Fecha/hora: 09/06/2024 02:48:48

Biblioteca(s): | INIA Las Brujas.
Fecha corriente: | 26/11/2015
Fecha de la última actualización: | 29/01/2020
Autoria: | 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.
Afiliación: | D. A. L. LOURENCO, Universidad de Georgia (UG); SHOGO TSURUTA, Universidad de Georgia (UG); B. O. FRAGOMENI, Universidad de Georgia (UG); Y. MASUDA, Universidad de Georgia (UG); IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; A. LEGARRA, INRA (Institut National de la Recherche Agronomique); J. K. BERTRAND, Universidad de Georgia (UG); T. S. AMEN, Angus Genetics Inc.; L. WANG, Angus Genetics Inc.; D. W. MOSER, Angus Genetics Inc.; IGNACY MISZTAL, Universidad de Georgia (UG).
Título: | Genetic evaluation using single-step genomic best linear unbiased predictor in American Angus.(*)
Año de publicación: | 2015
Fuente/Imprenta: | Journal of Animal Science, 2015, v. 93, p. 2653-2662. Published June 25, 2015. OPEN ACCESS.
DOI: | 10.2527/jas.2014-8836
Idioma: | Inglés
Notas: | (*) 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 National Institute of Food and Agriculture. We gratefully acknowledge the very helpful comments by the two anonymous reviewers.

Contenido:

ABSTRACT.

Predictive ability of genomic EBV when using single-step genomic BLUP (ssGBLUP) in Angus cattle was investigated. Over 6 million records were available on birth weight (BiW) and weaning weight  (WW), almost 3.4 million on postweaning gain (PWG), and over 1.3 million on calving ease (CE). Genomic information was available on, at most, 51,883 animals,
which included high and low EBV accuracy animals. Traditional EBV was computed by BLUP and genomic EBV by ssGBLUP and indirect prediction based on SNP effects was derived from ssGBLUP; SNP effects were calculated based on the following reference populations: ref_2k (contains top bulls and top cows that had an EBV accuracy for BiW &#8805;0.85), ref_8k (contains all parents that were genotyped), and ref_33k (contains all genotyped animals born up to 2012). Indirect prediction was obtained as direct genomic value (DGV) or as an
index of DGV and parent average (PA). Additionally, runs with ssGBLUP used the inverse of the genomic relationship matrix calculated by an algorithm for proven and young animals (APY) that uses recursions on a small subset of reference animals. An extra reference subset included 3,872 genotyped parents of genotyped animals (ref_4k). Cross-validation was used to assess predictive ability on a validation population of 18,721 animals born in 2013. Computations for growth traits used multiple-trait linear model and, for CE, a bivariate CE?BiW threshold-linear model. With BLUP, predictivities were 0.29, 0.34, 0.23, and 0.12 for BiW, WW, PWG, and CE, respectively. With ssGBLUP and ref_2k, predictivities were 0.34, 0.35, 0.27, and 0.13 for BiW, WW, PWG, and CE, respectively, and with ssGBLUP and ref_33k, predictivities were 0.39, 0.38, 0.29, and 0.13 for BiW, WW, PWG, and CE, respectively. Low predictivity for CE was due to low incidence rate of difficult calving. Indirect predictions with ref_33k were as accurate as with full ssGBLUP. Using the APY and recursions on ref_4k gave 88% gains of full ssGBLUP and using the APY and recursions on ref_8k gave 97% gains of full ssGBLUP. Genomic evaluation in beef cattle with ssGBLUP is feasible while keeping the models (maternal, multiple trait, and threshold) already used in regular BLUP. Gains in predictivity are dependent on the composition of the reference population. Indirect predictions via SNP effects derived from ssGBLUP allow for accurate genomic predictions on young animals, with no advantage of including PA in
the index if the reference population is large. With the APY conditioning on about 10,000 reference animals, ssGBLUP is potentially applicable to a large number of genotyped animals without compromising predictive ability. 

© 2015 American Society of Animal Science. All rights reserved

Palabras-Clave: | BEEF CATTLE; GENETIC RESURSION; INDIRECT PREDICTION.
Thesagro: | GANADO DE CARNE; GENOMIC SELECTION; MEJORAMIENTO GENETICO ANIMAL.
Categoría del tema: | L10 Genética y mejoramiento animal
URL: | http://www.ainfo.inia.uy/digital/bitstream/item/5303/1/Lourenco-et-al-2015-JAS.pdf
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (100869-1) - PXI - AP - DD -  -  -  - DIS