title: Effects of sex and age on genotype x environment interaction for beef cattle body weight studied using reaction norm models.
abstract: The interest in the effect of genotype × environment interaction is increasing because animal breeding programs have become geographically broader. Climate changes in the next decades are also expected to challenge the present breeding goals, increasing the importance of environmental sensitivity. The aim of this work was to analyze genotype × environment interaction effect on cattle BW using the environmental sensitivity predicted by random regression reaction norm models, including sex and age effects as additional dimensions in the study. Genetic parameters were estimated for adjusted BW of Brazilian Nelore cattle at different ages (120, 210, 365, and 450 d), using linear polynomials for random regression analysis. The analyses with sex as a fixed effect (total analyses) were compared with those with sex-separated progenies (male and female progeny analyses, respectively). (Co)variance components were estimated and breeding values calculated EPD. The results showed important differences in reaction norm model genetic parameter estimates according to different age and sex analyses. The results confirmed the presence of an important genotype × environment × sex × age interaction for Nelore cattle BW. The patterns in these results lead to a revision of the importance of sexual and developmental factors on plasticity and adaptation concepts.
authors: Department of Genetics, Faculdade de Medicina de Ribeirão Preto, Universidade de São Paulo, 14049-900, Ribeirão Preto, São Paulo, Brazil. newton.pegolo@gmail.com
authors: N T
authors: NT
authors: Pegolo
authors: L G
authors: LG
authors: Albuquerque
authors: R B
authors: RB
authors: Lôbo
authors: H N
authors: HN
authors: de Oliveira
mesh_terms: D000367:Age Factors; D000818:Animals; D001835:Body Weight / Q000235:genetics / Q000502:physiology*; D001938:Brazil; D002417:Cattle / Q000235:genetics / Q000502:physiology*; D004777:Environment; D005260:Female; D014644:Genetic Variation; D008297:Male; D008957:Models, Genetic; D012044:Regression Analysis; D012737:Sex Factors