Traditionally, exploration of genetic variance in humans, plants, and livestock species has mostly been limited to the use of additive effects estimated using pedigree data. However, with the development of dense panels of SNPs (Single Nucleotide Polymorphisms), the exploration of genetic variation of complex traits is moving from quantifying the resemblance between family members to the dissection of genetic variation at individual loci. With SNPs we were able to quantify the contribution of additive, dominance, and imprinting variance to the total genetic variance using a SNP regression method. The method was validated in simulated data and applied to three traits (number of teats, backfat and life-time daily gain) in three purebred pig populations. In simulated data, the estimates of additive, dominance, and imprinting variance were very close to the simulated values. In real data, dominance effects account for a substantial proportion of the total genetic variance (up to 44%) for these traits in these populations. The contribution of imprinting to the total phenotypic variance of the evaluated traits was relatively small (1-3%). Our results indicate a strong relationship between additive variance explained per chromosome and chromosome length, which has been previously described for other traits in other species. We also show that a similar linear relationship exists for dominance and imprinting variance. These novel results improve our understanding of the genetic architecture of the evaluated traits and shows promise to apply the SNP regression method to other traits and species, including human diseases.