Genetic diversity within and among Pinus pinaster populations: comparison between AFLP and microsatellite markers

Genetic diversity within and among Pinuspinaster populations: comparison between

AFLP and microsatellite markers

STEÂ PHANIE MARIETTE*, DAVID CHAGNEÂ , CEÂ LINE LEÂ ZIER, PATRICK PASTUSZKA,ANNIE RAFFIN, CHRISTOPHE PLOMION & ANTOINE KREMER

INRA, Equipe de GeÂneÂtique et AmeÂlioration des Arbres Forestiers, BP45, F-33610 Cestas, France

Twenty-three populations of Pinus pinaster (13 Aquitaine populations and 10 Corsican populations)were analysed at three microsatellite loci and 122 AFLP loci. The aims of the study were: (i) tocompare levels of within-population and among-population diversity assessed with both kinds ofmarkers; (ii) to compare Aquitaine and Corsican provenances of P. pinaster; and (iii) to know if bothmarkers gave the same information for conservation purposes. Classical population genetics statisticswere estimated and the ranking of populations obtained using di�erent markers and/or parameterswere compared by computing Spearman's rank correlations. Even though microsatellites showed ahigher within-population diversity, they showed the same level of di�erentiation as AFLP markers.Moreover, both markers also showed a higher genetic diversity in the Aquitaine provenance and ahigher di�erentiation among Corsican populations. AFLPs and microsatellites gave di�erentpopulation diversity rankings. Consequently, the results do not support the potential populationidenti®cation within each provenance for conservation purposes.

Keywords: AFLP, genetic diversity, genetic di�erentiation, microsatellite, Pinus pinaster.

Introduction

Di�erent marker systems are currently available formonitoring genetic diversity in natural populations.Examples of markers with contrasting properties areAFLP markers (Vos et al., 1995) and microsatellites(Tautz, 1989). First, AFLPs are considered to bedominant and biallelic, whereas microsatellites arecodominant and usually reveal a high number of alleles.Secondly, the AFLP technique provides many markersrandomly spread in the genome whereas, in a diversitystudy, the number of analysed microsatellites is usuallylow. Although mutation rates may be di�erent fordi�erent markers and may be considered `markerspeci®c', other evolutionary factors such as migrationor drift a�ect the whole genome regardless of thegenomic regions that are monitored by di�erent markersystems. The comparative analysis between di�erentmarkers is therefore intended to reveal the balancebetween di�erent evolutionary forces contributing togenetic diversity. In this paper, we compare the levels ofdiversity within and among Pinus pinaster Ait. popula-

tions estimated by both types of markers (AFLP andmicrosatellites).The natural range of P. pinaster is restricted to the

western part of the Mediterranean basin, includingcontinental France (mainly south-west and south-east),Corsica, Spain, Portugal, continental Italy (Liguria andTuscany), Italian islands (Sardinia and Pantelleria),Morocco and Tunisia. Previous genetic diversity studieshave been performed using terpene, protein and allo-zyme markers (Baradat & Marpeau-Bezard, 1988;Baradat et al., 1991; Bahrman et al., 1992; Petit et al.,1995; Bahrman et al., 1997). The results of these studiesindicated a subdivision of the species into three groups:Atlantic (including south-west France, Portugal andGalicia in Spain), peri-Mediterranean (including Anda-lusia in Spain, Corsica, Maures in south-east France andLiguria in Italy) and North African (Moroccan Atlas,Algeria and Tunisia). They also suggested that thespecies di�erentiated into regional ``races'' after the lastglaciation, beginning in the south-west of the IberianPeninsula. Salvador et al. (2000) studied the geneticvariability with 18 isozyme loci and concluded that thesouthern Iberian range could be the putative recolon-ization centre of the species after the last glaciation.*Correspondence. E-mail: [email protected]

Heredity 86 (2001) 469±479 Received 15 May 2000, accepted 22 December 2000

Ó 2001 The Genetics Society of Great Britain. 469

Chloroplast microsatellites were recently used in P. pin-aster for studying genetic diversity and colonizationprocesses of the species (Vendramin et al., 1998; Ribeiroet al., 2000). As a whole, few studies focused on the ®nescale description of genetic variability of P. pinasterwithin regional `races'.

Maritime pine is a widely a�orested species in France.An intensive breeding programme is conducted withbreeding populations originating from the Aquitaine andCorsican provenances. Natural resources of the speciesmight be threatened in France. In south-west France, thearti®cial selection in the improvement programme maycause a reduction of the genetic variability. In the south-east, the threat may be due to the ®res and to the bastscale Matsucoccus feytaudi Duc., which is a speci®c pestof P. pinaster (Burban et al., 1999). After proliferating insouth-east France, the pest recently appeared in Corsica(Jactel et al., 1996) where it is spreading and producingextensive damage (Jactel et al., 1998).

In this paper, 13 Aquitaine populations and 10Corsican populations of P. pinaster were screened withtwo di�erent types of molecular markers: three nuclearmicrosatellite loci and 122 AFLP loci. The ®rst objectiveof the study was to compare the levels of within- andamong-population diversity assessed by both types ofmarkers. The second objective was to analyse andcompare the genetic diversity of P. pinaster populationsfrom the Aquitaine provenance and from the Corsicanprovenance. Finally, we intended to draw recommenda-tions for conservation purposes based on the comparat-ive analysis of genetic diversity with di�erent markers.

Materials and methods

Plant material and DNA extraction

We sampled 13 populations in Aquitaine (south-westFrance). Populations were selected on the basis ofhistorical records about their native origin [FrenchNational Forest O�ce (ONF), personal communica-tion]. From palynological data, Paquereau (1964) indi-cates that P. pinaster appeared in Aquitaine about8000 years ago and spread along the coast, where thespecies constituted some monospeci®c pine forestsduring the last 3000 years. The populations used in thisstudy most likely originated from original stands aftersuccessive natural regenerations. Populations were sam-pled to represent the natural genetic variation of thisspecies in south-west France.

The Corsican set of populations was selected among30 previously collected populations (Durel & Bahrman,1995). Ten of those populations, regularly distributedalong the island, were chosen to cover the range ofaltitudes, from 10 m to 1105 m.

For the Aquitaine populations, needles were collectedfrom about 30 young trees (3±5-years-old) randomlydistributed over an area from 10 to 30 hectares for eachpopulation. In the Corsican populations, one seedlingwas sampled for each of about 30 open pollinatedprogenies per population. The mother trees of the openpollinated progenies were distributed on approximately50 hectares. Genomic DNA was extracted from needlesas described by Doyle & Doyle (1990).

Microsatellite and AFLP markers

The 23 populations were screened with three nuclearmicrosatellites (FRPP91, FRPP94 and ITPH4516) andwith two AFLP primer±enzyme combinations. Micro-satellite ampli®cations were performed as described byMariette et al. (2001) and AFLP markers were obtainedfollowing the protocol by Costa et al. (2000). Twoprimer±enzyme combinations, EcoRI + ACC/MseI +CCTG and EcoRI + ACG/MseI + CCCA, codedPEC 1 and PEC 2, respectively, were used. They wereselected according to the number of ampli®ed loci(respectively 110 and 81) and the number of polymor-phic loci (respectively 29 and 28) detected in a mappedpopulation (Costa et al., 2000). Microsatellite andAFLP loci were scored with the RFLPRFLP-SCANSCAN version 3.0(Scanalytics) software.

Statistical analyses

Data analysis of microsatellite markers. For each locus,the allelic richness (A), the allelic frequencies, theobserved heterozygosity (HO), the e�ective number ofalleles (AE� 1/(1 ) HE)) and the ®xation index (FIS)were calculated as described by Brown & Weir (1983).The analysis of diversity was also performed using Nei's(1987) single-locus estimators: the within-populationgene diversity (Hi within population i and HS meanvalue of Hi over several populations), the total genediversity (HT) and the coe�cient of gene di�erentiationamong populations (GST). These parameters were com-puted by using the DIPLOIDEDIPLOIDE program (Antoine Kremer,Equipe de GeÂ neÂ tique et AmeÂ lioration des ArbresForestiers, Cestas, France).

Data analysis of AFLP markers. To analyse AFLPmarkers, we assumed that each AFLP ampli®cationproduct, regardless of its relative intensity, correspon-ded to a dominant allele at a unique locus. Polymorphicampli®ed loci were scored as `1' for the presence and `0'for the absence of a locus. Only loci with clearlyampli®ed bands were used for data analysis.

The analysis of genetic diversity with AFLP frag-ments was done after estimating the frequencies of the

470 S. MARIETTE ET AL.

Ó The Genetics Society of Great Britain, Heredity, 86, 469±479.

alleles responsible for the presence and absence offragments. If p and q are the alleles responsible for thepresence and absence of an AFLP fragment, and if Q isthe frequency of trees that do not exhibit the fragment,then Q� q2(1 ± FIS) +qFIS, where FIS is the ®xationindex. Assuming that the true value of FIS is known, anasymptotically unbiased estimate of q is obtained by theuse of a second order Taylor expression:

q̂ � ÿFIS

2�1ÿ FIS� �D

12

2�1ÿ FIS� ÿ 2�1ÿ FIS�Dÿ32

Q�1ÿ Q�N

� ��1�

with D�FIS2 + 4(1 ) FIS)Q and N the number of trees

sampled per population.The analyses were performed using the FIS value that

was estimated based on the average value from the threemicrosatellites. We estimated the diversity over all lociand we also restricted the analysis to loci that showed anobserved frequency smaller than 1 ) (3/N), where N isthe sample size, as recommended by Lynch & Milligan(1994). These authors showed that the bias introducedon the estimation of q due to small sample size wassubstantial when the null allele was rare. HS, HT andGST were computed by using the allelic frequencies asestimated by formula (1).Analyses were performed by using the HAPDOMHAPDOM

program (Antoine Kremer, Equipe de GeÂ neÂ tique etAmeÂ lioration des Arbres Forestiers, Cestas, France).For both types of marker, diversity parameters were

estimated for each population and provenance (Corsicaand Aquitaine). Mean values were estimated over all 23populations, over all the Aquitaine populations andover all the Corsican populations.Levels of di�erentiation (GST) were calculated among

all 23 populations, among the Aquitaine populations,among the Corsican populations and between theAquitaine provenance and the Corsican one.

Comparison of diversity and di�erentiation between theCorsican and Aquitaine provenance. Resampling meth-ods were used to estimate the di�erences between thetwo provenances [Aquitaine (A) and Corsica (C)] for theparameters AE, HO, HS, HT, FIS and GST. For example,in the case of HS, bootstrapping was used, where all theindividuals were resampled with replacement withineach population of each provenance A and C, andHS was computed in each provenance as well as thedi�erence of HS computed for each provenance(HS

Aq ) HSCor). Resampling was repeated 1000 times.

The distribution of (HSAq ) HS

Cor) was then comparedwith the null hypothesis (HS

Aq ) HSCor � 0). Sampling

variances were obtained by bootstrapping over individ-

uals in populations for AE, HO, HS, HT and FIS and bybootstrapping over populations for GST. The samplesizes in the Aquitaine and in the Corsican provenanceswere uneven, therefore the rarefaction method asdescribed by Petit et al. (1998) was used for estimatingthe unbiased allelic richness at each locus, using 50, 100and 200 as sample sizes for each provenance.

Comparison of allele frequencies among populationswithin provenances. The geographical pattern of thestudied populations was analysed by using the principalcomponent analysis (PCA) and Mantel tests. PCA wasperformed using the allele frequencies for each micro-satellite and the frequencies of loci obtained in thegenotypic AFLP analysis. In the case of microsatellitesonly allele frequencies of the ®ve most frequent alleleswere used. The ACPACP program (Philippe Baradat, Equipede GeÂ neÂ tique et AmeÂ lioration des Arbres Forestiers,Cestas, France) was used to compute the PCA analysis.Mantel tests were performed for comparing the

pairwise population geographical distance (in kilo-metres) with the pairwise population genetic distancematrix (Nei, 1978). The strength of the relationshipbetween both matrices was measured using the Mantelmatrix-correspondence test (Mantel, 1967; Sokal, 1979).The null hypothesis refers to the absence of associationbetween the elements of the pairs of matrices. Anormalized Z-test was performed in which the observedvalue after 999 permutations should be signi®cantlylarger than that expected by chance in order for anassociation to be accepted as valid. The program used tocompute Mantel tests was TFPGATFPGA version 1.3 (Mark P.Miller, Northern Arizona University, U.S.A.).

Intra- and inter-marker comparisons. Diversity assessedat di�erent markers results from either `marker speci®c'factors (such as mutation) or `marker non-speci®c'factors (as for example drift or migration). Hence onewould expect that values of diversity of a givenpopulation as assessed with di�erent markers shouldbe di�erent. However, if two populations went throughdi�erent evolutionary histories involving drift andmigration, then they would di�er for their level ofdiversity in a same manner for two di�erent kinds ofmarkers. In other words, one expects congruent ran-kings of the populations between markers. As a result,the comparative analysis of diversity between markers isnot based on the comparison of levels of diversity withina population, but on the comparison of the ranking ofdi�erent populations by correlation analysis.For each type of marker (AFLP or microsatellites),

A, AE, HO and HS were estimated for each population(and provenance). Estimates of these diversity statisticswere then compared between populations by computing

GENETIC DIVERSITY IN PINUS PINASTER 471


Spearman's rank coe�cient correlation (Sokal & Rohlf,1995). A signi®cant correlation would indicate con-gruence between di�erent factors and the impact of`marker non-speci®c' factors on levels of diversity.Conversely, lack of correlation is likely to reveal that`marker speci®c' factors are su�ciently di�erent betweenpopulations to generate di�erent levels of diversity.

Results

Within-population diversity

Microsatellites. Considering all the 23 populations, thethree microsatellites showed a high level of polymorph-ism with an average allelic richness A of 27.33, rangingfrom 23 to 31 alleles. HO was 0.645, ranging from 0.584to 0.690, and HT was 0.832, ranging from 0.742 to 0.903(Table 1).

AFLP markers. For the PEC 1 and the PEC 2, 56 and 66ampli®ed loci were analysed, respectively. The numberof polymorphic loci in at least one population was 23(41%) for PEC 1 and 36 (55%) for PEC 2. Thus, on awhole, 122 loci were analysed and 48% of them werepolymorphic.

Using the ®xation index FIS obtained from microsat-ellites to estimate allelic frequencies (eqn 1), the totaldiversity was 0.161 for PEC 1, 0.194 for PEC 2 and

0.179 for all the studied loci. Using only the 36polymorphic markers, as suggested by reducing thenumber of loci from Lynch & Milligan (1994), the levelsof diversity were increased [0.321, 0.297 and 0.305 forPEC 1, PEC 2 and both PECs, respectively (Table 2)].

Comparison of diversity in Aquitaine and Corsica

At the single population level, Aquitaine populationsshowed higher within-population diversity levels thanCorsican populations. This result was signi®cant at the5% level both for microsatellites (Table 1) and AFLPmarkers (Table 2). However, locus FRPP94 showed asigni®cantly higher e�ective number of alleles andwithin-population diversity for Corsican populations(Table 1). The ®xation index within Corsican popula-tions was signi®cantly higher for locus FRPP91 andover all loci (Table 1).

At the provenance level, the Aquitaine provenanceshowed signi®cantly higher levels of diversity than theCorsican one, both for microsatellite and AFLP mark-ers (Table 1 and Table 2). However, loci FRPP94 andPEC 1 showed signi®cant higher diversity parametersfor the Corsican provenance.

With 50, 100 and 200 as sample sizes for eachprovenance, the rarefaction method gave a highernumber of alleles in Corsica for FRPP91 (27.4 inCorsica and 21.5 in Aquitaine for a sample size of 200)

Table 1 Genetic diversity statistics for microsatellite loci in Corsican and Aquitaine populations of Pinus pinaster

A HO HT

FRPP91 31 0.661 0.849FRPP94 23 0.584 0.742ITPH4516 28 0.690 0.903Three loci 27.33 0.645 0.832

AP AT AEP AET HO HS HT FIS

FRPP91 Aquitaine 11.31* 25 5.43* 5.79* 0.805* 0.827* 0.829* 0.026*Corsica 8.60 30 2.14 2.12 0.434 0.523 0.531 0.170

FRPP94 Aquitaine 6.62 ns 14 2.69* 2.82* 0.534* 0.641* 0.647* 0.167ns

Corsica 7.60 20 4.25 4.86 0.661 0.772 0.796 0.144

ITPH4516 Aquitaine 12.69* 25 7.29* 8.22* 0.741* 0.871* 0.883* 0.149*Corsica 8.70 20 4.37 5.76 0.605 0.765 0.829 0.210

Three loci Aquitaine 10.21* 21.33 4.24* 4.62* 0.693* 0.780* 0.786* 0.114*Corsica 8.3 23.33 3.07 3.52 0.567 0.687 0.718 0.175

A, allelic richness; AP, allelic richness at the population level; AT, allelic richness at the provenance level; AEP, e�ective number of alleles atthe population level; AET, e�ective number of alleles at the provenance level; HO, observed heterozygosity; HS, mean within-populationdiversity; HT, total gene diversity; FIS, ®xation index within populations.* Signi®cantly di�erent at the 5% level between the Aquitaine and the Corsican provenance.ns Values estimated for Aquitaine and Corsica are not signi®cantly di�erent at the 5% level.



and for FRPP94 (18.3 in Corsica and 11.7 in Aquitaine).In contrast, ITPH4516 showed more alleles in theAquitaine provenance (22.4 in Aquitaine and 18.8 inCorsica). The Corsican provenance showed a highermean allelic richness (A� 23.33) than the Aquitaineprovenance [A� 21.33 (Table 1)].Considering the distribution of allelic frequencies of

microsatellites, the provenances did not share the samecommon alleles for FRPP91 and for ITPH4516 (Fig. 1).For FRPP91, one allele showed divergent frequencies inCorsican and Aquitaine provenances (0.680 in Corsicaand 0.004 in Aquitaine). For all loci, each provenanceexhibited private alleles: for FRPP91, one rare allele wasspeci®c to Aquitaine and six were speci®c to Corsica; forFRPP94, three alleles were found in Aquitaine againstnine in Corsica and for ITPH4516, eight alleles werefound in Aquitaine vs. three in Corsica (Fig. 1). Corsicashowed a higher number of rare alleles (18 against 12 inAquitaine).AFLP markers also showed private alleles. Consider-

ing both PECs, seven polymorphic loci exhibited bandsin Aquitaine which were absent from Corsica. Nospeci®c allele was found in Corsica.

Subdivision of genetic diversityamong populations and between provenances

The average di�erentiation among all populations was11.1% for the microsatellite markers (Table 3), varyingfrom 6% for FRPP94 to 18.2% for FRPP91. For AFLPmarkers the level of di�erentiation was 10.2% for the

genotypic analysis, when all 122 loci were considered,and reduced to 6.1%, following Lynch & Milligan(1994). The di�erentiation levels estimated with the twoprimer±enzyme combinations were found to be signi®-cantly di�erent. The PEC 2 showed a signi®cantlyhigher di�erentiation than the PEC 1 (data not shown).The genetic di�erentiation assessed with microsatellite

markers was signi®cantly higher than the di�erentiationassessed with AFLP markers only when we used theLynch & Milligan (1994) method of analysis.The di�erentiation among Corsican populations was

higher than the di�erentiation among Aquitaine popu-lations with both microsatellite and AFLP markers(Table 3). The di�erence was signi®cant for microsatel-lites and for the analysis of AFLP when the 122 lociwere considered.The di�erentiation between provenances (9.2% for

microsatellites and 4.9% for AFLP markers) represen-ted more than half of the total di�erentiation (Table 3).

Comparison of levels of diversity assessedwith different measures (A and Hi)

Allelic richness and expected heterozygosity estimatedwith microsatellite loci within each population exhibitedsimilar rankings of populations within each provenance.The rankings of populations given by A calculated overall microsatellites were positively and signi®cantly(5% level) correlated with rankings given by Hi, bothfor Aquitaine populations (rS� 0.765, P� 0.018) andfor Corsican populations (rS� 0.710, P� 0.035). In the

Table 2 Genetic diversity statistics forAFLP loci in Corsican and Aquitainepopulations of Pinus pinaster

Total diversity Total diversityà

PEC 1 0.161 0.321PEC 2 0.194 0.297Two PECs 0.179 0.305

HS HT HSà HTà

PEC 1 Aquitaine 0.140ns 0.147* 0.326* 0.374ns

Corsica 0.149 0.156 0.286 0.375

PEC 2 Aquitaine 0.180* 0.183* 0.303* 0.353*Corsica 0.168 0.178 0.240 0.318

Two PECs Aquitaine 0.162ns 0.166ns 0.310* 0.361*Corsica 0.159 0.168 0.255 0.340

HS, mean within-population diversity; HT, gene diversity at the provenance level. The analysis is genotypic.àThe analysis is genotypic and restricted to loci whose observed frequency is less than1 ) (3/N) with N the population sample size, following Lynch & Milligan (1994).* Signi®cantly di�erent at the 5% level between the Aquitaine and the Corsicanprovenance.ns Values estimated for Aquitaine and Corsica are not signi®cantly di�erent at the 5% level.



Aquitaine populations, the correlation was also signi®-cantly positive for each microsatellite.

For Corsican populations, pairwise comparison ofdiversity statistics between loci did not always indicatecongruent results. For FRPP91, the ranking given byHO was positively and signi®cantly correlated with theranking given by HO on FRPP94. The ranking given byA on FRPP91 was also positively and signi®cantlycorrelated with the ranking given by HO on FRPP94and by HO on ITPH4516. The same analysis wasperformed for the Aquitaine provenance and no corre-lation was ever found.

Comparison of levels of diversity assessedwith different markers

For each type of analysis, the rankings of populationsgiven by PEC 1 and PEC 2 were not signi®cantlycorrelated for both Aquitaine and Corsican populations(Table 4). Rankings given by PEC 1 and PEC 2 werechecked separately but were never signi®cantly correla-ted (Table 5); they were positively and signi®cantlycorrelated, as expected, with rankings given by bothPECs, in general.

When comparing Hi values given by microsatellitesand AFLP markers, no positive and signi®cant corre-lation was found (Table 4).

Geographical pattern

The two ®rst axes of the principal component analysisseparated Aquitaine populations from Corsican ones(Fig. 2).

Mantel tests performed on Aquitaine populations didnot detect any geographical pattern with AFLP markersor with microsatellites. A signi®cant correlation(r� 0.360, P� 0.018) between the genetic distancesmatrix and the geographical distances matrix was foundfor Corsican populations when microsatellites wereused.

Discussion

Maritime pine is a highly polymorphic species as shownby the values of diversity measures and comparisonswith other species. For example, in this study, theaverage value of HO for microsatellites was 0.645 andthe average value of A was 27.33. These values aresimilar to the values found in other pine species (Smith& Devey, 1994; Echt et al., 1996). The ultimate aim ofthis study was to derive conservation decisions based ona comparative survey of genetic diversity conductedwith di�erent markers. The comparative analysis wasintended to reveal the di�erential impact of `marker

Fig. 1 Microsatellite allelic frequencies for Corsican andAquitaine populations of Pinus pinaster used in the paper.



speci®c' factors vs. `marker non-speci®c' factors ondiversity. In addition, as conservation should be basedon genetic diversity at the whole genome level, thecomparative analysis will provide insights on thegenomic heterogeneity for diversity and di�erentiation.Therefore, we will ®rst discuss congruencies and dis-crepancies between markers, and then consider theirconsequences on conservation strategies.

Congruent results of differentiation obtainedwith microsatellites and AFLPs

As for diversity, some evolutionary factors such asmigration may have an impact on di�erentiationregardless of the marker, whereas others (such as

mutation) may be considered as `marker speci®c'. Formost markers, the contribution of mutation to di�er-entiation has generally been ignored because mutationrates of traditional isozyme markers are negligiblewhen compared to migration rates. This may not bethe case when comparing microsatellites and AFLP.Because microsatellite markers show higher mutationrates than other molecular markers (Weber & Wong,1993), they are expected to exhibit lower levels ofdi�erentiation. Furthermore, as reported by Estoupet al. (1995), homoplasy due to the high mutation ratemay increase the underestimation of di�erentiation. Onthe other hand, the dominant property of AFLPmarkers is also responsible for a bias in the estimationof di�erentiation. Jenczewski et al. (1999) showed, both

Table 3 Levels of di�erentiation (withstandard deviations) among Aquitaineand Corsican populations of Pinuspinaster

GSTT GST

Aq vs. Cor GSTAq GST

Cor

Three microsatellites 0.111 (0.012) 0.092 ()) 0.009 (0.004) 0.044 (0.008)AFLP (two PECs) 0.102 (0.004) 0.066 ()) 0.032 (0.005) 0.054 (0.008)AFLP (two PECs)à 0.061 (0.003) 0.049 ()) 0.017 (0.004) 0.027 (0.005)

GSTT, Nei's GST among all 23 populations; GST

Aq vs. Cor, Nei's GST between Aquitaineprovenance and Corsican provenance; GST

Aq, Nei's GST among 13 Aquitaine populations;GST

Cor, Nei's GST among 10 Corsican populations. The analysis is genotypic.àThe analysis is genotypic and restricted to loci whose observed frequency is less than1 ) (3/N) with N the population sample size, following Lynch & Milligan (1994).

Table 4 Spearman's rank correlation analysis among diversity values obtained with di�erent markers in Pinus pinaster

Hi (2 PECs) Hi (PEC 1) Hi (PEC 2) Hià (2 PECs) Hià (PEC 1) Hi (microsatellites)

AquitaineHi (2 PECs) )0.220 (0.441)Hi (PEC 1) 0.830* (0.004) 0.016 (0.962)Hi (PEC 2) 0.703* (0.015) 0.258 (0.376) )0.445 (0.121)Hià (2 PECs) 0.955* (0.001) 0.839* (0.004) 0.569* (0.050) )0.272 (0.341)Hià (PEC 1) 0.582* (0.045) 0.764* (0.080) )0.011 (0.962) 0.713* (0.014) )0.060 (0.827)Hià (PEC 2) 0.874* (0.003) 0.588* (0.043) 0.874* (0.003) 0.831* (0.004) 0.319 (0.274) )0.462 (0.108)

CorsicaHi (2 PECs) )0.370 (0.260)Hi (PEC 1) 0.442 (0.191) )0.127 (0.689)Hi (PEC 2) 0.845* (0.012) 0.146 (0.675) )0.517 (0.117)Hià (2 PECs) 0.733* (0.030) 0.212 (0.537) 0.760* (0.024) )0.430 (0.191)Hià (PEC 1) 0.018 (0.971) 0.539 (0.110) )0.243 (0.455) 0.248 (0.467) )0.248 (0.445)Hià (PEC 2) 0.733* (0.029) 0.067 (0.856) 0.863* (0.010) 0.867* (0.010) )0.212 (0.513) 0.248 (0.445)

Each Spearman's rank correlation is followed by the associated probability.Hi: within-population diversity. The analysis of AFLP markers is genotypic.àThe analysis of AFLP markers is genotypic and restricted to loci whose observed frequency is less than 1 ) (3/N) with N the populationsample size, following Lynch & Milligan (1994).* Signi®cant positive correlation at the 5% level.



Table 5 Comparison of diversity in Corsican and Aquitaine populations of Pinus pinaster

Aquitaine Micro-satellites AquitaineAFLP122 loci Aquitaine

AFLP(Lynch & Milligan)

UsageÁ re de Biscarosse 0.798 A LeÁ ge 0.172 A Lit-et-Mixe 0.331 AHourtin 0.776 A Lit-et-Mixe 0.171 A LeÁ ge 0.331 ASt-Julien-en-Born 0.775 A St-Julien-en-Born 0.171 A B St-Julien-en-Born 0.330 A BPointe de Grave 0.771 A Vielle-St-Girons 0.168 A B Vielle-St-Girons 0.328 A BLeÁ ge 0.765 A Ste-Eulalie-en-Born 0.167 A B C Ste-Eulalie-en-Born 0.318 A BMimizan 0.763 A Pointe de Grave 0.163 A B C D Carcans 0.312 A BCarcans 0.762 A Carcans 0.163 A B C D Mimizan 0.312 A BLit-et-Mixe 0.759 A Mimizan 0.162 A B C D Pointe de Grave 0.311 A BLacanau 0.758 A Hourtin 0.161 A B C D Domaniale de Biscarosse 0.306 A B CDomaniale de Biscarosse 0.752 A Boulevard des Allemands 0.158 B C D Hourtin 0.299 A B CBoulevard des Allemands 0.751 A Domaniale de Biscarosse 0.154 C D E UsageÁ re de Biscarosse 0.295 B CSte-Eulalie-en-Born 0.750 A A UsageÁ re de Biscarosse 0.151 D E Boulevard des Allemands 0.293 CVielle-St-Girons 0.744 A Lacanau 0.144 E Lacanau 0.269 C

Corsica Microsatellites Corsica AFLP 122 loci CorsicaAFLP

(Lynch & Milligan)

Vero 0.751 A Pineto 0.168 A Ominanda 0.288 ATova 0.714 A B Ominanda 0.167 A Pineto 0.274 A BCagna 0.709 A B C Cagna 0.165 A Ventilegne 0.267 A B CPinia 0.679 A B C Ventilegne 0.164 A Restonica 0.264 A B CPineto 0.679 A B C Bonifatu 0.159 A B Cagna 0.260 A B CAullene 0.662 B C Aullene 0.158 A B Aullene 0.250 B C DVentilegne 0.636 B C Vero 0.158 A B Tova 0.245 C DRestonica 0.630 B C Restonica 0.154 B Vero 0.244 C DBonifatu 0.624 C Tova 0.153 B Bonifatu 0.241 C DOminanda 0.599 C Pinia 0.150 B Pinia 0.220 D

Populations having the same letter do not show a signi®cant di�erence in their level of diversity.

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with simulation and experimental results, that FST isbiased upward when using RAPD phenotypes toestimate allelic frequencies and Krutovskii et al.(1999) showed that RAPDs can reasonably estimatepopulation di�erentiation if sample sizes are largerthan about 30 individuals. In our case, sample sizeswere around 30 individuals for each population andsome loci were ®xed for the presence of ampli®ed lociso an overestimation of di�erentiation for AFLPscannot be excluded. Despite these expected discrepan-cies, our results lead to similar conclusions for geneticdi�erentiation assessed with microsatellite and AFLPmarkers. Although `absolute values' of di�erentiationmay slightly di�er between markers, they lead tosimilar conclusions (Table 3): (i) when all populationswere considered, a high di�erentiation among popula-tions was found both with microsatellites and AFLPmarkers; (ii) furthermore, both markers indicate that apredominant part of the total di�erentiation is due tothe subdivision between the Aquitaine and Corsicanprovenances; and (iii) lastly the two markers reveal thatthere is more di�erentiation among the Corsicanpopulations than among the Aquitaine populations.The congruent results obtained with di�erent markersmost likely indicate that marker di�erences (mutationrates, homoplasy, estimation biases) had only a minorimpact on di�erentiation. Conversely, migration anddrift may still be the prevailing factors involved. This isillustrated by the contrasting di�erence between theAquitaine and Corsican forest conditions. The Aqui-taine populations were sampled within a broad con-tinuous forest occupying a ¯at area of about 1 millionhectares. In contrast, the Corsican populations camefrom an heterogeneous discontinuous forest distributedin mountainous regions. Consequently there is likely to

be more gene ¯ow among stands in Aquitaine than inCorsica.Interestingly our results (Table 3) could be compared

with previous reports based on di�erent markers, butalso on di�erent sampling of populations. GST valuesestimated on six populations chosen throughout therange of the species (Petit et al., 1995) were 0.170, 0.161and 0.139, respectively, for protein, isozyme and terpeneloci. Since the sampling area was larger, di�erentiationwas also higher. However this study also indicatedcongruent results of di�erentiation across three di�erentmarker systems.

Congruent results of diversity obtainedwith microsatellites and AFLPs

Among the di�erent evolutionary factors that have animpact on genetic diversity, mutation can be consideredas `marker speci®c'. However there are other factorssuch as genetic drift and migration that can be consid-ered as `non-marker speci®c'. For example, a reductionin population size in a given population will decrease thelevel of diversity for any marker (AFLP and microsat-ellites) regardless of its mutation rates. As a result, onewould expect that populations that had di�erent evolu-tionary histories would also di�er in their levels ofdiversity, following a similar trend for both markers.Most of the diversity measures estimated with di�erentmarkers showed a signi®cantly lower level in Corsicanpopulations than in Aquitaine populations (Table 1 andTable 2). For microsatellites, the Corsican populationsshowed a lower allelic richness than the Aquitaine onesbut the alleles tended to be di�erent in each population.For AFLPs, there are more pronounced di�erencesbetween the two provenances for the analysis restrictedto the polymorphic markers (according to the rules ofLynch & Milligan, 1994) than for the analysis conductedon the whole set of data.The congruent results of diversity levels between the

two markers suggest that population di�erences indiversity are more related to `marker non-speci®c' than`marker speci®c' causes. Among the former, populationhistory may be advocated to interpret these results. Thefrequent occurrence of ®re over large areas, the moresevere climatic conditions in Corsica and the mountain-ous topography may have induced repetitive sequencesof restriction and expansion of maritime pine forest,leading to progressive genetic erosion. Furthermoregenetic erosion can not be prevented by gene ¯ow fromthe continent, as Corsica is isolated by a few hundredkilometres from France or Italy. An alternative hypo-thesis, and not exclusive with the previous one, may bethat the number of founder populations that becameestablished on the Corsican island was limited.

Fig. 2 Principal component analysis on Pinus pinaster popu-

lations: d Aquitaine populations; m Corsican populations.



Discrepancy between AFLPs and microsatellitesfor measuring within-population diversity

If the estimates of levels of diversity with di�erentmarkers were congruent for the comparison betweenthe Corsican and Aquitaine provenances, they do notlead to the same conclusions for the comparison ofpopulations within each of the two provenances. Thereis no signi®cant correlation among the diversity esti-mates calculated for the AFLPs and microsatellites(Table 4). Considering AFLP markers alone, a strikingresult was that the two primer±enzyme combinationsprovided di�erent rankings of populations, particularlyin Corsica. Furthermore, rankings given by two di�er-ent microsatellite loci were rarely signi®cantly andpositively correlated. When marker systems were com-pared, neither A nor Hi, estimated by microsatellites,gave similar rankings to Hi estimated by AFLPmarkers. The discrepancy found between markersmay be due to either biological and/or technical causes.`Marker non-speci®c' factors (drift, migration, popula-tion history) did not di�er su�ciently between di�erentpopulations to generate di�erent levels of diversity.This would result in the lack of di�erentiation forpopulation diversity. Hence populations within theCorsica or Aquitaine provenance would be homogen-eous for their level of diversity due, for example, tointensive and equal gene ¯ow, and the absence of driftwithin each provenance. This hypothesis is supportedby the statistical multipopulation comparison of diver-sity (Table 5), showing that, except with microsatellitesin Corsican populations, no diversity di�erence couldbe detected among populations. The technical inter-pretation is related to the sampling used. The di�erencein levels of diversity may be so small among popula-tions that our sampling strategy did not allow thedetection of any signi®cant di�erences. All di�erencesamong diversity estimates are therefore so small thatthe ranking observed is only generated by the noise ofthe estimation.

Conservation implications

The comparative analysis of genetic diversity withdi�erent markers has provided interesting insights notonly into the organization and subdivision of diversitybut also into the genetic mechanisms that contributed tothe extant structure of diversity. All markers indicatedthat the Corsican and Aquitaine provenance arestrongly di�erentiated. This is suggested by the highGST values between the two provenances and by theprincipal component analysis (Fig. 2). It is also illustra-ted by the important di�erences in allele frequencies forthe microsatellite locus FRPP91 (Fig. 1). Conservation

actions are therefore recommended to save diversity foreach of the two provenances. Our results indicatehowever, that sampling of candidate populations ortrees for conservation should be achieved di�erently inthe two provenances. The Aquitaine provenance ischaracterized by a low di�erentiation for allele frequen-cies (extremely low GST values) and a low di�erentiationfor within-population diversity, and these results areagain consistent across markers. As a result ex situ orin situ conservation could be based on a random sampleof trees throughout the Aquitaine area. On the otherhand the Corsica provenance is characterized by ahigher population di�erentiation for allele frequencies(GST values) and a slightly higher di�erentiation forwithin-population diversity. Consequently, it is expectedthat di�erent populations may contain di�erent alleles,as suggested by the distribution of allelic richness amongpopulations. Sampling guidelines for conservationwould therefore recommend concentrating on a fewpopulations that would sample the total diversity. Atthis stage, our results indicate that a more intensemonitoring of diversity should be conducted in theCorsican provenance in order to identify the candidatepopulations for conservation. To conclude on theconservation issue, we would also recommend comple-menting the present study with a parallel investigationon adaptive traits (drought, pest and insect resistance)and other economic traits (growth and form) before ade®nite strategy is adopted.

Acknowledgements

We are very grateful for the technical help provided byCeÂ cile Cabrero and Audrey Lartigue. We thankDominique Charon and the French National ForestO�ce (ONF) for the help in collecting material inAquitaine. This work was supported by grants fromFrance (MinisteÁ re de l'Agriculture et de la PeÃ che-DERFno. 61.21.04/98 and Bureau des Ressources GeÂ neÂ tiques)and the European Union (INCO, ERBIC-08CT-970200). The authors thank two anonymous reviewersand Don Stratton for their comments on the manu-script.

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Genetic diversity within and among Pinus pinaster populations: comparison between AFLP and microsatellite markers