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| Registros recuperados : 223 | |
| 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. | | 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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| 165. | | 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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| 166. | | 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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| 167. | | 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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| 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. | | 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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| 170. | | 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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| 171. | | 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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| 172. | | 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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| 173. | | 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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| 175. | | 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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| 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. | | 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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| 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.; CANTET, R.J.C.; MISZTAL, I. Quality control of genotypes using heritability estimates of gene content. Volume Genetic Improvement Programs: Selection using molecular information (Posters), 471. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.471.| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 223 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha actual : |
21/02/2014 |
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Actualizado : |
18/12/2018 |
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Tipo de producción científica : |
Artículos Indexados |
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Autor : |
MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LOURENÇO, D. A. L.; FRAGOMENI, B.; LEGARRA, A.; AGUILAR, I.; LAWLOR, T. J. |
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Afiliación : |
IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay. |
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Título : |
Single-step genomic evaluations with 570K genotyped animals in US Holsteins. |
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Fecha de publicación : |
2015 |
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Fuente / Imprenta : |
Interbull Bulletin, 2015, v. 49, p. 85-89. |
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Idioma : |
Inglés |
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Contenido : |
ABSTRACT.
The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a large number of genotyped animals. MenosABSTRACT.
The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a lar... Presentar Todo |
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Palabras claves : |
APY; SSGBLUP; VALIDATION. |
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Asunto categoría : |
-- |
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URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/12203/1/1382-2378-1-PB.pdf
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Marc : |
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100 1 $aMASUDA, Y.
245 $aSingle-step genomic evaluations with 570K genotyped animals in US Holsteins.$h[electronic resource]
260 $c2015
520 $aABSTRACT. The objectives of this study were to implement and evaluate the ?Algorithm for proven and Young? (APY) for inversion of the genomic relationship matrix (G) in single-step genomic BLUP (ssGBLUP). Phenotypic data included 11,626,576 final scores on 7,093,380 US Holsteins and genotypes were available for 569,404 animals. Daughter deviations for young genotyped bulls with no classified daughters in 2009 but with at least 30 classified daughters in 2014 were computed using BLUP with all the phenotypes and pedigrees. Genomic predictions (GEBV) were obtained by ssGBLUP using phenotypes up to 2009. We calculated the G inverse with APY based on genomic recursions on a subset of ?base? animals. We tested several subsets including 9,406 bulls with at least 1 daughter, 9,046 bulls and 1052 dams, 9,046 bulls and 7,422 classified cows, and random samples of 5,000, 10,000, 15,000, 20,000, and 30,000 animals. Validation reliability was calculated as R2 with a linear regression of daughter deviations on GEBV for young genotyped bulls. The reliabilities were 0.39 with 5,000 randomly chosen base-animals, 0.45 with base-animals including bulls and cows, and 0.44 with the remaining subsets. Setting up the G inverse for all the genotypes with 10,000 base-animals took 1.3 hours and 57GB of memory. Genomic predictions with G inverse are accurate when the number of base animals is at least 10,000. Single-step genomic BLUP using the G inverse via APY is applicable to populations with a large number of genotyped animals.
653 $aAPY
653 $aSSGBLUP
653 $aVALIDATION
700 1 $aMISZTAL, I.
700 1 $aTSURUTA, S.
700 1 $aLOURENÇO, D. A. L.
700 1 $aFRAGOMENI, B.
700 1 $aLEGARRA, A.
700 1 $aAGUILAR, I.
700 1 $aLAWLOR, T. J.
773 $tInterbull Bulletin, 2015$gv. 49, p. 85-89.
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