Plant & Animal Genomes XIII Conference Plant & Animal Genomes XIII ConferenceJanuary 15-19, 2005
Town & Country Convention Center
San Diego, CA
Takeshi Hayashi , Takashi Awata
Many traits such as coat color and some behavioral properties in animals are recorded in discrete categories. Such categorical traits are usually analyzed with the threshold model, which assumes a latent continuous variable, called the liability, underlying a categorical trait. The categorical phenotype and the liability are linked through the fixed thresholds, where monotonic relationship between the phenotype and the liability is assumed. However, phenotypes of some categorical traits are purely nominal and not ordinal, then the threshold model is not applicable. In this study we developed an interval mapping method for categorical traits with more than two categories without assuming the liability. We considered that the probability of the phenotype of an individual falling in each of the categories depended on covariates including the genotypes of putative loci affecting a trait. This probability was modeled using a polychotomous logistic model, in which the log-odds for each category relative to the reference category followed a linear model. Based on the model, the interval mapping using a maximum likelihood method was applied to the analysis of categorical traits, estimating the genotype of the putative locus by the genotypes of flanking markers for each individual. The power of detecting loci affecting a trait was evaluated for the developed method with simulated F2 data, where two chromosomes with two loci affecting a trait on each chromosome were assumed and 300 F2 individuals were generated. As a result, the method showed high efficiency in detecting the true association between genomic regions and phenotypes.