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142. | | 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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143. | | 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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144. | | CIAPPESONI, G.; NAVAJAS, E.; BAPTISTA, R.; AGUILAR, I.; PERAZA, P.; CARRACELAS, B.; DE BARBIERI, I. Proyecto SMARTER. INIA ya está en el Mundial de la Genética Ovina. Producción Animal. Revista INIA Uruguay, Marzo 2022, no.68, p.15-18. (Revista INIA; 68).Biblioteca(s): INIA Las Brujas. |
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149. | | 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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150. | | NAVAJAS, E.; RAVAGNOLO, O.; AGUILAR, I.; CIAPPESONI, G.; PERAZA, P.; DALLA RIZZA, M.; MONTOSSI, F. Selección genómica animal: quién, cómo y dónde. 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. 17-19 (INIA Serie Actividades de Difusión; 702) INIA TacuarembóBiblioteca(s): INIA Tacuarembó. |
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151. | | 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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152. | | LADO, B.; VÁZQUEZ, D.; QUINCKE, M.; SILVA, P.; AGUILAR, I.; GUTIÉRREZ, L. Resource allocation optimization with multi-trait genomic prediction for bread wheat (Triticum aestivum L.) baking quality. [Original article]. Theoretical and Applied Genetics, 1 December 2018, Volume 131, Issue 12, pp. 2719-2731. OPEN ACCESS. Article history: Received: 29 January 2018 / Accepted: 10 September 2018 / Published online: 19 September 2018.
Supplementary materials.
Acknowledgements: We express our appreciation for the effort of the technical personnel of INIA La...Biblioteca(s): INIA Las Brujas. |
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153. | | 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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154. | | MISZTAL, I.; AGUILAR, I.; LEGARRA, A.; JOHNSON, D.; TSURUTA, S.; LAWLOR, T. J. A unified approach to utilize phenotypic, full pedigree, and genomic information for genetic evaluation. Volume Methods and tools: Software and bioinformatics - Lecture Sessions, 0050. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 9., Leipzig, Germany, August 1-6, 2010. p. 0050. Acknowledgements: This study was partially funded by the Holstein Association, Smithfield Premium Genetics, and AFRI grants 2009-65205-05665 and 2010-65205-20366 from the USDA NIFA Animal Genome Program.Biblioteca(s): INIA Las Brujas. |
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156. | | FRAGOMENI, B.O.; LOURENCO, D.A.L.; TSURUTA, S.; MASUDA, Y.; AGUILAR, I.; MISZTAL, I. Use of genomic recursions and algorithm for proven and young animals for single-step genomic BLUP analyses - a simulation study. Journal of Animal Breeding and Genetics, 2015, v.132, no.5, p. 340-345.Biblioteca(s): INIA Las Brujas. |
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157. | | AGUILAR, I.; MISZTAL, I.; JOHNSON, D. L.; LEGARRA, A.; TSURUTA, S.; LAWLOR, T. J. Uso de información genómica en evaluaciones genéticas. Agrociencia Uruguay, 2010, v. 14, no. 3, p. 43-47. Agrociencia, Nro especial: Congreso Asociación Uruguaya de Producción Animal, 3., 4-5 Noviembre 2010, Montevideo, UY: INIA, Facultad de Agronomía, SMVU.Biblioteca(s): INIA Las Brujas. |
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158. | | LOURENCO, D.A.L.; MISZTAL, I.; TSURUTA, S.; AGUILAR, I.; LAWLOR, T.J.; FORNI, S.; WELLER, J.I. Are evaluations on young genotyped animals benefiting from the past generations?. Journal of Dairy Science, 2014, v.97, no.6, p.3930-3942. OPEN ACCESS Article history: Received November 26, 2013. // Accepted February 11, 2014. OPEN ACCESSBiblioteca(s): INIA Las Brujas. |
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159. | | MOTTA, R. R.; SILVA, F. F.; LOPES, P. S.; TEMPELMAN, R. J.; SOLLERO, B. P.; AGUILAR, I.; CARDOSO, F. F. Analyses of reaction norms reveal new chromosome regions associated with tick resistance in cattle. Animal, 2018, volume 12, Issue 2, pages 205-214. OPEN ACCESS. doi: https://doi.org/10.1017/S1751731117001562 Article history: Received 12 December 2016; Accepted 22 May 2017; Published online: 13 July 2017.
Corresponding author: R.R. Mota, Gembloux Agro-Bio Tech Faculty, TERRA Teaching and Research Centre, University of Liège, B-5030 Gembloux,...Biblioteca(s): INIA Las Brujas. |
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160. | | LEMA, O.M.; BRITO, G.; CLARIGET, J.; PEREZ, E.; LA MANNA, A.; RAVAGNOLO, O.; AGUILAR, I.; MONTOSSI, F. Dos años de evaluación de ganancia diaria invernal de terneros con paternidad conocida sobre la recría y terminación.[Presentación oral]. In: CONGRESO ARGENTINO DE PRODUCCIÓN ANIMAL, 38., 2015. Resúmenes. Santa Rosa, La Pampa, AR: ASAS/AAPA, 2015Biblioteca(s): INIA Treinta y Tres. |
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Registros recuperados : 223 | |
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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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