Human Molecular Genetics

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Human Molecular Genetics, 2003, Vol. 12, No. 1 33-40
© 2003 Oxford University Press

Recombination hotspots rather than population history dominate linkage disequilibrium in the MHC class II region

Liisa Kauppi¹, Antti Sajantila² and Alec J. Jeffreys^1,*

¹Department of Genetics, University of Leicester, University Road, Leicester LE1 7RH, UK and ²Department of Forensic Medicine, University of Helsinki, Helsinki, Finland

Received August 2, 2002; Accepted November 5, 2002

	ABSTRACT

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Recombination, demographic history, drift and selection influence the extent of linkage disequilibrium (LD) in the human genome, but their relative contributions remain unclear. To investigate the effect of meiotic recombination versus population history on LD, three populations with different demographic histories (UK north Europeans, Saami and Zimbabweans) were genotyped for high-frequency single-nucleotide polymorphisms (SNPs) across a 75 kb DNA segment of the MHC class II region. This region spans three well-characterized recombination hotspots and a 60 kb long LD block. Despite a high level of underlying haplotype diversity and considerable divergence in haplotype composition between populations, all three populations showed very similar patterns of LD. Surprisingly, the entire 60 kb LD block was present even in Africans, although it was relatively difficult to detect owing to a systematic deficiency of high frequency SNPs. In contrast, DNA within recombination hotspots did not show this low nucleotide diversity in Africans. Thus, while population history has some influence on LD, our findings suggest that recombination hotspots play a major global role in shaping LD patterns as well as helping to maintain localized SNP diversity in this region of the MHC.

	INTRODUCTION

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Patterns of linkage disequilibrium (LD) in the human genome are being studied intensively since knowledge of haplotype structure would greatly facilitate attempts to map complex diseases (1,2). Association mapping relies on the assumption that LD—the non-random association of alleles at closely linked loci—is highest between a disease-causing mutation and its closest markers. The level of LD between a pair of markers depends on both molecular and population genetic factors. At the molecular level, crossover, gene conversion and recurrent mutation can reduce LD; at the population genetic level, population size, bottlenecks, admixture, drift and selection can have complex effects (3). With so many factors contributing to LD, it is hardly surprising that estimates of the extent of LD vary greatly both in different regions of the human genome and in different populations.

Earlier LD studies used microsatellites as markers (4–6), but more recently the focus has shifted to single-nucleotide polymorphisms (SNPs) because of their simpler mutational dynamics and greater prevalence in the human genome (7–11). LD between microsatellites has been reported to extend over very long distances, from over 1 Mb (4) up to 14 Mb (5) and can vary between populations, as shown by studies of microsatellites in Xq13 which have revealed LD extending further in the Saami, a small and constant-sized population from the Arctic region of Europe, than in three other north European populations (5). Such long-range associations are not seen between pairs of SNP markers, with some rare exceptions (7). Pritchard and Przeworski (12) recently termed the two classes of LD as ‘long-distance LD’ and ‘short-scale LD’. The differences probably reflect the different mutational dynamics of the two types of marker—microsatellites are multiallelic, mutate frequently and thus carry young alleles, whereas SNPs are biallelic with relatively ancient alleles. For SNPs, an early simulation study predicted that ‘useful levels of LD are unlikely to extend beyond an average distance of 3 kb in the general population’ (13), but this has since proven inconsistent with empirical observations. Dunning et al. (8) found that SNP marker pairs up to 20 kb apart could show significant LD and that levels of LD were similar across four populations of European ancestry. Abecasis et al. (9) examined LD in three genomic regions in UK north Europeans and found that half of the SNP markers were in ‘useful’ LD at a distance up to 50 kb, with occasional associations extending as far as 500 kb. Reich and colleagues estimated that LD in north Europeans extends on average 60 kb from a SNP with high (0.35) minor allele frequency, but less far in Nigerians (11). Lower levels of LD in sub-Saharan Africans were also reported by Lonjou et al. (14) and Gabriel et al. (15). The Evenki from Siberia and the Saami, two small and constant-sized populations, showed higher LD over short (up to 8 kb) distances compared with Finns and Swedes (16). In contrast, in the pseudoautosomal SHOX gene region, LD declines with physical distance at a similar rate in UK north Europeans, Vlax Roma (Gypsies) from Bulgaria and Saami, despite their very different histories (17). To summarize, most studies comparing the extent of LD in different populations have observed less LD in sub-Saharan Africans, similar levels of LD in most populations of north European ancestry and, on occasion, markedly higher LD in small and isolated populations.

There is growing evidence that meiotic recombination events in human chromosomes tend to be clustered into hotspots 1–2 kb in width, and that these recombination hotspots can strongly influence patterns of LD (17–21). Hotspots tend to be separated by extended blocks of recombinationally suppressed DNA containing markers in strong LD. This structuring of diversity into LD blocks appears to be common in the human genome (15,22), and there is evidence that LD blocks and their underlying haplotypes can be shared by diverse populations (15). It remains unclear, however, to what extent these LD blocks are the result of chance clustering of historical crossovers, in the absence of true hotspots. Also, evidence for LD blocks created by recombination hotspots comes solely from studies of north Europeans (19,20), and it is unclear how population history might influence block structure in the presence of hotspots.

To determine how recombination hotspots and population history affect LD, we chose a region over which fine-scale LD patterns and meiotic crossovers in sperm have been well characterized in UK north Europeans (20): the 75-kb long HLA-DOA/HLA-DMB interval in the MHC class II region. It contains, centromeric to telomeric, a highly active recombination hotspot termed DNA3, followed by a 60 kb long recombinationally suppressed LD block (seen in UK north Europeans) that terminates at two hotspots about 3 kb apart, termed DMB1 and DMB2, showing weak and intermediate male recombination activity respectively (Fig. 1). We investigate the extent of LD in this region in two additional populations chosen for their very different demographic histories. The Saami appear to have been of historically constant population size (23) and show more extensive LD than rapidly expanding populations (5,16). The second population is from Zimbabwe. These sub-Saharan Africans are expected to contain more ancient and diverse haplotypes and thus less extensive LD compared with Europeans, and should provide a test for erosion of the extended LD block by population processes. Very high diversity in this population has been verified by studies of the insulin gene region and its associated minisatellite, both of which show far higher levels of diversity than seen in European and Asian populations (24) (J.D.H. Stead and A.J. Jeffreys, unpublished). The present study aims to determine how known recombination hotspots influence patterns of LD in these very different populations.

View larger version (30K): [in this window] [in a new window]   Figure 1. Allele-frequency comparisons between populations. Frequencies of the allele which is less common in the UK population are shown for the UK (blue), Saami (black) and Zimbabweans (red). SNPs discovered through re-sequencing Zimbabweans are marked with white crosses. Beneath are shown the location of genes (black boxes) and LD blocks seen in the UK (open boxes). Recombination hotspots are indicated with arrows sized in proportion to their activity in male meiosis (20). Regions re-sequenced in Zimbabweans are shown as grey bars below the LD blocks.

 

	RESULTS

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Population allele frequencies differ dramatically within an LD block
We genotyped 64 SNPs in a 75 kb DNA segment of the human MHC class II region in three populations with different demographic histories—Saami, UK north Europeans and Zimbabweans. This region spans three previously characterized recombination hotspots (DNA3, DMB1 and DMB2) and a 60 kb long LD block (20) (Fig. 1). Fifty of these SNPs were identified by re-sequencing UK north Europeans and were chosen for their high (>0.2) minor allele frequency in the UK. As discussed previously (20), common SNPs have the greatest statistical power to define LD levels and, together with their relative antiquity, are most effective at identifying LD block structure. Seven SNPs were taken from dbSNP (25) and seven identified by re-sequencing four 600 bp long regions, located within the UK LD block, in six Zimbabweans (Fig. 1). In Zimbabweans, there is a striking lack of markers with high (>0.25) minor allele frequency in the inter-hotspot region between 17 and 70 kb (Figs 1 and 2A). In and near hotspots DNA3, DMB1 and DMB2, however, the density of high frequency markers is similar to that seen in the Saami and the UK. Of the seven SNPs that were discovered through re-sequencing Zimbabweans, only one had a minor allele frequency >0.25. This suggests that the rarity of high frequency SNPs is a genuine feature of the inter-hotspot region in Zimbabweans, rather than arising through biased ascertainment of SNPs.

View larger version (57K): [in this window] [in a new window]   Figure 2. Population comparisons of linkage disequilibrium (LD) patterns. (A) LD in UK north Europeans, Saami and Zimbabweans. |D'| measures (lower right) are shown for all pairs of markers with minor allele frequency >0.15 together with the associated likelihood-ratio (LR) versus free association (upper left), and colour-coded as indicated in the box. Each point is plotted as a rectangle centered on each SNP (locations shown below and to right of the plot, minor allele frequencies shown under the plot) and extending half-way to adjacent markers. In Zimbabweans, only one marker within the LD block has a minor allele frequency >0.25 (dashed line). (B) Plots expanded to focus on regions around recombination hotspots [open boxes on distance scale in 2(A), hotspots arrowed]. The locations of SNPs are shown below each plot. (C) Decay of the || measure of LD with distance within the LD block. Only markers in the interval 11689–64980 bp and with minor allele frequency >0.15 were included. Lines show the least squares best-fit curves (UK, blue; Saami, black; Zimbabweans, red) for the relationship 2=1/(1+4Nerd) where Ne=effective population size, r=recombination rate per base pair interval and d is the distance in bp between markers (29).

 
Minor allele frequencies at these SNPs differed systematically between the three populations studied, with Saami allele frequencies tending to be higher and Zimbabwean allele frequencies lower than seen in the UK (Fig. 1). This is reflected in Nei's genetic distance (26), which is greatest between Saami and Zimbabweans (0.0912) and smaller for UK/Saami (0.0205) and UK/Zimbabwean (0.0340) comparisons. The GENEPOP test for genic differentiation, which compares allele frequencies between pairs of populations (27), showed that allele frequencies at 41% of markers (24 of 59 possible comparisons) were significantly different (P<0.05) between UK and Saami, at 50% of markers (29/59) between UK and Zimbabweans and at 71% of markers (40/56) between Saami and Zimbabweans. These shifts in allele frequency were most marked for SNPs located within the extended LD block seen in the UK (Fig. 1).

The same LD block is observed in all populations
SNP genotypes were used to predict maximum-likelihood haplotypes for pairs of markers which were then subjected to LD analyses. D' is a commonly used measure of linkage disequilibrium, where |D'|=1 for marker pairs showing complete association with at most only three of the four possible haplotypes (28), and is useful for detecting obligate historical recombination between markers. Analysis of D' values for all marker pairs (Fig. 2A) showed LD patterns structured into LD blocks, within which most or all SNPs were in significant LD, separated by regions corresponding to known recombination hotspots across which markers did not show significant associations. The block-like LD structures seen in UK north Europeans (20) are also present in the Saami. Somewhat surprisingly, the outline of the 60 kb LD block is still recognizable in Zimbabweans. In all three populations, this extended LD block terminates at experimentally verified recombination hotspots. The LD block appears to be incomplete in Zimbabweans, but does include highly significant associations spanning the entire length of the block; the apparent decay in Zimbabweans is in part due to the relatively low minor allele frequencies and the consequently reduced statistical power to detect associations.

Closer examination of LD patterns near recombination hotspots (Fig. 2B) shows that the UK sample has the ‘cleanest’ block-like structure, with no significant associations across any of the hotspots and with clear LD blocks lying upstream of hotspot DNA3, downstream of DMB2 and between DMB1 and DMB2. In the Saami, only one marker in the 60 kb LD block shows statistically significant associations across DNA3. In contrast, the weakest hotspot (DMB1) has not left any signature on Saami LD structure, with the LD block that lies between hotspots DMB1 and DMB2 being fused to the 3' end of the extended LD block. Instead, in the Saami there is a region of LD breakdown a few kilobases further 5', at 70 kb, which is not observed in either UK north Europeans or Zimbabweans (Fig. 2A and B). In Zimbabweans, there are no significant associations across hotspots, except for one marker pair spanning DNA3, and the short LD block lying between DMB1 and DMB2 is still discernable.

is a measure of absolute association (29) and is dependent on allele frequencies; it only shows values of 1 when just two haplotypes per marker pair are observed, whence both markers must have the same allele frequencies. also has a formal relationship to effective population size N_e, recombination rate r per unit distance and inter-marker distance d, where ²=1/(1+4N_erd ) for a population at recombination/drift equilibrium for selectively neutral haplotypes (30). Comparison of values within the 60 kb LD block with inter-marker distance (Fig. 2C) showed that declines much more rapidly in Zimbabweans than in UK north Europeans and Saami, who show very similar decay profiles. The least squares best-fit values for the product N_er per Mb were 10 for Saami, 11 for UK north Europeans and 220 for Zimbabweans. Assuming that recombination rate is constant between populations, this suggests that the effective population size of the Zimbabwean population is 20 times higher than either UK north Europeans or Saami. This high estimate for Zimbabweans provides further evidence that this population is considerably more ancient and diverse than north Europeans.

Cosmopolitan haplotypes within the extended LD block are uncommon
To investigate the underlying haplotypes within the 60 kb LD block, we inferred full haplotypes using the PHASE program (31) from the unambiguous genotypes of 29 SNPs that are located in the region between the DNA3 and DMB1 hotspots; SNPs in recombinationally active regions within hotspots were excluded. Twenty different haplotypes were found in the 49 UK north Europeans typed, compared with 21 haplotypes in 40 Saami and 40 haplotypes in 44 Zimbabweans. Haplotype diversity (32) is higher in Zimbabweans (0.97) than in Saami (0.91) or UK north Europeans (0.87), as expected for an older population.

Comparison of haplotypes across all three populations revealed 15 common haplotypes (H1–H15) each with a frequency of 5% in at least one population (Fig. 3A). Results for common haplotypes, cosmopolitan haplotypes present in all three populations and population-specific haplotypes for the full data set of 29 SNPs spanning 53 kb of the 60 kb LD block are summarized in Figure 3A and Table 1. Common haplotypes can be loosely divided into two groups according to structure (Fig. 3A): green/largely green haplotypes (H1–H5) and largely yellow haplotypes (H6–H15), where green and yellow indicate alternative alleles of SNP sites. No intermediate (half green–half yellow) haplotypes were found among the common haplotypes. Four SNPs that lie well within the LD block show evidence for obligate historical recombination, appearing in all four possible haplotype combinations with at least one other marker within the LD block. Haplotypes tend to show a high degree of population specificity. For example, haplotype H15 is common in the UK but was not seen in Saami or Zimbabweans. When all haplotypes are considered, each population shows a large fraction of population-specific haplotypes. Cosmopolitan haplotypes shared by all three populations are uncommon, accounting for only 27% of UK chromosomes and 19% of Saami chromosomes, and for just 5% of Zimbabwean chromosomes (Fig. 3B).

View larger version (30K): [in this window] [in a new window]   Figure 3. Haplotypes within the extended LD block. (A) Fifteen common haplotypes, each at 5% frequency in at least one population (labelled H1–H15), were inferred from diploid genotype data. The structure of each haplotype is shown on the left, with circles representing SNP sites, shaded green or yellow to indicate alternative alleles. SNP positions are shown under the haplotypes. Two SNPs that were monomorphic among the 15 common haplotypes are not shown. Haplotypes can be roughly grouped according to structure, with H1–H5 largely green and H6–H15 largely yellow. SNPs showing evidence for recombination (four haplotypes with at least one other marker) are arrowed. The frequencies of each haplotype in each population are shown on the right (UK, blue; Saami, black; Zimbabweans, red). (B) Percentage of haplotypes that are shared between all three populations, between two populations and that are unique to each population (percentages in blue for UK, black for Saami and red for Zimbabweans). All haplotypes predicted by the PHASE program were included.

 

View this table: [in this window] [in a new window]   Table 1. Inferred haplotypes within the extended LD block using the full data set and reduced data sets (see text)

 
Because higher marker density will tend to increase haplotype diversity, we also inferred LD block haplotypes from a reduced data set using 15 of the 29 SNPs selected at random, giving an average marker density of 1 SNP every 2.8 kb and retaining three of the four SNPs that show evidence for obligate historical recombination (‘first random half’ data set in Table 1). We also inferred haplotypes from the remaining 14 SNPs, containing just one marker with evidence for obligate historical recombination, and from a data set where only the four SNPs showing evidence for obligate historical recombination were removed (‘second random half’ and ‘without recombinant SNPs’ data sets in Table 1, respectively). The first reduction of the data set had a more dramatic effect on lowering haplotype diversity and increasing the incidence of cosmopolitan haplotypes than the second, suggesting that both recombination within the LD block and marker density contribute to haplotype diversity and the population-specificity of haplotypes.

	DISCUSSION

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
We have previously shown that within the MHC class II region, there are extended blocks of SNPs in LD, separated by short regions where LD breaks down and which correspond to recombination hotspots of varying intensities in UK north Europeans (20). The present study of the HLA-DOA/HLA-DMB interval shows that this LD block pattern, as defined by SNPs with high frequency alleles that are likely to be ancient, is shared by two additional populations with very different histories. This sharing is even seen in Zimbabweans, despite the evidence that this population is ancient and genetically very diverse. Surprisingly, the Saami do not exhibit either reduced haplotype diversity or increased levels of association within the extended LD block or across the strongest recombination hotspots, as might be expected of a constant-sized population.

Previous analyses of LD structure elsewhere in the human genome have similarly shown that LD blocks seem to be common and are often shared between populations (11,15). LD blocks tend to contain limited repertoires of typically two to five common haplotypes defined by common SNPs (10,15,22,33), some of which can be shared across major population divides, for example non-Africans and Africans (10,15,33). The existence of these apparently cosmopolitan haplotypes suggests that much of the current haplotype structure in human populations is ancient and was established prior to the recent diversification of mankind. As a result, LD block structure can show similarities in diverse populations, with more recent influences such as founder effects modifying LD patterns, for example with two or more ancient LD blocks, as seen in Africans, being fused into a single block in younger (non-African) populations.

This study of the MHC class II region reveals what appears to be a very different picture. First, the three populations surveyed all show very high levels of haplotype diversity within the extended LD block, with 15 common haplotypes in the overall data set. This diversity is not the result of our using an excessively high density of SNPs; our density (averaging 1 SNP per 1.8 kb) is comparable to the density used in the LD surveys of a 500 kb region on chromosome 5 (one SNP per 5 kb) (22) and of chromosome 21 (one SNP per 1.3 kb) (33). The 60 kb LD block is therefore unusually diverse, possibly reflecting diversifying selection acting on the MHC. Alternatively, the increased diversity may reflect differences in the definition of LD blocks. Our definition is based on the very clear-cut localized breakdowns of LD which correspond to recombination hotspots and serve to demarcate LD blocks (Fig. 2A). The studies of Daly et al. (22) and Gabriel et al. (15) instead used the identification of SNP pairs showing ‘strong LD’ or ‘strong evidence for historical recombination’ to delimit LD blocks. It appears that these criteria are more stringent than ours, and if applied to our LD block could result in an artificial break-up into smaller blocks, each of lower diversity.

More significantly, there is little evidence within the MHC LD block for cosmopolitan haplotypes as seen elsewhere in the human genome (10,15,33). Rather, many of the haplotypes appear, within the limits of our sample sizes, to be largely if not completely population-specific. This specificity even extends to the two European samples; for example, the second most common Saami haplotype (H8 at 14% frequency) was not seen in the UK, and likewise the second most common UK haplotypes (H12 and H15, both at 17% frequency) were not found in the Saami (Fig. 3A). This implies that this region has been subjected to a high rate of haplotype turnover and that current haplotype structures were not established early in human history. Despite this turnover, LD block structure has remained remarkably constant in all three populations. It therefore follows that the recombination hotspots must have played the dominant role in shaping these patterns in all three populations, and that they have been sufficiently active to prevent LD block fusion, even in young populations. The only exception is hotspot DMB1, which has left no clear imprint on LD structure in Saami. This hotspot is weak, contributing only 0.003 cM to linkage map distance in males (its activity in female meiosis is unknown), compared with 0.13 cM and 0.03 cM for hotspots DNA3 and DMB2, respectively (20). It therefore appears that the more intense hotspots are sufficiently active to over-ride effects of population history on LD patterns, a conclusion supported by a recent study of human genome-wide sequence variation (34).

Haplotype turnover events within the MHC LD block include what appear to have been recombinational exchanges involving four SNPs deep within the block. However, these exchanges have not generated any obvious crossover haplotypes (half green–half yellow, Fig. 3A) and may instead have involved either localized gene conversion events or alternatively recurrent mutation at these SNPs. The latter appears unlikely because two of these sites are transversions and only one is a transition at a potentially hypermutable CpG doublet. It is also noticeable that these apparently recombinational events within the LD block have not resulted in the collapse of the extended LD block into two or more clearly defined shorter LD blocks in Zimbabweans, who are an old population in which very weak recombination hotspots would have the potential to leave their mark on LD structure. This suggests that rare recombination events within the LD block do not cluster into weak hotspots.

While the MHC LD block structure is remarkably similar in the three populations tested, the extended LD block is relatively difficult to detect in Zimbabweans. Part of the difficulty lies in the systematic dearth of high frequency SNPs within the LD block in Zimbabweans, which limits the statistical power to detect associations. A similar systematic shift is seen in the higher frequencies of minor alleles in Saami compared with UK north Europeans (Fig. 1). This correlated behaviour of multiple SNPs is expected for a recombinationally suppressed region of DNA in which allele fixation or extinction at different SNPs will not occur independently; thus, loss of a haplotype from a population will result in loss of all variants restricted to that haplotype. It is noticeable that these correlated shifts in allele frequencies in different populations do not appear to affect SNPs within and near the recombination hotspots (Fig. 1). Again, this is expected; SNPs in recombinationally active DNA can escape rapid correlated extinctions by being constantly reshuffled onto different haplotypes. The implication under this model is that hotspots should always show relatively stable levels of nucleotide diversity (in the absence of additional molecular processes that could influence SNP diversity) (35). In contrast, recombinationally inactive LD blocks will show much more unpredictable levels of high frequency SNPs. A block will be difficult to detect by LD analysis if it happens to be in a period of low diversity, whether purely by chance or through processes such as selective sweeps.

It remains unclear whether the MHC class II region is wholly exceptional in its level of haplotype diversity and its rapid turnover, with perhaps turnover processes being aided by selection on the MHC. Additional work is needed to see if LD structuring in other regions of the human genome does not merely reflect ancient events but is instead a dynamic ongoing process involving a complex interplay between recombination hotspots, SNP turnover, drift and selection.

	MATERIALS AND METHODS

TOP ABSTRACT INTRODUCTION RESULTS DISCUSSION MATERIALS AND METHODS REFERENCES

 
Population samples
Saami blood DNA samples were collected from 40 unrelated individuals living in the Kola Peninsula region of Russia. The 49 UK north Europeans are from the semen donor panel described previously (20). Forty-eight Zimbabwean DNA samples are from unrelated men from Harare.

Identification and selection of SNP markers
SNPs previously discovered in UK north Europeans (20) were genotyped as described previously (20). Seven SNPs were identified from dbSNP (25). All SNPs with minor allele frequency higher than 0.2 in UK north Europeans were also genotyped in Saami and Zimbabweans. To screen for additional polymorphisms in Zimbabweans, four 600 bp regions were re-sequenced in six individuals. Seven new SNPs so discovered were typed in all populations.

PCR and genotyping
We used PCR primers designed from the current MHC consensus sequence (36) to amplify twelve 3.4–6.7 kb long DNA segments from 50 UK north Europeans, 40 Saami and 48 Zimbabweans. Sixty-four SNPs were typed by ASO hybridization to dotblots of PCR products (19) from all three populations. Primer and ASO sequences are available on request and at www.le.ac.uk/genetics/ajj/HLA. Some of these SNPs (one in the UK, five in Saami, six in Zimbabweans) could not be typed, presumably because of additional unknown SNPs that block ASO hybridization. Amongst the scored genotypes, some were ambiguous, mainly due to poor PCR amplification resulting from low or poor-quality DNA input, particularly in the Zimbabwean DNA samples; these ambiguous genotypes (three out of 3084 in the UK, seven out of 2360 in Saami, 122 out of 2784 in Zimbabweans) were excluded from further analyses. In the final dataset, very few markers showed deviation from Hardy–Weinberg equilibrium (two in the UK, one in Saami and three in Zimbabweans); after Bonferroni correction, none of these deviations was significant.

Linkage disequilibrium analyses
LD analyses were carried out on unphased diploid genotype data and plotted using software written in True BASIC 4.1 by A.J.J. (20). The program estimates maximum-likelihood haplotype frequencies from diploid genotypes of pairs of markers and calculates LD measures for both complete association (|D'|) (28) and absolute association (||) (29). It also estimates the likelihood ratio (LR) in favour of significant LD. SNPs with lower than 0.15 minor allele frequency were excluded from LD analyses.

Haplotype analysis
Multi-site haplotypes were inferred from genotype data using PHASE software version 0.21 (31) available at www.stats.ox.ac.uk/mathgen/software.html. Each run was repeated 10 times with different seeds and the average haplotype frequency generated by the runs was calculated. The input data for PHASE runs consisted of unambiguous SNP genotypes for 29 SNPs (SNPs with minor allele frequency >0.2 in UK north Europeans plus all SNPs identified through re-sequencing Zimbabwean DNA) located within the LD block in 40 Saami, 49 UK north Europeans and 44 Zimbabweans. When an individual is heterozygous for a SNP site, the PHASE program gives a probability for correct phase calling. These probabilities were generally high (P>0.95) for the common haplotypes; for 11 of the haplotypes, at most only one SNP showed any evidence for uncertain phase calling in any of the individuals. To analyse the effect of numbers of markers on haplotype diversity, we also inferred haplotypes from the following reduced data sets: excluding 14 randomly chosen SNPs across the region; excluding the ‘opposite’ set of 15 SNPs; and excluding all four SNPs that displayed evidence for obligate historical recombination.

	ACKNOWLEDGEMENTS

 
We thank J. Blower for providing UK semen samples, S.B. Kanoyangwa for providing Zimbabwean samples, A. Kozlov and G. Vershubskaja for help in contacting Saami volunteers and UK and Saami volunteers for blood samples. We are grateful to C. May, J. Stead, R. Badge and other colleagues for helpful discussions. This work was funded by grants to L.K. from the Instrumentarium Science Foundation, the Finnish Cultural Foundation and the Osk. Huttunen Foundation and to A.J.J. from the Medical Research Council and Royal Society.

	FOOTNOTES

 
^* To whom correspondence should be addressed. Tel: +44 1162523435; Fax: +44 1162523378; Email: ajj{at}le.ac.uk

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