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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 : |
07/11/2018 |
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Actualizado : |
07/11/2018 |
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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 : |
CHIAIA, H.L.J.; PERIPOLLI, E.; DE OLIVEIRA SILVA, R.M.; FEITOSA, F.L.B.; DE LEMOS, M.V.A.; BERTON, M.P.; OLIVIERI, B.F.; ESPIGOLAN, R.; TONUSSI, R.L.; GORDO, D.G.M.; DE ALBUQUERQUE, L.G.; DE OLIVEIRA, H.N.; FERRINHO, A.M.; MUELLER, L.F.; KLUSKA, S.; TONHATI, H.; PEREIRA, A.S.C.; AGUILAR, I.; BALDI, F. |
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Afiliación : |
HERMENEGILDO LUCAS JUSTINO CHIAIA, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; ELISA PERIPOLLI, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; RAFAEL MEDEIROS DE OLIVEIRA SILVA, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; FABIELE LOISE BRAGA FEITOSA, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; MARCOS VINÍCIUS ANTUNES DE LEMOS, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; MARIANA PIATTO BERTON, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; BIANCA FERREIRA OLIVIERI, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; RAFAEL ESPIGOLAN, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; RAFAEL LARA TONUSSI, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; DANIEL GUSTAVO MANSAN GORDO, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; LUCIA GALVÃO DE ALBUQUERQUE, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; HENRIQUE NUNES DE OLIVEIRA, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; ADRIELLE MATHIAS FERRINHO, Faculdade de Medicina Veterinária e Zootecnia, USP, Brazil.; LENISE FREITAS MUELLER, Faculdade de Zootecnia e Engenharia de Alimentos, USP, Brazil.; SABRINA KLUSKA, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; HUMBERTO TONHATI, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil.; ANGÉLICA SIMONE CRAVO PEREIRA, Faculdade de Medicina Veterinária e Zootecnia, USP, Brazil.; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Faculdade de Ciências Agrárias e Veterinárias, UNESP, Brazil. |
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Título : |
Genomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
Journal of Applied Genetics, 1 November 2018, volume 59, Issue 4, pages 493-501. |
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DOI : |
10.1007/s13353-018-0470-5 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received: 15 May 2018 // Revised: 28 August 2018 // Accepted: 17 September 2018. |
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Contenido : |
ABSTRACT.
The aim of the present study was to compare the predictive ability of SNP-BLUP model using different pseudo-phenotypes such as phenotype adjusted for fixed effects, estimated breeding value, and genomic estimated breeding value, using simulated and real data for beef FA profile of Nelore cattle finished in feedlot. A pedigree with phenotypes and genotypes of 10,000 animals were simulated, considering 50% of multiple sires in the pedigree. Regarding to phenotypes, two traits were simulated, one with high heritability (0.58), another with low heritability (0.13). Ten replicates were performed for each trait and results were averaged among replicates. A historical population was created from generation zero to 2020, with a constant size of 2000 animals (from generation zero to 1000) to produce different levels of linkage disequilibrium (LD). Therefore, there was a gradual reduction in the number of animals (from 2000 to 600), producing a ?bottleneck effect? and consequently, genetic drift and LD starting in the generation 1001 to 2020. A total of 335,000 markers (with MAF greater or equal to 0.02) and 1000 QTL were randomly selected from the last generation of the historical population to generate genotypic data for the test population. The phenotypes were computed as the sum of the QTL effects and an error term sampled from a normal distribution with zero mean and variance equal to 0.88. For simulated data, 4000 animals of the generations 7, 8, and 9 (with genotype and phenotype) were used as training population, and 1000 animals of the last generation (10) were used as validation population. A total of 937 Nelore bulls with phenotype for fatty acid profiles (Sum of saturated, monounsaturated, omega 3, omega 6, ratio of polyunsaturated and saturated and polyunsaturated fatty acid profile) were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. To compare the accuracy and bias of direct genomic value (DGV) for different pseudo-phenotypes, the correlation between true breeding value (TBV) or DGV with pseudo-phenotypes and linear regression coefficient of the pseudo-phenotypes on TBV for simulated data or DGV for real data, respectively. For simulated data, the correlations between DGV and TBV for high heritability traits were higher than obtained with low heritability traits. For simulated and real data, the prediction ability was higher for GEBV than for Yc and EBV. For simulated data, the regression coefficient estimates (b(Yc,DGV)), were on average lower than 1 for high and low heritability traits, being inflated. The results were more biased for Yc and EBV than for GEBV. For real data, the GEBV displayed less biased results compared to Yc and EBV for SFA, MUFA, n-3, n-6, and PUFA/SFA. Despite the less biased results for PUFA using the EBV as pseudo-phenotype, the b(Yi,DGV estimates obtained for the different pseudo-phenotypes (Yc, EBV and GEBV) were very close. Genomic information can assist in improving beef fatty acid profile in Zebu cattle, since the use of genomic information yielded genomic values for fatty acid profile with accuracies ranging from low to moderate. Considering both simulated and real data, the ssGBLUP model is an appropriate alternative to obtain more reliable and less biased GEBVs as pseudo-phenotype in situations of missing pedigree, due to high proportion of multiple sires, being more adequate than EBV and Yc to predict direct genomic value for beef fatty acid profile.
© 2018, Institute of Plant Genetics, Polish Academy of Sciences, Poznan. MenosABSTRACT.
The aim of the present study was to compare the predictive ability of SNP-BLUP model using different pseudo-phenotypes such as phenotype adjusted for fixed effects, estimated breeding value, and genomic estimated breeding value, using simulated and real data for beef FA profile of Nelore cattle finished in feedlot. A pedigree with phenotypes and genotypes of 10,000 animals were simulated, considering 50% of multiple sires in the pedigree. Regarding to phenotypes, two traits were simulated, one with high heritability (0.58), another with low heritability (0.13). Ten replicates were performed for each trait and results were averaged among replicates. A historical population was created from generation zero to 2020, with a constant size of 2000 animals (from generation zero to 1000) to produce different levels of linkage disequilibrium (LD). Therefore, there was a gradual reduction in the number of animals (from 2000 to 600), producing a ?bottleneck effect? and consequently, genetic drift and LD starting in the generation 1001 to 2020. A total of 335,000 markers (with MAF greater or equal to 0.02) and 1000 QTL were randomly selected from the last generation of the historical population to generate genotypic data for the test population. The phenotypes were computed as the sum of the QTL effects and an error term sampled from a normal distribution with zero mean and variance equal to 0.88. For simulated data, 4000 animals of the generations 7, 8, and 9 (with genotype a... Presentar Todo |
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Palabras claves : |
BOS INDICUS; GENOMIC PREDICTION; LIPID PROFILE; SINGLE-STEP; SNP-BLUP. |
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Asunto categoría : |
-- |
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Marc : |
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100 1 $aCHIAIA, H.L.J.
245 $aGenomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes.$h[electronic resource]
260 $c2018
500 $aArticle history: Received: 15 May 2018 // Revised: 28 August 2018 // Accepted: 17 September 2018.
520 $aABSTRACT. The aim of the present study was to compare the predictive ability of SNP-BLUP model using different pseudo-phenotypes such as phenotype adjusted for fixed effects, estimated breeding value, and genomic estimated breeding value, using simulated and real data for beef FA profile of Nelore cattle finished in feedlot. A pedigree with phenotypes and genotypes of 10,000 animals were simulated, considering 50% of multiple sires in the pedigree. Regarding to phenotypes, two traits were simulated, one with high heritability (0.58), another with low heritability (0.13). Ten replicates were performed for each trait and results were averaged among replicates. A historical population was created from generation zero to 2020, with a constant size of 2000 animals (from generation zero to 1000) to produce different levels of linkage disequilibrium (LD). Therefore, there was a gradual reduction in the number of animals (from 2000 to 600), producing a ?bottleneck effect? and consequently, genetic drift and LD starting in the generation 1001 to 2020. A total of 335,000 markers (with MAF greater or equal to 0.02) and 1000 QTL were randomly selected from the last generation of the historical population to generate genotypic data for the test population. The phenotypes were computed as the sum of the QTL effects and an error term sampled from a normal distribution with zero mean and variance equal to 0.88. For simulated data, 4000 animals of the generations 7, 8, and 9 (with genotype and phenotype) were used as training population, and 1000 animals of the last generation (10) were used as validation population. A total of 937 Nelore bulls with phenotype for fatty acid profiles (Sum of saturated, monounsaturated, omega 3, omega 6, ratio of polyunsaturated and saturated and polyunsaturated fatty acid profile) were genotyped using the Illumina BovineHD BeadChip (Illumina, San Diego, CA) with 777,962 SNP. To compare the accuracy and bias of direct genomic value (DGV) for different pseudo-phenotypes, the correlation between true breeding value (TBV) or DGV with pseudo-phenotypes and linear regression coefficient of the pseudo-phenotypes on TBV for simulated data or DGV for real data, respectively. For simulated data, the correlations between DGV and TBV for high heritability traits were higher than obtained with low heritability traits. For simulated and real data, the prediction ability was higher for GEBV than for Yc and EBV. For simulated data, the regression coefficient estimates (b(Yc,DGV)), were on average lower than 1 for high and low heritability traits, being inflated. The results were more biased for Yc and EBV than for GEBV. For real data, the GEBV displayed less biased results compared to Yc and EBV for SFA, MUFA, n-3, n-6, and PUFA/SFA. Despite the less biased results for PUFA using the EBV as pseudo-phenotype, the b(Yi,DGV estimates obtained for the different pseudo-phenotypes (Yc, EBV and GEBV) were very close. Genomic information can assist in improving beef fatty acid profile in Zebu cattle, since the use of genomic information yielded genomic values for fatty acid profile with accuracies ranging from low to moderate. Considering both simulated and real data, the ssGBLUP model is an appropriate alternative to obtain more reliable and less biased GEBVs as pseudo-phenotype in situations of missing pedigree, due to high proportion of multiple sires, being more adequate than EBV and Yc to predict direct genomic value for beef fatty acid profile. © 2018, Institute of Plant Genetics, Polish Academy of Sciences, Poznan.
653 $aBOS INDICUS
653 $aGENOMIC PREDICTION
653 $aLIPID PROFILE
653 $aSINGLE-STEP
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700 1 $aDE OLIVEIRA SILVA, R.M.
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700 1 $aDE LEMOS, M.V.A.
700 1 $aBERTON, M.P.
700 1 $aOLIVIERI, B.F.
700 1 $aESPIGOLAN, R.
700 1 $aTONUSSI, R.L.
700 1 $aGORDO, D.G.M.
700 1 $aDE ALBUQUERQUE, L.G.
700 1 $aDE OLIVEIRA, H.N.
700 1 $aFERRINHO, A.M.
700 1 $aMUELLER, L.F.
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700 1 $aAGUILAR, I.
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773 $tJournal of Applied Genetics, 1 November 2018, volume 59, Issue 4, pages 493-501.
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