| |
|
|
| Registros recuperados : 34 | |
| 21. |  | 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. |
|    |
| 22. | | 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. |
|  |
| 23. | | 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. |
| |
| 24. | | 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. |
| |
| 25. | | 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. |
| |
| 26. | | LONDOÑO-GIL, M.; LÓPEZ-CORREA, R.; AGUILAR, I.; MAGNABOSCO, C.U.; HIDALGO, J.; BUSSIMAN, F.; BALDI, F.; LOURENCO, D. Strategies for genomic predictions of an indicine multi-breed population using single-step GBLUP. Journal of Animal Breeding and Genetics, 2024. https://doi.org/10.1111/jbg.12882 - [Early view] Article history: Received 22 March 2024, Revised 10 May 2024, Accepted 15 May 2024. -- Corresponding author: Londoño-Gil, M.; Faculdade de Ciências Agrárias e Veterinárias, Universidade Estadual Paulista Júlio de Mesquita Filho, Via de...| Biblioteca(s): INIA Las Brujas. |
| |
| 27. | | LOURENCO, D.; TSURUTA, S.; FRAGOMENI, B.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; MOSER, D.; MISZTAL, I. Single-step genomic BLUP for national beef cattle evaluation in US: from initial developments to final implementation. Volume Species - Bovine (beef) 1, 495. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018.| Biblioteca(s): INIA Las Brujas. |
| |
| 28. | | MASUDA, Y.; MISZTAL, I.; TSURUTA, S.; LOURENÇO, D. A. L.; FRAGOMENI, B.; LEGARRA, A.; AGUILAR, I.; LAWLOR, T. J. Single-step genomic evaluations with 570K genotyped animals in US Holsteins. Interbull Bulletin, 2015, v. 49, p. 85-89.| Biblioteca(s): INIA Las Brujas. |
| |
| 29. | | MASUDA, Y; MISZTAL, I.; LEGARRA, A.; TSURUTA, S.; LOURENCO, D.A.L.; FRAGOMENI, B.O.; AGUILAR, I. Technical note: Avoiding the direct inversion of the numerator relationship matrix for genotyped animals in single-step genomic best linear unbiased prediction solved with the preconditioned conjugate gradient. Journal of Animal Science, 2017, v. 95(1): 49-52. Article history: Received: July 05, 2016; Accepted: Aug 16, 2016; Published: February 2, 2017.
This research was partially funded by the United States Department of Agriculture?s National Institute of Food and Agriculture (Agriculture and...| Biblioteca(s): INIA Las Brujas. |
|  |
| 30. | | LOURENCO, D. A. L.; TSURUTA, S.; FRAGOMENI, B. O.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; BERTRAND, J. K.; AMEN, T. S.; WANG. L.; MOSER, D. W.; MISZTAL, I. Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*) Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS. (*) This study was partially funded by the American Angus Association (St. Joseph, MO), Zoetis (Kalamazoo, MI), and Agriculture and Food Research Initiative Competitive Grants no. 2015-67015-22936 from the U.S. Department of Agriculture?s...| Biblioteca(s): INIA Las Brujas. |
| |
| 31. | | 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. |
| |
| 32. | | 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. |
| |
| 33. | | 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. |
| |
| 34. | | 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. |
| |
| Registros recuperados : 34 | |
|
|
|
|
Registro completo
|
|
Biblioteca (s) : |
INIA Las Brujas. |
|
Fecha actual : |
31/03/2021 |
|
Actualizado : |
31/03/2021 |
|
Tipo de producción científica : |
Trabajos en Congresos/Conferencias |
|
Autor : |
LOURENCO, D.; TSURUTA, S.; FRAGOMENI, B.; MASUDA, Y.; AGUILAR, I.; LEGARRA, A.; MILLER, S.; MOSER, D.; MISZTAL, I. |
|
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. |
|
Título : |
Single-step genomic BLUP for national beef cattle evaluation in US: from initial developments to final implementation. |
|
Complemento del título : |
Volume Species - Bovine (beef) 1, 495. |
|
Fecha de publicación : |
2018 |
|
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. |
|
Idioma : |
Inglés |
|
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 |
|
Palabras claves : |
Algorithm for proven and young; Angus; Genomic selection; Indirect prediction. |
|
Asunto categoría : |
L01 Ganadería |
|
URL : |
http://www.ainfo.inia.uy/digital/bitstream/item/15436/1/Lourenco-et-al-2018-WCGALP.pdf
|
|
Marc : |
LEADER 03286nam a2200253 a 4500
001 1061912
005 2021-03-31
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.
700 1 $aFRAGOMENI, B.
700 1 $aMASUDA, Y.
700 1 $aAGUILAR, I.
700 1 $aLEGARRA, A.
700 1 $aMILLER, S.
700 1 $aMOSER, D.
700 1 $aMISZTAL, I.
Descargar
Esconder MarcPresentar Marc Completo |
|
Registro original : |
INIA Las Brujas (LB) |
|
|
Biblioteca
|
Identificación
|
Origen
|
Tipo / Formato
|
Clasificación
|
Cutter
|
Registro
|
Volumen
|
Estado
|
Volver
|
| Expresión de búsqueda válido. Check! |
|
|
