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Haplotype Variation and Linkage Disequilibrium in 313 Human Genes

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Science  20 Jul 2001:
Vol. 293, Issue 5529, pp. 489-493
DOI: 10.1126/science.1059431

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Abstract

Variation within genes has important implications for all biological traits. We identified 3899 single nucleotide polymorphisms (SNPs) that were present within 313 genes from 82 unrelated individuals of diverse ancestry, and we organized the SNPs into 4304 different haplotypes. Each gene had several variable SNPs and haplotypes that were present in all populations, as well as a number that were population-specific. Pairs of SNPs exhibited variability in the degree of linkage disequilibrium that was a function of their location within a gene, distance from each other, population distribution, and population frequency. Haplotypes generally had more information content (heterozygosity) than did individual SNPs. Our analysis of the pattern of variation strongly supports the recent expansion of the human population.

Large-scale investigations of sequence variation within the human species have only just begun (1–3). Initial estimates are that sequence differences between an individual's maternal and paternal genomes occur on average at about every 500 to 2000 bases (2–4), with the most frequently cited value being one difference approximately every kilobase (5). However, relatively little is known about the pattern of DNA sequence variation among humans, within a population and between different populations. In particular, the pattern of linkage disequilibrium among closely spaced SNPs, for example, those that are less than 20 kb apart, is known only for a few well-studied genes, and the results from these studies are highly discordant (6–9).

We have undertaken a systematic discovery of gene-based sequence variation in 82 unrelated individuals, whose ancestors were from various geographical origins. The sample size and composition were sufficient to detect, with high certainty, globally distributed variants present at a frequency of at least 2% and population-specific variants present at a frequency of at least 5%. Our population sample, using the definitions of the U.S. Census Bureau, was comprised of approximately an equal number of self-described Caucasians, African-Americans, Asians, and Hispanic-Latinos (10). Our goal was to identify SNPs and to organize them into their gene-specific allelic haplotypes. A haplotype is the specific combination of the nucleotides, one from each of the polymorphic sites that are present on an individual chromosome. We sequenced the exons (coding regions, 5′UTR and 3′UTR), up to 100 bases into the introns from the exon-intron boundaries (including the splice junctions), and the 5′ upstream genomic region (11). The 313 genes were chosen from those genes for which complete genomic organization was publicly available. To assist in assessing the quality of the sequence information and to validate the construction of haplotypes, we also included a three-generation Caucasian family and a two-generation African-American family. For evolutionary comparisons, we also sequenced the corresponding genomic regions from a chimpanzee. The position and sequence of the human polymorphisms have been deposited in GenBank.

We discovered 3899 polymorphic sites in nearly 720 kb of genomic sequence or an average of one SNP approximately every 185 bases. Less than 2% of these polymorphic sites were previously described (12). The average number of polymorphic sites per kilobase of DNA was 3.4 in the coding regions, 5.3 in the 5′UTR, 5.9 in the 5′ upstream region, 6.5 in the exon-intron boundaries, and 7.0 in the 3′UTR (13). Fifty-one of these polymorphisms were within splice sites (14). Of the 1033 polymorphic sites within the coding regions, 565 coded for an amino acid change, 459 did not result in an amino acid change, and nine changed an amino acid codon to a termination codon. In addition, we observed proportionately fewer polymorphisms that resulted in an amino acid change than have been observed in pseudogenes (Table 1), which are presumably subject to less stringent natural selection than are functional genes (15). Furthermore, of the mutations that resulted in an amino acid change, we identified fewer that caused either a radical change or a termination codon than have been observed in pseudogenes.

Table 1

The functional consequences of coding region polymorphisms. None means a silent nucleotide substitution. For amino acid changes, the type of change is categorized based upon Grantham values (50), which are derived from physiochemical considerations. The range that was used for Grantham values corresponds to that of Li et al. (15) and is as follows: conservative is <50; moderately conservative is between 51 and 100; moderately radical is between 101 and 150; and radical is ≥151.

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For 38% of the SNPs, the minor allele was observed only once as a single heterozygote (16). The occurrence of these variants was different among the four population samples. The African-American sample had 662 as compared with 294, 223, and 273 in the Asian, Caucasian, and Hispanic-Latino samples, respectively (17). In addition, the African-American sample had the greatest number of population-specific rare alleles that occurred only two, three, or four times (Table 2). For 32% of all SNPs, the minor allele frequency was between 1 and 5% (17). For about 17%, the minor allele frequency was between 5 and 20%, and for the remaining 13%, the minor allele frequency was between 20 and 50%.

Table 2

The distribution of rare SNPs among the four populations. SNPs with minor alleles observed two, three, or four times in the sample of 20 African-Americans (AF), 20 Asians (AS), 21 Caucasians (CA), and 18 Hispanic-Latinos (HL). Values on the diagonal are the number of population-specific SNPs. The other values are the number of SNPs shared between specific pairs of populations.

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Population genetics theory suggests that rare variants are more likely to be recently derived than are the common variants and are, therefore, more likely to be population-specific (18, 19). Hence, rare variants are sensitive indicators of recent migration and the relationships among various populations (20). Our Hispanic-Latino sample shared a substantial number of rare variants with the African-American and Caucasian samples. By comparison, fewer rare variants were shared between the Caucasian and African-American samples, and even fewer were shared between the Asian and non-Asian samples (Table 2). This pattern of sharing is consistent with the history of these populations in the United States and with the self-identification given when our samples were collected (10, 21).

Not all population-specific alleles were observed at a low frequency. In the African-American and Asian samples, some population-specific alleles were found at frequencies >25%. Highly frequent population-specific alleles are particularly useful in mapping genes responsible for disease susceptibility and other traits in populations of mixed ancestry (22–24). On the other hand, SNPs, in which both alleles are present in all populations (“cosmopolitan” SNPs), are useful in conventional multigeneration linkage studies, as well as in genome-wide scans that use smaller family units (25–27). Of the 3899 SNPs, 21% were found to be cosmopolitan (Fig. 1A).

Figure 1

(A) The distribution of SNPs among the four population samples. The SNPs were categorized as to whether they were variable in one, two, three, or all four populations. (B) The distribution of haplotypes among the four population samples. The haplotypes were categorized as to whether they were observed in one, two, three, or all four populations. Population codes are AF, African-American; AS, Asian; CA, Caucasian; and HL, Hispanic-Latino.

Nucleotide diversity provides a measure of genetic variation that is normalized by the number of chromosomes sampled. We calculated two conventional measures of nucleotide diversity for each gene: π, the average heterozygosity per site (28, 29), and θ, the population mutation parameter (13, 30). The average nucleotide diversity for the 292 autosomal genes (π = 0.058% and θ = 0.096%) and the 21 X-linked genes (π = 0.028% and θ = 0.045%) were within the range of values previously described (2–4). The fact that the average nucleotide diversity for the X-linked genes was reduced compared with the average autosomal nucleotide diversity is consistent with an equal number of males and females in the human population, in which males have only a single copy of the X chromosome.

We also calculated the autosomal nucleotide diversity values separately for each functional gene region and for each population. Exon-intron boundaries showed significantly higher average π values (P < 0.01 by single-factor ANOVA) than did the coding regions (0.088 and 0.034%, respectively), and the African-American sample had a significantly higher average π value than did the other population groups (0.068% and a range of 0.047 to 0.053%, respectively; P ≪ 0.0001).

In our analyses of nucleotide diversity, π was consistently and significantly lower than θ (P < 0.0001). The difference between π and θ forms the basis of Tajima's D, a statistic that is used to detect departures from the standard neutral model (9, 31, 32). For an individual gene, a positive Tajima's D value is evidence for heterozygotes having a selective advantage, whereas a negative value is evidence for selection of one specific allele over alternate alleles. If, however, a majority of genes have a negative Tajima's D value, the simplest explanation for such results would be that the human population underwent a recent expansion. Previous studies of sixteen nuclear genes reported an even distribution between positive and negative Tajima's D values (9), results that offer no support for a recent population expansion. In contrast, of the 313 genes analyzed in our study, 281 showed a negative Tajima's D value. We interpret this result as strong evidence for a recent expansion of the human population.

We categorized the SNPs according to their 5′ to 3′ orientation on the sense strand of DNA (17). Seventy-one percent of the SNPs were transitions (35.8% G⇔A and 35.4% C⇔T), even though transitions represent only one third of the total possible types of mutation. Additionally, for the four categories of SNPs, G⇔A, C⇔T, C⇔A, and G⇔T, there was a pronounced bias observed. SNPs, in which the G or the C allele was more common than the alternate allele, were observed 1.9 to 2.4 times more frequently than were SNPs, in which the G or C allele was the less common allele. This bias was most prominent for rare (observed once or twice) and population-specific variants and was statistically significant (P = 0.001) for transitions. Population genetics theory predicts that the more frequent allele is usually the ancestral allele (18); hence, the bias observed suggests that the predominant direction of mutation was a change from G or C to A or T. For the two categories of SNPs, G⇔C and A⇔T, there was no apparent bias and, therefore, no predominant direction of mutation was apparent.

Methylation of CpG dinucleotides is thought to account for a large number of mutations, most of which would involve G⇔A or C⇔T transitions (7, 33). Nearly 40% of the SNPs were consistent with mutation of either base in a CpG dinucleotide. Evolutionary pressure to relax the strength of base pairing would favor the conversion of G and C to A or T, which was the pattern of bias that was observed. On the other hand, the changes G⇔C and A⇔T, for which we observed no bias, are the only changes that do not alter the strength of base pairing.

Instead of using the frequency of an allele as a surrogate for ancestry, an alternative approach is to compare the alleles seen in humans with the corresponding sequence of a chimpanzee. With this approach, the human allele that matches the chimpanzee sequence is assumed to be the ancestral allele (34, 35). There was general agreement between the two approaches of inferring ancestry for an allele, namely, the more common human allele generally matched the chimpanzee sequence (36).

We identified an average of approximately 12.5 biallelic SNPs per gene (13). If SNPs were randomly associated with each other within a gene, there would be about 212 possible haplotypes. In fact, without recombination or recurrent mutation, the number of haplotypes should be less than the number of SNPs (7, 8). In each gene studied, the combination of alleles present at each site of polymorphism in each individual was analyzed by a computer program (37) that assigned a specific pair of haplotypes to each individual, as well as a score reflecting the confidence in that assignment.

We observed an average of approximately 14 different haplotypes per gene, which was about 1.1 times the average number of individual SNPs identified per gene. Although the number of SNPs and haplotypes varied considerably among the genes studied, there was a linear relationship between the number of individual SNPs identified within a gene and the number of different haplotypes assigned per gene [r 2 = 0.74 (38)]. The fact that the number of haplotypes was greater than the number of SNPs is an indication that some level of recombination and recurrent mutation occurred within these genes (7, 8).

The number of different haplotypes identified for a gene ranged from 2 to 53 in our sample of 313 genes (13). We estimated the heterozygosity at each gene by treating each haplotype as an individual allele (39). The haplotype heterozygosity of the 313 genes ranged from 0.012 to 0.929 in the pooled population sample and had an average of 0.534 (13). The average haplotype heterozygosity ranged from 0.437 in Asians to 0.584 in African-Americans. The maximum attainable heterozygosity for a single biallelic SNP is only 0.50. Of the 313 genes, 199 had a haplotype heterozygosity greater than 0.50. Thus, in general, the higher heterozygosity and multiallelic nature make haplotypes more informative than biallelic SNPs.

Sixteen percent of the 4304 haplotypes were cosmopolitan (Fig. 1B). If, however, the frequency of occurrence of each individual haplotype is considered, the cosmopolitan haplotypes accounted for nearly 82% of the total haplotypes observed, whereas population-specific haplotypes accounted for only about 8% of the total (40). Nearly 4% of the total haplotypes were present in two populations, and almost 6% were present in three populations.

We determined the extent of allele sharing among individuals both within and among our four populations. The neighbor-joining algorithm (41) was used to cluster individuals on the basis of their haplotype pairs for each of the 313 genes. The results confirmed the integrity of the self-described ancestry of these individuals (42). The Asians and the African-Americans each formed separate clusters. Individual Hispanic-Latinos clustered with Caucasians or were connected to the base of either the Asian or African-American clusters. The lack of a defined cluster of Hispanic-Latinos is consistent with some Hispanic-Latinos being either primarily of European or Amerindian descent and others being combinations of European, Amerindian, and African descent. The extent of allele sharing between individuals in the same population was only slightly greater than that observed between individuals from different populations. This result presumably reflects Lewontin's (43) observation that the majority of human genetic variation occurs among individuals within a local population group with only a small additional variation occurring between individuals from different populations.

The population distribution of haplotypes was similar to the population distribution of SNPs, with many of the haplotypes being rare and population-specific (Fig. 1B). Of the 2782 population-specific haplotypes, a significant fraction (48%) was seen only in the African-American sample. The Asian sample had the second largest number of population-specific haplotypes, followed by the Caucasian and Hispanic-Latino samples. As with SNPs, the African-American sample had the largest number of distinct haplotypes, and the Asian sample had the smallest.

Our results indicate that many genes do not have one predominant haplotype. For 35% of the genes, no single haplotype had a frequency that was ≥50%. Therefore, the concept that there is one predominant or “wild-type” form of a gene and various rare or “mutant” forms is overly simplistic and misleading. Instead, there are multiple haplotypes, each of which is observed in multiple populations, that account for a large fraction of human genomic variability. This variety of different forms, or haplotypes, for most genes constitutes an opportunity for functional adaptation and diversification.

The large number of SNPs identified per gene facilitated the investigation of heritable associations (linkage disequilibrium) between SNPs within a gene. To estimate the relationship between linkage disequilibrium and physical distance, we calculated all the ∣D′∣ values for pairs of SNPs with sufficiently high frequencies (44, 45) in the four different population samples as a function of the distance separating them (Fig. 2). Of the 313 genes, 235 had a pair of SNPs whose minor allele was sufficiently frequent to estimate linkage disequilibrium in at least one population (13). There were pairs of SNPs that did not agree with the general concept that linkage disequilibrium decreases as a function of distance. For example, of the pairs that were separated by <1 kb, 6% had a ∣D′∣ <0.3 and, hence, were only minimally associated (in linkage equilibrium). On the other hand, of the pairs that were separated by >20 kb, nearly 30% had a ∣D′∣ = 1 and, therefore, were maximally associated (in linkage disequilibrium). These results demonstrate that the probability of any particular pair of SNPs being in linkage disequilibrium is not predictable, and, as a result, linkage disequilibrium should be determined empirically for any specific genomic region.

Figure 2

Linkage disequilibrium for pairs of SNPs within a gene. Linkage disequilibrium (∣D′∣) was estimated separately for each population for each pair of SNPs within each of the genes. Only SNPs for which a rare variant was observed at least five times in a population were used in this calculation.

We further analyzed the SNPs from those pairs that exhibited either extremely high or extremely low levels of association with each other. First, the SNPs from pairs for which the level of association was maximal were compared with the SNPs from pairs for which the level of association was minimal. There was no significant difference between the SNPs from the two groups regarding their distribution among either functional regions of a gene or the specific base pair defining the polymorphism. Second, we examined those pairs of SNPs that were exceptions to the general concept that the shorter the distance the greater the level of linkage disequilibrium. The SNPs from pairs, for which the level of association was maximal and which were separated from each other by >20 kb, were compared with the SNPs from pairs, for which the level of association was minimal and which were separated from each other by <1 kb. There was no significant difference between the SNPs from these two groups in the specific base pair defining the polymorphism. Likewise, there was no apparent difference in the proportion of SNPs found in the 5′ upstream, 5′UTR, coding, or 3′UTR regions. However, the proportion of SNPs from within exon-intron boundaries was significantly different (P = 0.0121) between these two categories (54 and 28%, respectively). These results suggest that SNPs found in exon-intron boundaries are the most likely SNPs to be in strong linkage disequilibrium at long distances.

Recently, Reich et al. determined the linkage disequilibrium relationship of 272 SNPs distributed over 19 genomic regions, each approximately 160 kb in size, in a population of 44 individuals of Northern European ancestry (46). In their study, D′ varied from no apparent association beyond 5 kb to maximal association at the longest distance measured. The extensive variability in linkage disequilibrium, which they observed for regions defined by a specific size, agrees with our results obtained for genomic regions defined by the transcriptional unit of a gene.

Our observations demonstrate the necessity of understanding patterns of human genomic evolution if genomic variability is to be used as a tool in human health research. The processes underlying genomic evolution are obviously subject to varying levels of natural selection, which invalidates overly simplistic theoretical models. Additionally, complex or unknown patterns of human migration complicate the distribution and interpretation of genomic variation. In particular, the pattern of linkage disequilibrium within genes is more complicated than was previously estimated. The fluidity of genomic parameters, such as linkage disequilibrium, questions the applicability of genome-wide studies that assume that SNPs, randomly distributed throughout the genome, will be sufficient to detect an association with a phenotype. Haplotypes, on the other hand, can correlate a specific phenotype with a specific gene in a small population sample even when individual SNPs cannot (47). Thus, attempts to draw associations between phenotypes and genomic variation are more likely to succeed when the SNPs used in such studies have been confirmed to be in linkage disequilibrium by methods such as haplotyping.

  • * To whom correspondence should be addressed. E-mail: c.stephens{at}genaissance.com

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