Genetic Variation and Differentiation at Microsatellite Loci in Drosophila simulans: Evidence for Founder Effects in New World Populations

Corresponding author: Charles F. Aquadro, Section of Genetics and Development, Cornell University, 401 Biotechnology Building, Ithaca, NY 14853., cfa1{at}cornell.edu (E-mail).

Communicating editor: A. G. CLARK

	ABSTRACT

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

Drosophila simulans isofemale lines from Africa, South America, and two locations in North America were surveyed for variation at 16 microsatellite loci on the X, second, and third chromosomes, and 18 microsatellites, which are unmapped. D. simulans is thought to have colonized New World habitats only relatively recently (within the last few hundred years). Consistent with a founder effect occurring as colonizers moved into these New World habitats, we find less microsatellite variability in North and South American D. simulans populations than for an African population. Population subdivision as measured at microsatellites is moderate when averaged across all loci (F_ST = 0.136), but contrasts sharply with previous studies of allozyme variation, which have showed significantly less differentiation in D. simulans than in D. melanogaster. There are substantially fewer private alleles observed in New World populations of D. simulans than seen in a similar survey of D. melanogaster. In addition to possible differences in population size during their evolutionary histories, varying colonization histories or other demographic events may be necessary to explain discrepancies in the patterns of variation observed at various genetic markers between these closely related species.

DIFFERENTIATION between geographically distinct populations of Drosophila simulans has been estimated using several forms of genetic variation. Patterns of polymorphism for morphological traits (HYYTIA et al. 1985 ), allozymes (CHOUDHARY and SINGH 1987 ), and mitochondrial DNA (BABA-AISSA et al. 1988 ; HALE and SINGH 1991 ; Rand et al. 1994 ; BALLARD et al. 1996 ) indicate little spatial substructure for D. simulans in comparison to D. melanogaster. In addition to differences in spatial substructuring, fewer protein loci are polymorphic, and clines are less pronounced in D. simulans than in D. melanogaster (reviewed in SINGH and LONG 1992 ).

Although both species are largely cosmopolitan in their range, it has been suggested that differences in genetic variation between these closely related species may reflect differences in their adaptive strategies (CHOUDHARY and SINGH 1987 ), or in the length of time since each has colonized its current range (SINGH 1989 ). It is also possible there have been differences in population size of each species over their evolutionary histories (AQUADRO et al. 1988 ). In a survey of restriction site polymorphism in the rosy region, AQUADRO et al. 1988 found sixfold higher nucleotide polymorphism in a North Carolina D. simulans population in comparison to a sample of D. melanogaster lines collected in the same location. Nucleotide data from additional nuclear loci support this difference (reviewed in MORIYAMA and POWELL 1996 ).

In contrast to studies of allozyme variation, a survey of nucleotide sequence from the vermilion locus (BEGUN and AQUADRO 1995 ) indicated moderate genetic differentiation between African and non-African populations of both species. Fixation indices (F_ST) at this locus in D. simulans and D. melanogaster were approximately equal. D. simulans populations from diverse geographic localities also vary in their number of genomic copies of various transposable elements (GIRAUD and CAPY 1996 ; VIEIRA and BIEMONT 1996 ), suggesting that the differentiation between D. simulans populations observed at vermilion is not atypical.

We wanted to use a more broad, genome-based approach to estimate levels of population structure within D. simulans. Markers for the quantification of genetic differentiation would ideally evolve neutrally and not be highly influenced by selection acting at linked sites. Mitochondrial DNA shows very little variation among D. simulans populations worldwide (BABA-AISSA et al. 1988 ; HOFFMANN et al. 1990 ), quite possibly due to recent selection (Rand et al. 1994 ; BALLARD et al. 1996 ) and is therefore of little use in estimating population structure for this species. Like allozymes, microsatellites are spread throughout the nuclear genome (TAUTZ 1989 ; SCHUG et al. 1998 ) and may be affected by linkage to loci which are under strong selection (SLATKIN 1995 ). There is less evidence, however, of fitness effects associated with microsatellites, and specific alleles are not expected to have adaptive consequences as are some allozyme charge variants.

The main objective of this article is to estimate levels of genetic differentiation within D. simulans using the variation at microsatellites. We initially survey microsatellites identified through a search of D. melanogaster sequences in GenBank, finding significantly less variation in D. simulans than in D. melanogaster (this study; WETTERSTRAND 1997 ). Analysis of additional microsatellites isolated in D. simulans shows that this reduction is likely an artifact of ascertainment bias. The patterns of spatial substructuring observed are much the same within each subset of markers, and useful comparisons can be made using the information from the localization of the former set. We interpret subtle differences in the partitioning of microsatellite variation among populations to suggest complex differences in the demographic histories of D. simulans and D. melanogaster.

	MATERIALS AND METHODS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

Population samples:
Twenty D. simulans isofemale lines were sampled for Harare, Zimbabwe; Atacames, Ecuador; and Soda Lake, California and for a combined sample of 20 lines from Floral City and Homosassa, Florida (the data were pooled as the sites are within about 50 km of each other). The Zimbabwe, Ecuador, and California lines are as described previously (BEGUN and AQUADRO 1995 ). Floral City and Homosassa, Florida lines were collected in March, 1994 at Banes Orchard and Sugarmill Woods, respectively, by C. F. Aquadro. Single female flies were prepared as templates for PCR amplification using the method of GLOOR et al. 1993 .

Isolation, amplification and detection of microsatellites:
The microsatellites surveyed in this study were either identified by a search of D. melanogaster sequences in GenBank (16 mapped di-, tri-, and tetranucleotide loci listed in Table 7; SCHUG et al. 1998 ), or as the result of hybridization of genomic clones to probes consisting of an array of all possible dinucleotide repeats (the remaining 18 dinucleotide loci with the prefix DSIM; HUTTER et al. 1998 ). The PCR primers used in this study that were designed for use in D. melanogaster (SCHUG et al. 1998 ) were found to work well in D. simulans using the same conditions for amplification. (The primer sequences and conditions for amplification of these microsatellites can be found on the World Wide Web at http://www.bio.cornell.edu/genetics/aquadro/aquadro.html/.)

Microsatellites were scored by PCR amplification of the desired locus where one of the primers had been [-³³P]dATP end-labeled using T4 polynucleotide kinase (see SCHUG et al. 1998 for complete details). The resulting PCR products were size-fractionated on standard acrylamide sequencing gels. Gels were dried on blotting paper and placed next to autoradiographic film for 1- to 2-day exposures. Allele sizes were scored by comparison to microsatellite PCR products of known length and a DNA sequence run on the same gel. The distribution of microsatellite alleles from our survey of D. simulans populations is given in Table 7 along with the name and repeat type of each microsatellite locus.

Data analysis:
Microsatellite allele sizes were scored by comparison of PCR product lengths to the sequence of the locus in GenBank, or from a genomic clone. Repeat length was estimated by first subtracting the length of flanking sequences and dividing the remainder by the number of bases in the repeat type of the locus in question (i.e., two, three, or four nucleotides). To limit the bias introduced by the effects of inbreeding in small laboratory populations, only a single allele was scored for each individual tested. In scoring heterozygotes, a single allele was chosen at random for estimates of population parameters.

Analyses of microsatellite variation within and between populations were carried out using standard spreadsheet packages and the FSTAT program (GOUDET 1997 ) for calculating F_ST. Expected heterozygosity (H) for each locus in each population was calculated as

where n is the number of chromosomes sampled and p_i is the frequency of the ith allele (NEI 1978 ). Variance in repeat number is calculated as the sum of the squares of the difference between the mean number of repeats at the locus and the repeat number for each allele times its frequency in the population.

Differentiation between populations was estimated from variance in allele frequencies using the method of WEIR and COCKERHAM 1984 for F_ST = , where a is the variance in allele frequency between populations and b is the variance in allele frequency within populations. We used the allelic permutations generated by FSTAT (GOUDET 1997 ) to test the significance of F_ST and by randomly pairing alleles into genotypes within populations. Mean differentiation or diversity statistics are simply averaged across all loci in each population.

	RESULTS

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

Variability of microsatellites in D. simulans:
D. melanogaster-derived microsatellites: For microsatellites identified from D. melanogaster sequences in GenBank, the per locus expected heterozygosities in our D. simulans population surveys averaged 0.373 and ranged from 0 to 0.717 (see Table 1). Variance in repeat number averaged 3.19, ranging from 0 to 20.32. The maximum number of alleles found at a single locus for these microsatellites is eleven (for the DROTROPI1 locus), and the average number of alleles per locus is 4.69 for the entire sample of 80 isofemale lines (Table 1).

D. simulans-derived microsatellites: For microsatellites isolated from a screen of a D. simulans genomic library, variability in our survey populations is higher. These data are summarized in Table 2. The per locus expected heterozygosity in our D. simulans sample ranges from 0.124 to 0.809, averaging 0.576. Although the range of expected heterozygosities is similar between the two sets of microsatellites, the histograms in Figure 1 show that there are more alleles at intermediate frequency (heterozygosity is, on average, higher) for the D. simulans-derived microsatellites surveyed than for D. melanogaster-derived microsatellites surveyed in the same four populations. The number of alleles per locus ranges similarly from 2 to 11, but the average is 7.11 alleles per microsatellite locus at D. simulans-derived microsatellites.

View larger version (36K): In this window In a new window Download PPT slide   Figure 1. Histograms of expected heterozygosity at 16-D. melanogaster-derived, and 18-D. simulans-derived microsatellites in D. simulans from Zimbabwe, Ecuador, Florida, and California.

Patterns of locus-specific variability: For D. melanogaster-derived microsatellites, a single dinucleotide repeat microsatellite locus (DROACS2) was fixed for a single allele length (12 repeats) in all populations surveyed, while two others (DROEXO2 and DMU1951) have very little variation. These markers are polymorphic only in the Zimbabwe sample and have just two alleles. Other microsatellite loci are monomorphic in specific populations from the survey (see Table 7). For example, two markers (DROFASI and DROSEV1) are completely fixed for one allele size for our Florida sample, while remaining variable in other populations. Another locus (DMPROSPER) is fixed in the Ecuador population and highly variable in three other populations (heterozygosities at the locus are 0.508, 0.337, and 0.268, for Zimbabwe, California, and Florida, respectively). In contrast, only one locus (DSIM18) among the D. simulans-derived microsatellites is fixed for allele length; this occurs in both the Zimbabwe and California populations.

Variation among populations of D. simulans: We find that variability is less in non-African populations of D. simulans compared to the Zimbabwe sample. In Figure 2, we have summarized the variability among populations in our D. simulans surveys. For the D. melanogaster-derived (GenBank) microsatellites, the average expected heterozygosity in Zimbabwe is 0.449, with the range of values at individual polymorphic loci from 0.100 to 0.835. Similarly, variation is higher in this sample than in other populations for the D. simulans-derived microsatellites, with an average expected heterozygosity of 0.638, ranging from 0.314 to 0.879 at individual loci.

View larger version (27K): In this window In a new window Download PPT slide   Figure 2. Variability at D. melanogaster- and D. simulans-derived microsatellites in D. simulans from Zimbabwe, Ecuador, Florida, and California. (A) Average expected heterozygosity per locus. (B) Average variance in repeat number. (C) Average number of alleles per locus. (D) Private alleles. Bars represent the upper bound of the 95% confidence interval.

Although the trend is for heterozygosity to be lower in surveys of New World D. simulans populations than in Zimbabwe (Figure 2), ANOVA tests of both the D. melanogaster-derived and the D. simulans-derived microsatellite data indicate that average expected heterozygosity is not significantly different between populations (D. melanogaster-derived: F = 0.702, d.f. = 3, and P = 0.554; D. simulans-derived: F = 0.831, d.f. = 3, and P = 0.481). However, both the number of alleles per locus (D. melanogaster-derived: F = 2.90, d.f. = 3, and P = 0.042; D. simulans-derived: F = 3.15, d.f. = 3, and P = 0.030), and the number of private alleles (D. melanogaster-derived: H = 17.788, d.f. = 3, and P < 0.0001; D. simulans-derived: H = 14.351, d.f. = 3, and P = 0.0002) differ significantly between populations for each set of markers. Note that for these analyses we used ANOVA to test for a difference in the average number of alleles per locus in the four populations, but to test for a difference in the number of private alleles in each population the nonparametric Kruskall-Wallis test was employed as the data are not normally distributed.

To analyze the difference between Zimbabwe and the remaining populations for the number of alleles per locus, we performed a second (posthoc) test. We employed Fisher's least significant difference test with a Bonferroni correction. Six pairwise comparisons were necessary to isolate the source of the difference between populations with the hypothesis that there were no differences between populations for any pairwise comparison. This test and the similar Scheffé test do not show significant differences in all comparisons, but do indicate that the average number of alleles per locus is higher in our Zimbabwe sample than in the other populations surveyed. A similar nonparametrical test to isolate the source of the differences in the number of private alleles among populations is not available. However, Zimbabwe clearly has more private alleles than do the other populations surveyed (see Figure 2).

D. simulans population structure: Table 3 is a matrix of pairwise F_ST values between each of the populations. Although there is no clear trend across all loci, for the average of loci as in this table we see more genetic differentiation between Ecuador and the Florida and California populations than between Zimbabwe and the Florida and California populations. Interestingly, a higher average value of F_ST is found for loci between the Florida and California populations than in a comparison of the North American populations and Zimbabwe.

For the microsatellites surveyed in our study that were identified in D. melanogaster, the average for polymorphic loci is 0.142 (SD = 0.031). This is significantly different from zero in an allelic permutation analysis (P < 0.001) and gives a calculated F_ST value of 0.158 (see Table 1). F_ST for each locus ranges from 0 to 0.587. Similarly, for our survey of D. simulans-derived microsatellites the average statistic is = 0.137, SD = 0.021, also significantly different from zero (P < 0.001) and F_ST = 0.151 (see Table 2). F_ST for each locus for this set of markers ranges from 0.012 to 0.478. The 95% bootstrap confidence interval of for the 18 unmapped D. simulans microsatellites is completely contained within that of the microsatellites identified in D. melanogaster (GenBank microsatellites 0.085 to 0.200 compared to 0.100 to 0.180 for D. simulans-derived microsatellites), and the means differ by less than 1%.

	DISCUSSION

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

Variability of microsatellites in D. simulans:
To assess levels of microsatellite variability in D. simulans, we conducted a survey of PCR product lengths at 34 loci. For 16 of these microsatellites, which were identified from D. melanogaster sequences in GenBank (WETTERSTRAND 1997 ), the expected heterozygosity and variance in repeat number detected in our survey of D. simulans are significantly less than the variability found in a similar survey of the homologous microsatellite loci in D. melanogaster (see Figure 2 and Figure 3; paired sign test, P = 0.021 for heterozygosity and P = 0.021 for variance in repeat number; D. melanogaster data from WETTERSTRAND 1997 ). In contrast, D. melanogaster and D. simulans expected heterozygosities and average variance in repeat number are not significantly different from each other (Mann Whitney U = 45, P = 0.064, and U = 53, P = 0.150, respectively) when assaying the same types of microsatellites (e.g., dinucleotide repeats) in the species in which they were identified (i.e., when one compares D. simulans-derived dinucleotide microsatellites surveyed in D. simulans to D. melanogaster-derived dinucleotide microsatellites surveyed in D. melanogaster levels of variability are similar; we compared only the D. simulans data from Zimbabwe, Ecuador, and Florida to the D. melanogaster data from Zimbabwe, Ecuador, and Florida). This is consistent with the ascertainment bias hypothesis regarding the choice of microsatellite loci to be surveyed (ELLEGREN et al. 1997 ). A separate investigation of this issue in D. simulans and D. melanogaster will be reported elsewhere (HUTTER et al. 1998 ).

View larger version (20K): In this window In a new window Download PPT slide   Figure 3. Microsatellite variability in D. melanogaster from Zimbabwe, Ecuador, Florida, China, and Australia (data from WETTERSTRAND 1997 ). (A) Average expected heterozygosity per locus. (B) Average variance in repeat number. (C) Average number of alleles per locus. (D) Private alleles. Numbers in parentheses are the average values for nine dinucleotides only.

Patterns of locus-specific variability:
A recent study of microsatellite variation in natural populations of D. melanogaster shows that microsatellites may be influenced by the effects of selection acting on linked sites (SCHLOTTERER et al. 1997 ), leading to a reduction in variation at the microsatellite locus. We have seen this pattern as well in our surveys of microsatellite variation in D. simulans. Two microsatellite markers (DROFASI and DROSEV1) are completely fixed for one allele size for our Florida sample, while remaining variable in other populations. In addition, one locus (DMPROSPER) is fixed in the Ecuador population and highly variable in three other populations (heterozygosities at the locus are 0.508, 0.337, and 0.268, for Zimbabwe, California, and Florida, respectively). Adaptive substitutions closely linked to the microsatellite loci may be responsible for these patterns. Variability is especially low near the achaete-scute region of D. simulans where no variation is seen at microsatellite DROACS2 across all four populations. This microsatellite is in the 5' flanking region of the scute gene, and the reduced level of microsatellite variation is consistent with the reduced nucleotide sequence variation found in this region near the tip of the X chromosome (BEGUN and AQUADRO 1991 ). Further analysis of the region surrounding these microsatellites is needed to determine whether adaptive fixation (e.g., BEGUN and AQUADRO 1991 ) or background selection (CHARLESWORTH et al. 1993 ) account for these low levels of variation.

Population structuring and genetic differentiation:
Surveys of D. melanogaster-derived and D. simulans-derived microsatellites in D. simulans yield roughly equivalent F_ST between the Zimbabwe, Ecuador, Florida, and California population samples. F_ST is moderate among the four D. simulans populations overall (mean = 0.136), and not significantly different (Table 4; Wilcoxon rank sum test, P = 0.256) from the F_ST found for a similar microsatellite survey in D. melanogaster (mean = 0.105). Our calculations of F_ST in D. simulans do not differ significantly between D. melanogaster-derived and D. simulans-derived microsatellites, while average heterozygosity differs by 36% between the two surveys overall.

Unlike similar surveys of allozymes, our surveys of microsatellites in D. simulans (this study) and in D. melanogaster (WETTERSTRAND 1997 ) do not show significant differences between the species for their overall level of differentiation. As a comparison to the spatial structure detected for allozymes, in Table 4 we have summarized the average F_ST values for the microsatellite markers on each chromosome. Differences in the levels of population structure would not be expected between D. simulans chromosomes a priori because inversion polymorphisms are not common for the species (LEMEUNIER and AULARD 1992 ). However, the X and second chromosomes are the main chromosomes where allozyme differentiation in D. simulans is markedly lower than for D. melanogaster (SINGH 1989 ; Table 3 from CHOUDHARY and SINGH 1987 ). Microsatellite F_ST values for any one of the chromosomes, or for all loci pooled together are not significantly different between the species (Wilcoxon rank sum test; see Table 4).

Partitioning of variation among D. simulans populations:
Levels of variability vary widely among populations of D. simulans. Having fewer alleles per locus and fewer private alleles in our New World D. simulans samples suggests that founder effects may have occurred during the spread of D. simulans populations into the New World (LACHAISE et al. 1988 ).

A decrease in the average number of alleles per locus with less of an effect on average heterozygosity is consistent with theoretical and experimental studies of population bottlenecks (MARUYAMA and FUERST 1985 ; LEBERG 1992 ). MARUYAMA and FUERST 1985 predict that a population just having undergone a single bottleneck event should have an apparent deficiency in the number of alleles compared to its heterozygosity. LEBERG 1992 demonstrated empirically that a reduction in the number of alleles per locus is a more sensitive indicator of a postbottleneck population than is the multiple-locus heterozygosity. The deficit in the number of alleles is mainly expected due to the absence of alleles expected to appear only once or twice in a sample and could be formulated as an excess in heterozygosity, given the number of alleles observed. However, when the population bottleneck is followed by rapid population growth (MARUYAMA and FUERST 1985 ) an apparent excess in the number of alleles (or deficiency of heterozygosity) should be observed.

To further investigate whether founder effects may have occurred during the colonization of New World habitats by D. simulans, we used the program BOTTLENECK (CORNUET and LUIKART 1996 ; PIRY et al. 1996 ) to implement three tests for an excess of heterozygosity in our D. simulans data when compared to the number of alleles observed. This is essentially the equivalent of testing for a deficiency in the number of alleles observed, given the heterozygosity expected from microsatellite allele frequencies. The results of these tests in Table 5 are consistent with a historically recent reduction in size for New World populations of D. simulans under the infinite alleles model, but results do not show a significant deviation from the expectation in these populations under the stepwise mutation model. We could interpret this to mean that the microsatellites in our survey follow the stepwise mutation model in New World populations and that there has been a rapid expansion of the Zimbabwe population (or some other reason for an excess of rare alleles such as recent migration, or that the alleles are being maintained at low frequencies because they are slightly deleterious). However, given the distribution of private alleles among D. simulans populations and our knowledge of the biogeography the species subgroup, we are led to favor the interpretation that the data may more closely fit the infinite alleles model and that founder effects occurred during colonization of New World habitats by D. simulans.

Also interesting are the average F_ST values for the four D. simulans populations surveyed as summarized in Table 3. The level of differentiation found between Ecuador and Florida is highest among pairwise comparisons of differentiation including comparisons between Zimbabwe and Ecuador or Zimbabwe and either North American population. One logical way to interpret these data is to infer that the Ecuador population was founded earlier than the Florida and California populations as a separate occurrence rather than as a sequential founding of South, then North America.

Implications of our study for understanding the demographies of D. simulans and D. melanogaster:
Several aspects of the microsatellite, allozyme, and nucleotide variation suggest complex historical differences between these species. The primary goal of this effort was to understand the levels of population subdivision within D. simulans. A related motivation for surveying microsatellites was to assess species-effective population size, as this is also useful in interpreting the demography of this species. In Table 6, we have summarized the results of several comparisons of variability and differentiation for D. simulans and D. melanogaster. Summary tables of this sort are difficult to compile due the peculiarities of each study, and it has not been altogether possible to limit the comparisons to surveys which included samples from geographically similar locations in each species. Viewed in a qualitative sense, however, some meaningful conclusions can be drawn.

Assuming that microsatellite alleles are selectively neutral or nearly neutral, one would expect microsatellite variability to be greater in a species with a larger effective population size. Surveys of nucleotide polymorphisms have suggested that the population size of D. simulans has remained large for a significant period of time, and the inferred effective population size of this species being on average two- to threefold higher than for D. melanogaster (AQUADRO et al. 1988 ; AQUADRO 1992 ; BEGUN and AQUADRO 1995 ; MORIYAMA and POWELL 1996 ).

We have compared the levels of microsatellites variability for D. simulans and D. melanogaster using the measures of both heterozygosity and variance in repeat number. For the most equitable comparison permitted by our analysis (a comparison of just dinucleotide repeats surveyed in the species from which they were identified, assaying similar populations), we do not see a significant difference in the level of variability between these species (see Table 6). There is small (though nonsignificant) trend for variability to be higher in D. melanogaster than in D. simulans. There is also a significant difference in the average number of alleles per locus, with D. melanogaster having more alleles on average than D. simulans. However, much of this difference results from the deficit of alleles among New World populations D. simulans as described above. While we do not yet know the significance of these findings, they seem inconsistent with a larger effective population size in D. simulans relative to D. melanogaster, equal mutation rates in the species, and/or strict neutrality of microsatellites. One possibility is a lower mutation rate in D. simulans; however, additional studies are needed to determine this directly. Also, it is worth noting that if we compare just African populations of the two species, there is no difference in the level of nucleotide variability () in the introns of the vermilion gene (see Table 6). This is interesting because the Zimbabwe is the only population from our sample predicted to be at migration-drift equilibrium. Among the New World populations of D. simulans, variability seems to be higher than D. melanogaster in single nucleotide polymorphisms yet lower for microsatellite variability. The reasons for this discrepancy in the direction of the difference in these populations for nucleotide variability and microsatellite remains to be explored. But there may be differences in the rate of the introduction or loss of new microsatellite or single nucleotide polymorphisms under the varying demographic parameters that are suggested from the current analysis in D. simulans. An important test will be to determine the impact of regional rates of recombination with respect to the variability at these microsatellites in D. simulans.

The distribution of private alleles among populations of D. simulans is most striking in comparison to that for D. melanogaster. In contrast to our finding that private alleles for D. simulans are scarce outside of Africa (Figure 2), private alleles in D. melanogaster populations are distributed more uniformly among populations (WETTERSTRAND 1997 ; see Figure 3). This suggests D. simulans colonized its current species range more recently than did D. melanogaster. Based on the assumption that variation within newly colonized areas represents a subset of variation segregating in more ancestral populations, and that each unique allele arises by an independent mutation, we estimate that D. simulans populations have had much less time than even D. melanogaster for mutations (private alleles) to arise since colonization of the New World. This hypothesis is consistent with theoretical and empirical studies of population bottlenecks and is supported by few rare alleles among New World populations of D. simulans. If such a process has also occurred in D. melanogaster, it appears that enough time has elapsed to allow recovery of rare variants among D. melanogaster New World populations. However, if the mutation in D. simulans were lower as suggested above, recovery of private alleles after a founding event would be slower.

Studies of allozyme, morphological, and behavioral traits have revealed less differentiation in D. simulans compared to D. melanogaster, and allozyme clines are much less pronounced in D. simulans than in D. melanogaster. Allozyme differentiation data for geographically similar populations from each species are summarized in Table 6. There is a significant difference in the level of allozyme differentiation but not for microsatellites. Given that microsatellites might be expected to evolve closer to neutrality, these data may indicate that a sufficient amount of time has not passed for selection to become apparent in D. simulans. However, these patterns could also result from lack of genetic heterogeneity within which such clines are ultimately selected. Colonization of much of the current D. simulans species range may have occurred from a source lacking spatial substructure, or simply may have occurred too recently for the type of selection that has modified the genetic architecture of D. melanogaster to be effective in D. simulans. To test between these hypotheses, and further understand the contribution of genetic differentiation to the colonization history of each species, it will be necessary to analyze genetic variation in populations that are believed to be more closely linked to founding D. simulans and D. melanogaster populations and to look for evidence of genetic differentiation among them. More extensive sampling is needed especially in D. simulans to truly get a picture of what differentiation has occurred within this species and to understand the changes that may have occurred during worldwide colonization. Our results do suggest, however, that there have been some significant historical differences in the demography of each species.

	ACKNOWLEDGMENTS

The work was supported by National Institutes of Health (NIH) grant GM36431 to C.F.A., an NIH predoctoral fellowship to S.D.I. and a Howard Hughes predoctoral fellowship to C.M.H. We thank all the members of the Aquadro lab for their help during preparation of this manuscript, two anonymous reviewers, and Andrew G. Clark for their constructive criticisms that have helped to improve the work. We are specifically indebted to Martha Hamblin for discussion of key issues.

Manuscript received March 18, 1998; Accepted for publication July 10, 1998.

	APPENDIX 1

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

	LITERATURE CITED

TOP ABSTRACT MATERIALS AND METHODS RESULTS DISCUSSION APPENDIX 1 LITERATURE CITED

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