Fecha/hora: 04/06/2024 11:33:40

Biblioteca(s): | INIA Las Brujas.
Tipo de la producción científica: | Trabajos en Congresos/Conferencias
Fecha corriente: | 31/03/2021
Fecha de la última actualización: | 31/03/2021
Autoria: | MOTA, R.R.; TEMPELMAN, R.J.; FERNANDO F CARDOSO; AGUILAR, I.; LOPES, P.S.
Afiliación: | RODRIGO REIS MOTA, Michigan State University; Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil; ROBERT J TEMPELMAN, Michigan State University; CARDOSO, F.F., Embrapa Southern Region Animal Husbandry, Bagé, Rio Grande do Sul, Brazil; IGNACIO AGUILAR GARCIA, INIA (Instituto Nacional de Investigación Agropecuaria), Uruguay; PAULO S LOPES, Universidade Federal de Viçosa, Viçosa, Minas Gerais, Brazil.
Título: | Genomic wide-selection for tick resistance in Hereford and Braford cattle via reaction norm models.
Complemento del título: | Volume Species Breeding: Beef cattle, 235.
Año de publicación: | 2014
Fuente/Imprenta: | In: Proceedings of the World Congress on Genetics Applied to Livestock Production, 10., Vancouver, BC, Canada, August 17-22, 2014. p.235.
Idioma: | Inglés
Notas: | Acknowledgments: The authors thank Delta G Connection by providing the data used in this research; Embrapa Southern Region Animal Husbandry and Michigan State University for theoretical and technical support; CAPES, CNPq and FAPEMIG by granting the scholarship.

Contenido:

ABSTRACT.
The objective of this study was to compare a conventional genomic model (GBLUP) and its extension to a linear reaction norm model (GLRNM) specifying genotype by environment interaction (G*E) for tick resistance in Brazilian cattle. Tick counts (TC) from 4,363 Hereford and Braford cattle from 146 contemporary groups (CG) were available of which 3,591 animals had BovineSNP50 Illumina v2 BeadChip genotypes. The reaction norm covariate was based on CG estimates of TC from a first-step model. Analysis was conducted based on adapting the single step GBLUP/REML procedure. Five-fold cross validation based on K-means and random partitioning was used to compare the fit of the two models. Cross validation correlations were strong and not significantly different between models for either partitioning strategy. Nevertheless, it seems apparent that G*E for tick infestation exists and can captured by GLRNM models.

Palabras-Clave: | Cross validation; Single-step; Tick counts.
Categoría del tema: | L10 Genética y mejoramiento animal
URL: | http://www.ainfo.inia.uy/digital/bitstream/item/15448/1/Mota-et-al.-2014.-WCGALP.pdf
Registro original: | INIA Las Brujas (LB)
Ejemplares: | LB - (102603-1) - PXI - PC - DD - WCGALP/10/2014 -  -  - DIS