Free access
Issue
Ann. For. Sci.
Volume 67, Number 5, July-August 2010
Article Number 512
Number of page(s) 8
DOI http://dx.doi.org/10.1051/forest/2010014
Published online 18 May 2010

© INRA, EDP Sciences, 2010

1. INTRODUCTION

The genus Crataegus L. (Rosaceae) is widely distributed in temperate regions of the Northern hemisphere including North America, Europe, Northern Asia and the Mediterranean region. It is represented by over 265 species (Christensen, 1992). Species naturally occur as small trees and shrubs, mainly diploid (x = 17) (Evans and Campbell, 2002). The systematic of the genus based on morphological (Phipps, 2005), cytological (Dickinson and Talent, 2007) and reproductive traits (Christensen, 1992; Evans and Campbell, 2002) is still unclear owing to interspecific hybridization, polyploidy and apomixis. Studies of phylogenic relationships among species based on molecular markers are currently under progress (Albarouki and Peterson, 2007; Evans and Campbell, 2002; Fineschi et al., 2005; Lo et al., 2007; 2009).

In Tunisia, the genus Crataegus L. includes two species: Crataegus monogyna Jacq. var. monogyna Jacq. (=Crataegus oxyacanthus L. subsp. monogyna (Jacq.) Rouy and Camus) and Crataegus azarolus L. which can be sympatric over a wide area of the Tunisian Dorsal Mountain (Pottier-Alapetite, 1979). Hybridization between the two species may occur (Albarouki and Peterson, 2007; Christensen, 1992). Crataegus azarolus L. (orientalis series, Crataegus section) is cultivated, with mixed trees (i.e. Almond, Olive) in small orchards (1-6 individuals/field) for fruit use. It comprises two botanical varieties (Pottier-Alapetite, 1979): C. azarolus L. var. aronia L. [=var. aronia (Willd.) Batt.] and C. azarolus var. azarolus L. The latter is extremely rare and occurs in few individuals mixed with Crataegus monogyna and/or C. azarolus var. aronia. The two varieties are similar in vegetative and floral traits but differ by fruit colour. When completely ripe, fruits of C. azarolus var. azarolus and C. azarolus var. aronia are typically red and yellow, respectively.

C. azarolus var. aronia is predominantly diploid (2n = 2x = 34) and outcrosser (Christensen, 1992; Talent and Dickinson, 2005). It reproduces via seeds and shows a vegetative propagation through sprouts. The species grows in humid and semi-arid bioclimates, on marneous soil usually below 800 m, in edges of forests and in garrigues dominated by Pinus halepensis Mill., Juniperus phoenicea L., Quercus ilex L. and Tetraclinis articulata Benth. The flowering period extends from mid-March to mid-May. Flowers are hermaphrodite, pentamerous with numerous stamens, and grouped in racemes. They are pollinated by bumble bees and smaller hymenoptera (Dickinson and Campbell, 1991). The fruit ripening period extends from August to December. Fruits (pomes), that differ in size (10–25 mm in diameter), contain 2–3 pyrenes each including one seed. Birds, small mammals and ungulates are the major seed dispersal vectors (Dickinson and Campbell, 1991).

Tunisian natural C. azarolus var. aronia populations are fragmented and represented by scattered individuals. All populations are highly affected by human practices (i.e. clearing, charcoal production, over harvesting) and characterized by a low size (often below 50 cm). Many populations are lost or endangered. Population isolation and the decreasing size increase genetic erosion, reducing therefore adaptability to environmental changes. Thus, knowledge of genetic diversity and genetic structure of populations is required for the development of appropriate in situ and ex situ conservation strategies.

The purpose of this paper is to assess, by RAPDs (Random Amplified Polymorphic DNA) (Williams et al., 1990), the genetic diversity within and among Tunisian populations of Crataegus azarolus var. aronia from different sites, with a focus on developing conservation strategies for the species. RAPD markers are a valuable tool for genetic studies in natural populations for woody plants and can yield a large number of loci by providing a wide representative sample of the genome (Ferrazzini et al., 2008; Fournier et al., 2006).

2. MATERIALS AND METHODS

2.1. Analysed populations

Nine Natural populations collected from different geographical regions were assessed (Fig. 1 and Tab. I). They belong to upper semi-arid (populations 1, 2, 3, 4, 5 and 6) and sub-humid (populations 7, 8 and 9) bioclimates according to Emberger’s (1966), pluviothermic coefficient Q2 (Q2 = 2000P/(M2m2)); where P is the average of annual rainfall (mm), M is the mean of maximal temperature (Kelvin) for the warmest month (July) and m is the average of minimal temperature (Kelvin) for the coldest month (February). Altitudes of sites ranged from 150 to 865 m. The average annual rainfall varied from 400 to 600 mm. All populations were collected in Pinus halepensis Mill. margin forests.

thumbnail Figure 1

Map of Tunisia: Geographical distribution of the 9 Tunisian Crataegus azarolus var. aronia populations analysed. •: Sub-humid; ▴: Upper semi-arid. 1, 2, 3, ..., 9: Population code.

Table I

Properties of the 9 Tunisian Crataegus azarolus var. aronia populations analysed.

Six to twelve trees in each population (at fruit ripening period), with 50 to 300 m between individuals, were sampled. Sample numbers were dictated by the scarcity of individuals and the small size of the populations encountered. From each individual, branches with leaves were taken for RAPD analyses.

2.2. DNA extraction

Three hundred milligrams of leaves from each plant were grounded to fine powder in liquid nitrogen and mixed with 1.5 mL of preheated extraction buffer (100 mM Tris-HCl, pH 8; 20 mM EDTA; 2% CTAB; 1.4 M NaCl; 1% β-mercaptoéthanol) and 100 mg PVP 40000. Samples were then incubated at 65 °C for 1 h with slow shaking every 5 min. Subsequently the mixture was treated twice with 600 μL chloroform-isoamyl alcohol (24:1). Cold ethanol 95% and NaCl (5M) were used to precipitate the DNA following the method described by Lodhi et al. (1994). The DNA pellet was re-suspended in TE buffer (10 mM Tris-HCl, 0.1 mM EDTA). The RNA was eliminated by adding 2 μL of Rnase-Dnase free solution (10 mg/mL). The quality of the DNA was estimated on an agarose gel (0.8%) stained with ethidium bromide. DNA quantity was evaluated spectrophotometrically by measuring absorbance at 260 nm.

2.3. Random amplification and sampling primers

Reactions were standardized and all PCR reactions were run on the same thermal cycler (Mark Maximum-Gene). For every 25 μL of volume reaction, (50 ng of DNA), 2.5 μL of 10X Taq polymerase buffer, 40 pmoles of primer, 2.5 mM of MgCl2, 200 μM of dNTP and 1.5 U of Taq polymerase were included. Each reaction was overlaid with an equal volume of mineral oil. The PCR program was set as follow: an initial denaturation step of 94 °C for 2 min, followed by 45 cycles of 30 s at 94 °C, 1 min at 36 °C (annealing step) and 2 min at 72 °C (elongation step). An additional 10 min period for elongation at 72 °C followed this cycle.

Amplification products were separated on 1.5% agarose gel in TAE buffer (1X; pH 8), stained with ethidium bromide, and photographed under UV light using a DOC PRINT Photo Documentation System. Molecular weights were estimated using a 200 bp DNA Promega ladder. To ensure the reproducibility within and between runs, DNA from the same two additional individuals was included and amplified twice in every PCR run.

Sixteen primers (Operon Technologies) were tested for RAPD amplification. Eight primers (OPB08, OPB13, OPB14, OPB16, OPC17, OPJ07, OPJ16 and OPJ17), giving reliable banding patterns with high reproducibility and clear band resolution, have been selected.

2.4. Data analysis

RAPD bands were recorded as presence (1) or absence (0) of a band for each marker in each individual sample, and data were entered as a binary matrix. As RAPDs limitations (i.e. reproducibility of bands, dominant expression) may have a biased effect on the estimation of the genetic diversity and population structure, we have therefore (i) removed from the data bands with a frequency lower than 3/N (N = 77 plants analysed; frequency > 0.249), and (ii) used, jointly to classical genetic parameters, the molecular variance (AMOVA) considered to be the less unbiased differentiation coefficient for RAPD analyses (Excoffier et al., 1992; Holsinger and Wallace, 2004).

The percentage of polymorphism (P% = (number of polymorphic bands/number of total bands) × 100), at the population and the ecological group (populations from the same bioclimate) levels, was calculated. The genetic diversity was determined by calculating Shannon’s index (H′) for each population and each group (H′ = −Σpi log 2pi; where pi is the frequency of the presence or absence of a RAPD band in a population or in a group). A variance analysis (ANOVA procedure) (SAS, 1990) was used to estimate the significance of variation of H′ among populations and among ecological groups. The correlation among Shannon’s indices (H′) and altitude or Emberger’s Q2 matrices was evaluated using Kandell’s test. The average diversity over all populations (Hpop) was calculated as: Hpop = −1/H′; where n is the number of populations. The total diversity among all individuals within the species was estimated as: Hsp = −Σps log 2ps; where ps is the frequency of presence or absence of the RAPD band in the whole sample.

The differentiation among populations was assessed by GST [GST = (HSPHPOP)/HSP]. The POPGENE computer package (Yeh et al., 1999) was used to calculate the different indices. The genetic structure among populations was also determined by analyses of the molecular variance (AMOVA) using the program WINAMOVA 1.55 (Excoffier et al., 1992). Φstatistics were calculated to estimate ΦST (differentiation among populations), ΦCT (differentiation among ecological groups) and ΦSC (differentiation among populations within groups). The significance of variance components was determined using 1000 independent permutations runs. Pairwise genetic distance (ΦST) between the nine populations were used to estimate the gene flow as the number of individuals migrating among populations per generation, using Wright’s (1951) migrate number Nm [Nm = 1/4(1 / ΦST − 1)]. The correlation between the matrices of genetic and geographic distances among pairs of populations was estimated by a Mantel test (Mantel, 1967) using ZT program (Bonnet and van de Peer, 2002).

A Neighbour-joining cluster was produced to illustrate the relationship between individuals using Nei’s and Li’s (1979) genetic distance Dxy generated from the similarity coefficient Sxy [Sxy = 2mxy/(mx + my); where mxy is the number of bands shared by samples x and y, and mx and my are the number of bands in samples x and y, respectively]. The genetic distance Dxy between individuals was estimated using the complementary value Sxy; [Dxy = 1 − Sxy]. The program MEGA version 2.0 (Kumar et al., 2001) was used to construct the dendrogram. UPGMA tree based on pairwise ΦST was also generated to compare similarities among populations using the program MVSP version 3 (Kovach, 1999).

Table II

Selected RAPD primers, number of polymorphic bands and percentages of polymorphic loci (Pr%) per primer.

3. RESULTS

A total of 105 RAPD bands were scored by the eight selected primers, among which 81 (Pr = 77.1%) are polymorphic (Tab. II). The revealed number of bands per primer varied from 11 (OPC17, OPJ07, OPJ17) to 16 (OPB16). The highest number of polymorphic bands was evidenced by OPB13 (12 bands) and OPB16 (13 bands). The polymorphism within a population (P%) ranged from 34.3% (population 8 from the sub-humid bioclimate) to 47.6% (populations 2 and 4 from the upper semi-arid zone), with an average of 42.1% (Tab. III). The polymorphism was slightly higher in the semi-arid (76.2%) than in the sub-humid populations (64.8%).

Table III

Polymorphism (P%), and genetic diversity parameters within and among populations and ecological groups.

Shannon’s diversity index (H′) within a population ranged from 0.218 (population 8, sub-humid zone) to 0.278 (population 2, upper semi-arid zone). However, the level of variation among populations was not significant (ANOVA test, P > 0.05). Besides, there was no correlation between Shannon’s diversity index (H′) and altitude matrices (Kendall’s test; r = 0.43; P > 0.05) or between H′ and Emberger’s Q2 matrices (Kendall’s test; r = −0.42; P > 0.05). Averages H′ did not differ between the sub-humid and the upper semi-arid groups (0.371 and 0.414, respectively). The average diversity within populations (Hpop) was 0.245, and that within ecological groups 0.393. Diversity within the species was relatively low (Hsp = 0.423) (Tab. III).

A high level of differentiation was observed among populations (GST = 0.421). This value was higher than that observed among the ecological groups (GSTg = 0.122). AMOVA indicated also a substantial level of differentiation among populations (ΦST = 0.371), and 63.31% of the genetic variation is apportioned within populations (Tab. IV). The level of gene flow is low (Nm = 0.423). Nm values between pairs of populations ranged from 0.278 (between populations 5 and 8) to 1.07 (between populations 1 and 9). Among the 36 Nm values, 35 were below 1 (Tab. V).

Table IV

Nested analysis of molecular variance (AMOVA) at different hierarchical levels.

Table V

Geographical distance (km) (above diagonal) and genetic (ΦST) distance (below diagonal) among population pairs of Crataegus azarolus var. aronia. Nm values are given in parentheses.

The differentiation among ecological groups was low (ΦCT = 0.014; P > 0.05), that among populations within groups was important (0.363).The maximum variance (62.86%) was found within populations (Tab. IV).

Pairwise comparison of ΦST values were all highly significant (P < 0.001 after 1000 permutations). The highest ΦST value (0.473) has been observed among populations 5 and 8 belonging to the upper semi-arid and the sub-humid bioclimates, respectively. These two populations were separated by 213 km each from another. The lowest value (0.189) was noted between the sub-humid population 9 and the upper semi-arid population 1, geographically 135 km apart each from another. At a low scale space (less than 20–25 km), ΦST values ranged from 0.312 to 0.406. Genetic distance (ΦST) and geographical distance matrices (km) did not show significant correlation (r = 0.297; P > 0.05). For populations grouped into two ecological groups, the isolation by distance was not revealed neither for the upper semi-arid populations (r = 0.497; P > 0.05), nor for sub-humid ones (r = 0.950; P > 0.05).

thumbnail Figure 2

Neighbour-joining dendrogram generated for all individuals of C. azarolus var. aronia analysed using genetic distances of Nei and Li (1979). 1, 2, 3, …, 9: Population code.

The dendrogram based on Nei’s and Li’s genetic distance showed that all individuals from the same population clustered together except for one individual from the population 1 grouped with samples from the population 5 (Fig. 2). The populations 6 and 8 from the upper semi-arid and the sub-humid bioclimates, respectively (53 km distant) were more isolated from the other populations. Results of UPGMA cluster analysis based on ΦST distance matrix revealed two main population groups (Fig. 3). The first contains populations 6 (upper semi-arid zone) and 8 (sub-humid zone). The second cluster is constituted by seven populations from different geographical and bioclimatic areas.

thumbnail Figure 3

Dendrogram of the 9 populations based on ΦST pairwise values. 1, 2, 3, …, 9: Population code. * Usa: Upper semi-arid; Sh: Sub-humid.

4. DISCUSSION AND CONCLUSIONS

The analysis of the genetic diversity within and among populations of Crataegus azarolus var. aronia in Tunisia is prerequisite for conservation and improvement strategies. Our data based on RAPDs revealed a low level of variation within populations and high differentiation among them. RAPD markers are dominantly inherited (Williams et al., 1993). The analysis of population genetic variation with RAPDs could be hampered by a loss of a part of genetic information (Kremer et al., 2005; Lynch and Milligan, 1994; Nybom, 2004). However, this disadvantage could be buffered by the detection of a high number of loci (Aagaard et al., 1998) and the use of appropriate genetic population parameters such as ΦST which reduces the bias in estimating the genetic variation. In our study, the eight selected primers revealed 105 loci (Frequency > 0.249), of which 81 were polymorphic. This large number of loci could be considered sufficient to compensate loss of genetic information content at loci.

Crataegus azarolus var. aronia populations maintain a relatively low level of genetic diversity as observed in other Crataegus (Ferrazini et al., 2008; Fineschi et al., 2005) or Rosaceae species (Petit et al., 2003). The low value of genetic diversity recorded in our study may result from loss of genetic variation through inbreeding and/or genetic drift due to the restriction of the species to small and degraded populations. However, amounts of the vegetative reproduction and selfing reported in Crataegus species could contribute to the low level of diversity detected. Thus, analyses including allo-autopollination experiments were required for collecting more information about the reproductive biology of the species and understanding the dynamic of its populations.

The observed averages of gene diversity at the population (Hpop = 0.245) and species (Hsp = 0.423) levels are within those reported from RAPDs for outcrossing trees (Hogbin and Peakall, 1999), but relatively lower compared to values observed in several gymnosperms with outcrossing mating system and wind-dispersed pollen (Begona et al., 2005).

The analysis of the molecular variation according to geographical and ecological factors (altitude and Q2) has not revealed clinal structuring. Populations or ecological groups have similar values of average genetic diversity. This could be explained by the neutrality of RAPD markers, the large number of revealed loci and probably by the genomic characteristics of the species (high repetitive and non encoding DNA). However, the genetic similarity among populations, from RAPDs, may mask special morphological and/or physiological adaptations to bioclimates that will not be revealed through RAPDs.

The GST estimates using Shannon’s index revealed a high differentiation among populations (GST = 0.421), and the majority of the genetic variation was attributable to variation within populations. The observed GST value was higher than that based on Shannon’s index for outbreeding species (14.5 < GST < 38%) (Bussel, 1999) and Rosaceae species generally showing low level of genetic differentiation (Fineschi et al., 2005; Petit et al., 2003). With AMOVA, the amount of variation (ΦST = 0.371) was higher than that for outcrossers and wind-dispersal species (ΦST = 0.22 − 0.28, Nybom, 2004; Nybom and Bratish, 2000).

In most cases, the high differentiation among populations was caused by factors such as breeding system, isolation of populations, seed and pollen dispersal distance. This study showed that the population genetic structure, at all scale spaces, was not correlated to geographical distance. Thus isolation by distance could not alone explain the genetic structure observed. The high differentiation might result from habitat fragmentation, which led to the isolation of populations, the decreasing of their size and the limitation of gene flow among them. Similar results were obtained in Italian C. monogyna (Ferrazini et al., 2008).

The UPGMA dendrogram based on ΦST genetic distances among populations did not clearly separate populations according to their bioclimate and/or geographical location. Two groups of populations were revealed. The populations 6 and 8 constitute one group and seem to show low genetic divergence among them despite their different geographical and bioclimatic localization. The second group was composed of populations from different origins.

The isolation of populations 6 and 8 from the other populations could be explained by two hypothesis: firstly, it is possible that they have undergone a very high degree of genetic drift due to their low size (6 and 7 individuals) and their isolation, and are now very different from the others populations. Secondly, the two populations may correspond to hybrids among Crataegus azarolus and Crataegus monogyna. In fact, they grow with several individuals of Crataegus monogyna, and introgression between the two taxa may occur (Albarouki and Peterson, 2007; Christensen, 1992). In order to elucidate the hybrid character of these populations and their relationship with the two taxa, analyses using species specific molecular (i.e. ISSR, chloroplast microsatellite markers) and morphological (i.e. style and ovule numbers per flowers, leaf and fruit shape, pyrene number per fruit) markers are necessary to gain further insight into the hybrid character of these populations.

The aggregation of populations, in the second group, without any relationship to geographic distance and bioclimate, provides further evidence of genetic drift which can not be easily confirmed by RAPDs only. These markers show a dominant expression and are assumed to possess two alleles per locus, which may bias the estimation of some genetic parameters (i.e. frequency of null homozygotes, F index) mainly if selfing is occurring or if the populations are not randomly mating. On the other hand, RAPDs are dispersed throughout the genome and their association with ecological traits (i.e. climate, soil) is influenced by selection only in the region under selection pressure. The other loci are subject to random genetic drift. Thus, the genetic relationship between populations revealed by RAPDs did not necessary reflect natural selection process leading to similar local environment adaptation of populations.

Most Crataegus azarolus var. aronia populations in Tunisia were represented by few individuals. They suffer from a loss of genetic variation, and were highly differentiated. The long term viability of populations could be affected by an increasing habitat destruction. Taking into account these points, as well as the small of number of populations, efforts should be made to protect all populations and limit human impact. Given the high genetic differentiation among populations and the low level of genetic variation recorded, any in situ conservation strategy should aim to include populations from both sub-humid and upper semi-arid bioclimates. Such strategy could include restoration within a population through cuttings from the same population. Ex situ approaches may also be appropriate as apart of an overall conservation strategy. Seeds may be collected rather within than between populations, because the maximum amount of genetic diversity within population was high. Populations from the upper semi-arid exhibiting a slightly high level of diversity must be protected in the first place.

Acknowledgments

The authors thank the Tunisian Ministry of Scientific Research and Technology and the National Institute of Applied Science and Technology for their financial support (Research grant 99/UR/09-10).

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All Tables

Table I

Properties of the 9 Tunisian Crataegus azarolus var. aronia populations analysed.

Table II

Selected RAPD primers, number of polymorphic bands and percentages of polymorphic loci (Pr%) per primer.

Table III

Polymorphism (P%), and genetic diversity parameters within and among populations and ecological groups.

Table IV

Nested analysis of molecular variance (AMOVA) at different hierarchical levels.

Table V

Geographical distance (km) (above diagonal) and genetic (ΦST) distance (below diagonal) among population pairs of Crataegus azarolus var. aronia. Nm values are given in parentheses.

All Figures

thumbnail Figure 1

Map of Tunisia: Geographical distribution of the 9 Tunisian Crataegus azarolus var. aronia populations analysed. •: Sub-humid; ▴: Upper semi-arid. 1, 2, 3, ..., 9: Population code.

In the text
thumbnail Figure 2

Neighbour-joining dendrogram generated for all individuals of C. azarolus var. aronia analysed using genetic distances of Nei and Li (1979). 1, 2, 3, …, 9: Population code.

In the text
thumbnail Figure 3

Dendrogram of the 9 populations based on ΦST pairwise values. 1, 2, 3, …, 9: Population code. * Usa: Upper semi-arid; Sh: Sub-humid.

In the text