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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
11/12/2018 |
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Actualizado : |
18/06/2019 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
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. |
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Afiliación : |
RAFAEL LARA TONUSSI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; RAFAEL MEDEIROS DE OLIVEIRA SILVA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; FABRÍCIA BRAGA MAGALHÃES, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; RAFAEL ESPIGOLAN, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazi; ELISA PERIPOLLI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; BIANCA FERREIRA OLIVIERI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; FABIELI LOISE BRAGA FEITOSA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; MARCOS VINICÍUS ANTUNES LEMOS, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; MARIANA PIATTO BERTON, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; HERMENEGILDO LUCAS JUSTINO CHIAIA, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil; ANGELICA SIMONE CRAVO PEREIRA, Department of Nutrition and Animal Production, Faculty of Animal Science and Food Engineering, Pirassununga, Brazil; RAYSILDO BARBOSA LÔBO, National Association of Breeders and Researchers (ANCP), Ribeirão Preto, Brazil; LUIZ ANTÔNIO FRAMARTINO BEZERRA, Department of Genetic, Medical School of Ribeirão Preto, Ribeirão Preto, Brazil; CLÁUDIO DE ULHOA MAGNABOSCO, Brazilian Agricultural Research Corporation (EMBRAPA), Distrito Federal, Brazil; DANIELA ANDRESSA LINO LOURENÇO, Department of Animal and Dairy Science, University of Georgia, Athens, Georgia, United States of America; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; FERNANDO BALDI, Department of Animal Science, School of Agricultural and Veterinarian Sciences, Jaboticabal, São Paulo, Brazil. |
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Título : |
Application of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article). |
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Fecha de publicación : |
2017 |
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Fuente / Imprenta : |
PLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS. |
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ISSN : |
1932-6203 |
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DOI : |
10.1371/journal.pone.0181752 |
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Idioma : |
Inglés |
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Notas : |
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 work was funded by the Sao Paulo Research Foundation (FAPESP), 2013/25910-0, Mr Rafael Lara Tonussi, and Sao Paulo Research Foundation (FAPESP), 2011/21241-0, PhD Fernando Bald. |
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Contenido : |
ABSTRACT.
The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty.
© 2017 Tonussi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. MenosABSTRACT.
The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the popula... Presentar Todo |
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Palabras claves : |
CATTLE; COMPUTER SIMULATION; GENETIC VARIABILITY; GENETICS; GENOMICS; INHERITANCE PATTERNS; PEDIGREE. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12157/1/journal.pone.0181752.pdf
https://journals.plos.org/plosone/article/file?id=10.1371/journal.pone.0181752&type=printable
https://journals.plos.org/plosone/article?id=10.1371/journal.pone.0181752#sec009
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Marc : |
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100 1 $aTONUSSI, R. L.
245 $aApplication of single step genomic BLUP under different uncertain paternity scenarios using simulated data. (Research article).$h[electronic resource]
260 $c2017
500 $aArticle 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 work was funded by the Sao Paulo Research Foundation (FAPESP), 2013/25910-0, Mr Rafael Lara Tonussi, and Sao Paulo Research Foundation (FAPESP), 2011/21241-0, PhD Fernando Bald.
520 $aABSTRACT. The objective of this study was to investigate the application of BLUP and single step genomic BLUP (ssGBLUP) models in different scenarios of paternity uncertainty with different strategies of scaling the G matrix to match the A22 matrix, using simulated data for beef cattle. Genotypes, pedigree, and phenotypes for age at first calving (AFC) and weight at 550 days (W550) were simulated using heritabilities based on real data (0.12 for AFC and 0.34 for W550). Paternity uncertainty scenarios using 0, 25, 50, 75, and 100% of multiple sires (MS) were studied. The simulated genome had a total length of 2,333 cM, containing 735,293 biallelic markers and 7,000 QTLs randomly distributed over the 29 BTA. It was assumed that QTLs explained 100% of the genetic variance. For QTL, the amount of alleles per loci randomly ranged from two to four. The BLUP model that considers phenotypic and pedigree data, and the ssGBLUP model that combines phenotypic, pedigree and genomic information were used for genetic evaluations. Four ways of scaling the mean of the genomic matrix (G) to match to the mean of the pedigree relationship matrix among genotyped animals (A22) were tested. Accuracy, bias, and inflation were investigated for five groups of animals: ALL = all animals; BULL = only bulls; GEN = genotyped animals; FEM = females; and YOUNG = young males. With the BLUP model, the accuracies of genetic evaluations decreased for both traits as the proportion of unknown sires in the population increased. The EBV accuracy reduction was higher for GEN and YOUNG groups. By analyzing the scenarios for YOUNG (from 0 to 100% of MS), the decrease was 87.8 and 86% for AFC and W550, respectively. When applying the ssGBLUP model, the accuracies of genetic evaluation also decreased as the MS in the pedigree for both traits increased. However, the accuracy reduction was less than those observed for BLUP model. Using the same comparison (scenario 0 to 100% of MS), the accuracies reductions were 38 and 44.6% for AFC and W550, respectively. There were no differences between the strategies for scaling the G matrix for ALL, BULL, and FEM groups under the different scenarios with missing pedigree. These results pointed out that the uninformative part of the A22 matrix and genotyped animals with paternity uncertainty did not influence the scaling of G matrix. On the basis of the results, it is important to have a G matrix in the same scale of the A22 matrix, especially for the evaluation of young animals in situations with missing pedigree information. In these situations, the ssGBLUP model is an appropriate alternative to obtain a more reliable and less biased estimate of breeding values, especially for young animals with few or no phenotypic records. For accurate and unbiased genomic predictions with ssGBLUP, it is necessary to assure that the G matrix is compatible with the A22 matrix, even in situations with paternity uncertainty. © 2017 Tonussi et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
653 $aCATTLE
653 $aCOMPUTER SIMULATION
653 $aGENETIC VARIABILITY
653 $aGENETICS
653 $aGENOMICS
653 $aINHERITANCE PATTERNS
653 $aPEDIGREE
700 1 $aSILVA, R. M. D. O.
700 1 $aMAGALHÃES, A.F.B.
700 1 $aESPIGOLAN, R.
700 1 $aPERIPOLLI, E.
700 1 $aOLIVIERI, B. F.
700 1 $aFEITOSA, F. L. B.
700 1 $aLEMOS, M. V. A.
700 1 $aBERTON, M. P.
700 1 $aCHIAIA, H. L. J.
700 1 $aPEREIRA, A. S. C.
700 1 $aLÔBO, R. B.
700 1 $aBEZERRA, L. A. F.
700 1 $aMAGNABOSCO, C. D. U.
700 1 $aLOURENÇO, D.A.L.
700 1 $aAGUILAR, I.
700 1 $aBALDI, F.
773 $tPLoS ONE, September 2017, Volume 12, Issue 9, Article number e0181752. OPEN ACCESS.
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INIA Las Brujas (LB) |
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| Registros recuperados : 218 | |
| 201. |  | ROMAN, L.; LA MANNA, A.; ACOSTA, Y.; MENDOZA, A.; AGUILAR, I.; MORALES-PIÑEYRUA, J.; PLA, M.; LAURA ASTIGARRAGA, L.; SARAVIA, C. Evaluación de medidas de mitigación del estrés por calor sobre las respuestas productivas de vacas lecheras de alta producción. In: Día de Campo: producción de forraje y leche en verano. La Estanzuela, Colonia, (Uruguay): INIA, 2013. p. 15. (Serie Actividades de Difusión; 705).| Biblioteca(s): INIA La Estanzuela. |
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| 202. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 203. | | 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.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Tacuarembó. |
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| 204. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 205. | | 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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| 206. | | 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)| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA La Estanzuela. |
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| 207. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 208. | | 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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| 209. | | 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.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 210. | | 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.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 211. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 212. | | 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. --| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 213. | | 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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| 214. | | 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...| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 215. | | LEMOS, M.V.A.; CHIAIA, H.L.J.; BERTON, M.P.; FEITOSA, F.L.B.; ABOUJAOUD, C.; CAMARGO, G.M.F.; PEREIRA, A.S.C.; ALBUQUERQUE, L.G.; FERRINHO, A.M.; MUELLER, L.F.; MAZALLI, M.R.; FURLAN, J.J.M.; CARVALHEIRO, R.; GORDO, D.M.; TONUSSI, R.; ESPIGOLAN, R.; SILVA, R.M.O.; DE OLIVEIRA, H.N.; DUCKETT, S.; AGUILAR, I.; BALDI, F. Genome-wide association between single nucleotide polymorphisms with beef fatty acid profile in Nellore cattle using the single step procedure. BMC Genomics, 2016, v. 17:213. Received: 19 November 2015 / Accepted: 23 February 2016 /Published: 9 March 2016| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 216. | | 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. Genomic prediction ability for beef fatty acid profile in Nelore cattle using different pseudo-phenotypes. Journal of Applied Genetics, 1 November 2018, volume 59, Issue 4, pages 493-501. Article history: Received: 15 May 2018 // Revised: 28 August 2018 // Accepted: 17 September 2018.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| 217. | | NAVAJAS, E.; VELAZCO, J.I.; SOTELO, J.; NOYA, H.; CASAL, A.; GIANOLA, D.; PERAZA, P.; BIELLI, A.; ITHURRALDE, J.; GENOVESE, P.; PÉREZ, R.; CANTALAPIEDRA, G.; AGUILAR, I.; LEMA, O.M.; RAVAGNOLO, O.; DEVINCENZI, T.; CARRACELAS, B.; DE SOUZA, G.; CIAPPESONI, G.; BRITO, G.; LUZARDO, S. Plataforma de Fenotipado intensivo - Kiyú. Anuario Hereford (Montevideo), 2020, p. 210-213.| Biblioteca(s): INIA La Estanzuela; INIA Tacuarembó. |
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| 218. | | FEITOSA, F. L. B.; OLIVIERI, B. F.; ABOUJAOUDE, C.; PEREIRA, A. S. C.; DE LEMOS, M. V. A.; CHIAIA, H. L. J.; BERTON, M. P.; PERIPOLLI, E.; FERRINHO, A. M.; MUELLER, L. F.; MAZZALI, M. R.; DE ALBUQUERQUE, L. G.; DE OLIVERA, H. N.; TONHATI, H.; ESPIGOLAN, R.; TONUSSI, R. L.; DE OLIVIERA SILVA, R. M.; GORDO, D. G. M.; MAGALHAES, A. F. B.; AGUILAR, I.; BALDI, F. S. B. Genetic correlation estimates between beef fatty acid profile with meat and carcass traits in Nellore cattle finished in feedlot. Journal of Applied Genetics, 2017, 58 (1), 123-132. Article history: Received: 15 December 2015 /Revised: 10 March 2016 /Accepted: 5 July 2016 / Published Online: 30 July 2016| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 218 | |
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