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| Registros recuperados : 224 | |
| 201. |  | NAVAJAS, E.; PRAVIA, M.I.; LEMA, O.M.; CLARIGET, J.M.; AGUILAR, I.; RAVAGNOLO, O.; BRITO, G.; PERAZA, P.; DALLA RIZZA, M.; MONTOSSI, F. Genetic improvement of feed efficiency and carcass and meat quality of hereford cattle by genomics. In: INTERNATIONAL CONGRESS OF MEAT SCIENCE AND TECHNOLOGY, 60., 2014, Punta del Este, Uruguay: ICOMST. Oral Poster Presentation :Sessions I and II: 2 Posters.| Biblioteca(s): INIA La Estanzuela; INIA Tacuarembó. |
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| 202. | | NAVAJAS, E.; RAVAGNOLO, O.; DE BARBIERI, I.; PRAVIA, M.I.; AGUILAR, I.; LEMA, O.M.; VERA, B.; PERAZA, P.; MARQUES, C. B.; VELAZCO, J.I.; CIAPPESONI, G. Genetic selection of feed efficiency and methane emissions in sheep and cattle in Uruguay: progress and limitations. [29] Part 5 - Novel traits: environment and greenhouse gas- 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_29 164-167. Article history: Published online: February 9, 2023. -- Corresponding author: E.A. Navajas, email: enavajas@inia.org.uy -- Acknowledgements: The authors acknowledge the funding organizations INIA, Agencia Nacional de Investigación e...| Biblioteca(s): INIA Las Brujas. |
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| 203. | | MOTA, R. R.; LOPES, P. S.; TEMPELMAN, R. J.; SILVA, F. F.; AGUILAR, I.; GOMES, C. C. G.; CARDOSO, F. F. Genome-enabled prediction for tick resistance in Hereford and Braford beef cattle via reaction norm models. Journal of Animal Science, May 2016, Volume 94, Issue 5, Pages 1834 - 1843. Article history: Received December 11, 2015. // Accepted March 10, 2016.| Biblioteca(s): INIA Las Brujas. |
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| 204. | | WANG, H.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A.; FERNANDO, R.L.; VITEZICA, Z.; OKIMOTO, R.; WING, T.; HAWKEN, R.; MUIR, W.M. Genome-wide association mapping including phenotypes from relatives without genotypes in a single-step (ssGWAS) for 6-week body weight in broiler chickens. Frontiers in Genetics, 2014, v.5, p.1-10. OPEN ACCESS. Article history: Received 03 March 2014 // Paper pending published 04 April 2014 // Accepted 25 April 2014 // Published online: 20 May 2014.| Biblioteca(s): INIA Las Brujas. |
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| 205. | | CHEN, C.Y.; MISZTAL, I.; AGUILAR, I.; TSURUTA, S.; MEUWISSEN, T.H.E.; AGGREY, S.E.; WING, T.; MUIR, W.M. Genome-wide marker-assisted selection combining all pedigree phenotypic information with genotypic data in one step: An example using broiler chickens. Journal of Animal Science, 2011, v.89, no.1, p.23-28. Article history: Received April 9, 2010 / Accepted September 22, 2010.| Biblioteca(s): INIA Las Brujas. |
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| 206. | | LONDOÑO-GIL, M.; CARDONA-CIFUENTES, D.; ESPIGOLAN, R.; PERIPOLLI, E.; LÔBO, R. B.; PEREIRA, A. S. C.; AGUILAR, I.; BALDI, F. Genomic evaluation of commercial herds with different pedigree structures using the single-step genomic BLUP in Nelore cattle. Tropical Animal Health and Production, 2023, Volume 55, Issue 2, Article 95. doi: https://doi.org/10.1007/s11250-023-03508-4 Article history: Received 28 April 2022, Accepted 11 February 2023, To be Published April 2023. -- Correspondence author: Cardona-Cifuentes, D.; Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista Júlio de...| Biblioteca(s): INIA Las Brujas. |
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| 207. | | LOURENCO, D.A.L.; FRAGOMENI, B.O.; BRADFORD, H.L.; MENEZES I.R.; FERRAZ, J.B.S.; AGUILAR, I.; MISZTAL, I. Implications of SNP weighting on single-step genomic predictions for different reference population sizes. Journal of Animal Breeding and Genetics, 2017, v. 134 (6), p. 463-471. Article history: Received: 28 February 2017 / Accepted: 19 July 2017.
This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI) and by Agriculture and Food Research Initiative Competitive...| Biblioteca(s): INIA Las Brujas. |
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| 208. | | PRAVIA, M.; NAVAJAS, E.; LEMA, O.; AGUILAR, I.; RAVAGNOLO, O.; BRITO, G.; CLARIGET, J.; PERAZA, P.; DE LOS SANTOS, J.; DALLA RIZZA, M.; MONTOSSI, F. Mejoramiento genético en eficiencia de conversión de alimento y características de canal: oportunidades a través del uso de la genómica. In: Congreso Asociación Uruguaya de Producción Animal (AUPA) (5º, 3-4 Dic. 2014, Montevideo, UY). Sede del evento: Facultad de Agronomía, Av. Garzón 780, Montevideo, Uruguay.| Biblioteca(s): INIA Tacuarembó. |
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| 209. | | NAVAJAS, E.; PRAVIA, M.I.; LEMA, O.M.; RAVAGNOLO, O.; AGUILAR, I.; BRITO, G.; CLARIGET, J.; DALLA RIZZA, M.; MONTOSSI, F. Selección genómica en eficiencia de conversión y calidad de canal de la raza Hereford en Uruguay. Anuario Hereford (Montevideo), p. 160-172, 2014.| Biblioteca(s): INIA La Estanzuela. |
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| 210. | | Aguilar, I.; Pravia, Ma.I.; Ravagnolo, O.; Chiappesoni, G. (INIA Las Brujas); Mattos, M.; Ahlig, I. (Soc.Criadores Aberdeen Angus); Urioste, J.; Naya, H. (UDELAR, Fac.Agronomía) Servicio de evaluación de reproductores Aberdeen Angus Canelones (Uruguay): INIA, 2004. 23 p.| Biblioteca(s): INIA Las Brujas. |
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| 211. | | RODRÍGUEZ NEIRA, J.D.; PERIPOLLI, E.; DE NEGREIROS M.P.M.; ESPIGOLAN, R.; LÓPEZ-CORREA R.; AGUILAR, I.; LOBO R.B.; BALDI, F. Prediction ability for growth and maternal traits using SNP arrays based on different marker densities in Nellore cattle using the ssGBLUP. Journal of Applied Genetics, 2022, Volume 63, Issue 2, pages 389-400. doi: https://doi.org/10.1007/s13353-022-00685-0 Article history: Received 26 September 2021; Revised 25 January 2022; Accepted 2 February 2022.
Corresponding author: Rodriguez Neira, J.D.; Departamento de Zootecnia, Faculdade de Ciências Agrarias e Veterinárias, Universidade...| Biblioteca(s): INIA Las Brujas. |
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| 212. | | TONUSSI, R.L.; LONDOÑO-GIL, M.; DE OLIVEIRA SILVA, R.M.; MAGALHÃES, A.F.B.; AMORIM, S:T.; KLUSKA, S.; ESPIGOLAN, R.; PERIPOLLI, E.; PEREIRA, A.S.C.; LÔBO, R.B.; AGUILAR, I.; LOURENÇO, D.A.L.; BALDI, F. Accuracy of genomic breeding values and predictive ability for postweaning liveweight and age at first calving in a Nellore cattle population with missing sire information. Tropical Animal Health and Production, 2021, Volume 53, Issue 4, Article number 432. doi: https://doi.org/10.1007/s11250-021-02879-w Article history: Received 19 March 2021; Accepted 30 July 2021; Published online 10 August 2021.
Corresponding author: Londoño-Gil, M.; Grupo de Melhoramento Animal, Faculdade de Ciências Agrárias E Veterinárias, Universidade Estadual...| Biblioteca(s): INIA Las Brujas. |
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| 213. | | TORO OSPINA, A.M.; AGUILAR, I.; VARGAS DE OLIVEIRA, M.H.; CRUZ DOS SANTOS CORREIA, L. E.; VERCESI FILHO, A. E.; ALBUQUERQUE, L.G.; JOSINEUDSON AUGUSTO II DE VASCONCELOS SILVA Assessing the accuracy of imputation in the Gyr breed using different SNP panels. Genome, 2021 Oct, Volume 64 , Issue 10, pag 893-899. Open Acces. Doi: https://doi.org/10.1139/gen-2020-0081 Article history: Received 22 May 2020./ Accepted 17 April 2021. Corresponding author: Alejandra Maria Toro Ospina (email: toroospina92@gmail.com)| Biblioteca(s): INIA La Estanzuela. |
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| 214. | | CARDOSO, F. F.; YOKOO, M. J. I.; GULIAS-GOMES, C. C.; OLIVEIRA, M. M. DE; TEIXEIRA, B. B. M.; ROSO, V. M.; BRITO, F. V.; CAETANO, A. R.; AGUILAR, I. Avaliação genômica de touros Hereford e Braford. Bagé: Embrapa Pecuária Sul, 2012. 32 p. (Embrapa Pecuária Sul. Documentos, 127).| Biblioteca(s): INIA Las Brujas. |
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| 215. | | MISZTAL, I.; WANG, H.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.; FRAGOMENI, B. O.; ZHANG, X.; MUIR, W. M.; CHENG, H. H.; OKIMOTO, R.; WING, T.; HAWKEN, R. R.; ZUMBACH, B.; FERNANDO, R. GWAS using ssGBLUP. Volume Species Breeding: Poultry, 325. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.325.| Biblioteca(s): INIA Las Brujas. |
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| 216. | | CARVALHO, F.E.; ESPIGOLAN, R.; BERTON, M.P.; NETO, J.B.S.; SILVA, R.P.; GRIGOLETTO, L.; SILVA, R.M.O.; FERRAZ, J.B.S.; ELER, J.P.; AGUILAR, I.; LÔBO, R.B.; BALDI, F. Genome-wide association study and predictive ability for growth traits in Nellore cattle. Livestock Science, January 2020, Volume 231, Article number 103861. OPEN ACCESS. Doi: https://doi.org/10.1016/j.livsci.2019.103861 Article history: Received 25 June 2019 / Revised 29 October 2019 / Accepted 4 November 2019 / Available online 6 November 2019.
Funding information: F.E. CARVALHO received a scholarship from Coordinating for the Improvement of Higher...| Biblioteca(s): INIA Las Brujas. |
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| 217. | | CARDOSO, F. F.; GOMES, C.C.G.; SOLLERO, B. P.; OLIVEIRA, M. M.; ROSO, V. M.; PICCOLI, M. L.; HIGA, R. H.; YOKOO, M. J.; CAETANO, A. R.; AGUILAR, I. Genomic prediction for tick resistance in Braford and Hereford cattle. Journal of Animal Science, 2015. v. 95, p. 2693-2705. Published June 25, 2015 Article history: Received December 19, 2014 / Accepted April 6, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 218. | | TONUSSI, R.L.; SILVA, R.M.O.; MAGALHÃES, A.F.B.; PERIPOLLI , E.; OLIVIERI, B.F.; FEITOSA, F.L.B.; PEREIR, A.S.C.; LÔBO, R.B.; MAGNABOSCO, C.U.; AGUILAR, I.; BALDI, F. Impact of multiple sire mating system on the accuracy of genomic breeding value prediction in a beef cattle population under selection . [abstract 206]. Issue Section: Breeding and Genetics. Journal of Animal Science. 2017, Volume 95, Issue Supplement 4, Page 102. https://doi.org/10.2527/asasann.2017.206 Article history: Published 01 August 2017. --| Biblioteca(s): INIA Las Brujas. |
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| 219. | | NAVAJAS, E.; PRAVIA, M.I.; AGUIRRE, L.; MACEDO, F.; DE LA FUENTE, J.; MENDIOLA, B.; DEL PINO, M.L.; RAVAGNOLO, O.; LEMA, O.M.; PERAZA, P.; AGUILAR, I.; CARRAU, J.; CIAPPESONI, G. Tercer año de la evaluación de eficiencia de conversión de kiyú. Anuario Hereford (Montevideo), p. 182-186, 2016.| Biblioteca(s): INIA La Estanzuela; INIA Treinta y Tres. |
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| 220. | | TONUSSI, R. L.; SILVA, R. M. D. O.; MAGALHÃES, A.F.B.; ESPIGOLAN, R.; PERIPOLLI, E.; OLIVIERI, B. F.; FEITOSA, F. L. B.; LEMOS, M. V. A.; BERTON, M. P.; CHIAIA, H. L. J.; PEREIRA, A. S. C.; LÔBO, R. B.; BEZERRA, L. A. F.; MAGNABOSCO, C. D. U.; LOURENÇO, D.A.L.; AGUILAR, I.; BALDI, F. Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article). PLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS. Article history: Received September 22, 2016 // Accepted July 6, 2017 // Published September 28, 2017.
Data Availability Statement: All relevant data are within the paper, its Supporting Information files, and in Figshare.
Funding: This...| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 224 | |
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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 : |
26/11/2015 |
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Actualizado : |
15/10/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Circulación / Nivel : |
Internacional - -- |
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Autor : |
CARDOSO, F. F.; GOMES, C.C.G.; SOLLERO, B. P.; OLIVEIRA, M. M.; ROSO, V. M.; PICCOLI, M. L.; HIGA, R. H.; YOKOO, M. J.; CAETANO, A. R.; AGUILAR, I. |
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Afiliación : |
F. F. CARDOSO, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); Universidad Federal de Pelotas; C.C.G. GOMES, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); B. P. SOLLERO, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); M.M. OLIVEIRA, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); V.M. ROSO, Gensys Associated Consulants; M.L. PICCOLI, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); R.H. HIGA, Gensys Associated Consulants; Universidad Federal de Rio Grande Do Sul (UFRGS); M.J. YOKKO, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); A.R. CAETANO, EMBRAPA (Empresa Brasileira de Pesquisa Agropecuária); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Genomic prediction for tick resistance in Braford and Hereford cattle. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Journal of Animal Science, 2015. v. 95, p. 2693-2705. Published June 25, 2015 |
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DOI : |
10.2527/jas2014-8832 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received December 19, 2014 / Accepted April 6, 2015. |
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Contenido : |
ABSTRACT.
One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and
928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV
accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for k-means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breedspecific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance.
© 2015 American Society of Animal Science. All rights reserved. MenosABSTRACT.
One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and
928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 f... Presentar Todo |
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Palabras claves : |
BEEF CATLLE; GENOMIC SELECTION; HEALTH; TICK RESISTANCE. |
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Thesagro : |
GANADO DE CARNE; MEJORAMIENTO GENETICO ANIMAL; SALUD. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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Marc : |
LEADER 03639naa a2200337 a 4500
001 1054002
005 2019-10-15
008 2015 bl uuuu u00u1 u #d
024 7 $a10.2527/jas2014-8832$2DOI
100 1 $aCARDOSO, F. F.
245 $aGenomic prediction for tick resistance in Braford and Hereford cattle.$h[electronic resource]
260 $c2015
500 $aArticle history: Received December 19, 2014 / Accepted April 6, 2015.
520 $aABSTRACT. One of the main animal health problems in tropical and subtropical cattle production is the bovine tick, which causes decreased performance, hide devaluation, increased production costs with acaricide treatments, and transmission of infectious diseases. This study investigated the utility of genomic prediction as a tool to select Braford (BO) and Hereford (HH) cattle resistant to ticks. The accuracy and bias of different methods for direct and blended genomic prediction was assessed using 10,673 tick counts obtained from 3,435 BO and 928 HH cattle belonging to the Delta G Connection breeding program. A subset of 2,803 BO and 652 HH samples were genotyped and 41,045 markers remained after quality control. Log transformed records were adjusted by a pedigree repeatability model to estimate variance components, genetic parameters, and breeding values (EBV) and subsequently used to obtain deregressed EBV. Estimated heritability and repeatability for tick counts were 0.19 ± 0.03 and 0.29 ± 0.01, respectively. Data were split into 5 subsets using k-means and random clustering for cross-validation of genomic predictions. Depending on the method, direct genomic value (DGV) prediction accuracies ranged from 0.35 with Bayes least absolute shrinkage and selection operator (LASSO) to 0.39 with BayesB for k-means clustering and between 0.42 with BayesLASSO and 0.45 with BayesC for random clustering. All genomic methods were superior to pedigree BLUP (PBLUP) accuracies of 0.26 for k-means and 0.29 for random groups, with highest accuracy gains obtained with BayesB (39%) for k-means and BayesC (55%) for random groups. Blending of historical phenotypic and pedigree information by different methods further increased DGV accuracies by values between 0.03 and 0.05 for direct prediction methods. However, highest accuracy was observed with single-step genomic BLUP with values of 0.48 for k-means and 0.56, which represent, respectively, 84 and 93% improvement over PBLUP. Observed random clustering cross-validation breedspecific accuracies ranged between 0.29 and 0.36 for HH and between 0.55 and 0.61 for BO, depending on the blending method. These moderately high values for BO demonstrate that genomic predictions could be used as a practical tool to improve genetic resistance to ticks and in the development of resistant lines of this breed. For HH, accuracies are still in the low to moderate side and this breed training population needs to be increased before genomic selection could be reliably applied to improve tick resistance. © 2015 American Society of Animal Science. All rights reserved.
650 $aGANADO DE CARNE
650 $aMEJORAMIENTO GENETICO ANIMAL
650 $aSALUD
653 $aBEEF CATLLE
653 $aGENOMIC SELECTION
653 $aHEALTH
653 $aTICK RESISTANCE
700 1 $aGOMES, C.C.G.
700 1 $aSOLLERO, B. P.
700 1 $aOLIVEIRA, M. M.
700 1 $aROSO, V. M.
700 1 $aPICCOLI, M. L.
700 1 $aHIGA, R. H.
700 1 $aYOKOO, M. J.
700 1 $aCAETANO, A. R.
700 1 $aAGUILAR, I.
773 $tJournal of Animal Science, 2015.$gv. 95, p. 2693-2705. Published June 25, 2015
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