HUMAN MUTATION 28(5), 441^450, 2007 447 FIGURE 2. Frequencies of the ancestral haplotypes (A) and the distribution of major haplotypes among haplotype allelic classes (B) (cf. Fig. 1) in 28 studied segments.The data (solid bars) are compared with theoretical expectations from coalescent simulations under the standard model in the absence (solid line) and in the presence (dashed line) of recombination at 10-fold the genomic average (10 cm/Mb). Simulations were for a sample size of 80 chromosomes, a mutation rate of 2.13 10 8 per bp per generation, corresponding to the average S density of 9.1, and N 510,000. haplotype falling within each of the four frequency quartiles. The frequency ‘‘0’’ and the first quartile [0–0.25] represent 15 loci in a category of segments lacking or with ancestral haplotypes at minor frequencies. The three other quartiles [0.25–1.0] include 12 loci where the ancestral represents the major haplotype and CDKN1B segment and where two haplotypes, the ancestral one and the one carrying one derived allele, happened to have equal frequencies (M 5 0/1 in Table 1). Coalescent simulations were used to compare these data with theoretical distributions expected under a simple population model [Akey et al., 2004; Hudson, 1990; Schaffner et al., 2005]. We evaluated the expected distribution in 28 sequence segments, given the average density of polymorphic sites in this data set. Simulations were carried out under the constant population size in the absence and in the presence of recombinations (10-fold the genomic average). It turns out that in 28 segments analyzed we observe ancestral haplotypes more often than predicted under this model and that these ancestral haplotypes tend to occur at frequencies higher than expected. They prevail in the uppermost frequency quartile (Fig. 2A). The difference between the observed and the expected is even more acute in the presence of recombinations. On the other hand, to visibly affect the distribution, the recombinations would have to occur at a rate well above the genomic average. In Figure 2B, the histogram of the partition of major haplotypes among haplotype allelic classes (i.e., M from Table 1) shows a U-like skewed distribution, as in Figure 2A. We observe an excess of the ancestral haplotypes (on the left) and of haplotypes carrying five or six new alleles, on the right of the distribution. The first effect becomes more pronounced in the presence of recombina- tions, while the second becomes attenuated but does not disappear in their presence. Our simulations also examined different demographic scenarios, such as those described by Akey et al. [2004], showing that neither population growth nor population bottlenecks substantially affected the simulated distributions with respect to the simple population model (Supplementary Fig. S4). In other words, among our loci there are more ancestral haplotypes that are major haplotypes than would be expected under the simple neutral model. At the same time, we observe a surplus of haplotypes being major and carrying excessive numbers of the derived alleles, consistent with the results of the statistical tests from Table 2. In summary, the analysis presented above suggests that in the investigated set of segments, certain loci appear as evolutionarily conserved while others seem to be more evolved relative to the average. DISCUSSION We have analyzed 28 genomic segments located upstream from the transcription start sites of the protein-coding genes, where transcription control elements usually reside. The overall pattern of the observed diversity, both qualitatively and quantitatively, did not differ from the genomic average of nonexonic DNA segments. Nucleotide diversity of 0.082% was similar to that observed by others in noncoding sequences [Livingston et al., 2004; Zhao et al., 2000]. Likewise, the rate of evolution estimated from the sequence difference with chimpanzees (d 5 1.28%; m 5 1.07 10 9 per bp per year) represented the genomic average [Chen and Li, 2001], leading to an estimate of the effective population size of 9,600, a value typically obtained in studies of human DNA diversity. However, large variances in different diversity indices, in summary statistics, and in distinct estimates of the population mutation parameter Y (Table 1) suggested that the observed averages did not accurately reflect the extent of the investigated segments’ diversities. This effect was particularly well captured by the analysis of the prevalence of the ancestral haplotypes and that of the major haplotypes among haplotype allelic classes (Fig. 2). In a large number of loci, the ancestral haplotype was a major haplotype, but at the same time, there were other, relatively numerous loci with MZ5 with rare or nonexistent ancestral haplotype. Together this led to a skewed, U-like distribution of the data plotted in Figure 2, showing departure from the neutral model based on its empirical evaluation by coalescence simulations. Therefore, it is tempting to propose that such a distribution is a product of the combined effects of the purifying selection acting on some of the loci and of adaptive evolution on the other loci. Indeed, significant results of statistical tests, such as that of Tajima (negative D) or Fay and Wu (negative H), are consistent with these opposite selection effects. On the other hand, the incongruence in different diversity estimators revealed by neutrality tests can be also ascribed to the demographic history itself affecting gene genealogies even in the absence of selection. It is usually argued that selection acts upon specific loci, while demography is common to all genomic segments and thus should affect them in the same way [Akey et al., 2004; Reed et al., 2005]. As a result, for loci sampled from the same population, the associated variance, due to shared demography, is expected to be lower and the detection of selection easier. Nevertheless, one has to consider that natural selection likely acts on different loci at different time periods and that the resulting Human Mutation DOI 10.1002/humu