Haplotype Structure and Evidence for Positive Selection at the Human IL13 Locus
http://www.100md.com
分子生物学进展 2004年第1期
* Department of Genomics and Proteomics, Beijing Institute of Radiation Medicine
Chinese National Human Genome Center at Beijing, Beijing, China
E-mail: hefc@nic.bmi.ac.cn.
Abstract
Interleukin-13 (IL13) is believed to play an important role in the pathogenesis of atopy and allergic asthma. To better understand genetic variation at the IL13 locus, we resequenced a 5.1-kb genomic region spanning the entire locus and identified 26 single-nucleotide polymorphisms (SNPs) in 74 individuals from three major populations—Chinese, Caucasian, and African. Our survey suggests exceptionally high and significant geographic structure at the IL13 locus between African and outside Africa populations. This unusual pattern suggests that positive selection that acts in some local populations may have played a role on the IL13 locus. In support of this suggestion, we found a significant excess of high frequency–derived SNPs in the Chinese population and Caucasian population, respectively, as expected after a recent episode of positive selection. Further, the unusual haplotype structure indicates that different scenarios of the action of positive selection on the IL13 locus in different populations may exist. In the Caucasian population, the skewed haplotype distribution dominated by one common haplotype supports the hypothesis of simple directional selection. Whereas, in the Chinese population, the two-round hitchhiking hypothesis may explain the skewed haplotype structure with three dominant ones. These findings may provide insight into the likely relative roles of selection and population history in establishing present-day variation at the IL13 locus, and, motivate further studies of this locus as an important candidate in common diseases association studies.
Key Words: interleukin-13 ? single nucleotide polymorphism ? positive selection
Introduction
It has been reported that polymorphisms in Interleukin-13 (IL13) can result in the interindividual variability in the expression (van der Pouw Kraan et al. 1999) and activity level of the gene product (Heinzmann et al. 2000). Numerous studies have also been performed on the association of this locus to various atopy and asthma phenotypes, such as bronchial hyperresponsiveness (BHR), positive allergen skin-test responses, and elevated total-serum immunoglobulin IgE levels, in several populations (Graves et al. 2000; Liu et al. 2000; Howard et al. 2001; Leung et al. 2001), but positive and negative associations have been accepted with reservation and have been difficult to replicate in subsequent studies. This inconsistency may reflect differences in phenotype definition, lack of statistical power, the effects of other loci, and the varying effects of presumably several disease-predisposing variants within IL13 (Lalouel 2001; Glazier, Nadeau, and Aitman 2002). Besides that, the potential for allergenic responsiveness to change in novel environments makes IL13 a possible target of local adaptation. Thus, failure to take into account the evolutionary history of the IL13 locus, such as the effects of population history and structure and/or natural selection, which may shape the linkage disequilibrium (LD) pattern and hence the likelihood of an association, may be another important cause of inconsistency in association studies (Jobling et al. 1998; Fullerton et al. 2002; Rosenberg et al. 2002).
An important step for studies explaining the role of genetic variation in risk of disease is a description of quality, quantity, and organization of genetic variation within and between human populations. To further understand genetic variability at the IL13 locus, we undertook a continuous scan for sequence variation patterns in unrelated individuals. The corresponding chimpanzee (Pan troglodytes) sequence was also completed, to serve as an outgroup for evolutionary and population genetic tests. Our study provides insight into the likely relative roles of selection and population history in establishing present-day genetic variation at the IL13 locus.
Materials and Methods
DNA Samples
Human genomic DNA was derived from two sources. (1) Forty-seven DNA samples were provided by Coriel Cell Repositories, Camden, NJ. These consisted of 24 Caucasian and 23 African DNA samples. (2) Samples from 27 unrelated Chinese individuals unselected for disease status were provided by Chinese human genome center at Shanghai, and Institute of Genetics and Developmental Biology, CAS. Informed consent was obtained from all Chinese participants, and the study was performed with the approval of the Ethical Committee of Chinese Human Genome. The same genomic regions were also sequenced in one common chimpanzee, which was also provided by Coriel Cell Repositories, Camden, NJ.
Laboratory Analysis
Overlapping primer sets covering the genomic sequence of IL13 (GenBank accession number AC074127.2), which span more than 5 kb, were designed on the basis of size and overlap of PCR amplicons by use of Primer 3.0, release 0.9 (http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi). We performed PCR in a total volume of 25 μl, containing 0.2 mM dNTPs, 4.5 mM MgCl2, 150 pM of each primer, 1 x standard buffer, 1 x Q-solution, 1 U Hotstar Taq polymerase (Qiagen), and 10 ng of genomic DNA. PCR conditions were as follows: 41 cycles of denaturation at 95°C, annealing at 56°C, and primer extension at 72°C, each step for 45 s. The first step of denaturation and the last step of extension were 15 min and 5 min, respectively. PCR products were purified by use of the 96-well microtitre purification plate according to the manufacturer's protocol (Millipore). Cycle sequencing was performed on PCR products in both directions according to the manufacturer's instructions using ABI PRISM Dye Terminator Sequencing Kits with Amplitaq DNA polymerase, FS (PerkinElmer). Excess dye terminators were removed by ethanol precipitation. The extension products were evaporated to dryness under vacuum (Savant Instruments), resuspended in 10 μl ddH2O, heated for 2 min at 92°C and loaded onto an Applied Biosystems 3700 sequencer.
SNP Identification
The ABI sequence software version 1.1 was used for lane tracking and first pass base-calling (PerkinElmer). The Phred-Phrap-Consed-PolyPhred package was used to assemble the sequences and identify SNPs. Specific descriptions and documentation on the above programs are available at http://www.genome.washington.edu. Once identified by PolyPhred, SNPs were visually inspected by at least two observers. Each SNP position and each individual's genotype has been confirmed by reamplifying and resequencing the SNP site from the same or opposite strand. Furthermore, because of the sequence overlap within the analyzed regions, more than one call for each genotype was often obtained for each position in a sample.
Data Analysis
Allele frequencies for each SNP were determined by gene counting, and the significance of deviations from Hardy-Weinberg equilibrium was tested using the random-permutation procedure implemented in the Arlequin package (http://lgb.unige.ch/arlequin/).
IL13 haplotypes were assigned by the computer program PHASE (Stephens, Smith, and Donnelly 2001). The Netwok 3.0 package (http://www.fluxus-technology.com/sharenet.htm) was used to construct the minimum-mutation network, which reflect the mutational relationships among the inferred haplotypes and the evolutionary history of genetic changes at the IL13 locus by means of the Reduced Median (RM) algorithm (Bandelt et al. 1995), with the common chimpanzee as an outgroup species. Trees were also constructed using the neighbor-joining, parsimony, and maximum-likelihood methods implemented in the PHYLIP software package (http://evolution.genetics.washington.edu/phylip.html). Two different statistical tests of the null hypothesis of neutrality—the haplotype partition test (HP test) (Hudson et al. 1994) and the haplotype diversity test (Hd test) (Depaulis and Veuille 1998)—were carried out, assuming randomly generated haplotypes. Significance values for each of the above two test statistics were estimated from 104 coalescent simulations using the program ALLELIX (http://www.snv.jussieu.fr/mousset/), which condition on the sample size and the number of segregating sites as the observed data, under a conservative assumption of no recombination.
To test for differentiation between populations, FST (Wright 1951), which reflects differences in allele frequencies among samples and increase as allele frequency differences between population samples become more pronounced, was calculated using the program Arlequin.
The human sequences were aligned with the chimpanzee sequence to identify fixed difference and the ancestral allele/haplotype. Sequence divergence was measured by aligning the chimpanzee outgroup sequence with the human polymorphic sample.
Genetree software (http://www.maths.monash.edu.au/mbahlo/mpg/gtree.html) was used to estimate the likelihood that the observed outside Africa haplotypic distribution could arise through neutral evolution under a simple out-of-Africa model (Griffiths and Tavaré 1994).
Three measures of diversity were computed for each of the three population samples and the pooled samples: (1) Watterson's W (Watterson 1975), based on the number of segregating sites in the sample, an estimate of the expected per-site nucleotide heterozygosity, theoretically equal to the neutral mutation parameter 4Nem; (2) (Nei and Li 1979), the direct estimate of per-site heterozygosity derived from the average number of pairwise sequence differences in the sample; and (3) H (Fay and Wu 2000), a summary that gives more weight to high frequency–derived variants. To test whether the frequency spectrum of mutations conformed to the expectations of the standard neutral model, we calculated the values of two test statistics: (1) Tajima's D statistic (Tajima 1989), which considers the difference between W and , and (2) Fay and Wu's H statistic, which considers the difference between H and . Under neutrality, the two test statistics should be close to 0. Fu and Li's D statistic (Fu and Li 1993) was used to compare the observed number of singleton polymorphisms with those expected under a neutral model. Significance values for each of the above three test statistics were estimated from 104 coalescent simulations of a Wright-Fisher equilibrium model that condition on the sample size and level of polymorphism as the observed data, with no recombination (Hudson 1990), using DnaSP Software (Rozas and Rozas 1999) and Fay's H-test version 1.0, respectively. The Hudson/Kreitman/Aguadé (HKA) test (Hudson 1987) was used to compare diversity patterns in the IL13 region with diversity patterns found at two other loci: ?-globin (Harding et al. 1997) and DMD intron 44 (Nachman and Crowell 2000a), using the HKA computer program (http://lifesci.rutgers.edu/heylab).
Results and Discussion
Rescreening of 5,100 bp of IL13 genomic DNA in the overall 74 samples revealed 26 SNPs (table 1). The extent of nucleotide diversity (table 2) for the overall sample ( = 7.5 x 10–4) was similar to the diversity reported for other autosomal human genetic loci (Harding et al. 1997; Clark et al. 1998; Rieder et al. 1999; Hamblin and Di Rienzo 2000; Subrahmanyan et al. 2001). Among the three population samples, the African population had the highest value, followed by the Chinese and Caucasian populations. The Caucasian population had a value ( = 3.3 x 10–4) about two times lower than those of the Chinese and African populations, respectively, and, fell at approximately the 5th percentile in the International SNP Map Working Group's distribution (see fig. 2a in International SNP Map Working Group 2001), which found a modal value of about 7.0 x 10–4, with a range 0.0 to 20.0 x 10–4.
Table 1 Alleles and Their Frequencies in the Chinese, Caucasian, and African samples, and, Pairwise Estimates of FST.
Table 2 Population Variability Parameters and Neutrality Tests for Human IL13 Locus.
FIG. 2. Suggested minimum-mutation network for IL13 haplotypes, based on 11 SNPs and the chimpanzee sequence. Node areas are proportional to haplotype frequency. Each node is shaded to indicate the fraction of time it was found in each population. Mutational differences between haplotypes are indicated on the branches of the network (SNPs and haplotypes are numbered as in table 1 and table 3, respectively; SNPs that result in amino acid substitutions are boxed). The solid branches represent mutation events, and the dashed branches indicate alterative topologies of equal length (may be recurrent mutation or recombination events). Haplotype cluster A and B are shown in the top and bottom dashed boxes, respectively
One common chimpanzee sequence (4,588 bp) was obtained to infer the ancestral and derived states for each human SNP and haplotypes (tables 1 and 3) and to estimate the number of fixed differences between humans and chimpanzee. It was monomorphic at all of the positions that were variable in humans. Human-chimpanzee divergence was 0.72% (33 sites). From divergence, the estimate of the average mutation rate per site per year is 7.14 x 10–10 (assuming a divergence time of 5 Myr BP between human and chimpanzee), lower than, but not significantly different from, those described for other loci (Harris and Hey 1999; Jaruzelska et al. 1999; Kaessmann et al. 1999; Nachman and Crowell 2000b; Yu et al. 2001), suggesting a slightly stringent level of selective constraint in this locus. Estimates of the effective size, Ne, were similar to earlier estimates when calculated under the assumption of a mutation rate of 7.14 x 10–10 (5,000 to 20,000 range) (Harding et al. 1997; Nachman 1998; Zhao et al.2000). W yielded Ne estimates of 16,282 for the overall sample, of 9,302 for Chinese, of 10,161 for Caucasian, and of 15,931 for African.
Table 3 Haplotypes and Their Estimated Frequencies in Each Population.
We calculated the FST statistic to assess whether there was evidence for differentiation among the populations in our sample. Application of the FST statistic to all pairs of populations revealed significant geographic structure (table 1). It is noteworthy that the FST between Caucasian and African (FST = 0.25) is considerably higher than that typically observed (Cavalli-Sforza, Menozzi, and Piazza 1994). To further resolve the degree of geographic structure of IL13 variation pattern, we calculated the FST statistic on a site-by-site basis for all pairs of populations (table 1). Each of the population pairs has five SNPs with high and significant FST values. To determine if the degree of interpopulation differentiation at the IL13 locus differs from the genomewide pattern, we compared the FST values of the IL13 SNPs to those of the 86 biallelic variants with similar sets of pooled African versus pooled non-African samples (the allele frequency data of these 86 biallelic variants were used to construct an empirical distribution of FST values [see fig. 2 in Fullerton et al. 2002]). This analysis suggested that the IL13 FST values are exceptionally high and significant, with estimates for one (i.e., SNP T749C), three (i.e., SNPs T749C, T1922C, and C2579A), and two (i.e., SNPs T749C and T1922C) SNPs falling above the 95th percentile of the genomewide distribution for Chinese–African, Caucasian–African, and non-African–African population pairs, respectively. This unusual pattern of geographic structure at the IL13 locus, which has also been observed at other human loci in other studies (Taylor, Shen, and Kreitman 1995; Hamblin and Di Rienzo 2000; Fullerton et al. 2002), may be consistent with the action of positive natural selection.
To further validate the hypothesis of positive selection attributed to the locus-specific pattern of unusual population differentiation at the IL13 region, a series of neutral model tests was used on each population and pooled populations (table 2). Tajima's D statistic suggested no statistically significant deviation from selective neutrality. Fu and Li's D test indicated a significant excess of singletons in the overall population but not in individual and pooled outside-Africa populations. In addition, by the comparison of the level of IL13 polymorphism and divergence to that observed at two other sampled human loci, ?-globin (Harding et al. 1997) and DMD intron 44 (Nachman and Crowell 2000a), HKA test suggested no significant differences (P > 0.05, data not shown).
However, when we use the recent Fay and Wu's H test, which compares the fit of the observed derived allele frequency spectrum of the SNPs with that expected under neutrality (fig. 1), it is significant in the Chinese (P = 0.043), Caucasian (P = 0.010), and pooled non-African (P = 0.032) populations but not in the African population (P = 0.783). A significant H test is thought to be the unique signature of a very recent sweep (Fay and Wu 2000; Otto 2000).
FIG. 1. Frequency spectrum of derived alleles. (A) Chinese population; (B) Caucasian population; (C) African population. Obs., the observed number of SNPs; Exp., the expected number of SNPs. The expected frequency spectrum is given by Watterson (1975). That is, at the neutral equilibrium, the expected number of SNPs sites at which the derived allele is present i times in the sample is given by 4Nv/i, where N and v are the effective population size and mutation rate, respectively. The formula to estimate 4Nv is the number of observed sites divided by (1 +1/2 + 1/3 + ... + 1/n–1), where n is the number of chromosomes in each population
The failure of Tajima's D and Fu and Li's D tests to reject the hypothesis of neutrality within individual populations and the lack of substantial reduction of nucleotide diversity (assuming ?-globin and DMD intron 44 locus are evolving neutrally) may be due to several reasons. One possibility is the power of these two tests to detect the effects of selection is weak when the sample sizes are small and the numbers of segregating sites are few (Simonsen, Churchill, and Aquadro 1995). Another possibility is that the number of selectively driven events is much smaller and the last sweep occurred too long ago to leave a trace. Alternatively, positive selection may have been constantly at work but too weak to depress the nucleotide diversity, thus leaving no trace detectable by either Tajima's D or Fu and Li's D test. Thus, diversity reduction may be viewed as an extreme example of strong selection disrupting the gene frequency spectrum, while weaker selection may leave a different signature by dragging nearby variations to higher than expected frequencies without causing fixation. Under this circumstance, such weak positive selection can be more effectively detected by examining the frequency spectrum of derived alleles, as shown in figure 1. The successful application of Fay and Wu's H test may have justified the above hypothesis.
Having informed ourselves that positive selection may have operated at the IL13 locus in the Caucasian and Chinese population, we attempt to clarify how selection might have worked in this system. We constructed haplotypes on the basis of the genotype data from 11 SNPs selected to span most of IL13 using PHASE program. A 97% phase assignment was made with greater than 90% certainty. Thirty-eight haplotypes were identified. Consistent with above substantial difference in terms of FST among populations, haplotype diversity, the probability that two haplotypes randomly chosen from the sample will be different, also appeared quite different, with 0.979 in the Africans, 0.857 in the Chinese, and 0.551 in the Caucasians, respectively.
Further, the outside-Africa population data sets suggested unusual haplotype distribution. In the Caucasian population, the haplotype 3 was the only predominant haplotype, having a frequency of 0.67. In the Chinese population, the haplotypes 1, 3, and 4 were most common, having frequencies of 0.20, 0.26, and 0.19, respectively, and frequencies of only 0.02, 0.07, and 0.02, respectively, in the African population (table 3). To determine whether the observed haplotype distribution was consistent with the expectations of a neutral equilibrium model, we applied two tests of neutrality: Hd and HP. The Hd test suggested a significant reduction with respect to the neutral expectation in the haplotype diversity of the Caucasian sample (table 2). The HP test further revealed that polymorphic sites are not uniformly distributed among the sequences in the Caucasian sample (table 2). The above three most common haplotypes may have expanded outside Africa because of natural selection, which may fix different haplotypes in different populations.
The likely genealogical history of the observed SNPs was inferred from RM network (Bandelt et al. 1995) constructed for 12 common haplotypes (fig. 2), using the Netwok 3.0 software package. As shown in the RM network, the picture was dominated by two main clusters that differ at five SNP sites (involving SNPs T1922C, A2043G, A2524G, C2579A, and T2748C). One cluster, contained haplotypes 1 and 10 (referred to here as "cluster A"), and the other cluster, contained haplotypes 2, 3, 4, 7, and 8 (referred to here as "cluster B"). The same clusters and root position were also seen in trees constructed by the neighbor-joining and parsimony methods performed by the PHYLIP package. Haplotypes from cluster A and cluster B were found in approximately 12% and 54% of sampled chromosomes, respectively. Both clusters were found in the Chinese, Caucasian, and African samples. The observation that two distinct haplotype clusters with broadly overlapping geographical distribution are present provided further evidence for positive selection on the IL13 region. Furthermore, the RM network could give us more detailed information and indicate that different scenarios of action of positive selection in different populations may exist. Indeed, there are an accumulating number of examples where distinct selective pressures appear to apply in different environments (Harris and Hey 1999; Rana et al. 1999; Hamblin and Di Rienzo 2000). Clearly, the genetic variation pattern in the Caucasian population can be explained by the simple selection sweep hypothesis (Maynard Smith and Haigh 1974; Hudson 1990). However, in the Chinese population, the situation may be more complex. It is possible that an older selection sweep may have happened and driven the cluster B (including haplotypes 2, 3, 4, 7, and 8) to high frequency. The higher haplotype diversity of the cluster B is consistent with its relative antiquity. Afterwards, a more recent hitchhiking event may have taken place and driven the cluster A (including haplotypes 1 and 10) to high frequency. This second round of selection sweep in the Chinese population may still be active because of the very low frequency of cluster A outside of the Chinese population (table 3). Alternatively, the focal point of positive selection is a bit further away that allows recombination to happen before haplotypes 1 and 10 even get to beyond 0.20.
Another plausible factor that can explain the present-day variation pattern at the IL13 locus in the Chinese population is balancing selection. Balancing selection can maintain old evolutionary lineages at low frequencies by protecting them from genetic drift (Lewontin and Hubby 1966) and can also cause excess of high frequency–derived variants. However, the fact that there is much LD (data not shown) and the number of haplotypes is small (eight haplotypes) in the Chinese population indicates the balancing selection hypothesis may be unlikely.
Although selection is one primary explanation for the observed variation patterns in the Chinese and Caucasian populations, the effect of population growth should not be debarred completely. In fact, SNPs and haplotypes found outside Africa were mostly a subset of those found within Africa (tables 1 and 3). It is conceivable that a reduction in population size (e.g., founder effect caused by migration out of Africa) would cause the frequencies of some chromosomes (haplotypes) to be increased, leaving one predominant haplotype (i.e., haplotype 3) in the Caucasian population and three common haplotypes (i.e., haplotype 1, 3, and 4) in the Chinese population, respectively. On inspection, it seems improbable that the outside-Africa population haplotype distribution could be obtained by sampling from the African population. Coalescent modeling of this process using the Genetree program (data not shown) shows that the three most common outside-Africa haplotypes are among the least likely to become common after migration. This suggests that population growth alone is an unlikely explanation for the unusual population-specific haplotype distribution pattern at the IL13 locus. In addition, under population growth, high frequency–derived alleles are expected to be less abundant than under a constant population size model (Fay and Wu 2000). Thus, population growth could not make Fay and Wu's H statistic significant, although it is true for Fu and Li's and Tajima's D statistics.
Conclusions
The variation pattern at the human IL13 locus reveals substantial locus-specific population differentiation and skewed haplotype structure with three dominant ones outside Africa. The significant excess of high frequency–derived SNPs in the Chinese and Caucasian population suggests that the underlying population differentiation and haplotype structure could be caused by the action of positive natural selection. Furthermore, there may exist different scenarios of the action of positive selection on the IL13 locus in different populations in our sample: simple directional selection in the Caucasian sample and two-round hitchhiking in the Chinese sample. These findings may provide insight into the likely relative roles of selection and population history in establishing present-day variation at the IL13 locus and motivate further studies of this locus as an important candidate in common diseases association studies.
Acknowledgements
We would like to thank the Chinese Human Genome Center at Shanghai, and the Institute of Genetics and Developmental Biology, CAS, for the 27 unrelated Chinese DNA samples. Additionally, we thank Justin Fay for providing computer program H-test version 1.0 and Sylvain Mousset for providing a new version of the program ALLELIX. We also thank two anonymous reviewers for valuable comments and suggestions on an earlier draft. This work was supported by the Chinese High-Tech Program grant 2001AA224011.
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Chinese National Human Genome Center at Beijing, Beijing, China
E-mail: hefc@nic.bmi.ac.cn.
Abstract
Interleukin-13 (IL13) is believed to play an important role in the pathogenesis of atopy and allergic asthma. To better understand genetic variation at the IL13 locus, we resequenced a 5.1-kb genomic region spanning the entire locus and identified 26 single-nucleotide polymorphisms (SNPs) in 74 individuals from three major populations—Chinese, Caucasian, and African. Our survey suggests exceptionally high and significant geographic structure at the IL13 locus between African and outside Africa populations. This unusual pattern suggests that positive selection that acts in some local populations may have played a role on the IL13 locus. In support of this suggestion, we found a significant excess of high frequency–derived SNPs in the Chinese population and Caucasian population, respectively, as expected after a recent episode of positive selection. Further, the unusual haplotype structure indicates that different scenarios of the action of positive selection on the IL13 locus in different populations may exist. In the Caucasian population, the skewed haplotype distribution dominated by one common haplotype supports the hypothesis of simple directional selection. Whereas, in the Chinese population, the two-round hitchhiking hypothesis may explain the skewed haplotype structure with three dominant ones. These findings may provide insight into the likely relative roles of selection and population history in establishing present-day variation at the IL13 locus, and, motivate further studies of this locus as an important candidate in common diseases association studies.
Key Words: interleukin-13 ? single nucleotide polymorphism ? positive selection
Introduction
It has been reported that polymorphisms in Interleukin-13 (IL13) can result in the interindividual variability in the expression (van der Pouw Kraan et al. 1999) and activity level of the gene product (Heinzmann et al. 2000). Numerous studies have also been performed on the association of this locus to various atopy and asthma phenotypes, such as bronchial hyperresponsiveness (BHR), positive allergen skin-test responses, and elevated total-serum immunoglobulin IgE levels, in several populations (Graves et al. 2000; Liu et al. 2000; Howard et al. 2001; Leung et al. 2001), but positive and negative associations have been accepted with reservation and have been difficult to replicate in subsequent studies. This inconsistency may reflect differences in phenotype definition, lack of statistical power, the effects of other loci, and the varying effects of presumably several disease-predisposing variants within IL13 (Lalouel 2001; Glazier, Nadeau, and Aitman 2002). Besides that, the potential for allergenic responsiveness to change in novel environments makes IL13 a possible target of local adaptation. Thus, failure to take into account the evolutionary history of the IL13 locus, such as the effects of population history and structure and/or natural selection, which may shape the linkage disequilibrium (LD) pattern and hence the likelihood of an association, may be another important cause of inconsistency in association studies (Jobling et al. 1998; Fullerton et al. 2002; Rosenberg et al. 2002).
An important step for studies explaining the role of genetic variation in risk of disease is a description of quality, quantity, and organization of genetic variation within and between human populations. To further understand genetic variability at the IL13 locus, we undertook a continuous scan for sequence variation patterns in unrelated individuals. The corresponding chimpanzee (Pan troglodytes) sequence was also completed, to serve as an outgroup for evolutionary and population genetic tests. Our study provides insight into the likely relative roles of selection and population history in establishing present-day genetic variation at the IL13 locus.
Materials and Methods
DNA Samples
Human genomic DNA was derived from two sources. (1) Forty-seven DNA samples were provided by Coriel Cell Repositories, Camden, NJ. These consisted of 24 Caucasian and 23 African DNA samples. (2) Samples from 27 unrelated Chinese individuals unselected for disease status were provided by Chinese human genome center at Shanghai, and Institute of Genetics and Developmental Biology, CAS. Informed consent was obtained from all Chinese participants, and the study was performed with the approval of the Ethical Committee of Chinese Human Genome. The same genomic regions were also sequenced in one common chimpanzee, which was also provided by Coriel Cell Repositories, Camden, NJ.
Laboratory Analysis
Overlapping primer sets covering the genomic sequence of IL13 (GenBank accession number AC074127.2), which span more than 5 kb, were designed on the basis of size and overlap of PCR amplicons by use of Primer 3.0, release 0.9 (http://www-genome.wi.mit.edu/cgi-bin/primer/primer3_www.cgi). We performed PCR in a total volume of 25 μl, containing 0.2 mM dNTPs, 4.5 mM MgCl2, 150 pM of each primer, 1 x standard buffer, 1 x Q-solution, 1 U Hotstar Taq polymerase (Qiagen), and 10 ng of genomic DNA. PCR conditions were as follows: 41 cycles of denaturation at 95°C, annealing at 56°C, and primer extension at 72°C, each step for 45 s. The first step of denaturation and the last step of extension were 15 min and 5 min, respectively. PCR products were purified by use of the 96-well microtitre purification plate according to the manufacturer's protocol (Millipore). Cycle sequencing was performed on PCR products in both directions according to the manufacturer's instructions using ABI PRISM Dye Terminator Sequencing Kits with Amplitaq DNA polymerase, FS (PerkinElmer). Excess dye terminators were removed by ethanol precipitation. The extension products were evaporated to dryness under vacuum (Savant Instruments), resuspended in 10 μl ddH2O, heated for 2 min at 92°C and loaded onto an Applied Biosystems 3700 sequencer.
SNP Identification
The ABI sequence software version 1.1 was used for lane tracking and first pass base-calling (PerkinElmer). The Phred-Phrap-Consed-PolyPhred package was used to assemble the sequences and identify SNPs. Specific descriptions and documentation on the above programs are available at http://www.genome.washington.edu. Once identified by PolyPhred, SNPs were visually inspected by at least two observers. Each SNP position and each individual's genotype has been confirmed by reamplifying and resequencing the SNP site from the same or opposite strand. Furthermore, because of the sequence overlap within the analyzed regions, more than one call for each genotype was often obtained for each position in a sample.
Data Analysis
Allele frequencies for each SNP were determined by gene counting, and the significance of deviations from Hardy-Weinberg equilibrium was tested using the random-permutation procedure implemented in the Arlequin package (http://lgb.unige.ch/arlequin/).
IL13 haplotypes were assigned by the computer program PHASE (Stephens, Smith, and Donnelly 2001). The Netwok 3.0 package (http://www.fluxus-technology.com/sharenet.htm) was used to construct the minimum-mutation network, which reflect the mutational relationships among the inferred haplotypes and the evolutionary history of genetic changes at the IL13 locus by means of the Reduced Median (RM) algorithm (Bandelt et al. 1995), with the common chimpanzee as an outgroup species. Trees were also constructed using the neighbor-joining, parsimony, and maximum-likelihood methods implemented in the PHYLIP software package (http://evolution.genetics.washington.edu/phylip.html). Two different statistical tests of the null hypothesis of neutrality—the haplotype partition test (HP test) (Hudson et al. 1994) and the haplotype diversity test (Hd test) (Depaulis and Veuille 1998)—were carried out, assuming randomly generated haplotypes. Significance values for each of the above two test statistics were estimated from 104 coalescent simulations using the program ALLELIX (http://www.snv.jussieu.fr/mousset/), which condition on the sample size and the number of segregating sites as the observed data, under a conservative assumption of no recombination.
To test for differentiation between populations, FST (Wright 1951), which reflects differences in allele frequencies among samples and increase as allele frequency differences between population samples become more pronounced, was calculated using the program Arlequin.
The human sequences were aligned with the chimpanzee sequence to identify fixed difference and the ancestral allele/haplotype. Sequence divergence was measured by aligning the chimpanzee outgroup sequence with the human polymorphic sample.
Genetree software (http://www.maths.monash.edu.au/mbahlo/mpg/gtree.html) was used to estimate the likelihood that the observed outside Africa haplotypic distribution could arise through neutral evolution under a simple out-of-Africa model (Griffiths and Tavaré 1994).
Three measures of diversity were computed for each of the three population samples and the pooled samples: (1) Watterson's W (Watterson 1975), based on the number of segregating sites in the sample, an estimate of the expected per-site nucleotide heterozygosity, theoretically equal to the neutral mutation parameter 4Nem; (2) (Nei and Li 1979), the direct estimate of per-site heterozygosity derived from the average number of pairwise sequence differences in the sample; and (3) H (Fay and Wu 2000), a summary that gives more weight to high frequency–derived variants. To test whether the frequency spectrum of mutations conformed to the expectations of the standard neutral model, we calculated the values of two test statistics: (1) Tajima's D statistic (Tajima 1989), which considers the difference between W and , and (2) Fay and Wu's H statistic, which considers the difference between H and . Under neutrality, the two test statistics should be close to 0. Fu and Li's D statistic (Fu and Li 1993) was used to compare the observed number of singleton polymorphisms with those expected under a neutral model. Significance values for each of the above three test statistics were estimated from 104 coalescent simulations of a Wright-Fisher equilibrium model that condition on the sample size and level of polymorphism as the observed data, with no recombination (Hudson 1990), using DnaSP Software (Rozas and Rozas 1999) and Fay's H-test version 1.0, respectively. The Hudson/Kreitman/Aguadé (HKA) test (Hudson 1987) was used to compare diversity patterns in the IL13 region with diversity patterns found at two other loci: ?-globin (Harding et al. 1997) and DMD intron 44 (Nachman and Crowell 2000a), using the HKA computer program (http://lifesci.rutgers.edu/heylab).
Results and Discussion
Rescreening of 5,100 bp of IL13 genomic DNA in the overall 74 samples revealed 26 SNPs (table 1). The extent of nucleotide diversity (table 2) for the overall sample ( = 7.5 x 10–4) was similar to the diversity reported for other autosomal human genetic loci (Harding et al. 1997; Clark et al. 1998; Rieder et al. 1999; Hamblin and Di Rienzo 2000; Subrahmanyan et al. 2001). Among the three population samples, the African population had the highest value, followed by the Chinese and Caucasian populations. The Caucasian population had a value ( = 3.3 x 10–4) about two times lower than those of the Chinese and African populations, respectively, and, fell at approximately the 5th percentile in the International SNP Map Working Group's distribution (see fig. 2a in International SNP Map Working Group 2001), which found a modal value of about 7.0 x 10–4, with a range 0.0 to 20.0 x 10–4.
Table 1 Alleles and Their Frequencies in the Chinese, Caucasian, and African samples, and, Pairwise Estimates of FST.
Table 2 Population Variability Parameters and Neutrality Tests for Human IL13 Locus.
FIG. 2. Suggested minimum-mutation network for IL13 haplotypes, based on 11 SNPs and the chimpanzee sequence. Node areas are proportional to haplotype frequency. Each node is shaded to indicate the fraction of time it was found in each population. Mutational differences between haplotypes are indicated on the branches of the network (SNPs and haplotypes are numbered as in table 1 and table 3, respectively; SNPs that result in amino acid substitutions are boxed). The solid branches represent mutation events, and the dashed branches indicate alterative topologies of equal length (may be recurrent mutation or recombination events). Haplotype cluster A and B are shown in the top and bottom dashed boxes, respectively
One common chimpanzee sequence (4,588 bp) was obtained to infer the ancestral and derived states for each human SNP and haplotypes (tables 1 and 3) and to estimate the number of fixed differences between humans and chimpanzee. It was monomorphic at all of the positions that were variable in humans. Human-chimpanzee divergence was 0.72% (33 sites). From divergence, the estimate of the average mutation rate per site per year is 7.14 x 10–10 (assuming a divergence time of 5 Myr BP between human and chimpanzee), lower than, but not significantly different from, those described for other loci (Harris and Hey 1999; Jaruzelska et al. 1999; Kaessmann et al. 1999; Nachman and Crowell 2000b; Yu et al. 2001), suggesting a slightly stringent level of selective constraint in this locus. Estimates of the effective size, Ne, were similar to earlier estimates when calculated under the assumption of a mutation rate of 7.14 x 10–10 (5,000 to 20,000 range) (Harding et al. 1997; Nachman 1998; Zhao et al.2000). W yielded Ne estimates of 16,282 for the overall sample, of 9,302 for Chinese, of 10,161 for Caucasian, and of 15,931 for African.
Table 3 Haplotypes and Their Estimated Frequencies in Each Population.
We calculated the FST statistic to assess whether there was evidence for differentiation among the populations in our sample. Application of the FST statistic to all pairs of populations revealed significant geographic structure (table 1). It is noteworthy that the FST between Caucasian and African (FST = 0.25) is considerably higher than that typically observed (Cavalli-Sforza, Menozzi, and Piazza 1994). To further resolve the degree of geographic structure of IL13 variation pattern, we calculated the FST statistic on a site-by-site basis for all pairs of populations (table 1). Each of the population pairs has five SNPs with high and significant FST values. To determine if the degree of interpopulation differentiation at the IL13 locus differs from the genomewide pattern, we compared the FST values of the IL13 SNPs to those of the 86 biallelic variants with similar sets of pooled African versus pooled non-African samples (the allele frequency data of these 86 biallelic variants were used to construct an empirical distribution of FST values [see fig. 2 in Fullerton et al. 2002]). This analysis suggested that the IL13 FST values are exceptionally high and significant, with estimates for one (i.e., SNP T749C), three (i.e., SNPs T749C, T1922C, and C2579A), and two (i.e., SNPs T749C and T1922C) SNPs falling above the 95th percentile of the genomewide distribution for Chinese–African, Caucasian–African, and non-African–African population pairs, respectively. This unusual pattern of geographic structure at the IL13 locus, which has also been observed at other human loci in other studies (Taylor, Shen, and Kreitman 1995; Hamblin and Di Rienzo 2000; Fullerton et al. 2002), may be consistent with the action of positive natural selection.
To further validate the hypothesis of positive selection attributed to the locus-specific pattern of unusual population differentiation at the IL13 region, a series of neutral model tests was used on each population and pooled populations (table 2). Tajima's D statistic suggested no statistically significant deviation from selective neutrality. Fu and Li's D test indicated a significant excess of singletons in the overall population but not in individual and pooled outside-Africa populations. In addition, by the comparison of the level of IL13 polymorphism and divergence to that observed at two other sampled human loci, ?-globin (Harding et al. 1997) and DMD intron 44 (Nachman and Crowell 2000a), HKA test suggested no significant differences (P > 0.05, data not shown).
However, when we use the recent Fay and Wu's H test, which compares the fit of the observed derived allele frequency spectrum of the SNPs with that expected under neutrality (fig. 1), it is significant in the Chinese (P = 0.043), Caucasian (P = 0.010), and pooled non-African (P = 0.032) populations but not in the African population (P = 0.783). A significant H test is thought to be the unique signature of a very recent sweep (Fay and Wu 2000; Otto 2000).
FIG. 1. Frequency spectrum of derived alleles. (A) Chinese population; (B) Caucasian population; (C) African population. Obs., the observed number of SNPs; Exp., the expected number of SNPs. The expected frequency spectrum is given by Watterson (1975). That is, at the neutral equilibrium, the expected number of SNPs sites at which the derived allele is present i times in the sample is given by 4Nv/i, where N and v are the effective population size and mutation rate, respectively. The formula to estimate 4Nv is the number of observed sites divided by (1 +1/2 + 1/3 + ... + 1/n–1), where n is the number of chromosomes in each population
The failure of Tajima's D and Fu and Li's D tests to reject the hypothesis of neutrality within individual populations and the lack of substantial reduction of nucleotide diversity (assuming ?-globin and DMD intron 44 locus are evolving neutrally) may be due to several reasons. One possibility is the power of these two tests to detect the effects of selection is weak when the sample sizes are small and the numbers of segregating sites are few (Simonsen, Churchill, and Aquadro 1995). Another possibility is that the number of selectively driven events is much smaller and the last sweep occurred too long ago to leave a trace. Alternatively, positive selection may have been constantly at work but too weak to depress the nucleotide diversity, thus leaving no trace detectable by either Tajima's D or Fu and Li's D test. Thus, diversity reduction may be viewed as an extreme example of strong selection disrupting the gene frequency spectrum, while weaker selection may leave a different signature by dragging nearby variations to higher than expected frequencies without causing fixation. Under this circumstance, such weak positive selection can be more effectively detected by examining the frequency spectrum of derived alleles, as shown in figure 1. The successful application of Fay and Wu's H test may have justified the above hypothesis.
Having informed ourselves that positive selection may have operated at the IL13 locus in the Caucasian and Chinese population, we attempt to clarify how selection might have worked in this system. We constructed haplotypes on the basis of the genotype data from 11 SNPs selected to span most of IL13 using PHASE program. A 97% phase assignment was made with greater than 90% certainty. Thirty-eight haplotypes were identified. Consistent with above substantial difference in terms of FST among populations, haplotype diversity, the probability that two haplotypes randomly chosen from the sample will be different, also appeared quite different, with 0.979 in the Africans, 0.857 in the Chinese, and 0.551 in the Caucasians, respectively.
Further, the outside-Africa population data sets suggested unusual haplotype distribution. In the Caucasian population, the haplotype 3 was the only predominant haplotype, having a frequency of 0.67. In the Chinese population, the haplotypes 1, 3, and 4 were most common, having frequencies of 0.20, 0.26, and 0.19, respectively, and frequencies of only 0.02, 0.07, and 0.02, respectively, in the African population (table 3). To determine whether the observed haplotype distribution was consistent with the expectations of a neutral equilibrium model, we applied two tests of neutrality: Hd and HP. The Hd test suggested a significant reduction with respect to the neutral expectation in the haplotype diversity of the Caucasian sample (table 2). The HP test further revealed that polymorphic sites are not uniformly distributed among the sequences in the Caucasian sample (table 2). The above three most common haplotypes may have expanded outside Africa because of natural selection, which may fix different haplotypes in different populations.
The likely genealogical history of the observed SNPs was inferred from RM network (Bandelt et al. 1995) constructed for 12 common haplotypes (fig. 2), using the Netwok 3.0 software package. As shown in the RM network, the picture was dominated by two main clusters that differ at five SNP sites (involving SNPs T1922C, A2043G, A2524G, C2579A, and T2748C). One cluster, contained haplotypes 1 and 10 (referred to here as "cluster A"), and the other cluster, contained haplotypes 2, 3, 4, 7, and 8 (referred to here as "cluster B"). The same clusters and root position were also seen in trees constructed by the neighbor-joining and parsimony methods performed by the PHYLIP package. Haplotypes from cluster A and cluster B were found in approximately 12% and 54% of sampled chromosomes, respectively. Both clusters were found in the Chinese, Caucasian, and African samples. The observation that two distinct haplotype clusters with broadly overlapping geographical distribution are present provided further evidence for positive selection on the IL13 region. Furthermore, the RM network could give us more detailed information and indicate that different scenarios of action of positive selection in different populations may exist. Indeed, there are an accumulating number of examples where distinct selective pressures appear to apply in different environments (Harris and Hey 1999; Rana et al. 1999; Hamblin and Di Rienzo 2000). Clearly, the genetic variation pattern in the Caucasian population can be explained by the simple selection sweep hypothesis (Maynard Smith and Haigh 1974; Hudson 1990). However, in the Chinese population, the situation may be more complex. It is possible that an older selection sweep may have happened and driven the cluster B (including haplotypes 2, 3, 4, 7, and 8) to high frequency. The higher haplotype diversity of the cluster B is consistent with its relative antiquity. Afterwards, a more recent hitchhiking event may have taken place and driven the cluster A (including haplotypes 1 and 10) to high frequency. This second round of selection sweep in the Chinese population may still be active because of the very low frequency of cluster A outside of the Chinese population (table 3). Alternatively, the focal point of positive selection is a bit further away that allows recombination to happen before haplotypes 1 and 10 even get to beyond 0.20.
Another plausible factor that can explain the present-day variation pattern at the IL13 locus in the Chinese population is balancing selection. Balancing selection can maintain old evolutionary lineages at low frequencies by protecting them from genetic drift (Lewontin and Hubby 1966) and can also cause excess of high frequency–derived variants. However, the fact that there is much LD (data not shown) and the number of haplotypes is small (eight haplotypes) in the Chinese population indicates the balancing selection hypothesis may be unlikely.
Although selection is one primary explanation for the observed variation patterns in the Chinese and Caucasian populations, the effect of population growth should not be debarred completely. In fact, SNPs and haplotypes found outside Africa were mostly a subset of those found within Africa (tables 1 and 3). It is conceivable that a reduction in population size (e.g., founder effect caused by migration out of Africa) would cause the frequencies of some chromosomes (haplotypes) to be increased, leaving one predominant haplotype (i.e., haplotype 3) in the Caucasian population and three common haplotypes (i.e., haplotype 1, 3, and 4) in the Chinese population, respectively. On inspection, it seems improbable that the outside-Africa population haplotype distribution could be obtained by sampling from the African population. Coalescent modeling of this process using the Genetree program (data not shown) shows that the three most common outside-Africa haplotypes are among the least likely to become common after migration. This suggests that population growth alone is an unlikely explanation for the unusual population-specific haplotype distribution pattern at the IL13 locus. In addition, under population growth, high frequency–derived alleles are expected to be less abundant than under a constant population size model (Fay and Wu 2000). Thus, population growth could not make Fay and Wu's H statistic significant, although it is true for Fu and Li's and Tajima's D statistics.
Conclusions
The variation pattern at the human IL13 locus reveals substantial locus-specific population differentiation and skewed haplotype structure with three dominant ones outside Africa. The significant excess of high frequency–derived SNPs in the Chinese and Caucasian population suggests that the underlying population differentiation and haplotype structure could be caused by the action of positive natural selection. Furthermore, there may exist different scenarios of the action of positive selection on the IL13 locus in different populations in our sample: simple directional selection in the Caucasian sample and two-round hitchhiking in the Chinese sample. These findings may provide insight into the likely relative roles of selection and population history in establishing present-day variation at the IL13 locus and motivate further studies of this locus as an important candidate in common diseases association studies.
Acknowledgements
We would like to thank the Chinese Human Genome Center at Shanghai, and the Institute of Genetics and Developmental Biology, CAS, for the 27 unrelated Chinese DNA samples. Additionally, we thank Justin Fay for providing computer program H-test version 1.0 and Sylvain Mousset for providing a new version of the program ALLELIX. We also thank two anonymous reviewers for valuable comments and suggestions on an earlier draft. This work was supported by the Chinese High-Tech Program grant 2001AA224011.
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