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Biblioteca (s) : |
INIA Las Brujas. |
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Fecha : |
27/08/2020 |
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Actualizado : |
27/08/2020 |
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Tipo de producción científica : |
Artículos en Revistas Indexadas Internacionales |
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Autor : |
MACEDO, F.; CHRISTENSEN, O. F.; ASTRUC, J.M.; AGUILAR, I.; MASUDA, Y.; LEGARRA, A. |
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Afiliación : |
FERNANDO LIBER MACEDO, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; GenPhySE, Castanet Tolosan, France; OLE F. CHRISTENSEN, Center for Quantitative Genetics and Genomics, Tjele, Denmark; JEAN-MICHEL ASTRUC, Institut de l’Elevage, Castanet Tolosan, France; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; YUTAKA MASUDA, Department of Animal and Dairy Science, University of Georgia, Athens, GA, USA; ANDRÉS LEGARRA, GenPhySE, INRAE, Castanet Tolosan, France. |
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Título : |
Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups. |
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Fecha de publicación : |
2020 |
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Fuente / Imprenta : |
Genetics, Selection, Evolution : GSE, 12 August 2020, Volume 52, Issue 1, Page 47. OPEN ACCESS. DOI: https://doi.org/10.1186/s12711-020-00567-1 |
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ISSN : |
1297-9686 |
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DOI : |
10.1186/s12711-020-00567-1 |
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Idioma : |
Inglés |
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Notas : |
Article history: Received 03 March 2020; Accepted 04 August 2020; Published 12 August 2020. |
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Contenido : |
Abstract
BACKGROUND: Bias has been reported in genetic or genomic evaluations of several species. Common biases are systematic differences between averages of estimated and true breeding values, and their over- or under-dispersion. In addition, comparing accuracies of pedigree versus genomic predictions is a difficult task. This work proposes to analyse biases and accuracies in the genetic evaluation of milk yield in Manech Tête Rousse dairy sheep, over several years, by testing five models and using the estimators of the linear regression method. We tested models with and without genomic information [best linear unbiased prediction (BLUP) and single-step genomic BLUP (SSGBLUP)] and using three strategies to handle missing pedigree [unknown parent groups (UPG), UPG with QP transformation in the [Formula: see text] matrix (EUPG) and metafounders (MF)]. METHODS: We compared estimated breeding values (EBV) of selected rams at birth with the EBV of the same rams obtained each year from the first daughters with phenotypes up to 2017. We compared within and across models. Finally, we compared EBV at birth of the rams with and without genomic information. RESULTS: Within models, bias and over-dispersion were small (bias: 0.20 to 0.40 genetic standard deviations; slope of the dispersion: 0.95 to 0.99) except for model SSGBLUP-EUPG that presented an important over-dispersion (0.87). The estimates of accuracies confirm that the addition of genomic information increases the accuracy of EBV in young rams. The smallest bias was observed with BLUP-MF and SSGBLUP-MF. When we estimated dispersion by comparing a model with no markers to models with markers, SSGBLUP-MF showed a value close to 1, indicating that there was no problem in dispersion, whereas SSGBLUP-EUPG and SSGBLUP-UPG showed a significant under-dispersion. Another important observation was the heterogeneous behaviour of the estimates over time, which suggests that a single check could be insufficient to make a good analysis of genetic/genomic evaluations. CONCLUSIONS: The addition of genomic information increases the accuracy of EBV of young rams in Manech Tête Rousse. In this population that has missing pedigrees, the use of UPG and EUPG in SSGBLUP produced bias, whereas MF yielded unbiased estimates, and we recommend its use. We also recommend assessing biases and accuracies using multiple truncation points, since these statistics are subject to random variation across years. MenosAbstract
BACKGROUND: Bias has been reported in genetic or genomic evaluations of several species. Common biases are systematic differences between averages of estimated and true breeding values, and their over- or under-dispersion. In addition, comparing accuracies of pedigree versus genomic predictions is a difficult task. This work proposes to analyse biases and accuracies in the genetic evaluation of milk yield in Manech Tête Rousse dairy sheep, over several years, by testing five models and using the estimators of the linear regression method. We tested models with and without genomic information [best linear unbiased prediction (BLUP) and single-step genomic BLUP (SSGBLUP)] and using three strategies to handle missing pedigree [unknown parent groups (UPG), UPG with QP transformation in the [Formula: see text] matrix (EUPG) and metafounders (MF)]. METHODS: We compared estimated breeding values (EBV) of selected rams at birth with the EBV of the same rams obtained each year from the first daughters with phenotypes up to 2017. We compared within and across models. Finally, we compared EBV at birth of the rams with and without genomic information. RESULTS: Within models, bias and over-dispersion were small (bias: 0.20 to 0.40 genetic standard deviations; slope of the dispersion: 0.95 to 0.99) except for model SSGBLUP-EUPG that presented an important over-dispersion (0.87). The estimates of accuracies confirm that the addition of genomic information increases the accuracy of... Presentar Todo |
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Palabras claves : |
Animal experiment; Animal model; Dairy sheep; Genetic marker. |
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Asunto categoría : |
L10 Genética y mejoramiento animal |
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URL : |
https://gsejournal.biomedcentral.com/track/pdf/10.1186/s12711-020-00567-1
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Marc : |
LEADER 03420naa a2200265 a 4500
001 1061282
005 2020-08-27
008 2020 bl uuuu u00u1 u #d
022 $a1297-9686
024 7 $a10.1186/s12711-020-00567-1$2DOI
100 1 $aMACEDO, F.
245 $aBias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups.$h[electronic resource]
260 $c2020
500 $aArticle history: Received 03 March 2020; Accepted 04 August 2020; Published 12 August 2020.
520 $aAbstract BACKGROUND: Bias has been reported in genetic or genomic evaluations of several species. Common biases are systematic differences between averages of estimated and true breeding values, and their over- or under-dispersion. In addition, comparing accuracies of pedigree versus genomic predictions is a difficult task. This work proposes to analyse biases and accuracies in the genetic evaluation of milk yield in Manech Tête Rousse dairy sheep, over several years, by testing five models and using the estimators of the linear regression method. We tested models with and without genomic information [best linear unbiased prediction (BLUP) and single-step genomic BLUP (SSGBLUP)] and using three strategies to handle missing pedigree [unknown parent groups (UPG), UPG with QP transformation in the [Formula: see text] matrix (EUPG) and metafounders (MF)]. METHODS: We compared estimated breeding values (EBV) of selected rams at birth with the EBV of the same rams obtained each year from the first daughters with phenotypes up to 2017. We compared within and across models. Finally, we compared EBV at birth of the rams with and without genomic information. RESULTS: Within models, bias and over-dispersion were small (bias: 0.20 to 0.40 genetic standard deviations; slope of the dispersion: 0.95 to 0.99) except for model SSGBLUP-EUPG that presented an important over-dispersion (0.87). The estimates of accuracies confirm that the addition of genomic information increases the accuracy of EBV in young rams. The smallest bias was observed with BLUP-MF and SSGBLUP-MF. When we estimated dispersion by comparing a model with no markers to models with markers, SSGBLUP-MF showed a value close to 1, indicating that there was no problem in dispersion, whereas SSGBLUP-EUPG and SSGBLUP-UPG showed a significant under-dispersion. Another important observation was the heterogeneous behaviour of the estimates over time, which suggests that a single check could be insufficient to make a good analysis of genetic/genomic evaluations. CONCLUSIONS: The addition of genomic information increases the accuracy of EBV of young rams in Manech Tête Rousse. In this population that has missing pedigrees, the use of UPG and EUPG in SSGBLUP produced bias, whereas MF yielded unbiased estimates, and we recommend its use. We also recommend assessing biases and accuracies using multiple truncation points, since these statistics are subject to random variation across years.
653 $aAnimal experiment
653 $aAnimal model
653 $aDairy sheep
653 $aGenetic marker
700 1 $aCHRISTENSEN, O. F.
700 1 $aASTRUC, J.M.
700 1 $aAGUILAR, I.
700 1 $aMASUDA, Y.
700 1 $aLEGARRA, A.
773 $tGenetics, Selection, Evolution : GSE, 12 August 2020, Volume 52, Issue 1, Page 47. OPEN ACCESS. DOI: https://doi.org/10.1186/s12711-020-00567-1
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INIA Las Brujas (LB) |
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| Registros recuperados : 34 | |
| 1. |  | MACEDO, F.; NAVAJAS, E. Heredabilidad genómica en caracteres de canal para la raza Hereford: resultados preliminares. GGM 20 - COMUNICACIONES LIBRES - GGM. GENÓMICA Y GENÉTICA MOLECULAR In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p.264| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 3. | | GOLDBERG, V.; MACEDO, F.; CIAPPESONI, G. SNP genotyping for parentage identification in a Merino nucleus and in a commercial Highlander flock. Volume Electronic Poster Session - Genetic Gain - Genotyping & Phenotyping Strategies, , 359. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018, 359.| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 6. | | GOLDBERG, V.; MACEDO, F.; PIERUCCIONI, F.; NAVAJAS, E.; CIAPPESONI, G. Diagnóstico para la presencia de cuernos en ovinos Merino a través del uso de herramientas genómicas. GGM 14 - COMUNICACIONES LIBRES - GGM. GENÓMICA Y GENÉTICA MOLECULAR In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 261| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 8. | | PIERUCCIONI, F.; MACEDO, F.; CORREA, O.; CIAPPESONI, G.; NAVAJAS, E. Estudio preliminar de asociación entre marcadores SNP y conteo de huevos por gramo en los ovinos criollos del Parque Nacional de San Miguel en Uruguay. [Resumen]. Congreso de la Asociación Latinoamericana de Producción Animal, 24.; Congreso de la Sociedad Chilena de Producción Animal, 40., Puerto Varas, Chile, 9 al 13 noviembre 2015. ln: Reunión ALPA (24., Puerto Varas, Chile). Resúmenes. Puerto Varas (Chile): ALPA, 2015. p. 758| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 12. | | CIAPPESONI, G.; GOLDBERG, V.; MACEDO, F.; ARMSTRONG, E.; GIMENO, D. Evaluaciones genéticas y uso de marcadores moleculares en ovinos. 2 - SIMPOSIOS "MEJORA GENÉTICA EN PRODUCCIÓN Y CALIDAD DE CARNE EN ESPECIES DE INTERÉS ECONÓMICO" In: JOURNAL OF BASIC & APPLIED GENETICS, 2016, Vol.27, Iss. 1 (Supp.). XVI LATIN AMERICAN CONGRESS OF GENETICS, IV CONGRESS OF THE URUGUAYAN SOCIETY OF GENETICS, XLIX ANNUAL MEETING OF THE GENETICS SOCIETY OF CHILE, XLV ARGENTINE CONGRESS OF GENETICS, 9-12 October 2016. PROCEEDINGS. Montevideo (Uruguay): SAG, 2016. p. 28| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 16. | | MACEDO, F.; PIERUCCIONI, F.; VILLANUEVA, B.; NAVAJAS, E. Uso de información genómica para optimizar apareamientos en ovinos criollos. [Resumen]. Congreso de la Asociación Latinoamericana de Producción Animal, 24.; Congreso de la Sociedad Chilena de Producción Animal, 40., Puerto Varas, Chile, 9 al 13 noviembre 2015. ln: Reunión ALPA (24., Puerto Varas, Chile). Resúmenes. Puerto Varas (Chile): ALPA, 2015. p. 938.| Tipo: Abstracts/Resúmenes |
| Biblioteca(s): INIA Las Brujas. |
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| 18. | | NAVAJAS, E.; MACEDO, F.; LEMA, O.M.; LUZARDO, S.; AGUILAR, I. Accuracy of genomic predictions for carcass and meat quality traits in the Uruguayan Hereford breed. Volume Species - Bovine (beef) 1, p. 636. 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. Acknowledgements: This work was supported by the Agencia Nacional de Investigación e Innovación (ANII) (grants RTS_1_2012_1_3489 and FMV_1_2011_1_6671), Instituto Nacional de Investigación Agropecuaria (INIA), Sociedad de Criadores de...| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 19. | | PRAVIA, M.I.; NAVAJAS, E.; MACEDO, F.; CLARIGET, J.M.; LUZARDO, S. Association between feed efficiency and carcass and meat quality traits in Hereford steers. Volume Electronic Poster Session - Biology - Feed Intake and Efficiency 1, p. 604. In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 11., Aotea Centre Auckland, New Zealand: WCGALP, ICAR, 11-16 feb 2018. Acknowledgements: This work was supported by the Agencia Nacional de Investigación e Innovación (ANII) (grant RTS_1_2012_1_3489), Instituto Nacional de Investigación Agropecuaria (INIA), Sociedad de Criadores de Hereford (SCH), Instituto...| Tipo: Trabajos en Congresos/Conferencias |
| Biblioteca(s): INIA Las Brujas. |
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| 20. | | MACEDO, F.; CHRISTENSEN, O. F.; ASTRUC, J.M.; AGUILAR, I.; MASUDA, Y.; LEGARRA, A. Bias and accuracy of dairy sheep evaluations using BLUP and SSGBLUP with metafounders and unknown parent groups. Genetics, Selection, Evolution : GSE, 12 August 2020, Volume 52, Issue 1, Page 47. OPEN ACCESS. DOI: https://doi.org/10.1186/s12711-020-00567-1 Article history: Received 03 March 2020; Accepted 04 August 2020; Published 12 August 2020.| Tipo: Artículos en Revistas Indexadas Internacionales | Circulación / Nivel : Internacional - -- |
| Biblioteca(s): INIA Las Brujas. |
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| Registros recuperados : 34 | |
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