Li et al. Genetics Selection Evolution 2010, 42:32 http://www.gsejournal.org/content/42/1/32 distributions of branch length estimates, while some loci do not. Overall, we identified two loci (SOD1 and AGLA17) that were probably subject to selection in the three Finnish native populations. Thus, we concluded that the distribution of variability at these loci could have been shaped by forces other than demographic effects e.g. genetic drift. Although the locus DIK4591 was located on the edge or fell just outside the high probability region of the expected conditional distribu- tion in the Finnish native populations, we must be cau- tious about the locus because the estimation of Fi parameters is discontinuous as a result of the discrete nature of the data, i.e. the allele counts (e.g. [7]). How- ever, it is worth noting that not all significant loci detected by other methods could be accepted as trust- worthy outliers with DetSel due to technical constraints, which means that if a locus is monomorphic in one population of the pair analyses with DetSel are not possible. Tests to detect outlier loci that deviate from neutral expectation cannot identify false positives (type I errors). Thus, we conducted the three different neutrality tests (the Ewens-Watterson test, the FDIST test and the BAYESFST test), setting a 95% P level criterion to iden- tify loci under selection pressure, at which the expected number of false positive loci is 51 × 0.05 = 2.55. We still found 13, four and five outlier loci, respectively, indicating that at least some of the outlier loci are unli- kely to be false positives. As suggested by [5], a practical approach to strengthen the candidate status of identified outlier loci is to apply two or more neutrality tests simultaneously based on different assumptions and para- meter estimation and only consider outlier loci that are supported by several methods for subsequent validation steps. Thus, the fact that some loci are identified by one neutrality test, but not by others, suggests that their sta- tus as candidate loci under selection must be regarded with considerable caution. However, significant devia- tions from neutrality expectation using multiple tests do not necessarily mean that a particular locus has been affected by hitchhiking selection. In this case, we applied three different pairwise population neutrality tests in 12 separate comparisons using two loci (across the popula- tions: 3 × 12 × 2 = 72 separate tests). This is expected to result in approximately four false positives at the 95% P level. The fact that we observed as many as 54 devia- tions (Table 2) at the 95% P level indicates that it is unlikely that all the outliers identified by pairwise ana- lyses are due to type I errors. Moreover, no locus showed only one significant deviation in one pairwise population comparison (see Table 2). Therefore, it can be considered that the approach was quite robust and conservative in the detection of the effects of Page 11 of 14 hitchhiking selection, particularly when additional pair- wise analyses were applied. Interpretation of the outlier loci and caveats Actually microsatellites are unlikely to be the target of selection, but are merely tightly linked to the candidate genes. Since the microsatellites used are located close to some functional candidate genes (or QTLs) on the same chromosome, this indicates a high probability that one or several good candidate genes (or QTLs) is/are tightly linked to some of the microsatellites. In many of the cases examined to date, selective sweeps have affected only a very small region, potentially containing only one or a few genes, except in the case of extremely strong selection (see [57]). Empirical studies indicate that the negligible LD between a hitchhiking locus and a candi- date gene underlying selection varied from tens of bp (e.g. [55]) to tens or even hundreds of kb (see [58,59]), which depends on a variety of factors such as the geno- mic regions (e.g. sex chromosome vs. autosome) and populations (e.g. domesticated vs. wild) investigated, and the type of markers (e.g. EST- or MHC-microsatellites vs. microsatellites) used. It has also been suggested that the LD between loci and candidate genes affected by selection is determined mainly by the strength of selec- tion, local recombination rate, population history, and the age of the beneficial allele [60]. Whatever the rea- son, significant LD was detected with inter-marker genomic distances between ca.1100 kb and ca.10300 kb in this study (see Figure 1), a considerably wider interval than reported previously. We detected two microsatellite loci (AGLA17 and SOD1) probably linked to the candidate gene for the polled trait in the populations investigated. The polled trait is an autosomal dominant trait in cattle and to date the genes controlling this trait have not been spe- cifically identified. However, the gene causing the absence of horns is known to be at the centromeric end of BTA1. Several factors have potentially driven evolution of the functionally important candidate locus including artificial selection and mating system. In Fin- nish native cattle populations, polled animals were par- ticularly favored during selective breeding. However, we did not detect any locus under selection on BTA20 despite that the fact that several microsatellites includ- ing GHRJA surround the growth hormone receptor gene. Growth hormone receptor belongs to the large superfamily of class 1 cytokine receptors. It has various roles in growth, lactation and reproduction in cattle and has been identified as a candidate gene affecting a few key quantitative traits. Therefore, it is not specific to dairy traits but to traits related with growth, lacta- tion and reproduction. Among the cattle populations