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14 th QTL-MAS Workshop, Poznań University of Life Sciences, Poland 2010The estimation of SNP effects on a binary and a quantitative traitKacper Żukowski 1,∗ , Joanna Szyda 1,21Department of Genetics and Animal Breeding, Wrocław University of Environmental and Life Sciences,Kożuchowska 7, 51-631 Wrocław, Poland2Institute of Natural Sciences, Wrocław University of Environmental and Life Sciences, Norwida 25, 50-375Wrocław, Poland∗ Presenting author: Kacper Żukowski, email: kacper.zukowski@up.wroc.plBackground . The analysis concerns on estimating the effects of Single NucleotidePolymorphisms (SNP) on a binary and a quantitative trait, based on the simulated QTL-MASworkshop data. Moreover, the association between the two traits is considered.Methods. For a quantitative trait a gBLUP model was appliedy = µ + Za + ε , where: y isa quantitative trait, Z is an incidence matrix for SNP effects, a is a vector of random SNPeffects assuminga2⎛ σ⎟ ⎞N⎜0,I with n representing the number of SNPs, ε is a vector of⎝ n ⎠~α2random errors assuming e N( 0, Iσ )~ε. This model was applied for all animals, for affectedanimals only, and for unaffected animals only. Further on, a modification of the gBLUPmodel with SNP effects estimated separately for affected and unaffected animals (CgBLUP)was used: y = µ + Za unaff+ Zaaff+ ε , where aunaffand aaffare random vectors for unaffectedand affected animal respectively, both effects were assumed to be uncorrelated. For a binarytrait a logistic regression model (LOGIT) was used:probability of being affected, β0is an intercept andwith a corresponding column in incidence matrix⎛ p ⎞log ⎜ ⎟ = β0+ β⎝1−p ⎠Z i i, where p is aβirepresents an additive effect of SNP iResults. The most significant SNPs for both traits were found on chromosome 1 andchromosome 3. Two most significant SNPs influencing both, a binary and a quantitative trait:#4480 (22 030 629 bp) and #4491 (22 520 568 bp) were located on chromosome 3.Generally, similar locations were significant for both traits, but no significant SNPs effectswere reported by CgBLUP model.Conclusions. The analysis showed many significant SNPs, one gene located on 22,0-22,5 Mbon chromosome 3 could have influence on a quantitative and a binary trait simultaneously.Zi.38