Biologia 66/6: 1003—1010, 2011 Section Botany DOI: 10.2478/s11756-011-0106-2

Population genetic structure of Tunisian humifusum assessed by RAPD markers

Afef Béjaoui, Abdennacer Boulila,ChokriMessaoud & Mohamed Boussaid*

Laboratory of Biotechnology, National Institute of Applied Science and Technology. Centre Urbain Nord, B.P. 676, 1080 Tunis Cedex, Tunisia; e-mail: [email protected]

Abstract: The genetic variation within and among seven Tunisian natural Hypericum humifusum L. populations belonging to three bioclimatic zones (sub-humid, upper semi-arid, and lower semi-arid) was assessed using random amplified poly- morphic DNA markers. Eight selected primers produced a total of 166 bands, of which 153 were polymorphic. The genetic diversity within a population, based on Shannon’s index and percentage of polymorphic loci, was relatively high. The level of variation among populations did not differ significantly. However, the variation among populations grouped according to their bioclimates was significant. A high differentiation and a low gene flow were observed at all spatial scales among all populations. The upper semi- arid populations exhibited the highest differentiation. The relationship between genetic and geographic distances was not significant indicating that structuring occurred due to founding events. The UPGMA analysis based on Nei & Li’s coefficients showed that individuals from each population clustered together. The cluster analysis based on genetic distances among populations did not show clear groupings relevant to geographical distances or bioclimates. The high differentiation among populations even through a small geographic range implies the collection of seeds from all populations to preserve, ex-situ, extant variation in the species. Populations from the upper semi-arid zone showing the highest genetic diversity should be first prospected. Key words: Hypericum humifusum; genetic structure; RAPD markers; Tunisia

Introduction humid to the upper arid, usually below 300 m a.s.l. It is a diploid species (2n =2x = 16) and belongs to The genus Hypericum () is represented the Oligostema section (Carine & Christenhusz 2010; by more than 458 species (trees, shrubs and herbs) Robson 2010; Crockett & Robson 2011). Stems (20–70 subdivided into 36 sections (Robson 2003; Robson cm in height) are glabrous. Leaves are sessile, opposite 2010; Crockett & Robson 2011). Species are distributed with dark glands at the edges. Flowers produced from mainly in temperate regions of the Northern hemi- April to September are bright yellow, and arranged sphere and tropical high elevation habitats (Robson in branched cymes. They are regular with five short 2003; C¨uneyt et al. 2007). Most previous studies on sepals, five petals, and numerous stamens. The gynoe- Hypericum species have focused on ploidy level, breed- cium has 3–4 locules. Fruits are small capsules, dark ing system, genetic diversity (Dlugosch & Parker 2007; purple, producing ∼20 dark brown seeds (∼2–5 mm in Percifield et al. 2007; Poutaraud & Giradin 2008), phy- size). The species reproduces via seeds and shows some logenetic relationships (Robson 2003; Crockett & Rob- capacity to propagate vegetatively. It contains amounts son 2011), chemical composition and biological activ- of hypericin and hyperforin (Tanaka & Takaishi 2006; ity (Meral & Karabay 2002; Conforti et al. 2005). The Smelcerovic et al. 2006), and is used to treat several most studied species is H. perforatum L. known mainly diseases such as wounds and burns (Smelcerovic et al. for its antidepressive, anticancer and antiviral activities 2006). In Tunisia, the species tends to occur in scat- (Gartner et al. 2005; Kubin et al. 2005). tered metapopulations, often with a low size and be- H. humifusum L. is found mainly in wet habi- comes abundant, forming extensive populations, within tats in the North and the Center of Europe, Argentina and at the edges of the northern crop fields. Populations and several Mediterranean regions (Robson 2010). In are heavily harvested and affected by agricultural prac- Tunisia, the species grows widely in the north and in tices (i.e. ploughing, weeding, crop rotation schemes). the center of the country on sandy soils under a rain- The dynamic of populations was influenced by the dis- fall ranging from 350 to 992mm/year (Pottier-Alapetite persion of dry fragments or entire individuals and seeds 1979). It grows in bioclimates extending from the sub- by wind. The fragmentation of populations and site dis-

* Corresponding author

c 2011 Institute of Botany, Slovak Academy of Sciences 1004 A. Béjaoui et al.

Table 1. Location and main ecological traits for the seven Tunisian H. humifusum populations analysed.

b Bioclimatic Population Simple Q2 Geographic Altitude Rainfall zonea Site code size (site) region (m) Longitude Latitude (mm/year)

Sh Edkhila 1 10 144.31 Kroumiri and Mogods 500 8◦38E36◦50N 992

Touiref 2 10 49.77 High Tell 550 8◦32E36◦33N 466 Triaate 3 10 49.77 High Tell 400 8◦22E36◦28N 466 Usa ◦  ◦  Testour 4 10 65.39 High Tell 450 9 25 E3635 N 585 El Kssour 5 10 49.77 High Tell 400 8◦48E36◦06N 466

Bir Mchergua 6 8 50.09 Sahel 150 9◦55E36◦25N 486 Lsa ◦  ◦  Ain Errahma 7 10 35.24 Sahel 50 10 22 E3613 N 250 a b Bioclimatic zone; Sh – sub-humid; Usa – upper semi-arid and Lsa – lower semi-arid; Q2 – Emberger’s pluviothermic coefficient 2 2 ◦ (1966). Q2 = 2000P/M − m where P is the mean of annual rainfall (mm). M (K ) is the mean of maximal temperatures for the warmest month (July) and m (K◦) is the mean of minimal temperatures for the coldest month (February). P , M and m values were calculated as the average for the period from 1953 to 2003.

Bizerte on the amount of genetic diversity maintained in the species to face environmental changes. Tunis Molecular markers such as AFLP, RFLP and ◙ 1 °Le Kef ALGERIA RAPD have been widely used to assess the genetic di- ♦ 2 ♦ 4 Hammamet MEDITERRANEAN SEA versity within and among populations in Hypericum ♦ 3 ▲ 6 species (Arnholdt-Schmidt 2000; Mayo 2003; Percifield ♦ 5 ▲ 7 et al. 2007; Dlugosch & Parker 2007). RAPD mark- ers are well established in population genetics and have proven to be useful tools in the assessment of genetic variation and population structure of plant species. They provide high number of loci and reveal a large Sfax amount of variation with good coverage of the entire genome (Mirali & Nabulsi 2003; Zhang et al. 2005; Gabès Sreekumar et al. 2006). They have been found to be use- ful in differentiating medicinal plant populations, and in establishing phylogenetic relationships among species (Taylor-Grant & Soliman 1999; Rout 2006). However, RAPD markers are dominant, and thus are less suitable

LIBYA for linkage analysis than codominant markers. This dis- advantage could be overcome by using several statisti- cal methods such as the analysis of molecular variance (Excoffier et al. 1992). The aim of this study is to determine the level of genetic diversity within and among Tunisian H. humi- fusum populations sampled from different bioclimatic zones throughout the geographic range of the species. For this purpose RAPD markers were used. This anal- ysis, a complementary to that previously published on the genetic diversity of the same populations using al- lozymes (Béjaoui et al. 2010), should be important for Fig. 1. Map of Tunisia. Geographical distribution of the seven informing decisions about conservation and improve- Tunisian Hypericum humifusum populations analysed. Numbers (1. 2...) – population code. Symbols before numbers indicate the ment strategy. bioclimatic zone: – Sub-humid,  –Uppersemi-arid, –Lower semi-arid. Material and methods Surveyed populations and sampling turbance are the main factors causing random genetic Tunisian H. humifusum populations were collected, from drift which enhances the risk of extinction of the species seven sites belonging to the sub-humid, upper semi-arid and lower semi-arid bioclimatic zones according to Emberger’s (Young et al. 1996; van Rossum & Prentice 2004). Thus, Q2 (1966) pluviothermic coefficient (Table 1). Altitudes of conservation strategies taking into account the patterns sites varied from 50 m (population 7 from Ain Errahma) of genetic variation within and among populations are to 550 m (population 2 from Touiref). The average annual crucial to evaluate the actual status of populations. rainfall ranged from 250 mm (population 7 from Ain Er- The capacity of these populations to evolve will depend rahma) to 992 mm (population 1 of Edkhila). The popu- Genetic diversity of Hypericum humifusum 1005 lation size ranged from 100 (population of Ain Errahma) also was used to estimate average diversity within all pop-  to > 1000 individuals (populations of Twiref and Triaate). ulations HPOP [HPOP =(1/nΣH )wheren is the number Almost all populations (2–7) growing in suboptimal habi- of populations], and the total diversity among all individu- tats for the species suffered some degree of human impact, als within the species HSP [HSP = −Σps log2 ps where ps is (e.g., ploughing, weeding, harvesting) and collected within the frequency of RAPD fragments in the entire sample]. The Triticum durum and T. aestivum fields after harvesting, and proportion of diversity within populations is HPOP/HSP and in roadsides near these fields. The main ecological traits of the proportion of diversity among populations is GST [GST sites are reported in Table 1 and Fig. 1. Eight to ten =(HSP−HPOP)/HSP]. The components of variability at the were sampled at distances exceeding 50 m to avoid the sam- ecological group level were estimated by HEG (the diversity pling of closely related individuals. within a group), HEG/HSPG (The proportion of diversity within ecological groups), and GSTG (The proportion of di- RAPD procedure versity among ecological groups). DNA extraction The different indices were calculated by the POP- For each plant, DNA was isolated from young leaves (0.3g) GENE computer package (Yeh et al. 1999). The compari- using 2 mL CTAB extraction buffer and 50 mg PVP son, among Shannon’s diversity indices for populations, and 40000. The extraction buffer consisted of 100 mM Tris- ecological groups, was performed using a variance analysis HCl, pH 8.0, 20 mM EDTA, 1.4 M NaCl, 2% CTAB, and (ANOVA procedure, SAS 1990) followed by Duncan’s test 1% β-mercaptoethanol. Samples were then incubated at (Dagnelie 1975). Pearson’s test was performed to estimate ◦  65 C for one hour with a slow shaking every 10 minutes. the correlation of altitude with H or Pr%matrices. Subsequently the mixture was treated twice with 500 µL The genetic similarity between individuals was esti- chloroform-isoamyl alcohol (24:1) and centrifuged for 10 min mated using Nei & Li’s (1979) similarity coefficient Sxy at 8000 rpm. 400 µL of the supernatant were removed and [Sxy =2mxy/(mx + my)], where mxy is the number of mixed with 200 µL of NaCl (5M) and 800 µL of cold ethanol bands shared by samples x and y, and mx and my are the 95%, and refrigerated at 20 ◦C overnight (Lodhi et al. 1994). number of bands in samples x and y, respectively. The ge- After centrifugation at 12000 rpm for 6 minutes the super- netic distance Dxy between individuals was estimated using natant was decanted and the DNA pellet was washed with the complementary value of the similarity coefficient Sxy; 1 ml of 76% ethanol, dried, and resuspended in 100 µLTE Dxy =1− Sxy. A dendrogram (UPGMA) based on Nei & buffer (10 mM Tris, 1 mM EDTA; pH 8.0). The mixture was Li’s similarity matrix between individuals was constructed treated with 2 µL Rnase-Dnase free (10 µg/mL) and incu- to ordinate relationships among individuals using the soft- bated at 37 ◦C for 15 minutes. The quality of the DNA was ware package NTSYS-pc (version 2.0) (Rohlf 1998). estimated on an agarose gel (0.8%) stained with ethidium The genetic variation within and among populations or bromide. within and among ecological groups also was estimated by AMOVA performed on the genetic distances (ΦST) between Primers and PCR conditions individuals using WINAMOVA program, version 1.55 (Ex- PCR reactions were performed using twenty random de- coffier et al. 1992). Φ-statistics (ΦST: differentiation among camer primers from the Operon Technologies (Kit J). Eight populations, ΦCT: differentiation among groups and ΦSC: primers (OPJ05, OPJ07, OPJ11, OPJ14, OPJ16, OPJ17, differentiation among populations within groups) were cal- OPJ18 and OPJ19 Promega mark) were selected on the ba- culated. The significance of variance components and that of sis of their high reproducibility and clear band resolution. Φ-statistics were estimated using permutations procedures. The PCR reaction was performed in 25 µLreactionvolume The correlation between the matrices of genetic and geo- containing 50 ng DNA template, 2.5 µL of 10X reaction graphic distances among pairs of populations was estimated buffer, 40 pmoles of primer, 200 µM of each dNTP, 2.5 mM by a mantel test (Mantel 1967) using ZT program (Bonnet MgCl2 and 1.5U Taq polymerase. Mixture was overlaid with & van de Peer 2002). The gene flow (Nm) between popu- 1 drop of mineral oil and amplified in a Programmable Stu- lations was estimated as Nm = [(1/ΦST) − 1]/4) (Wright art Thermal Cycler (Maxi-Gene) under the following condi- 1951). A cluster analysis based on ΦST genetic distances tions: 94 ◦C for 2 minutes, followed by 45 cycles at 94 ◦Cfor was constructed to ordinate population’s relationships us- 30 seconds, 36 ◦C for 1 minute and 72 ◦C for 2 minutes, and ing NTSYS-pc (version 2.0) program (Rohlf 1998). then a final extension at 72 ◦C for 10 minutes. PCR products were resolved by electrophoresis in 1.5% agarose gel at 160 Results V for 1 hour in 1X TAE buffer (pH 8), stained with ethid- ium bromide, visualized under UV light and photographed with DOC PRINT Photo Documentation System. Molecu- Level of genetic diversity lar weights were estimated using a 200 pb DNA Promega The eight selected primers generate a total of 166 bands ladder. (from 150 to 1800 bp), 153 of them were polymorphic (Prp% = 92.42) (Table 2). The number of generated Data analysis bands varied from 18 (OPJ17 and OPJ18) to 23 (OPJ05 RAPD bands were scored for their presence (1) or absence and OPJ11). The percentage of polymorphic loci per (0) and then transformed into a binary matrix. Each marker primer ranged from 82.61 (OPJ11) to 95.45 (OPJ16). band is assumed as a single locus. Specific bands were revealed in several populations. The The genetic diversity within a population or within band 1300bp (OPJ05) was found in the population 2 an ecological group (each group includes populations from from the sub-humid bioclimate. Bands 500bp (OPJ17), the same bioclimate) was estimated using the percentage of polymorphic bands [Pr% = (number of polymorphic 330bp (OPJ18) were restricted to the population 6 (Bir bands/number of total bands) × 100)] and Shannon’s di- M’chergua). The populations 6 and 7 (lower semi-arid   versity index H [H =(−Σpi log2 pi); pi is the frequency of zone) were characterized by bands 1200bp and 900bp a given RAPD band] (Lewontin 1972). The Shannon index (OPJ17). Bands 350bp (OPJ113) and 900bp (OPJ14) 1006 A. Béjaoui et al.

Table 2. Selected RAPD primers, number of polymorphic bands and percentages of polymorphic loci (Prp%) per primer.

Primer Sequence Polymorphic bands Total bands Prp%

OPJ05 5’CTCCATGGGG3’ 20 23 86.96 OPJ07 5’CCTCTCGACA3’ 20 21 95.24 OPJ11 5’ACTCCTGCGA3’ 19 23 82.61 OPJ14 5’CACCCGGATG3’ 20 21 95.24 OPJ16 5’CTGCTTAGGG3’ 21 22 95.45 OPJ17 5’ACGCCAGTTC3’ 17 18 94.44 OPJ18 5’TGGTCGCAGA3’ 17 18 94.44 OPJ19 5’GGA CACCACT3’ 19 20 95.00

Total bands and percentage of polymorphic bands 153 166 92.42

Table 3. Percentage of polymorphism (Pr%) in each population and each ecological group, Shannon’s indices and ratio of genetic diversity.

Population 1234567

Pr% 39.16 30.12 31.93 35.54 31.33 31.33 29.52 H 0.200 a 0.152 a 0.154 a 0.185 a 0.163 a 0.16 a 0.15 a ns HPOP 0.170 HSP 0.388 HPOP/HSP 0.438 GST 0.561

Ecological groupa Sh Usa Lsa

Pr% 39.16 82.53 58.43  HEG 0.200 c 0.320 a 0.264 b HEG 0.261** HSPG 0.350 HEG/HSPG 0.747 GSTG 0.253

** Significant at P < 0.05; ns not significant (ANOVA test). Numbers with the same letter are not significantly different (Duncun’s test, P > 0.05); a Sh – Sub-humid; Usa – Upper semi-arid; Lsa – Lower semi-arid.

Table 4. Pairwise gene flow (Nm) (above diagonal) and ΦST (below diagonal) values between pairs of populations analyzed.

Populationa 12 3 4 5 6 7

1 0.247(25)b 0.280(34) 0.317(88.5) 0.248(79) 0.327(135) 0.236(180) 2 0.503∗∗ 0.218(7.5) 0.263(81) 0.197(56) 0.229(126) 0.198(166) 3 0.472∗∗ 0.534∗∗ 0.344(79) 0.237(48) 0.271(123) 0.232(161) 4 0.441∗∗ 0.487∗∗ 0.421∗∗ 0.295(90) 0.306(49) 0.295(95) 5 0.502∗∗ 0.559∗∗ 0.513∗∗ 0.459∗∗ 0.249(118) 0.236(105) 6 0.433∗∗ 0.522∗∗ 0.480∗∗ 0.450∗∗ 0.501∗∗ 0.247(54) 7 0.514∗∗ 0.558∗∗ 0.519∗∗ 0.459∗∗ 0.514∗∗ 0.503∗∗ a 1, 2, ...population code; b Geographic distances (km) between population pairs are in parenthesis; ∗∗ Highly significant at P < 0.001. were only detected in the population 4 from the upper formed on altitude and H (r = 0.441, P > 0.05) or  semi-arid zone. H and Pr%(r = 0.48, P > 0.05) matrices did not re- The percentage of polymorphic loci (Pr%) at veal significant correlation between data sets. The av- the population level was relatively high, ranging from erage of diversity within all populations (HPOP)was 29.52% (population 7 from the lower semi-arid climate) 0.170. The amount of diversity among all individuals to 39.16% (population 1 from the sub-humid area) (Ta- within the species (HSP), and the proportion of vari- ble 3). The highest genetic diversity estimated by Shan- ation within populations (HPOP/HSP) were 0.388 and non’s index (H = 0.2) was observed for the popu- 0.438, respectively. The genetic diversity at the ecolog-  lation 1 from the sub-humid zone and located at an ical group level (HEG) varied significantly. The highest   altitude of 500 m, while the lowest (H = 0.15) was HEG value was shown for the upper semi-arid group  noted for the lower semi-arid population 7 situated at (HEG = 0.320), while the lowest was found in the sub-  an altitude of 50 m (Table 3). However, there are no humid group (HEG = 0.200). The average within all  significant differences between H values among pop- groups (HEG) was 0.261. The genetic diversity across ulations (ANOVA test, P < 0.05). Pearson’s test per- all groups (HSPG) was 0.350, and the amount of varia- Genetic diversity of Hypericum humifusum 1007

Table 5. Analysis of molecular variance (AMOVA) for the 68 individuals sampled from the 7 populations.

Source of variation d.f. M.s. Variance % of total variance Φ – statistics

Within populations 61 0.177 0.177 50.63 Population ΦST = 0.494** Among populations 6 1.844 0.172 49.37

Within populations 61 0.177 0.177 50.63 ΦSC = 0.492** Ecological group Among populations within bioclimates 4 1.83 0.171 48.97 ns ΦCT = 0.004 Among bioclimates 2 1.85 0.0014 0.40 d.f. – Degrees of freedom; M.s. – Mean square; ** Significant at P < 0.001 (after 1000 permutations).

◙ ◙ ◙ ◙ ◙ ◙ ◙ ◙ ◙ ◙ ▲ G1 ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ▲ ♦ ♦ ♦ ♦ ♦ ♦ G2 ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦ ♦

Fig. 2. Dendrogram of the 68 individuals based on Nei & Li’s similarity coefficient. * Bioclimatic zone: – Sub-humid,  –Upper semi-arid,  – Lower semi-arid. 1, 2, ... population code.

tion within groups was high (HEG/HSPG = 0.747). (r = 0.16, P > 0.05 after 1000 permutations). AMOVA analysis showed that 50.63% of the total Population genetic structure variation was found within populations (Table 5). The The genetic differentiation among populations was high differentiation among all pairs of populations (ΦST = (GST = 0.561), while that between ecological groups 0.494, P < 0.001) or among populations within groups waslessimportant(GSTG = 0.253). ΦST values among (ΦSC = 0.492) was significant. However, the total ge- population pairs are all highly significant (Table 4) even netic variation among ecological groups (ΦCT = 0.004) among those separated by a distance < 8km(pop- was not significant. ulations 2 and 3). The lowest ΦST value (0.421) was The dendrogram based on Nei’s & Li’s similar- observed among populations 3 and 4 from the upper ity coefficients showed that individuals from the same semi-arid bioclimate and distant by 79 km, whereas the population clustered together, and two major popula- highest (0.559) was detected among the upper semi-arid tions groups could be distinguished (Fig. 2). The first populations 2 and 5 (55.5 km). The values of Nm ranged subcluster (G1), grouped populations 1 from the sub- from 0.197 (populations 2 and 5) to 0.344 (populations humid zone and 6 (lower semi-arid bioclimate) distant 3 and 4). The Mantel test performed on geographic and each from the other by 135 km. The second aggregate ΦST distance matrices among population-pairs did not (G2) includes populations from different geographical reveal significant correlation between the two matrices areas and bioclimates. In this subcluster populations 2, 1008 A. Béjaoui et al.

1 Sh populations (Poschlod et al. 2000; Reish et al. 2003) and can cause environmental adaptation and differenti- 6 Lsa ation of populations (van Tiendern et al. 2002). In our 3 Usa study we cannot confirm precisely the influence of these factors (mainly climatic factors) because we used only 4 Usa Emberger’s pluviometric coefficient based on tempera- 5 Usa ture and rainfall. Results from AMOVA and GST gave a similar pat- 7 Lsa tern of high differentiation among populations coupled 2 Usa with limited gene flow among them. Our results were 0.53 0.50 0.47 0.45 0.42 similar to those reported for other Hypericum species (Quintana-Ascencio et al. 1998). The low gene flow Fig. 3. Dendrogram of the 7 analysed populations based on ΦST genetic distance. * 1, 2, ... populations code; **Sh, Usa and Lsa and the high differentiation among metapopulations – sub-humid, upper semi-arid and lower semi-arid bioclimates, has been explained mainly by founder events such as respectively. time since colonization (Jacquemyn et al. 2004), num- ber of initial founders in populations and their repro- ductive and dispersal potentials (Coleman & Abbott 3, 4, and 5 from the upper semi-arid zone are separated 2003). The ΦST value reported in our study is greater by the population 7 from the lower semi-arid zone. than those reported for outcrossing species dispersed Cluster analysis based on ΦST genetic distance by wind (Nybom & Bartish 2000). ΦST values among showed that the populations grouped into four distinct population pairs were high and highly significant sug- clusters (Fig. 3). The first three groups were each con- gesting that gene flow is impeded between them even at stituted by a single population (populations 2, 5, and a shorter distance (from 8 to 25 km). Pairwise genetic 7). The fourth group is formed by the populations 1 distances using ΦST between populations were not sig- (sub-humid bioclimate), 6 (lower semi-arid area), 3 and nificantly correlated with the corresponding geograph- 4 (both from the upper semi-arid zone). ical distances at all spatial scales. Thus, isolation by distance only could not explain the observed popula- Discussion tion genetic structure. The lack of correlation between the two sets of matrices indicates that the differentia- The eight used primers produced 166 RAPD markers, tion among populations is more likely caused by found- of which 153 were polymorphic. The high number of ing events. The differentiation among ecological groups markers revealed in our work may permit to estimate estimated by AMOVA was low (ΦCT = 0.004) indicat- correctly the genetic variation within and among popu- ing that most variation is within groups. This value is lations of Hypericum humifusum, despite some classical comparable to that reported for further short perennial disadvantages of RAPDs (e.g., dominance and biallelic species colonizing ecologically different habitats (Ward nature of RAPDs) (Aagaard et al. 1998). 2006). Hypericum species were expected to be charac- UPGMA cluster analysis based on Nei & Li’s ge- terized by a high level of genetic variation resulting netic distances showed that individuals from each pop- from the reproduction mode, gene flow and founder ulation clustered together in a single group indicating effects (Torimaru et al. 2003; Barcaccia et al. 2006; highly restricted gene flow among pairs of populations. Gaudeul 2006). Tunisian Hypericum humifusum pop- The dendrogram based on ΦST distance did not reveal ulations maintained a relatively high genetic variation clearly geographical/bioclimatic patterns of genetic dif- that could be attributed to the mixed mating system ferentiation. We detected a clear separation of popula- and the number of initial founders that differed genet- tions 6 and 7 belonging to the lower semi-arid biocli- ically in a population. Outcrossing species, especially mate. Besides, the populations from the upper semi- those with seed dispersed by wind, exhibited higher ge- arid (populations 2, 3, 4 and 5) were also significantly netic variation within than among populations (Ham- differentiated, and clustered in three separated groups. rick & Godt 1996). However, the vegetative reproduc- This finding indicates that differentiation among pop- tion and the low size of most H. humifusum populations ulations at a large scale could not be explained by eco- may lead to the reduction of variation within popula- logical differences or geographical location but should tions (Ward 2006). The levels of variation did not differ be attributed to a specific differentiation. significantly among populations, and were not related Knowledge of the distribution of genetic variation to the altitude. Thus, the adaptive potential, to buffer of populations plays an important role in the formula- consequences of this factor, is likely to be similar in tion of appropriate conservation strategies (Francisco- all populations. The level of genetic variation between Ortega et al. 2000). Populations of Hypericum humi- populations grouped according to the bioclimate is sig- fusum are severely affected by regular human distur- nificant. The upper semi-arid group showed the high- bance causing a significant destruction of sites. The in- est genetic diversity. Ecological factors such as rain- situ conservation is difficult to conceive because of in- fall, temperature, soil, and land-use practices affected tensive agricultural practices. Conservation of seeds in strongly the genetic variation within and among plant a gene bank should be the best way to ensure retention Genetic diversity of Hypericum humifusum 1009 of allelic and genotypic diversity. Therefore, to preserve Francisco-Ortega J., Santos-Guerra A., Kim S.C. & Crawford the maximum of diversity in the species, many popu- D.J. 2000. Plant genetic diversity in the Canary Islands: a 87: lations must be protected even at a small geographic conservation perspective. Am. J. Bot. 909–919. Gartner M., Muller T., Simon J.C, Giannis A. & Sleeman J.P. range. Collections should be done among rather within 2005. Aristoforin, a novel stable derivative of hyperforin, is a populations because of their high level of differentia- potent anticancer agent. Eur. J. Chem. Biol. 6: 171–177. tion. Populations from the upper semi-arid zone, ex- Gaudeul M. 2006. Disjunct distribution of Hypericum nummula- hibiting a high level of genetic variation should be first rium L. (Hypericaceae): molecular data suggest bidirectional colonization from a single refugium rather than survival in prospected. distinct refugia. Biol. J. Linn. Soc. 87(3): 437–447. Hamrick J.L. & Godt M.J.W. 1996. Effects of life history traits on genetic diversity in plant species. Philo. Trans. Roy. Soc. Acknowledgements LondonB 35(1): 1291–1298. Jacquemyn H., Honnay O., Galbusera P. & Roldán-Ruiz I. 2004. This research was supported by a grant of the Ministry of Blackwell Publishing Ltd. Genetic structure of the forest herb Scientific Research and Technology and the National In- Primula elatior in a changing landscape. Mol. Ecol. 13: 211– stitute of Applied Science and Technology (Research grant 219. 99/UR/09–10). Kubin A., Wierrani F., Burner U., Alth G. & Grunberger W. 2005. Hypericin- the facts about a controversial agent. Curr. Pharm. Design 11: 233–253. Lewontin R.C. 1972. The apportionment of human diversity. References Evol. Biol. 6: 381–398. Lodhi M.A., Ye G.N., Weeden N.F. & Reisch B.I. 1994. A sim- Aagaard J.E., Krutovskii K.V. & Strauss S.H. 1998. RAPDs and ple and efficient method for DNA extraction from grapevine allozymes exhibit similar levels of diversity and differentiation cultivars and Vitis species. Plant Mol. Biol. Rep. 12: 6–13. among populations and races of Douglas-fir. Heredity 81: 69– Mantel N. 1967. The detection of disease clustering and a gener- 78. alized regression approach. Cancer Res. 27: 209–220. Arnholdt-Schmitt B. 2000. RAPD analysis: a method to investi- Mayo G.M. 2003. Modes of reproduction in Australian popula- gate aspects of the reproductive biology of Hypericum perfo- tions of L. (St. John’s wort) revealed ratum.Theor.Appl.Genet.100: 906–911. by DNA fingerprinting and cytological methods. Genome 46: Barcaccia G., Arzenton F., Sharbel T.F., Varotto S., Parrini P. & 573–579. Lucchin M. 2006. Genetic diversity and reproductive biology Meral G. & Karabay N.U.¨ 2002. In vitro antibacterial activities in ecotypes of the facultative apomict Hypericum perforatum of three Hypericum species from west Anatolia. Turk. Elect. L. Heredity 96: 322–334. J. Biotech. (Special issue), pp. 6–10. Béjaoui A., Boulila A., Messaoud C., Rejeb M.N. & Boussaid M. Miral N. & Nabulsi I. 2003. Genetic diversity of almonds (Prunus 2010. Genetic diversity and population structure of Hyper- dulcis) using RAPD technique. Scientia Hort. 98: 461–471. icum humifusum L. (Hypericacae) in Tunisia and implication Nei M. & Li W.H. 1979. Mathematical model for studying genetic for conservation. Plant Biosystems 144(3):592-601. variation in terms of restriction endonucleases. Proc. Nat. Bonnet E. & van de Peer Y. 2002. zt: a software tool for simple Acad. Sci. USA. 76: 5269–5273. and partial Mantel tests. J. Stat. Software 7(10): 1–12. Nybom H. & Bartish I.V. 2000. Effects of life history traits and Carine M.A. & Christenhusz M.J.M. 2010. About this volume: sampling strategies on genetic diversity estimates obtained the monograph of Hypericum by Norman Robson. Phytotaxa with RAPD markers in plants. Persp. Plant Ecol. Evol. Syst. 4: 1–4. 3: 93–114. Coleman M. & Abbott R. J.2003. Possible causes of morphologi- Percifield R.J., Hawkins J.S., mc Coy J.A., Widrlechner M.P. & cal variation in an endemic Moroccan groundsel (Senecio leu- Wendel J.F. 2007. Genetic diversity in Hypericum and AFLP canthemifolius var. casablancae): evidence from chloroplast Markers for species-specific identification of H. perforatum L. DNA and random amplified polymorphic DNA markers. Mol. Planta Med. 73(15): 1614–1621. Ecol. 12: 423–434. Poschlod P., Dannemann A., Kahmen S., Melzheimer V., Bieder- Conforti F., Statti G.A., Tundis R., Bianchi A., Agrimonti C., mann H. & Mengel C. 2000. Genes in the landscape. Changes Sacchetti G., Andreotti E., Menichini F. & Poli F. 2005. Com- in central European land use and its impact on genetic diver- parative chemical composition and variability of biological sity of plants. S. Vegetationskunde 32: 111–127. activity of methanolic extracts from Hypericum perforatum Pottier-Alapetite G. 1979. Flore de la Tunisie, Angiospermes di- L. Nat. Prod. Res. 19(3): 295–303. cotylédones. Apétales-Dialypétales, I.O.R. Tunisie, 654 pp. Crockett S.L. & Robson N.K.B. 2011. and chemo- Poutaraud A. & Giradin P. 2008. Agronomic and chemical char- taxonomy of the genus Hypericum. Medicinal and Aromatic acterization of 39 Hypericum perforatum accessions between Plant Science and Biotechnology 5(Spec. Iss. 1): 1–13. 1998 and 2000. Plant Breed. 123(5): 480–484. C¨uneyt Y.T.C., Radušiené J., Ivanauskas L. & Janulis V. 2007. Quintana-Ascencio P.F., Dolan R.W. & Menges E.S. 1998. Hy- Variation of bioactive secondary metabolites in Hypericum pericum cumulicola demography in unoccupied and occupied origanifolium during its phenological cycle. Acta Physiol. Florida scrub patches with different time-since-fire. J. Ecol. Plant. 29: 197–203. 86: 640–651. Dagnelie P. 1975. Analyse statistique `a plusieurs variables. Reisch C., Poschlod P. & Wingendern R. 2003. Genetic differenti- Presses Agronomiques (eds), Gembloux (Belgium), 362 pp. ation among populations of Sesleria albicans Kit. Ex Schultes Dlugosch K.M. & Parker I.M. 2007. Molecular and quantitative (Poaceae) from ecologically different habitats in Central Eu- traits variation a cross the native range of the invasive species rope. Heredity 91: 519–527. Hypericum canariensis: evidence for ancient patterns of colo- Robson N.K.B. 2003. Hypericum botany, pp. 1–22. In: Ernst E. nization via pre-adaptation ? Mol. Ecol. 16(20): 4269–4283. (ed.), Hypericum.TheGenusHypericum,TaylorandFrancis, Emberger L. 1966. Une classification biogéographique des cli- London. mats. Recherches et Travaux des Laboratoires de Géologie, Robson N.K.B. 2006. Studies in the genus Hypericum L. (Clusi- Botanique et Zoologie, Faculty of the Science of Montpellier aceae). 1 Section 9. Hypericum series 2. Senanensia, subsec- (France), 7: 1–43. tion 2. Erecta and section 9b. Graveolentia. Syst. Biodiversity Excoffier L., Smouse P.E. & Quattro J.M. 1992. Analysis of 4: 19–98. molecular variance inferred from metric distances among Robson N.K.B. 2010a. Studies in the genus Hypericum L. (Glusi- DNA haplotypes: application to human mitochondrial DNA aceae). 5(1). Sections 10. Olympia to 15/16. Crossophyllum. restriction data. Genetics 131: 479–491. Phytotaxa 4: 5–126. 1010 A. Béjaoui et al.

Rohlf F.J. 1998. NTSYSpc version 2.0: User Guide. Applied Bio- van Rossum F. & Prentice H.C. 2004. Structure of allozyme vari- statistics Inc., Setauket. ation in Nordic Silene nutans (Caryophyllaceae): population Rout G.R. 2006. Evaluation of genetic relationship in Typhonium size, geographical position and immigration history. Biol. J. species through random amplified polymorphic DNA mark- Lin. Soc. 81: 357–371. ers. Biol. Plantarum 50(1): 127–130. van Tienderen P.H., de Haan A.A., van der Linden C.G. & Vos- SAS (statistical analysis system) 1990. SAS user’s guide: SAS man B. 2002. Biodiversity assessment using markers for eco- STAT, SAS BASIC. Version 6 fourth edition. SAS incl, Box logically important traits. Trends Ecol. Evol. 17(12): 577– 8000. Cary, NC 27512–8000, Cary: NC: SAS institut Inc. 582. Smelcerovic A., Verma V.M., Spiteller S., Syed M.A., Satish C.P. Ward S. 2006. Genetic analysis of invasive plant populations at & Ghulam N.Q. 2006. Phytochemical analysis and genetic different spatial scales. Biological Invasions 8: 541–552. characterisation of six Hypericum species from Serbia. Phy- Wright S. 1951. The genetical structure of populations. Ann. Eug. tochem 67: 171–177. 15: 323–354. Sreekumar V.B. & Renuka C. 2006. Assessment of genetic diver- Yeh F., Yang R. & Boyle T. 1999. Popgene, version 1.31. Mi- sity in Calamus thwaitesii BECC. (Arecaceae) using RAPD crosoft window-based freeware for population genetic analy- markers. Biochem. Syst. Ecol. 34: 397–405. sis. University of Alberta, Edmonton. Tanaka N. & Takaishi Y. 2006. Xanthones from Hypericum chi- Young A., Boyle T. & Brown T. 1996. The population genetic con- nense.Phytochem67: 2146–2151. sequences of habitat fragmentation for plants. Trends Ecol. Taylor-Grant N. & Soliman K.M. 1999. Detection of polymor- Evol. 11: 413–418. phic DNA and taxonomic relationships among 10 wild peren- Zhang Y., Yang J. & Rao G.Y. 2005. Genetic diversity of an am- nial soybean species using specific and arbitrary nucleotide phicarpic species, Amphicarpaea edgeworthii Benth. (Legu- primers. Biol. Plant 42(1): 25–37. minosae) based on RAPD markers. Biochem. Syst. Ecol. 33: Torimaru T., Tomaru N., Nishimura N. & Yamamoto S. 2003. 1246–1257. Clonal diversity and genetic differentiation in Ilex leucoclada M.patchesinanold-growthbeechforest.Mol.Ecol.12: 809– Received February 26, 2010 818. Accepted June 29, 2011