Bayesian Segregation Analysis of Somatic Cell Scores of Ontario Holstein Cattle

¹ Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Ontario, Canada, N1G 2W1
² Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Ontario, Canada, N1G 2W1 and ANAFI Via Bergamo 292, 26100 Cremona, Italy
³ Centre for Genetic Improvement of Livestock, Department of Animal and Poultry Science, University of Guelph, Ontario, Canada, N1G 2W1 and International Livestock Research Institute, P.O. Box 30709, Nairobi, Kenya

Bayesian segregation analysis using a Gibbs sampling approach was applied to four sets of simulated data and one set of field data to detect evidence of major genes affecting the evaluated trait. The substitution effect of a major gene and its allelic frequency were estimated for each set of data. For two datasets simulated with a model with no major gene effect, the resulting estimates of polygenic variance and heritability agreed with the simulated values and tests for the presence of a major gene were not significant. Analyses of two sets of data simulated with a major gene produced posterior distributions that gave significant evidence of major gene effects but underestimated the substitution values of the major gene. The segregation analysis of field data suggested that a major gene significantly affected somatic cell score (SCS) in the population of Ontario Holstein cattle. The estimated heritability of SCS was approximately 0.16. The major gene variance accounted for about 17% of the total genetic variance and the point estimate of the frequency of the allele having a positive effect on SCS was 0.30. However, the precision of these estimates is questionable based on the simulation results. The effect of the major gene may be underestimated.

Key Words: major genes • somatic cell scores • Bayesian segregation analysis

Submitted on April 10, 2001
Accepted on August 14, 2001