MARINE ECOLOGY PROGRESS SERIESMar Ecol Prog Ser

Vol. 474: 243–261, 2013doi: 10.3354/meps10080

Published January 31

INTRODUCTION

It is now well-established that marine organismscan be genetically structured across a broad range ofgeographic scales, despite being in an environmentthat is considered to be highly interconnected (Hauser

& Carvalho 2008). Estimated levels of connectivityamong marine populations reflect events rangingfrom distant historical allopatric divergence or cli-mate shifts, to current-day environmental features,oceanographic patterns, or behaviours that con straingenetic exchanges among populations (Selkoe et al.

© Inter-Research 2013 · www.int-res.com*Email: jean-dominique.durand@ird.fr

Population genetic structure of Mugil cephalusin the Mediterranean and Black Seas: a single

mitochondrial clade and many nuclear barriers

J. D. Durand1,*, H. Blel2, K. N. Shen3,4, E. T. Koutrakis5, B. Guinand6

1Institut de Recherche pour le Développement (IRD), UMR 5119 ECOSYM, Université Montpellier II, Place Eugène Bataillon, CC 93, 34095 Montpellier cedex 5, France

2Unité de Recherche de Génétique: Biodiversité et Valorisation des Bio ressources (UR: 09/30), Institut Supérieur de Biotechnologie de Monastir, Université de Monastir, 5000 Monastir, Tunisia

3Department of Environmental Biology and Fisheries Science, and 4Center of Excellence for Marine Bioenvironment andBiotechnology, National Taiwan Ocean University, Keelung 20224, Taiwan

5Fisheries Research Institute-NAGREF, 640 07 Nea Peramos, 64007 Kavala, Greece6Institut des Sciences de l’Evolution de Montpellier, Evolution des Poissons, CNRS-UMR 5554, Université Montpellier II,

Place Eugène Bataillon, CC 65, 34095 Montpellier cedex 5, France

ABSTRACT: The population structure and evolutionary history of Mugil cephalus wereinvestigated across 18 sampling sites in the NE Atlantic Ocean, Mediterranean and Black Seas, us-ing 2 classes of genetic markers: sequence polymorphism of an 857 bp fragment of mitochondrial(mtDNA) cytochrome b, and allele size variation at 7 nuclear loci. The level of nucleotide diversityrecovered with the mtDNA marker was very low (~0.6% divergence), indicating the presence of asingle clade over the entire area. Mismatch distribution, Bayesian skyline plots and associated sta-tistics revealed a recent demographic crash followed by population expansion, but nuclear data in-dicated population constancy in the area covered in this study. While a single clade was detected,significant mtDNA genetic differentiation was, however, observed between the samples from theBlack Sea and the samples from other (sub-) basins (ΦST = 0.17; p = 0.029). The nuclear loci also re-vealed significant genetic differentiation and isolation-by-distance in M. cepha lus. Patterns of ge-netic structure were, however, significantly more pronounced with nuclear than with mtDNAmarkers; the former indicated the presence of 3 (Bayesian clustering) to 6 (Monmonnier’s method)populations. The highest levels of genetic heterogeneity at nuclear markers occurred at the well-known Almeria-Oran Front, but also in the Bosporus Strait. Thus, both sets of markers revealed theimportance of this strait as a barrier to gene flow, probably during the Pleistocene. The results alsorevealed genetic heterogeneity in the eastern Mediterranean basin, and suggested that the popula-tion expanded from this sub-basin towards the Atlantic Ocean and Black Sea.

KEY WORDS: Microsatellites · Mitochondrial DNA · Gene flow · Demography · MediterraneanSea · Mugilidae · Bayesian clustering · Bayesian skyline plot

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OPENPEN ACCESSCCESS

Mar Ecol Prog Ser 474: 243–261, 2013

2008). The nature and patterns of inheritance ofgenetic markers can provide information about howthese processes affect marine connec tivity: mito-chondrial DNA (mtDNA) is traditionally consideredto illustrate historical processes, while nuclear mark-ers such as microsatellites are better at revealingcontemporary processes and resolving populationstructure on a finer scale (e.g. Gonzalez & Zardoya2007). Comparative studies of both types of markersare, therefore, useful for elucidating populationstructure of marine organisms, and possibly shed-ding light on the relative effects of genetic drift,mutation and migration, selection, differences ineffective population size, or sex-biased dispersal(Buonaccorsi et al. 2001, Canino et al. 2010b). Collec-tively, this information is important for the efficientmanagement of marine resources.

The flathead (or striped) grey mullet Mugil cepha -lus L., 1758 is considered to be a single species with aworldwide distribution comprising most of the coastaland estuarine environments between ca. 42° N and42° S (Thomson 1997). This distribution includesmajor biogeographic zones and barriers to dispersal(Thomson 1997). The ecological success of the flat-head mullet across such a broad geographic rangehas raised doubts about its true taxonomic status(Crosetti et al. 1994, Durand et al. 2012) and stimu-lated phylogeographical studies at an inter-oceanicscale (Crosetti et al. 1994, Rossi et al. 1998, Rocha-Olivares et al. 2000, Heras et al. 2009, Livi et al.2011). While the inter-oceanic structure has beenextensively investigated, further population geneticstudies are now necessary at smaller oceanic scales.To date, these have found genetic homogeneitywithin the NW Atlantic and the Gulf of Mexico(Campton & Mahmoudi 1991, Rocha-Olivares et al.2000). Studies performed in the Mediterranean Seahave also reported genetic homogeneity amongM. cephalus samples (allozymes: Rossi et al. 1998;mtDNA: Livi et al. 2011; microsatellites: Blel et al.2010). By contrast, genetic studies conducted in theNW Pacific demonstrated the existence of largegenetic heterogeneity (review in Shen et al. 2011).Indeed, using mtDNA and micro satellite loci simul -taneously, Shen et al. (2011) reported that the NWPacific population of flathead mullet, which hadbeen considered to harbour a single mitochondriallineage (Crosetti et al. 1994, Heras et al. 2009), con-sisted of 3 mitochondrial lineages corresponding todistinct parapatric species. These results warrant are-evaluation of the genetic structure of the flatheadmullet in other geographic areas, based on data frommultiple genetic markers. This is especially true for

the Mediterranean Sea and adjacent NE Atlantic (i.e.Moroccan, Spanish and Portuguese coastlines)because previous studies of genetic variation in M.cephalus only analysed limited sets of samples (n ≤ 5;Rossi et al. 1998, Blel et al. 2010, Livi et al. 2011) thatdid not fully cover the marine phylogeographicregions recognized there (NE Atlantic, western andeastern Mediterranean basins, and the Black Sea;e.g. Patarnello et al. 2007). A wider picture of geneticdifferentiation for reliable monitoring of this impor-tant marine resource is lacking in this area, wheremullet has been fished and cultured for centuries,providing an important income for artisanal fisher-men in Mediterranean and other countries (Koutrakiset al. 2007, Whitfield et al. 2012), but which is nowheavily impacted by climate change and humanactivities.

In the present study, the population genetic struc-ture of Mugil cephalus was investigated in the Medi-terranean Sea, the adjacent area of the NE Atlanticand the Black Sea, using 2 classes of genetic markers:sequence polymorphism of a mitochondrial gene (cyto -chrome b), plus allele size variation at 7 nuclear loci(6 microsatellite loci and 1 exon-primed intron-cross-ing [EPIC] locus). Based on extensive sampling cover-age, we investigated (1) the null hypothesis of no ge-netic structure at each class of markers, (2) the pastdemographic history of flathead grey mullet in thisarea based on mtDNA and nuclear markers, and (3)estimates of number of effective migrants and patternsof asymmetric migration among phylogeogra phic areas based more specifically on nuclear markers.

MATERIALS AND METHODS

Sampling

Eighteen locations are considered in this study,from the Atlantic Ocean to the Black Sea, hence covering the 2 main biogeographic regions of theMediterranean (western and eastern basins; Table 1,Fig. 1). Mugil cephalus specimens, comprising asample of pectoral fins preserved in 95% ethanol,were collected in 2005 and 2006 from the landings ofartisanal fisheries (cast nets, fish traps, purse seinesand drift nets).

Molecular methods

Total genomic DNA was extracted from musclesamples or fin clips using standard phenol-chloroform

244

Durand et al.: Population structure of Mugil cephalus in the Mediterranean and Black Seas

protocols (Sambrook et al. 1989). The nuclearmarkers comprised 6 microsatellite loci(MCS1EH, MCS2FH, MCS15AM, MCS 15CM,MCS 2DM and MCS16DM; Miggiano et al.2005) and the first intron of the prolactin 1gene locus (prl-1; Blel et al. 2010). Primersand polymerase chain reaction (PCR) pro -tocols are reported in Miggiano et al. (2005)and Blel et al. (2010), respectively. PCR prod-ucts were used undiluted and mixed with anequal volume of formamide loading dye(95% formamide, 20 mM EDTA, 0.05% xy-lene cyanol and 0.05% bromophenol blue),and denatured at 94°C for 5 min. Then, 6 µl ofthis mixture was loaded into 6% denaturingpolyacrylamide gel and run using 1× TBEbuffer at 50 W for 2 h. The gel was then laserscanned, and the fluorescent bands were vi-sualized in an FMBio II fluorescence imagingapparatus (Hitachi Instruments). Several in-dividuals of known genotype were used asadditional allele-size standards on each gel.The mitochondrial marker was an 857 basepair (bp) fragment of the cytochrome b (cytb)gene. MtDNA amplification was performedwith the primers Fishcytob-F (Sevilla et al.2007) and Mix Cytob-0937-1-R (5’-GGK CGGAAT GTY AGK CYT CG-3’). The PCR wascarried out in a 50 µl reaction volume contain-ing 5 µl of 10× reaction buffer (Pro mega), 1.5µl of MgCl2 (25 mM), 2 µl of dNTP (5 mM), 0.5µl of each primer (10 µM), 1 U of GoTaq DNApolymerase (Promega) and 1 µl of templateDNA of unknown concentration. PCR ampli-fication conditions were as follows: prelimi-nary denaturation at 92°C (5 min), strand de-naturation at 92°C (1 min), primer annealingat 52°C (45 s) and primer extension at 72°C(1.5 min) repeated for 35 cycles and final ex-tension at 72°C (5 min). All sequencing reac-tions were performed according to the manu-facturer’s protocol (Applied Biosystems).Sequences were de po sited in GenBank (ac-cession numbers JN390976 to JN391159).

Data analysis

Diversity indices (haplotype and nucleotidediversity) were estimated using ARLEQUIN v3.5(Excoffier & Lischer 2010), and phylogeneticrelationships among Mugil cephalus haplo-types were depicted through a phylo genetic

245

No.

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Tab

le 1

. Mu

gil

cep

hal

us.

Sam

pli

ng

loca

tion

s in

th

e N

E A

tlan

tic

and

th

e M

edit

erra

nea

n a

nd

Bla

ck S

eas,

wit

h t

he

sam

ple

siz

e (N

) an

d s

ome

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ersi

ty in

dic

es e

stim

ated

wit

h m

icro

sate

llit

e lo

ci (

µsa

ts)

and

cyt

och

rom

e b

seq

uen

ces

(cyt

b).

L.:

lag

oon

; R

.: ri

ver;

n:

mea

n n

um

ber

of

alle

les

from

th

e 7

loci

use

d i

n t

his

stu

dy

(µsa

ts)

or a

llel

e n

um

ber

(cy

tb);

Hob

s: o

bse

rved

het

eroz

ygos

ity;

h: h

aplo

typ

e d

iver

sity

; π: n

ucl

eoti

de

div

ersi

ty; D

: Taj

ima’

s D

; FS: F

u’s

FS. *

p <

0.0

5,**

p <

0.0

1, *

**p

< 0

.001

Mar Ecol Prog Ser 474: 243–261, 2013

analysis based on a partitioned maximum-likelihood(ML) method implemented in MEGA 5 (Tamura et al.2011). The HKY + G model of substitutions was usedas it better fit our data set than any other models ac-cording to the model test implemented in ARLEQUIN

v.3.5 (Bayesian information criterion = 6938.825). Toprovide an overview of the genetic diversity of M.cephalus and highlight phylogenetic relationshipsamong mtDNA lineages ob served in the Atlantic andin the East Pacific (Durand et al. 2012), we included inthe phylogenetic analyses the cytb haplotypes de-scribed in Durand et al. (2012). The tree was rooted us-ing 5 cytb sequences of M. bananensis as outgroups(GenBank accession numbers JQ060267, JQ060268)and M. capurii (JQ060269, JQ060270, JQ060271).

Observed heterozygosities (Hobs) were estimatedfrom raw nuclear genotype data at each nuclear lo -cus using GENETIX v.4.05 software (http://kimura.univ- montp2.fr/genetix/), while nucleotide and hap-lotype diversity indices at cytb were estimated usingARLEQUIN v.3.5. Deviations from Hardy-Weinbergexpectations (HWE) within samples were investi-gated using Weir & Cockerham’s (1984) estimate of ƒ(quoted as ƒ̂ ) with GENETIX. A test for significantdeparture from HWE (ƒ̂ = 0) was performed by ran-domly permuting alleles from the original matrix ofgenotypes using the appropriate procedure inGENETIX. Critical significance levels for multiple test-ing were corrected following the sequential Bonfer-roni procedure. Linkage disequilibrium betweenpairs of nuclear loci (i.e. non-random associations ofparticular genotypes) was tested with GENETIX.

The occurrence of bottlenecks among Mugil cepha -lus samples was investigated using BOTTLENECK on thenuclear genotypes (Piry et al. 1999). Tests (1000 repli-cates) were performed using the stepwise mutationmodel that best described the data. A Wilcoxon sign-ranked test was used to assess the significance of results. This test is recognized as having better statis-tical power when a low number of loci (<15) is consid-ered (Luikart et al. 1998). For mtDNA, further insightinto the historical demography of M. cephalus wasachieved by mismatch distributions (i.e. the observednumber of differences between pairs of haplotypes), aBayesian skyline plot model (Drummond et al. 2005)and classical statistical tests of neutrality (Tajima1989, Fu 1997) over observed mtDNA haplotypes. Amismatch distribution is usually multimodal for popu-lations at demographic equilibrium (i.e. stationary),and unimodal for populations that experienced a re-cent demographic expansion. Harpending’s (1994)raggedness test (RI for ‘raggedness index’) was usedto determine if the observed mismatch distributionwas drawn from an expanded or a stationary popula-tion (small versus large RIs, respectively). Past popu-lation demography was also estimated using aBayesian skyline plot (BSP) model that generated aposterior distribution of effective population sizethrough time using a Markov chain Monte Carlo(MCMC) sampling procedure. The parameter m thatrepresents the number of grouped intervals was set to5. The MCMC analysis was run for 20 × 106 genera-tions (sampled every 1000 iterations), of which thefirst 10% was discarded as burn-in. The substitution

246

AOT

AOC

AOM

WMT

WME

WMA

WMB

WMG

EMZ EMK

WMO BSS

ASH

EML

EMH

EMV

BSI

EMM

A

BScenarios of dispersal:

Western (BSS, BSI, ASH, EMM, EMV, WMG, WMO, WMB, WMT, WME, WMA, AOC, AOM) Central (BSS, BSI, ASH, EMM,EMV, WMG, EMK, EMZ)Eastern (BSS, BSI, ASH, EML, EMH)

Fig. 1. Sampling locations ofMugil cephalus investigatedin the NE Atlantic and theMediterranean and BlackSeas. Location details andcodes are given in Table 1.(A) Admixture proportions ofthe 3 genetic clusters recov-ered by TESS software inM. ce phalus samples fromthe NE Atlantic (blue) andthe Mediterranean (green)and Black Seas (red). Lightblue arrows represent con-temporary currents. (B) Sce-narios of dispersal throughthe Mediterranean area usedfor ana lysis of isolation-by-distance patterns at nuclearand mtDNA markers (see

’Results: Nuclear loci’)

Durand et al.: Population structure of Mugil cephalus in the Mediterranean and Black Seas 247

model used was HKY + G. The BSP model was com-puted using BEAST v.1.7.2 (http://beast.bio.ed.ac.uk/Main_Page). The median and corresponding credibil-ity intervals of the BSP were depicted using TRACER

v.1.5 (http://tree.bio.ed.ac.uk/software/tracer/). BSPsare now a common tool in phylogeographic studies ofmarine fishes (reviewed in Grant et al. 2012), butover- interpretations concerning population growth,stasis, or population decrease and timing of demo-graphic events can easily occur because of multiplefactors. These include inadequate sampling (numberof individuals and incomplete sampling of haplo-types), but molecular clock calibrations are alsocrucial to unravel uncertainties in demographic time-lines (Ho et al. 2008, Ruzzante et al. 2008). Weadopted a conservative approach, and, in this study,we have not, to date, searched events using BSP, as noreliable calibration of mutation rate was accessible.We only observed the trends in estimates of effectivepopulation size as a function of inferred mutationalunits (Grant et al. 2012). Tajima’s D and Fu’s FS testswere used to test neutrality, with significant D valuesdue to factors such as population expansion, bottle-necks and selection (Tajima 1989). Fu’s FS test com-pares the number of haplotypes expected in a randomsample under the assumption of an infinite-site modelwithout recombination (Fu 1997). This test is sensitiveto the population demographic expansion that gener-ally leads to large negative values of FS. Analyses ofmtDNA data were carried out using ARLEQUIN v.3.5.For nuclear loci, features of past demographic eventswere examined using the interlocus g-test (Reich et al.1999), which is appropriate for the low number of lociconsidered in this study. The interlocus g-test assumesthat, in an expanding population, the variance in thewidths of the allele length distribution across loci isusually lower than in a population of constant size; anunusually low value of the g-statistic may be inter-preted as an indication of expansion. The KGTESTS Ex-cel macro provided by Bilgin (2007) was used to com-pute the interlocus g-test. Significance was assessedby computer simulations that established cut-off val-ues for a given number of samples and loci as de-scribed in Reich et al. (1999). As results of the inter-locus g-test are sensitive to variation in mutation rate(Reich et al. 1999), data were analysed with and with-out the prl-1 locus.

For both nuclear and mtDNA loci, pairwise levelsof population differentiation were investigated usingWeir & Cockerham’s (1984) θ̂. Population structurewas further examined using the analysis of molecularvariance method (AMOVA; Excoffier et al. 1992) asimplemented in ARLEQUIN v.3.5, with significance

determined by 10 000 random permutations of thedata. The number of different alleles and of pairwisedifferences were used to estimate distances in molec-ular variance analyses using nuclear and mtDNAloci, respectively. In these analyses molecular vari-ance is decomposed as follows: the variation ob servedwithin samples (ΦST), among samples with groups(ΦSC) and among groups (ΦCT). Isolation-by-distance(IBD) was tested across mtDNA and nuclear lociusing the Mantel test as implemented in GENETIX,with significance assessed by permuting data (5000iterations). The minimum distance over the continen-tal plateau (Mugil cephalus is primarily a demersalspecies foraging over this plateau) and θ̂/(1 − θ̂)(nuclear data) or ΦST/(1 − ΦST) (mtDNA data) wereconsidered among all pairs of populations in thegenetic distance matrix (Rousset 1997).

The population genetic structure was further inves-tigated using 2 different methods aimed at detectingspatial population structure and locating discontinu-ities in allele frequencies. The Bayesian clusteringmethod implemented in the software TESS (Chen etal. 2007) was used. TESS is a spatially explicit Baye -sian admixture model implementing a MCMC algo-rithm that estimates individual ancestry proportionsby incorporating spatial trends and autocorrelation inthe prior distribution. As an ‘admixture model’, TESS

assumes that the data originate from the admixture ofK putative parental populations. In these models, theparameters of interest are the ancestry coefficients (oradmixture proportions), computed for each individualin the sample and stored in a matrix, Q, with elements(qik; i = individuals, k = sample [Table 1]) representingthe proportion of the individual’s genome that origi-nates from the parental population (or cluster) K. InTESS, spatial trends are also incorporated in the Q ma-trix together with admixture proportions and are al-lowed to vary over space at both local and globalscales. In other words, the fraction of an individual’sgenome originating in the putative parental popula-tion A is proportional to its distance to A (Durand etal. 2009). Consideration of spatial trends and autocor-relation should limit the fact that non-spatial Bayesianalgorithms may be confounded by discontinuous spa-tial sampling. TESS includes a Voronoï diagram de-scribing spatially neighbouring and non-neighbour-ing populations (i.e. a ‘tessellation’), and a priordistribution on cluster labels based on the Potts model(i.e. a statistical model in which the state [multi locusgenotype] of each individual is influenced only by thestates of its neighbours in the same sample and inclose geographical samples). TESS has been shown todisplay results comparable to or better than the

Mar Ecol Prog Ser 474: 243–261, 2013

results from other types of software based on admix-ture models (Chen et al. 2007, Fran çois & Durand2010). Like other Bayesian clustering techniques,TESS not only aims to minimise the Wahlund effectwhen grouping individuals in K putative parentalpopulations, but also incorporates spatial local de-pendencies when performing clustering. To deter-mine the most probable value of K, the maximumnumber of clusters, Kmax, was sequentially increaseduntil the final inferred number of clusters, K, was lessthan Kmax. First the non-admixture model was usedwith a burn-in period of 20 000 cycles, and estimationwas performed using 30 000 additional cycles. Themaximal number of clusters from Kmax = 2 to 6 (30replicates for each value) was increased. Then, theconditional auto-regressive Gaussian mo del of ad-mixture with linear trend surface (Durand et al. 2009)was used for Kmax = 3. One-hundred runs (burn-in 3 ×104, run length 105, ρ = 0.6, α = 1) were performed,and the estimated admixture coefficients (Q matrix)were averaged over the 20 runs with the smallest de-viance information criterion (DIC). To account for la-bel switching among runs, the CLUMPP v.1.1. software(Jakobsson & Rosenberg 2007) was used.

In order to compare and to confirm outcomes ofTESS with results from an independent method, theBARRIER v.2.2 program was also used to identify thegeographic areas associated with genetic discontinu-ities at nuclear loci (Manni et al. 2004). Monmonier’salgorithm implemented in the program identifiesboundaries associated with the highest genetichetero geneity on a map where the samples are rep-resented according to their geographical coordinatesand are connected by Delaunay triangulation, withedges associated by genetic differentiation measures(θ̂). Analyses were conducted both for each of the7 nu clear loci separately as well as for the wholenuclear data set. As there is no objective criterion todefine the number of putative genetic boundaries, 4to 6 im plicit boundaries were tested to estimate relia-bility of the method. A bootstrapping procedure overthe 7 genetic matrices was used to determine howmany loci supported each barrier identified, and thusto verify the extent of data redundancy. To date, nopublished studies have applied TESS and BARRIER

together, and their relative performance in locatingdiscontinuities in allele frequencies have not beenrigorously compared.

Finally, the MIGRATE-n v.3.0 program (http:// popgen. scs.fsu.edu/Migrate/Migrate-n.html) was used toinfer the mutation-scaled migration rate M (M = m/μ,where m is the immigration rate per generation and μis the mutation rate) among the most relevant groups

of the populations identified by the AMOVA, TESS

and BARRIER using nuclear loci. The method assumesthat the populations are at equilibrium with respectto drift and migration and that the population sizesand migration rates have remained constant over thecoalescent period (~4Ne generations). A Brownianmutation model was used, and the mutation consid-ered was constant for all loci. The coalescent MLbased on MCMC with Hastings Metropolis impor-tance sampling was used to infer the various param-eters (Beerli & Felsenstein 1999, 2001). FST estimates(θ̂) among groups of populations were used as initialparameters for the estimation of Θ (= 4Neμ) and M inMIGRATE-n v.3.0. For each locus, the ML was run for10 short and 5 long chains with 50 000 and 100 000recorded genealogies, respectively, after discardingthe first 10 000 genealogies (burn-in) for each chain.One of every 20 reconstructed genealogies was sam-pled for both short and long chains. An adaptiveheating scheme with 4 concurrent chains was used;the analyses were run on a cluster computer using 1master and 15 compute nodes. Analyses usingMIGRATE-n were performed in 3 replicates. Prelimi-nary tests were performed with or without the prl-1locus to ensure consistency of the results (i.e. assum-ing that this intronic locus may influence the resultscompared to the anonymous microsatellite loci), andresults did not appear to be affected by the presenceof this locus (not reported). Hence, we hereby reportresults based on the 6 nuclear loci. Unlike estimatesof gene flow using F-statistics, MIGRATE-n allowsasymmetrical migration rates among pairs of popula-tions (e.g. MA→B and MB→A) separated by barriers togene flow as identified by TESS and BARRIER. Thus,the ratio of these estimates was used to report theestimated main direction of gene flow across recog-nised population breaks.

RESULTS

mtDNA

The genetic diversity and historical demography ofMugil cephalus in the NE Atlantic area were assessedby sequencing a 857 bp fragment of the cytb se-quence in 184 individuals from 18 locations (31.83%of the 578 individuals studied for nuclear DNA;Table 1). Twenty-three sites were polymorphic, and 5were parsimony informative in this fragment.Twenty-four mtDNA haplotypes of 29 re cor ded inthis NE Atlantic lineage (82.76%) were identified inthis study (Fig. 2), with the highest difference among

248

Durand et al.: Population structure of Mugil cephalus in the Mediterranean and Black Seas 249

H21

H22

H20

H19

H24

H18

H3

314

319

321

H10

H11

H12

H7

325c

H8

H6

H14

H15

H5

H9

H13

H16

H17

H4

322

H23

H1

H2

342

343

343c

341

343b

295

298

378

379

344

347

373

333

316

315

327

325b

308

326

337

349

371

371b

371c

286

289

285

282

283

100

100

99

75

79

97

100

73

99

88

89

99

100

98

0.05

East Atlantic (Morocco, Senegal,Guinea, Togo, Benin,Angola)

West Pacific (W Mexico, Peru)

NW Atlantic (USA, E Mexico)

M. liza (SW Atlantic)

M. bananensis

M. capurrii

South Africa

NE Atlantic(Morocco, Tunisia, SyriaIsrael, Turkey, UkraineGreece, Italy, FranceSpain, Portugal)

BS

S

BS

I

AS

H

EM

L

EM

H

EM

M

EM

V

EM

Z

EM

K

WM

G

WM

O

WM

B

WM

T

WM

E

WM

A

AO

C

AO

M

AO

T

1

1

11

10 111215

2

11

1

1 1

11

1

2

1

11

1

1

1 1

1

11

1

1

1 11

11

1

8

1 2

2

1

9 9

3

2 2 2

2

2

1 1

1

4

4

4

1

1

1

1

111

11 1

7 5 5 5

1

1

2

3 3

Fig. 2. Mugil cephalus. Phylogenetic tree depicting relationships among M. cephalus haplotypes sampled in the NE Atlanticand Mediterranean Sea, and some M. cephalus lineages (including M. liza) described in other geographic areas of theM. cephalus distribution range (Durand et al. 2012). Haplotypes found in this study are indicated in bold (H1 to H24) andrespective number of observations at each sampling site are shown in tabular form. Relationships were inferred using parti-tioned maximum-likelihood (ML) analysis of 784 aligned nucleotides from the cytb gene. Branch lengths are proportional tothe number of substitutions (scale bar: 0.05 substitutions per site) under the HKY + G model. Numbers on the branches are MLbootstrap values; those below 50% are not shown. A minimum spanning tree presenting the haplotype network is provided in

Fig. A1 (Appendix 1)

Mar Ecol Prog Ser 474: 243–261, 2013

haplotypes being 5 nucleotides (0.6% of divergenceusing Kimura 2 parameters’ distance). HaplotypeH3 was the most frequent (96 observations; 52.17%of the total number of individuals), with the second-most frequent haplotype represented in only 22 in-dividuals (H19; 22.92%) (Fig. 2). Almost all otherhaplotypes were found to be derived directly or in-directly from these 2 common haplotypes (Fig. A1 inAppendix 1). We hypothesize missing haplotypeswere rare haplotypes not recovered in this study(Fig. 2). Haplotype diversity within samples ana-lysed in this study ranged from 0 to 0.93 (Table 1).

While belonging to a single lineage, a significantlevel of mtDNA differentiation existed among pop-ulations (ΦST = 0.268, p < 0.001). Nevertheless, pair-wise estimates of mtDNA population differentiationrevealed a genetic distinctness in Black Sea sam-ples (BSS, BSI), and also for the Israeli EMH sample(Table 2). The genetic distinctiveness of EMH wasdue to fixation of Haplotype H18 in this locationonly (Fig. 2). When Black Sea samples, EMH and allother samples were treated as 3 different groups inAMOVA, no significant genetic variation was foundwithin these 3 groups (ΦSC = 0.036, p = 0.057), whilethis genetic structure explained 53.15% of the mito-chondrial variation (ΦCT = 0.53, p = 0.004). Whenthe EMH sample was excluded, mtDNA genetic dif-ferentiation was ΦST = 0.17 (p = 0.029), because ofthe Black Sea samples. A significant IBD patternwas detected when all populations were considered(Z = 334.45, p = 0.024). Nevertheless, as for the pop-ulation structuring, this relationship was due to theBlack Sea samples only. If the Black Sea sampleswere excluded, the pattern of IBD disappearedamong the remaining Atlantic and Mediterraneansamples (Z = 790.27; p = 0.302). On this basis, IBDappeared to be poorly supported in flathead mulletwith mtDNA, but see the following section for fur-ther details.

The observed mismatch distribution for Mugilcephalus was unimodal, with a peak around 1 singlesubstitution (Fig. 3), probably indicating recent pop-ulation growth, as further confirmed by the ragged-ness test (RI = 0.05, p = 0.5). BSP also supported pop-ulation growth on the whole and in Mediterraneansamples (Fig. 4). Atlantic and Black Sea samples de-picted flat BSPs, probably due to an insufficientnumber of sequences when analysed separatelythat do not provide sufficient information for reli -able inference of demographic events (Fig. 4). Ac-cordingly, with these results, numerous neutralitytests had negative values, which were sometimeshighly significant, indicative of a recent population

250

Tab

le 2

. Mu

gil

cep

hal

us.

Pai

rwis

e θ̂-

test

usi

ng

mic

rosa

tell

ite

loci

(u

pp

er m

atri

x) a

nd

cyt

och

rom

e b

hap

loty

pe

freq

uen

cies

(lo

wer

mat

rix)

bet

wee

n s

amp

lin

g lo

cati

ons

inth

e N

E A

tlan

tic,

fro

m e

ast

(Bla

ck S

ea)

to w

est

(Atl

anti

c O

cean

). I

n b

old

, si

gn

ific

ant

valu

es a

fter

Bon

ferr

oni

corr

ecti

on;

*p <

0.0

5, *

*p <

0.0

1, *

**p

< 0

.001

. S

amp

lin

g

cod

es a

re g

iven

in

Tab

le 1

BS

SB

SI

AS

HE

ML

EM

HE

MM

EM

VE

MZ

EM

KW

MG

WM

OW

MB

WM

TW

ME

W

MA

AO

CA

OM

BS

S−

0.00

00.

019*

**0.

023*

**0.

026*

**0.

051*

**0.

032*

**0.

032*

**0.

033*

**0.

023*

**0.

027*

**0.

026*

**0.

023*

**0.

024*

**0.

021*

**0.

042*

**0.

032*

**B

SI

−0.

099

−0.

029*

**0.

022*

**0.

030*

**0.

047*

**0.

029*

**0.

026*

**0.

026*

**0.

022*

**0.

020*

**0.

024*

**0.

016*

**0.

020*

**0.

014*

*0.

042*

**0.

032*

**A

SH

0.17

30.

151*

−0.

023*

**0.

013

0.03

5***

0.02

5***

0.01

8***

0.02

8***

0.01

9***

0.02

0***

0.01

6***

0.02

0***

0.01

5***

0.01

80.

035*

**0.

027*

**E

ML

0.15

20.

162*

*0.

020

−0.

010

0.02

6***

0.00

80.

012*

**0.

007

0.00

90.

003

0.00

70.

016*

**0.

007

0.00

90.

025*

**0.

015*

**E

MH

0.84

0***

0.73

7***

0.82

8***

0.79

6***

−0.

019

0.01

10.

002

0.01

20.

003

0.01

00.

001

0.00

80.

003

0.01

30.

028*

**0.

020*

**E

MM

0.32

9**

0.27

4***

−0.

013

0.01

00.

879*

**−

0.01

10.

005

0.01

00.

006

0.01

60.

016

0.00

30.

013

0.02

00.

025*

**0.

014

EM

V0.

149

0.13

6−

0.07

00.

034

0.80

3***

0.02

0−

0.00

80.

005

0.00

70.

008

0.01

2***

0.01

00.

008

0.00

80.

028*

**0.

017*

**E

MZ

0.23

60.

142

−0.

119

−0.

071

0.96

2***

−0.

062

−0.

111

−0.

001

0.00

30.

002

0.00

30.

001

−0.

001

0.00

60.

024*

**0.

009*

*E

MK

−0.

052

−0.

026

0.04

10.

078

0.72

2***

0.12

4*0.

046

0.00

7−

0.00

6*0.

000

0.00

60.

007

0.00

30.

003

0.02

5***

0.00

9**

WM

G0.

003

0.01

4−

0.00

50.

056

0.78

1***

0.07

2−

0.01

00.

016

−0.

038

−0.

004

0.00

40.

000

0.00

40.

005

0.02

4***

0.00

9W

MO

0.38

2***

0.29

2***

−0.

027

−0.

015

0.93

0***

−0.

062

0.01

0−

0.05

30.

140*

*0.

091*

−0.

001

0.00

30.

000

0.00

40.

024*

**0.

007

WM

B0.

113

0.12

8***

−0.

020

−0.

032

0.77

3***

−0.

001

−0.

009

−0.

034

0.04

3−

0.00

7−

0.01

8−

0.00

50.

000

0.00

90.

024*

**0.

012*

**W

MT

0.06

00.

060

−0.

027

0.01

10.

800*

**0.

008

−0.

020

−0.

176

−0.

011

−0.

037

0.02

70.

007

−0.

003

0.00

10.

022*

**0.

010

WM

E0.

284*

0.23

4***

−0.

029

0.04

60.

875*

**−

0.01

70.

008

−0.

049

0.09

1*0.

046

−0.

032

−0.

010

0.01

8−

0.00

40.

024*

**0.

014*

**W

MA

0.18

3*0.

177*

0.02

60.

040

0.71

4***

0.00

90.

041

−0.

060

0.03

40.

065

0.02

50.

035

0.02

60.

043

−0.

032*

**0.

018*

**A

OC

0.19

4*0.

165

−0.

015

0.01

10.

833*

**−

0.01

60.

016

0.01

80.

021

0.00

4−

0.01

2−

0.03

00.

020

−0.

014

−0.

014

−0.

017*

**A

OM

0.15

60.

142*

0.03

60.

071

0.76

1***

0.04

40.

045

−0.

011

0.01

00.

047

0.08

00.

043

0.02

20.

068

−0.

070

−0.

012

–

Durand et al.: Population structure of Mugil cephalus in the Mediterranean and Black Seas

expansion. On the overall population (or mtDNAclade) scale, FS estimates were negative and signifi-cant, indicating departure from neutrality (Table 1).

Nuclear loci

A total of 578 Mugil cephalus from 17 locationswere screened for nuclear loci (except for the Taguspopulation [AOT]; Table 1). Allelic richness and

observed levels of gene diversity were quite variableamong these loci, ranging from 4 alleles at prl-1 (Hobs:range 0.385 to 0.710) to 43 alleles at MCS15AM (Hobs:range 0.871 to 1.0). Eleven out of 119 sample−locuscombinations deviated significantly from HWE aftercorrection for multiple tests, and 5 out of 7 nuclearloci had such deviations (Table A1 in Appendix 1).This distribution makes the probability of a null allelespecifically affecting a given locus very low. No sig-nificant linkage disequilibrium was detected withinthe populations (p > 0.05; details not reported). Also,no sign of a bottleneck based on Wilcoxon sign-ranktests was detected at the nuclear loci, irrespective ofthe model of mutation used for analysis (not shown).

A low but significant level of differentiation acrosssamples was found at nuclear loci (θ̂ = 0.016, p <0.001). After correction for multiple tests, pairwise es-timates of population differentiation revealed a ge-netic distinctness of the Black Sea samples (BSS, BSI),similar to mtDNA, but also of the 2 remaining Atlanticsamples (AOC, AOM) (Table 2). Results associatedwith the classical estimation of population differenti-ation indicated 3 main genetic units in flathead mul-let: the Atlantic, the Mediterranean, and the BlackSea. These 3 units were apparent when using BARRIER

(Fig. 5), but more so when using TESS with Kmax = 3(this value was found to minimize DIC; details for al-ternative models not reported). The results can be in-

terpreted as a differential intro gressionamong parental genomes, for example,low but existing contributions of At-lantic and Black Sea parental genomesto the Mediterranean pool (Fig. 1; seebelow for additional results).

Besides these well-supported units,the eastern Mediterranean samples(EMM, EMV, ASH, EML and EMH)were different from each other whenthe corrections for multiple tests werenot considered (Table 2). This indicatesdifferent population structures, beingpanmictic in the western but differen-tiated in the eastern Mediterranean.Supplementary subdivisions amongeastern Mediterranean samples wereconfirmed by BARRIER, which identifiedgenetic breaks between Greece andLibya and in the far eastern Mediter-ranean Sea, isolating the EML popula-tion (although only 4 loci showed dif-ferentiation from the neighbouringEMH sample; Fig. 5). TESS was incon-clusive in identifying those areas as

251

0

1000

2000

3000

4000

5000

6000

7000

0 1 2 3 4 5 6Pairwise differences

Freq

uenc

y

A B

C D

Neμ

Time (×10–4)

0 0.5 1 1.5 2 2.5 3 3.5 0 0.5 1 1.5 2

0 0.5 1 1.5 2 2.5 3 3.5

1

10–2

10–3

10–4

1

10–2

10–3

10–4

0 0.5 1 1.5 2

Fig. 4. Mugil cephalus. Bayesian skyline plots estimated from an alignment ofM. cephalus sequences collected in (A) the NE Atlantic and MediterraneanSea, (B) the Atlantic, (C) the Mediterranean Sea and (D) the Black Sea. Theblack line indicates the median estimate, whereas the grey lines indicate the

95% credibility intervals

Fig. 3. Mugil cephalus. Mismatch distributions amongmtDNA cytb sequences of M. cephalus in the NE Atlanticand Mediterranean Sea: the observed distribution (darkgrey) versus the simulated distribution (light grey) under apopulation expansion model. Using the raggedness test, thepopulation expansion assumption could not be rejected

(raggedness index = 0.05, p = 0.5)

Mar Ecol Prog Ser 474: 243–261, 2013

additional barriers to gene flow (i.e.supporting Kmax = 6, no improvementof DIC; details not reported).

A significant proportion of the ex -plained genetic variance amonggroups was recovered using differentmodels of population structure (i.e.different groups of samples based onbasins, currents and different num-bers of barriers) in AMOVA (Table 3).Among those models, only the par -tition of samples that included the5 main geographic barriers estima -ted with BARRIER resulted in a non-significant nuclear genetic differentia-tion among groups (ΦSC; apparent de -crease of the Wahlund effect; Table 3).Concurrently, the partition accordingto the 3 clusters delineated by TESS didnot allow minimizing ΦSC (Table 3).

252

Fig. 5. Mugil cephalus. Genetic differences in M. cephalus in the Mediter-ranean Sea and adjacent seas, recovered with 6 microsatellite loci and 1exon-primed intron-crossing locus. Sampled locations (grey dots) with corre-sponding Voronoï tessellation (connecting grey lines) and Delaunay triangu-lation (blue and black lines) were calculated using BARRIER 2.2. Reliability ofgene flow barriers was estimated using a bootstrap procedure on 7 θ̂ ma -trices (1 per nuclear locus). Line thickness of gene flow barriers is propor-tional to the bootstrap value, and numbers indicate the number of loci thatshow significant genetic heterogeneity (i.e. number of loci supporting a

genetic break)

Groups considered in the AMOVA Fixation µsat cytbindex Φ Variation Φ Variation

(%) (%)

Black Sea [BSS/BSI] ΦST 0.0126*** 98.74 0.2633*** 73.66East Mediterranean Sea [ASH/EML/EMH/EMM/EMV/EMK/EMZ] ΦSC 0.0017** 0.16 0.2759*** 28.07West Mediterranean Sea [WMO/WMB/WMT/WME/WMA/WMG] ΦCT 0.011*** 1.10 −0.0174 −1.74Atlantic Ocean [AOC/AOM/AOTa]

Black Sea [BSS/BSI] ΦST 0.0111*** 98.89 0.2735*** 72.65Aegean Sea [ASH] ΦSC 0.0026** 0.25 0.2245*** 21.03East Mediterranean Sea [EMM/EMV] ΦCT 0.0086** 0.86 0.0632 6.32Ionian Sea [EML/EMH]SW Mediterranean Sea [WMG/EMK/EMZ]NW Mediterranean Sea [WMO/WMB/WMT/WME/WMA]Atlantic Ocean [AOC/AOM/AOTa]

Black Sea [BSS/BSI] ΦST 0.014*** 98.59 0.2858*** 71.77Aegean & Ionian Sea [ASH/EML/EMH] ΦSC 0.002*** 0.16 0.2336*** 21.77Mediterranean Sea [WMO/WMB/WMT/WME/WMA/WMG/ ΦCT 0.013*** 1.25 0.0681 6.81

EMM/EMV/EMK/EMZ]Atlantic Ocean [AOC/AOM/AOTa]

Black Sea [BSS/BSI] ΦST 0.012*** 98.80 0.2778*** 72.22Aegean Sea [ASH] ΦSC 0.001 0.05 0.2175*** 20.07East Mediterranean Sea [EML/EMH] ΦCT 0.012*** 1.15 0.077 7.7Middle Mediterranean Sea [EMK/EMZ/EMV/EMM]West Mediterranean Sea [WMO/WMB/WMT/WME/WMA/WMG]Atlantic Ocean [AOC/AOM/AOTa]

Black Sea [BSS/BSI] ΦST 0.012*** 98.81 0.3021*** 69.79Aegean Sea [ASH] ΦSC 0.0001 0.01 0.0467* 3.42NE Mediterranean Sea [EML] ΦCT 0.012*** 1.18 0.268** 26.8SE Mediterranean Sea [EMH]Middle Mediterranean Sea [EMK/EMZ/EMV/EMM]West Mediterranean Sea [WMO/WMB/WMT/WME/WMA/WMG]Atlantic Ocean [AOC/AOM/AOTa]asample only includes cytb test

Table 3. Mugil cephalus. AMOVA results considering different groups of samples based on basins, currents and differentnumbers of barriers; *p < 0.05,**p < 0.01, ***p < 0.001. ΦST: fixation index within samples; ΦSC: fixation index among samples;

ΦCT: fixation index among groups. Sampling codes and other abbreviations are given in Table 1

Durand et al.: Population structure of Mugil cephalus in the Mediterranean and Black Seas

Despite the problem associated with the EMH sam-ple (see previous subsection), this grouping also min-imized the percentage of variation associated withΦSC for mtDNA, compared to other models consid-ered (Table 3). This indicates that results from BAR-RIER based on nuclear loci were applicable to mtDNA,despite some sampling bias at this genetic marker.

The use of TESS was nevertheless informative of therelative proportion of each cluster (Kmax = 3) based onan average qik of individuals belonging to each sample. The relative proportions of each putative pa -rental genome varied spatially (Fig. 1A). Thisallowed the testing of IBD using 3 alternative sce -narios of dispersal: western, central and eastern(Fig. 1B). When considering the whole set of samples,there was no significant correlation between thegenetic and geographic distances at nuclear loci (Z =35.21, p = 0.184). Excluding peripheral populationsfrom IBD analyses according to groupings inAMOVA (e.g. the Back Sea or Atlantic samples) didnot reveal a significant IBD relationship either (notreported). A significant IBD pattern was found whenthe so-called western axis of dispersal(Z = 21.55, p = 0.015) was considered,but no significant IBD pattern wasdetected in the other 2 scenarios (cen-tral: Z = 5.96, p = 0.096; eastern: Z =1.47, p = 0.212), possibly because thenumber of populations was lowerand/or overall distance shorter than(i.e. the IBD slope/gradient was notsufficient to counteract sampling noisein estimates of θ̂) (Fig. 1B). Whenreconsidering IBD patterns at themtDNA locus according to these 3 sce-narios, the results were similar tothose for microsatellites. In deed, therewas a significant IBD pattern for theso-called western dispersal scenario (Z= 78.17, p = 0.048 [10 000 permuta-tions instead of 5000 to ensure signifi-cance at α = 0.05]), whereas no IBDpattern was found for the other sce-narios (central: Z = 13.36, p = 0.264;eastern: Z = 29.70, p = 0.218). Thiswestern IBD scenario was thereforeindicated by both nuclear and mtDNAmarkers and provides further supportfor a differential introgression amongthe 3 main population clusters.

Interlocus g-tests unravelling pastdemography from nuclear data werecomputed according to the full data

set, then to the main results provided by TESS andBARRIER (i.e. for data sets composed of 3 and 6 popu-lation clusters, respectively). Regardless of the dataset considered, results were globally negative todetect population expansion, when considering locusprl-1 or not. Values of the g-statistic ranged from 0.86to 1.62, when considering all 6 nuclear loci, and from0.98 to 1.87, when excluding prl-1. None of theseestimated g-statistics were found to report significantpopulation expansion when compared with the fifth-percentile rejection values (≤0.10 and ≤0.08, respec-tively) appropriate for the number of loci and samplesizes given in Reich et al. (1999; their Table 1).

Results from MIGRATE-n were also tested accordingto the main results provided by TESS and BARRIER

(Fig. 6). While analyses were not performed on thesame number of clusters, results were similar. HigherΘ values occurred in the Mediterranean in each case,and more specifically in the eastern Mediterraneanbasin when considering the larger number of geneticboundaries detected with BARRIER (Fig. 6). Conse-quently, lower Θ values occurred in peripheral

253

66

6

6

6

4

55

46.08

A) K = 3 (TESS)

B) K = 6 (BARRIER)

35.61

11.75

21.44

10.83

13.55

8.47

42.56 18.42

16.40

16.78

11.1936.45

23.52

Θ = 1.37

Θ = 5.18Θ = 0.60

Θ = 0.39

Θ = 0.52

Θ = 0.93

Θ = 4.16

Θ = 2.02

Θ = 1.21

Fig. 6. Mugil cephalus. Estimates of historical effective population size (num-bers in red) as estimated by Θ using MIGRATE-n among the most relevantgroups of populations identified by both (A) TESS and (B) BARRIER v.2.2, usingnuclear loci. Arrows depict the main direction of mutation-scaled migrationrate among population groups. Italic numbers represent asymetrical estimatednumber of migrants among adjacent groups of populations. Thickness ofarrows roughly illustrates the strength of asymmetric migration rate from onepopulation group to nearby groups. K: number of nuclear clusters recovered

Mar Ecol Prog Ser 474: 243–261, 2013

Atlantic and Black Sea populations. In each case, theratios of estimated numbers of migrants across theboundaries indicated a net flux of grey mullet fromthe Mediterranean population through other basins(Fig. 6), and especially from the eastern Mediterran-ean to other basins when considering K = 6 (Fig. 6B).

DISCUSSION

This study revealed patterns of population differ-entiation at mtDNA and nuclear markers in Mugilcephalus over an area spanning from the NE Atlanticto the Mediterranean and Black Seas. Previousgenetic studies focussed on reciprocal monophylyand used limited individual samples, or consideredsmaller sampling areas and did not aim to detectgenetic differentiation (Rossi et al. 1998, Blel et al.2010, Livi et al. 2011). As the genetic structure ofmarine organisms (plants, invertebrates and verte-brates) has been extensively studied in the NEAtlantic and the Mediterranean and Black Seas(Patarnello et al. 2007), patterns of genetic differenti-ation for the flathead mullet can be compared with aplethora of other data. Only a few species have, how-ever, been analysed for both mtDNA and nuclearmarkers in this area (e.g. 8 of 75 studies reviewed inPatarnello et al. 2007).

Confirmation of a single clade and mito-nuclearsignals of population expansion

In agreement with Crosetti et al. (1994) and Livi etal. (2011), the mtDNA data in our study confirms theexistence of a single clade over the Mediterraneanand Black Seas, and extends it further to the NEAtlantic (Portugal, Morocco), although the latterrequires further validation. The occurrence of a sin-gle clade is not surprising because the enclosedgeography of the Mediterranean Sea and associatedbasins, and their complex paleo-climatic history(glacial−interglacial cycling) during the Pleistoceneera, makes the whole area particularly prone tomajor demographic impacts (Patarnello et al. 2007).Similar to other fishes and invertebrates, which alsoexhibit unimodal mismatch distributions at mtDNAmarkers (review in Patarnello et al. 2007), the flat-head mullet has probably undergone recent popula-tion expansion in this area, as also demonstrated bythe star-like phylogeny of haplotypes, BSPs and thesignificant negative values of D and FS. Hence, miss-ing haplotypes probably do not affect the outcomes

of BSPs, the demographic results of which are quali-tatively congruent to more classical approaches. TheBSPs do, however, suggest rather continuous growthand did not indicate a sudden increase in effectivepopulation size (Grant et al. 2012). The BSPs have tobe considered with caution because the star-likephylogenies seen here seem especially prone tobiased inferences of quantitative aspects of pastdemographic processes (see Grant et al. 2012), whilestandard statistics such as Tajima’s D appeared to bemore buffered against biased inference when, forexample, θ̂ is low (St Onge et al. 2012).

The average level of nucleotide diversity was lowin this study (π = 0.0013), which is also consistentwith some demographic crashes, in a manner compa-rable to the intra-lineage diversity revealed with thesame mitochondrial gene in the northernmost NWPacific Mugil cephalus lineage (Shen et al. 2011). Acorrelation between the distribution range of the dif-ferent lineages and their nucleotide diversity hasbeen established in the NW Pacific. A northernmostlineage, distributed across the Sea of Japan, was lessgenetically diverse (π = 0.0003, NWP1 clade in Shenet al. 2011) and demonstrated signs of demographiccrashes during the Pleistocene era (non-equilibriumconditions), while temperate NW Pacific lineageshad larger diversity (i.e. π > 0.0030; Shen et al. 2011)and exhibited patterns of population differentiationthat reflected equilibrium conditions (Jamandre et al.2009, Shen et al. 2011). Hence, results obtained inde-pendently in other lineages support the thesis thatflathead mullet populations located at or close to thespecies’ northernmost range limit (NW Pacific orMediterranean and Black Seas) underwent rapidpopulation expansion. While timing of populationexpansion was not evaluated in this study because oflimitations to molecular clock calibrations (e.g. Ho etal. 2008, Grant et al. 2012), expansion revealed bythe mtDNA marker in Mediterranean flathead mulletvery probably arose during the Pleistocene, as signa-tures of older demographic events have shown to beerased by more recent events in marine fishes (Grant& Bowen 1998, Grant et al. 2012).

In the present study, patterns of genetic diversity atnuclear markers did not, however, suggest any bot-tleneck, and the interlocus g-tests did not providenuclear support for population expansion either.When testing for bottlenecks as well as for popula-tion expansion at the nuclear level, negative resultsmay be due to an insufficient number of loci tested(usually n = 15 or 20). Although it performs betterthan other methods when the number of loci is low,the Wilcoxon sign-rank test also has more power

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when the number of loci increases (Luikart et al.1998). Regarding the interlocus g-test, Reich et al.(1999) also reported that the use of more lociincreased the power to reject size constancy. To ourknowledge, the interlocus g-test has rarely beenused in marine species, and, in each case of use itwas with a relatively low number of microsatelliteloci (e.g. Babbucci et al. 2010, Canino et al. 2010a,b,Gaffney et al. 2010). It is therefore difficult to recon-cile patterns affecting the demographic history ofmtDNA and nuclear data in this study, maybe be -cause of an insufficient number of nuclear markers.Such results are, however, not entirely irrelevantbecause biparentally inherited nuclear genes areexpected to have effective population sizes (Ne) thatare 4 times those of uniparentally inherited genessuch as mtDNA markers. This makes nuclear genesless susceptible to erosion of neutral genetic varia-tion during population bottlenecks and less prone todetect population expansion resulting from founderevents or population recovery events after range con-traction. At some values of Ne, random drift mayreduce mtDNA gene diversities without affectingnuclear gene diversities (e.g. Canino et al. 2010b).This may have occurred in Mugil cephalus, possiblyexplaining why mtDNA did not appear to be at pop-ulation equilibrium as inferred by summary statisticssuch as, e.g. Tajima’s D and mismatch distributions,while nuclear markers may have reached this equi-librium as illustrated by detection of significant IBD,at least under a scenario involving larger distancesamong populations (the so-called ‘western scenarioof dispersal’). Babbucci et al. (2010) reported a simi-lar pattern of population expansion for mtDNA andpopulation stasis for nuclear marker in the spiny lob-ster Palinurus elephas in the NE Atlantic.

It has also been suggested that lower mtDNA diver-sity may result from various selective effects at suchmarkers (reviewed in Galtier et al. 2009). Some selec-tive events acting on mtDNA may lead to star-likephylogenies and mimic demographic population ex-pansion (Babbucci et al. 2010, Canino et al. 2010b).Demographic and selective scenarios are not mutuallyexclusive, and are, therefore, difficult to disentanglewhen using a single mtDNA marker (Haney et al.2010) and when regarding a single lineage as donehere. Haney et al. (2010) demonstrated that distinctmtDNA markers provided different pictures of demo-graphic history in the Caribbean reef fish Halochoeresbivittatus and that inference of population growthbased on the 2 mtDNA markers they used (COX1,ATPase6-8) could be an artefact of selection on thesemitochondrial proteins compared to the picture pro-

vided by a non-coding (neutral) mtDNA region (con-trol region, CR) and a nuclear-encoded marker. Popu-lation expansion of Mugil cephalus in the NE Atlanticand the Mediterranean should therefore be confirmedusing other mtDNA markers such as CR and/or se-quences of nuclear genes. However, it should benoted that in 2 of the 3 known lineages of the flatheadmullet inhabiting the NW Pacific, the COX1 and cytbmarkers exhibited reduced nucleotide diversitiescompared to CR diversity (not assessed for the thirdlineage; data compiled in Shen et al. 2011). However,as for cytb, CR also showed a star-like phylogeny andunimodal mismatch distribution for the northern line-age (Jamandre et al. 2009), indicating in this case thatvarying levels of nucleotide diversity did not translateinto conflicting population histories as reported inHaney et al. (2010). Furthermore, numerous studies ofmtDNA diversity in marine fish species within theMediterranean area were based on CR polymor-phisms, and most of them also reported a singlemtDNA lineage and rapid population expansion inthis area, as found for M. cephalus with cytb (e.g.Atarhouch et al. 2006, Charrier et al. 2006). It is un-likely that marine fish species with very distinct life-histories such as sardines (Atarhouch et al. 2006) andanglerfishes (Charrier et al. 2006) were affected byselection acting on mtDNA, producing similar star-like phylogenies. In light of these observations, con-formity to neutral expectation and interpreting resultsas a signature of population expansion appears moreparsimonious than a selection-based hypothesis.

Overall, demographic inferences suggest that thereduction in population size followed by the popula-tion expansion that occurred in Mugil cephalus andin some marine invertebrates such as spiny lobster inthis area was possibly not strong enough to affectnuclear variability (see also Canino et al. 2010b for areported case in the NW Pacific of Atka mackerelPleurogrammus monopterygius). Repeated observa-tions of possible, distinct demography should moti-vate further comparative studies of mito-nucleargenetic variation to decipher the role of neutral andselective processes.

MtDNA population differentiation

Although a single mtDNA clade/lineage was recov-ered, significant population differentiation was foundat the cytb marker between Mediterranean and BlackSea samples (ΦST = 0.17; p = 0.029). The presence inthe Black Sea of a distinct population has alreadybeen reported in other marine species, including sea

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grasses, fishes and invertebrates using mtDNA (Patar-nello et al. 2007). To our knowledge, among the mar-ine fish species found in the area, only the anchovyEngraulis encrasicolus, the sprat Sprattus sprattusand the pipefish Syngnathus typhle have beenscreened for genetic differentiation between theMediterranean and Black Seas (Magoulas et al. 2006,Debes et al. 2008, Wilson & Eigenmann Veraguth2010, respectively). The particular status of this basinwas confirmed in the present study, but contrary toanchovy and pipefish (Magoulas et al. 2006, Wilson &Eigenmann Veraguth 2010) and other studies on in-vertebrates (e.g. Peijnenburg et al. 2006), reduction ofmtDNA diversity in Black Sea samples was not ob-served. In the Black Sea samples of Mugil cephalus 3to 4 haplotypes were found, whereas the easternMediterranean contained 5 to 6 haplotypes (except atEMH). This could only be due to low samples sizes formtDNA in this study, with less sampling effort in theBlack Sea compared to the Mediterranean Sea ex-plaining lower observed diversity.

It should also be noted that Haplotype H18 wasrestricted to the Israeli (EMH) sample, while otherswere widely distributed. Together with Black Seasamples, this haplotype significantly affected mtDNAgenetic differentiation, while nuclear markers didnot show this sample to be genetically distinct. Thishaplotype clearly belongs to the single mtDNA cladedepicted in our study, and was not related to otherknown foreign clades (Fig. 2). The presence ofthis apparently private haplotype in a dispersive spe-cies such as Mugil cephalus needs further examina-tion, but it probably did not arise from repeatedsequencing errors in all individuals from this sam-pling location.

Differentiation at nuclear markers and possiblegender-biased dispersal

The inclusion of nuclear markers shed complemen-tary but distinct light on the population structurerevealed by the mtDNA in the flathead mullet.Indeed, while levels of genetic differentiation wereca. 10 to 15 times lower than those observed withmtDNA, nuclear markers demonstrated finer geneticstructuring and more genetic breaks than the uni-parentally inherited marker. They identified the NEAtlantic, the Mediterranean and the Black Seas asgenetically differentiated units. Genetic breaks lo ca -ted at the Almeria-Oran front, in the Siculo-TunisianStrait and south of the Greek Peninsula are widelyreported in the literature (Patarnello et al. 2007).

Hence, the geographical patterns of nuclear geneticdifferentiation in Mugil cephalus match those al -ready reported in numerous marine species. Never-theless, possibly due to insufficient sampling in someareas (e.g. eastern Mediterranean Sea; see below),these genetic breaks are typically not detected simul-taneously in a single species (but see Rolland et al.2007). Furthermore, when differentiation is recov-ered with nuclear markers in these areas, it is alsodetected with mtDNA (e.g. Calderón et al. 2008;more references in Patarnello et al. 2007). That isclearly not the case in M. cephalus, as the only pat-tern of genetic differentiation shared by both types ofmarkers was the distinctness of the Black Sea. Aspreviously mentioned for mtDNA, studies of geneticdifferentiation between the Mediterranean andBlack Seas using nuclear genetic markers are alsorare, being restricted so far to pipefish (Wilson &Eigenmann Veraguth 2010), flat oyster Ostrea edulis(Launey et al. 2002) and seagrass Zostera marina(Olsen et al. 2004). Studies reported nuclear geneticdifferentiation between the Mediterranean and BlackSeas, together with lower allelic richness and/ or genediversity in Black Sea samples. As for mtDNA, thisdecrease in diversity was not really observed in M.cephalus, even though the Istanbul sample (BSI) hadthe lowest gene diversity.

Partial discrepancy between levels of diversityand/or inferred patterns and levels of genetic differ-entiation at each class of loci is not unusual and hasbeen reported on several occasions for organismsfrom the Atlantic and Mediterranean (e.g. flat oyster:Diaz-Almela et al. 2004; sea bass: Lemaire et al. 2005;spiny lobster: Babbucci et al. 2010), or other marinespecies distributed worldwide (e.g. Buonaccorsi et al.2001, Canino et al. 2010b). Because of the 4-foldlower Ne, estimates of population differentiation areexpected to be higher for mitochondrial markers (e.g.Lemaire et al. 2005). At migration−drift equilibrium,an expected 4:1 ratio in mtDNA versus nuclear levelsof genetic differentiation should theoretically beobserved. Deviations from this ratio of the levels ofpopulation differentiation among markers may resultfrom the differential effects of genetic drift, mutationand migration on a marker class, or may result fromselection (i.e. general violations of the migration−drift equilibrium assumptions), or sex-biased disper-sal (e.g. Buonaccorsi et al. 2001). Indeed, sexes oftendiffer in their degree of dispersal and, hence, in theircontribution to spatial genetic structure both withinand among populations (Handley & Perrin 2007).Asymmetric migration rates among sexes, but alsospatio-temporal variation in sex ratio will then facili-

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tate differential genetic structuring between nuclearand mitochondrial markers (e.g. Consuegra & Garcíade Leániz 2007). Some authors are proponents ofpurely neutral processes. Differences in the magni-tude of estimated population subdivision fromnuclear and mtDNA markers could be accounted forentirely by differences in Ne and variance in esti-mates of population differentiation among loci (e.g.Buonaccorsi et al. 2001, Wilson & Eigenmann Ver-aguth 2010). In contrast, other authors have indicatedthat such differences cannot be accounted for with-out selection (Bensch et al. 2006, Canino et al. 2010b)and/or without sex-biased dispersal or sex-biasedphilopatry (FitzSimmons et al. 1997). As discussed forother marine species (e.g. Pleuronectes platessa:Hoarau et al. 2004), assumptions of the mutation−drift equilibrium in flathead mullet are certainly vio-lated, as indicated by probable recent populationexpansion (above), selection is poorly supported(above) and large differences in levels of populationdifferentiation resulting in different genetic struc-tures at marker loci cannot be easily interpreted.Data suggest, however, that male philopatry (female-biased gene flow) could be a component of increasedgenetic differentiation at nuclear loci. Unfortunately,there is poor empirical support for this interpretationas, while movements and migrations of flathead mullet have been extensively investigated, sex orsex ratio of migrant individuals was not considered(review in Whitfield et al. 2012).

Reliability of nuclear genetic breaks

Results obtained by TESS and BARRIER did not matchexactly, as TESS identified K = 3 versus K = 6 popula-tion clusters with BARRIER, but the 3 main clusterswere identified by both methods. Indeed, spatialinformation is not incorporated in the same mannerin each method. Basically, TESS considers both localand global trends of allelic variation that would allowfiner modelling of admixture proportions (François &Durand 2010). BARRIER only considers local trendsamong neighbouring populations without consider-ing distant ones; hence, it considers less availableinformation than TESS. Detailed comparisons of theoutcomes provided by each method using simula-tions are necessary. In the present case, however, the3 additional clusters found by BARRIER are biologi-cally relevant, as the Siculo-Tunisian Strait and thearea south of the Peloponnesus are recognized barri-ers to gene flow in numerous marine fish species (e.g.Bahri-Sfar et al. 2000, Yebra et al. 2011).

Differentiation of populations within the easternMediterranean Sea, such as the isolation of the EMLsample revealed by BARRIER, has rarely been re -ported. This area is poorly studied in the literaturebecause of a bias in sampling, with western and cen-tral areas of the Mediterranean overrepresented inthe published literature. When considered, samplingin the Aegean Sea and the eastern Mediterraneanbasin is often restricted to 1 or 2 samples that stronglylimit our knowledge of the genetic structure of taxawithin this basin. By considering 5 distinct samples ofMugil cephalus in this basin, our study is a notableexception. To our knowledge, differentiation at nu -clear loci within the eastern Mediterranean basin hasonly been reported for sea bass (Bahri-Sfar et al.2000, Castilho & Ciftci 2005). These studies supportgenetic differentiation of fish populations within theeastern Mediterranean basin, such as differentiationbetween Tunisian and Aegean populations (Bahri-Sfar et al. 2000) and differentiation among Aegeanand Turkish populations (Castilho & Ciftci 2005), asreported there for M. cephalus. Results indicate theneed for further investigation of the genetic structureof taxa within the eastern Mediterranean basin, inorder to better manage important marine resources.For example, M. cephalus is highly prized in adjoin-ing countries such as Tunisia, Egypt and Israel (Whit-field et al. 2012).

A possible history of dispersal: from the Mediterranean to the margins

Interestingly, the estimates of Θ based on clustersdetected by TESS and BARRIER indicated larger effec-tive population size for Mugil cephalus in the easternMediterranean basin compared to in more peripheralpopulations (basins). This indicates an asymmetricmigration, with a net flux of migrants from the Medi-terranean basin to adjacent basins with K = 3 asinferred with TESS. When K was set to 6, as suggestedby BARRIER, the net flux of migrants was directed fromthe eastern to the adjacent western cluster (exceptbetween the 2 easternmost Mediterranean divisions).Values of Θ decreased from eastern (Aegean Sea) towestern (Atlantic) population clusters.

However, these results obtained with nuclearmarkers have to be interpreted with caution becausepopulations must be at demographic equilibrium tocorrectly estimate these values, and this equilibriumis equivocal between mtDNA and nuclear markers.The spatial variation of the coefficient of membership(i.e. mean qik values) of the Black Sea parental popu-

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lation with TESS seems, at least intuitively, to indicateexchange of individuals from this basin to the Medi-terranean basin and that the net flux of migrants esti-mated with MIGRATE-n could be reversed. However,the very recent origin of the Black Sea (∼9000 yr BP;Major et al. 2006) does not support this interpreta-tion, and genetic markers that are at low frequencyin the Mediterranean Sea but that provide a farhigher contribution to the Black Sea gene pool havealready been reported. In the anchovy, Magoulas etal. (2006) reported very low frequency of Black SeamtDNA haplotypes within the Mediterranean,whereas they had very high frequency within theBlack Sea. We would interpret our flathead mulletresults as an increase in frequency of some low-fre-quency Mediterranean alleles in the Black Sea,rather than the reverse. Furthermore, the easternMediterranean Sea is considered to have been arefuge during glaciations, the resident organisms ofwhich dispersed when Atlantic and Mediterraneanwaters came into contact (Patarnello et al. 2007).Hence, as inferred with MIGRATE-n, a larger esti-mated population size in this area compared to moreperipheral populations is expected under this sce-nario, together with migration predominantly occur-ring from this refuge to other areas. In marine fishes,the east to west migration was also suggested by,e.g., Aurelle et al. (2003) and Lemaire et al. (2005)when studying the Atlantic−Mediterranean divide atthe Almeria-Oran front (i.e. the westernmost geneticbreak detected in this study). In Syngnathus typhle,Wilson & Eigenmann Veraguth (2010) also suggestedmigration from the Mediterranean to peripheral seas,but, as the eastern Mediterranean basin was poorlysampled, comparison with the flathead mullet cannotbe made.

Overall, patterns of dispersal inferred by thenuclear markers in this study indicated that the pre-dominant flux of migrants was against the directionof the main currents connecting those basins, as indi-cated in Fig. 1. This illustrates that the historical pro-cess — albeit certainly recent — shaped the geneticvariation of Mugil cephalus in this area.

CONCLUSIONS

For the first time, nuclear genetic variation at thescale of a single basin was demonstrated in the cos-mopolitan species Mugil cephalus. To date, suchvariation has only been detected at an inter-oceanicscale using allozymes (Crosetti et al. 1994), or in theNW Pacific, where several cryptic species are pres-

ent (e.g. Liu et al. 2009, Shen et al. 2011). As is thecase for other marine species, the Atlantic, Mediter-ranean and Black Seas were the main units thatstructured genetic variation, although furthergenetic divisions were recorded within the Mediter-ranean Sea. All the population clusters found in thisstudy with nuclear markers have been re por ted inthe literature, but this is the first time they havebeen detected together in a single species. Patternsof population structure across markers are coherentdespite less genetic structure being detected usingmtDNA and past differences in demography beinginferred by each class of markers. The data suggestthe existence of a refugium in the eastern Mediter-ranean for M. cephalus, which then dispersed to theBlack Sea and to the proximal Atlantic. Furtherwork using more nuclear and mtDNA loci and con-sidering relationships within the NE Atlantic andamong the close M. cephalus clades delineated byDurand et al. (2012) are, however, necessary to gaininformation on the historical demography of thisspecies.

Acknowledgements. We thank all the people who partici-pated in the sampling: O. Akyol, A. P. Apostolidis, C. Perdi-caris, J. A. Balbuena, P. Berrebi, H. Cabral, L. Euzet,G. Lepra, M. Hassan, P. Merella, B. Morales Nin, H. Nouiri,H. Rosenfeld, V. Sarabeev, Z. Smolenicka and E. Ünlü. Weacknowledge M. Pagès for her help with Bayesian skylineplots, O. François and R. Vitalis for further counselling andpointing out the appropriate data analysis for the presentdata set. K. Belkhir is acknowledged for implementing pro-grams on a bioinformatic cluster. Thanks to D. McKenzie forEnglish language editing. This study was funded by IRD-UR070, UMR5119, and the MUGIL program (INCO-DEV-SSA-1) and MULTRACE program (ORCHID 2011) of the NationalScience Council of Taiwan (NSC100-2911-I-291-501-MY2)and the French Ministry of Foreign Affairs.

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APPENDIX 1

Table A1. Mugil cephalus. ƒ̂ estimate of Weir & Cockerham’s (1984) equivalent of Wright’s fixation index; average valuesacross all 7 nuclear loci. Bold values significant after Bonferroni correction. *p < 0.025, ***p < 0.001. Sampling codes are given

in Table 1

Prl-1 MCS2FH MCS15CM MCS15AM MCS1EH MCS2DM MCS16DM

BSS 0.002 −0.002 −0.109 −0.074*** −0.049 0.000 0.060BSI 0.277 −0.059 0.011 0.014 0.063 −0.017 0.034ASH −0.199 −0.003 0.044 −0.020 −0.079 −0.101*** −0.119EML −0.127 −0.063 −0.062 0.072 0.028 −0.045 0.039EMH 0.077 −0.079 0.037 −0.059*** 0.001 0.078 0.144EMM 0.358 −0.080*** 0.087 0.057 −0.036 0.175 −0.257***EMV 0.127 −0.054 0.087 0.019 −0.061 −0.032 0.003EMZ −0.083 −0.045 −0.043 0.008 0.027 −0.015 −0.016EMK −0.065 −0.011 −0.040 −0.073*** 0.001 −0.041 −0.157*WMG −0.055 0.000 −0.029 −0.029 −0.016 0.035 −0.153WMO 0.200 −0.039 −0.028 −0.029 −0.106*** 0.010 −0.074WMB −0.093 −0.056 −0.017 0.006 0.020 −0.004 −0.140WMT −0.068 −0.104*** 0.100 −0.015 −0.034 −0.055*** −0.228***WME −0.184 0.022 0.016 −0.067*** −0.056 0.037 −0.173WMA 0.180 0.080 0.010 0.052 0.043 −0.026 −0.170AOC 0.036 −0.042 −0.016 0.053 −0.031 0.004 −0.040AOM −0.075 0.025 0.072 −0.026 −0.003 0.006 −0.084

H14

H15 H3

H23

H18

H20 H21

H22 H19

H17 H16

H13

H11 H10

H12

H9 H8

H7 H6 H5

H4

H2

H1

AOC

AOM

AOT

ASH

BSI

BSS

EMK

EML

EMM

EMV

EMZ

WMA

WMB

WME

WMG

WMO

WMT

EMH

H24

+90

+20

+5321

Fig. A1. Mugil cephalus.Network of cytochrome bhaplotypes collected inthe NE Atlantic and theMediterranean and BlackSeas, and considered inthis study. The lengths ofthe connecting lines relateto the number of muta-tions between haplotypes.Each circle represents ahaplotype, with the diam-eter of the circle propor-tional to the number ofsequences of that haplo-type. Populations are la -

belled as in Table 1

Editorial responsibility: Hans Heinrich Janssen, Oldendorf/Luhe, Germany

Submitted: February 10 2012; Accepted: September 26, 2012Proofs received from author(s): January 20, 2013