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Registros recuperados : 81 | |
41. | | LEGARRA, A.; CHRISTENSEN, O. F.; VITEZICA, Z. G.; AGUILAR, I.; MISZTAL, I. Across-breeds ancestral relationships and metafounders for genomic evaluation. Volume Genetic Improvement Programs: Selection using molecular information, 075. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.075. Acknowledgements: This project has been financed by X-Gen and GenSSeq actions from SelGen metaprogram (INRA). We are grateful to the genotoul bioinformatics platform Toulouse Midi-Pyrenees for providing computing resources.Biblioteca(s): INIA Las Brujas. |
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42. | | AGUILAR, I.; TSURUTA, S.; MASUDA, Y.; LOURENCO, D.A.L.; LEGARRA, A.; MISZTAL, I. BLUPF90 suite of programs for animal breeding with focus on genomics. Volume Methods and Tools - Software, p. 751. 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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43. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Correction: Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP (Genetics, selection, evolution : GSE (2022) 54:1 (66)). Genetics, Selection, Evolution : GSE, 2023, Volume 55, Issue 1, Pages 26. OPEN ACCESS. https://doi.org/10.1186/s12711-023-00799-x Article history: Published online 17 April 2023. -- Document: Erratum - Gold Open Access. -- The original article can be found online at https://doi.org/10.1186/s12711-022-00752-4Biblioteca(s): INIA Las Brujas. |
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44. | | MISZTAL, I.; AGUILAR, I.; LOURENCO, D.; MA, L.; STEIBEL, J.P. Emerging issues in genomic selection. Animal Genetics and Genomics. Journal of Animal Science, June 2021, Volume 99, Issue 61, skab092. OPEN ACCESS. Doi: https://doi.org/10.1093/jas/skab092 Article history: Received 23 January 2021; Accepted 26 March 2021; Advance Access publication March 27, 2021.
This is an Open Access article distributed under the terms of the Creative Commons Attribution License...Biblioteca(s): INIA Las Brujas. |
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45. | | FRAGOMENI, B.O.; MISZTAL, I.; LOURENCO, D.L.; AGUILAR, I.; OKIMOTO, R.; MUIR, W.M. Changes in variance explained by top SNP windows over generations for three traits in broiler chicken Frontiers in Genetics, 2014, v.5, no.Oct., Article number 332. OPEN ACCESS. Article history: Published 01 October 2014.Biblioteca(s): INIA Las Brujas. |
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46. | | LOURENÇO, D. A. L.; MISZTAL, I.; TSURUTA, S.; FRAGOMENI, B.; AGUILAR, I.; MASUDA, Y.; MOSER, D. Direct and indirect genomic evaluations in beef cattle. Interbull Bulletin, 2015, v. 49, p.80 - 84.Biblioteca(s): INIA Las Brujas. |
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47. | | CHEN, C.Y.; MISZTAL, I.; AGUILAR, I.; LEGARRA, A.; MUIR, W.M. Effect of different genomic relationship matrices on accuracy and scale. Journal of Animal Science, 2011, v.89, no.9, p.2673-2679. Article history: Received September 29, 2010. / Accepted March 21, 2011.Biblioteca(s): INIA Las Brujas. |
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48. | | AGUILAR, I.; LEGARRA, A.; CARDOSO, F.; MASUDA, Y.; LOURENCO, D.; MISZTAL, I. Frequentist p-values for large-scale-single step genome-wide association, with an application to birth weight in American Angus cattle. (Short Communication) Genetics Selection Evolution, 20 June 2019, v. 51, Issue 1, Article number 28. OPEN ACCESS. Article history: Received: 3 January 2019 // Accepted: 27 May 2019 // Published Online: 20 June 2019.
Funding text: This study was partially funded by the American Angus Association (St. Joseph, MO) and by Agriculture and Food Research...Biblioteca(s): INIA Las Brujas. |
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49. | | AGUILAR, I.; MISZTAL, I.; JOHNSON, D.L.; LEGARRA, A.; TSURUTA, S.; LAWLOR, T.J. Hot topic: A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation of Holstein final score. Journal of Dairy Science, 2010, v. 93, no. 2, p. 743-752. OPEN ACCESS Article history: Received September 14, 2009 / Accepted November 10, 2009 / Published in issue: February 2010.Biblioteca(s): INIA Las Brujas. |
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50. | | MISZTAL, I.; LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; CESARANI, A.; LEGARRA, A. How ssGBLUP became suitable for national dairy cattle evaluations. [668]. Part 37 - Bovine dairy - genetic evaluation methods. 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_668 2757-2760. Article history: Published online: February 9, 2023 -- Corresponding author: I. Misztal, email: ignacy@uga.eduBiblioteca(s): INIA Las Brujas. |
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53. | | TSURUTA, S.; AGUILAR, I.; MISZTAL, I.; LEGARRA, A.; LAWLOR, T. J. Multiple trait genetic evaluation of linear type traits using genomic and phenotypic data in US Holsteins. Volume Genetic improvement programmes: Selection using molecular information - Poster Sessions, 0489. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0489.Biblioteca(s): INIA Las Brujas. |
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55. | | LOURENCO, D.A.L.; MISZTAL, I.; WANG, H.; AGUILAR, I.; TSURUTA, S.; BERTRAND, J.K. Prediction accuracy for a simulated maternally affected trait of beef cattle using different genomic evaluation models. Journal of Animal Science, 2013, v.91, no.9, p.4090-4098. Article history: Published online July 26, 2013.
This study was partially funded by the American Angus Association (St. Joseph, MO) and the USDA Agriculture and Food Research Initiative (Grant no. 2009-65205-05665 from the USDA National...Biblioteca(s): INIA Las Brujas. |
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56. | | MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LEGARRA, A.; VAN RADEN, P.M.; LAWLOR, T.J. Methods to approximate reliabilities in single-step genomic evaluation. Journal of Dairy Science, 2013, v.96, no.1, p.647-654. OPEN ACCESS. Article history: Received April 24, 2012. / Accepted September 18, 2012.Biblioteca(s): INIA Las Brujas. |
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57. | | LOURENCO, D.; TSURUTA, S.; AGUILAR, I.; MASUDA, Y.; BERMANN, M.; LEGARRA, A.; MISZTAL, I. Recent updates in the BLUPF90 software suite. [366]. Part 19 - Methods and tools: software and computing strategies. 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_366 1530-1533. Article history: Published online: February 9, 2023. -- Corresponding author: D. Lourenco, email: danilino@uga.eduBiblioteca(s): INIA Las Brujas. |
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58. | | LOURENCO, D.; LEGARRA, A.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. Single-step genomic evaluations from theory to practice: using snp chips and sequence data in blupf90. Genes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790 Article history: Received: 19 June 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020.
(This article belongs to the Special Issue Genomic Prediction Methods for Sequencing Data):...Biblioteca(s): INIA Las Brujas. |
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59. | | MISZTAL, I.; AGUILAR, I.; TSURUTA, S.; SÁNCHEZ, J.P.; ZUMBACH, B. Studies on heat stress in dairy cattle and pigs. Volume Special topics: Animal breeding and the environmental challenges - Lecture Sessions, 0625. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0625.Biblioteca(s): INIA Las Brujas. |
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60. | | GARCÍA, A.; AGUILAR, I.; LEGARRA, A.; TSURUTA, S.; MISZTAL, I.; LOURENCO, D. Theoretical accuracy for indirect predictions based on SNP effects from single-step GBLUP. Genetics, Selection, Evolution : GSE, 2022, Volume 54, Issue 1, Pages 66. OPEN ACCESS. doi: https://doi.org/10.1186/s12711-022-00752-4 Article history: Received 22 March 2022; Accepted 23 August 2022; Published 27 September 2022.Biblioteca(s): INIA Las Brujas. |
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Registros recuperados : 81 | |
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Registro completo
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Biblioteca (s) : |
INIA Las Brujas. |
Fecha actual : |
24/07/2020 |
Actualizado : |
24/07/2020 |
Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
Circulación / Nivel : |
Internacional - -- |
Autor : |
LOURENCO, D.; LEGARRA, A.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. |
Afiliación : |
DANIELA LOURENCO, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; ANDRÉS LEGARRA, Institut National de la Recherche Agronomique, UMR1388 GenPhySE, 31326 Castanet Tolosan, France; SHOGO TSURUTA, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; YUTAKA MASUDA, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; IGNACY MISZTAL, Department of Animal and Dairy Science, University of Georgia, Athens, GA 30602, USA. |
Título : |
Single-step genomic evaluations from theory to practice: using snp chips and sequence data in blupf90. |
Fecha de publicación : |
2020 |
Fuente / Imprenta : |
Genes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790 |
ISSN : |
2073-4425 |
DOI : |
10.3390/genes11070790 |
Idioma : |
Inglés |
Notas : |
Article history: Received: 19 June 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020.
(This article belongs to the Special Issue Genomic Prediction Methods for Sequencing Data):
https://www.mdpi.com/journal/genes/special_issues/Genomic_Prediction |
Contenido : |
ABSTRACT.
Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data. |
Palabras claves : |
Genome-wide association; Genomic prediction; Genomic selection; SINGLE-STEP GENOMIC BLUP. |
Asunto categoría : |
A50 Investigación agraria |
URL : |
https://www.mdpi.com/2073-4425/11/7/790/pdf
https://www.mdpi.com/2073-4425/11/7/790/review_report
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Marc : |
LEADER 02392naa a2200265 a 4500 001 1061236 005 2020-07-24 008 2020 bl uuuu u00u1 u #d 022 $a2073-4425 024 7 $a10.3390/genes11070790$2DOI 100 1 $aLOURENCO, D. 245 $aSingle-step genomic evaluations from theory to practice$busing snp chips and sequence data in blupf90.$h[electronic resource] 260 $c2020 500 $aArticle history: Received: 19 June 2020 / Revised: 3 July 2020 / Accepted: 6 July 2020 / Published: 14 July 2020. (This article belongs to the Special Issue Genomic Prediction Methods for Sequencing Data): https://www.mdpi.com/journal/genes/special_issues/Genomic_Prediction 520 $aABSTRACT. Single-step genomic evaluation became a standard procedure in livestock breeding, and the main reason is the ability to combine all pedigree, phenotypes, and genotypes available into one single evaluation, without the need of post-analysis processing. Therefore, the incorporation of data on genotyped and non-genotyped animals in this method is straightforward. Since 2009, two main implementations of single-step were proposed. One is called single-step genomic best linear unbiased prediction (ssGBLUP) and uses single nucleotide polymorphism (SNP) to construct the genomic relationship matrix; the other is the single-step Bayesian regression (ssBR), which is a marker effect model. Under the same assumptions, both models are equivalent. In this review, we focus solely on ssGBLUP. The implementation of ssGBLUP into the BLUPF90 software suite was done in 2009, and since then, several changes were made to make ssGBLUP flexible to any model, number of traits, number of phenotypes, and number of genotyped animals. Single-step GBLUP from the BLUPF90 software suite has been used for genomic evaluations worldwide. In this review, we will show theoretical developments and numerical examples of ssGBLUP using SNP data from regular chips to sequence data. 653 $aGenome-wide association 653 $aGenomic prediction 653 $aGenomic selection 653 $aSINGLE-STEP GENOMIC BLUP 700 1 $aLEGARRA, A. 700 1 $aTSURUTA, S. 700 1 $aMASUDA, Y. 700 1 $aAGUILAR, I. 700 1 $aMISZTAL, I. 773 $tGenes, July 2020. Volume 11, Issue 7, Article number 790, Pages 1-32. Open Access. Doi: https://doi.org/10.3390/genes11070790
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