Genetics Selection Evolution 2009, 41:38 http://www.gsejournal.org/content/41/1/38 DR, even for a QTL of very large effect. Consequently, backcrossing programs using GBLUP selection are far more efficient in preserving and increasing frequencies of such alleles, while for CBLUP selection programs these alleles may easily be lost during the backcrossing process. The advantage of genomic over classical selection with respect to a major QTL for DR may be explained by two main factors: 1) generally higher accuracy of selection for GBLUP compared with CBLUP [5] and 2) for a trait solely recorded on sibs of selection candidates, classical selec- tion can only distinguish between families, while genomic selection may distinguish between single indi- viduals of different genotypes within families segregating for the major QTL. With respect to the major QTL, the most efficient selection schemes were those combining genomic selection with gene-assisted selection for the target QTL. However, the relative advantage of GasBLUP relative to GBLUP selec- tion was rather small with respect to genetic gain in TMI (4–5%). In GBLUP selection, the favourable allele was lost in a few replicates (5–6 out of 50), which never hap- pened using GasGBLUP. Therefore, the results of this study indicate that the main advantage of GasGBLUP compared with GBLUP selection is that it acts as a precau- tion against the loss of the favourable major QTL allele during the early backcrossing phase. This is of special importance if the allele of interest has a low frequency within the donor population, and when the target QTL is in unfavourable LD with other loci, since selection on the target QTL would be detrimental for background genetic effects. However, because of the latter, rapid introgression of the major QTL is not necessarily a substantial advan- tage. As long as the favourable allele of the target QTL is preserved, it would most likely approach fixation in the long run. Further, according to a study by Gibson [13], less intense selection on a major QTL is likely to increase the long-term genetic gain, implying that GBLUP selec- tion is expected to be superior over GasGBLUP selection in the long run, except for replicates where the favourable QTL alleles were lost during the initial backcrossing proc- ess. However, in Gibson's study, unfavourable LD between the major QTL and the background genetic effects were generated as a result of selection, while in our case, such unfavourable relationships are present already at the start of the selection experiment as a result of cross- ing the two base populations, i.e., the positive QTL allele is located on a donor chromosome segment that is more likely to contain negative alleles with respect to PT. Thus, in the current introgression scheme, substantial weight on the target QTL is needed in order to avoid its loss, whereas in Gibson's single population, risk of loss is low even if the major QTL receives little weight. In this study, the genotypic value of the major QTL implies that this locus explains 2/3 of the total genetic var- iance in DR within a population having an allele fre- quency of 50% (assuming Hardy-Weinberg equilibrium). The advantage of efficient introgression of the favourable allele will increase with the effect of the allele and with the economic weight of DR. However, for all selection meth- ods, the efficiency of selection with respect to the target QTL will also increase with the same factors. Preliminary analyses using Scenario 2, showed that for a doubled gen- otypic value of the target QTL, GasGBLUP selection only slightly increased genetic gain for DR (7%) and hardly increased genetic gain in TMI (1%), compared with GBLUP selection (results not shown). Hence, the relative advantage of gene-assisted selection is seemingly lower for QTL of very large effect, since the favourable allele would be preserved and effectively selected for even without gene-assisted selection. The GasGBLUP schemes require that knowledge on both the exact position of the target QTL and its effect exists prior to the selection experiment, in addition to a dense marker map including segregating marker loci for both populations. If this knowledge is readily available prior to the experiment, the GasGBLUP method is naturally pre- ferred. This can be considered a best-case scenario, but in practical breeding schemes, these assumptions would often be unrealistic. The GBLUP selection schemes do not require prior knowledge about the target QTL, and are therefore much easier to implement. An alternative approach would be to do simultaneous QTL detection and introgression as described in Yazdi et al. [4]. However, the latter approach would be less efficient when applied to complex traits affected by numerous QTL of varying effects, while genomic selection is well suited to handle this situation. Due to computing time considerations, the BLUP method of genomic selection was used. This method assumes homogeneous genetic variance at all marker loci [5]. However, more advanced methods of genomic selection are also available, i.e., the so-called BayesA and BayesB methods [5]. Here, the genetic variance explained by each marker locus is evaluated and different weights are thereby given to different genomic regions in the EBV cal- culation. Thus, these more advanced methods are expected to be more effective in selecting QTL of major importance, and the results of the current study should therefore be considered as conservative. In a recent study [14], where analyses were based on simulated crossbred populations using the BayesB method, it was concluded that fitting population-specific marker effects may not be necessary, especially for high marker densities. However, using the BLUP method, as in the current study, all mark- ers are assumed to have effects of equal magnitude, not Page 9 of 10 (page number not for citation purposes)