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Am J Hum Genet. 2000 Oct; 67(4): 901–925.
Published online 2000 Sep 14. doi:  10.1086/303068
PMCID: PMC1287905

Short Tandem-Repeat Polymorphism/Alu Haplotype Variation at the PLAT Locus: Implications for Modern Human Origins


Two dinucleotide short tandem-repeat polymorphisms (STRPs) and a polymorphic Alu element spanning a 22-kb region of the PLAT locus on chromosome 8p12-q11.2 were typed in 1,287–1,420 individuals originating from 30 geographically diverse human populations, as well as in 29 great apes. These data were analyzed as haplotypes consisting of each of the dinucleotide repeats and the flanking Alu insertion/deletion polymorphism. The global pattern of STRP/Alu haplotype variation and linkage disequilibrium (LD) is informative for the reconstruction of human evolutionary history. Sub-Saharan African populations have high levels of haplotype diversity within and between populations, relative to non-Africans, and have highly divergent patterns of LD. Non-African populations have both a subset of the haplotype diversity present in Africa and a distinct pattern of LD. The pattern of haplotype variation and LD observed at the PLAT locus suggests a recent common ancestry of non-African populations, from a small population originating in eastern Africa. These data indicate that, throughout much of modern human history, sub-Saharan Africa has maintained both a large effective population size and a high level of population substructure. Additionally, Papua New Guinean and Micronesian populations have rare haplotypes observed otherwise only in African populations, suggesting ancient gene flow from Africa into Papua New Guinea, as well as gene flow between Melanesian and Micronesian populations.


Haplotypic variation consisting of both fast-evolving short tandem-repeat polymorphisms (STRPs) and more slowly evolving markers such as restriction-fragment-length polymorphisms (RFLPs), single-nucleotide polymorphisms (SNPs), and insertion/deletion polymorphisms (indels) have proved to be useful for both the tracing of population migrations and determining when mutation events occurred (Tishkoff et al. 1996a, 1998a, 1998b; Kidd et al. 1998). STRPs have moderate to high mutation rates (usually 10−5–10−2/generation [Weber and Wong 1993; Tautz and Schlötterer 1994; Chakraborty et al. 1997; Brinkmann et al. 1998]) and are thought to mutate via the “stepwise” gain or loss of single-repeat units, although larger “jumps” in repeat size occasionally do occur (Shriver et al. 1993; Valdes et al. 1993; Di Rienzo et al. 1994; Tishkoff et al. 1998a). The instability of STRPs results in the formation of many alleles, and stable flanking markers allow greater certainty in tracing the lineage of each haplotype and in determining the identity by descent of haplotype lineages. Scoring these markers as haplotypes allows analysis both in terms of haplotype frequencies and identity and in terms of linkage disequilibria. Thus, in addition to differing in the frequency of alleles at the individual polymorphic sites, populations may differ in the particular combination of alleles on a chromosome, and a shared pattern of linkage disequilibrium (LD) may be informative for determination of recent common ancestry and for reconstruction of historic migration events (Tishkoff et al. 1996a, 1998a, 1998b; Kidd et al. 1998, 2000). In addition, if one knows or can estimate the mutation rate of an STRP, as well as the recombination rate between the STRP and a stable allele marker, it becomes possible to estimate the age of the stable SNP or indel marker. Such an analysis has been applied to the CD4 gene, as well as to a number of mutations resulting in disease and disease resistance (Serre et al. 1990; Hästbacka et al. 1992; Risch et al. 1995; Bertranpetit and Calafell 1996; Tishkoff et al. 1996a, 1998b; Rannala and Slatkin 1998; Stephens et al. 1998).

We have examined the global frequency distribution of two dinucleotide STRPs and an Alu-insertion polymorphism encompassing a 22-kb region within the tissue-plasminogen–activator locus (PLAT) located on the short arm of chromosome 8 (8p12-q11.2; see fig. 1) (Degen et al. 1986). The polymorphic Alu element (often referred to as “TPA Alu”) is located within intron 8 of the PLAT gene (GenBank sequence position 28804 [accession number K03021; see the NCBI GenBank Overview Web site]; see fig. 1) and is a member of the human-specific (HS) (also known as “PV”) subfamily of Alu elements that recently have retroposed within the human genome (Batzer et al. 1991, 1996). It has been hypothesized that the presence of the Alu-insertion allele, herein denoted “Alu(+),” at PLAT may predict risk for coronary thrombosis. However, two recent studies (Ridker et al. 1997; Steeds et al. 1998) have observed no significant difference in the frequency of the Alu(+) allele in individuals at high risk for myocardial infarction, compared with that in healthy control cases, suggesting that the indel is not a major independent risk factor for coronary thrombosis.

Figure  1
Diagram of PLAT gene structure, showing location of the polymorphic PLAT Alu and the (CA)n-1 and (CA)n-2 STRPs used in the haplotype analysis. Exons are shown as blackened boxes.

Alu insertions are useful for the study of human evolution because they are unique, stable mutation events and because the ancestral state is known to be the absence of the Alu element, herein denoted “Alu(−)” (Perna et al. 1992; Batzer et al. 1994, 1996; Tishkoff et al. 1996b; Sherry et al. 1997; Stoneking et al. 1997). We have examined haplotypes involving the PLAT Alu and the two closely linked STRPs in 1,225–1,375 individuals originating from 30 geographically diverse human populations (fig. 2). The patterns of haplotype variation and LD observed at the PLAT locus support a recent African origin of non-African human populations and suggest that, throughout much of modern human history, sub-Saharan Africa has maintained a large effective population size and a high level of population substructure.

Figure  2
Global distribution of populations included in the PLAT haplotype study. 1 = Biaka; 2 = Mbuti; 3 = Wolof; 4 = Ewondo; 5 = Bamileke; 6 = Bantu-speakers; 7 = Herero; 8 = Zu/Wasi !Kung San; 9 = Kwengo; 10 = Nama; 11 = Va/Sekele !Kung San; 12 = Ethiopians; ...

Subjects and Methods


Individuals originating from 30 geographically diverse populations were typed for the Alu, PLAT (CA)n-1, and PLAT (CA)n-2 polymorphisms. In most cases populations represent well-defined ethnic groups, but in some cases ethnically diverse populations from the same geographic region have been pooled because of small sample sizes. For example, the Bantu-speakers, Somali, and Papua New Guineans each represent here a pooling of ethnically diverse groups. Populations examined include 13 African populations (country of origin is given in parentheses): Wolof (Senegal), Ewondo (Cameroon), Bamileke (Cameroon), Mbuti (Democratic Republic of Congo), Biaka (Central African Republic), Bantu-speakers from various southern-African chieftainships (South Africa), Herero (Namibia), Kwengo (Namibia), Nama (Namibia), Va/Sekele !Kung San (Namibia), Zu/Wasi !Kung San (Namibia), Somali, Ethiopian Jews; two Middle Eastern populations—Yemenite Jews (Yemen) and Druze (Israel); two European populations—Finns and Danes; five Asian populations—Japanese, San Francisco Chinese, Ami (Taiwan), Atayal (Taiwan), and Yakuts (Siberia); three Oceanic populations—Micronesians (assorted islands), Nasioi (Melanesia), and Papua New Guineans; and five Amerindian populations— Cheyenne (Oklahoma), Maya (Yucatan, Mexico), Karitiana (Rondonia, Brazil), Surui (Rondonia, Brazil), and Ticuna (Amazonia, Brazil). Most of the population samples have been described elsewhere, by Nurse et al. (1985), Scozzari et al. (1988, 1999), Stoneking et al. (1990), Bowcock et al. (1991), Spurdle and Jenkins (1992), Barr and Kidd (1993), Goldman et al. (1993), Lichter et al. (1993), Destro-Bisol et al. (1994), Castiglione et al. (1995), Soodyall et al. (1996), Tishkoff et al. (1996a, 1998a), Calafell et al. (1998), Kidd et al. (1998), and Spedini et al. (1999). Genomic DNA was extracted from blood or from Epstein-Barr virus–transformed lymphoblastoid cell lines, by standard methods. The great apes sampled for this project include 19 Pan troglodytes, 6 Pan paniscus, and 4 Gorilla gorilla (described in Deinard and Kidd 1999). All blood samples were obtained with informed consent, and typings were done under protocols approved by the human-subjects committees of all universities and research institutions involved in this study.

PCR Methods

The Alu-insertion polymorphism was typed with the published primer sequences and methods described by Tishkoff et al. (1996b). Amplification produces a 570-bp fragment from chromosomes with the Alu insertion and a 260-bp fragment from those without it. PCR products were separated on a 1% agarose gel, were stained with ethidium bromide, and were visualized with UV light.

The two dinucleotide repeats were typed by use of the published primers for (CA)n-1 (Thomas and Drayna 1992) and (CA)n-2 (Sadler et al. 1991). Amplification was performed with 50 ng of genomic DNA in a 25-μl (total volume) reaction mixture. The reaction mixture for (CA)n-1 contained 5 pmol each of fluorescent-labeled primer (PLAT1A 5′-GAC AGC ACA TTC TCT TAG CAA-3-′) and unlabeled primer (PLAT1B 5′-GTG ATG GAG TCA GAC CTT GTC-3′), 200 μM of each dNTP, 50 mM KCl, 10 mM Tris-HCl, 1.5 mM MgCl2, and .625 U of Taq polymerase. Samples were denatured for 1 min at 94°C, followed by 25 cycles of 94°C for 1 min, 57°C for 1 min, and 72°C for 1 min, followed by a 10-min extension at 72°C. The amplification conditions for (CA)n-2 were identical, except for the use of 5 pmol each of fluorescent-labeled primer (PLAT2A 5′-GCC TGG ACA ACA TAG AGA AAC C-3′) and unlabeled primer (PLAT2B 5′-ACT TCA GGC ATG TGC CAC TG-3′) and the addition of 1.5 μl of deionized formamide to the reaction mix. Amplification products were run on a 6% polyacrylamide gel, on either an ABI 373 or ABI 377 DNA sequencer, and fragment sizes were determined with GENESCAN software.


STRP alleles were sequenced either from clones or directly from PCR-amplification products. Cloning was used to sequence large-sized alleles at (CA)n-1, which were present only as heterozygotes with small-sized alleles. STRP alleles were amplified by the method described above and were visualized on a 3.5% Nusieve gel. Bands containing the STRP alleles were excised from the gel, and the DNA was isolated by a Sephaglas DNA isolation kit (Pharmacia). These purified products were cloned into a PT7Blue-3 plasmid vector by use of a Novagen cloning kit. Minipreps of the plasmids containing the cloned alleles were performed by use of Promega’s Wizard Plus SV miniprep kit. Plasmids containing the STRP allele inserts were cycle sequenced in both directions, with fluorescently labeled terminators, by use of either an ABI dideoxy terminator kit or a Beckman CEQ DTCS sequencing kit and T7 and U19 primers specific to the PT7Blue-3 vector. PCR products were run on either an ABI 373 or Beckman CEQ2000 automated DNA sequencer. For sequencing from PCR products from individuals homozygous for STRP alleles, alleles from (CA)n-1 were amplified with primers TpaSeq1A (5′-AAA GCT CAT CCA CCC TGC TC-3′) and TpaSeq1 B (5′-CAT GCC CCT GTA GTC CTA GC-3′), which produce a 302-bp product for a 113-bp allele. Alleles from (CA)n-2 were amplified with primers TpaSeq2A (5′-AAG GAA GGA AAA ATG CTG GG-3′) and TpaSeq2B (5′-GAC TGG AGT GCA GTG GCA TG-3′), which produce a 302-bp product for a 111-bp allele. Amplification was performed by use of 50–100 ng of genomic DNA in a 25-μl (total volume) reaction mixture. The reaction mixture contained 10 pmol of each forward (A) and reverse (B) primer, 200 μM of each dNTP, 50 mM KCl, 10 mM Tris-HCl, 1.5 mM MgCl2, and 0.625 U of Taq polymerase. For TpaSeq1, samples were denatured for 1 min at 94°C, followed by 25 cycles of 94°C for 1 min, 60°C for 1 min, and 72°C for 1 min, followed by a 10-min extension at 72°C. For TpaSeq2, samples were denatured for 1 min at 94°C, followed by 25 cycles of 94°C for 1 min, 58°C for 1 min, and 72°C for 1 min, followed by a 10-min extension at 72°C. The amplified products were purified by use of a Qiagen PCR purification kit and were cycle sequenced by use of a Beckman CEQ DTCS sequencing kit. Products were run and analyzed on a Beckman CEQ2000 automated DNA sequencer.

Allele- and Haplotype-Frequency Estimates

The allele frequencies at the separate sites—(CA)n-1, (CA)n-2, and Alu—were estimated by gene counting. Heterozygosities for individual sites and for the haplotypes have been estimated as n(1-Σp2i)/(n-1), where pi represents the frequency of the ith allele or haplotype for any given system and where n is the number of chromosomes in the sample. Probability values of Hardy-Weinberg (HW) exact tests and tests for heterozygosity excess or deficiency (Guo and Thompson 1992; Rousset and Raymond 1995; Rousset 1996) as well as values of FST (Weir and Cockerham 1984) were calculated with GENEPOP software (release 3.1b). Summary statistics for the STRP allele distributions were calculated by software available at the Microsat Web site. The computer program HAPLO (Hawley and Kidd 1995) was used to generate maximum-likelihood estimates of the haplotype frequencies for the (CA)n-1/Alu and (CA)n-2/Alu haplotypes. No individuals with missing STRP data were included in the data set used to estimate STRP/Alu haplotype frequencies. The number of possible three-locus haplotypes, including the two dinucleotide repeats and the Alu indel, was >500, and most were rare. In the African populations, nearly every individual had a unique three-locus phenotype. Consequently, haplotype-phase estimation would have very large standard errors, and, therefore, the complete three-locus haplotypes were not estimated; however, frequencies of two-locus haplotypes could be obtained with high statistical accuracy, because there were fewer “ambiguous” multisite heterozygotes. Tishkoff et al. (2000) have demonstrated that frequencies of two-locus STRP/indel haplotypes inferred by the HAPLO program do not differ significantly from frequencies based on gene counting using haplotypes identified unambiguously by molecular haplotyping methods. The inaccuracy in statistically estimated haplotype frequencies is greatest for rare (i.e., population frequency <.05) haplotypes. Because these errors are restricted to rare haplotypes, and because statistics such as haplotype diversity depend on the square of haplotype frequencies, the errors have negligible impact on subsequent calculations of population statistics.

Tests of Population Subdivision and Principal-Components Analysis (PCA)

Genetic differentiation among populations grouped by geographic region were estimated by FST (Wright 1931), DSW (Shriver et al. 1995), and DLR, the last of which is a likelihood-ratio statistic developed by Paetkau et al. (1997). FST (Wright 1931) partitions variance into within- and among-population components. DSW (Shriver et al. 1995) is based on the stepwise-mutation model and makes use of the fact that STRP alleles of similar size most likely have a more recent common ancestor than do STRP alleles of grossly divergent size. The likelihood-ratio test DLR (Paetkau et al. 1997) is used for testing the observed data against the null hypothesis that the sample is drawn from a single panmictic population. This measure is particularly sensitive to rare alleles or haplotypes that occur when highly variable STRP systems are examined.

Let f0 be the probability (averaged over populations) that two identical haplotypes within a population will be drawn, and let equation M1 be the probability that two identical haplotypes will be drawn across the entire sample; then equation M2. Shriver et al. (1995) defined the statistic DSW as a measure of population divergence for STRP loci. Let Xik be the frequency of a haplotype with i copies of the repeat at locus k in population X, and let Yik be the corresponding frequency in population Y. Letting j be a dummy index, assume that WXkΣiΣji-jxikxjk, WYkΣiΣji-jyikyjk, and WXYkΣiΣji-jxikyjk; then, according to the method of Shriver et al. (1995), DSW=WXY-[(WX+WY)/2]. In applying this statistic to haplotypes, we need to consider the distance between haplotypes that differ with respect to the Alu indel. Two haplotypes that have the same number of STRP repeats but differ at the Alu indel are treated as having a difference of x repeats for purposes of the DSW calculation, where x is allowed to be 1,2,3,…,5. This weighting is arbitrary and, in practice, was found to change the absolute estimates of DSW, but it did not change either the level of significance or the pattern of DSW among regions.

Define Lij as the likelihood that haplotype i will be drawn in population j, and let LiT be the likelihood that haplotype i will be drawn in any population other than j. A slight modification of the method of Paetkau et al. (1997) gives

equation image

where n is the number of chromosomes in the sample. Tail probabilities for DSW and DLR were generated as described by Hudson et al. (1992). Null distributions were obtained by randomly permuting the genotypes across the populations and calculating the test statistics over 10,000 such randomized data sets.


PCA was performed by defining each population as a vector of frequencies of two-locus haplotypes (composed of either the (CA)n-1 or (CA)n-2 repeat and the Alu indel). Frequencies were arcsine transformed and were treated as measures from a multivariate Gaussian distribution. PCA was performed on the correlation matrix of these scores, by Minitab Statistical Software (version 12).

LD Analysis

For each STRP allele, a 2×2 table was constructed for counts of that allele versus counts of all other alleles pooled, and for Alu(+) alleles versus Alu(−) alleles. The standardized, pairwise LD value D′ (Lewontin 1964) was calculated for each such 2×2 table, and the null hypothesis of LD (D=0) was tested by Fisher’s exact test (Sokal and Rohlf 1995, pp. 730–736). The significance of LD estimated by a likelihood-ratio test gave results that were virtually identical to those of Fisher's exact tests, so only the latter results are reported.


Alu Polymorphism

The full sample typed for the Alu indel represents 1,375 individuals originating from 30 geographically diverse populations (fig. 2 and table 1). Allele frequencies for the Alu polymorphism are shown in table 1. The Alu insertion is polymorphic, with moderate (⩾.30) heterozygosity levels in most populations, with the exceptions of the Nasioi and Papua New Guinean populations, which have low frequencies (7% and 16%, respectively) of the Alu(+) allele, and the South American Ticuna population, which has a very high frequency (91%) of the Alu(+) allele. All three of these populations are small and isolated and have experienced high levels of genetic drift, which likely played a role in the establishment of one allele at very high frequency.

Table 1
Allele Frequencies of the Alu-Insertion (+)/Deletion (−) Polymorphism

In general, African populations have low frequencies of the Alu(+) allele, in the range of .18–.38, with the exception of the Wolof (.44) and the Somali (.47). Non-African populations have high frequencies of the Alu(+) allele, in the range of .27–.91, with the exception of the Nasioi (.07) and Papua New Guineans (.16). These results are consistent with those of previous studies of the PLAT Alu polymorphism in a smaller sample of populations (Perna et al. 1992; Batzer et al. 1994; Tishkoff et al. 1996b; Stoneking et al. 1997; Novick et al. 1998). None of the populations exhibit a significant departure from HW equilibrium, with the exception of the Bamileke from Cameroon (P<.04), the Atayal from Taiwan (P<.02), and the Yakuts from Siberia (P<.01). However, these probability values are for individual tests, and none of the departures from HW expectation were significant at the experiment-wide level after the Bonferroni correction for multiple tests was applied. Only the Alu(−) allele was detected in 29 nonhuman primates examined (19 common chimpanzees, 6 pygmy chimpanzees, and 4 gorillas). Both the absence of the HS Alu in the nonhuman primates and the high heterozygosity of the Alu indel in most human populations support the hypothesis that the Alu-insertion event occurred after the divergence of humans from the great apes, ∼5 million years ago (Tishkoff et al. 1996b).

(CA)n Polymorphisms

The (CA)n-1 repeat is located ∼21,940 bp from the Alu polymorphism, at sequence position 7173 of the GenBank sequence (accession number K03021; fig. 1). Published primers flanking the repeat produce a PCR product that is 99–173 bp in size (Thomas and Drayna 1992). The GenBank sequence, which represents a 113-bp allele, is actually a compound repeat consisting of the sequence (GT)14(AT)12. The (CA)n-2 repeat is located ∼12,200 bp from the Alu polymorphism at sequence position 16911 of the GenBank sequence (fig. 1). Published primers flanking the repeat produce a PCR product that is 105–167 bp in size (Sadler et al. 1991). The GenBank sequence, which represents a 111-bp allele, is also a compound repeat consisting of the sequence (CA)15(CT)10. The (CA)n-1 and (CA)n-2 alleles in our analysis are based on the size of the PCR product when primers flanking the compound repeat are used, and therefore there is some possibility of additional heterogeneity at the sequence level.

In order to examine the possibility of sequence heterogeneity, (CA)n-1 and (CA)n-2 alleles were sequenced in a set of Bantu-speakers and Papua New Guinean individuals as well as in several chimpanzees and a gorilla; results are shown in table 2. In general, alleles of similar size in humans have a similar number of STRP repeats. But sequencing of multiple independently cloned alleles from the same individual indicates that slippage of Taq polymerase during PCR amplification prior to cloning can result in expansion or contraction of either of the two microsatellites that compose the “compound” STRP at (CA)n-1 and (CA)n-2; however, comparison of multiple alleles from several human individuals indicates that alleles of similar size at (CA)n-1 and (CA)n-2 are similar at the sequence level in Africans and Papua New Guineans. By contrast, (CA)n-1 and (CA)n-2 alleles of similar size in chimpanzees and gorillas are quite distinct at the sequence level, both from humans and from each other. Compared with humans, who have perfect, uninterrupted repeats, both the gorilla and the chimpanzee have highly compound repeats at (CA)n-1. In addition, the gorilla sequence at (CA)n-1 diverges from both the human sequence and the chimp sequence, in the region immediately flanking the STRP (table 2), because of deletions in the sequence farther from the STRP but within the 105-bp distance spanning the primer sites used for GENESCAN analysis (data not shown). At (CA)n-2, chimpanzees and humans differ slightly in the number of (AC)nCTn repeats, and chimpanzees have a TTC duplication absent in humans.

Table 2
Sequence Analysis of (CA)n-1 and (CA)n-2 Alleles in Selected Individuals Representing Various Human Populations and in Nonhuman Primates

Summary statistics of the size range, frequency, and diversity of alleles of the (CA)n-1 and (CA)n-2 STRPs are shown in table 3. In general, heterozygosity and allele-size ranges are highest in African populations, lower in Middle Eastern, European, and Asian populations, and lowest in Oceanic and New World populations (table 3). For the (CA)n-1 polymorphism, the only populations that exhibit genotype proportions that deviate significantly from HW expectations are the Central African Republic Biaka (P<.0001), Namibian Kwengo (P<.0001), Namibian Va/Sekele !Kung San (P<.0001), Namibian Zu/Wasi !Kung San (P<.002), North American Cheyenne (P<.004), and Rondonian Surui (P<.02) (table 3). All six of these populations have an excess of homozygosity. For the (CA)n-2 polymorphism, the only populations that exhibit genotype proportions that deviate significantly from HW expectations are the South African Bantu-speakers (P<.0001), Namibian Nama (P<.0001), Namibian Kwengo (P<.02), Namibian Va/Sekele !Kung San (P<.008), Namibian Zu/Wasi !Kung San (P<.0001), Papua New-Guineans (P<.04), and the Rondonian Surui (P<.01) (table 3). All seven of these populations have an excess of homozygosity. With the exception of the Cheyenne and Bantu-speakers, populations exhibiting a deviation from HW expectations for both STRPs have small population sizes. Additionally, the Rondonian Surui are a small Amazonian Amerindian tribe with high levels of consanguinity within the sample (Calafell 1999), which could account for deviation from HW expectations. It is also possible that the deficit of heterozygotes in some of these populations may indicate the presence of “null alleles” that, because of either mutations within the primer sequences or preferential amplification of an allele, we are not detecting; however, the fact that the Kwengo, Va/Sekele, Zu/Wasi, and Surui have a deficit of heterozygotes for both the (CA)n-1 and (CA)n-2 polymorphisms makes this possibility less likely and suggests that the deviation from HW expectations may be due to population-level effects (substructure, admixture, or inbreeding) or to chance deviations, rather than to the presence of “null alleles.”

Table 3
Allele-Size Statistics for PLAT (CA)n-1 and CA)n-2 STRP Markers, Based on PCR-Fragment Size

(CA)n-1 and (CA)n-2 allele sizes for nonhuman primates are within the range observed in humans but are less variable (table 4). The increased variability in humans may be due to the larger sample size examined, the bias resulting from selection of these STRPs on the basis of high heterozygosity in humans, and/or greater instability of the STRPs in humans, who have larger numbers of perfect repeats than do chimpanzees and gorillas (table 2).

Table 4
Frequencies of PLAT (CA)n-1 and (CA)n-2 Alleles in Nonhuman Primates

Haplotype Diversity

Each of the (CA)n repeats was analyzed separately as two-site haplotypes with the Alu polymorphism. Haplotype frequencies for both (CA)n-1/Alu and (CA)n-2/Alu haplotype systems, as well as haplotype-diversity values, are in Appendices A and B at the Kidd Lab Home Page and the Tishkoff lab Web page. Histograms of haplotype frequencies from a subset of geographically diverse populations are shown in figure 3. The total number of haplotypes and haplotype-diversity statistics for each major geographic region are given in table 5. For both (CA)n-1/Alu and (CA)n-2/Alu haplotype systems, both the total number of haplotypes and haplotype diversity are greatest in African populations, lower in Middle Eastern, European, and Asian populations, and lowest in Pacific Island and New World populations (fig. 3 and table 5). There are many more haplotypes specific to African populations than to non-African populations (table 5). In general, non-African populations have a subset of the haplotype diversity observed in Africa. This pattern of variation is consistent with results from the CD4 (Tishkoff et al. 1996a, 1998b), DM (Tishkoff et al. 1998a; S. A. Tishkoff, A. G. Clark, and T. Jenkins, unpublished data), DRD2 (Kidd et al. 1998), and PAH (Kidd et al. 2000) loci. In addition, African populations have highly divergent patterns of haplotype variation, whereas the non-African populations share a more similar pattern of haplotype variation. However, genetic drift has resulted in some divergent haplotype distributions in isolated populations from all regions of the world (fig. 3 ; also see Appendices A and B at the Kidd Lab Home Page and the Tishkoff lab Web page).

Figure  3Figure  3
Haplotype-frequency distributions of (CA)n-1 STRPs (this page) and (CA)n-2 STRPs (following page), on Alu(+) and Alu(−) chromosomes from a globally diverse subset of the populations included in this study. STRP allele sizes are shown on the X ...
Table 5
Haplotype Diversity Statistics for Populations Grouped by Geographic Region

The Papua New Guinean and Micronesian populations have low frequencies (8% and 13% frequency, respectively) of haplotypes containing large-sized (149–173 bp) (CA)n-1 alleles, which are absent in all other non-African populations studied (in which the maximum allele size is 145 bp). Such large alleles, however, are present at low to moderate frequencies in sub-Saharan African populations, which have a broader and more continuous distribution of alleles ranging up to 171 bp in size (fig. 3 and table 3). The very large number of dinucleotide repeats in the large-sized alleles made cloning and sequencing analysis difficult. However, sequence analysis of a 161-bp allele from a Papua New Guinean individual and a 139-bp allele in a Bantu-speaking individual demonstrates that both contain perfect repeats with no interruptions (table 2). Thus, it is not possible to distinguish whether these alleles are identical by descent or arose independently because of recurrent mutation.

PCA was used to provide a visual representation of population clustering based on haplotype variation (fig. 4). The first principal component (X-axis) accounts for 55.1% of the variance, and the second principal component (Y-axis) accounts for 10.5% of the variance. In general, populations cluster by geographic origin. The most distinct separation is between African and non-African populations. The northeastern-African—that is, the Ethiopian and Somali—populations are located centrally between sub-Saharan African and non-African populations. Among the non-Africans, populations cluster by geographic region, with some exceptions; the Siberian Yakut and the Japanese populations cluster with the North American populations and the Papua New Guinean and Taiwanese Ami populations have identical coordinates (fig. 4). On the PCA plot, the three Amazonian Amerindian populations (Ticuna, Surui, and Karitiana) and the Nasioi Melanesian population appear to be the groups that are most isolated from other geographically nearby populations, possibly because of high levels of genetic drift among these small and isolated populations.

Figure  4
PCA plot of populations, based on haplotype-frequency variation.• = Sub-Saharan African populations; + = northeastern-African populations; ▵ = European and Middle Eastern populations; * = Oceanic populations; ○ = Asian populations; ...

Population Subdivision

The amount of population subdivision was quantified with three statistics that capture different aspects of the data as described in the Subjects and Methods section. These estimates were obtained from populations grouped by geographic region; results are shown in table 6. FST values are lowest for European populations for the (CA)n-1/Alu haplotype system and are lowest for the New World populations for the (CA)n-2/Alu haplotype system; FST values are highest for the Oceanic and New World populations for the (CA)n-1/Alu haplotype system and for the Asian and Oceanic populations for the (CA)n-2/Alu haplotype system. However, FST is highly biased by within-population diversity levels. As can be seen by the formula for estimation of Wright’s FST (see the Subjects and Methods section), FST values will always be low when within-population diversity levels (i.e., heterozygosity levels) are high. Therefore, FST is not a good measure to use for comparison of levels of subdivision for highly variable STRP systems that vary widely in heterozygosity levels across geographic regions. The fact that African populations have FST values lower than those in other regions of the world is likely a result of the very high levels of STRP diversity within these populations, rather than a reflection of population history, subdivision, and migration.

Table 6
Estimates of Genetic Heterogeneity within Geographic Regions[Note]

Two measures of population subdivision that are particularly useful for highly variable STRP systems are DSW, which takes into account the stepwise-mutation process of STRPs (Shriver et al. 1995), and a likelihood-ratio test—DLR—described by Paetkau et al. (1997). Values for both DSW and DLR are lowest for the Oceanic populations and are highest for the African populations. These results demonstrate considerably higher haplotype heterogeneity among African populations than among populations from Europe and the Middle East, Asia, Oceania, or the New World.

Patterns of LD

Fisher’s exact test (Sokal and Rohlf 1995, pp. 730–736) was used to test for significance of LD between each STRP allele and the Alu indel polymorphism (table 7). If allele frequencies are sufficiently low, some alleles may fail to ever show statistically significant LD (Lewontin 1995), and these cases are indicated by blank spaces in table 7. Significance values in table 7 are not corrected for multiple comparisons. For the (CA)n-1/Alu haplotype system, with markers located ∼22 kb apart, there are sporadic cases of LD in both African and non-African populations (table 7). However, the pattern of LD in Africans and non-Africans is distinct. In 6 of the 13 African populations, there is an association between Alu(+) and either 121- or 123-bp alleles. However, in the non-African populations, only 3 of 18 populations exhibit this association, and, in 6 populations, the Alu(+) allele is most strongly associated with a 119-bp allele. The latter association is never observed in African populations. Alu(−) chromosomes are most frequently associated with 117–125-bp alleles in non-Africans (but rarely in Africa), whereas the Alu(−) chromosomes are most frequently associated with a 129-bp allele in Africans and in Middle Eastern Druze (this allele is rare or absent in all other non-African populations). For the (CA)n-2/Alu haplotype system, with markers located ∼12.2 kb apart, we observe a strong positive association between the 113-bp and Alu(+) alleles in 21 of the 31 African and non-African populations (table 7). However, for many other STRP alleles, Africans and non-Africans have distinct patterns of both allelic variation and LD (see table 7).

Table 7
Fisher’s Exact Test of Allele-Specific Pairwise LD, Estimated by Comparisons of Each Microsatellite Allele and Alu(+) and Alu(−) Alleles

Overall, there are fewer significant LD values (either positive or negative) in African populations than in non-African populations, relative to the number of alleles present at frequencies high enough to allow detection of significance. Also, the number of pairwise associations is considerably greater for the (CA)n-2/Alu haplotype system than for the (CA)n-1/Alu haplotype system. This pattern of LD is also demonstrated by the histograms of haplotype frequencies, shown in fig. 3 both the Alu(+) and Alu(−) chromosomes are associated with a wide range of STRP alleles for the (CA)n-1/Alu haplotype system. By contrast, for the (CA)n-2/Alu haplotype system, the Alu(+) allele tends to be associated predominantly with small-sized alleles (107–127-bp alleles, with 113 bp being most common) whereas the Alu(−) is associated with many alleles in the 105–169-bp range.


These results demonstrate the usefulness of haplotype analysis of STRPs, in combination with more-stable indels, for the reconstruction of human population history. Recently retroposed Alu elements are valuable tools for the reconstruction of historical population and demographic events, since they are unique, unidirectional, and stable mutation events for which the ancestral state (i.e., absence of the Alu element) is known. Additionally, analysis of Alu elements as haplotypes with highly variable STRP repeats makes it possible to estimate the time of insertion of the Alu element, on the basis of erosion of LD (A. G. Clark and S. A. Tishkoff, unpublished data). Knowledge of insertion times can be important for inference of the timing of historical evolutionary events and for reconstruction of human demographic history (Sherry et al. 1997).

Haplotype History at the PLAT Locus

STRP/Alu haplotype analysis can be useful for inference of the evolutionary history of a locus of interest. The absence of the HS Alu in chimpanzees and gorillas, as well as the fact that the Alu element is highly variable for presence/absence in populations from globally diverse regions, suggests that the insertion of this retroposable element occurred after the divergence of humans from the great apes, which occurred ∼5 million years ago (Wilson and Sarich 1969; Kumar and Hedges 1998), but prior to the divergence of modern human populations, which occurred during the past 150,000 years (Stringer and Andrews 1988; Harpending et al. 1993; Cavalli-Sforza et al. 1994; Goldstein et al. 1995; Nei 1995; Tishkoff et al. 1996a, 1996b, 1998b; Stoneking et al. 1997). The two dinucleotide repeats (CA)n-1 and (CA)n-2, which are located ∼22 and ∼12.2 kb, respectively, from the polymorphic Alu, are variable in common chimpanzees (P. troglodytes), pygmy chimpanzees (P. paniscus) and gorillas (G. gorilla). The allele sizes observed in nonhuman primates are similar to those observed in humans. However, sequence analysis of the STRPs in humans, chimpanzees, and gorillas demonstrates that alleles that (on the basis of PCR-product length) are found to be of similar size are heterogeneous at the sequence level (table 2). These results confirm and extend previous studies demonstrating sequence heterogeneity of STRP alleles (Blanquer-Maumont and Crouau-Roy 1995; Garza and Freimer 1996; Grimaldi and Crouau-Roy 1997; Rosenbaum and Deinard 1998; Deinard and Kidd 1999). Sequence analysis of (CA)n-1 in the gorilla also demonstrates that deletions outside the repeat unit can affect the size of the PCR product. Thus, one must be cautious about making inferences about the evolutionary history of different taxa based on sizes of PCR amplicons of STRPs without sequence analysis of alleles. Additionally, our results demonstrate that slippage by Taq polymerase during PCR amplification can result in expansion or contraction of either of the two repeats composing a “compound” STRP. Thus, multiple clones from multiple individuals must be sequenced, to obtain a “consensus sequence” of the dinucleotide composition of compound STRPs. Such knowledge could be important for determining whether alleles are identical by descent. However, even if STRP alleles are identical at the sequence level, this is not absolute proof of identity by descent, since identical alleles could have arisen by independent convergent mutation. In such a case, identity by descent can be determined only by detailed analysis of genetic diversity in the sequence flanking the STRP.

Initially, the Alu insertion into intron 8 of the TPA gene occurred on a chromosome containing a single allele at each of the neighboring dinucleotide markers. The “TPA Alu” likely inserted into a chromosome containing a small-sized (CA)n-2 allele (possibly the 113-bp allele, which is most common in modern populations). The close proximity of the Alu marker and the (CA)n-2 marker (which are 12.2 kb apart) has resulted in the maintenance of strong LD between the Alu(+) allele and the 113-bp allele. The unimodal distribution of (CA)n-1 and (CA)n-2 alleles on Alu(+) and Alu(−) haplotype backgrounds in most populations is consistent with a stepwise-mutation model in which mutations result in expansion or contraction by one or a few repeat units, as has been observed at many other STRP repeats in humans (Shriver et al. 1993; Valdes et al. 1993; Weber and Wong 1993; Di Rienzo et al. 1994, 1998). The greater variance of STRP alleles on Alu(−) chromosomes compared with Alu(+) chromosomes (table 3) is consistent with a recent origin of the Alu-insertion allele. LD between (CA)n-1 and (CA)n-2 can erode by mutation as fast as by recombination. The variance of STRP alleles is similar for both (CA)n-1 STRPs and (CA)n-2 STRPs (table 3), suggesting that their mutation rates may be similar. Additionally, at the sequence level, the numbers of perfect repeats in a 121-bp (CA)n-1 allele and those in a 113 bp (CA)n-2 allele (both of which are the alleles most common on Alu(+) chromosomes) are nearly identical, which makes it less likely that the differential pattern of LD observed could be due to fewer perfect repeats producing a lower mutation rate of the 113-bp (CA)n-2 allele. Thus, it seems likely that recombination has resulted in low levels of LD between (CA)n-1 and the Alu polymorphism (which are 22 kb apart), whereas high levels of LD have been maintained between (CA)n-2 and the Alu polymorphism (which are 12.2 kb apart). Because of the loss of LD between (CA)n-1 and the PLAT Alu, the haplotype history has become obscured, and it has become difficult to infer the ancestral (CA)n-1/Alu haplotype. However, the narrower distribution of (CA)n-1 alleles on Alu(+) chromosomes compared with Alu(−) chromosomes, with most alleles being 119–129 bp in size, suggests that the Alu-insertion event occurred on a chromosome containing a (CA)n-1 allele in this smaller size range, possibly on a chromosome containing a 121-bp allele, which is the most common Alu(+) haplotype in Africa (fig. 3). Analysis of variation of the two dinucleotide repeats on Alu(+) and Alu(−) haplotypes, as well as of the breakdown of disequilibrium between the markers, suggests that the Alu insertion occurred during the past 500,000 years (A. G. Clark and S. A. Tishkoff, unpublished data), whereas the global distribution of the Alu(+) allele suggests that the insertion event occurred prior to migration of modern humans out of Africa, ∼100,000 years ago.

Human Evolutionary History

The (CA)n-1/Alu and (CA)n-2/Alu haplotype systems are highly informative for reconstructing historical migration and population-differentiation events, as demonstrated by the PCA plot of population-clustering based on haplotype-frequency variation (fig. 4). These results are consistent with anthropological knowledge, results from studies of classical markers (Nei and Roychoudhury 1993; Cavalli-Sforza et al. 1994; Nei 1995), and results from molecular markers from autosomes (Bowcock et al. 1991, 1994; Jorde et al. 1995, 1997; Nei 1995; Armour et al. 1996; Tishkoff 1996a, 1998a, 1998b; Harding et al. 1997; Stoneking et al. 1997; Zietkiewicz 1997, 1998; Calafell et al. 1998; Kidd et al. 1998, 2000; Harris and Hey 1999), mtDNA (Cann et al. 1987; Vigilant et al. 1989, 1991; Merriwether 1991; Penny et al. 1995), and Y chromosome DNA (Hammer 1995; Hammer et al. 1997, 1998; Underhill et al. 1997). These studies suggest a recent and primary subdivision between African and non-African populations, high levels of divergence among African populations, and a recent shared common ancestry of non-African populations, from a population originating in Africa. The intermediate position, between African and non-African populations, that the Ethiopian Jews and Somalis occupy in the PCA plot also has been observed in other genetic studies (Ritte et al. 1993; Passarino et al. 1998) and could be due either to shared common ancestry or to recent gene flow. The fact that the Ethiopians and Somalis have a subset of the sub-Saharan African haplotype diversity—and that the non-African populations have a subset of the diversity present in Ethiopians and Somalis—makes simple-admixture models less likely; rather, these observations support the hypothesis proposed by other nuclear-genetic studies (Tishkoff et al. 1996a, 1998a, 1998b; Kidd et al. 1998)—that populations in northeastern Africa may have diverged from those in the rest of sub-Saharan Africa early in the history of modern African populations and that a subset of this northeastern-African population migrated out of Africa and populated the rest of the globe. These conclusions are supported by recent mtDNA analysis (Quintana-Murci et al. 1999). In light of the high variance expected on the basis of the stochastic effects of genetic drift at a single locus, it is particularly striking that the PCA plot of populations so accurately reflects population relationships as predicted on the basis of common ancestry as well as on the basis of geographic and linguistic similarity. For example, in the PCA plot of African populations (fig. 4), the Khoisan speakers (Nama, Va/Sekele, Zu/Wasi, and Kwengo) all cluster together, the Biaka and Mbuti populations cluster together, and the western-African, central-African, and southern-African Bantu-speaking populations cluster together. The latter cluster is predicted in light of linguistic evidence and the archeological record that suggest a Bantu migration from central Africa during the past 3,000 years (Clark 1959; Guthrie 1962; Greenberg 1963; Nurse et al. 1985). Additionally, the three Amazonian populations (Surui, Karitiana, and Ticuna) cluster together, as do the two North and Central American populations (Cheyenne and Maya). Interestingly, the Siberian Yakut and Japanese populations cluster with these North American Indian populations. This is consistent with the hypothesis, based on linguistic, archeological, and genetic data, that modern Amerindians may have originated from one or more populations migrating from Siberia or other regions in northeastern Asia (Kidd et al. 1991; Kidd and Kidd 1996; Kolman et al. 1996; Calafell et al. 1998; Starikovskaya et al. 1998; Karafet 1999; Schurr et al. 1999). The fact that these haplotype systems are so informative for the inference of population history is likely due to the combined use of highly variable STRP markers with the stable Alu-insertion polymorphism.

Tests of population subdivision that consider the high variability of STRP haplotypes (DSW and DLR) demonstrate that Africa has levels of population subdivision that are higher than those of any other geographic region (table 6). The high heterozygosity levels, high STRP variance, and high haplotype-diversity levels, within and between African populations, compared with populations from all other geographic regions (table 5), suggest that African populations have an older population history and have maintained both a large effective population size and high levels of population subdivision. These results are consistent with results of studies of other STRP haplotype systems (Tishkoff et al. 1996a, 1998a, 1998b; Kidd et al. 1998; S. A. Tishkoff, A. G. Clark, and T. Jenkins, unpublished data), Alu elements ( Sherry et al. 1997; Stoneking 1997; Harpending et al. 1998), STRPs (Shriver et al. 1997; Calafell et al. 1998; Kimmel et al. 1998; Reich and Goldstein 1998; Relethford and Jorde 1999), Y-chromosome DNA (Hammer et al. 1997, 1998; Pritchard et al. 1999; Scozzari et al. 1999), mtDNA (Rogers and Harpending et al. 1992; Sherry et al. 1994; Rogers and Jorde 1995), and craniometric data (Relethford and Harpending 1994; Relethford 1995), all of which suggest that African populations (a) may have expanded in size earlier than have non-African populations and (b) have maintained a larger effective population size. Africans have many more region-specific haplotypes, and, in general, non-Africans have a subset of the haplotypes present in Africa. Compared with African populations, the non-African populations have less haplotype diversity, more-extensive LD, and a similar pattern of haplotype variation across geographic regions (e.g., Asia, Europe, Oceania, and the New World) (fig. 3 and table 7). These results are consistent with both an appreciable founder effect associated with migration out of Africa and a recent shared common ancestry of non-African populations that has been followed by rapid population expansion. In addition, there is no indication that non-African populations have descended from multiple migrations from different source populations in Africa; rather, the shared pattern of variation among geographically diverse non-African populations supports previous findings (Tishkoff et al. 1996a, 1998a, 1998b; Calafell et al. 1998; Kidd et al. 1998) that indicate that all non-African populations have descended from a single source population, most likely from northeastern Africa (although subsequent gene flow from Africa to Australo-Melanesia remains a possibility, as is discussed below).

The pattern of LD between the (CA)n-1 and (CA)n-2 STRPs and the Alu polymorphism is distinct in Africans vis-à-vis non-Africans (table 7). With respect to the number of alleles present at high frequency, the African populations have more haplotypes, more-divergent patterns of LD, and, overall, fewer significant LD values than do non-Africans. These results are consistent with the pattern of LD observed at several loci: CD4 (Tishkoff et al. 1996a, 1998b), DM (Tishkoff et al. 1998a), DRD2 (Kidd et al. 1998), and PAH (Kidd et al. 2000). Levels and patterns of LD depend on a number of factors, including initial conditions (e.g., population size), population structure, founder effect, admixture, and the dynamics of molecular processes of mutation and recombination. If mutation and recombination rates are assumed to have remained constant across populations, then the global pattern of LD observed at these loci is a reflection of the population and demographic histories of these populations. The pattern of LD in African populations is consistent with a larger, more subdivided population structure in Africa. The divergent pattern of LD in non-African populations relative to African populations is likely the result of a founding event by one or more small populations emerging from Africa during the past 100,000 years and expanding and spreading throughout the rest of the world (Stringer and Andrews 1988; Stringer 1993). During this founding event, the particular pattern of pairwise allelic association may differ from that in the parental African population, because of the stochastic effects of drift during population founding. The pattern of LD established at the time of population founding will be preserved during subsequent rapid population expansion, because of the decreased effects of genetic drift. However, there are some exceptions. For the (CA)n-2/Alu haplotype system, the Oceanic and several New World populations lack the strong association, present in most other populations, between the 113-bp allele and the Alu(+) allele. This is due to an increase in the frequency of 113/Alu(−) chromosomes, possibly because of the effects of genetic drift in small populations that have recently undergone founding events; for example, in the Rondonian Surui sample, the 113/Alu(+) and 113/Alu(−) haplotypes exist at identical frequencies, resulting in complete linkage equilibrium (fig. 3). Interestingly, in the Amazonian Ticuna sample, only the 113/Alu(+) haplotype exists at high frequency (fig. 3), demonstrating the strong effects of genetic drift within these small, isolated tribal populations. These results also demonstrate that genetic drift can result in either the establishment of higher levels of LD, as likely occurred during migration out of Africa, or a decrease in disequilibrium, as occurred in some of the Oceanic and New World populations, for the (CA)n-2/Alu haplotype system. Thus, because of the stochastic effects of genetic drift, we anticipate that there will be some heterogeneity among loci, in their global patterns of LD (Peterson et al. 1999). In the case of common SNPs in autosomal genes, in which the variation may predate the expansion out of Africa, patterns of fine-scale LD among sites within genes may show less geographic variation (Clark et al. 1998). Genetic variation that arose after the time of population founding would exhibit the highest variability. A systematic study of patterns of LD of SNPs, indels, and STRPS at multiple loci among geographically diverse populations will thus provide a more precise reconstruction of modern human population and demographic history.

Implications for Oceanic-Island Population History

The high variability of STRP/Alu haplotype systems can be particularly informative for the reconstruction of historic migration events. For example, Papua New Guinean and Micronesian populations have haplotypes containing large-sized (149–173 bp) (CA)n-1 STRP alleles that have not been observed in any other non-African populations but that have been observed in sub-Saharan African populations, the latter of which have a continuous distribution of (CA)n-1 alleles up to 171 bp in size. These alleles are present on both Alu(+) and Alu(−) haplotype backgrounds. This observation is intriguing in light of hypotheses based on archeological, morphological, and genetic evidence that suggest that there could have been early colonization of Papua New Guinea by a distinct wave of migration out of Africa across southern and eastern Asia and into Australo-Melanesia (Birdsell 1967; 1993, pp. 22–23; Lahr and Foley 1995; Harpending et al. 1996; Stoneking et al. 1997). Archeological data indicate that Australia and New Guinea, which, during the Pleistocene, were a single landmass referred to as “Sahul,” were occupied as early as 40,000–65,000 years ago (Roberts and Jones 1994; Jones 1995; O’Connell and Allen 1998; Johnson et al. 1999; Miller et al. 1999; Redd and Stoneking 1999). Papua New Guinea highland populations are thought to be the descendants of the earliest migration into this region, whereas coastal Papua New Guinea populations are thought to be admixed with Austronesian speakers originating from Southeast Asia who colonized coastal Papua New Guinea during the past 5,000 years (Bellwood 1989; Redd and Stoneking 1999). The hypothesis of ancient ties between Papua New Guinean and African populations is supported by craniometric studies (Howells 1989, pp. 37–79), as well as by genetic studies of mtDNA variation (Redd and Stoneking 1999), autosomal sequence variation (Kofler et al. 1995), and polymorphic Alu loci (Harpending et al. 1996; Stoneking et al. 1997), all of which show Papua New Guinea populations as clustering near the ancestral African root of phylogenetic trees constructed from the data. However, analyses of classical genetic polymorphisms (Cavalli-Sforza et al. 1994) and of haplotype variation at the CD4 (Tishkoff et al. 1996a, 1998b) and DRD2 loci (Kidd et al. 1998) do not find evidence for a closer relationship of Papua New Guinea populations to Africans than to non-Africans. Thus, these nuclear-haplotype and classical-genetic data sets do not support an independent origin of Australo-Melanesians from a different source population in Africa, but they do not rule out the possibility of an ancient migration event from Africa, for which the genetic trail has been largely, but not completely, erased by subsequent migrations.

The presence of large-sized (CA)n-1 alleles in Papua New Guinean, Micronesian, and African populations could indicate either shared common ancestry, gene flow from African populations into these Oceanic populations, and/or independent mutation into the large-sized–allele range in African and Oceanic populations. Sequence analysis of a large-sized allele from a Papua New Guinea individual and of a large-sized allele from a Bantu-speaking individual indicate that both alleles consist of perfect repeats. Thus, in the absence of a more detailed analysis of sequence variation in the regions flanking the STRP, it is not possible to distinguish whether they are identical by descent or arose by recurrent mutation. However, because large “jumps” in allele size of STRP repeats are uncommon, it is likely that mutation into the large-sized range would have been a rare and unique event. The fact that we observe a wide range of large-sized alleles (nine alleles 149–173 bp in size) in Papua New Guinean and Micronesian populations, as well as the fact that we observe these alleles on both Alu(+) and Alu(−) haplotype backgrounds, would indicate that this rare mutational event was ancient and that there has been time for mutation and recombination to produce the haplotype variation observed in modern populations. Alternatively, these chromosomes could have been present at the time of population founding and could have drifted to moderate frequencies, and/or they could have been introduced by recent migration from Africa. We observe, in both highland (48 chromosomes) and lowland (94 chromosomes) Papua New Guineans, haplotypes containing large-sized (CA)n-1 alleles, although the frequency is greater in highlanders (16.8%) than in lowlanders (3.2%). Again, this observation would indicate an ancient origin for these haplotypes. In the PCA based on haplotype-frequency variance (fig. 4), the Papua New Guinean and Micronesian populations cluster closest to the Southeast Asian Chinese Han and to the Taiwanese Ami and Atayal populations, as well as to northeastern-African—that is, the Ethiopian and Somali—populations. The Nasioi appear to be outliers in the PCA plot, but this may be due to the small sample size and/or to high levels of genetic drift in this small, isolated population, as suggested by a number of other genetic studies of this same population (Bowcock et al. 1991; Kidd and Kidd 1996; Tishkoff et al. 1996a, 1996b, 1998a, 1998b). Analysis of haplotype variation at the DM locus in these same Papua New Guinean samples indicated the presence, at moderate frequency, of microsatellite haplotypes that are rare in all other non-African populations but that are present in African populations (Tishkoff et al. 1998a; S. A. Tishkoff and T. Jenkins, unpublished data). These data are consistent with the hypothesis of an early migration event into Australo-Melanesia, followed by long periods of isolation. However, it is also possible that these haplotypes could have evolved in situ in populations that have been isolated during the past 40,000–65,000 years and are subject to high levels of genetic drift. Additionally, the shared pattern of haplotype diversity and LD—for (CA)n-1/Alu haplotypes containing small-sized STRP alleles, for (CA)n-2/Alu haplotypes, and for haplotypes at the CD4 loci—suggest that Papua New Guinean populations originated from the same source population as did other non-African populations, although the migration events into different geographic regions may have been distinct and possibly could have occurred at different times. To differentiate among these possibilities, it will be necessary to do, at multiple loci, more-detailed haplotype and sequencing analysis of diverse Papua New Guinean and African populations.

The (CA)n-1/Alu haplotype data are also informative for reconstruction of historic migration patterns of remote Oceanic Island populations. According to the “express train” model (Diamond 1988), remote Oceanic populations originated from a wave of migration from Southeast Asia during the past 4,000 years. According to this model, there would have been limited gene flow between Melanesian populations and the ancestors of remote Oceanic populations, and the closest genetic affinity of remote Oceanic Islanders would be expected to be with Southeast Asian populations. This model is supported by a number of mtDNA analyses that identify predominantly Asian mtDNA types in Polynesians and Micronesians, with limited amounts of Melanesian mtDNA types (Hertzberg et al. 1989; Lum et al. 1994, 1998; Redd et al. 1995; Sykes et al. 1995; Lum and Cann 1998). According to the “slow-train” model of origin of remote Oceanic populations, there have been complex patterns of migration and gene flow among Southeast Asian, Melanesian, and Oceanic populations (Lum and Cann 1998; Terrell 1988). This model is supported by data on nuclear and Y-chromosome loci (Serjeantson 1985; O’Shaughnessy et al. 1990; Martinson 1996; Roberts-Thomson et al. 1996; Lum et al. 1998). Lum et al. (1998) have suggested that there may have been male-specific gene flow from coastal Papua New Guinea to Micronesia, which would explain the discrepancy between the mtDNA and nuclear-genetic data. The PLAT (CA)n-1/Alu haplotype data also support the slow-train model of origin of remote Oceanic populations. Because mutation from a small-sized repeat to a large-sized repeat probably has been a rare event, it seems unlikely that it would have occurred independently in both Micronesian and Papua New Guinean populations, and this, in turn, suggests that there has been gene flow between these regions. Additionally, the fact that the PCA coordinates of the Ami are identical with those of the Papua New Guineans is intriguing in light of other studies suggesting that Austronesian-speaking indigenous Taiwanese populations (such as the Ami and Atayal) played a significant role in the Austronesian expansion into Papua New Guinean and other regions of Oceania (Bellwood 1978, 1985, 1995; Melton et al. 1995, 1998; Sykes et al. 1995; Redd and Stoneking 1999). Further studies of autosomal, Y-chromosome, and mtDNA markers will help us to distinguish among these models of Oceanic Island origins.

Electronic-Database Information

Accession numbers and URLs for data in this article are as follows:

Kidd Lab Home Page, http://info.med.yale.edu/genetics/kkidd (for haplotype frequencies, available via ALFRED)
NCBI GenBank Overview, http://www.ncbi.nlm.nih.gov/Web/Genbank (for human PLAT reference sequence [accession number K03021])
Tishkoff lab Web page, http://www.life.umd.edu/biology/faculty/tishkoff/index.html (for haplotype frequencies)


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