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| Registros recuperados : 224 | |
| 161. |  | LEMA, O.M.; BRITO, G.; CLARIGET, J.; PEREZ, E.; LA MANNA, A.; RAVAGNOLO, O.; AGUILAR, I.; MONTOSSI, F. Can nutritional level and parental EPD for rib eye area influence feed conversion efficiency and carcass yield in steers?.[Poster]. In: AUSTRALIAN SOCIETY OF ANIMAL PRODUCTION; NEW ZEALAND SOCIETY OF ANIMAL PRODUCTION, 31st,2016. Proceedings. Adelaida, South Australia, AU: ASAP. 2016.| Biblioteca(s): INIA La Estanzuela. |
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| 162. | | LOURENCO, D.A.L.; FRAGOMENI, B.O.; TSURUTA, S.; AGUILAR, I.; ZUMBACH, B.; HAWKEN, R.J.; LEGARRA, A.; MISZTAL, I. Accuracy of estimated breeding values with genomic information on males, females, or both: An example on broiler chicken. Genetics Selection Evolution, 2015, v. 242, p. 47-56. OPEN ACCESS. Article history: Received: 14 October 2014 / Accepted: 22 June 2015 / Published: 02 July 2015.| Biblioteca(s): INIA Las Brujas. |
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| 163. | | RAVAGNOLO, O.; AGUILAR, I.; CROWLEY, J. J.; PRAVIA, M.I.; LEMA, O.M.; MACEDO, F.; SCOTT, S.; NAVAJAS, E. Accuracy of genomic predictions of residual feed intake in Hereford with Uruguayan and Canadian training populations. Volume: Electronic Poster Session - Species - Bovine (beef) 1, p. 723. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. 6 p.| Biblioteca(s): INIA Las Brujas. |
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| 164. | | ROSAS, J.E.; ALE, L.; REBOLLO, I.; SCHEFFEL, S.; AGUILAR, I.; MOLINA, F.; PÉREZ DE VIDA, F. Boosting INIA's Rice Breeding Program with molecular quantitative genetics approaches. [Abstract]. In: International Temperate Rice Conference (7., 2020, Pelotas, RS), Science & Innovation: feeding a world of 10 billion people: proceedings. Pelotas RS, Brasil, February 9-12, 2020. Brasília, DF : Embrapa, 2020.| Biblioteca(s): INIA Treinta y Tres. |
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| 165. | | BALMELLI, G.; SIMETO, S.; CASTILLO, A.; GASPARRI, P.; CABRERA, D.; AGUILAR, I.; QUEZADA, M.; DA SILVA, C.; GIORELLO, F. Breeding for resistance to Teratosphaeria nubilosa on Eucalyptus globulus. In: Pesquisa florestal brasileira = Brazilian journal of forestry research., v. 39, e201902043, Special issue, 2019. Colombo : Embrapa Florestas, 2019. Congreso IUFRO, 25., Curitiba, Brasil, 29 setiembre-05 octubre, 2019. Abstracts. p. 173| Biblioteca(s): INIA Tacuarembó. |
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| 166. | | NAVAJAS, E.; PERAZA, P.; RAVAGNOLO, O.; CIAPPESONI, G.; AGUILAR, I.; KELLY, L.; BRANDA, A.; DALLA RIZZA, M.; MONTOSSI, F. Banco de ADN genómico animal: pilar de una plataforma en selección genómica. Revista INIA Uruguay, 2012, no. 28, p. 20-24 (Revista INIA; 28)| Biblioteca(s): INIA Las Brujas. |
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| 167. | | CARRACELAS, B.; PERAZA, P.; VERGARA, A.; CIAPPESONI, G.; RAVAGNOLO, O.; AGUILAR, I.; LEMA, O.M.; NAVAJAS, E. Banco de ADN genómico animal - plataforma de evaluación genómica. Revista INIA Uruguay, Diciembre 2022, no.71, p. 38-42. (Revista INIA; 71)| Biblioteca(s): INIA Treinta y Tres. |
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| 168. | | MISZTAL, I.; FRAGOMENI, B.; LOURENÇO, D. A. L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T. J. Efficient inversion of genomic relationship matrix by the Algorithm for Proven and Young (APY). Interbull Bulletin, 2015, v. 49, p. 111-116.| Biblioteca(s): INIA Las Brujas. |
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| 169. | | FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; LAWLOR, T.J.; MIZTAL, I. Hot topic: Use of genomic recursions in single-step genomic best linear unbiased predictor (BLUP) with a large number of genotypes. Journal of Dairy Science, 2015, v.98, no.6, p.4090-4094. OPEN ACCESS. Article history: Received November 18, 2014 / Accepted March 13, 2015 / Published online: April 8, 2015.| Biblioteca(s): INIA Las Brujas. |
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| 170. | | CHEN, C. Y.; MISZTAL, I.; AGUILAR, I.; TSURUTA, S.; MEUWISSEN, T.; AGGREY, S. E.; MUIR, W. M. Genome wide marker assisted selection in chicken: making the most of all data, pedigree, phenotypic, and genomic in a simple one step procedure. Volume Genetic improvement programmes: Selection using molecular information - Lecture Sessions, 0288. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0288. Acknowledgements: The authors thank Cobb-Vantress for access to data for this study. This study was partially funded by the Holstein Association, Smithfield Premium Genetics, and by AFRI grants 2009-65205-05665 and 2010-65205-20366 from...| Biblioteca(s): INIA Las Brujas. |
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| 171. | | BRUNES, L.C.; FARIA, C.U.D.; MAGNABOSCO, C.U.; LOBO, R.B.; PERIPOLLI, E.; AGUILAR, I.; BALDI, F. Genomic prediction ability and genetic parameters for residual feed intake calculated using different approaches and their associations with growth, reproductive, and carcass traits in Nellore cattle. Journal of Applied Genetics, 2023, Volume 64, Issue 1, Pages 159 - 167. doi: https://doi.org/10.1007/s13353-022-00734-8 Article history: Received 25 February 2022; Revised 3 September 2022; Accepted 26 October 2022; Published online 15 November 2022; Published February 2023. -- Corresponding author: Brunes, L.C.; Animal Performance Center, Embrapa...| Biblioteca(s): INIA Las Brujas. |
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| 172. | | GRASSO, A.; GOLDBERG, V.; NAVAJAS, E.; IRIARTE, W.; GIMENO, D.; AGUILAR, I.; MEDRANO, J.F.; RINCÓN, G.; CIAPPESONI, G. Genomic variation and population structure detected by single nucleotide polymorphism arrays in Corriedale, Merino and Creole sheep. Genetics and Molecular Biology, 2014, v.37, n.2, p.389-395. Article history: Received: August 29, 2013 / Accepted: March 16, 2014.| Biblioteca(s): INIA Las Brujas. |
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| 174. | | RODRÍGUEZ, J.D.; PERIPOLLI, E.; LONDOÑO-GIL, M.; ESPIGOLAN, R.; LÔBO, R. B.; LÓPEZ-CORREA, R.; AGUILAR, I.; BALDI, F. Effect of minor allele frequency and density of single nucleotide polymorphism marker arrays on imputation performance and prediction ability using the single-step genomic Best Linear Unbiased Prediction in a simulated beef cattle population. Research paper. Animal Production Science. 2023, volume 63, issue 9, p. 844-852. https://doi.org/10.1071/AN21581 Article history: Submitted 1 December 2021, Accepted 1 March 2023, Published 4 April 2023. -- Correspondence to: Juan Diego Rodríguez,
Universidade Estadual Paulista (Unesp), Faculdade de Ciências Agrarias e Veterinárias, Departamento...| Biblioteca(s): INIA Las Brujas. |
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| 175. | | NEGRI, R.; AGUILAR, I.; FELTES, G. L.; MACHADO, J. D.; NETO, J. B.; COSTA-MAIA, F. M.; COBUCI, J. A. Inclusion of bioclimatic variables in genetic evaluations of dairy cattle.[Open Access]. Animal Bioscience [Asian-Australasian Journal of Animal Sciences], Volume 34, Issue 2, February 2021, Pages 163-171. Doi: https://doi.org/10.5713/ajas.19.0960 Article history: Submitted Dec 16, 2019 / Revised Mar 27, 2020 / Accepted Apr 28, 2020.
Corresponding Author: rn.negri@yahoo.com| Biblioteca(s): INIA Treinta y Tres. |
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| 176. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LEGARRA, A.; AGUILAR, I.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; LAWLOR, T.J. Implementation of genomic recursions in single-step genomic best linear unbiased predictor for US Holsteins with a large number of genotyped animals. Journal of Dairy Science, 2016, v.99, no.3, p.1968-1974. OPEN ACCESS OPEN ACCESS. Received 19 October 2015, Accepted 1 December 2015, Available online 21 January 2016| Biblioteca(s): INIA Las Brujas. |
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| 177. | | MCWHORTER, T.M.; BERMANN, M.; GARCIA, A.L.S.; LEGARRA, A.; AGUILAR, I.; MISZTAL, I.; LOURENCO, D. Implication of the order of blending and tuning when computing the genomic relationship matrix in single-step GBLUP. Journal of Animal Breeding and Genetics, 2023, volume 140, issue 1, pp. 60-78. OPEN ACCESS. doi: https://doi.org/10.1111/jbg.12734 Article history: Received 18 March 2019; Revised 15 July 2019; Accepted: 29 July 2019; First published 10 August 2022.
Correspondence: McWhorter, T.M.; Department of Animal and Dairy Science, University of Georgia, Athens, GA, United...| Biblioteca(s): INIA Las Brujas. |
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| 178. | | RAVAGNOLO, O.; NAVAJAS, E.; AGUILAR, I.; CIAPPESONI, G.; LEMA, O.M.; MONTOSSI, F.; PERAZA, P.; DALLA RIZZA, M. Mejoramiento genético animal e importancia del banco de ADN. ln: INIA TACUAREMBÓ. UNIDAD DE BIOTECNOLOGÍA INIA. Jornada técnica. Jornada de Agrobiotecnología INIA, 15 NOVIEMBRE, Tacuarembó, Biotecnología para el sector productivo: situación actual y perspectivas. Tacuarembó (Uruguay): INIA, 2012. p. 4-7 (INIA Serie Actividades de Difusión; 702)| Biblioteca(s): INIA Tacuarembó. |
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| 179. | | LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; EZRA, E.; RON, M.; SHIRAK, A.; WELLER, J.I. Methods for genomic evaluation of a relatively small genotyped dairy population and effect of genotyped cow information in multiparity analyses. Journal of Dairy Science, 2014, v.97, no.3, p.1742-1752. OPEN ACCESS. Article history: Received September 10, 2013. / Accepted December 6, 2013.| Biblioteca(s): INIA Las Brujas. |
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| 180. | | FORNERIS, N. S.; LEGARRA, A.; VITEZICA, Z. G.; TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; CANTET, R. J. C. Quality control of genotypes using heritability estimates of gene content at the marker. Genetics, 2015, v. 199, p. 675-681. OPEN ACCESS. Manuscript received September 26, 2014; accepted for publication December 18, 2014; published Early Online January 6, 2015.| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 224 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
31/03/2021 |
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Actualizado : |
31/03/2021 |
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Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
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Autor : |
LOURENCO, D.; TSURUTA, S.; FRAGOMENI, B.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; MOSER, D.; MISZTAL, I. |
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Afiliación : |
DANIELA LOURENCO, University of Georgia, Department of Animal and Dairy Science, GA, USA; SHOGO TSURUTA, University of Georgia, Department of Animal and Dairy Science, GA, USA; BRENO FRAGOMENI, University of Georgia, Department of Animal and Dairy Science, GA, USA; YUTAKA MASUDA, University of Georgia, Department of Animal and Dairy Science, GA, USA; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; ANDRÉS LEGARRA, Institut National de la Recherche Agronomique, Castanet Tolosan, France; STEPHEN MILLER, Angus Genetics Inc., MO, USA; DAN MOSER, Angus Genetics Inc., MO, USA; IGNACY MISZTAL, University of Georgia, Department of Animal and Dairy Science, GA, USA. |
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Título : |
Single-step genomic BLUP for national beef cattle evaluation in US: from initial developments to final implementation. |
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Complemento del título : |
Volume Species - Bovine (beef) 1, 495. |
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Fecha de publicación : |
2018 |
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Fuente / Imprenta : |
In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The objective of this study was to implement single-step genomic BLUP (ssGBLUP) for national Angus cattle evaluation in the US. National evaluations include a variety of models with several linear and categorical traits, maternal effects, multibreed data, and a large number of genotyped animals. For the initial investigation, we used a dataset from 2014 that comprised over 8 million animals, 6 million birth weight (BW) and weaning weight (WW) records, 3.4 million post-weaning gain (PWG) records, and genotypes for 52k animals. A dataset from 2017 was later used that included 335k genotyped animals. The ability to predict future performance of young animals was investigated when using regular BLUP and ssGBLUP. Because of the increasing number of genotyped animals and the high computing cost to invert the genomic relationship matrix (G), the algorithm for proven and young (APY) was used to approximate the inverse of G. The APY uses recursions on a small subset of genotyped animals, called core. We further tested the feasibility of having daily interim genomic predictions for newly-genotyped animals based on SNP effects derived from the previous official ssGBLUP evaluation. In addition, we extended all models used in traditional evaluations to ssGBLUP, and compared genetic trends from traditional BLUP, ssGBLUP, and a multistep method that was implemented for the American Angus genomic evaluation in 2009. A new algorithm to approximate accuracy of GEBV for large genomic data was also developed. On average, the increase in ability to predict future performance, for BW, WW, and PWG, with ssGBLUP was 25% in the 2014 data and 36% in the 2017 data, compared to the traditional BLUP. The ssGBLUP with APY was as accurate as the regular ssGBLUP when the number of core animals was at least 10,000, independently of which animals were in the core group. Interim predictions derived from ssGBLUP provided accurate genomic values for newly-genotyped animals. Genetic trends for ssGBLUP and BLUP were similar, revealing overestimation in multistep evaluations, especially for traits with less phenotypes. Single-step GBLUP became a reality for American Angus evaluation and its implementation process resulted in successful updates in methodology, making this approach mature for national beef cattle evaluation. Keywords: algorithm for proven and young, Angus, genomic selection, indirect prediction. MenosABSTRACT.
The objective of this study was to implement single-step genomic BLUP (ssGBLUP) for national Angus cattle evaluation in the US. National evaluations include a variety of models with several linear and categorical traits, maternal effects, multibreed data, and a large number of genotyped animals. For the initial investigation, we used a dataset from 2014 that comprised over 8 million animals, 6 million birth weight (BW) and weaning weight (WW) records, 3.4 million post-weaning gain (PWG) records, and genotypes for 52k animals. A dataset from 2017 was later used that included 335k genotyped animals. The ability to predict future performance of young animals was investigated when using regular BLUP and ssGBLUP. Because of the increasing number of genotyped animals and the high computing cost to invert the genomic relationship matrix (G), the algorithm for proven and young (APY) was used to approximate the inverse of G. The APY uses recursions on a small subset of genotyped animals, called core. We further tested the feasibility of having daily interim genomic predictions for newly-genotyped animals based on SNP effects derived from the previous official ssGBLUP evaluation. In addition, we extended all models used in traditional evaluations to ssGBLUP, and compared genetic trends from traditional BLUP, ssGBLUP, and a multistep method that was implemented for the American Angus genomic evaluation in 2009. A new algorithm to approximate accuracy of GEBV for large genomic... Presentar Todo |
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Palabras claves : |
Algorithm for proven and young; Angus; Genomic selection; Indirect prediction. |
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Asunto categoría : |
L01 Ganadería |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15436/1/Lourenco-et-al-2018-WCGALP.pdf
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Marc : |
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008 2018 bl uuuu u01u1 u #d
100 1 $aLOURENCO, D.
245 $aSingle-step genomic BLUP for national beef cattle evaluation in US$bfrom initial developments to final implementation.$h[electronic resource]
260 $aIn: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018.$c2018
520 $aABSTRACT. The objective of this study was to implement single-step genomic BLUP (ssGBLUP) for national Angus cattle evaluation in the US. National evaluations include a variety of models with several linear and categorical traits, maternal effects, multibreed data, and a large number of genotyped animals. For the initial investigation, we used a dataset from 2014 that comprised over 8 million animals, 6 million birth weight (BW) and weaning weight (WW) records, 3.4 million post-weaning gain (PWG) records, and genotypes for 52k animals. A dataset from 2017 was later used that included 335k genotyped animals. The ability to predict future performance of young animals was investigated when using regular BLUP and ssGBLUP. Because of the increasing number of genotyped animals and the high computing cost to invert the genomic relationship matrix (G), the algorithm for proven and young (APY) was used to approximate the inverse of G. The APY uses recursions on a small subset of genotyped animals, called core. We further tested the feasibility of having daily interim genomic predictions for newly-genotyped animals based on SNP effects derived from the previous official ssGBLUP evaluation. In addition, we extended all models used in traditional evaluations to ssGBLUP, and compared genetic trends from traditional BLUP, ssGBLUP, and a multistep method that was implemented for the American Angus genomic evaluation in 2009. A new algorithm to approximate accuracy of GEBV for large genomic data was also developed. On average, the increase in ability to predict future performance, for BW, WW, and PWG, with ssGBLUP was 25% in the 2014 data and 36% in the 2017 data, compared to the traditional BLUP. The ssGBLUP with APY was as accurate as the regular ssGBLUP when the number of core animals was at least 10,000, independently of which animals were in the core group. Interim predictions derived from ssGBLUP provided accurate genomic values for newly-genotyped animals. Genetic trends for ssGBLUP and BLUP were similar, revealing overestimation in multistep evaluations, especially for traits with less phenotypes. Single-step GBLUP became a reality for American Angus evaluation and its implementation process resulted in successful updates in methodology, making this approach mature for national beef cattle evaluation. Keywords: algorithm for proven and young, Angus, genomic selection, indirect prediction.
653 $aAlgorithm for proven and young
653 $aAngus
653 $aGenomic selection
653 $aIndirect prediction
700 1 $aTSURUTA, S.
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700 1 $aMASUDA, Y.
700 1 $aAGUILAR, I.
700 1 $aLEGARRA, A.
700 1 $aMILLER, S.
700 1 $aMOSER, D.
700 1 $aMISZTAL, I.
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