Genetic variability of Tunisian wild strawberry tree (Arbutus unedo L.) populations interfered from isozyme markers

Scientia Horticulturae 146 (2012) 92–98

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Genetic variability of Tunisian wild strawberry tree (Arbutus unedo L.) populations interfered from isozyme markers Malek Mhamdi Takrouni ∗ , Imen Ben El Haj Ali, Chokri Messaoued, Mohamed Boussaid National Institute of Applied Sciences and Technology (INSAT), Department of Biology Laboratory of Plant Biotechnology, Centre Urbain Nord, BP 676, 1080 Tunis Cedex, Tunisia

a r t i c l e

i n f o

Article history: Received 28 June 2012 Accepted 3 August 2012 Key words: Arbutus unedo Genetic diversity Isozymes Natural populations Ecological groups Conservation

a b s t r a c t In Tunisia, Arbutus unedo populations are severely destroyed due to deforestation and over-collecting. The species occurs in small scattered populations decreasing progressively in size. Yet, there is a lack of information’s regarding the amount of genetic diversity and its repartition for this resource. In this work, we analyzed the polymorphism of six isozymes in order to assess genetic variability and structuring of 15 natural populations prospected in three geographical areas. The analysis of the level and the distribution of the genetic diversity in this species might help in its conservation. Out of the 13 loci detected for all populations and isozymes analyzed, 4 loci were polymorphic. Allelic frequencies differed according to populations and particular alleles characterized ecological groups. A high genetic diversity within populations (Ap = 2.2; P = 63.33%) was observed. A relatively low level of differentiation (FST = 0.031) coupled with a high gene flow among populations (Nm = 6.81) were revealed. The differentiation of populations within the same bioclimate group was substantial and the upper semi-arid populations showed the highest differentiation (FST = 0.093). The relationship between FST and geographic distance matrices was not significant, indicating that the genetic structure among populations is not affected by geographic barriers but it is rather related to ecological factors such as altitudes and rainfall. Nei’s (1978) genetic distances among pairs of populations were low (0.001–0.030). The UPGMA cluster based on these distances showed three sub-clusters. Population groupings occur without evident relationship to bioclimates or geographic regions indicating that differentiation occurs at a local space scale. The species conservation strategies (in situ or ex situ) and the selection of genotypes should take into account the genetic diversity level within populations. © 2012 Elsevier B.V. All rights reserved.

1. Introduction Arbutus unedo L. is a perennial diploid (2n = 2x = 26) shrub or small tree belonging to the Ericaceae family. The genus Arbutus includes about 20 species from which A. unedo, commonly known as strawberry tree, is the most interesting species economically (Gomes and Canhoto, 2009). The species is typical to the Mediterranean climate (Celikel et al., 2008). It is one of the most component of oak and pine maquis and forests, growing at altitudes ranged from 400 to 1200 m in heavy clay and dry soils, on siliceous or decarbonated substrata (Castell et al., 1994; Torres et al., 2002; Ozcan and Haciseferogullari, 2007). The species can also grow on alkaline and relatively acidic soils. The species (1.5–3 m tall) can occasionally reach up 9–12 m in height (Tutin et al., 1981; Seidemann, 1995). The bark is colored. The leaves are alternate, simple, short-stalked and toothed. The flowers are bell-shaped, with recurved lobes, white and honey-scented.

∗ Corresponding author. Tel.: +216 71 232 052; fax: +216 71 232 052. E-mail address: [email protected] (M. Mhamdi Takrouni). 0304-4238/$ – see front matter © 2012 Elsevier B.V. All rights reserved. http://dx.doi.org/10.1016/j.scienta.2012.08.005

The fruits are globose berries, ripening from yellow to scarlet and deep crimson and matured in autumn. Since the fruits take about 12 months to ripen, the tree carries mature fruits and flowers at the same time. The strawberry tree is a valuable ornamental plant due to its attractive red fruits in the fall and winter, and pinkish-white flowers in the fall (Celikel et al., 2008). The flowering and fructification process extends from October to February (Mhamdi Takrouni, 2011). A. unedo L. is an autogamous plant. It reproduces sexually via seeds and vegetatively through root suckers. It is believed as a long distances dispersal species and seeds are dispersed by gravity and animals mostly birds and mammals (Debussche and Isenmann, 1989; Flynn et al., 2006; Aparicio et al., 2008). In folk medicine, the species is used for its antiseptic, diuretic laxative and vascular properties (Pallauf et al., 2008). Fruits are processed into jam, wine, distillates and liqueurs (Ayaz et al., 2000; Alarcão-Silva et al., 2001). From an ecological perspective, A. unedo is also an interesting plant. It contributes to maintain the biodiversity of the fauna, helps to stabilize soils avoiding erosion, has a strong regeneration capacity following fires, and survives quite well in poor soils (Gomes and Canhoto, 2009). Today uses of the strawberry tree are a result of traditional habits rather than of

M. Mhamdi Takrouni et al. / Scientia Horticulturae 146 (2012) 92–98

economics because of heterogeneity of its plants, the lack of selection and varietal identification (Jaradat, 1995). The breeding programs to obtain A. unedo cultivars with high fruit quality have rarely been attempted. Improvement works were mainly made in China (Songlin et al., 1995; Jihua et al., 1997; Cai-Huang, 1997), in Italy (Mulas and Deidda, 1998), in Turkey (Karadeniz et al., 1996, 2003; Gozlekci et al., 2003; Seker et al., 2004) and in Greece (Smiris et al., 2006). In Tunisia, A. unedo populations grow wild in different bioclimatic zones extending from the lower humid to the upper semi-arid bioclimate, in three isolated geographic regions (Cap Bon, North West and Tunisian Dorsal Mountain) (Mhamdi Takrouni and Boussaid, 2010). The species becomes scarce in the semi-arid area. In the Cap Bon, populations are found in several coastal areas (e.g. Korbous and Zaouiet El Mgaiez), on calcareous or acid soils, and at altitudes varying from 400 to 600 m. The average of annual rainfall varied from 400 to 600 mm (Nabli, 1995). All populations, mainly in the Cap Bon and Dorsal Mountain, are severely destroyed by deforestation and coal mining during the last decades (Mhamdi Takrouni, 2011). At present, sites are fragmented except for several large habitats in the North West where populations occur into local populations with a large size. Habitat fragmentation and the decreasing of the population’s size increase genetic drift impede gene flow and elevate the genetic differentiation among populations. The aim of this study is to assess the genetic diversity within and among Tunisian A. unedo populations according to the conditions of their ecological development using isozymic markers. Isozymes are codominants, neutral or nearly neutral and have been widely used to assess plant genetic diversity and population structure (Weeden and Wendel, 1989; Liu et al., 2006; Ben El Hadj Ali et al., 2011). This study is a complementary part of a wider work including the genetic variations of populations (via morphological and molecular markers) (Mhamdi Takrouni and Boussaid, 2010; Mhamdi Takrouni, 2011) in order to elaborate preservation and improvement programs. Our previous studies performed using RAPD markers showed that Tunisian A. unedo populations maintain a high variation within populations and a low genetic differentiation among them (Mhamdi Takrouni and Boussaid, 2010). 2. Materials and methods 2.1. Plant material and sampling Fifteen A. unedo populations in the whole distribution area of the species in Tunisia (North West, Cap Bon and Tunisian ridge) are chosen from different bioclimatic zones (lower-humid, sub-humid and upper semi-arid) according to Emberger’s (1966) Q2 pluviothermic coefficient. The main ecological features and the geographic location of the populations are reported in Fig. 1 and Table 1. In each population, 20 individuals were randomly sampled over 10 ha area. Samples were collected at a distance exceeding 20 m from each other to avoid collecting multiple plants from the same parent. From each individual, branches were collected, placed on ice in plastic bags and taken to the laboratory for isozyme analysis. 2.2. Enzyme analysis Three hundred milligrams of leaves from each sample were ground with liquid nitrogen. After grinding we add 1 ml of Tris–HCl (0.1 M, pH 7.5) mixed with 1% (v/v) ␤-mercaptoethanol, 1.5% (w/v) bovine serum albumin (BSA), 10 ␮L EDTA and 50 mg polyvinylpyrrolidone 40,000. The homogenate was centrifuged for 25 min at 12,000 rpm and at 4 ◦ C. The supernatant was adsorbed in Whatman no. 3 filter paper then introduced into gels.

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Fig. 1. Map of Tunisia: geographical distribution of the analyzed populations of Arbutus unedo. () sub-humid; () lower-humid; () upper semi-arid. 1, 2, 3, . . ., 15: populations code; (䊉) Great towns.

Two gel-buffer systems using 13% starch gels were used to assay six enzyme systems: phosphoglucomutase (Pgm, E.C. 2.7.5.1), phosphoglucoisomerase (Pgi, E.C. 5.3.1.9), malate dehydrogenase (Mdh, E.C. 1.1.1.37), were assayed using a histidine–citrate gel and electrode buffer system at pH 6.5 and a gel buffer dilution of 1:3 (0.065 mol/L l-histidine and 0.02 mol/L citric acid). Alcohol dehydrogenase (Adh, E.C. 1.1.1.1), glutamate oxaloacetate transaminase (Got, E.C. 2.6.1.1) and esterase (Est, E.C. 3.1.1) were assayed using lithium-borate gel and electrode buffer system at pH 8.3 (0.192 mol/L boric acid and 0.038 mol/L lithium hydroxide) and a gel buffer dilution 1:9. Both gels were run at a constant current of 20 mA (at 4 ◦ C), the histidine–citrate for 8 h and the lithium-borate for 6 h. Staining protocols were carried out followed standard methods (Weeden and Wendel, 1989). 2.3. Data analysis Zymograms were genetically interpreted according to standard principles (Wendel and Weeden, 1989). Loci were sequentially numbered (1, 2, 3, . . .) in decreasing order of the anodal mobility. Alleles at a locus were coded alphabetically with the most anodally migration allozyme designated “a”. All enzymes were interpreted as dimeric enzymes except for Pgm, Lap and Est which were monomeric according Wendel and Weeden (1989). The genetic variation within populations or within ecological groups (each group includes populations from the same bioclimate) was estimated using allele frequencies, the percentage of polymorphic loci (P), the mean number of alleles per polymorphic 1 locus (Ap), and averages of the observed (Ho ) (Ho = (1/N) i=1 Hi ;

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Table 1 Bioclimatic and geographic situations of the fifteen Tunisian Arbutus unedo populations analyzed. Bioclimatic zonea

Site

Lh

Babouche Amdoun El Feija Ain Soltane Tbeinia Sejnene Cap Negro Bellif

Sh

Usa

Code 1 2 3 4 5 6 7 8

Geographic region

Q2 b coefficient

Altitudes (m)

Rainfall (mm/year)

Latitude (N)

Longitude (E)

Nord Ouest

97.5 99.5 96.5 96.5 97.5 93.4 97.61 97.3

800 800 800 800 800 450 600 600

1100 1250 1100 1100 1100 1100 1250 1250

36◦ 42 36◦ 46 36◦ 48 36◦ 50 36◦ 42 36◦ 40 36◦ 41 36◦ 41

9◦ 30 8◦ 99 8◦ 18 8◦ 17 9◦ 30 10◦ 23 10◦ 25 10◦ 27

420 400 400 400 75

550 550 550 550 550

36◦ 40 36◦ 60 36◦ 80 36◦ 50 36◦ 57

10◦ 13 10◦ 41 10◦ 22 10◦ 35 10◦ 45

890 475

450 450

35◦ 36 36◦ 35

9◦ 00 8◦ 66

Abderahmane Jeb. Mt.c Rtiba Kef Errend Korbous Zaouiet El Mgaiez

9 10 11 12 13

Cap Bon

65.61 63.61 64.61 64.61 62.61

Kesra Sekiet Sidi youssef

14 15

Tunisian Dorsale High Tell

45.5 49.75

a

Bioclimatic zone: Lh: lower humid; Sh: sub humid; Usa: upper semi arid. Q2 : Emberger’s pluviothermic coefficient (1966). Q2 = 2000P/(M2 − m2 ) where P is the mean of annual rainfall (mm). M (K) is the mean of maximal temperatures for the warmest month (July) and m is the mean of minimal temperatures for the coldest month (February). P, M and m values for each site were calculated for the period from 1953 to 2008 (data provides by the Tunisian National Institute of Meteorology). c Jeb. Mt.: Jebel Mountain. b

N is the total number of studied loci that they be monomorphic or polymorphic and Hi is the heterozygosity  at the ith locus) and expected heterozygosity He (He = 2n(1 − pi2 )/(2n − 1); pi is the frequency of the ith allele and n is the number of individuals in the sample), under Hardy–Weinberg equilibrium (Nei, 1978). Calculations were made using Biosys software package (Swofford and Selander, 1981). Departure from the expected mean heterozygosity under HW equilibrium, for each locus and each population, was assessed by chi-square tests, with Levene’s (1949) corrections. The FIS inbreeding coefficient was calculated according to the formulae FIS = 1 − Ho /He where Ho and He are average of observed and expected heterozygosities respectively. Significant deviation of FIS from zero was tested after randomization procedures (Goudet, 1995). The genetic differentiation among populations or among ecological groups was estimated by Wright’s (1965) F-statistics: FIT (total inbreeding) and FST (subdivision among populations) and FIS (inbreeding within populations), according to Weir and Cockerham (1984) estimates. Calculations were made using the program FSTAT versions 1.2 and 2.9.3 (Goudet, 1995, 2001). Means and standard errors over loci were obtained by jackknifing over loci. The significance of indices was tested using permutations. Mantel’s tests (Mantel, 1967) were used to determine whether the matrix of genetic distances (FST ) was correlated with those of altitudes and Emberger’s Q2 pluviothermic coefficient using the TFPGA 1.3 program (Miller, 1997). Gene flow (Nm) among populations was estimated by the average of the effective number of migrants exchanged between populations for each generation using Crow’s and Aoki’s correction (Crow and Aoki, 1984), [Nm = [(1/FST ) − 1]/4˛, where ˛ = (n/(n − 1))2 , and n being the number of populations]. Isolation by distance was evaluated among populations using the entire dataset, according to Rousset (1997), by regressing FST /(1 − FST ) against the natural logarithm of geographic distance. The significance of the correlation between the two matrices was evaluated by Mantel’s test (Mantel, 1967) using the program TFPGA 1.3 (Miller, 1997). The significance of the correlation was tested after 999 permutations. The divergence among populations was also estimated by Nei’s (1978) genetic distances calculated for all pairs of populations and by the construction of the dendrogram from these distances using the unweighted pair group method with arithmetic averages (UPGMA).

3. Results 3.1. Genetic diversity Four out of the six surveyed isozymes were polymorphic (Table 2). Thirteen loci were detected; nine out of them were monomorphic. Among the polymorphic loci, the number of alleles per locus ranged from two (Adh-1 and Mdh-1) to five (Pgi-1). Rare alleles according to a population were revealed with frequencies ranging from 0.03 to 0.25 (i.e. Mdh-1b in populations 1–3, 9, 11, 15 and Pgi-1a in populations 3, 4, 7, 9, 10, 13–15). Some alleles were limited to a few populations (i.e. Pgi-1d was observed only in the populations 1, 3 and 6 from lower humid zone). Pgm-1c is absent in all the populations growing in the sub-humid zone (Table 2). A high genetic diversity within populations was revealed (Table 3). The number of alleles per polymorphic locus (Ap) varied from 2 (populations 2, 4, 5, 6, 8, 9, 13 and 14) to 2.8 (populations 3 and 15) with an average of 2.2. The mean percentage of polymorphic loci (P%) over all populations was 63.33%. The observed (Ho ) and expected (He ) heterozygosities were 0.14 and 0.16, respectively. At the ecological group level, the percentage of polymorphism varied from 62.5% (lower-humid and upper semi-arid zones) to 65% (sub-humid zone) (Table 3). A deficiency of heterozygotes was observed by the comparison of FIS , the inbreeding coefficient measuring the deviation of the genotypic proportions from HW equilibrium at the population level (Table 3). Four populations (populations 2, 5, 7 and 14) out of fifteen exhibited significant (p < 0.05) departures from Hardy–Weinberg expectations. For all populations, FIS values varied widely among loci and the mean value was significantly different from zero (FIS = 0.070) (Table 4). A high deficiency of heterozygosity was observed for Pgi-1. At the ecological level, the deficiency of heterozygote was more important for populations belonging to upper semi-arid (FIS = 0.247) bioclimate (Table 4). Populations of those stages develop on maquis destructed by human activities. 3.2. Genetic structure FST values at the loci level varied from 0.007 (Pgm-1) to 0.045 (Pgi-1) (Table 4). A relatively low genetic structure among populations (FST = 0.031) according to Wright’s (1965) estimates and a high level of gene flow (Nm = 6.81) were observed. The differentiation among population pairs ranged from 0.001 (among populations

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Table 2 Allelic frequencies for the polymorphic loci in the 15 populations of Arbutus unedo grouped in three bioclimatic groups. Bioclimatic group

Lh

Population

1

2

0.20 0.70 0.05 0.05

0.25 0.75

0.93 0.08

Pgi-1 a b c d e Pgm-1 a b c Mdh-1 a b Adh-1 a b

Sh 3

4

5

6

0.05 0.03 0.85 0.05 0.03

0.08 0.03 0.90

0.03 0.90 0.08

0.05 0.88 0.03 0.05

0.90 0.05 0.05

0.91 0.07 0.02

0.95

0.95 0.05

0.95 0.05

0.93 0.08

0.95 0.05

1.00

1.00

1.00

1.00

0.95 0.05

7

8

0.18

Usa

9

10

11

12

0.03

0.03 0.92

0.08 0.85

13

14

15

0.03

0.25

0.91

0.56

0.03 0.08 0.85

0.73

0.07 0.86

0.90

0.03 0.08 0.88

0.10

0.07

0.08

0.03

0.05

0.08

0.06

0.19

0.05

0.90 0.10

0.88 0.08 0.05

0.88 0.12

0.95 0.05

0.88 0.08

0.90 0.10

0.95 0.05

0.94 0.06

0.91 0.09

0.83 0.10 0.08

1.00

1.00

0.98 0.03

1.00

0.95 0.05

1.00

0.98 0.03

1.00

1.00

1.00

0.98 0.03

0.82 0.18

1.00

1.00

0.95 0.05

1.00

0.93 0.08

0.95 0.05

0.98 0.03

0.97 0.03

0.97 0.03

0.92 0.08

0.05

Lh: lower humid; Sh: sub humid; Usa: upper semi arid.

Table 3 Genetic diversity parameters for populations of Arbutus unedo. Population code

N

Ap

P%

Ho

He

FIS

1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 Mean

20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20(0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0) 20 (0)

2.3 (0.6) 2.0 (0.4) 2.8 (0.9) 2.0 (0.4) 2.0 (0.7) 2.0 (0.5) 2.3 (0.5) 2.0 (0.4) 2.0 (0.4) 2.5 (0.6) 2.3 (0.3) 2.0 (0.4) 2.0 (0.4) 2.0 (0.4) 2.8 (0.5) 2.2 (0.49)

75 75 50 75 75 50 50 50 75 75 75 50 50 50 75 63.33

0.16 (0.09) 0.14 (0.05) 0.15 (0.06) 0.10 (0.04) 0.12 (0.04) 0.11 (0.07) 0.20 (0.11) 0.15 (0.07) 0.10 (0.04) 0.15 (0.05) 0.13 (0.03) 0.11 (0.07) 0.09 (0.04) 0.13 (0.06) 0.20 (0.06) 0.14 (0.06)

0.18 (0.10) 0.18 (0.08) 0.14 (0.06) 0.10 (0.04) 0.15 (0.06) 0.10 (0.06) 0.18 (0.06) 0.14 (0.06) 0.10 (0.04) 0.15 (0.05) 0.12 (0.03) 0.10 (0.06) 0.09 (0.04) 0.20 (0.13) 0.20 (0.06) 0.16 (0.06)

0.095ns 0.237* 0.073ns −0.045ns 0.227* −0.075ns −0.102* −0.09ns −0.047ns 0.013ns −0.05ns −0.058ns −0.032ns 0.415* −0.028ns 0.07

Within bioclimate Lh Sh Usa

20 (0) 20 (0) 20 (0)

2.17 (0.54) 2.16 (0.42) 2.40 (0.45)

62.5 65 62.5

0.15 (0.07) 0.12 (0.05) 0.17 (0.06)

0.15 (0.07) 0.11 (0.04) 0.20 (0.09)

0.075 −0.038 0.208

Standard errors are in parentheses; N: mean sample size per locus; Ap: mean number of alleles per polymorphic locus; P%: percent of polymorphic loci; Ho : observed heterozygosity; He : expected heterozygosity; FIS : inbreeding coefficients. Lh: lower humid; Sh: sub humid; Usa: upper semi arid. * Significant at p < 0.05 after 1800 permutations. Table 4 Wright’s F statistics (FIT , FST , FIS ) for each locus for all populations, and within and among bioclimates. Locus

FIT

FST

FIS

Pgi-1 Pgm-1 Mdh-1 Adh-1 All populations Within bioclimate Lh Sh Usa Mean Among bioclimate Lh–Sh Lh–Usa Sh–Usa Lh–Sh–Usa

0.166 (0.092)** −0.082 (0.009)ns −0.021 (0.007)ns 0.192 (0.183)** 0.098 (0.095)**

0.045 (0.021)** −0.007 (0.005)ns 0.007 (0.009)ns 0.044 (0.034)** 0.031 (0.020)**

0.125 (0.079)** −0.074 (0.009)ns −0.028 (0.01)ns 0.149 (0.155)ns 0.070 (0.077)*

0.086 (0.069)* −0.04 (0.017)ns 0.335 (0.298)** 0.127 (0.128)**

0.03 (0.016)** −0.011 (0.004) ns 0.093 (0.067) ** 0.037 (0.029)**

0.056 (0.056)ns −0.028 (0.019)ns 0.247 (0.249)* 0.092 (0.108)**

0.014 (0.01)* 0.014 (0.01)* 0.043 (0.03)* 0.014 (0.011)**

0.131 (0.108)** 0.027 (0.017)** 0.092 (0.126)ns 0.089 (0.088)**

Standard errors in parentheses. * Significant at p < 0.05. ** Highly significant at p < 0.01 after 1800 permutations. ns Not significant at p > 0.05.

Sejnene and Sekiet Sidi Youssef) to 0.116 (between populations Tbeinia and Kesra) (Table 5). The Mantel’s test did not show a significant correlation between genetic distance (FST ) and geographic distance matrices (r = 0.0025; p = 0.47 > 0.05 after 999 permutations). However, a significant correlation was found between FST and altitude (r = 0.176; p = 0.041 < 0.05 after 999 permutations) and between FST and Emberger’s Q2 coefficient (r = 0.100; p = 0.046 < 0.05 after 999 permutations) matrices. Nei’s (1978) genetic distance values (D) between pairs of populations were low, and varied from 0.001 (between populations 3 and 6 from the lower-humid bioclimate and among populations 11 and 13 growing in the sub-humid area) to 0.030 (between populations 5 and 14 from the lower humid and the upper semi-arid, respectively) (Table 5). The UPGMA phenogram based on these distances showed three population groups without clear clustering according to bioclimatic zones or/and geographical distances (Fig. 2). The first one is constituted by the populations 1 and 2 belonging to the lower-humid zone. Populations 3, 4, 6, 8, 9, 10–13 and 1, from different bioclimates, formed the second group. The

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Fig. 2. Cluster analysis for the 15 populations of Arbutus unedo based on Nei’s (1978) genetic distances.

last sub-cluster includes populations 7 and 14 from the sub-humid and the upper semi-arid zones, respectively. 4. Discussion Tunisian A. unedo showed a high genetic diversity as estimated by the percentage of polymorphic loci (P = 63.33%) and the mean number of alleles per polymorphic locus (Ap = 2.2). The diversity level was comparable with that reported previously for forest species with similar life history such as oak and pine (Toumi and Lumaret, 2001; Fady et al., 2003) and for other wild Mediterranean species (Messaoud et al., 2006; Ben El Hadj Ali et al., 2011). Similar results were obtained for Tunisian A. unedo using RAPD’s (Mhamdi Takrouni, 2011; Mhamdi Takrouni and Boussaid, 2010). The high genetic variation within population or within ecological group could be explained by seeds and pollen dispersion between populations and the size of population habitat before fragmentation (Hamrick and Godt, 1989). The average of the observed heterozygosity (Ho = 0.140) is lower than that expected under the Hardy–Weinberg equilibrium (He = 0.160). Our values are higher than that reported by Hamrick and Godt (1989) for the perennials plants with large geographic distribution (Ho = 0.120) and comparable to that found by Hamrick et al. (1992) for forest trees populations (Ho = 0.148). The level of the genetic diversity varied according to populations and bioclimates. Several populations of Tunisian A. unedo showed high variation and excess of heterozygosity (9/15). The high level of heterozygosity could be explained by seeds and pollen migration between populations (Mesléard and Lepart, 1991) and the persistence of multiple individuals through generations issued from large populations before fragmentation (Hamrick and Godt, 1989; Young et al., 1996). However a deficit of heterozygotes was observed for populations Kesra (upper semi-arid), Amdoun and Tbeinia (lowerhumid) characterized by a high level of habitat fragmentation and a low rate of regenerated individuals from seeds. The restricted seed germination associated to the high rate of homozygotes in those populations may lead to a decrease in the species adaptive

potentialities to natural local environment changes (Reisch et al., 2003). The degree of polymorphism observed in A. unedo populations was relatively low compared to other long-lived plants using isozymes (Bakshi and Konner, 2011) or SSR’s (Breton et al., 2006; Belaj et al., 2007). These results are concordant to those found in our previous works for A. unedo populations using RAPD markers (Mhamdi Takrouni, 2011; Mhamdi Takrouni and Boussaid, 2010). This low level of variation could have resulted from inbreeding dictated by both the selfing mating system and the vegetative reproduction mode. Selfing taxa were believed to have less variation within a population than outcrossers (Godt et al., 2001). The genetic drift, occurring as a result of restriction of the species to small isolated populations and the difficulty of A. unedo to propagate by seeds (Mereti et al., 2003) might also in part account for the relative low level of the genetic diversity found within populations. A relatively low genetic structure coupled with a high gene flow among populations were detected (FST = 0.031; Nm = 6.81). The highest genetic structure was observed between the lower humid population 4 (Tbeinia) and the upper semi-arid population 14 (Kesra) geographically distant by 112 km. These populations were separated by forest barriers (Pinus halepensis and Quercus suber forests). The differentiation among populations 4 (from the lower humid zone) and 14 (from the upper semi-arid area) also was high. The observed FST value is similar to that expected for autogamous plants (Raspe and Jacquemont, 1998) and close to forest tree average (Hamrick and Godt, 1996; Austerlitz et al., 2000). The differentiation among-populations of A. unedo could have resulted from many factors such as the length of the vegetative period of the species, recent fragmentation of a large initial population and the long-distance seed dispersal facilitated by intervention of frugivores mainly birds (Aparicio et al., 2008; Debussche and Isenmann, 1989). Thus, the species should be less sensitive to habitats fragmentation than other selfing species lacking this possibility. The long-distance seed dispersal influences the colonization of new habitats, the migration capacity of the species and the spatial genetic structuring of populations (Aparicio et al., 2008). As in many selfing species, the differentiation among populations of Tunisian A. unedo was not related to geographical distance (Hamrick and Godt, 1989). Thus, genetic structure was not significantly affected by geographic barriers. This characteristic is always observed for wild species with a differentiation rate lower than 10% (Zanetto and Kremer, 1995) and for many selfing species with long-distance seed dispersal (Hamrick and Godt, 1996). However, it is related to ecological factors such as altitudes and rainfall influencing flowering time, repining longevity, seed production and germination. Our personnel observations suggest that flowering is asynchronous between bioclimatic regions and that the number of seeds by fruit differs between populations according to their appurtenance (Mhamdi Takrouni, 2011). Aradhya et al. (1993) reported also, that the distribution of genetic variation along altitudinal gradients is known to be the result of the interplay of gene flow and genetic drift. Nei’s (1978) genetic distances were low (D = 0.008) indicating a high genetic similarity between populations due to the high number of similar alleles with comparable frequencies. Our cluster analysis did not show a relationship between population groupings and bioclimates and/or geographic distances indicating a recent fragmentation of a large initial population and a local differentiation within bioclimates. The Northern west populations 14 and 15 from the upper semi-arid zone clustered into two distinct clusters. The populations from lower-humid also gathered clearly in different groups composed of populations from different origins. Populations from contiguous bioclimates (lowerhumid/sub-humid or upper semi-arid/lower-humid) were less differentiated than that from discontinuous ones.

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97

Table 5 FST values (above the diagonal) and ) genetic distances (below the diagonal) among pairs of populations. Population 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15

1 0.002 0.007 0.012 0.018 0.007 0.010 0.007 0.010 0.009 0.011 0.006 0.012 0.019 0.009

2

3

4

−0.019

0.09 0.071

0.061 0.059 0.008

0.009 0.013 0.020 0.009 0.014 0.009 0.012 0.009 0.012 0.008 0.014 0.027 0.009

0.003 0.011 0.001 0.005 0.003 0.002 0.003 0.002 0.002 0.002 0.020 0.004

0.007 0.004 0.009 0.005 0.003 0.002 0.003 0.003 0.002 0.024 0.005

5 0.077 0.084* 0.042 0.025 0.009 0.017 0.006 0.009 0.005 0.005 0.007 0.006 0.030 0.007

6

7

8

9

10

11

12

13

14

15

0.026 0.036* −0.011 0.014 0.044

0.031 0.047 −0.002 0.037 0.073 0.032

0.020 0.029 −0.006 0.015 0.016 −0.015 0.028

0.045 0.053 −0.013 0.007 0.043 −0.006 0.029 0.004

0.027 0.025 −0.002 −0.006 0.003 −0.007 0.028 −0.016 0.008

0.045 0.049 −0.003 0.005 0.011 −0.013 0.042 −0.015 −0.009 −0.014

0.027 0.038 −0.008 0.002 0.024 −0.014 0.034 −0.011 −0.011 −0.007 −0.011

0.055 0.065* −0.005 −0.008 0.020 −0.012 0.035 −0.007 −0.016 −0.007 −0.018 −0.018

0.058* 0.090* 0.051 0.114* 0.116* 0.104 −0.002 0.083* 0.103* 0.088* 0.113* 0.099* 0.109*

0.021 0.019 −0.003 0.009 0.010 −0.001 0.019 −0.013 0.013 −0.021 −0.008 0.004 0.005 0.070

0.008 0.002 0.002 0.002 0.002 0.002 0.002 0.023 0.003

0.008 0.008 0.009 0.010 0.008 0.008 0.006 0.008

0.003 0.002 0.002 0.002 0.002 0.021 0.002

0.004 0.002 0.002 0.002 0.023 0.006

0.002 0.002 0.002 0.023 0.002

0.002 0.002 0.026 0.003

0.001 0.021 0.004

0.024 0.005

0.022

Numbers for without stars are not significant at p > 0.05. * Significant at p < 0.05 after 1800 permutations.

5. Conclusions

Acknowledgments

The analysis of the genetic diversity of A. unedo provides information that should be of benefit for conservation programs and selection of genotypes. The ability of populations to respond to selection forces is related to the level of genetic variation available (Reed, 2007). According to our estimates of genetic diversity parameters, the majority of populations showed a high variation suggesting that populations constitute a valuable germplasm for conservation and improvement work. All populations, mainly in the Northwestern part of the country and Tunisian Dorsal Mountain, were represented by few individuals and were severely destroyed due to deforestation and over-collecting for coal mining during the last decades. The habitat fragmentation and the decreasing of the population’s size increase genetic drift. Conservation action is urgently required to preserve these populations by reducing anthropic pressures affecting both A. unedo and associated species. The majority of the total genetic diversity resided within populations. Thus, the ex situ conservation mainly should be based on the collection of the maximum number of individuals within, rather than among, populations in each ecological group. A. unedo being a selfing species, the sampling should take into account these criteria. Individuals within populations (i.e. populations 1, 4, 9 and 11) were highly heterogeneous and the collection of maximum individuals would be necessary for capturing most diversity. A low rate of heterozygotes was observed particularly in Dorsal and Higher Tell populations. Substantial efforts for conservation in situ must be made. Individuals issued from seeds must be introduced in some disturbed populations of upper semi-arid (in High Tell and Tunisian Dorsal) to avoid increasing deficiency of heterozygosities. Factors that favored seed germination and individual regeneration from seedling should be evaluated. That is a valuable factor to increase population size and genetic variability. Then, populations exhibiting rare alleles should be preserved in each geographic group. Thus, populations such as those of the Babouche, El Feija and Sejnene should be better protected. The analysis of chemical composition variation and of some reproductive biological traits of the species might lead to a better population preservation strategy. Furthermore, isozyme and chemical data should be related to those of the molecular markers variation (Mhamdi Takrouni and Boussaid, 2010) to ensure more efficiency in the management and the present use of populations. This research is in progress.

This research was supported by a grant of the Ministry of Scientific Research and Technology and the National Institute of Applied Science and Technology (Research grant 99/UR/09-10).

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