448 HUMAN MUTATION 28(5), 441^450, 2007 diversity patterns are also differently and randomly affected by their genealogical histories. Given all this, when postulating the effect of selection, the results of different tests and different descriptive statistics, as well as geographic distribution of the genetic variants, should be considered together, including data on functional testing, if available. A set of loci plausibly contributing to the observed excess of ancestral haplotypes among major haplotypes include CDC25A, CDKN2A, and SMAD4. These segments remained significant for negative Tajima’s D (and negative D of Fu and Li in the case of SMAD4) after correction for multiple testing. The interpretation of the haplotype-diversity-based tests, Fu’s Fs and Chakraborty’s statistics (Table 2) is more complicated. While corroborating Tajima’s test in the case of the segments above, in the case of GPX2 the significant results can also be ascribed to the effect of recombinations and/or to the population amalgamation [Chakraborty, 1990]. The population amalgamation can be also invoked in the equally diverse MICA and HDAC1, where the effect of recombination can be neglected. In other words, a plausible genetic (recombination) or demographic (population structure) explanation for the observed diversity patterns can be proposed in these loci even in the absence of selection and despite that these data originate from the same population sample as those from other loci analyzed here. On the other side of the diversity spectra (Table 1; Figs. 1 and 2) are the segments with elevated YH and M. They include BTN3A2, GPX3, GSTM3, and HTR2A, which were initially singled out by the Fay and Wu test; GSTP1, which remained significant for Fu and Li statistics after correction (Table 2); and CX3CR1. The latter was singled out by the departure from HWE and Fst values of its three segregating sites as well as by its distribution in the plot of haplotype allelic classes. Moreover, with S 5 16, Yp 5 4.03 (i.e., p 5 0.20%, 2 SD above the average), k 5 17, G 5 0.86, and Yk 5 6.032, CX3CR1was the most diversified segment among those analyzed in this study and the only one that turned out in the HKA test (po0.025; in which we compared each of the segments against the collection of 28 segments analyzed here). In these six loci, we observed an important skew toward high haplotype allelic classes (Fig. 1; Supplementary Fig. S2) compared to the neutral expectation under a simple population model. Consequently, all of them but GSTM3 (M 5 3) also contributed to a rightward skew of the data plot in Figure 2 that could not be explained by the demographic scenarios proposed by Akey et al. [2004] and only to some extent by recombination, although only at well above the average genomic rate. The question is, to what extent are our findings concerning 50 flanking regions particular to these segments and to what extent are they representative for other noncoding 2-kb sequences. One can also argue that our sample is biased due to a particular set of genes we examined and therefore not representative for the other 50 flanking sequences. But this is almost admitting that these loci are special, indirectly reinforcing a selectionist interpretation, whereby the effects of purifying and adaptive selection did interchangeably create opposite patterns of diversity. In any case, our results provide a useful reference for future comparative analyses that will eventually show to what extent the observed variance in genetic diversity among sequence segments reflects the genomic reality and what part is attributable to selection, to stochastic effects, and to complex demographic histories. On the other hand, additional data will be required to dissociate the effects particular to the examined region from the influence of the linked, adjacent sequences. Indeed, there are numerous reports describing promoter regions as containing variant sites affecting Human Mutation DOI 10.1002/humu their function and as containing variants associated with a disease or representing likely targets of selection. In this context, it is interesting to note that polymorphic site rs769214 in the CAT promoter (see Supplementary Table S2) was reported to be associated with different blood pressure levels (originally SNP844 in Jiang et al. [2001]). In turn, the new allele of the rs36228834 site in CDKN2A and the ancestral allele of the rs36228499 polymorphisms in CDKN1B were found to be associated with an increased risk of childhood acute lymphoblastic leukemia [Healy et al., 2006]. At another site in CDKN1B, the new T allele of rs3759217, with relatively high Fst in non-African populations, abolishes the myoblast-determining-factor binding site [Lassar et al., 1989], i.e., CANCtg-TANCtg (see TRANSFAC; www.gene-regulation.com/pub/databases.html), although the rele- vance of this mutation will have to be confirmed experimentally. In BTN3A2, with one dominant (68%) haplotype (Supplementary Figs. S1 and S2) carrying five derived alleles and conspicuously zero Fst (Table 1), a selection sweep preceding expansion of human populations could be suggested. Here, an adaptive change could have been associated with an increased transcription rate. By allelic-imbalance experiments [Pastinen et al., 2004], the expression of the ancestral haplotype was previously shown to be relatively suppressed. The same effect was demonstrated indepen- dently by in vitro transcription (N’Diaye, Pastinen, Paterson, Larivi`ere, Labuda, Hudson, and Sinnett, unpublished data) of cloned constructs of the 2-kb BTN3A2 haplotypes from the present study. Similarly, in GSTM3, the functional analysis of its rs1332018G4T polymorphism (originally 63 A/C in Liu et al. [2005]) has shown eight-fold lower transcription activity of the G allele related to its nine-fold reduced RNA Pol II binding capacity [Liu et al., 2005]. This ancestral G is absent in Africans but occurs at high frequencies outside Africa. In turn, in HTR2A and TGFB1, strong purifying selection on their coding segments was reported by Bustamante et al. [2005], and it appears not to be reflected in diversity profiles of their 50 flanking sequence (Tables 1 and 2). In contrast, in IL1A, the effect of local adaptation postulated from the analysis of the whole gene by Akey et al. [2004], seems to be reflected by the presence of three equally prevalent haplotypes of this segment, consistent with the scenario of balancing selection. In fact, a newer version of its mRNA (REFSEQ NM_000575.3) shifts the transcription start sites by 1.6 kb and all its polymorphisms are now found within the 50 portion of the gene and none within the 0.4-kb upstream sequence analyzed here. We note also a possible shift in the promoter region of the CX3CR1 locus (NM_001337.3), with its new first exon located about 13 kb upstream with respect to the NM_001337.1 mRNA version we used. In contrast, the transcription start sites of the remaining genes either stayed the same or changed the position of the analyzed 2-kb segment by less than 0.2 kb. In their recent work, Di Rienzo and Hudson [2005] proposed an evolutionary framework for common diseases, listing numerous examples where the ancestral allele represented a susceptibility variant. As shown above, such susceptibility alleles could be found in the promoter regions (CDKN1B) or represent plausible susceptibility candidates, conferring different expression activities and/or differing in geographic occurrence (e.g., BTN3A2 and GSTM3). If adaptive evolution is preferably regulatory [King and Wilson, 1975] and still prevalent in human populations, more regulatory variants could be expected in the promoter as opposed to in the coding segments. Our study provides new evidence suggesting the role of selection, including adaptive changes in the evolution of these segments. However, because molecular