Microsatellite Variability Differs Between Dinucleotide Repeat Motifs—Evidence from Drosophila melanogaster

Doris Bachtrog, Martin Agis, Marianne Imhof and Christian Schlötterer2,

Institut für Tierzucht und Genetik, Vienna, Austria

Abstract

Recently, the use of microsatellites as genetic markers has become very popular. While their evolutionary dynamics are not yet fully understood, the emerging picture is that several factors are influencing microsatellite mutation rates. Recent experiments demonstrated a significant effect of repeat motif length on microsatellite mutation rates. Here, we studied the influence of the base composition of the microsatellite. Forty-two microsatellite loci on the second chromosome with the three most abundant dinucleotide repeat motifs (TC/AG, AT/TA, GT/CA) were characterized for six different Drosophila melanogaster populations. Applying ANOVA to the variance in repeat number, we found a significant influence of repeat motif on microsatellite variability. Calculating relative mutation rates, GT/CA appears to have the highest mutation rate, and AT/TA appears to have the lowest. Similar differences in mutation rates were obtained by an alternative method which estimates microsatellite mutation rates from their genomic length distribution.

Introduction

Microsatellites are a special class of tandemly repeated DNA that is widely distributed in eukaryotic genomes. Their high variability has made microsatellites the marker of choice for many applications in life sciences, including linkage analysis (Dib et al. 1996Citation ), behavioral ecology (Schlötterer and Pemberton 1998Citation ), population genetics (Goldstein and Schlötterer 1999Citation ), and phylogeny reconstruction (Harr et al. 1998aCitation ).

Despite the widespread use of microsatellites, their evolutionary dynamics are still poorly understood. The predominant mutation mechanism of microsatellites is DNA replication slippage. Although molecular details of this mechanism are still uncertain, it is assumed that the gain/loss of repeat units in a microsatellite is caused by strand displacement of the nascent DNA strand followed by an out-of-register pairing (Levinson and Gutman 1987bCitation ; Tautz and Schlötterer 1994Citation ). Direct observations of microsatellite mutations in pedigrees (Weber and Wong 1993Citation ), as well as experimental data from Escherichia coli (Levinson and Gutman 1987aCitation ) and yeast (Henderson and Petes 1992Citation ), indicated that the most common microsatellite mutation encompasses one or a few repeats only. The distribution of repeat sizes in natural populations is also largely consistent with this stepwise mutation model (Di Rienzo et al. 1994Citation ).

An important observation was that mutation rates differ between loci (Harr et al. 1998bCitation ). Several other parameters which may influence microsatellite mutation rates have also been considered. One of the best studied parameters is the number of repeats. For a variety of organisms, it has been shown that microsatellite variability is positively correlated with repeat number (Jin et al. 1996Citation ; Wierdl, Dominska, and Petes 1997Citation ; Schlötterer et al. 1998Citation ; Schug et al. 1998bCitation ). More controversial is the influence of the repeat motif length on the mutation rate. An initial survey of di- and tetranucleotide repeats observed higher mutation rates for tetranucleotide repeats (Weber and Wong 1993Citation ). Later studies could not confirm this result, but found an inverse relationship between repeat motif length and microsatellite mutation rates (Chakraborty et al. 1997Citation ; Kruglyak et al. 1998Citation ; Schug et al. 1998bCitation ). A recent report accounted for the influence of repeat number by comparing the mutation rate of di- and tetranucleotide microsatellites with the same repeat number (Lee et al. 1999Citation ). The observation of a higher mutation rate of dinucleotide repeats is consistent with the results of Chakraborty et al. (1997)Citation . Apart from repeat number and repeat type, additional factors potentially influence microsatellite mutation rates, such as flanking sequence, chromosomal location, and base substitutions in the microsatellite array (Goldstein and Clark 1995Citation ; Harr et al. 1998bCitation ).

Here, we concentrate on the base composition of a repeat motif as a factor influencing microsatellite mutation rates. Forty-two loci of the three most abundant dinucleotide microsatellite motifs (TC/AG, AT/TA, and GT/CA) were characterized in natural Drosophila melanogaster populations, and significant differences between the three repeat motifs were detected.

Materials and Methods

Population Samples
Six different populations of D. melanogaster were used for microsatellite typing: Moscow, Russia (30 lines), Pedevilla, Italy (30 lines), Kenya (23 lines), Texel, the Netherlands (30 lines), Nussdorf, Austria (29 lines), and Prunay, France (30 lines). The African flies were provided from the Species Stock Center (Bowling Green) and have been propagated in the laboratory as isofemale lines at small population sizes; therefore, most individuals were homozygous. For heterozygous individuals, one allele was randomly discarded before data analysis. All other populations were collected in 1997, each population on the same day, and both chromosomes were analyzed from F1 individuals. Genomic DNA was prepared from single flies using a high-salt extraction method (Miller, Dykes, and Polesky 1988Citation ).

Selection of Microsatellites
Forty-two dinucleotide microsatellites were obtained from the Drosophila genome project web page (http://fruitfly.berkeley.edu/sequence/drosophila-regions.html). To account for potential differences in microsatellite mutation rate caused by position-specific effects (e.g., recombination rate) or differences in repeat count, we selected contiguous sequences on the basis of two criteria: (1) a suitable microsatellite of all three abundant dinucleotide repeat motifs had to be present, and (2) the number of repeats of the microsatellite had to be within a similar range (between 7 and 12 repeats). PCR primers were designed to amplify products of 100–200 nt (table 1 ).


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Table 1 Microsatellite Loci

 
Microsatellite Analyses
Microsatellite typing followed standard protocols (Schlötterer 1998Citation ). In brief, end-labeled (32P) PCR primers were used in a 10-µl reaction volume (1.5 mM MgCl2, 200 µM dNTP's, 1 µM of each primer, 50–100 ng template DNA, and 0.5 U Taq polymerase). Initial denaturation for 4 min at 94°C was followed by 30 cycles of 1 min at 94°C, 1 min at 46–57°C (depending on the primer combination; see table 1 ), and 1 min at 72°C. We used a final extension at 72°C for 45 min to assure a quantitative terminal transferase activity of the Taq polymerase. PCR products were separated on a 7% denaturing polyacrylamide gel (32% formamide, 5.6 M urea). PCR products were sized by running a sizing ladder next to the amplified microsatellites (Schlötterer and Zangerl 1999Citation ). Repeat numbers were estimated by subtracting the flanking region from the PCR product size and dividing the length of the microsatellite by the repeat motif size. After applying this calculation, a small number of alleles had negative repeat numbers. These 26 alleles were not included in the analysis.

Data Analyses
Genetic Variability
Number of alleles, heterozygosity, and variance in repeat number were determined for each locus and each population with the software package Microsat, version 1.5 (Minch et al. 1995Citation ). To account for small sample sizes, the heterozygosities obtained by Microsat 1.5 were multiplied by n/(n - 1), where n is the number of chromosomes typed.

Estimating Relative Mutation Rates
The variance in repeat number within a population can be described by the formula E() = (4Nµ){psi}'', where N is the effective population size, µ is the mutation rate, and {psi}'' is the variance of allele size change caused by each mutation. A two-way ANOVA on ln can be used to determine whether the variance in repeat number significantly depends on motif type or population. In the absence of a significant population effect, as well as no interaction between repeat motif and population, the logarithmic variance (ln ij) at the ith repeat motif type in the jth population has the expectation E(ln ij) = ln µi + ln Nj + const. Thus, the motif type specific average mutation rate can be determined up to a multiplicative constant. It should be noted that this method rests on several assumptions, such as selective neutrality of microsatellite variation, constant population sizes, absence of population subdivision, and independence of the analyzed populations. Furthermore, the mutation pattern (allele size change caused by individual mutations and its distribution) is assumed to be the same for all loci analyzed (Chakraborty et al. 1997Citation ; Chakraborty and Kimmel 1999Citation ). To account for the influence of repeat number on microsatellite variability, we standardized the data by dividing the observed variance in repeat number at each locus by its mean repeat number. The ratio of the standardized means was used to calculate the relative mutation rates of the three abundant dinucleotide repeat motifs.

To test whether repeat motif had a significant effect on ln , we followed the ANOVA-based approach outlined by Chakraborty et al. (1997)Citation . As already noted in earlier studies (Goldstein et al. 1996Citation ; Harr et al. 1998bCitation ), ln followed a normal distribution in our data set. Bartlett's test was carried out to test for homogeneity of variances (Sokal and Rohlf 1995, 396 pp.). To consider the well-described correlation between repeat number and microsatellite variability, we used the mean repeat number as a covariate in the ANOVA model.

Results

All measures of variability, number of alleles, heterozygosity, and variance in repeat number, vary across the 42 microsatellite loci studied (table 2 ). The mean heterozygosity was 0.49 and the mean variance in repeat number was 1.98. Our data set contained one population from East Africa, believed to be the origin of D. melanogaster, and five European populations. Consistent with previous reports based on nucleotide polymorphisms (Begun and Aquadro 1993Citation ), we found a higher variability in the African population than in the non-African populations. Heterozygosity was on average 30% higher in the African population, variance in repeat number was on average 52% higher, and number of alleles was 13% higher (tables 2 and 3 ). European populations had low, but significant, Fst values (Fst = 0.034, P < 0.0001). More detailed analyses will be presented elsewhere.


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Table 2 Measurements of Microsatellite Variability and Repeat Count

 

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Table 3 Microsatellite Variability in the Analyzed Populations

 
Repeat Count and Variability
The mean number of repeats in our data set was 8.85 (table 1 ), which is more than two repeats higher than the average repeat number of D. melanogaster microsatellites (Bachtrog et al. 1999Citation ). Despite the fact that all microsatellite loci were chosen to have similar repeat numbers, we detected differences in mean repeat number of up to 8.8 repeats. The number of repeats is one of the best-documented parameters influencing microsatellite mutation rates. Thus, we were interested to what extent the differences in repeat number contribute to the observed differences in microsatellite variability. We used different measurements of repeat number to test for a correlation with microsatellite variability. The mean number of repeats is expected to be the best measurement if microsatellite variability increases linearly with repeat number. Previous studies, however, showed that the maximum repeat number was more strongly correlated with variability (Goldstein and Clark 1995Citation ; Schug et al. 1998bCitation ). Because the maximum repeat number is a population estimator which is highly sensitive to sampling errors, we also used the 75th percentile. All measurements of microsatellite length were found to be positively correlated with heterozygosity and variance in repeat number (table 4 ). The strongest correlation was obtained with the maximum repeat number, followed by the 75th percentile and the mean repeat number.


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Table 4 Correlation Coefficients Between Microsatellite Length and Variability

 
Microsatellite Variability Differs Between Repeat Motifs
Because repeat number has a significant effect on microsatellite variability, any comparison of mutation rates needs to account for differences in repeat numbers. We compared the mean and maximum repeat numbers between repeat motifs and observed a significant difference for both (P = 0.0001 and P = 0.0003 for the latter; Kruskal-Wallis). To test whether motif type had a significant effect, we extended the ANOVA-based approach of Chakraborty et al. (1997)Citation . In a two-way ANOVA with ln as dependent variable and population and motif type as factors, we accounted for differences in repeat number by including mean repeat number as a covariate. Table 5 shows the summary results of our analysis. A substantial fraction of the variance in was explained by the covariate (repeat number). The component of variation due to population differences was not significant (P > 0.1). The interaction component was also not significant. However, motif type had a significant effect on the variance of ln (P = 0.008). We repeated the analysis excluding the African population with similar results (table 6) .


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Table 5 Two-Way ANOVA on ln {} in Repeat Number (including Africa), Including Repeat Number as Covariate

 

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Table 6 Two-Way ANOVA on ln {} in Repeat Number (European populations only), Including Repeat Number as Covariate

 
The absence of significant population and interaction effects permits the determination of the relative mutation rates. From the observed variance in repeat number, which was standardized for the number of repeats, we calculated the relative mutation rates. GT/CA microsatellites have a mutation rate 1.4 times (0.268/0.196) as high as that of TC/AG and 3.0 times (0.268/0.09) as high as that of AT/TA microsatellites (fig. 1 ).



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Fig. 1.—Observed variances in repeat number divided by the average repeat number for microsatellite loci, grouped by repeat motif. The vertical bars represent ±1 SE intervals

 
Flanking Region and Genetic Variability
A recent study demonstrated a lower variability for microsatellites with high GC contents in their flanking regions (Glenn et al. 1996Citation ). To test for the same phenomenon in our data set, we determined the GC content of 200 bp (100 bp on each side) adjacent to the microsatellite. No significant correlation between GC content and microsatellite variability was observed. However, the GC content was significantly lower around AT/TA microsatellites (41.0%) than around TC/GA (46.8%) and GT/CA (46.9%) (P < 0.05; Kruskal-Wallis).

Discussion

In this study, we tested whether the three most abundant dinucleotide microsatellites in D. melanogaster differ in their mutation rates. Because of background selection (Charlesworth, Morgan, and Charlesworth 1993Citation ) and selective sweeps (Kaplan, Hudson, and Langley 1989Citation ), the variability of DNA sequences is reduced in genomic regions of low recombination. While it is still unclear to what extent this effect also applies to microsatellites (Michalakis and Veuille 1996Citation ; Schlötterer, Vogl, and Tautz 1997Citation ; Schug et al. 1998aCitation ), we designed our experiment to minimize the influence of chromosomal position. Only those genomic regions that allowed us to select the same number of microsatellite loci of each repeat motif were used. Hence, positional effects could be disregarded in this study, although this phenomenon still needs further investigation.

The ANOVA on ln indicated that microsatellite mutation rates are influenced by the repeat motif. By taking the ratios of the variances in repeat number, we were able to estimate the relative mutation rates of the three different dinucleotide repeat motifs. GT/CA microsatellites had the highest mutation rate and AT microsatellites the lowest.

To further investigate the difference in microsatellite mutation rates, we used a recently published method that is not based on microsatellite variability in natural populations or directly observed mutations. The approach, introduced by Kruglyak et al. (1998)Citation , follows the rationale that the length distribution of microsatellites is dependent on the DNA slippage rate and the base substitution rate. For fixed substitution rates, higher slippage rates will result in longer microsatellites. Fitting the stationary distribution of uninterrupted microsatellite alleles to the model, the microsatellite mutation rate can be estimated. We used the data set from our recent survey of the distribution of dinucleotides in the D. melanogaster genome (Bachtrog et al. 1999Citation ) to estimate the mutation rates of the three different repeat motifs. Interestingly, the results obtained with this completely different approach yielded almost identical results. GT/CA repeats have the highest mutation rate (3.9 x 10-6), followed by TC/AG (3.4 x 10-6). The lowest mutation rate was observed for AT/TA microsatellites (2.1 x 10-6).

The consistency in the results of two completely different approaches is particularly important, as the ANOVA is based on the assumption of independence of the populations analyzed. All of the non-African populations were founded by a recent colonization event about 10,000 years ago (David and Capy 1988Citation ); therefore, they may not yet have reached mutation drift equilibrium. Furthermore, migration could also contribute to a nonindependence of D. melanogaster populations. Nevertheless, we obtained similar results with the method of Kruglyak et al. (1998)Citation , which does not rest on those assumptions. Therefore, our results of a different mutational behavior of dinucleotide repeat types are most likely not caused by a violation of the assumption of independence of the analyzed populations.

Sequence Dependence of the Mismatch Repair System
In vitro studies demonstrated that DNA slippage is an intrinsic property of simple-sequence DNA (microsatellites) (Schlötterer and Tautz 1992Citation ). These experiments, as well as S1 nuclease digests of a plasmid carrying a microsatellite, suggested that the primary slippage rate must be much higher than the frequency of observed microsatellite mutations (Hentschel 1982Citation ; Schlötterer and Tautz 1992Citation ). This discrepancy arises from the DNA mismatch repair system, which removes primary DNA slippage mutations with a high efficiency (Eisen 1999Citation ). Yeast cells lacking a functional mismatch repair system were found to have up to a 6,000-fold increase in microsatellite mutation rates (Sia et al. 1997Citation ). Provided that most primary DNA slippage events are repaired by the mismatch repair system, small differences in the efficiency of the enzymatic machinery to detect and remove slippage mutations could result in vastly different mutation rates. Earlier studies in yeast and E. coli showed that the mismatch repair systems in both organisms have some preferences. A systematic survey in yeast indicated that the efficiency of the mismatch repair system decreases with repeat motif length (Sia et al. 1997Citation ). However, the mutation rates of mono-, di-, and tetranucleotide repeats were similar in wild-type cells (Sia et al. 1997Citation ), confirming previous observations that primary slippage rates are negatively correlated with repeat motif length.

Our results suggest differences in mutation rates between the three dinucleotide repeats tested. If the mismatch repair system in D. melanogaster preferentially repairs primary DNA slippage events of a given repeat motif, this could explain the observed difference between repeat motifs. Most important, for the well-characterized mismatch repair system of E. coli, a sequence-specific ability to recognize mismatches has been demonstrated (Su et al. 1988Citation ). Hence, if the D. melanogaster mismatch system has a higher preference for mismatches/loops in AT-rich sequences, then those microsatellites should have the lowest mutation rate. Being that the D. melanogaster genome is AT-rich (Powell 1997), an adaptation of the mismatch repair system to AT mismatches could be selectively advantageous. In a genome with a higher AT content, mismatches/loops in an AT-rich region will be repaired more efficiently, thus reducing the mutational load.

Over evolutionary timescales, subtle differences in the mismatch repair system could lead to significant differences in the frequencies of different microsatellite repeats in the genome. It has been shown that the abundance of dinucleotide microsatellites differs between species. While in mammals and Drosophila, GT/CA is the most common dinucleotide, in plants, AT/TA dinucleotides are the most abundant (Langercrantz, Ellegren, and Andersson 1993Citation ); the most frequent dinucleotide in Caenorhabditis elegans is GA/CT (Schlötterer 2000Citation ). Apart from different motif specificities, variation in the mismatch repair system could also affect the average microsatellite length. The model by Kruglyak et al. (1998)Citation predicts that if modifications in the mismatch repair system cause a slightly higher microsatellite mutation rate, this would result in longer microsatellites. Such differences in microsatellite length have been detected between D. melanogaster and Drosophila virilis (Schlötterer and Harr, unpublished data), as well as between humans and chimpanzees (Rubinsztein et al. 1995Citation ; Cooper, Rubinsztein, and Amos 1998Citation ).

The Influence of the Primary Slippage Rate
DNA slippage requires the breaking of hydrogen bonds, which are formed between the two DNA strands. Thus, the null hypothesis would be that AT microsatellites have a higher slippage rate than GT/CA or GA/CT microsatellites. While in vitro experiments indicate such an overall trend (Schlötterer and Tautz 1992Citation ), our data show that mutation rates of AT/TA microsatellites are lower than those for GT/CA or GA/CT. Because our measurements of microsatellite variability are the outcome of primary slippage and DNA mismatch repair, further experiments are required to determine to what extent primary DNA slippage differs between loci.

The Influence of Flanking Sequences
One of the first hints that the flanking region may be involved in microsatellite mutation rates came from a study of alligator microsatellite loci (Glenn et al. 1996Citation ). In a survey of 14 microsatellite loci, Glenn et al. (1996)Citation detected a negative correlation between microsatellite variability and GC content in the flanking region. A later study on microsatellites in shrews, however, did not detect such an effect (Balloux et al. 1998Citation ). In our data set of 42 microsatellite loci, we determined the GC content of 200 bp adjacent to the microsatellite and did not detect a significant effect on microsatellite variability. Nevertheless, the absence of a significant correlation between GC content and microsatellite variability in our study as well as the report of Balloux et al. (1998)Citation does not necessarily imply that flanking sequences in general have no impact. In a systematic survey of a DNA stretch containing several mononucleotide microsatellites, the mutation frequencies of the different microsatellites were not found to be related in any simple way to repeat number or repeat sequence (Greene and Jinks-Robertson 1997Citation ). The authors concluded that the sequence context of the respective microsatellite has an important influence on the frequency of microsatellite mutations.

Influence of the Step Size
So far, we have assumed that the mutational process does not vary among loci. The most simple model of microsatellite evolution assumes that mutations occur in a strict stepwise manner, with each mutation encompassing only a single repeat unit. However, deviations from this simple model are well documented for a wide range of organisms, including humans (Di Rienzo et al. 1994, 1998Citation ), D. melanogaster (Schlötterer et al. 1998Citation ), yeast (Henderson and Petes 1992Citation ), and E. coli (Levinson and Gutman 1987aCitation ). If the distribution of mutations encompassing more than a single repeat unit differs between motifs, then this would also result in a significant effect of repeat motif on the variance of ln . Further studies are required to investigate the distribution of mutational step sizes to obtain a complete picture of the evolutionary dynamics of microsatellite DNA.

Acknowledgements

We are grateful to S. Kruglyak for calculating the relative mutation rates from the microsatellite length distribution. Anonymous reviewers provided helpful comments which significantly improved the manuscript. The Drosophila species stock center, J. David, and D. Slezak provided flies. Many thanks to S. Weiss and the members of the laboratory for helpful discussion and comments on the manuscript. This work is supported by a grant from the FWF to C.S.

Footnotes

Diethard Tautz, Reviewing Editor

1 Keywords: Drosophila melanogaster, microsatellite genome evolution mutation rates Back

2 Address for correspondence and reprints: Christian Schlötterer, Institut für Tierzucht und Genetik, Josef-Baumann Gasse 1, 1210 Wien, Austria. E-mail: christian.schloetterer{at}vu-wien.ac.at Back

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Accepted for publication May 2, 2000.