Samples

Three overlapping datasets were generated and used in the current study:

1. 1. Sequencing of the tyrosinase gene (TYR) was performed on DNA samples from 81 individuals representing genetic variation in 6 regions worldwide: Africa (n=24), Europe (n=16), East Asia (n=17), South Asia (n=13), Oceania (n=7) and America (n=4). Of these, 70 samples were from the HGDP-CEPH Human Genome Diversity Cell Line Panel [41]. The remaining eleven samples were healthy volunteers from South Asia and Europe. Samples were chosen to cover major continental regions in the HGDP-CEPH panel and additional individuals from India were sequenced to provide better representation of genetic diversity in South Asia.
2. 2. Illumina genotyping data for 351 samples was used for genome-wide scans of positive selection: 338 samples were from previously published data [42-45], and 13 are reported here for the first time. Of the 351 samples, 70 were also involved in the re-sequencing project. Genotyped samples were divided into the same six (sub-) continental groups: Africa (n=59), Europe (n=68), East Asia (n=80), South Asia (n=83), Oceania (n=28) and America (n=33). An additional Bantu sample (n=19) from the HGDP-CEPH panel was used as a reference population in XP-EHH analyses.
3. 3. The ancestral recombination graph was built using a combined set of 1108 individuals, including all the samples from panel 1 and 2 (362 samples in total), plus additional 746 HGDP-CEPH Illumina genotypes [42]. Samples were divided into seven groups according to their geographic origin: sub-Saharan Africa (n=123), North Africa (n=30), Europe (n=309), East Asia (n=246), South Asia (n=256), Oceania (n=36) and America (n=108).

Additional information on all samples used in the present study can be found in Table S1. DNA samples introduced for the first time in this study were collected with written informed consent. The study has been approved by the Bioethics Committee of the Estonian Biocentre.

DNA sequencing and genotyping

The following regions of TYR were sequenced: the 5’ and 3’ flanking regions, five complete exons including exon-intron junctions, and additional 12 intronic regions. The total amount of sequence produced is about 24.3 kb: 12.9 kb and 0.4 kb come from the 5’ and 3’ flanking regions, respectively, 1.6 kb are coding sequences and 9.4 kb are intronic sequences. A graphical overview of the sequenced regions is available in Figure S1 and additional detailed information is presented in Table S2. PCR conditions and primer information are available upon request from the authors. Nucleotide sequences are available through GenBank, accession numbers KC201427-KC201588.

Aligned sequences were compared to the hg19, GRCh37 human reference sequence and chimpanzee genome sequence build 3.1. Individual haplotypes were further reconstructed using the PHASE algorithm [46,47] implemented in the DNASP 5.10 software package [48]. The phase of the singletons was, where possible, determined by a cloning procedure with CloneJET™ PCR Cloning Kit (Thermo Fisher Scientific Inc.).

New samples were genotyped using the HumanHap650Y BeadChip, while some of the already published samples were genotyped either by the same chip or using the Illumina Human610-Quad BeadChip (see Table S1 for details). The genotype data were processed and filtered with PLINK v 1.06 [49]. Our original master-file included only SNPs shared between the three Illumina genotyping arrays: HumanHap650Y, Human610-Quad and Human660W-Quad. We further excluded all SNPs with call rates less than 0.95. A total of 531,315 autosomal SNPs passed this criterion. We further applied additional filters, the filter choice depended upon the analysis performed: (a) for the whole-genome d_i we used autosomal non-phased genotypes with call rates equal to 1.0, and SNPs with minor allele frequency over 0.05; (b) for iHS and XP-EHH, first, the haplotype reconstruction was performed using BEAGLE 3.1 [50], and later the same filters as for the whole-genome d_i were applied to the phased data. After all filtering steps our non-phased dataset included 415,334 and phased dataset 491,253 autosomal markers.

Sequence data-based tests

The Jukes-Cantor corrected nucleotide diversity (π) and Tajima’s D value [51] were estimated using the DNASP 5.10 software [48]. The significance of Tajima’s D statistics was assessed by two different approaches. Firstly, empirical TYR values were compared to 10,000 coalescent simulations performed under the hypothesis of selective neutrality and population equilibrium in ARLEQUIN 3.5.1.3 [52]. Secondly, Tajima’s D estimates of the longest consecutive sequence block (ca 13.8 kb), which comprises the 5’ flanking region and the first exon of TYR (Figure S1 and Table S2), were further compared to the average of D calculated from 10,000 neutral simulations using the COSI 1.2.1 software under the "best-fit" model [53]. COSI has been calibrated to simulate extant human genetic variation under neutrality. African, European and Asian sequences were generated using the parameters of the "best-fit" model. However, these parameters were not provided for American and Oceanian populations, for which we have chosen the closest proxy in terms of genetic similarity, namely the Asian model [42,54]. The model parameters were further adjusted to meet our re-sequencing project details: this included sequence length and mutation rate. Local TYR recombination rate from the HapMap GRCh37 genetic map was used in the coalescent simulations [55].

Within population differentiation was estimated using analysis of molecular variance (AMOVA) with ARLEQUIN 3.5.1.3 [52]; statistical significance was assessed by 1,000 permutations.

Genotype data-based selection tests

The following whole-genome selection scans were performed: integrated haplotype score (iHS) [18], cross-population extended haplotype homozygosity (XP-EHH) [17] and pairwise F_ST-based d_i [56]. All statistics were calculated using our Illumina genotyping sample set (n=351) for each of the six population groups separately. The dataset was filtered as explained above. In case of iHS and XP-EHH estimation we followed the previously described approach [16]. In XP-EHH analyses, we used Bantus as a reference group for all non-African populations and Europeans as a reference for the African population. Whole-genome autosomal pairwise F_ST values were estimated using GENEPOP 4.0 [57] and the function of pairwise F_ST between population i and the remaining populations (d_i) was calculated in R [58].

All iHS, XP-EHH and d_i genome-wide results were normalized by chromosome, divided into 200-kb non-overlapping windows and binned by the number of SNPs in each window (bin size=20SNPs for XP-EHH and d_i analysis, and bin size=15SNPs for iHS). We further used maximum value of XP-EHH, average value of d_i and fraction of |iHS|>2 in each window. A two hundred kb long TYR window was centered in the middle of the gene and included about 41 kb of upstream and downstream sequence. Percentile rank of the TYR window was calculated using the genome-wide distribution of windows from the same bin.

Phylogenetic tree reconstruction and coalescent age

We used two different approaches to reveal phylogenetic relationships among data. First, we used the median-joining (MJ) algorithm implemented in the NETWORK 4.6.1.0 software [59] to reconstruct phylogeny based on the alignment of phased sequences. The haplotype block structure of this alignment was established using HAPLOVIEW 4.2 [60]. We further reconstructed phylogenetic history and estimated time to the most recent common ancestor (TMRCA) in each haplotype block separately using local mutation rate estimates. Coalescent age was calculated using the rho statistics on the MJ network in the NETWORK 4.6.1.0 software. Mutation rate calibration was performed using 7 MYA human-chimpanzee split [61,62] assuming a 29 year generation time [63]. In addition, the age of derived non-synonymous alleles of rs1042602 (20 chromosomes in the TYR re-sequencing sample) and rs1126809 (10 chromosomes in the TYR re-sequencing sample) were estimated by two different methods. Firstly, the rho statistics was calculated using the MJ network of the complete re-sequencing alignment as described above. Secondly, a Bayesian coalescent approach was applied as implemented in BEAST 1.7.5 [64]. Data was partitioned into coding and non-coding regions. Coding nucleotides were analyzed with the SRD06 model [65]. MODELGENERATOR [66] was used to assess the substitution model of non-coding nucleotides independently in each dataset: the HKY model was chosen for sequences with the rs1042602 derived allele, and the HKY+I model was chosen for sequences with the rs1126809 derived allele. The analysis was performed using a local molecular clock of the TYR gene that was estimated for coding and non-coding regions separately, and using Extended Bayesian Skyline Plot as a coalescent tree prior [67]. Posterior distributions of parameters were estimated by Markov chain Monte Carlo simulation, with samples drawn every 1,000 steps over a total of 50,000,000 steps with the first 10% of samples discarded as burn-in. Three independent runs were conducted to check for convergence. Sufficient sampling of parameters was evaluated using TRACER 1.5.0 [68] and convergent runs were combined; 95% Highest Posterior Density intervals (HPD) were used as confidence intervals.

Second, we reconstructed the minimum recombination history of TYR haplotypes using phased Illumina genotype data for 1108 individuals. This was performed using only those TYR SNPs in the genotype data that were within the range of our re-sequencing alignment (n=7), or SNPs that were phylogenetically equivalent to them (n=8). Equivalency of a SNP missing from the re-sequencing project was assumed if it was in complete linkage disequilibrium (r²=1) with one of the re-sequenced SNPs among samples present in both re-sequencing and genotyping sample sets (Table S1). We applied filtering on our data prior to the analysis: individuals having one of the chromosomes belonging to the rare haplotype with total frequency of less than 1% in our sample were removed. In total, 942 individuals (1884 chromosomes) passed the filtering criteria. Further, ancestral recombination graphs (ARG) based on filtered and non-filtered data were reconstructed in BEAGLE and KWARG, respectively. Both programs implement a branch and bound method for determining the minimum number of recombinations in a dataset [69]. Initially, the draft ARG was reconstructed and compared to the median-joining network solution of the data. To detect fine-scale phylogeographic patterns we further genotyped eight additional sub-haplogroup defining SNPs among the individuals belonging to the particular lineage (see Table S3 for details).

Nucleotide diversity, mutation rate and sequence-based selection tests

We assessed the degree of TYR 5’ flanking region genetic variation by sliding window nucleotide diversity (π) analysis, which estimates the average number of nucleotide differences per site between two sequences [48,70]. Additional π estimates were obtained for the combined coding, intronic and complete 5’ flanking region sequences separately (Figure 1). The average and standard deviation of nucleotide diversity among six studied populations were 0.00091±0.00007 for the 5’ flanking region, 0.00121±0.00020 for combined intronic sequence and 0.00019±0.00025 for combined coding sequence. The European sample had the highest coding π estimates among all continental groups (0.00067 in Europe, followed by 0.00021 in Africa). Nucleotide diversity in the complete re-sequencing alignment of our total human sample (0.00110) was not significantly different (p=0.30) from the average of NIEHS SNPs re-sequencing data for 647 human genes [71]. We observed two highly conserved regions with almost complete lack of diversity in our global sample, 6.9 kb and 1.8 kb upstream of the first codon position of TYR (Figure 1). The latter contains a previously identified conserved element, called Tyrosinase Distal Element (TDE) [30].

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Figure 1. Sliding window analysis of pairwise nucleotide differences in the 5’ flanking region of the TYR gene.

Average estimates of pairwise differences (π) at exons, introns and the complete 5’ flanking region are provided for reference. Pairwise differences in six regional population groups are shown separately. Approximate locations of previously known regulatory elements (TDE, TPE and h5’URS) are marked with red diamonds. A newly identified region with decreased genetic variability is marked with a blue diamond. Position numbers are shown relative to the first codon of the TYR gene. Sliding window size is 1500 bp and step size is 375 bp.

https://doi.org/10.1371/journal.pone.0074307.g001

The Jukes-Cantor corrected average number of nucleotide substitutions per site between the human consensus sequence estimated from the data and chimpanzee (0.01447) yielded an average mutation rate at TYR of 3.0x10^-8 per site per generation, assuming 7 MYA human-chimpanzee split and a human generation time of 29 years [61–63]. Mutation rate of coding and non-coding nucleotides was estimated as 8.2x10^-9 and 3.2x10^-8 per site per generation, respectively.

To assess the evolutionary forces acting on the human and chimpanzee branches, we calculated the ratio of the rates of non-synonymous (K_a) and synonymous (K_s) substitutions between the two species. The K_a/K_s ratio is a measure of overall evolutionary constraints, where a value <<1 points to numerous amino acid substitutions having been eliminated by purifying selection [72]. The estimation yielded a K_a/K_s ratio of 0.158, which is smaller than the genome-wide average (0.230) [73]. The difference, although not significant, comes largely from the lower rates of non-synonymous substitutions (K_a) in our sample (0.0018 for TYR vs. 0.0034 genome-wide mean, p=0.94), while the rates of synonymous substitutions (K_s) are similar (0.0114 for TYR vs. 0.0142 genome-wide mean, p=0.98).

Before performing neutrality tests we evaluated within population differentiation of six groups in our re-sequencing alignment using AMOVA analysis. Only the African sample showed marginally significant F_ST higher than zero (0.08, p=0.03, not significant after Bonferroni correction), while other populations all had slightly negative estimates pointing to the limited role of the TYR locus in genetic differentiation within studied (sub-) continental groups (Table S5) [74]. We further investigated our data using Tajima’s D neutrality statistics. By its original description this test assumes constant population size and lack of recombination [51]. These assumptions are overly conservative and do not normally hold in case of evolutionary history of modern humans [75]. In addition to the basic model implemented in ARLEQUIN, we used demography-corrected “best-fit” coalescent simulation approach and compared the distribution of D values obtained from neutral simulations in COSI with the empirical estimates of the TYR sequence data. This allowed us to include recombination into the model and to specify an explicit demographic scenario implying African origin and Out-of-Africa dispersal of anatomically modern humans [53]. To avoid possible bias which might have been introduced by the partial TYR re-sequencing strategy, we applied COSI simulations only to the longest consecutive sequence block in our alignment. This block included the complete 5’ flanking region and exon 1 and comprised ca 57% of total re-sequencing data (Figure S1 and Table S2).

The results of the neutrality tests are shown in Table 1. Only the Oceanian sample revealed significant deviation from the null hypothesis in the combined re-sequencing alignment under the basic model. In addition to Oceania, the European population similarly showed moderate departure from neutrality in the 5’ flanking region and exon 1 in the model that considers demographic history and recombination. However, European Tajima’s D value was not significant after Bonferroni correction for multiple testing. Both Europeans and Oceanians revealed positive test values pointing to an excess of intermediate frequency alleles, which could be an indication of either balancing selection or the effect of population structure. Even though the latter alternative cannot be entirely ruled out, our AMOVA analysis indicates a limited degree of within population differentiation in all studied populations (Table S5).

Genotype-based selection tests

The Illumina genotyping dataset from 351 individuals was used to explore the genetic variability in the TYR gene in the context of genome-wide data. Data was analyzed in 200-kb non-overlapping windows. Both haplotype-based and population differentiation-based selection tests were employed. XP-EHH and iHS belong to the first class of tests and detect complete or partial selective sweeps, respectively. In the first case the selected allele is approaching or has achieved fixation, whereas in the second case selection has driven new alleles up to intermediate frequency [17,18]. The population differentiation F_ST-based d_i statistic, on the other hand, is capable of detecting genomic regions with higher than expected levels of population differentiation regardless of whether selection has acted on newly arisen or preexisting variation [56]. As with other empirical data-based tests, the distinction between selection and demographic processes can be made by comparing the locus of interest, the TYR gene in this case, with the empirical distribution of other genes in the genome, assuming that demography affects all loci while selection affects only a subset of them. Certainly, caution is required in the interpretation because we do not actually know the proportion of the genome that has been affected by selection.

The empirical ranking order of the 200-kb window containing the TYR gene was determined from the genome-wide distribution of XP-EHH, iHS and d_i statistics calculated using the same population sample, with the 95^th percentile values of genome-wide distribution chosen as the significance threshold. None of the studied populations showed unusual properties in the window containing the TYR gene in any of the three tests performed (Table 2). The highest estimates for both haplotype-based (XP-EHH=2.11, percentile rank=0.87) and population differentiation-based selection tests (d_i=0.93, percentile rank=0.71) were detected in the European sample. Based on these tests we cannot reject the neutral hypothesis in any of the geographic regions analyzed, but have to note that these tests have limited power to detect only certain aspects of local adaptation through positive selection.

Phylogenetic analysis

To further examine the geographic distribution of the allelic variation in the tyrosinase gene we reconstructed the phylogenetic tree of TYR haplotypes. Firstly, we determined the LD structure using HAPLOVIEW. We identified two major linkage blocks, one between 11.8 kb and 3.1 kb upstream from the first TYR codon and the other between 0.5 kb upstream and 106.8 kb downstream from the first TYR codon (Figure S2). The first block is covered by 8.6 kb uninterrupted re-sequencing data and includes 67% of our TYR 5’ flanking sequence. The second block spans from promoter 3’ end to exon 4 and includes a partial promoter, complete exons 1, 2, 3 and 4, plus additional intronic amplicons, and has a total length of 10.8 kb in our re-sequencing alignment. Median-joining network of the first block is presented in Figure 2. When using chimpanzee sequence as an outgroup for rooting the network, the deepest and most diverse branches appear to be among Africans, who are also represented by the largest number of individual haplotypes: 28 different haplotypes in Africa vs. 16 outside. African sequences are largely unique and share common haplotypes with non-Africans in only four cases. On the other hand, all non-Africans cluster closely together: 100 out of 114 non-African chromosomes belong to three major haplotypes or their single step relatives (Figure 2). There is no obvious geographic sub-structure among non-African variation: the majority of the branches are shared by populations with different ancestry and latitude of origin (Figure 2, Figure S3 and Figure S4). The few population specific lineages that can be observed all have low frequency. Time to the most recent common recent ancestor of the first and the second haploblock was estimated as 1.4±0.3 and 1.6±0.3 MYA, respectively. The age of the derived non-synonymous rs1042602 allele was estimated to be around 6,100±3,600 years BP by rho statistics and around 15,600 years BP (95% HPD=400–46,600 years BP) by Bayesian coalescent approach in BEAST. Time to the most recent common ancestor of samples bearing the derived non-synonymous rs1126809 allele was estimated to be around 20,400±13,600 years BP by rho statistics and around 29,400 years BP (95% HPD=1,900–68,600 years BP) by Bayesian coalescent approach.

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Figure 2. Median-joining network of TYR haplotypes.

The network is based on the analysis of sequence data of the first haplotype block of 8634 bp length in 81 samples (162 chromosomes), color-coded by the geographic region of origin of the samples. Chimpanzee sequence (white circle) was used as an outgroup and chimpanzee specific variants have been excluded from the network output.

https://doi.org/10.1371/journal.pone.0074307.g002

The second phylogenetic analysis was performed with the Illumina genotyping sample set, 942 individuals (1884 chromosomes) were included after the removal of rare haplotypes. Eighty-one samples from the re-sequencing dataset showed complete concordance at positions examined by both Illumina genotyping and direct sequencing techniques. True minimum recombination history of the rooted tree, based on the inference of the minimum number of recombination events needed for the evolution of a given set of haplotypes, was estimated on phased data using the branch and bound algorithm in BEAGLE, and the most parsimonious outcome was visualized as an ancestral recombination graph [69]. Phylogenetic relationships of the 18 common haplotypes (haplogroups) are shown in Figure 3. In naming these major branches, we followed the nomenclature rules applied in the classification schemes of mtDNA and Y-chromosomal phylogenies for convenience [76]. The recombination graph has a deep split between clades we call A and BCDE. Haplogroup A has 8 branches found mainly in sub-Saharan Africa (56%) and Oceania (57%), whereas in other geographic regions its frequency ranges from 7 to 16%. While the Oceanian samples are represented by only three distinct lineages, the sub-Saharan African population contains all but one branches of haplogroup A. Four (A1*, A1c, A3* and A3a) out of eight A haplotypes are almost exclusively confined to sub-Saharan Africa.

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Figure 3. Ancestral recombination graph of TYR haplotypes.

The tree is rooted by the chimpanzee sequence and presents recombination history of 942 worldwide samples (1884 chromosomes). Haplogroup frequency by populations is shown below the tree. Haplogroup names are shaded in yellow. Green arrows show the origin of recombination prefixes, blue arrows show the origin of recombination suffixes. Recombination points are shown by rectangles. Numerical superscript prefixes to the left of rs identifiers correspond to the relative physical position of SNPs. SNPs which were out of the range of our re-sequencing alignment are marked with superscript suffixes to the right of respective rs identifiers and correspond to the following phylogenetic equivalents in our re-sequencing data: A – rs12799137, B – rs7108676, C – rs12799347, D – rs12417632, E and F – rs5021654, G – rs7934747, H – rs1126809. Non-synonymous mutations or their phylogenetic equivalents are shown in red font with amino-acid substitutions specified. 95% confidence intervals for the detected haplogroup frequencies are given in Table S6.

https://doi.org/10.1371/journal.pone.0074307.g003

Apart from Oceanian populations, the majority of non-African samples belong to the macrohaplogroup BCDE. Again, as with haplogroup A, there is limited haplotype sharing between sub-Saharan Africa and other (sub-) continental groups, with 3 out of 10 haplogroups being exclusively confined to sub-Saharan African populations. The most frequent haplogroup outside Africa is B, followed by C and D. Haplogroups B1, defined by the non-synonymous rs1042602 mutation (Ser192Tyr), and C2a, defined by rs72963135 (phylogenetically equivalent to rs1126809, Arg402Gln), are found mainly in North Africa and Europe. In contrast, the majority of Asian, Oceanian and American chromosomes belong to either B* or C2* clades. The exclusion of rare haplotypes (Figure 3 vs. Figure S5) did not significantly affect the geographic pattern of haplogroup distribution. For example, 13 samples with rare haplotypes bearing the non-synonymous rs1042602 mutation all originated from either North Africa or Europe. Among the 166 samples excluded in total, 60 were from sub-Saharan Africa, further highlighting the fact that this is the continental group with the highest genetic diversity (Table S1). However, despite the high overall number of distinct haplotypes in sub-Saharan Africans, the combined frequency of haplotypes with a non-synonymous mutation was among the lowest (3%) of all studied populations.

Selection

There is some evidence from previous studies based on genotype data that the non-synonymous rs1042602 polymorphism (Ser192Tyr) in TYR exon 1 may play an important role in the evolution of light skin color in Europe and South Asia [29,33,34]. By means of a genome-wide association approach, Stokowski et al. [31] estimated this variant to explain up to 2.5% of skin reflectance difference between lightly and heavily pigmented individuals of South Asian origin. We have tested whether the TYR gene has been under selection in human evolution using sequence- (Tajima’s D) and genotype data-based (iHS, XP-EHH and d_i) selection statistics. Positive Tajima’s D estimates pointed to an excess of intermediate frequency alleles in Oceania and Europe. This statistics is influenced by both population history and natural selection. For example, positive values could be yielded by balancing selection, but also by a recent bottleneck or population subdivision [83–85]. Considering the diverse geographic origin of our group of samples representing Europe, which combined various HGDP-CEPH populations from Europe and the Near East, we cannot rule out the possibility that population structure has, to some extent, affected the results of the Tajima’s D test. For example, the exclusion of five Israeli individuals lowers the European D value to 1.61 for the 5’ flanking region and TYR exon 1, but raises it to 1.48 for combined re-sequencing alignment without substantially affecting the probability estimates (Table 1). The presented AMOVA analysis of TYR re-sequencing data similarly did not detect any significant differentiation within population in either the European or the Oceanian sample, indicating a limited effect of population structure on the reported Tajima’s D values (Table S5). Furthermore, populations from the Near East and Europe have previously been shown to share signals of selection in other pigmentation genes, including SLC24A5 and KITLG [16], and the majority of the individual samples used here have previously been examined by STRUCTURE-like analyses and clustered into similar (sub-) continental groups as defined by us in the present study (references provided in Table S1). We conclude that although a minor effect of population structure is possible, it seems unlikely to be the major cause of the significantly positive Tajima’s D in our European sample.

While modeling population history of the Oceanian populations we used as a proxy the “best-fit” demographic model of East Asians. The interpretation of the results of significantly positive Tajima’s D in our study should thus be considered with caution as the demographic parameters of population history of Papuans and Bougainville Islanders, who formed the Oceanian group, are likely to be quite different from East Asians, considering their isolation and existing genetic data on these populations [86–88]. It is possible that small founding population size, long-term isolation and high level of genetic drift, rather than natural selection, are responsible for the observed pattern of genetic variation in the TYR locus in Oceania.

Other selection scanning approaches employed here – extended haplotype homozygosity-based iHS and XP-EHH tests, and population differentiation-based d_i tests – did not reject the neutral hypothesis in the TYR gene and adjacent genomic regions in any of the population groups considered in this study. Nevertheless, even if significantly positive Tajima’s D values do indeed indicate traces of balancing selection and/or population structure in the Oceanian and European samples, the lack of a selection signal in our genotyping data is not unexpected: Tajima’s D utilizes different evolutionary assumptions and operates on a different time scale. For example, the haplotype homozygosity tests are only capable of detecting a particular kind of selection, one involving a recent selective sweep, and, thus, more ancient selection events and those involving standing variation or multiple low effect size mutations may go undetected [85,89].

Geographic distribution of the functional variation of TYR

The ancestral recombination graph based on the genotyping results of 942 individuals (Figure 3) shows that haplogroup B is frequent and widely spread among non-African populations. Europeans harbor the highest frequency of one of its branches, B1, which is defined by a non-synonymous rs1042602 polymorphism. B1 and B* (containing all other branches of B except for B1) show contrasting frequency patterns: while B* is common in East Asia, Oceania and America, B1 is virtually absent there. It is interesting to note that B1 is also rare in sub-Saharan Africans (0.03, 95%CI=0.01–0.08; 95% confidence intervals for detected haplogroup frequencies are given in Table S6). In contrast, B1 chromosomes are frequent in North Africa among Algerian Mozabites, where they occur at 46% frequency (95%CI=0.34–0.59). The same is true for the other non-synonymous mutation, rs1126809. Its phylogenetic equivalent in our genotyping panel, rs72963135 (r²=1.0), is absent in darkly pigmented sub-Saharan populations, while it reaches 35% frequency in North African Mozabites. Moreover, non-synonymous variation in sub-Saharans is represented only by a single private mutation in the re-sequenced Kenyans (Table S4). The highest combined frequency of non-synonymous derived alleles of the TYR gene was observed in Europe (0.59, 95%CI=0.55–0.64) and North Africa (0.81, 95%CI=0.69–0.90). The majority of this variation is due to the presence of either rs1042602 in exon 1 or rs1126809 in exon 4 tagged by the rs72963135 polymorphism in the genotyping data. The latter mutation defines haplogroup C2a, which is again represented mainly in European (0.23, 95%CI=0.20–0.27) and North African samples (0.35, 95%CI=0.24–0.49). The human ancestral alleles of both rs1042602 (Ser192Tyr) and rs1126809 (Arg402Gln) are almost completely conserved among different species, and mutations at these positions are classified as probably having damaging impact on protein function by the PolyPhen-2 tool [90]. Functional assays of Tyr192 and Gln402 alleles have also revealed about 40% and up to 75% reduced enzymatic activity, respectively, confirming the in silico results [91,92]. In total, 72% of the chromosomes in our genotyping dataset that were inferred to carry at least one non-synonymous difference compared to the ancestral human sequence were confined to European and North African samples. The sharing of this pattern between these two populations is not surprising considering that both are characterized by low pigmentation level. Furthermore, the present-day North Africans have been proposed to derive from several distinctive migrations, including an ancient back-migration from Europe and the Near East [93]. The proportion of the ancestry component shared with Europeans in the HGDP-CEPH Mozabite sample has been estimated to be around 80% [42,43,94] and, therefore, the allele sharing patterns observed in the TYR gene are likely due to common demographic history rather than convergent adaptation.

Similarly to the results observed here for TYR, Harding et al. [15] also detected the absence of non-synonymous alleles in the MC1R gene among sub-Saharan Africans and an excess of non-synonymous mutations in Europe. This locus, coding for the melanocortin 1 receptor, is responsible for the activation of the dark eumelanin biosynthesis pathway [95]. Mutations in MC1R, which lead to higher pheomelanin level, lower photoprotection and increased vitamin D production, could have been advantageous when humans dispersed from Africa to environments with lower annual UV levels. However, no traces of selective enhancement have been detected, suggesting that the relaxation of a strong functional constraint in low UV environment may have been an important factor in the evolution of the MC1R gene [15]. Thus, the moderate excess of intermediate frequency polymorphisms in TYR, the highest incidence of non-synonymous mutations and failure to detect any directional positive selection by haplotype homozygosity tests can be ascribed to the relaxation of selective pressure in the European subcontinent. This is further confirmed by the highest coding nucleotide diversity (0.00067) observed in our European sample. A similar pattern was found in the MC1R gene [15,96] and is quite unusual on the genome-wide level, as more generally populations with African ancestry have the highest nucleotide diversity [97]. Furthermore, studies on these two loci are consistent with the view that accumulation of functional variation in pigmentation genes is restricted in high UV environment. In fact, in our data both sub-Saharan African and Oceanian samples almost completely lack non-synonymous TYR polymorphisms and show a virtual fixation of the amino-acid sequence ancestral to anatomically modern humans. However, it is intriguing to observe that South Asians possess considerable variation in the TYR gene. We speculate that this could be explained by the mosaic pattern of their geographic ancestry, as our sample includes populations from both the northwestern and southern parts of the Indian peninsula (Table S1).

Although we did not detect any traces of selective sweeps in TYR using haplotype-based iHS and XP-EHH tests, there is evidence from previous studies for strong sweeps acting upon the SLC24A5 and SLC45A2 genes in Europe [16,17,98]. Therefore, it is possible that various evolutionary mechanisms have affected genetic diversity within different pigmentation loci: relaxation of functional constraints or weak balancing selection may have been responsible for the excess of European-specific non-synonymous alleles in MC1R, and, as we show here, in TYR, while strong positive selection has led to the nearly complete fixation of amino-acid changing substitutions in the SLC24A5 and SLC45A2 genes.

Variation patterns in different pigmentation genes suggest that skin lightening in Eurasia was a gradual multistage process. It included the evolution of the KITLG gene in the proto-Eurasian population and convergent evolution of other loci after the split of proto-Europeans and proto-East Asians. This is reflected by the European-specific sweep in the SLC24A5, SLC45A2 and TYRP1 genes which have been dated to 19,000 to 11,000 years BP [23,99]. The tyrosinase haplogroups B1 and C2a are defined by non-synonymous substitutions and are common in Europe and North Africa. Haplogroup B1 coalesces at 15,600 and 6,100, and haplogroup C2a at 29,400 and 20,400 years BP as calculated by the Bayesian-based and rho statistics, respectively. These dates suggest that both non-synonymous mutations occurred after the split of the East and West Eurasian populations. However, the TMRCA of 6,100±3,600 years of haplogroup B1 estimated by the rho approach is still surprisingly young, considering its more than 20% frequency in Europe, North Africa and South Asia. The point estimates of these coalescent times should be interpreted with caution because of our still imperfect understanding of the mutation rates at different genetic loci. It should be noted here that our local calibration of the TYR gene mutation rate (3.0x10^-8 per site per generation) is almost three times higher than the genome average rate (1.2x10^-8 per site per generation) [80]. Applying the slower genome-wide rate would have yielded a 17 MYA coalescent date of the TMRCA of the human and chimpanzee TYR genes, which would have been in conflict with paleontological evidence. Different computational methods may also return non-identical results. The more than two-fold difference in mean coalescence times of B1 as calculated by MJ network-based rho (6,100 years BP) and Bayesian coalescence-based BEAST (15,600 years BP) approaches can be ascribed to the differences in parameter settings of the two TMRCA evaluation techniques. Overall, the most recent common ancestors of both haplogroups appear to, at least partly, overlap with the time period at which the selective sweeps at three other pigmentation genes, SLC24A5, SLC45A2 and TYRP1, have been estimated [23,99]. It is therefore possible that TYR polymorphisms have also contributed to the same adaptive process in the genetic ancestry of the West Eurasian population. This process may have been driven by various factors, including climatic, cultural and demographic changes during the cooler LGM and early post-LGM period: decrease in the winter UVR level and extensive use of protective clothing, both affecting vitamin D bioavailability, and population size growth [3,23,100]. Our results also provide evidence that besides the non-synonymous polymorphisms, variation in the 5’ flanking sequence of the TYR gene has potentially played an important role in the adaptation to UV environment.