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| Registros recuperados : 81 | |
| 21. |  | BERMANN, M.; MISZTAL, I.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A. Definition of reliabilities for models with metafounders. [289] Part 17 - Challenges - improving genomic prediction. 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_289 1217-1220. Article history: Published online: February 9, 2023. -- Corresponding author: A. Legarra, email: andres.legarra@inrae.fr -- Acknowledgment: This work received financing from European Unions' Horizon 2020 Research & Innovation Programme,...| Biblioteca(s): INIA Las Brujas. |
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| 24. | | TSURUTA, S.; MISZTAL, I.; AGUILAR, I.; LAWLOR, T. J. Genome wide association study on cow mortality in three US regions. Volume Species Breeding: Dairy cattle (Posters), 805. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.805.| Biblioteca(s): INIA Las Brujas. |
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| 25. | | FORNI, S.; AGUILAR, I.; MISZTAL, I.; DEEB, N. Genomic relationships and biases in the evaluation of sow litter size. Volume Genetic improvement programmes: Selection using molecular information - Poster Sessions, 0506. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0506.| Biblioteca(s): INIA Las Brujas. |
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| 28. | | DE MATTOS, D.; BERTAND, J.K.; MISZTAL, I. Investigation of genotype × environment interactions for weaning weight for Herefords in three countries. Journal of Animal Science, August, v. 78, no. 8, p. 2121-2126, 2000. Article history: Received September 16, 1999 // Accepted April 3, 2000.| Biblioteca(s): INIA Tacuarembó. |
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| 29. | | TSURUTA, S.; MISZTAL, I.; AGUILAR, I.; LAWLOR, T.J. Multiple-trait genomic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Journal of Dairy Science, 2011, v.94, no.8, p.4198-4204. OPEN ACCESS. Article history: Received February 9, 2011. / Accepted April 8, 2011.| Biblioteca(s): INIA Las Brujas. |
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| 30. | | AGUILAR, I.; MISZTAL, I.; TSURUTA, S.; LEGARRA, A.; WANG, H. PREGSF90 - POSTGSF90: Computational tools for the implementation of single-step genomic selection and genome-wide association with ungenotyped individuals in BLUPF90 programs. Volume Methods and Tools: Statistical and genomic tools for mapping QTL and genes (Posters), 680. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.680.| Biblioteca(s): INIA Las Brujas. |
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| 31. | | BERMANN, M.; AGUILAR, I.; LOURENCO , D.; MISZTAL, I.; LEGARRA, A. Reliabilities of estimated breeding values in models with metafounders. Research article. Genetics, Selection, Evolution : GSE, 2023, volume55, issue 1, article 6. OPEN ACCESS. doi: https://doi.org/10.1186/s12711-023-00778-2 Article history: Received 29 June 2022; Accepted 04 January 2023; Published 23 January 2023. -- Corresponding author: Matias Bermann, Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA, email: mbermann@uga.edu...| Biblioteca(s): INIA Las Brujas. |
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| 33. | | MASUDA, Y.; AGUILAR, I.; TSURUTA, S.; MISZTAL, I. Technical note: Acceleration of sparse operations for average-information REML analyses with supernodal methods and sparse-storage refinements. Journal of Animal Science, 2015, v. 93, p. 4670 - 4674. Published October 9, 2015 Article history: Received June 8, 2015.; Accepted August 7, 2015.
1. We acknowledge the work by François Guillaume in programming a hash function. We greatly appreciate the work of the two anonymous reviewers.
2. The AIREMLF90 program...| Biblioteca(s): INIA Las Brujas. |
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| 34. | | DE MATTOS, D.; MISZTAL, I.; BERTRAND, J. K. Variance and covariance components for weaning weight for Herefords in three countries. Journal of Animal Science, January 2000, volume 78, Issue 1, pages 33-37. OPEN ACCESS. Article history: Received January 19, 1999. // Accepted August 8, 1999.
Research was funded by the American Hereford Assoc., Kansas City, MO; Canadian Hereford Assoc., Calgary, Alberta, Canada; and Instituto Nacional de Investigacion...| Biblioteca(s): INIA Las Brujas. |
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| 35. | | ZHANG, X.; LOURENCO, D.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A. Weighted single-step genomic BLUP: an iterative approach for accurate calculation of GEBV and GWAS. Volume Methods and Tools: Statistical and genomic tools for mapping QTL and genes (Posters), 681. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.681.| Biblioteca(s): INIA Las Brujas. |
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| 36. | | ZHANG, X.; LOURENCO, D.; AGUILAR, I.; LEGARRA, A.; MISZTAL, I. Weighting strategies for single-step genomic BLUP: An iterative approach for accurate calculation of GEBV and GWAS. Frontiers in Genetics, 19 August 2016, Volume 7, Issue AUG, Article number 151. OPEN ACCESS Article history: Received 15 May 2016 // Accepted 04 August 2016 // Published 19 August 2016.
Specialty section:
This article was submitted to Statistical Genetics and Methodology, a section of the journal Frontiers in Genetics.| Biblioteca(s): INIA Las Brujas. |
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| 38. | | LOURENCO, D; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LAWLOR, T. J.; WELLER, J. I. Are evaluations on young genotyped dairy bulls benefiting from the past generations? [conference paper]. Volume Species Breeding: Dairy cattle, 297. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.297.| Biblioteca(s): INIA Las Brujas. |
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| 40. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Accuracy of indirect predictions for large datasets based on prediction error covariance of SNP effects from single-step GBLUP. [abstract 22]. Issue Section: Animal Breeding and Genetics. Journal of Animal Science, 2020, Volume 98, Issue Supplement 4, Pages 6-7. doi: https://doi.org/10.1093/jas/skaa278.012 Article history: 30 November 2020.
ASAS Annual 2020 Meeting Abstracts.| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 81 | |
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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 actual : |
21/02/2014 |
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Actualizado : |
13/12/2018 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
A - 1 |
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Autor : |
SÁNCHEZ, J. P.; MISZTAL, I.; AGUILAR, I.; BERTRAND, J. K. |
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Afiliación : |
J. P. SÁNCHEZ, Animal and Dairy Science Department, University of Georgia, United States; Departamento de Producción Animal, Facultad de Veterinaria, Universidad de León, Spain; I. MISZTAL, Animal and Dairy Science Department, University of Georgia, United States; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; J. K. BERTRAND, Animal and Dairy Science Department, University of Georgia, United States. |
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Título : |
Genetic evaluation of growth in a multibreed beef cattle population using random regression-linear spline models. |
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Fecha de publicación : |
2008 |
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Fuente / Imprenta : |
Journal of Animal Science, 2008, 86 (2): 267-277. |
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ISSN : |
0021-8812 |
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DOI : |
10.2527/jas.2007-0064 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received January 24, 2007. // Accepted October 2, 2007. |
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Contenido : |
ABSTRACT.
The objective of this study was to examine the feasibility of using random regression-spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the results from the RR-spline model were compared with the widely used multitrait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals) provided by the American Gelbvieh Association. The effect of prior information on the EBV of sires was also investigated. In both RR-spline and MT models, the following effects were considered: individual direct and maternal additive genetic effects, contemporary group, age of the animal at measurement, direct and maternal heterosis, and direct and maternal additive genetic mean effect of the breed. Additionally, the RR-spline model included an individual direct permanent environmental effect. When both MT and RR-spline models were applied to a data set containing records for weaning weight (WWT) and yearling weight (YWT) within specified age ranges, the rankings of bulls' direct EBV (as measured via Pearson correlations) provided by both models were comparable, with slightly greater differences in the reranking of bulls observed for YWT evaluations (≥0.99 for BWT and WWT and ≥0.98 for YWT); also, some bulls dropped from the top 100 list when these lists were compared across methods. For maternal effects, the estimated correlations were slightly smaller, particularly for YWT; again, some drops from the top 100 animals were observed. As in regular MT multibreed genetic evaluations, the heterosis effects and the additive genetic effects of the breed could not be estimated from field data, because there were not enough contemporary groups with the proper composition of purebred and crossbred animals; thus, prior information based on literature values had to be included. The inclusion of prior information had a negligible effect in the overall ranking for bulls with greater than 20 birth weight progeny records; however, the effect of prior information for breeds or groups poorly represented in the data was important. The Pearson correlations for direct and maternal WWT and YWT ranged from 0.95 to 0.98 when comparing evaluations of data sets for which the out-of-range age records were removed or retained. Random regression allows for avoiding the discarding of records that are outside the usual age ranges of measurement; thus, greater accuracies are achieved, and greater genetic progress could be expected.
©2008 American Society of Animal Science. All rights reserved. MenosABSTRACT.
The objective of this study was to examine the feasibility of using random regression-spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the results from the RR-spline model were compared with the widely used multitrait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals) provided by the American Gelbvieh Association. The effect of prior information on the EBV of sires was also investigated. In both RR-spline and MT models, the following effects were considered: individual direct and maternal additive genetic effects, contemporary group, age of the animal at measurement, direct and maternal heterosis, and direct and maternal additive genetic mean effect of the breed. Additionally, the RR-spline model included an individual direct permanent environmental effect. When both MT and RR-spline models were applied to a data set containing records for weaning weight (WWT) and yearling weight (YWT) within specified age ranges, the rankings of bulls' direct EBV (as measured via Pearson correlations) provided by both models were comparable, with slightly greater differences in the reranking of bulls observed for YWT evaluations (≥0.99 for BWT and WWT and ≥0.98 for YWT); also, some bulls dropped from the top 100 list when these lists were compared across methods. For maternal effects, the estimated correlations were slightly smaller, particularly for YWT; again, som... Presentar Todo |
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Palabras claves : |
BEEF CATTLE; GROWTH; MULTIBREED; RANDOM REGRESSION MODEL; SPLINE. |
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Asunto categoría : |
L01 Ganadería |
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Marc : |
LEADER 03374naa a2200253 a 4500
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008 2008 bl uuuu u00u1 u #d
022 $a0021-8812
024 7 $a10.2527/jas.2007-0064$2DOI
100 1 $aSÁNCHEZ, J. P.
245 $aGenetic evaluation of growth in a multibreed beef cattle population using random regression-linear spline models.
260 $c2008
500 $aArticle history: Received January 24, 2007. // Accepted October 2, 2007.
520 $aABSTRACT. The objective of this study was to examine the feasibility of using random regression-spline (RR-spline) models for fitting growth traits in a multibreed beef cattle population. To meet the objective, the results from the RR-spline model were compared with the widely used multitrait (MT) model when both were fit to a data set (1.8 million records and 1.1 million animals) provided by the American Gelbvieh Association. The effect of prior information on the EBV of sires was also investigated. In both RR-spline and MT models, the following effects were considered: individual direct and maternal additive genetic effects, contemporary group, age of the animal at measurement, direct and maternal heterosis, and direct and maternal additive genetic mean effect of the breed. Additionally, the RR-spline model included an individual direct permanent environmental effect. When both MT and RR-spline models were applied to a data set containing records for weaning weight (WWT) and yearling weight (YWT) within specified age ranges, the rankings of bulls' direct EBV (as measured via Pearson correlations) provided by both models were comparable, with slightly greater differences in the reranking of bulls observed for YWT evaluations (≥0.99 for BWT and WWT and ≥0.98 for YWT); also, some bulls dropped from the top 100 list when these lists were compared across methods. For maternal effects, the estimated correlations were slightly smaller, particularly for YWT; again, some drops from the top 100 animals were observed. As in regular MT multibreed genetic evaluations, the heterosis effects and the additive genetic effects of the breed could not be estimated from field data, because there were not enough contemporary groups with the proper composition of purebred and crossbred animals; thus, prior information based on literature values had to be included. The inclusion of prior information had a negligible effect in the overall ranking for bulls with greater than 20 birth weight progeny records; however, the effect of prior information for breeds or groups poorly represented in the data was important. The Pearson correlations for direct and maternal WWT and YWT ranged from 0.95 to 0.98 when comparing evaluations of data sets for which the out-of-range age records were removed or retained. Random regression allows for avoiding the discarding of records that are outside the usual age ranges of measurement; thus, greater accuracies are achieved, and greater genetic progress could be expected. ©2008 American Society of Animal Science. All rights reserved.
653 $aBEEF CATTLE
653 $aGROWTH
653 $aMULTIBREED
653 $aRANDOM REGRESSION MODEL
653 $aSPLINE
700 1 $aMISZTAL, I.
700 1 $aAGUILAR, I.
700 1 $aBERTRAND, J. K.
773 $tJournal of Animal Science, 2008, 86 (2): 267-277.
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