• genetic diversity;
  • serpentine;
  • hyperaccumulator;
  • Alyssum bertolonii;
  • chloroplast microsatellite


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
  • Chloroplast microsatellites (cpSSR) were used to analyze the patterns of genetic variation within and among populations of the serpentine endemic, Alyssum bertolonii .
  • Thirty-five different chloroplast haplotypes were identified in 90 plants sampled from nine populations originating from the four disjunct northern-Italian serpentine regions where the species is found.
  • High levels of genetic diversity were found within each of the populations sampled. Analysis of Molecular Variance (AMOVA) showed high degrees of differentiation among both different populations of the same serpentine region and different regions (Φ ST = 0.622, Φ CT = 0.252, respectively).
  • The results indicated that: each population was established by few founders and then subsequently differentiated the existing chloroplast haplotypes; each population is a distinct genetic entity; and populations within the same serpentine region are more related than populations from different regions.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Serpentine soils are distributed all over the world. They originate from an array of ultramafic rock types and are characterized by high levels of nickel, cobalt and chromium, low levels of N, P, K, Ca, and a high Mg : Ca ratio (Brooks, 1987). These chemical properties render serpentine soils uninhabitable by most plant species but also give them a major role in the evolution of endemic taxa (Pichi Sermolli, 1948; Kruckeberg, 1954; Kruckeberg & Kruckeberg, 1990). Serpentine soils are in fact considered as ‘ecological islands’ (Lefèbvre & Vernet, 1990) and the occurrence of plant species restricted to serpentine substrates was documented as long ago as the sixteenth century (Vergnano Gambi, 1992). Serpentine soils are particularly abundant in northern and central Italy (Abbate et al., 1980). In central Italy the flora of these outcrops is considered one of the most typical because it shows the highest number of endemics and peculiar forms, probably as a consequence of the minor influence of Pleistocene glaciations (Vergnano Gambi, 1992). Among the plants adapted to these soils, the so-called hyperaccumulators (Baker, 1981) are able to concentrate nickel in their above-ground parts to levels higher than 10 000 ppm on a d. wt basis. Alyssum bertolonii (Brassicaceae) is a diploid (2n = 16, Arrigoni et al., 1983) perennial plant, living exclusively on serpentine outcrops in central Italy, particularly Tuscany (Pignatti, 1997). A. bertolonii is one of the 14 European species of Alyssum that hyperaccumulate nickel (Brooks, 1978). It was the first plant species reported to do so (Vergnano Gambi, 1992). The species has been suggested to be a useful indicator plant in prospecting for nickel (Brooks, 1983). Recently, cultivars of Alyssum have been proposed for phytoremediation (Salt et al., 1998) and patented for phytomining practices (Chaney et al., 1998).

A few studies have investigated the population structure of serpentine endemic plants (Mayer et al., 1994; Wolf et al., 2000). These point to habitat fragmentation and genetic isolation of serpentine plant populations. In the serpentine endemic Calystegia collina, populations were found to be highly differentiated, even those within the same serpentine outcrop (Wolf et al., 2000). Up to now little is known about the genetic diversity and population structure of hyperaccumulating plants and in particular about the molecular biogeography of these species.

Chloroplast molecular markers have been extensively exploited in studies of plant genetic variability (Powell et al., 1995a). (Vendramin et al., 1999; 2000, Powell et al., 1995b; 1996, Provan et al., 1996; 1998, Echt et al., 1998; Mengoni et al., 2000a; 2001).

The aims of the present work were: to quantify the level of chloroplast diversity within population of the serpentine endemic A. bertolonii, to analyze its population structure in relation to the spatial distribution of serpentine outcrops, and to evaluate the number of different genetic pools present in this endemic species.

Materials and Methods

  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Plant material, DNA extraction, cpSSR identification and PCR conditions

Nine populations of A. bertolonii were sampled in four serpentine regions of central Italy (I, II, III, IV) (Fig. 1). The serpentine regions were as described by Abbate et al. (1980). In serpentine region II there was a strong geographic separation due to hills (Colline Metallifere, 600 m above sea level) between coastal and inland populations. The distance between each pair of populations was in the range 25–205 km. Ten plants per population were sampled.


Figure 1. The sampling sites of A. bertolonii . Solid squares represent the location of the sampled populations in the serpentine regions. The outcrops exposing the serpentine bedrock mainly occur at these sites, the remaining part of the serpentine region being covered by sediments of other origin. Roman numbers indicates the different serpentine regions (in grey). Region I: PO, Pomaia; RS, Rocca di Sillano; CO, Collesalvetti; LA, Larderello; MR, Monterufoli. Region II: IM, Impruneta; GA, Galceti. Region III: PS, Pieve Santo Stefano. Region IV: MP, Monte Prinzera.

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DNA was extracted from leaves and quantified as described by Mengoni et al. (2000b). PCR amplification reactions were performed in a 25-µl total volume containing 5 mM KCl, 1 mM Tris-HCl (pH 9.0), 0.1% Triton X-100, 2.5 mM MgCl2, 0.2 mM of each dNTP, 0.8 U of Taq DNA polymerase (Dynazyme II, Finnzyme, Espoo, Finland), 4 pmols of each primer, 10–25 ng of template DNA. The amplifications for the cpSSR haplotype definition were done in two separate multiplex reactions, one with primer pairs CCMP2, CCMP6 and CCMP10, the other one with primer pairs CCMP1 and CCMP7 (Weising & Gardner, 1999). Reactions were performed in a Perkin-Elmer 9600 thermal cycler (Perkin Elmer, Norwalk, CT, USA) programmed for an initial melting at 94°C for 5 min followed by 35 cycles at 94°C for 1 min, 50°C for 1 min (45°C for CCMP1 and CCMP7 primer pairs) and 72°C for 1 min. A final extension step at 72°C for 10 min was performed. Forward primers were labeled at the 5′ end with 6-FAM (6-carboxyfluorescein) for CCMP1, HEX (4,7,2′,4′,5′,7′-hexachloro-6-carboxyfluorescein) for CCMP2 and CCMP6, TET (4,7,2′,7′-tetrachloro-6-carboxyfluorescein) for CCMP7 and CCMP10. The amplification products of the two PCR reactions for each sample were mixed together and resolved in a Perkin-Elmer ABI 310 (PE Biosystems, Perkin Elmer, Norwalk, CT, USA) genetic analyzer by capillary electrophoresis. The capillary was filled with POP-4 (PE Biosystems, Perkin Elmer, Norwalk, CT, USA), and 3 µl of PCR product plus 0.5 µl of GenScan internal size standard TAMRA-500 (PE Biosystems, Perkin Elmer, Norwalk, CT, USA) were added to 11 µl of deionized formamide. Samples were denatured for 3 min at 95°C, chilled on ice, transferred into a sample tray, and injected at 15 KV for 3 s onto a 47-cm capillary and run at 15 kV for 30 min at 60°C. The data analysis was performed using ABI GenScan analysis software (PE Biosystems, Perkin Elmer, Norwalk, CT, USA) and size of the fragment was obtained by the comparison with an internal size standard (TAMRA-500, Perkin Elmer, Norwalk, CT, USA). The DNA fragments obtained from PCR amplification of single cpSSR loci were cloned into the pCR2.1 vector (Life Technologies-Invitrogen, Carlsbad, CA, USA) and sequenced using M13 universal primer with the BigDye system (Perkin Elmer, Norwalk, CT, USA) in a Perkin-Elmer ABI 310 genetic analyzer.

Data analysis

Values of genetic diversity within populations were computed following either the Infinite Allele Model (IAM, Kimura & Crow, 1964) or the Stepwise Mutational Model (SMM, Ohta & Kimura, 1973). For the IAM, the effective number of haplotypes (inline image) and the haplotypic diversity (inline image), were computed (where n is the number of individuals analyzed in a population and pi is the frequency of the i-th haplotype in the population, Nei, 1987). For the SMM, the inline image measure, which is based on the distance measure of Goldstein et al. (1995), applied to plastid microsatellites (Morgante et al., 1997), was calculated (inline image, where m is the number of cpSSR loci and a is the base-pair length of the marker at the cpSSR locus k in the i-th and j-th individuals). For this diversity measure the chloroplast genome is regarded as a single nonrecombining locus and repeat length differences between plants are summed over all cpSSR loci (Echt et al., 1998). Genetic differentiation among populations was estimated by the Analysis of Molecular Variance (AMOVA, Excoffier et al., 1992) using Arlequin software (ver. 2.000; Schneider et al., 2000) (University of Geneva, Geneva, Switzerland). This test allowed for estimation of variance components among individuals within populations, among populations within groups and among groups. Significance values were computed by a permutation test from 16000 permutated matrices. The AMOVA was based on distances between cpSSR haplotypes calculated from the sum of the squared number of repeat differences between two haplotypes: dxy =Σ[axi− ayi]2 (where axi and ayi are the number of repeats for the ith locus in haplotype x and y). This gives an analogue of Slatkin's RST (Slatkin, 1995) for population differentiation (Michalakis & Excoffier, 1996). Mantel's test (Mantel, 1967) was carried out using NTSYS-pc ver. 2.0 (Rohlf, 1990) on geographical distances and pairwise RST values; normalized Mantel Z statistics were calculated after 1000 permutations. In accordance with several theoretical studies (Heywood, 1991), logarithmically transformed geographical distances were used.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

Polymorphism of chloroplast microsatellite loci

Among 10 universal primer pairs (Weising & Gardner, 1999) tested for amplification on A. bertolonii total DNA, five pairs (CCMP1, CCMP2, CCMP6, CCMP7 and CCMP10) were found to be able to promote the amplification of single bands. The identified cpSSR loci were named with the prefix AB (to indicate A. bertolonii) followed by the name of the primer pair used to amplify it. The sequences of all the amplification products were shown to contain simple sequence repeat regions of different complexity (Table 1). The most complex locus was ABCCMP1, which contained three blocks of homoadenine repeats separated by 42 bp and 12 bp of nonrepeated sequences, while ABCCMP10 was the simplest, being composed of one repeat block only. The five cpSSR loci examined were all variable, giving from two (ABCCMP2) to eight (ABCCMP1) alleles per locus and a total of 24 alleles combined in 35 different chloroplast haplotypes was scored among the 90 individuals surveyed (Table 2).

Table 1.  Characterization of the five chloroplast microsatellite loci identified in A.bertolonii*
Code (bp)Primer sequences (5′-3′)Location in TobaccoRepeats in A. bertoloniin° of alleles detectedSize range
Total   24 
Table 2.  Chloroplast haplotypes identified on 90 A. bertolonii plants

Haplotype composition of the populations

Table 3 shows the haplotype composition of each of the nine populations. No haplotype was shared by all populations, while six haplotypes were shared by more than one population. In particular haplotype number 2 was the most widespread, being present in five out of nine populations (IM, LA, RS, PS and MR).The other 29 haplotypes were found to be restricted to single populations (private haplotypes).

Table 3.  Haplotype composition of the populations *
Serpentine regionPopulationsHaplotype numberFrequency
  • *

    The frequency of the haplotypes present in each population is shown.

CoastalPomaia (PO)220.1
ICollesalvetti (CO)210.1
InlandMonterufoli (MR)20.5
Larderello (LA)20.3
Rocca di Sillano (RS)130.3
IIImpruneta (IM)10.1
Galceti (GA)100.7
IIIPieve Santo Stefano (PS)160.1
IVMonte Prinzera (MP)260.1

Genetic diversity within populations

The estimates of genetic diversity within the different populations are shown in Table 4. The most variable population was IM for the IAM-based measures and RS for inline image. The least variable were GA for IAM-based measures and LA for inline image. The average values of genetic diversity for the serpentine region I were lower (for IAM-based measures) than those for populations of regions III and IV (P < 0.01). Large differences in the values of genetic diversity were found within the same serpentine region, in particular for region II between IM and GA which showed the highest and the lowest ne values over the whole study, respectively.

Table 4.  Genetic diversity within populations *
Serpentine regionPopulationsHEneinline image
  • *

    Measures were based on the IAM ( ne, effective number of haplotypes , HE , haplotypic diversity) and the SMM ( inline image ). s.d., Standard deviation.

 CoastalPomaia (PO)0.6672.500.178
  Collesalvetti (CO)0.8003.750.522
 InlandMonterufoli (MR)0.6892.630.178
  Larderello (LA)0.6892.630.160
  Rocca di Sillano (RS)0.7112.780.638
  Mean( ± ΣΔ )0.71 ± 0.052.82 ± 0.430.33 ± 0.23
  Impruneta (IM)0.9788.330.542
  Galceti (GA)0.5111.850.212
  Mean( ± ΣΔ )0.74 ± 0.335.09 ± 4.580.38 ± 0.23
  Pieve Santo Stefano (PS)0.8896.250.530
  Monte Prinzera (MP)0.8895.000.478

Genetic structure of the populations

In Table 5 the results of the Analysis of Molecular Variance following these two hypotheses are reported. The largest part of the genetic variation in the sampled populations was attributed to variation within populations (ΦST = 0.515, Table 5a and ΦST = 0.722, Table 5b). The AMOVA, performed to test the possible genetic grouping of populations, detected a separation (ΦCT = 0.252), among four groups representing the four serpentine regions considered (Table 5a, first row). However, the variation among populations contributed more to the total variance than did the variation among groups (ΦST = 0.475; Table 5a, last row). A locus-by-locus analysis of the genetic differentiation indicated that the most important contribution to the differentiation of populations was from the ABCCMP1 locus (ΦST = 0.566), while the lowest was from the ABCCMP10 locus (ΦST = 0.137) (data not shown). Then, the serpentine region I was analyzed for the internal genetic differentiation of its five populations (Table 5b), showing that of the genetic variation attributed to variation among populations was high (ΦST = 0.622, Table 5b, last row), mainly due to differences at the ABCCMP1 locus (ΦST = 0.647) (data not shown). However, in the same serpentine region the AMOVA revealed a high differentiation (ΦCT = 0.662) between the coastal (PO and CO) and the inland (MR, RS, LA) populations. (Table 5b, first row).

Table 5.  Analysis of molecular variance (AMOVA) for 90 individual plants using 24 cpSSR alleles combined in 35 chloroplast haplotypes *
(a) Different serpentine regions may have different genetic pools
Source of variationd.f.Sum of squaresVariance% TotalΦ statisticsP -value
Between groups (regions)3113.1571.22125.22ΦCT = 0.252< 0.01
Among populations/groups575.5101.27526.34ΦSC = 0.352< 0.01
Within populations81190.0002.34648.44ΦST = 0.515< 0.01
Among populations irrespective of groups    ΦST = 0.475 
(b) Different locations in the same serpentine region may have different genetic pools
Source of variationd.f.Sum of squaresVariance% TotalΦ statisticsP -value
  • *

    The AMOVA was performed attributing the following two types of grouping: computation (a) was made over the entire set of populations partitioned into the four serpentine regions (groups). Computation (b) was made on the populations of serpentine region I partitioned between coastal (PO, CO) and inland (LA, MR, RS) populations. For each grouping the percent of the total variance observed was attributed to the three hierarchical partitions: first lane, among groups; second lane, among populations within groups; third lane, among single individuals within populations. The ‘Among populations irrespective of groups’ lane indicates the Φ ST value obtained, estimating the differentiation among populations. Data show the degrees of freedom (d.f), the sum of squared deviation, the variance component estimate, the percentage of total variance contributed by each component and the Φ statistics and P -values, estimated computing 16 000 permutations. Φ CT is the correlation of random pairs of haplotypes drawn from a group relative to the correlation of pairs of random haplotypes drawn from the whole population. Φ SC is the correlation of random pairs of haplotypes drawn from a population relative to the correlation of pairs of random haplotypes drawn from the whole group, averaged over all populations. Φ ST is the correlation of random pairs of haplotypes drawn from within populations relative to the correlation of pairs of random haplotypes drawn from the whole population.

Between groups (coastal/inland)161.1432.41466.24ΦCT = 0.662< 0.01
Among populations/groups39.6170.2196.02ΦSC = 0.178< 0.01
Within populations4545.5001.01127.74ΦST = 0.722< 0.01
Among populations irrespective of groups    ΦST = 0.622 

Mantel's test, carried out on the pairwise RST values (Slatkin, 1995) and on logarithmically transformed geographical distances showed a significant association (r = 0.31, P < 0.04) over all the populations.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

A high chloroplast genetic variation was found in the whole sample of 90 plants together with a high percentage of population-specific cpSSR haplotypes (private haplotypes). Only six haplotypes were found in more than one population (public haplotypes), and public haplotype number 2 the most widespread, being present in six different populations. The presence of a large fraction of private chloroplast haplotypes could suggest a model in which the different populations, especially those present in different serpentine regions, encountered ancient bottleneck or founder effects and differentiated into the present-day chloroplast haplotypes. Tuscany was indicated as glacial refugium for this species (Pignatti Wikus & Pignatti, 1977) and glaciations could have caused bottlenecks and founder effects, due to migration and fragmentation of the distribution area.

As would be expected from an ancient origin of the present populations, a high genetic diversity was found within them. In particular the IAM-based parameters, which roughly measure the number of different haplotypes present in the populations, gave relatively high values (Provan et al., 1998 and for a comparison with an other serpentine plant species see Mengoni et al., 2001 and Mayer et al., 1994), especially for the population IM, which also included the haplotype number 2. The SMM parameter inline image, measuring the molecular evolutionary divergence between haplotypes, gave high values as well (Mengoni et al., 2001), but the population having the highest value was RS, in which haplotypes 2, 13, 14 and 15 were present. These haplotypes show large differences in their allelic composition which are responsible for the high value of inline image observed.

According with the low haplotype sharing between populations, the ΦST values obtained after AMOVA were also high in the same serpentine region (see Raspéet al., 2000 for an estimate of GST on chloroplast DNA). These values are in good agreement with previous reports on serpentine flora (Silene paradoxa) analyzed for polymorphism at the same homologous chloroplast loci (Mengoni et al., 2001): in S. paradoxa the measured ΦST value was 0.526 for the differentiation between coastal and inland populations of the same serpentine region I. The ΦST values were also comparable (considering their chloroplast origin) with those found at enzymatic loci (FST = 0.417) in populations of the serpentine endemic C. collina (Wolf et al., 2000). The patterns of chloroplast genetic differentiation depicted by AMOVA showed that the most significant grouping over the whole sample was based on the different serpentine regions. However, the between-region variance was comparable with the among population-within region variance, indicating, together with the high ΦST value, that single populations contribute more than regions to the genetic differentiation. A more detailed analysis within the same region confirmed this hypothesis: serpentine region I, which is represented by five populations, was found to be composed of at least two different genetic pools including the coastal populations and the inland populations, respectively. Interestingly, in both the analyses, ABCCMP1 locus, which had the highest number of alleles and a complex pattern of sequence repeats, was the main contributor to the genetic differentiation, indicating that the molecular evolution of the chloroplast haplotypes was mainly driven by this locus.

The population structure observed suggests a long history of spatial isolation between individual populations and could be interpreted in terms of the ‘ecological island model’ (Lefèbvre & Vernet, 1990) as for other serpentine plant species such as Streptanthus glandulosus (Mayer et al., 1994), Armeria maritima (Vekemans & Lefèbvre, 1997), Silene paradoxa (Mengoni et al., 2000b; 2001) and Calystegia collina (Wolf et al., 2000). Actually, a Mantel's test carried out on the whole sample revealed a significant correlation of the genetic differentiation with the geographical distance. As chloroplast markers will not reflect pollen-mediated gene flow and might therefore overestimate the degree of interpopulation genetic isolation, an analysis of genetic polymorphism at nuclear loci could be helpful in elucidating the amount of gene flow between A. bertolonii populations in the perspective of an ‘isolation-by-distance’ model of genetic differentiation (Hanson, 1966). An investigation on the Ni-hyperaccumulation variation in A. bertolonii, as for other hyperaccumulators such as Arabidopsis halleri and Thlaspi caerulescens (Pollard & Baker, 1996; Meerts & Van Isacker, 1997; Escarrèet al., 2000; Reeves et al., 2001; Bert et al., 2002; Macnair, 2002), and on its relation with molecular genetic polymorphism, could be interesting for the study of the evolution of metal hyperaccumulation in plants and for the improvement of phytoremediation practices.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References

We are grateful to Dr B. Foggi and Dr L. Di Fazio for their assistance with the collection of plant material. We thank three anonymous referees for their comments and suggestion.


  1. Top of page
  2. Summary
  3. Introduction
  4. Materials and Methods
  5. Results
  6. Discussion
  7. Acknowledgements
  8. References
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