Abstract

Two approaches to marker assisted complex segregation analysis of halfsib data are presented. In the first alternative, the alleles at the potential QTL are assumed to have fixed effects. The corresponding statistical model is rather complex and does not allow a joint estimation of fixed environmental effects, genetic effects and variance components. In the second approach, the QTL effects are assumed to be random. The resulting statistical model is much less complex, and so are the computational demands. Under this model, fixed effects can be included and both maximum likelihood and residual maximum likelihood estimates of the dispersion parameters can be obtained. Both approaches have been applied to analyze milk production traits with milk protein markers. Their characteristical properties are compared theoretically in the discussion

Henner Simianer, Z. Liu, H. Haussmann

Proceedings of the World Congress on Genetics Applied to Livestock Production, Volume 21. Gene mapping; polymorphisms; disease genetic markers; marker assisted selection; gene expression; transgenes; non-convention, , 264–267, 1994
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