*Centre d'Ecologie Fonctionnelle et EvolutiveCentre National de la Recherche Scientifique, Montpellier, France;
and
Modélisation et Biologie Evolutive, URLBINRA, Montpellier, France
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Abstract |
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Introduction |
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Microsatellite alleles generally refer to DNA fragments of different sizes (electromorphs) revealed by classical electrophoretic methods. Electromorphs are identical in state (i.e., have identical sizes) but are not necessarily identical by descent. A fraction of this homoplasy may be uncovered because a given electromorph may hide different sequences. This corresponds to the molecularly observable fraction of size homoplasy and will hereinafter be referred to as size homoplasy. Compound or interrupted microsatellite loci, or loci showing variation in their flanking regions, constitute favorable situations for the detection of size homoplasy (Estoup et al. 1995
; Garza and Freimer 1996
; Grimaldi and Crouau-Roy 1997
). It is worth noting that an unknown part of homoplasy at such microsatellite loci remains concealed, because even identical sequences may not be identical by descent. The few empirical studies which attempted to assess the effect of size homoplasy on population genetics parameters suggest that uncovering size homoplasy may substantially affect the estimation of several of these parameters (Estoup et al. 1995
; Viard et al. 1998
). However, these studies were limited in the number of individuals analyzed because detection of size homoplasy was based on cloning and sequencing of electromorphs. In this context, a proper population genetics study should make use of a method allowing (1) the ability to distinguish between electromorphs and sequences and (2) to analysis of a sufficiently large number of individuals per population (ca. 1530) at a low cost in both time and money. The single-strand conformation polymorphism (SSCP; Orita et al. 1989
) method has these qualities. It relies on the ability of a single nucleotide change to alter the electrophoretic mobility of pieces of DNA and allows analysis of both copies of a given gene for a given individual. SSCP variants will be referred to as conformers. Orti, Pearse, and Avise (1997)
showed that the SSCP technique can be used for detecting mutations along the flanking regions and for assessing size convergence at a microsatellite locus. However, these authors used a pure-repeat locus and hence could not detect size homoplasy occurring in the microsatellite core region, where most length variability arises. Moreover, they were not concerned with the effect of size homoplasy on population genetics parameters.
In this paper, we investigate the extent of microsatellite size homoplasy in natural populations of the selfing snail Bulinus truncatus using the SSCP method and evaluate its effects on the estimation of several population genetics parameters. Size homoplasy was studied at the compound microsatellite locus BT1 (Viard et al. 1996
). This locus was chosen for two reasons: (1) previous work based on sequencing revealed that electromorphs may hide several sequences (Viard et al. 1998
), and (2) length variation at this locus is relatively limited, and a given electromorph may be shared by several populations, allowing the possibility of substantial size homoplasy (Viard et al. 1996
; Viard, Justy, and Jarne 1997
). The SSCP screening was performed for 13 populations sampled over a large part of the distribution area of B. truncatus, and data analysis was conducted using some standard and more recent tools.
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Materials and Methods |
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Data analysis was conducted using either conformers or electromorphs, that is, considering or not considering the fraction of size homoplasy revealed by SSCP. The genetic variability within populations was estimated by counting the number of electromorphs or conformers and by computing the observed heterozygote frequency and gene diversity (Nei 1987
). An estimate of Wright's inbreeding coefficient Fis (
) was computed according to Weir and Cockerham (1984)
. This allowed the estimation of the mean population selfing rate (
) using the formula
= 2
/(1 +
) (Pollak 1987
). Exact tests were performed to test for genotypic linkage disequilibria between the BT1 locus and three other polymorphic loci (Viard, Justy, and Jarne 1997
) and for differentiation among pairs of populations. The significance of tests was adjusted using a sequential Bonferroni procedure (Rice 1989
). The estimator
of the parameter Fst was calculated following Weir and Cockerham (1984)
. For electromorphs, we also estimated
st, an analog of Fst under the SMM (Rousset 1996
), following Michalakis and Excoffier (1996)
. Fst and
st were estimated both over all populations and between pairs of populations. Data analysis was conducted using the Genepop package, version 3.1d (Raymond and Rousset 1995
).
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Results |
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Pairwise values computed from electromorphs and conformers are presented in figure 2
. Note again that they could not be computed on electromorphs for the six pairs of populations fixed for the same electromorph. When conformers were considered, those population pairs exhibited
values ranging between 0.172 and 1.000.
values were higher for conformers than for electromorphs for 31 pairs of populations, while the reverse was found for 22 pairs and identical values were obtained for 19 pairs.
values were higher for conformers than for electromorphs when populations shared identical electromorphs corresponding to different conformers. For instance, Lampsar and Bala were almost fixed for the same electromorph hiding different conformers (fig. 1
):
increased from 0.069 to 0.906. On the other hand, the detection of size homoplasy for electromorphs not shared among populations resulted in a decrease in
values. For example, a decrease from 0.967 to 0.670 was observed for Arbatache and Tera D. Despite the change in many pairwise
values,
values computed over all populations using electromorph or conformer data were very similar (0.70 and 0.68, respectively). Finally, the
st value computed over all populations using electromorph variation was similar to the previous
values (0.75).
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Discussion |
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What are the consequences of size homoplasy on within-population structure? Previous studies suggested that size homoplasy reduces the number of alleles per population, the gene diversity, and the observed heterozygote frequency (e.g., Estoup et al. 1995
; Garza and Freimer 1996
; Angers and Bernatchez 1997
; Viard et al. 1998
; Taylor, Sanny, and Breden 1999
). This was confirmed here in a population context. The SSCP method allows the uncovering of a concealed part of diversity, hence producing some more accurate estimates of intrapopulational diversity parameters. An interesting result is that heterozygote frequencies remained unchanged, while gene diversity increased considerably. As a consequence, estimates of Fisand therefore of the selfing ratesubstantially increased in three populations. This result is unexpected, since the Fis-based method used here to infer the selfing rate has been shown to be robust to mutation model and rate (Rousset 1996
), so size homoplasy is not expected to downwardly bias estimates of selfing rates in a population at mutation-drift-migration equilibrium. A possible situation that may lead to heterozygote deficiencies is the mixture of sampled individuals originating from differentiated subgroups (i.e., the "Walhund effect"). The ability to detect a Walhund effect is expected to increase with the level of polymorphism of the markers. This may explain why a larger amount of heterozygote deficiency was detected with conformers than with electromorphs. In agreement with this, significant genotypic linkage disequilibria were detected with conformers but not with electromorphs in Tera D and, to a lesser extent, in Bouktra.
Size homoplasy affects our perception of the distribution of variability among populations. Viard, Justy, and Jarne (1997)
showed little heterogeneity in the distribution of BT1 electromorphs at a spatial scale lower than a few hundred kilometers. The present study clearly shows more heterogeneity when conformers are considered. This pattern is more similar to the one observed at more polymorphic microsatellite loci (Viard, Justy, and Jarne 1997
). Additional variability detected by SSCP resulted in significant differentiation between all pairs of populations with conformers, while only 75% of tests were significant with electromorphs. A possible reason is that higher levels of polymorphism increase the power of exact tests of population differentiation (Rousset and Raymond 1997
). This was previously observed when microsatellite loci in B. truncatus (Viard, Justy, and Jarne 1997
) were studied and when categories of markers with different levels of polymorphism were compared (e.g., microsatellites vs. allozymes, as in Estoup et al. 1998
).
Quantification of population structure using Fst indicated that uncovering size homoplasy may increase or decrease population differentiation, as both within- and among-population diversity influence estimates of population structure. The detection of size homoplasy does indeed increase the observed diversity among populations when populations share identical electromorphs corresponding to different conformers, while it increases within-population diversity when electromorphs not shared among populations hide several conformers. In any case, identity-based parameters of population structure estimated on conformers are likely to be more accurate than those calculated on electromorphs, as the number of allelic states is higher (Estoup and Angers 1998
).
Size homoplasy leads to underestimation of genetic diversity within populations and differentiation among populations. Its effects are expected to be more marked for loci displaying low variability and for which a large fraction of electromorphs are shared among highly structured populations, as observed here. However, size homoplasy similarly affects diversity both within and among populations. As a consequence, values (or estimates of
st) computed over all populations based on electromorphs and conformers are very similar. A general conclusion of our work is that detection of size homoplasy does not invariably produce higher estimates of population structure, contrary to what is sometimes asserted (e.g., Taylor, Sanny, and Breden 1999
). This conclusion is consistent with the prediction, based on theoretical analyses, that size homoplasy in general should not lead to stronger population structure (Rousset 1996
).
Two intriguing molecular results have to be highlighted because they may be relevant not only to the question of size homoplasy, but also to that of the mutation process at microsatellite loci. The first point bears on the variability of the microsatellite arrays studied. The BT1 locus has a GTnCTm core sequence, with n varying from 9 to 13 and m varying from 2 to 5 for the conformers studied. That n varies is expected, given that pure repeats longer than about 10 units are generally variable (Weber 1990
; reviewed in Estoup and Angers 1998
). On the other hand, that m shows a level of variation similar to that of n is surprising, given its low value. Variation in the number of repeats at short microsatellite stretches has been reported when orthologous loci have been compared across species (Messier, Li, and Stewart 1996
; Primmer and Ellegren 1998
; Taylor, Durkin, and Breden 1999
), but not within species (Estoup et al. 1995
), and even less within populations. Moreover, analyses conducted on large numbers of microsatellite loci extracted from DNA databases have indicated that dynamic mutation occurs for an array larger than four repeats (Jurka and Pethiyagoda 1995
; Rose and Falush 1998
). Mutation rates for very short stretches of repeats are probably very low. For instance, the average mutation rate for short microsatellites in Drosophila is about 5 x 10-6 (Schug, Mackay, and Aquadro 1997
). A possible explanation for our results is that conformers represent very ancient lineages, but this seems unlikely given the absence of variation in the regions flanking the core sequence. Alternatively, the variability of consecutive arrays may be higher than if they were considered independently, as already suggested by Metzgar et al. (1998)
. The second point relates to the conformer diversity detected within some populations and between related populations. Size homoplasy was reported in four populations (fig. 1
). The pattern observed in Tera D is puzzling, since there were three conformers for electromorph 184, and no additional electromorph. Genetic drift, which would have maintained electromorph 184 only, cannot be ruled out as an explanation for this result. However, electromorph 186 has not been reported in the vicinity of this population and is found only 200 km southeast of this area (Viard, Justy, and Jarne 1997
). Moreover, electromorph 182 has never been reported in B. truncatus.
Altogether, these two points seem incompatible with a simple SMM, since this model assumes that mutation at locus BT1 should proceed through the addition/deletion of a single CT or GT repeat at a time. We propose two hypothetical mechanisms that may explain the pattern observed here and, more generally, some patterns of variation at compound dinucleotide loci. Let us assume a locus with a GTnCTm core sequence, as in the present study. Under the first mechanism, a point mutation at the boundary between the GT stretch and the CT stretch may produce a new allele within the same electromorph. However, this requires a GC transversion mutation, which is known to occur at a low rate in most genomes. A similar mechanism based on the more frequent G
A transition may explain homoplasious variation at other compound microsatellites (e.g., GTnATm loci). The second mechanism is based on the simultaneous occurrence (through slippage) of single-repeat-unit mutations in both arrays, for example, a deletion within the GT stretch and an addition within the CT stretch. Such a pattern has never been documented but is suggested by figure 2B
in Levinson and Gutman (1987)
. Such a process would go undetected in pure loci. This second mechanism implies nonindependence in the mutation process of the two (or more) parts of a compound microsatellite (see also Metzgar et al. 1998
). It is worth mentioning that this mechanism would result in a higher rate of size homoplasy than that under the standard SMM. Only intensive SSCP and/or sequencing programs could provide the empirical data needed to detail such a mechanism, since mutation would have to be looked for within electromorphs, and not among electromorphs, as is usually done.
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Acknowledgements |
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Footnotes |
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1 Present address: Department of Zoology and Entomology, University of Queensland, Queensland, Australia.
2 Keywords: microsatellites
SSCP
homoplasy
population structure
freshwater snails
3 Address for correspondence and reprints: B. Angers, Centre d'Ecologie Fonctionnelle et EvolutiveCentre National de la Recherche Scientifique, 1919 route de Mende, 34293 Montpellier cedex 5, France. E-mail: angers{at}cefe.cnrs-mop.fr
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