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 | Acceso al texto completo restringido a Biblioteca INIA Las Brujas. Por información adicional contacte bibliolb@inia.org.uy. |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
11/09/2014 |
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Actualizado : |
30/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
LOURENCO, D.A.L.; MISZTAL, I.; WANG, H.; AGUILAR, I.; TSURUTA, S.; BERTRAND, J.K. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, Instituto Nacional de Investigación Agropecuaria (INIA), Uruguay. |
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Título : |
Prediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models. |
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Fecha de publicación : |
2013 |
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Fuente / Imprenta : |
Journal of Animal Science, 2013, v.91, no.9, p.4090-4098. |
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ISSN : |
0021-8812 |
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DOI : |
10.2527/jas.2012-5826 |
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Idioma : |
Inglés |
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Notas : |
Article history: Published online July 26, 2013.
This study was partially funded by the American Angus Association (St. Joseph, MO) and the USDA Agriculture and Food Research Initiative (Grant no. 2009-65205-05665 from the USDA National Institute of Food and Agriculture Animal Genome Program). Helpful comments and suggestions from W. M. Snelling (U.S. Meat Animal Research Center, ARS, USDA, Clay Center, NE) and two anonymous reviewers are gratefully acknowledged. |
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Contenido : |
ABSTRACT.
Different methods for genomic evaluation were compared for accuracy and feasibility of evaluation using phenotypic, pedigree, and genomic information for a trait influenced by a maternal effect. A simulated population was constructed that included 15,800 animals in 5 generations. Genotypes from 45,000 SNP were available for 1,500 animals in the last 3 generations. Genotyped animals in the last generation had no phenotypes. Weaning weight data were simulated using an animal model with direct and maternal effects. Additive direct and maternal effects were considered either noncorrelated (Graphic) or negatively correlated (Graphic). Methods of analysis were traditional BLUP, BayesC using phenotypes and ignoring maternal effects (BayesCPR), BayesC using deregressed EBV (BayesCDEBV), and single-step genomic BLUP (ssGBLUP). Whereas BayesCPR can be used when phenotypes of only genotyped animals are available, BayesCDEBV can be used when BLUP EBV of genotyped animals are available, and ssGBLUP is suitable when genotypes, phenotypes, and pedigrees are jointly available. For all genotyped and young genotyped animals, mean accuracies from BayesCPR and BayesCDEBV were lower than accuracies from BLUP for direct and maternal effects. The differences in mean accuracy were greater when genetic correlation was negative. Gains in accuracy were observed when ssGBLUP was compared with BLUP; for the direct (maternal) effect the average gain was 0.01 (0.02) for all genotyped animals and 0.03 (0.02) for young genotyped animals without phenotypes. Similar gains were observed for 0 and negative genetic correlation. Accuracy with BayesCPR was affected by ignoring phenotypes of nongenotyped animals and maternal effect and by not accounting for parent average. Accuracy with BayesCDEBV was affected by approximations needed for deregression, not accounting for parent average, and sequential rather than simultaneous fitting of genomic and nongenomic information. Whereas BayesCDEBV presented a considerable bias, especially for maternal effect, ssGBLUP was unbiased for both effects. The computing time was 1 s for BLUP, 44 s for ssGBLUP, and over 2,000 s for BayesC. Greatest computational efficiency and accuracy of genomic prediction for a maternally affected trait was obtained when information from all nongenotyped but related individuals was included and phenotypes, pedigree, and genotypes were available and considered jointly. Increasing the gain in accuracy of genomic predictions obtained by ssGBLUP over BLUP may require an increase in the number of genotyped animals. MenosABSTRACT.
Different methods for genomic evaluation were compared for accuracy and feasibility of evaluation using phenotypic, pedigree, and genomic information for a trait influenced by a maternal effect. A simulated population was constructed that included 15,800 animals in 5 generations. Genotypes from 45,000 SNP were available for 1,500 animals in the last 3 generations. Genotyped animals in the last generation had no phenotypes. Weaning weight data were simulated using an animal model with direct and maternal effects. Additive direct and maternal effects were considered either noncorrelated (Graphic) or negatively correlated (Graphic). Methods of analysis were traditional BLUP, BayesC using phenotypes and ignoring maternal effects (BayesCPR), BayesC using deregressed EBV (BayesCDEBV), and single-step genomic BLUP (ssGBLUP). Whereas BayesCPR can be used when phenotypes of only genotyped animals are available, BayesCDEBV can be used when BLUP EBV of genotyped animals are available, and ssGBLUP is suitable when genotypes, phenotypes, and pedigrees are jointly available. For all genotyped and young genotyped animals, mean accuracies from BayesCPR and BayesCDEBV were lower than accuracies from BLUP for direct and maternal effects. The differences in mean accuracy were greater when genetic correlation was negative. Gains in accuracy were observed when ssGBLUP was compared with BLUP; for the direct (maternal) effect the average gain was 0.01 (0.02) for all genotyped animals an... Presentar Todo |
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Thesagro : |
GANADERÍA; GANADO DE CARNE; MEJORAMIENTO GENÉTICO ANIMAL; MODELOS DE SIMULACIÓN; SELECCIÓN GENÓMICA. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
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008 2013 bl uuuu u00u1 u #d
022 $a0021-8812
024 7 $a10.2527/jas.2012-5826$2DOI
100 1 $aLOURENCO, D.A.L.
245 $aPrediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models.$h[electronic resource]
260 $c2013
500 $aArticle history: Published online July 26, 2013. This study was partially funded by the American Angus Association (St. Joseph, MO) and the USDA Agriculture and Food Research Initiative (Grant no. 2009-65205-05665 from the USDA National Institute of Food and Agriculture Animal Genome Program). Helpful comments and suggestions from W. M. Snelling (U.S. Meat Animal Research Center, ARS, USDA, Clay Center, NE) and two anonymous reviewers are gratefully acknowledged.
520 $aABSTRACT. Different methods for genomic evaluation were compared for accuracy and feasibility of evaluation using phenotypic, pedigree, and genomic information for a trait influenced by a maternal effect. A simulated population was constructed that included 15,800 animals in 5 generations. Genotypes from 45,000 SNP were available for 1,500 animals in the last 3 generations. Genotyped animals in the last generation had no phenotypes. Weaning weight data were simulated using an animal model with direct and maternal effects. Additive direct and maternal effects were considered either noncorrelated (Graphic) or negatively correlated (Graphic). Methods of analysis were traditional BLUP, BayesC using phenotypes and ignoring maternal effects (BayesCPR), BayesC using deregressed EBV (BayesCDEBV), and single-step genomic BLUP (ssGBLUP). Whereas BayesCPR can be used when phenotypes of only genotyped animals are available, BayesCDEBV can be used when BLUP EBV of genotyped animals are available, and ssGBLUP is suitable when genotypes, phenotypes, and pedigrees are jointly available. For all genotyped and young genotyped animals, mean accuracies from BayesCPR and BayesCDEBV were lower than accuracies from BLUP for direct and maternal effects. The differences in mean accuracy were greater when genetic correlation was negative. Gains in accuracy were observed when ssGBLUP was compared with BLUP; for the direct (maternal) effect the average gain was 0.01 (0.02) for all genotyped animals and 0.03 (0.02) for young genotyped animals without phenotypes. Similar gains were observed for 0 and negative genetic correlation. Accuracy with BayesCPR was affected by ignoring phenotypes of nongenotyped animals and maternal effect and by not accounting for parent average. Accuracy with BayesCDEBV was affected by approximations needed for deregression, not accounting for parent average, and sequential rather than simultaneous fitting of genomic and nongenomic information. Whereas BayesCDEBV presented a considerable bias, especially for maternal effect, ssGBLUP was unbiased for both effects. The computing time was 1 s for BLUP, 44 s for ssGBLUP, and over 2,000 s for BayesC. Greatest computational efficiency and accuracy of genomic prediction for a maternally affected trait was obtained when information from all nongenotyped but related individuals was included and phenotypes, pedigree, and genotypes were available and considered jointly. Increasing the gain in accuracy of genomic predictions obtained by ssGBLUP over BLUP may require an increase in the number of genotyped animals.
650 $aGANADERÍA
650 $aGANADO DE CARNE
650 $aMEJORAMIENTO GENÉTICO ANIMAL
650 $aMODELOS DE SIMULACIÓN
650 $aSELECCIÓN GENÓMICA
700 1 $aMISZTAL, I.
700 1 $aWANG, H.
700 1 $aAGUILAR, I.
700 1 $aTSURUTA, S.
700 1 $aBERTRAND, J.K.
773 $tJournal of Animal Science, 2013$gv.91, no.9, p.4090-4098.
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INIA Las Brujas (LB) |
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| 129. |  | CIAPPESONI, G.; GIMENO, D.; RAVAGNOLO, O.; DE BARBIERI, I.; AGUILAR, I.; MONTOSSI, F.; GRATTAROLA, M. Evaluación genética preliminar del Núcleo Fundacional Merino Fino: análisis combinado población Merino fino - generación 2003. ln: INIA Tacuarembó. Sociedad Criadores Merino Australiano del Uruguay. SUL. Proyecto Merino Fino del Uruguay: quinta distribución de carneros generados en el núcleo fundacional de merino fino de la Unidad Experimental Glencoe, INIA Tacuarembó, 1999 - 2004. Glencoe, Paysandú, 10 diciembre, 2004. Tacuarembó (Uruguay): INIA, 2004. p. 69-83 (INIA Serie Actividades de Difusión ; 392)| Biblioteca(s): INIA Tacuarembó. |
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| 131. | | MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LEGARRA, A.; VAN RADEN, P.M.; LAWLOR, T.J. Methods to approximate reliabilities in single-step genomic evaluation. Journal of Dairy Science, 2013, v.96, no.1, p.647-654. OPEN ACCESS. Article history: Received April 24, 2012. / Accepted September 18, 2012.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
| Biblioteca(s): INIA Las Brujas. |
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| 132. | | AGUILAR, I.; MISZTAL, I.; JOHNSON, D.L.; LEGARRA, A.; TSURUTA, S.; LAWLOR, T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 2010, v. 93, no. 2, p. 743-752. OPEN ACCESS Article history: Received September 14, 2009 / Accepted November 10, 2009 / Published in issue: February 2010.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : A - 1 |
| Biblioteca(s): INIA Las Brujas. |
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| 133. | | MISZTAL, I.; LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; CESARANI, A.; LEGARRA, A. How ssGBLUP became suitable for national dairy cattle evaluations. [668]. Part 37 - Bovine dairy - genetic evaluation methods. In: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_668 2757-2760. Article history: Published online: February 9, 2023 -- Corresponding author: I. Misztal, email: ignacy@uga.edu| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 135. | | TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; LEGARRA, A.; LAWLOR, T. J. Multiple trait genetic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Volume Genetic improvement programmes: Selection using molecular information - Poster Sessions, 0489. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0489.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 137. | | MACEDO, F.; NAVAJAS, E.; AGUILAR, I.; GRASSO, A.; PIERUCCIONI, F.; CIAPPESONI, G. New parentage testing SNP panel for commercial breeds will be a useful tool for conservation of creole sheep. Volume Genetic Improvement Programs: Selection for harsh environments and management of animal genetic resources (Posters), , 441. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p. 441. 3 p.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 138. | | LADO, B.; VÁZQUEZ, D.; QUINCKE, M.; SILVA, P.; AGUILAR, I.; GUTIÉRREZ, L. Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article]. Theoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS. Article history: Received: 29 January 2018 / Accepted: 10 September 2018 / Published online: 19 September 2018.
Supplementary materials.
Acknowledgements: We express our appreciation for the effort of the technical personnel of INIA La...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 139. | | CIAPPESONI, G.; NAVAJAS, E.; BAPTISTA, R.; AGUILAR, I.; PERAZA, P.; CARRACELAS, B.; DE BARBIERI, I. Proyecto SMARTER. INIA ya está en el Mundial de la Genética Ovina. Producción Animal. Revista INIA Uruguay, Marzo 2022, no.68, p.15-18. (Revista INIA; 68).| Tipo: Artículos en Revistas Agropecuarias |
| Biblioteca(s): INIA Las Brujas. |
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| 140. | | LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; LEGARRA, A.; MISZTAL, I. Recent updates in the BLUPF90 software suite. [366]. Part 19 - Methods and tools: software and computing strategies. In: Proceedings of the World Congress on Genetics Applied to Livestock Production (WCGALP), 12., Rotterdam, the Netherlands, 3-8 July 2022. doi: https://doi.org/10.3920/978-90-8686-940-4_366 1530-1533. Article history: Published online: February 9, 2023. -- Corresponding author: D. Lourenco, email: danilino@uga.edu| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 217 | |
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