solea solea and solea senegalensis and its relationships with life...

Universidade de Lisboa

Faculdade de Ciências

Departamento de Biologia Animal

Genetic diversity and population structure of

Solea solea and Solea senegalensis and its

relationships with life history patterns

Tatiana Fonseca de Araújo Teixeira

Tese orientada por

Professora Doutora Maria Manuela Coelho

Professor Doutor Henrique Nogueira Cabral

Mestrado em Biologia e Gestão dos Recursos Marinhos

Especialidade em Gestão e Ordenamento do Meio Marinho

2007

"I recognize the right and duty of this generation to develop and use our

natural resources, but I do not recognize the right to waste them, or to rob by wasteful use, the generations that come after us."

Theodore Roosevelt

“Nature provides a free lunch, but only if we control our appetites.” William Ruckelshaus

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ACKNOWLEDGMENTS

To all the people that somehow have contributed to this work I hereby

express my sincere gratitude, especially to

Professor Maria Manuela Coelho and Professor Henrique N. Cabral for their

support, supervision and advice, and for guiding me trough my first steps

into marine science,

Dr. Joana Marques for her enormous support, advice, help, and especially,

friendship in all the moments, at any time and any place, even from the

other side of the World,

Dr. Célia Teixeira, for her great help from the very beginning of this work,

especially for the late night sampling at MARL and all the North to South

trips, and for making all “peixes chatos” less boring,

All the team from the laboratory of Ecologia Evolutiva e Molecular –

Carina, Irene, Rita, Maria Ana, Cristiane and Vera – for their practical help,

shared knowledge and support, and a very especial thanks to Francisco, for

always having a nice word to say and a huge lot of patience,

All the team from the laboratory of Zoologia Marinha, at the Instituto de

Oceanografia, especially to Dr. Inês Cardoso and my “final rush hour”

colleagues, Marisa, Sofia and Miguel,

People from allover Europe that contributed to the sampling process,

Cris, my true and always present friend, for all the support even 300km

apart, and companion in “Lado lunar” song in the traffic, Ju, forever

dinosaurs friends, for all the patience and care trough my horst days and for

sharing the happiness of the better ones,

Acknowledgments

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Artur for the huge help to do such amazing maps, “colouring my work”,

My family, for all the love, care and outstanding support, especially to my

mother (for all the nights that she “worked” with me), father and sister that

were always at my side encouraging me and that had a lot of patience, and

to Tó, for everything, especially for always be at my side – thank you a lot,

there are not enough words to express my gratitude.

This thesis was supported by the Project SOLEA (FEDER 22-05-01-FDR-00024), “Biologia e

estado de exploração dos stocks de espécies de linguados e solhas com interesse comercial

da costa portuguesa: contributos para a gestão sustentável dos recursos”, co-financed by EC

(FEDER-MARE).

"Let us be grateful to people who make us happy; they are the charming gardeners who

make our souls blossom."

Marcel Proust

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RESUMO

A avaliação da variação genética e o conceito de estrutura geográfica das

populações de peixes são fundamentais para a compreensão da dinâmica

das mesmas e para a conservação e exploração sustentável dos recursos

pesqueiros.

Inúmeras espécies de peixes chatos (Pleuronectiformes) possuem um

elevado valor comercial sendo, por isso, fortemente exploradas em todo o

mundo, tanto a nível das pescas como da aquacultura. Nalgumas áreas

geográficas, e em particular nos oceanos Atlântico e Pacífico, os valores das

capturas dos peixes chatos correspondem entre 10% a 30% do total de

capturas. Na costa Portuguesa, e apesar do valor total de desembarques

não ser particularmente elevado, os peixes chatos são um importante

recurso dado o seu elevado valor comercial, especialmente o do linguado

legítimo, Solea solea (Linnaeus, 1758), uma das principais espécies alvo da

pesca de arrasto na Europa. No entanto, o conhecimento sobre a biologia e

estado de exploração dos stocks das espécies de Pleuronectiformes com

elevada importância económica, é ainda incipiente e limitado,

principalmente no Sul da Europa e no Norte de África, onde a importância

destes recursos é também elevada.

S. solea e Solea senegalensis, Kaup, 1858, são espécies de linguado

marinhas, com morfologia similar, cuja principal característica do ciclo de

vida consiste na existência de uma fase juvenil, predominantemente

estuarina, e uma fase adulta, marinha. Ambas utilizam os sistemas

estuarinos como áreas de viveiro, beneficiando, assim, da elevada

disponibilidade de alimento e da existência de poucos predadores nestas

áreas. Este padrão de história vital poderá ter impacto na estruturação das

Resumo

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populações adultas, que habitam áreas costeiras marinhas mais profundas,

particularmente no que se refere à sua diferenciação genética, uma vez que

poderá induzir reduzidos valores de fluxo genético, como resultado de

comportamentos “homing” a áreas de desova e de uma forte associação

entre os locais de desova e as zonas de viveiro.

Alguns estudos de diferenciação genética, considerando vastas áreas

geográficas, e recorrendo a diferentes tipos de marcadores moleculares,

têm sido desenvolvidos em peixes chatos com interesse comercial, sendo o

linguado legítimo uma das espécies mais estudadas. No entanto, nenhum

destes estudos usou como marcador molecular o citocromo b (gene do DNA

mitocondrial). Por outro lado, o único estudo populacional existente para S.

senegalensis foi desenvolvido apenas na costa Portuguesa. A análise de

nove loci polimórficos de isoenzimas, permitiu verificar uma grande

homogeneidade genética entre as diversas amostras.

O principal objectivo deste trabalho consistiu em determinar a diversidade

genética e a estrutura populacional de S. solea e S. senegalensis ao longo

das suas áreas de distribuição, desde o Mar Báltico até ao Norte de África e

Mar Mediterrâneo, relacionando-as com os seus padrões de história vital.

A diversidade genética e estrutura populacional de S. solea e de S.

senegalensis foram analisadas com base em sequências completas do

citocromo b do DNA mitocondrial (cerca de 1141 pares de bases) de

diversas amostras recolhidas ao longo das suas áreas de distribuição.

Valores de elevada variação genética (h) e reduzida a moderada diversidade

nucleotídica (π) foram observados em todas as populações analisadas de S.

solea e S. senegalensis (excepto na população do Norte de Portugal de S.

senegalensis), níveis esses característicos de espécies com amplas áreas de

distribuição geográfica e elevado fluxo de indivíduos. Os resultados da

análise demográfica, assim como as árvores haplotípicas em forma de

estrela sugerem expansão em termos do efectivo populacional das

populações de ambas as espécies.

Resumo

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Para S. solea, foram detectados níveis significativos de diferenciação

genética à escala inter-regional, verificando-se a existência de dois grupos

de populações: um correspondente às populações do Atlântico e outro

correspondente às populações do Mediterrâneo. Esta diferenciação genética

Atlântico – Mediterrâneo poderá ser explicada pelas características

biogeográficas, nomeadamente pela grande descontinuidade oceanográfica

do estreito de Gibraltar-Mar de Alboran. As populações de S. solea do

Atlântico demonstraram, ainda, constituir uma unidade panmíctica ou

“quasi-panmíctica”, presumivelmente devido aos elevados níveis de fluxo

genético que ocorrem em cada geração. No entanto, as populações do

Mediterrâneo exibiram níveis significativos de diferenciação populacional

entre as regiões Este e Oeste, o que poderá ser consequência de uma

possível recolonização do Mediterrâneo por populações do Atlântico. Uma

outra explicação para os elevados níveis de diferenciação encontrados entre

populações do Mediterrâneo, parece residir na complexa história do

Mediterrâneo, que sofreu a acção de várias forças estruturadoras durante os

últimos episódios glaciares. A diminuição do nível do mar nestas épocas

provocou alteração das linhas de costa, levando à criação de refúgios

distintos nesta área, separando as zonas Este e Oeste, que, desde então,

apresentam diferentes regimes hidrográficos, sendo o da zona Oeste mais

uniforme que o da zona Este devido à geografia de cada uma destas zonas.

A referida diferenciação poderá, ainda, ser atribuída a factores relacionados

com a biologia de S. solea, tal como o intervalo de temperaturas toleradas

pelas larvas desta espécie. Analisando todos os indivíduos amostrados, i.e.,

populações do Atlântico e Mediterrâneo, verifica-se a existência de

isolamento por distância entre as populações de S. solea.

S. senegalensis exibiu um padrão de heterogeneidade genética

significativa, mesmo entre populações separadas por curtas distâncias

geográficas, presumivelmente contidas na área potencial de migração dos

indivíduos desta espécie, e onde, a longo prazo, o balanço entre fluxo

genético e forças responsáveis pela diferenciação genética poderá resultar

em gradientes, aumentando a diferenciação genética em função do

aumento da distância geográfica. Por si só, as distâncias geográficas

parecem, de facto, ser muito importantes na estruturação das populações

Resumo

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de S. senegalensis, havendo uma forte associação entre estas e as

divergências genéticas verificadas no grupo de amostras analisadas,

estando esta associação fortemente relacionada com as diferenças

latitudinais entre amostras. Os resultados de diferenciação obtidos para S.

senegalensis, salientam, ainda, a importância da temperatura como factor

redutor do fluxo genético entre populações, uma vez que a variação da

temperatura condiciona a duração do período larvar, assim como a taxa de

sobrevivência das larvas, restringindo a dispersão larvar e,

consequentemente, o nível de fluxo genético, promovendo, assim, o

isolamento genético de populações geograficamente próximas.

A homogeneidade verificada entre as amostras de S. solea e a

diferenciação encontrada entre as amostras de S. senegalensis, observadas

no presente estudo, sugerem uma reduzida importância dos sistemas

estuarinos como forças estruturantes da diferenciação genética das

populações destas espécies, uma vez que, embora ambas possuam um

padrão similar de utilização dos sistemas estuarinos, exibem diferentes

níveis de diferenciação populacional.

Em conclusão, os resultados obtidos neste estudo demonstraram a

existência de estruturação populacional em ambas as espécies, embora a

diferentes escalas: enquanto em S. solea a diferenciação genética se

verifica entre as populações do Atlântico e as do Mediterrâneo, assim como

no interior do Mediterrâneo, entre as populações localizadas a Este e a

Oeste, em S. senegalensis foi detectada diferenciação genética entre

populações de acordo com a sua distância geográfica, sendo tanto maior

quanto mais distantes se encontram as populações. Os níveis de

diferenciação detectados para cada espécie reflectem, de uma forma

generalizada os seus padrões de história vital, estando particularmente

relacionados com a duração do período larvar pelágico e com a sua

tolerância a variações na temperatura.

O desenvolvimento de uma análise mais aprofundada, incluindo um

estudo combinado de vários marcadores moleculares, e uma amostragem

espacial mais alargada, incluindo amostras de locais representativos de toda

Resumo

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a área de distribuição das espécies e o maior número possível de amostras

de um mesmo local, poderá permitir uma análise mais precisa e completa,

conduzindo a uma melhor compreensão da estruturação das populações de

S. solea e S. senegalensis.

Os resultados deste estudo poderão ter particular interesse para sustentar

a definição de unidades populacionais (stocks) destas espécies,

contribuindo, assim, para uma gestão mais sustentável destes recursos

pesqueiros.

Palavras-chave: linguado comum, linguado do Senegal, DNA

mitocondrial, estrutura genética populacional, padrões de história vital.

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SUMMARY

Soles (Solea spp.) are heavily exploited all round the world (fisheries and

aquaculture) due to their high commercial value. Nonetheless, the

knowledge on their biology and the exploitation status of their stocks is

limited to certain geographical areas. A key issue to management is the

population structure of fisheries resources.

The aim of the present study is to determine the genetic diversity and

population structure of Solea solea (Linnaeus, 1758), and Solea

senegalensis, Kaup, 1858, throughout their distribution range and to

evaluate its relationships with life history patterns.

The genetic diversity and population structure of both species were

analysed based on sequences of cytochrome b of mitochondrial DNA (about

1141 bp in length).

A low nucleotide diversity (π<0.005) and high haplotype diversity

(h>0.600) was observed for both species (except for Portugal-North

population of S. senegalensis, h=0.378). The pairwise Φ-statistics and

AMOVA for S. solea evidenced a high genetic divergence between Atlantic

and Mediterranean populations and between the Eastern and Western areas

of the Mediterranean. Significant differences were also observed between

samples of S. senegalensis, with geographical distance per se assuming a

very important role in structuring populations and presenting a strong

association with genetic divergence amongst the set of samples analyzed.

Minimum spanning network analyses, revealed star-shaped patterns for

populations of both species, suggesting that populations had undergone

Summary

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expansion following bottlenecks. Atlantic populations of S. solea, ranging

from the Baltic Sea to South Portugal could be considered as representative

of the same panmictic unit, presenting high levels of gene flow.

The higher levels of diversity observed in S. senegalensis compared to S.

solea may be due to differences in the duration of the pelagic larval phase,

spawning period and habitat use patterns, with water temperature

assuming a major role in restricting gene flow and consequently in the

population genetic structure of both species.

Key-words: common sole, Senegal sole, mitochondrial DNA, genetic

population structure, life history patterns.

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TABLE OF CONTENTS

AKNOWLEDGMENTS ............................................................................ i

RESUMO......................................................................................... iii

SUMMARY ....................................................................................... ix

Chapter 1

General Introduction......................................................... 3

Chapter 2

Genetic diversity and population structure of Solea solea and

Solea senegalensis and its relationships with life history

patterns ......................................................................... 19

2.1 Introduction .............................................................................. 19

2.2 Material and methods ................................................................. 23

2.2.1 Sampling and DNA extraction ............................................ 23

2.2.2 PCR amplification and sequencing ...................................... 24

2.2.3 Sequence alignment ......................................................... 25

2.2.4 Population genetic analysis ............................................... 25

2.2.5 Neutrality and demographic history .................................... 27

2.3 Results ..................................................................................... 28

2.3.1 Solea solea ..................................................................... 28

2.3.2 Solea senegalensis ........................................................... 37

2.4 Discussion ................................................................................ 42

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Chapter 3

Concluding remarks and challenges .................................... 59

ANNEX. Supplementary information

Chapter 1

Chapter 1

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General Introduction

The use of molecular genetic techniques in fisheries research began in the

1950s with studies of blood group variants, primarily in tunas, salmonids

and cod, successfully demonstrating the existence of genetically controlled

variation which could be the basis of analyses of population structure of

those species (Ward & Grewe, 1994). In the 1960s decade, the study of

haemoglobin variants of whiting (Gadus melangus) and cod (Gadus

morhua), by Sick (1961), increased the use of protein electrophoresis

among fish geneticists (Avise & Smith, 1974; Allendorf et al., 1976), for

being a quicker, reasonably inexpensive, reproducible method, especially

because the majority of fish species with commercial interest showed

enough variation, allowing to develop a fast analysis of population structure.

Although the initial knowledge about fish genetics came from the use of

protein electrophoresis, this technique presents certain limitations, like the

requirement of fresh or frozen tissue, the need for a larger amount of tissue

samples than most DNA methods, and the inappropriate resolution to detect

interpopulational and interindividual differences (Ward & Grewe, 1994).

The use of mitochondrial DNA (mtDNA) in genetic studies is generally

assumed to be more powerful than the referred protein analysis, for both

phylogenetic and population studies, mostly due to the characteristics

presented by that marker: haploidy; maternal transmission - it presents ¼

of effective population size of nuclear DNA (nDNA), being, therefore, more

sensitive to detect reductions in genetic variation, particularly genetic drift

effects; putative lack of recombination; and relatively high mutation rates –

it has a large capacity to accumulate mutations that gives it a faster rate of

evolution than nDNA in higher animals (Ward & Grewe, 1994). Another


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advantage relies in the fact that the study of this molecular marker can be

done using fresh, frozen or ethanol-stored tissues and only requires a small

amount of sample (few nanograms). Moreover, the whole molecule may be

regarded as a single locus with multiple alleles (Park & Moran, 1994).

Mitochondrial genome has been widely used to study phylogenetic

relations between several taxa, from family level to population level, not

only because it evolves 10 times faster than nuclear DNA, but also due to

the characteristics that make it easy to amplify and sequence (Ward &

Grewe, 1994). However, the maternal inheritance of mtDNA can be a

limitation to its use since it does not provide information about the genome

of males, whose dispersal behaviour might be different from that of

females, from the same population.

Although the reference to tandemly repeated sequences of DNA in

eukaryotic genomes appeared during the 1960s, it was the development of

recombinant DNA technology, namely the development of “DNA

fingerprinting” techniques (Jeffreys et al., 1985), that enhanced the

importance of using this highly diverse sequences in studies regarding

population biology. With the finding of highly polymorphic microsatellite loci

in the middle 1990s, the potential to detect very low levels of differentiation

in species presenting a high gene flow increased substantially, allowing the

discrimination of individuals and populations (Carvalho & Hauser, 1994).

Such genetic markers have been routinely used in recent studies

considering fish species with high dispersal capabilities such as cod (Nielsen

et al., 2003), European seabass (Bahri-Sfar et al., 2000) and eel (Wirth &

Bernatchez, 2001), constantly detecting population substructure.

Due to their origin, microsatellites are multi-allelic in a population and di-

alellic in an individual. They are codominant markers that exhibit Mendelian

heredity, allowing the distinction of heterozygote or homozygote individuals

in a given loci, therefore enabling analyses of relationships, structure and

classification at the individual (genotype) and population (allelic

frequencies) levels (Wan et al., 2004).

Chapter 1

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Nonetheless, and independently of the molecular marker used, data from

DNA is easy comparable and allows to search for the relations among

organisms at any level, from sibling individuals to species of different

kingdoms (Avise, 1994).

Population structure of a species is the result of a complex interaction

between demographic parameters (e.g. growth, recruitment, reproduction,

mortality), life history patterns (e.g. homing behaviour, pelagic larval

stages) and genetic processes (e.g. selection, mutation, drift, gene flow).

Since the end of 19th century, population dynamics (life history and

demography) of several fish species with commercial interest have been

studied. However, several methods are quite difficult to be used on the

analyses of the structure of exploited stocks or populations of marine fish

species (ecological performance, parasites distribution, physiological and

behavioural characteristics, tagging, morphometric and meristic analysis,

calcified structures, cytogenetics, immunogenetics, blood pigments and

genetic molecular tools). Therefore, the resort to heterogeneity of molecular

markers, such as proteins and nucleic acids, has become of an universal

and undeniable utility (Carvalho & Hauser, 1994), but only more recently

have become available to complete studies of populational structure,

especially those aiming the definition of stocks, not only due to the

increasing availability of different molecular techniques in genetics, but also

due to the recognition of the importance of genetic data.

The analysis of genetic variation among fish species allows the

discrimination at the species, population and individual levels, the

identification of hybrids, the establishment of species and population

phylogeny and phylogeographic history, the discrimination of different

stocks and the analyses of their migration patterns and effective size, and

to assess individual stock contribution to mixed stock fisheries, evaluating

the response of stocks to fisheries exploitation (Wirgin & Waldman, 1994).

In the fisheries context, genetic tools have also been used in aquaculture,

to study pathogenic organisms in high commercial value species and the

expression of growth factors during maturation (Park & Moran, 1994). Other


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genetic studies have also considered introduced species, the effects of

fisheries and pollution on genetic diversity and the genetics of rare and

endangered species (Ward & Grewe, 1994).

Sustainable exploitation of fish stocks is a concept that dominates the

fisheries management for almost 50 years. The central idea is that each

stock has a harvestable surplus, and that fisheries that do not exceed this

will not compromise the stock’s natural perpetuation (Carvalho & Hauser,

1994). However, in 2002, almost 76% of the world’s marine stocks were

considered fully exploited or overexploited (FAO, www.fao.org).

Unfortunately, and even after the collapse of major fisheries, such as cod

and herring (Hutchings, 2000), remains the idea that marine fishes,

particularly pelagic fishes, are resilient to large population reductions. The

trend of stocks offering potential for expansion is clearly downwards,

decreasing from 40% in 1970, to 24%, in 2004 (FAO, 2005).

The definition of stocks and their boundaries has become an essential part

of fisheries management, especially since several studies developed in

Northern Europe have referred high pressure on marine resources, resulting

in a decrease of effective population size, being some stocks already out of

their biological safety limits. However, the geographic areas considered in

the establishment of management policies do not often coincide with the

biological stocks’ distribution, simply because of seasonal movements of

these stocks between the several management areas, or because different

fish stocks may occur simultaneously in a unique area, generally resulting in

a mismatch in the spatial scale of management and biological reality

(Pawson & Jennings, 1996).

To achieve the sustainable development of fisheries resources at a global

scale, it is necessary the accurate knowledge of the ecology and biology of

exploited species, particularly regarding their evolution and population

dynamics in space and time. Likewise, studies such as those already

developed for cod , by Knutsen et al. (2004), for herring by Ruzzante et al.

(2006), and for common sole, by Rolland et al. (2007), are needed in order

Chapter 1

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to predict the impact of fishing exploitation and to forecast the efficiency of

management measures.

The stock concept has numerous meanings in the fisheries context, such

as an abstract and undefined unit or a spatial location in which the fish are

found and can be exploited by a specific fishing technique, and in the

biological context – a genetic unit defined as a group of individuals that

mate randomly, with a variable degree of spatial and temporal integrity

(Carvalho & Hauser, 1994).

In marine species with high dispersal patterns, which includes most of

marine fishes, it is considered that high gene flow leads to population

homogeneity, at a large scale, as a result of their life cycle patterns; factors

like high fecundity, passive dispersal of larvae and active migration of

adults, lead to the lower levels of genetic differentiation exhibited by marine

species, relatively to fresh water or anadromous species (Carvalho &

Hauser, 1994; Ward et al., 1994; Ward, 2002).

The extent of gene flow will generally determine the genetic heterogeneity

of the species, in the absence of localised selection (Exadactylos et al.,

1998). Several marine fish exhibit low levels of haplotype diversity and

population divergence (Avise, 1994), that can be a result of low rates of

genomic evolution or recent bottleneck events. Mechanisms such as climatic

fluctuations, different time and place of spawning (Ruzzante et al., 2006),

and physical structuring forces, like geographical distance (Hoarau et al.,

2002), depth, ocean currents and fronts favouring larval retention (Nielsen

et al., 2005), transitions in temperature and salinity (Nielsen et al., 2003),

as well as strong phylopatry, can explain how population structure can

evolve in a environment without any obvious physical boundaries to gene

flow (Hemmer-Hansen et al., 2007), resulting in small, but significant and

usually temporally stable, levels of genetic divergence in many species of

marine fishes (Ruzzante et al., 1996; Wirth & Bernatchez, 2001; Nielsen et

al., 2003; Nielsen et al., 2004; Ruzzante et al., 2006).


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The failure in detecting differentiation can be a consequence of the

incapability to detect variation, explained by insufficient resolution of the

markers used, or of the reduced knowledge of the biology of the studied

species.

Genetic structure of a species reflects individual’s organization. In a

simplified theoretic perspective, there are three basic models of structure in

natural populations (Richardson et al., 1986). The simplest model considers

the existence of a unique panmictic unit, where there is no population

subdivision, and random mating between individuals is verified, resulting in

the absence of significant genetic differentiation between groups of

individuals of certain regions. Another model considers discrete populations

in a major panmictic group, but genetic flow between them is limited,

suggesting an accentuated genetic differentiation between different units,

conducing to a discontinuity of allele frequencies in several loci within the

same geographical area. There are also several variants of these models

which take into account the genetic flow between several population units.

A third group of models, based on the isolation by distance (IBD) concept,

consider a continuous geographical distribution of populations, but gene

flow between them is limited by the dispersal capacity of each individual.

Although they consider the existence of genetic differentiation between

population units, genetic variation in several loci is gradual, and discrete

boundaries like those referred in the previous model do not exist. But more

important than the identification of a structural model, is the recognition of

the factors determining population genetic structure.

The knowledge on population structure is fundamental to manage fisheries

of high commercial value species that present a broad-scale distribution.

Several flatfish species (Pleuronectiformes) are heavily exploited all around

the world (fisheries and aquaculture). In some geographical areas,

particularly in the Atlantic and the Pacific, flatfish represent from 10% to

30% of total catches (Millner et al., 2005). In the Portuguese coast, and

although the value regarding their total catch is not particularly high,

flatfishes are amongst the species with the highest commercial value.

Chapter 1

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In several geographical areas, especially in Northern Europe,

Pleuronectiformes have been studied for a long time. Aspects like

abundance of some of these resources (Rijnsdorp et al., 1992), feeding

ecology (Knutsen, 1992), growth (Andrade, 1992) and reproduction (Deniel,

1984; Deniel et al., 1989) are well documented in the literature.

Nonetheless, knowledge on their biology and exploitation status is limited,

especially in Southern Europe and Northern Africa, where the importance of

these resources in undeniably high. In the Portuguese coast, most studies

on the ecology of Pleuronectiformes have focused juvenile stages,

particularly in estuaries and coastal lagoons (e.g. Dinis, 1986; Andrade,

1990; Cabral, 1998, 2000, 2003; Cabral & Costa, 1999; Cabral et al.,

2002). However, the acquired knowledge in some geographic areas cannot

be transposed to other areas, because of their distinct oceanographic and

climatic characteristics.

Several differentiation studies have been conducted on commercially

important flatfish species considering a broad geographic scale. For plaice,

Pleuronectes platessa (Linnaeus, 1758), Purdom and Thompson (1976) and

Ward and Beardmore (1977) used allozyme loci to compare samples from

the Irish Sea, Bristol Channel and southern North Sea and were not able to

establish any differentiation. However, significant population differentiation

was detected by Hoarau et al. (2004) between shelf and off-shelf

populations (with microsatellites and mtDNA), and with mtDNA data they

were able to detect differentiation within the continental shelf.

For halibut, Hippoglossus hippoglossus (Linnaeus, 1758) (Foss et al.,

1998) and brill, Scophthalmus rhombus (Linnaeus, 1758) (Blanquer et al.,

1992), the conduced allozyme analysis were not able to detect

differentiation within North Atlantic populations. In turbot, Scophthalmus

maximus (Linnaeus, 1758), Nielsen et al. (2004) reported subtle

differentiation between the Baltic and the North Sea, and Florin and

Höglund (2007) found low, although significant, genetic differentiation

within the Baltic Sea, both studies with microsatellites analysis.


- 10 -

For flounders, Platichthys flesus (Linnaeus, 1758), and Platichthys

stellatus (Pallas, 1787), through the analysis of allozyme variation, Borsa et

al. (1997) detected a strong differentiation between Atlantic, Western

Mediterranean and Adriatic populations. High differentiation levels were also

found within the Mediterranean area. In the North Atlantic region, the levels

of differentiation were much lower although indicating some isolation by

distance. Considering the North Sea region, differentiation has been

reported, north and south of the Dogger Bank. Hemmer-Hansen et al.

(2007) analysed microsatellite loci and found a clearly large and highly

significant genetic structuring among the samples of P. flesus from several

localities of the Northeast Atlantic and Baltic Sea.

In sole, Solea solea (Linnaeus, 1758), Kotoulas et al. (1995) detected,

with allozyme loci analysis, significant differentiation between

Mediterranean and Atlantic populations, as well as a weak North-South

differentiation across the European Atlantic coast and East-West

differentiation across the Mediterranean, suggesting the existence of an

isolation by distance (IBD) model. The authors further conclude that the

Atlantic populations constitute however, one single panmictic or quasi-

panmictic unit. Considering the same geographical scale, Rolland et al.

(2007) obtained similar results of differentiation, with the analysis of

nuclear-DNA non-coding loci. Differentiation within the Mediterranean

region was also documented by Guarniero et al. (2002) and Garoia et al.

(2007), with the study of control region of mtDNA and microsatellites and

amplified fragment length polymorphisms (AFLPs), respectively.

The between-region differences found in flounder and sole are generally

attributed to narrow larval temperature tolerances of these two flatfish

species, compared with other flatfish of the same region (Hoarau et al.,

2002).

Within the Portuguese coast, Cabral et al. (2003) obtained low genetic

differentiation between samples of common sole and Senegal sole, Solea

senegalensis, Kaup, 1858, from several estuarine systems, and Pinheiro et

al. (2005) indicated a great variability among samples of sand sole, Solea

Chapter 1

- 11 -

lascaris, (Risso, 1810), suggesting low levels of differentiation of this

species, both using allozyme electrophoresis.

The main objective of this study was to determine the genetic diversity

and population structure of S. solea and S. senegalensis, throughout their

distribution range, from the Baltic Sea to North Africa and Mediterranean

Sea, evaluating the relationships found in the context of the life history

patterns and ecology of these flatfishes.

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Chapter 2

Chapter 2

- 19 -

Genetic diversity and population structure of Solea solea and

Solea senegalensis and its relationships with life history

patterns

T. F. Teixeira1, C. M.Teixeira1, M. M. Coelho2 and H. N. Cabral1

Universidade de Lisboa, Faculdade de Ciências, 1Instituto de Oceanografia & 2Centro de

Biologia Ambiental, Campo Grande, 1749-016 Lisboa, Portugal

Abstract: The genetic diversity and population structure of Solea solea and Solea senegalensis were analysed, based on the complete cytochrome b sequence of mitochondrial DNA (about 1141 bp in length), of samples obtained throughout the species distribution range. A low nucleotide diversity (π<0.005) and high haplotype diversity (h>0.600) was observed in both species (except for Portugal-North population of S. senegalensis, h=0.378). The pairwise Φ-statistics and AMOVA of S. solea samples evidenced the genetic divergence of Atlantic and Mediterranean populations and of Eastern and Western Mediterranean populations. Significant differences were also observed between samples of S. senegalensis. Atlantic populations of S. solea, ranging from Baltic Sea to South Portugal could be considered as representative of the same panmictic unit. Minimum spanning network analysis revealed star-shaped patterns for populations of both species, suggesting that populations have undergone expansion following bottlenecks. The higher levels of diversity observed in S. senegalensis, compared to S. solea, may be due to differences in the duration of the pelagic larval stage, spawning period and habitat use patterns, with water temperature assuming a major role in restricting gene flow and consequently in the population genetic structure of both species. Key-words: common sole, Senegal sole, mitochondrial DNA, genetic population structure, life history patterns.

2.1 Introduction

The assessment of genetic variation and the concept of geographical

structure in marine fish populations are fundamental to the understanding

of population dynamics and to the conservation and sustainable

management of fisheries resources (Carvalho & Hauser, 1994; Bailey,

1997). Soles (Solea spp.) are heavily exploited resources all around the

world (fisheries and aquaculture) presenting a high commercial value. In

Genetic diversity and population structure

- 20 -

fact, common sole, Solea solea (Linnaeus, 1758) is one of the main target

species for the European beam-trawl fishery, and heavy fishing pressure on

its stocks over the past years has reduced landings from 60.000 tones, in

1994, to 40.000 tones, in 2003 (FAO, www.fao.org). Concern for collapse of

this resource has emphasized the importance of conducting studies of its

stocks biology, distribution, origin and structure (Millner et al., 1996).

According to the Portuguese fisheries statistics of the past few years,

flatfishes represent approximately 1.1% of total fish landings, which

corresponds to 143.25 million euros, 7.3% of the total value of landings

(source: DGPA). This area has, in fact, a peculiar interest to flatfishes: it is

a border area between three biogeographic zones - the warm temperate

North Atlantic, the cold temperate North Atlantic and the Mediterranean –

constituting the northern or southern limit of distribution for many of the

species found here (Cabral et al., 2003a, 2003b), and allowing the

occurrence in simpatry of species characteristic from North Africa,

Mediterranean and North Europe, all presenting a high diversity of life

history patterns and habitat use (i.e. species typical of estuarine

environment, species that are exclusively marine, occurring in high depth,

with several feeding habitats, different reproductive strategies, different

distribution patterns, longevity, etc). The geomorphological particularities of

the Portuguese coast, namely a narrow continental shelf divided by deep

canyons, could induce a population substructuring pattern (Cabral et al.,

2003a).

Beyond common sole, other flatfishes such as the Senegalese sole, Solea

senegalensis, Kaup, 1858, sand sole, Solea lascaris, (Risso, 1810), flounder,

Platichthys flesus, (Linnaeus, 1758), brill, Scophthalmus rhombus,

(Linnaeus, 1758), turbot, Scophthalmus maximus, (Linnaeus, 1758),

Microchirus azevia, (Capello, 1867) and Atlantic spotted flounder, Citharus

linguatula, (Linnaeus, 1758), are also of high commercial value in

Southwest Europe fisheries.

S. solea and S. senegalensis are marine species, similar in their

morphology and distribution, from North Africa and the Western

Chapter 2

- 21 -

Mediterranean up to the Bay of Biscay, being found on sandy and muddy

bottoms at depths of 0-200 m (Quéro et al., 1986). The main feature of

their life cycle is a division into a juvenile phase, predominantly estuarine,

and an adult phase, which is marine. Both species use estuarine systems as

nursery areas, in order to benefit from the high food availability and the

existence of few predators (Cabral et al., 2003a). This life history pattern

may have an impact on the structuring of offshore adult populations,

particularly on their genetic differentiation, since it may be related to a low

gene flow, as the result of the possible homing behaviour to spawning

grounds and a strong association between spawning and nursery areas.

Moreover, the existence of physical barriers to larval dispersion, such as

sharp temperature and salinity gradients, hydrodynamic eddies favouring

larval retention, and the active vertical swimming of larvae, by which they

can avoid passive transport off nursery areas (Kotoulas et al., 1995a), can

also contribute to a high genetic differentiation. However, high genetic

exchanges can be induced by the long duration of spawning season and

larval period and high fecundity (Kotoulas et al., 1995a) as well as by the

planktonic stages, although these are limited in their dispersal by

temperature tolerance (Borsa et al., 1997).

Few studies of broad-scale geographic differentiation have considered

commercially important flatfish, but common sole inhabiting the northern

areas of the Eastern Atlantic have been particularly well studied using

different kinds of genetic markers: allozymes (Quignard et al., 1986;

Kotoulas et al., 1995a; Exadactylos et al., 1998; Cabral et al., 2003a),

control region of mitochondrial DNA (mtDNA) (Guarniero et al., 2002),

RAPDs (random amplification of polymorphic DNA) (Exadactylos et al.,

2003), nuclear-DNA non-coding loci (Rolland et al., 2007), microsatellites

and amplified fragment length polymorphisms (AFLPs) (Garoia et al., 2007).

Kotoulas et al. (1995a) detected significant differentiation between

Mediterranean and Atlantic S. solea populations, as well as a North-South

differentiation across the European Atlantic coast and East-West

differentiation across the Mediterranean, suggesting the existence of an

isolation by distance (IBD) model in population structure. At a smaller

geographical scale (Central Mediterranean region), Guarniero et al. (2002)


- 22 -

revealed the existence of genetic structure among adjacent basins, related

to the hydrogeographical features of the region. Local and regional studies

with North European and Mediterranean samples (e.g. Exadactylos et al.,

1998; Cabral et al., 2003a) suggested the absence of population structure,

although the results of Cabral et al. (2003a) supported an IBD model.

However, most studies conducted with different nuclear markers pointed

out the differentiation between Atlantic and Mediterranean populations of S.

solea, being the differences within the Mediterranean explained by historical

processes favouring vicariance, and to combined effects of contemporary

gene flow modulated by ecological traits and hydrologic features (Garoia et

al., 2007; Rolland et al., 2007).

Less is known about S. senegalensis populations. Ecological information

concerning this species is scarce and refers almost exclusively to the

Portuguese coast (e.g. Andrade, 1992; Cabral & Costa, 1999, Vinagre et al.,

2006). The generality of genetic studies developed with this flatfish focuses

its systematics and phylogeny, particularly in the Mediterranean (Goucha &

Pasteur, 1983; Goucha et al., 1987; Borsa & Quignard, 2001; Infante et al.,

2004), only recently including a broader-scale area (Pardo et al., 2005).

The only population genetic study was developed by Cabral et al. (2003a)

that analysed nine polymorphic allozyme loci, pointing out a low genetic

differentiation and the absence of population structure for S. senegalensis

inhabiting several estuarine systems along the Portuguese coast.

The aim of the present study is to determine the genetic diversity and

population structure of S. solea and S. senegalensis throughout their

distribution range, using mtDNA cytochrome b data, and to evaluate its

relationships with species life history patterns, that could be especially

useful for the sustainable management of these resources.

Chapter 2

- 23 -

2.2 Material and methods

2.2.1 Sampling and DNA extraction

A total of 172 soles, belonging to both species, were collected from 13

different locations, covering their distribution range, from the Baltic Sea to

the Mauritanian coast, and throughout the Mediterranean Sea (Figure 1).

The number of individuals analysed for each species and the location of

sampling areas are presented in Table 1.

Fig. 1- Sampling areas for each species analysed in this study and their distribution

range (blue – S. solea; orange – S. senegalensis). Codes of sampling areas are

defined in Table 1.


- 24 -

Table 1- Geographic location of the sampling areas, their codes, species sampled and number of individuals collected in each area (SS - Solea solea; SN - Solea senegalensis).

Geographical location Area

Code Coordinates

Sampled

Species

Sample

size

Denmark (Baltic Sea–North Sea transition-Kattegat) MBA N 54.13º E 011.26º SS 10 Denmark (North Sea) MN N 54.80º E 008.13º SS 10 Belgium (North Sea) B N 51.57º E 003.24º SS 10 United Kingdom (Irish Sea) UK N 53.90º W 003.30º SS 12 France (Biscay Bay) BY N 45.84º W 001.48º SS/ SN 12/10 Portugal-North (Atlantic Ocean–off Figueira da Foz) PN N 40.14º W 008.89º SS/SN 10/10 Portugal-Centre (Atlantic Ocean–off Setúbal) PC N 38.45º W 008.99º SS/SN 10/9 Portugal-South (Atlantic Ocean-off Olhão) PS N 37.00º W 007.79º SS/SN 10/10 Mauritânia (Atlantic Ocean) MAUR N 18.28º W 016.40º SN 10 France(Gulf of Lyon) GL N 43.45º E 004.01º SS 10 Italy (Adriatic Sea- off Venice) IT N 45.36º E 012.44º SS 10 Greece (Aegean Sea-off Thessaloniki) ME N 40.36º E 022.77º SS 9 Turkey (Aegean Sea-off Izmir) TQ N 38.79º E 026.60º SS 10

Total genomic DNA was extracted from tissue samples (fin or muscle),

following a phenol-chloroform protocol, as described by Wasko et al.

(2003).

2.2.2 PCR amplification and sequencing

The entire cytochrome b (cyt b) mitochondrial DNA gene (about 1141 bp

in length) was amplified by PCR, using two specific primers (Infante et al.,

2004): GLU1 (5’-GGGGATTTTAACCTCAGGCGTTCAGTTTAC-3’) and Thr2 (5’-

GGACTAATCGCTTGAAAAAACCACCGTTG-3’).

PCR reactions of 25 µl total volume, containing approximately 50 ng of

template DNA, 2 mM of MgCl2, 0.2 µM of dNTP´s, 0.5 µM of each primer, 2

U of Taq DNA Polymerase (Fermentas) and 10x Taq buffer (10mM Tris-HCl,

ph 9.0; 50 mM KCl) (Fermentas), were conducted as follows: an initial

preheat step at 92ºC for 120s, followed by 5 cycles of denaturing at 92ºC

for 15s, annealing at 51ºC for 45s and extension at 72ºC for 90s, and 30

cycles of denaturing at 92ºC for 15s, annealing at 52ºC for 45s and

extension at 72ºC for 90s, finishing with an extension step at 72ºC for 7

min.

Chapter 2

- 25 -

PCR products were subjected to electrophoresis in 1% agarose gels,

containing ethidium bromide staining, and visualized under UV light.

Products were then purified using 10 U of Exonuclease I (Fermentas), 1 U of

Shrimp Alkaline Phosphatase (SAP) (Fermentas), and 6.25x SAP buffer

(Fermentas). The protocol for purifying PCR products consisted of 30 min at

37ºC, 15 min at 80ºC and 5 min at 12ºC. All products were sequenced in

both directions, using the PCR primers and the BigDye Terminator Cycle

Ready reaction Kit (Applied Biosystems), and visualized in an AbiPrism 377

Automated Sequencer (Applied Biosystems) (Stabvida®).

2.2.3 Sequence alignment

Contiguous sequences were assembled in Sequencher ver. 4.0

(GeneCodes Corp.) and compared to similar sequences deposited in

GenBank, using the Basic Local Alignment Search Tool (BLAST) available on

the NCBI website (NCBI, http://www.ncbi.nlm.nih.gov/Genbank). All

sequences were aligned using Sequencher ver. 4.0 (GeneCodes Corp.) and

checked by eye.

2.2.4 Population genetic analysis

Intrapopulation diversity was analysed by estimating gene diversity (h),

and nucleotide diversity (π) (Nei, 1987), using DNASP ver. 4.10.9 (Rozas et

al., 2003). Population structure and genetic variation were characterised by

Φ–statistics (analogous to the F- Statistics of Wright (1969)), which

incorporate genetic distance between haplotypes and haplotipic frequencies,

using Arlequin ver. 3.11 (Excoffier et al., 2005). The software Modeltest 3.7

(Posada & Crandall, 1998) was used to find the best model of evolution that

fitted the data, according with the AKAIKE criterion. Although resultant

models were different for both species (GTR+I+G - general time reversible

plus Proportion invariant plus Gamma, for S. solea, and GTR- general time

reversible for S. senegalensis) the pairwise distance method, with γ = 0,


- 26 -

was considered for both species analyses, since the resultant models were

not included in Arlequin v. 3.11.

Analysis of molecular variance (AMOVA) was used to assess the population

configuration and the geographical pattern of population subdivision

(Excoffier et al., 1992). For hierarchical analyses, populations were grouped

according to their geographic location. Several other rearrangements were

tested and the one that maximised among group variation (θCT) was

assumed to be the most probable subdivision. Simulations with 1000

permutations were made to test the statistic significance of results. The

isolation by distance (IBD) model was analysed by testing the association

between geographic and genetic distances (Smouse et al., 1986) through a

Mantel test (Mantel, 1967) with 10 000 permutations, as implemented in

Arlequin ver. 3.11. Geographical distances between populations were

measured as a straight line along the coast between each two areas. A

standard Bonferroni a posteriori correction was applied to determine the

level of significance in multiple tests.

Minimum spanning networks (using the median joining agglomeration

method) were constructed with Network ver. 4.201 (Bandelt et al., 1999)

based on haplotype data of the sampled populations, and generated with

MacClade 4.08 (Maddison & Maddison, 1989). Network ver. 4.201 uses the

maximum parsimony method for reconstructing trees, choosing the smallest

and simplest as the best. Median-joining algorithm was used with default

parameters, as recommended for this kind of data (Bandelt et al., 1999).

The population structure was also investigated using the program BAPS

4.1 (Corander et al., 2007), which allows the analysis of sequence data.

Given a maximum value of partitions, the algorithm uses a stochastic

optimization procedure to find the clustering solution with the highest

‘marginal likelihood’ of K (i.e., an approximation of the most probable

number of differentiated genetic populations conditional on observed data).

The maximum number of partitions, K, was set as ranging from 5 to 20 (S.

senegalensis) and from 12 to 20 (S. solea) and, in each case, we the

Chapter 2

- 27 -

analyses were ran several times, recording the best partition found and the

corresponding ‘marginal likelihood’.

2.2.5 Neutrality and demographic history

Arlequin ver. 3.11 was used to test for departures from mutation-drift

equilibrium with Tajima’s D-test (Tajima, 1989) and Fu’s Fs (Fu, 1997). In a

constant-size neutral equilibrium population, Tajima's D is expected to be

nearly zero, and when some kind of balancing selection is acting Tajima's D

tends to be positive. However, changes in population size can also affect

Tajima's D and, therefore, in a population with decreasing size, Tajima's D

is expected to be positive, while a negative Tajima's D is predicted for a

population with increasing size. Fu's Fs statistics also provide a test for

population growth. Negative Fs values may indicate the existence of an

excess of rare alleles, which can be explained by an excess of recent

mutation, and processes like growth of effective populational size or

hitchhiking, occurred in the past, can also be evidenced by the values of

this statistic (Fu, 1997). The relationship between nucleotide (π) and

haplotype (h) diversities can also provide some information on history of

populations (Grant & Bowen, 1998).

Demographic history of the two species was also studied by analysing

mismatch distributions of pairwise differences between all individuals of

each population using Arlequin ver. 3.11. These analyses allowed the

discrimination of a rapid population expansion (possibly after a bottleneck)

or a state of stability over time. The mismatch distribution appears like a

Poisson curve (unimodal), if accumulation of new mutations is greater than

the loss of variation through genetic drift (resulting in population

expansion), or multimodal if the generation of new mutations is offset by

random genetic drift, maintaining population size (Rogers & Harpending,

1992).


- 28 -

2.3 Results

2.3.1 Solea solea

Genetic diversity was very high, with 75 haplotypes recovered from 123

individuals. Of these, 77% were unique. The most common haplotype, H7

(15% of the samples) was shared by 18 individuals from Northeast (NE)

Atlantic populations (B, BY, MBA, MN, PC, PN and UK), and did not included

any of the Mediterranean populations. Moreover, no haplotypes were shared

between individuals from NE Atlantic and Mediterranean populations. The

second major common haplotype, H38, was shared by 10 individuals, all

from Mediterranean populations (ME and TQ) (Table 2).

Table 2- Haplotype frequencies and composition of Solea solea populations. Haplotype MBA MN B UK BY PN PC PS GL IT ME TQ TOTAL

1 - - 1 - - - - - - - - - 1

2 - - 1 1 - - - - - - - - 2

3 - - 1 - - - - - - - - - 1

4 - - 1 - 1 - - - - - - - 2

5 - - 1 - - - - - - - - - 1

6 - - 1 - - - - - - - - - 1

7 1 6 2 4 2 2 1 - - - - - 18

8 - - 1 - - - - - - - - - 1

9 3 - 1 - - - - - - - - - 4

10 - - - - 1 - - - - - - - 1

11 - - - - 1 - - - - - - - 1

12 - - - - 1 - - - - - - - 1

13 - - - - 1 - 1 - - - - - 2

14 - - - - 1 - - - - - - - 1

15 - - - - 2 - - - - - - - 2

16 - - - 1 1 - - - - - - - 2

17 - - - 1 1 1 - - - - - - 3

18 - - - - - - - - 1 - - - 1

19 - - - - - - - - 1 - - - 1

20 - - - - - - - - 1 - - - 1

21 - - - - - - - - 1 - - - 1

22 - - - - - - - - 1 - - - 1

23 - - - - - - - - 1 - - - 1

24 - - - - - - - - 1 - - - 1

25 - - - - - - - - 1 - - - 1

26 - - - - - - - - 1 - - - 1

27 - - - - - - - - 1 2 - - 3

28 - - - - - - - - - 1 - - 1

29 - - - - - - - - - 1 - - 1

30 - - - - - - - - - 2 - - 2

31 - - - - - - - - - 1 - - 1

32 - - - - - - - - - 1 - - 1

33 - - - - - - - - - 1 - - 1

34 - - - - - - - - - 1 - - 1

35 3 1 - - - - - - - - - - 4

Chapter 2

- 29 -

Table 2- continued

The overall level of haplotype diversity (h) was high, ranging from 0.667

in the North Sea (MN) and Turkey (TQ) populations, to 1.000 in Portugal-

South (PS) and Gulf of Lyon (GL) populations. On the other hand,

nucleotide diversity (π) exhibited by all populations was low, ranging from

0.001 in Turkey (TQ) to 0.007 in Portugal-South (PS). The number of

haplotypes presented by each population varied, ranging from 5 in the

Baltic Sea (MBA), North Sea (MN) and Turkey (TQ) populations to 10 in Bay

of Biscay (BY), Portugal-South (PS) and Gulf of Lyon (GL) (Table 3).

Haplotype MBA MN B UK BY PN PC PS GL IT ME TQ TOTAL

36 2 - - - - - - 1 - - - - 3

37 1 - - - - - - 1 - - - - 2

38 - - - - - - - - - - 4 6 10

39 - - - - - - - - - - 1 - 1

40 - - - - - - - - - - 1 - 1

41 - - - - - - - - - - 1 - 1

42 - - - - - - - - - - 1 1 2

43 - - - - - - - - - - 1 - 1

44 - 1 - - - - - - - - - - 1

45 - 1 - - - - - - - - - - 1

46 - 1 - - - - - - - - - - 1

47 - - - - - - 2 - - - - - 2

48 - - - - - - 1 - - - - - 1

49 - - - - - - 1 - - - - - 1

50 - - - - - - 1 - - - - - 1

51 - - - - - - 1 - - - - - 1

52 - - - - - - 1 - - - - - 1

53 - - - - - - 1 - - - - - 1

54 - - - - - 1 - - - - - - 1

55 - - - - - 2 - - - - - - 2

56 - - - - - 1 - - - - - - 1

57 - - - - - 1 - - - - - - 1

58 - - - - - 1 - - - - - - 1

59 - - - - - 1 - - - - - - 1

60 - - - - - - - 1 - - - - 1

61 - - - - - - - 1 - - - - 1

62 - - - - - - - 1 - - - - 1

63 - - - - - - - 1 - - - - 1

64 - - - - - - - 1 - - - - 1

65 - - - - - - - 1 - - - - 1

66 - - - - - - - 1 - - - - 1

67 - - - - - - - 1 - - - - 1

68 - - - - - - - - - - - 1 1

69 - - - - - - - - - - - 1 1

70 - - - - - - - - - - - 1 1

71 - - - 1 - - - - - - - - 1

72 - - - 1 - - - - - - - - 1

73 - - - 1 - - - - - - - - 1

74 - - - 1 - - - - - - - - 1

75 - - - 1 - - - - - - - - 1


- 30 -

Table 3- Genetic diversity of cyt b sequences for Solea solea populations (standard deviation is presented between brackets).

Population Nucleotide diversity

(π) Haplotype diversity

(h) Number of haplotypes

MBA 0.005 (0.003) 0.844 (0.080) 5

MN 0.003 (0.002) 0.667 (0.163) 5

B 0.005 (0.003) 0.978 (0.054) 9

UK 0.005 (0.003) 0.909 (0.080) 9

BY 0.004 (0.003) 0.970 (0.044) 10

PN 0.004 (0.003) 0.956 (0.059) 8

PC 0.004 (0.003) 0.978 (0.054) 9

PS 0.007 (0.004) 1.000 (0.045) 10

GL 0.003 (0.002) 1.000 (0.045) 10

IT 0.003 (0.002) 0.956 (0.059) 8

ME 0.002 (0.001) 0.833 (0.127) 6

TQ 0.001 (0.001) 0.667 (0.163) 5

From all the tested rearrangements (see Tables I and II of results in

Annex, page i), the one considering the existence of two groups, one

including NE Atlantic populations and another including Mediterranean

populations, was the combination that maximised the among group

variation (θCT=0.485; P<0.001) (Table 4), therefore being assumed as the

most probable genetic subdivision.

Table 4- Results of the AMOVA performed for Solea solea, considering two groups (Atlantic and Mediterranean).

Source of variation Total variance (%) Fixation indices P value

Among groups 48.5 θCT=0.485 <0.001 Among populations within groups 4.31 θSC=0.084 <0.001

Within populations 47.19 θST=0.528 <0.001

Low ΦST values were found in all pairwise analyses within the NE Atlantic

populations, while those obtained between the group of NE Atlantic

populations and the group of Mediterranean populations were high (0.385-

0.725) and significant (P<0.001), after the Bonferroni correction being

applied. High and significant ΦST values (0.191-0.368; P<0.001) were also

obtained by pairwise analysis between Western (GL and IT) and Eastern

(ME and TQ) Mediterranean populations (Table 5).

Chapter 2

- 31 -

Table 5- ΦST values for Solea solea samples (* indicates significant values, P<0.001)

A Mantel test including all sampled populations (from Baltic Sea to Aegean

Sea) revealed a clear correlation between genetic and geographical distance

(Z= 0.63; P<0.05). On the other hand, Mantel tests including only Atlantic

populations or Mediterranean populations, revealed that genetic distances

are not correlated with geographical distances (Z= 0.30, P>0.05 and Z=

0.44, P>0.05, respectively) (see Figure I in Annex, page ii).

The haplotype network derived from cyt b sequences, and using the

maximum parsimony method, is presented in Figure 2. Size of circles is

proportional to the number of individuals within each haplotype (Table 2).

Two major common haplotypes were found, and represent individuals

from NE Atlantic populations (H7, shared between 18 individuals) and

Mediterranean populations (H38, shared between 10 individuals of Aegean

Sea (ME) and Turkey (TQ) populations).

These two haplotypes differ from each other by 8 mutations, and 3

haplotypes are missing between them. It is also possible to visualize a third

haplotype (H27), shared by the individuals from Gulf of Lyon (GL) and Italy

(IT) populations, from which several haplotypes derive by only one

mutation. This network suggests the existence of two main sub-populations,

Atlantic and Mediterranean, and population structuring within the

Mediterranean, as no shared haplotypes were found between individuals

from Western (GL and IT) and Eastern (ME and TQ) Mediterranean

MBA MN B UK BY PN PC PS GL IT TQ ME MBA - MN 0.080 - B -0.028 0.013 - UK 0.023 0.174 0.007 - BY 0.021 0.021 -0.09 0.083 - PN 0.044 0.158 0.027 0.047 0.015 - PC 0.030 0.046 -0.003 0.075 0.000 0.007 - PS 0.085 0.207 0.085 0.083 0.095 0.001 0.020 - GL 0.462* 0.599* 0.465* 0.414* 0.502* 0.482* 0.488* 0.385* - IT 0.528* 0.657* 0.530* 0.480* 0.563* 0.537* 0.531* 0.412* 0.056 - TQ 0.627* 0.771* 0.630* 0.566* 0.652* 0.664* 0.664* 0.553* 0.232* 0.368* - ME 0.587* 0.725* 0.587* 0.533* 0.617* 0.618* 0.618* 0.506* 0.191* 0.285* 0.017 -


- 32 -

populations. These results are in agreement with the ones obtained by the

pairwise ΦST analysis. The star-shaped network also suggests that

populations have undergone expansion following bottlenecks.

Fig. 2- Minimum spanning network analysis of haplotypes identified in samples of Solea solea. Distances between haplotypes are proportional to the number of mutational steps. Colours correspond to populations as follows: Baltic Sea-North Sea transition (MBA), Denmark coast (MN), United Kingdom (UK), Belgium coast (B), Bay of Biscay (BY), Portugal-North (PN), Portugal-Centre (PC), Portugal-South (PS), Gulf of Lyon (GL), Italy (IT), Aegean Sea (ME) and Turkey (TQ).

The population analysis performed in BAPS (Figure 3) suggests the

existence of three different clusters, represented by the blue, red and green

vertical bars. Two of the clusters are present in all Atlantic populations (blue

and green), but not in Mediterranean populations, and the red cluster is

only found in Mediterranean populations.

Chapter 2

- 33 -

Fig. 3- Population structure obtained with BAPS in Solea solea populations. Each colour corresponds to a different cluster. Legend: B- Belgium coast; BY- Bay of Biscay; GL- Gulf of Lyon; IT- Italy; MBA Baltic Sea-North Sea transition; ME- Aegean Sea; MN- Denmark coast; PC- Portugal-Centre; PN- Portugal-North; PS- Portugal-South; TQ- Turkey; UK-United Kingdom.

The population structure presented in both analyses, haplotype network

and BAPS, is concordant, indicating the absence of genetic structure within

the Atlantic. However, the sub-structure in the Mediterranean presented by

the haplotype network (absence of shared haplotypes between Western and

Eastern Mediterranean populations) was not detected trough BAPS analysis.

All together, these results suggest a significant genetic differentiation

between NE Atlantic and Mediterranean populations, low levels of genetic

differentiation within the Mediterranean area and absence of differentiation

within NE Atlantic region.


- 34 -

In the demographic analysis, all populations exhibited moderate to highly

negative D-values in Tajima’s D-test, except for Italy (IT) and Baltic Sea

(MBA), although significant D-values were only obtained for the Turkey (TQ)

population (P<0.05). Fs-values were negative and significant in all

Mediterranean populations (Gulf of Lyon (GL), Italy (IT), Aegean Sea (ME)

and Turkey (TQ)), and in some Atlantic populations (Belgium (B), Bay of

Biscay (BY), Portugal-Centre (PC) and Portugal-South (PS)) (Table 6).

Table 6- Results of Tajima’s D-test (Tajima, 1989) and Fu’s Fs-test (Fu, 1997) with associated probability for Solea solea populations (significant values in bold).

Tajima's D P Fu’s Fs P

MBA 0.929 >0.05 1.838 >0.05

MN -1.023 >0.05 0.322 >0.05

B -0.856 >0.05 -3.284 <0.05

UK -0.853 >0.05 -1.593 >0.05

BY -0.769 >0.05 -0.371 <0.05

PN -0.773 >0.05 -2.153 >0.05

PC -1.016 >0.05 -3.604 <0.05

PS -0.872 >0.05 -4.380 <0.05

GL -1.189 >0.05 -6.974 <0.05

IT 0.087 >0.05 -3.291 <0.05

ME -1.286 >0.05 -2.410 <0.05

TQ -1.667 <0.05 -2.847 <0.05

The analysis of the parameters of the sudden expansion model and the

goodness-of-fit test applied to it, (Table 7), suggested the occurrence of

expansion in all S. solea populations, except for Baltic Sea (MBA) and

Portugal-North (PN), where significant SSD-values ( Sum of squared

deviations) results in the rejection of null hypothesis of sudden expansion in

population size.

Chapter 2

- 35 -

Table 7- Parameters of the sudden expansion model and its goodness-of-fit test significance, applied to Solea solea populations. S, number of polymorphic sites; θ0, pre-expansion population size; θ1, post-expansion population size; τ, time in number of generations; SSD, sum of squared deviations and P value (* indicates significant values, P<0.05) .

S θ0 θ1 Τ SSD P value

MBA 13 0 99999 8.0 0.113* 0.003

MN 11 0 3.725 5.9 0.094 0.220

B 19 0 36.367 7.4 0.022 0.358

UK 23 0 99999 7.9 0.181 0.204

BY 18 0 13.567 6.9 0.014 0.712

PN 16 0 99999 5.6 0.101* 0.003

PC 18 2.438 50.625 3.4 0.011 0.700

PS 26 0 99999 8.0 0.008 0.691

GL 15 0 99999 4.1 0.006 0.783

IT 9 0.017 99999 3.3 0.008 0.712

ME 7 0 99999 1.6 0.018 0.568

TQ 4 0 99999 1.0 0.031 0.292

Results from the analysis of mismatch distributions of pairwise

differences between all individuals of each population, as revealed from the

mutimodal curves, suggested that Atlantic populations are stable over time,

with the exception of Portugal-Centre (PC) and Portugal-South (PS).

Histograms from Mediterranean populations showed a pattern proximal to

unimodal curves, suggesting a sudden expansion in population size

(P>0.05) (Figure 4). However, only Turkey (TQ) population exhibited

concordant results of SSD-values (non-significant), mismatch distributions

(unimodal curve), Tajima’s D-value (negative and significant) and Fu’s Fs-

value (negative and significant) supporting a sudden expansion on its size.

According to all the previous analyses, Atlantic populations seem to

constitute a panmictic unit (i.e. very low ΦST values between Atlantic

populations), demographic analyses were also performed considering all the

Atlantic populations as one unit, and the results suggested a sudden

expansion in population size (see Figure II, in Annex, page iii), concordant

with the star-shaped haplotype network.


- 36 -

MBA

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9

MN

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10

B

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10

UK

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10

BY

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11

PN

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8

PC

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11

PS

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9 10 11 12

GL

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8 9

IT

0

5

10

15

20

25

30

0 1 2 3 4 5 6 7 8

ME

0

5

10

15

20

25

30

0 1 2 3 4 5 6

TQ

0

5

10

15

20

25

30

0 1 2 3

Fig. 4- Pairwise mismatch distributions (Rogers & Harpending, 1992) and simulated model of sudden expansion (Rogers, 1994) for each population of Solea solea.

Observed Simulated

Number of pairwise differences

Pairw

ise m

ism

atc

h

Chapter 2

- 37 -

2.3.2 Solea senegalensis

The cyt b diversity was relatively high, with 15 haplotypes recovered from

the 49 individuals analysed, being 60% of these haplotypes unique. A major

haplotype, corresponding to 45% of the samples, was shared between 22

individuals belonging to the Bay of Biscay (BY) and Portugal-North, Centre

and South populations (PN, PC and PS, respectively) (Table 8).

Table 8- Haplotype frequencies and composition of Solea senegalensis populations

Haplotype BY PN PC PS MAUR TOTAL

1 2 - - - - 2

2 3 8 6 5 - 22

3 4 - - - - 4

4 1 - - - - 1

5 - - - - 6 6

6 - - - - 1 1

7 - - - - 1 1

8 - - - - 1 1

9 - - - - 1 1

10 - - 1 3 - 4

11 - 1 1 - - 2

12 - - 1 - - 1

13 - 1 - - - 1

14 - - - 1 - 1

15 - - - 1 - 1

Haplotype diversity (h) presented a wide range of values, from 0.378 in

the Portugal-North population to 0.778 in Bay of Biscay population.

However, the nucleotide diversity (π) exhibited by all populations was low

(0.001 to 0.002) and the number of haplotypes per population was also low,

varying between 3 in Portugal-North (PN) to 5 in Mauritania (MAUR) (Table

9).

Table 9- Genetic diversity of cyt b sequences for Solea senegalensis populations (standard deviation is presented between brackets).

Population Nucleotide diversity

(π) Haplotype diversity

(h) Number of haplotypes

BY 0.002 (0.001) 0.778 (0.091) 4

PN 0.001 (0.001) 0.378 (0.181) 3

PC 0.001 (0.001) 0.583 (0.183) 4

PS 0.001 (0.001) 0.711 (0.118) 4

MAUR 0.001 (0.001) 0.667 (0.163) 5


- 38 -

The AMOVA performed to the three specified groups (BY; PN, PC and PS;

MAUR) indicated that a high and significant proportion of the total variance

was attributed to differences between the predefined groups of populations

(P<0.001) (Table 10). Nevertheless, the highest, and significant,

percentage of variation (52.66%, P<0.001) was obtained within populations

(the other tested rearrangements, Tables III and IV, are presented in the

Annex, page i).

Table 10- Results of the AMOVA performed for Solea senegalensis, considering three groups (Bay of Biscay (BY); Portugal-North, Centre and South (PN, PC and PS); Mauritania (MAUR))


Among groups 48.55 θCT=0.485 <0.001

Among populations within groups (-) 1.21 θSC= (-) 0.024 <0.001

Within populations 52.66 θST=0.473 <0.001

The highest levels of genetic differentiation were obtained between the

Bay of Biscay (BY) population and all the others under study (Table 11). No

genetic differentiation was found between Portuguese coast samples, which

were the geographically closest ones, being the highest and significant

values of ΦST presented by a pair of the most geographically distant

populations, BY and MAUR (ΦST =0.502). It is also worth noticing that

Portugal-Centre (PC) population did not present significant genetic

differentiation from any of the sampled populations.

Table 11- ΦST values for Solea senegalensis samples (*indicates significant values, P<0.01)

BY PN PC PS MAUR BY - PN 0.453* - PC 0.405 -0.032 - PS 0.429* 0.095 0.000 -

MAUR 0.502* 0.444* 0.301 0.405* -

Chapter 2

- 39 -

The Mantel test including all the sampled populations (from Bay of Biscay

to Mauritania) failed to show a significant correlation between genetic and

geographical distance (P=0.06), despite the high value of the correlation

coefficient obtained (Z=0.75) (see Figure III in Annex, page iii).

The haplotype network based on the cyt b sequences presented a star-

shape (Figure 5), suggesting population expansion. Size of circles is

proportional to the number of individuals within each haplotype.

Fig. 5- Minimum spanning network analysis of haplotypes identified in samples of Solea senegalensis. Distances between haplotypes are proportional to the number of mutational steps. Colours correspond to samples as follows: Bay of Biscay (BY), Portugal-North (PN), Portugal-Centre (PC), Portugal-South (PS), Mauritania (MAUR).

The most common haplotype, H2, was shared by individuals from four of

the five sampled populations – Bay of Biscay (BY), Portugal-North (PN),

Portugal-Centre (PC) and Portugal-South (PS). All other haplotypes derived

from this one, by one to five mutations, with the highest differentiation

being found between the Bay of Biscay (BY) and Mauritania (MAUR)

populations, which was also evidenced by the absence of shared haplotypes

between these populations. Since Mauritania (MAUR) shared no haplotypes

with the other populations, and it is the most southern area sampled, a

latitudinal differentiation was also suggested.

The structure obtained trough BAPS analysis (Figure 6) revealed three

different clusters, represented by blue, red and green vertical bars.

Whereas the green cluster is present in all populations, the blue one occurs


- 40 -

only in Bay of Biscay (BY) population, corroborating the pattern obtained in

the network. The presence of the red cluster only in Portugal-Centre (PC)

and Mauritania (MAUR) populations is concordant with the non-significance

of the ΦST value exhibited in the pairwise analysis of genetic differences

between these two populations.

Fig. 6- Population structure obtained with BAPS in Solea

senegalensis populations. Each colour corresponds to a different

cluster. Legend: BY: Bay of Biscay; MAUR- Mauritania; PC-

Portugal-Centre; PN- Portugal-North; PS- Portugal-South.

In the demographic analyses using Tajima’s D-test and Fu’s Fs-test,

Portugal-Centre (PC) population was the only one that presented negative

and significant D-values and Fs-values (D=-1.610; Fs=-1.283; P<0.05).

Mauritania (MAUR) and Portugal-North (PN) populations also exhibited

negative and significant Fs-values (Table 12).

Table 12- Results of Tajima’s D-test (Tajima, 1989) and Fu’s Fs-test (Fu, 1997) with associated probability for Solea senegalensis populations (significant values in bold).

Tajima's D P Fu’s Fs P

BY 1.284 >0.05 0.942 >0.05

PN 1.401 >0.05 -1.164 <0.05

PC -1.610 <0.05 -1.283 <0.05

PS -0.658 >0.05 -1.176 >0.05

MAUR -1.388 >0.05 -1.896 <0.05

Chapter 2

- 41 -

Pairwise mismatch distributions in each population and the parameters of

the model of sudden expansion and the values of the goodness-of-fit test

applied to it are given in Figure 7 and Table 13, respectively.

BY

0

10

20

30

40

0 1 2 3 4 5 6

PN

0

10

20

30

40

0 1 2 3

PC

0

10

20

30

40

0 1 2 3 4

PS

0

10

20

30

40

0 1 2 3

MAUR

0

10

20

30

40

0 1 2 3 4

Fig.7- Pairwise mismatch distributions (Rogers & Harpending, 1992) and simulated model of sudden expansion (Rogers, 1994) for each population of Solea senegalensis.

Observed Simulated

Pairw

ise m

ism

atc

h



- 42 -

Histograms resulting from the analysis of mismatch distributions of

pairwise differences between all individuals showed a pattern proximal to a

mutimodal curve for the Bay of Biscay (BY) population, indicating its

stability over time. The other populations presented distributions similar to

unimodal curves in the mismatch analysis, and non-significant SSD values

(P>0.05).

Table 13- Parameters of the sudden expansion model and its goodness-of-fit test significance, applied to Solea senegalensis populations. S, number of polymorphic sites; θ0, pre-expansion population size; θ1, post-expansion population size; τ, time in number of generations; SSD, sum of squared deviations and P values.

S θ0 θ 1 τ SSD P value

BY 5 0.002 4.817 4.5 0.066 0.221

PN 2 0 99999 0.5 0.006 0.693

PC 4 0.197 3.450 0.9 0.001 0.920

PS 3 0 99999 1.1 0.040 0.163

MAUR 5 0.007 3.492 1.7 0.012 0.621

Portugal-Centre (PC) was the only population that exhibited concordant

results of SSD-values (non-significant), pairwise mismatch distributions

(unimodal curve), Tajima’s D-value (negative and significant) and Fu’s Fs-

value (negative and significant) supporting a sudden expansion in

population size.

2.4 Discussion

Nucleotide and haplotype diversities can provide some information on

history of populations. High genetic variation (h) and low to moderate

nucleotide diversity (π) were found in all populations of S. solea and S.

senegalensis analysed, except for Portugal-North population of S.

senegalensis. The values obtained for both diversity indices were similar to

those obtained for another flatfish species, plaice, in the Atlantic area

(Hoarau et al., 2004) and are characteristic of species with wide geographic

Chapter 2

- 43 -

distribution areas, which can be related to a higher number of available

habitats and the possible diversification associated with their colonization.

The detected pattern of genetic diversity showed by both species can be

attributed to a recent population expansion after a low effective population

size caused by bottlenecks or founder events (Grant & Bowen, 1998).

Although the results of all methods used in the present study to

investigate the demographic history of populations of S. solea and S.

senegalensis, were not always concordant, which can be due to the low

number of individuals examined (approximately 10 individuals per

population), a general pattern of sudden expansion in population size,

consistent with the star-shaped haplotype networks, was obtained for both

species (Figure 2 and 5, respectively).

A general pattern of low genetic divergence among populations of marine

fish species has been pointed out (Smith & Fujio, 1982) but, for some

marine species with high dispersal capabilities, several studies have

detected the existence of population differentiation (e.g. Diplodus sargus

(Linnaeus, 1758) (Planes & Lenfant, 2002) and Dicentrarchus labrax

(Linnaeus 1758) (Castilho et al., 1998)). In the present study, results

obtained from Φ-statistics, AMOVA, haplotype networks and BAPS, all

indicated significant genetic structure in S. solea and S. senegalensis

populations, although at different scales for each species.

S. solea spawns large number of pelagic eggs (about 1 000 000), resulting

in high levels of gene flow and genetic uniformity (Katoulas et al., 1995a).

In the present study, significant genetic differentiation was detected at an

interregional scale, mainly between two major groups of populations, the

Atlantic and the Mediterranean, whereas little or no differentiation could be

detected beneath that scale. This Atlantic-Mediterranean differentiation was

demonstrated not only by AMOVA results and significant ΦST values (Tables

4 and 5 respectively), but also by the haplotype network (Figure 2) that

showed two main groups of haplotypes: one comprising Atlantic

population’s and another comprising Mediterranean individuals, with no

shared haplotypes between them. BAPS diagram (Figure 3) also


- 44 -

corroborated these results. The geographical distance between these two

major areas seems to be the main cause underlying the genetic

differentiation found, as revealed by the significant results of the Mantel

test performed to these two groups, evidencing a clear relationship between

geographical distances and genetic differentiation (see Figure Ia in Annex,

page ii). These results are, therefore, in agreement with the existence of an

isolation by distance model (IBD), as suggested in Kotoulas et al. (1995a).

Separation between Atlantic and Mediterranean S. solea populations can

be explained by the colonization of the Mediterranean, from the Atlantic,

during the early Pliocene and their settlement there since then, which is

consistent with conclusions of Mediterranean biogeographers (Kotoulas et

al., 1995a). Thus, an interruption of gene flow between these populations,

probably due to the major oceanographic discontinuity between these

areas– the Gibraltar Strait-Alboran Sea region – might be the reason for the

exhibited pattern, that has already been reported for other fish species, like

sea bass, D. labrax (Bahri-Sfar et al., 2000), mackerel, Scomber scombrus

(Linnaeus 1758) (Zardoya et al., 2004) and black anglerfish, Lophius

budegassa (Spinola, 1807) (Charrier et al., 2006).

Results of the present study also support the eastward-westward

differentiation among Mediterranean populations of common sole,

suggested by previous studies using allozymes (Kotoulas et al., 1995a),

control region of mtDNA (Guarniero et al., 2002) nuclear-DNA intronic loci

markers (Rolland et al., 2007) and amplified fragment length

polymorphisms (AFLPs) (Garoia et al., 2007). This Mediterranean

differentiation is supported by significant ΦST values between the

populations of Gulf of Lyon and Italy (western) and the populations from

Aegean Sea and Turkey (eastern) and by the haplotype network, where no

haplotypes were shared between this two Mediterranean areas, being also

possible to detect two major haplotypes – one corresponding to eastern

Mediterranean populations and the other western Mediterranean

populations.

Chapter 2

- 45 -

Differentiation among such populations could be due to the complex

history of the Mediterranean that was strongly impacted during last glacial

episodes. During these periods the lower sea level modified coast lines,

creating distinct refuges in the Mediterranean and allowing the splitting of

the eastern and western basins; since then, they present different

hydrographic regimes, the western one being much more uniform than the

eastern one because of their respective geographies (Bahri-Sfar et al.,

2000). The possible partial recolonization by populations from the Atlantic

can, therefore, also be an explanation for the detected differentiation within

the Mediterranean (Rolland et al., 2007). These differences have also been

attributed to larval temperature tolerances, for S. solea (Kotoulas et al.,

1995a) and P. flesus (Borsa et al., 1997) and to local adaptations to

different salinities for S. maximus (Nielsen et al., 2004). The present study

excludes the geographical distances as a structuring force responsible for

the genetic differentiation within the Mediterranean, since the Mantel test

performed, considering only Mediterranean populations revealed the

absence of a significant correlation between genetic and geographical

distances (see Figure Ic, in Annex, page ii). This “Mediterranean division”

has also been reported in other flatfish (S. maximus, Suzuki et al., 2004)

and roundfish (D. labrax, Bahri-Sfar et al., 2000).

According to Kotoulas et al. (1995a), S. solea populations from the

Atlantic region are expected to constitute panmictic or quasi-panmictic units

(structural units that occur in neighbouring localities within a radius of 100

km), presenting high levels of gene flow that, presumably, occur each

generation through the gathering of individuals from different areas of

spawning, and the passive diffusion of eggs and larvae back to coastal and

estuarine nursery areas. Results of the present study are also in agreement

with this model, as there was no indication of within-population genetic

structure at the regional scale. Low levels of differentiation from the Baltic

Sea to South Portugal exhibited by S. solea populations, supported by low

ΦST values and high number of shared haplotypes by Atlantic populations,

with no particular geographical organization, were also obtained for other

flatfishes, such as flounders P. flesus, and Platichthys stellatus (Pallas,

1787) (Borsa et al., 1997), plaice, Pleuronectes platessa (Linnaeus, 1758)


- 46 -

(Hoarau et al., 2002; 2004) and turbot, S. maximus (Nielsen et al., 2004),

and also for roundfish bonito, Sarda sarda (Bloch, 1793) (Viñas et al.,

2004). In general, marine species seem to be more genetically variable

than anadromous and freshwater species (Dewoody & Avise, 2000) and at

the same time, less differentiated into populations (Ward, 2002). In the

light of these considerations, the absence of genetic differentiation among

S. solea samples throughout the NE Atlantic is not unexpected, as well as

the absence of correlation between geographical distances and genetic

differentiation of samples (see Figure Ib, in Annex, page ii).

Considering the NE Atlantic area, S. solea and S. senegalensis occur in

simpatry from Bay of Biscay to North Africa. Since both species present

similar life history pattern (a division into a juvenile phase, predominantly

estuarine and an adult phase, marine, that may have an impact on the

structuring of offshore adult populations, particularly on their genetic

differentiation, since a strong association between a particular spawning

and nursery area can be expected), similar patterns of genetic

differentiation throughout their simpatry area were, somehow, expected.

However the level of genetic differentiation obtained for each species was

different, with S. solea samples presenting genetic homogeneity, conversely

to significant genetic differentiation among S. senegalensis samples,

contradicting the assumption that marine organisms capable of extensive

dispersal (those that undergo lengthy planktonic larval development) will

necessarily demonstrate widespread genetic homogeneity (Exadactylos et

al., 1998).

S. senegalensis exhibited a pattern of significant genetic heterogeneity

among populations separated by geographic distances presumably short

enough to lie within the fishes´ potential migration range, and where the

balance between gene flow and the forces responsible for genetic

differentiation may, in a long term, result in clines, with genetic

differentiation increasing with geographic distances (Borsa et al., 1997).

This pattern has also been reported for other marine fishes, like swordfish,

Xiphias gladius (Linnaeus, 1758) (Kotoulas et al., 1995b).

Chapter 2

- 47 -

For S. senegalensis, geographical distance per se seems to be very

important for the structuring of populations, as it was strongly associated

with genetic divergence amongst the set of samples analyzed (see Figure

III, in Annex, page iii). This association appeared to be highly related with

latitudinal differences between samples, since more geographically distant

S. senegalensis populations, such as Bay of Biscay and Mauritania, showed

the highest pairwise ΦST value (0.502), absence of shared haplotypes in the

network and unique clusters in BAPS analysis. Results obtained for the

geographically closest S. senegalensis populations, such as those from the

Portuguese coast - North, Centre and South of Portugal - presented no

genetic differentiation at all (ΦST ranging from 0.000 to 0.095), and shared

the most common haplotype present in the minimum spanning network of

this species. These results are in agreement with those obtained by Cabral

et al. (2003a) using allozymes, which detected the absence of genetic

differentiation throughout the Portuguese coast. Considering the strong

association obtained between geographic distances and genetic distances, a

significant IBD model, confirmed by the Mantel test would be expected.

However, the resulting correlation coefficient was high (Z=0.75), but not

significant (P=0.06), probably due to the reduced number of populations

analysed and/or to a low sample size.

The importance of geographical distances per se, acting as a structuring

force in Northeastern Atlantic populations, has been found in other marine

fishes such as cod, Gadus morhua (Linnaeus, 1758) (Hutchinson et al.,

2001), plaice, P. platessa (Hoarau et al., 2002) and Atlantic herring, Clupea

harengus (Linnaeus, 1758) (Mariani et al., 2005). A weak pattern of

isolation by distance along a latitudinal axis was also found in European

flounder, P. flesus, from the Western Baltic Sea to Portugal (Borsa et al.,

1997).

The results obtained in the present study, by revealing homogeneity

among S. solea samples and differentiation among S. senegalensis samples

throughout the Northeastern Atlantic, suggest a small role for estuarine

systems as structuring forces of genetic differentiation, according to that

pointed out by Cabral et al. (2003a). In fact, and although both species


- 48 -

have a similar pattern of use of estuarine systems, their genetic

differentiation among sympatric populations is different. The low genetic

differentiation exhibited by Atlantic S. solea populations and Portuguese

coast S. senegalensis populations, can be due to a high genetic flow

between populations at different stages of their life cycles, namely adult

migration between spawning grounds and juvenile dispersion after the

estuarine phase. Other authors suggest that the larval period is the most

important in this context, with genetic flow increasing with the duration of

the pelagic larval period. This latter fact should lead to lower values of

genetic differentiation in S. senegalensis relatively to S. solea, when

analysing samples from the same geographical area, since this species

presents a widest spawning period. Whereas the main spawning period of S.

senegalensis occurs from February to May, with a secondary spawning in

Autumn (Anguis & Cañavate, 2004), being the pelagic larval duration (PDL)

of this species of about 38 days (Dinis et al., 1999), S. solea presents a

similar value of PDL (35 days) (Fuchs, 1982), but a reduced spawning

period (approximately 3 months) (Koutsikopoulos et al., 1991).

Kotoulas et al. (1995a) demonstrated the important role of temperature

as a factor contributing to restrict larval dispersion and promote geographic

isolation. The temperature interval for the development of common solea

eggs ranges from 7ºC to approximately 20ºC (Koutoulas et al., 1995a)

while for Senegal sole the temperature should be above 16ºC (Imsland et

al., 2003). Temperatures outside these limits are lethal, and can

circumscribe the distribution range of both species. Within these limits, the

planktonic stage duration is known to decrease with the variation of

temperature, since the length of the larval phase in flatfish is highly

dependent on this factor (Amara, 2003; Hutchinson & Hawkins, 2004). For

this reason it is possible that the PDL in the Bay of Biscay is smaller,

resulting in a decrease of genetic flow, evidenced by the larger and

significant ФST values obtained between this population and the Portuguese

coast samples of S. senegalensis, not observed in S. solea.

The comparison of these two sole species suggests that water

temperature during the larval period, which is critical for the survival of

Chapter 2

- 49 -

offspring during their pelagic stage, is a major factor affecting gene flow

and consequently the population genetic structure of a species. Similar

results were observed in other flatfishes, such as flounder, P. flesus (Borsa

et al., 1997).

In conclusion, results showed a significant population structure in S. solea,

between Atlantic and Mediterranean populations, and also throughout the

Mediterranean, and an increasing genetic differentiation with increasing

geographic distances for S. senegalensis. The differences found between

these species reflect some aspects of their life history patterns, namely

duration of pelagic larval stage, larval temperature tolerances and fecundity

(Avise, 1994; Kotoulas et al. 1995a; Hilbish, 1996).

However, the detection of global genetic differentiation in high gene flow

species is especially troublesome and subjected to several potential errors

(Waples, 1998). It is also important to note that a lack of genetically

detectable differentiation between populations may arise from: (i) sufficient

gene flow to maintain panmixia; (ii) occasional “sweepstake” events such as

sporadic recruitment from distant, non-neighbouring areas which could

produce the appearance of panmixia; (iii) stabilizing selection arising from

exposure to similar environments; (iv) recent divergence of the compared

populations or (v) failure to detect genetic variants due either to the

technique employed or to insufficient sample sizes (Carvalho & Hauser,

1994). Considering the high dispersal capacity of soles, further studies

using higher sampling sizes, and the analyses of both mitochondrial and

nuclear molecular markers, should be conducted for S. solea and S.

senegalensis in order to define more accurately the genetic stock structure

and gene flow within each species.

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Chapter 3

Chapter 3

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Concluding remarks and challenges

This work has brought new insights to the knowledge on Solea solea

(Linnaeus, 1758) and Solea senegalensis, Kaup, 1858, population structure.

The main conclusions of the present work were:

• S. solea and S. senegalensis presented diversity indices

characteristic of species with broad distribution areas;

• There is significant genetic differentiation at an inter-regional scale

for S. solea populations, mainly between two major groups, the

Atlantic and the Mediterranean, that can be explained by

biogeographic and oceanographic features;

• S. solea populations from the Atlantic region constitute panmictic or

quasi-panmictic units, but it can be noticed a eastward-westward

differentiation among Mediterranean populations, probably as a

consequence of glacial episodes in the Mediterranean or of a partial

recolonization by populations from the Atlantic;

• Geographical distance per se seems to be very important for the

structuring of S. senegalensis populations, as it was significantly

associated with genetic divergence amongst the set of samples

analyzed;

• Since both species have a similar pattern of use of estuarine

systems, but the genetic differentiation exhibited between samples

of both species is different, results reduced the importance of

estuarine systems as structuring forces of genetic differentiation;

• Water temperature during the larval period, is probably one of the

major factors restricting planktonic stage duration and survival of

Concluding remarks and challenge

- 60 -

larvae, restricting gene flow and consequently contributing to the

population genetic structure of S. senegalensis;

• The comparison of two closely related species with very similar life-

history characteristics brought to light differences in their genetic

population structure and demographic histories;

• This study proved that mitochondrial DNA (mtDNA) is a molecular

marker with high value to detect genetic stock structure and gene

flow in species with large population size and high dispersal

potential such as S. solea and S. senegalensis.

The combined analysis of the results from this study and those from

previous ones, mainly conducted in S. solea populations, allowed the

conclusion that the use of molecular markers with high polymorphism, such

as microsatellites, might not be of such extreme importance since the

results obtained with mtDNA and microsatellites were similar. For this

reason, microsatellites analyses for S. senegalensis, within the same

sampled area, should give similar results to the ones obtained in the

present study using mtDNA. However, it has already been proved that the

combination of different molecular markers is more informative and allows a

more precise analysis and complete conclusions, and, as so, it would be

interesting to develop a study combining the use of several molecular

markers in a broader scale, including samples from the entire distribution

range of both species, and a higher sample sizes (which was the major

limitation of the present work, mainly for the study of S. senegalensis).

Samples from North and South Spain should also be included in the analysis

since they could be very informative about the Atlantic-Mediterranean

genetic differentiation for S. solea, in this transition area. For S.

senegalensis analysis, samples from the Mediterranean should also be

included to verify if the Atlantic-Mediterranean genetic differentiation

obtained for S. solea, and detected in other fish species, is also present in

S. senegalensis. Samples from North Africa are also worth to include as

they would allow the comparison between several Solea species. Associated

biological and environmental data should be collected, especially in areas

less studied, to help interpreting the genetic variation.

Chapter 3

- 61 -

All the conclusions obtained in this study emphasize the importance of

investigating marine fishes with wide geographical and ecological

distribution, such as S. solea and S. senegalensis, to increase our

understanding of evolution in the marine environment. Of particular interest

is the applicability of such studies to the sustainable management and

conservation of these species, especially of those intensively exploited by

fisheries.

Annex

- i -

Supplementary Information

Table I- Results of the AMOVA performed for Solea solea, considering three groups (Atlantic,

Western Mediterranean and Eastern Mediterranean).


Among groups 45.06 θCT=0,45060 <0.001

Among populations within groups 5.03 θSC=0,09160 <0.001

Within populations 49.91 θST=0,50093 <0.01

Table II- Results of the AMOVA performed for Solea solea, considering three groups

(Atlantic North, Atlantic South and Mediterranean).


Among groups 38.97 θCT=0,38968 <0.001

Among populations within groups 4.37 θSC=0,07152 <0.001

Within populations 56.67 θST=0,43333 <0.001

Table III- Results of the AMOVA performed for Solea senegalensis, considering three groups (Bay of Biscay (BY) Portugal-North (PN); Portugal-Centre and South (PC and PS); Mauritania

(MAUR))


Among groups 8.87 θCT=0,08866 > 0,05

Among populations within groups 30.86 θSC=0,33862 < 0,001

Within populations 60.27 θST=0,39725 < 0,001

Table IV- Results of the AMOVA performed for Solea senegalensis, considering two groups (Bay of Biscay (BY) Portugal-North, Centre and South (PN, PC and PS); Mauritania (MAUR))


Among groups 14.54 θCT=0,14542 > 0,05

Among populations within groups 29.4 θSC=0,34408 < 0,001

Within populations 56.05 θST=0,43946 < 0,001

Supplementary Information

- ii -

Solea solea TOTAL

0

0.2

0.4

0.6

0.8

0 5000 10000 15000

Kilometers

FST

Fig.Ia

Solea solea ATLANTIC

0

0.2

0.4

0.6

0.8

0 5000 10000 15000

Kilometers

FST

Fig.I.b

Solea solea MEDITERRANEAN

0

0.2

0.4

0.6

0.8

0 5000 10000 15000

Kilometers

Fst

Fig. Ic

Fig. I- Relation between genetic differentiation (Pairwise ΦSTs) and geographical distances

(Km) for Solea solea populations. Samples are included following a geographical transect

going from the Baltic Sea (MBA) to Aegean Sea (ME) (Fig. Ia), from Baltic Sea (MBA) to

Portugal-South (PS) (Fig. Ib) and from Gulf of Lyon (GL) to Aegean Sea (ME) (Fig. Ic).

ΦSTs

ΦSTs

ΦSTs

Annex

- iii -

Solea solea ATLANTIC

0

100

200

300

400

500

600

0 1 2 3 4 5 6 7 8 9 10 11 12 13

Nº of paiwise differences

Pa

iwis

e m

ism

atc

h

Observed

Simulated

Fig. II- Pairwise mismatch distributions (Rogers & Harpending, 1992) and simulated model

of sudden expansion (Rogers, 1994) for Atlantic populations of Solea solea.

Solea senegalensis

0

0.2

0.4

0.6

0.8

0 5000 10000 15000

Kilometers

FST

Fig. III- Relation between genetic differentiation (Pairwise ΦSTs) and geographical distances

(Km) for Solea senegalensis populations. Samples are included following a geographical

transect going from the Bay of Biscay (BY) to Mauritania (MAUR)

ΦSTs


solea solea and solea senegalensis and its relationships with life...

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