Model for fitting longitudinal traits subject to threshold response applied to genetic evaluation for heat tolerance

• Published in: Genetics selection evolution (Paris) Vol. 41; no. 1; p. 10
• Main Authors: Sánchez, Juan Pablo, Rekaya, Romdhane, Misztal, Ignacy
• Format: Journal Article
• Language: English
• Published: London BioMed Central 14.01.2009; BioMed Central Ltd; BMC
• Subjects: Agriculture; Animal breeding; Animal Genetics and Genomics; Animals; Animals, Domestic - genetics; Animals, Domestic - physiology; Bayesian analysis; Biomedical and Life Sciences; Breeding; Computer Simulation; Environmental aspects; Evolutionary Biology; Genetic aspects; Genetic diversity; Genetics; Genotype; Genotypes; Heat stress; Heat tolerance; Hot Temperature; Independent variables; Life Sciences; Mathematical models; Methods; Model testing; Models, Genetic; Multilevel analysis; Phenotype; Quantitative Trait, Heritable; Stress, Physiological; United States; Spain; Gibbs Sampler; Variance Matrix; Conditional Posterior Distribution; Marginal Posterior Distribution; Additive Genetic Effect
• ISSN: 1297-9686; 0999-193X; 1297-9686
• DOI: 10.1186/1297-9686-41-10

A semi-parametric non-linear longitudinal hierarchical model is presented. The model assumes that individual variation exists both in the degree of the linear change of performance (slope) beyond a particular threshold of the independent variable scale and in the magnitude of the threshold itself; these individual variations are attributed to genetic and environmental components. During implementation via a Bayesian MCMC approach, threshold levels were sampled using a Metropolis step because their fully conditional posterior distributions do not have a closed form. The model was tested by simulation following designs similar to previous studies on genetics of heat stress. Posterior means of parameters of interest, under all simulation scenarios, were close to their true values with the latter always being included in the uncertain regions, indicating an absence of bias. The proposed models provide flexible tools for studying genotype by environmental interaction as well as for fitting other longitudinal traits subject to abrupt changes in the performance at particular points on the independent variable scale.