OPEN ACCESS |
DOI : |
10.3168/jds.2009-2730 |
Idioma : |
Inglés |
Notas : |
Article history: Received September 14, 2009 / Accepted November 10, 2009 / Published in issue: February 2010. |
Contenido : |
ABSTRACT.
The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2. h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes.
© 2010 American Dairy Science Association. MenosABSTRACT.
The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assu... Presentar Todo |
Thesagro : |
FENOTIPOS; GANADO DE LECHE; MEJORAMIENTO GENETICO ANIMAL; PRODUCCION DE LECHE. |
Asunto categoría : |
L10 Genética y mejoramiento animal |
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/3702/1/Aguilar-I.-2010.-Jr.Dairy-Sci.v.93-p.743-752.pdf
https://www.journalofdairyscience.org/article/S0022-0302(10)71517-4/pdf
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Marc : |
LEADER 03453naa a2200253 a 4500 001 1012834 005 2019-10-15 008 2010 bl uuuu u00u1 u #d 024 7 $a10.3168/jds.2009-2730$2DOI 100 1 $aAGUILAR, I. 245 $aHot topic$bA unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score.$h[electronic resource] 260 $c2010 500 $aArticle history: Received September 14, 2009 / Accepted November 10, 2009 / Published in issue: February 2010. 520 $aABSTRACT. The first national single-step, full-information (phenotype, pedigree, and marker genotype) genetic evaluation was developed for final score of US Holsteins. Data included final scores recorded from 1955 to 2009 for 6,232,548 Holsteins cows. BovineSNP50 (Illumina, San Diego, CA) genotypes from the Cooperative Dairy DNA Repository (Beltsville, MD) were available for 6,508 bulls. Three analyses used a repeatability animal model as currently used for the national US evaluation. The first 2 analyses used final scores recorded up to 2004. The first analysis used only a pedigree-based relationship matrix. The second analysis used a relationship matrix based on both pedigree and genomic information (single-step approach). The third analysis used the complete data set and only the pedigree-based relationship matrix. The fourth analysis used predictions from the first analysis (final scores up to 2004 and only a pedigree-based relationship matrix) and prediction using a genomic based matrix to obtain genetic evaluation (multiple-step approach). Different allele frequencies were tested in construction of the genomic relationship matrix. Coefficients of determination between predictions of young bulls from parent average, single-step, and multiple-step approaches and their 2009 daughter deviations were 0.24, 0.37 to 0.41, and 0.40, respectively. The highest coefficient of determination for a single-step approach was observed when using a genomic relationship matrix with assumed allele frequencies of 0.5. Coefficients for regression of 2009 daughter deviations on parent-average, single-step, and multiple-step predictions were 0.76, 0.68 to 0.79, and 0.86, respectively, which indicated some inflation of predictions. The single-step regression coefficient could be increased up to 0.92 by scaling differences between the genomic and pedigree-based relationship matrices with little loss in accuracy of prediction. One complete evaluation took about 2. h of computing time and 2.7 gigabytes of memory. Computing times for single-step analyses were slightly longer (2%) than for pedigree-based analysis. A national single-step genetic evaluation with the pedigree relationship matrix augmented with genomic information provided genomic predictions with accuracy and bias comparable to multiple-step procedures and could account for any population or data structure. Advantages of single-step evaluations should increase in the future when animals are pre-selected on genotypes. © 2010 American Dairy Science Association. 650 $aFENOTIPOS 650 $aGANADO DE LECHE 650 $aMEJORAMIENTO GENETICO ANIMAL 650 $aPRODUCCION DE LECHE 700 1 $aMISZTAL, I. 700 1 $aJOHNSON, D.L. 700 1 $aLEGARRA, A. 700 1 $aTSURUTA, S. 700 1 $aLAWLOR, T.J. 773 $tJournal of Dairy Science, 2010$gv. 93, no. 2, p. 743-752. OPEN ACCESS
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2. | | ARCIA, P.; LÓPEZ, M.; BILLIRIS, A.; TRESSO, G.; SUBURÚ, G.; LUZARDO, C.; FIGUEREDO, V.; SANGUINETTI, M.N.; TERRA, J.A.; PÉREZ DE VIDA, F.; GONNET, D.; URAGA, R. Consolidando el trabajo en red. Arroz (ACA), 2020, v.20, no. 101, p.58-60. Proyecto financiado por ANNI "Red tecnológica del arroz: articulando producción, calidad y mercados y potenciando la sinergia de la cadena agroindustrial".Tipo: Artículos en Revistas Agropecuarias |
Biblioteca(s): INIA Treinta y Tres. |
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3. | | LÓPEZ RODRÍGUEZ, M.; ARCIA, P.; PÉREZ DE VIDA, F.; TRESSO, G.; FIGUEREDO, V.; LUZARDO, C.; GONNET, D.; URAGA, R.; SANGUINETTI, M.N.; BILLIRIS, A. Red tecnológica de arroz: grupos de calidad del arroz uruguayo. In: Terra, J. A.; Martínez, S.; Saravia, H.; Mesones, B.; Álvarez, O. (Eds.) Arroz 2020. Montevideo (UY): INIA, 2020. p. 113-116. (INIA Serie Técnica; 257)Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA Treinta y Tres. |
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4. | | LÓPEZ RODRÍGUEZ, M.; ARCIA, P.; PÉREZ DE VIDA, F.; TRESSO, G.; FIGUEREDO, V.; LUZARDO, C.; GONNET, D.; URAGA, R.; SANGUINETTI, M.N.; BILLIRIS, A. Pautas y criterios para el manejo industrial de numerosas variedades: aspectos de calidad física y sensorial. In: Terra, J. A.; Martínez, S.; Saravia, H.; Mesones, B.; Álvarez, O. (Eds.) Arroz 2020. Montevideo (UY): INIA, 2020. p. 117-120. (INIA Serie Técnica; 257)Tipo: Capítulo en Libro Técnico-Científico |
Biblioteca(s): INIA Treinta y Tres. |
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5. | | DEAMBROSI, E.; ZORRILLA DE SAN MARTÍN, G.; LAUZ, M.; TERRA, J.A.; BLANCO, P.H.; CASTILLO, J.; MÉNDEZ, R.; PÉREZ DE VIDA, F.; MACEDO, I.; URAGA, R.; GONNET, D.; ROVIRA, G.; MARELLA, M.; STIRLING, E.; ZORRILLA, H. Breaking yield barriers of uruguayan rice farmers.[Abstract]. In: Rice Technical Working Group, 37, 2018, Proceedings. Long Beach, California (USA): Rice Technical Working Group, 2018. p. 126-127.Tipo: Abstracts/Resúmenes |
Biblioteca(s): INIA Treinta y Tres. |
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Registros recuperados : 5 | |
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