Li et al. Genetics Selection Evolution 2010, 42:32 http://www.gsejournal.org/content/42/1/32 Different statistical methods have been developed to identify outlier loci under the influence of selection [6-13] and adaptations have been attempted to improve the original methods of Lewontin and Krakauer [14], which have been criticized because of their sensitivity to population structure and history (e.g. [15]). Nevertheless, recent studies have shown somewhat inconsistent results obtained by applying the above statistical tests to the same data (e.g. [7,12,16,17]). The Lewontin- Krakauer test [14] is the oldest of these multilocus-comparison methods. Broadly speaking, these methods are derived by using one of the two general approaches detailed below. The first approach is to develop methods with Lewontin and Krakauers’ original idea and to use the distribution of estimates of genetic differentiation coeffi- cient FST and diversity parameters from individual genetic loci to detect the effects of selection, hereafter termed the FST-based approach, such as the FDIST pro- gram-based method [9], Bayesian regression [12], and population-specific [7] methods. Schlötterer and collea- gues have proposed alternative multilocus simulation- based tests that use summary statistics other than FST, such as the ln RV [10], the ln RH [6], and the ln Rθ’ [13] tests. These tests involve considering the idea of a ‘selective sweep’ that arises from natural and artificial selection, and recent genetic exchanges driven by the selective sweep leave a record or “genetic signature” in the genome covering the selected sites and their linked neutral loci. Given that microsatellite loci associated with a recent selective sweep differ from the remainder of the genome, they are expected to fall outside the dis- tribution of neutral estimates of ln RV, ln RH or ln Rθ’ values. As reviewed by [18-20], all the methods have potential advantages and drawbacks, which can be due to different underlying assumptions regarding the demo- graphic and mutational models on which they are based, as well as on uncertainty associated with the robustness of the approaches. The recent increased availability of large genomic data sets and the identification of a few genes or loci as the targets of domestication or subsequent genetic improve- ment in cattle have renewed the investigation of the genomic effects of selection. Candidate genes and QTL have been described on both BTA1 [21-25] and BTA 20 [26]. On BTA1, the POLL gene, characterized by two alleles: P (polled) dominant over H (horn), is responsible for the polled (i.e. hornless) and horn phenotypes in cat- tle and has been subjected to both natural and artificial selection. Georges et al. [21] have demonstrated genetic linkage between the POLL gene and two microsatellites, GMPOLL-1 and GMPOLL-2. These loci are syntenic to the highly conserved gene for superoxide dismutase 1 (SOD1). In addition, in various breeds the POLL gene has been found to be linked to the microsatellites Page 2 of 14 TGLA49, AGLA17, INRA212 and KAP8, located in the centromeric region of BTA1 close to the SOD1 locus [22,23,25]. To date, on BTA20 several QTL and candi- date genes have been reported e.g. growth hormone and prolactin receptor genes [27] affecting conformation and milk production traits, such as body depth (e.g. [28]), udder (e.g. [29]), udder attachment (e.g. [30]), milk yield (e.g. [31]), fat percentage (e.g. [28]), and especially pro- tein content (e.g. [28-30]). In this study on Bos taurus, we present microsatellite data using a relatively larger number of loci than pre- viously reported, which mainly included the 30 microsa- tellite markers recommended by the International Society for Animal Genetics (ISAG)/Food and Agricul- ture Organization of the United Nations (FAO) working group (e.g. [2,24]; but see also [32]). Among the 51 microsatellites genotyped on 10 representative cattle populations of different origins (native and modern commercial) and horn statuses (polled and horned) in the northern territory of the Eurasian subcontinent, seven were on BTA1 and 16 on BTA20. We applied four tests to detect molecular signatures of selection, ranging from tests for loci across populations and the recently proposed pairwise population tests using a dynamically adjusted number of linked microsatellites [13]. We compared the consistency of the different neu- trality tests available to identify loci under selection in the north Eurasian cattle populations investigated here. Materials and methods Population samples and genetic markers Microsatellite data from 10 different cattle (Bos taurus) populations including 366 individuals were analyzed. Finnish populations were represented by Finnish Ayrshire (modern commercial, horned, n = 40), Finnish Holstein-Friesian (modern commercial, horned, n = 40), Eastern Finncattle (native, mostly polled, n = 31), Western Finncattle (native, mostly polled, n = 37), and Northern Finncattle (native, mostly polled, n = 26). We were able to inference the heterozygotic status at the POLL locus in 19 phenotypically polled cattle of the three Finnish native populations, on the basis of their offspring/parent phenotypes. In addition, there were 19 animals horned (recessive homozygotic) in the Finnish native populations. Istoben (native, horned, n = 40), Yakutian (native, horned, n = 51), and Kholmogory (native, horned, n = 32) cattle were sampled in Russia. Ukrainian Grey (native, horned, n = 30) and Danish Jersey (modern commercial, horned, n = 39) were sampled in Ukraine and Denmark, respectively. During sample collection, the pedigree information and the herdsman’s knowledge were used to ensure the animals were unrelated. Additional information on these popula- tions has been reported in previous publications [2,33].