Isolation and Characterization of Nuclear and ...elib.suub.uni-bremen.de/diss/docs/00011432.pdf ·...

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Isolation and Characterization of Nuclear and

Mitochondrial Genetic Markers for Population

Studies of Ucides cordatus cordatus (Decapoda:

Brachyura)

Dissertation

zur Erlangung des Grades eines Doktors der Naturwissenschaften (Dr. rer. nat.)

vorgelegt von

Marco Ewald

angefertigt am Zentrum für Umweltforschung und Technologie (UFT)

Abteilung Molekulare Genetik und Biotechnologie innerhalb des Fachbereichs 2 der Universität Bremen

Bremen 2006

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Drawing on cover: The uçá, Ucides cordatus cordatus (Linnaeus 1763) as depicted in Zacharias Wagner's "Thier Buch," c. 1640. Reproduced from Dutch Brazil (Rio de Janeiro: Editora Index, 1997), vol. 2, plate 25.

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Principal supervisor: Prof. Dr. Dietmar Blohm, UFT at the University of Bremen, Germany

Co-supervisor: Prof. Dr. Horacio Schneider, at the Laboratório de Genética e Biologia Molecular- Nucleo de Estudos Costeiros, UFPA, Federal University of Para Bragança, Para, Brazil

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Contents

ACKNOWLEDGMENTS………………………………………………………. vi

SUMMARY........................................…………………................................ viii

ZUSAMMENFASSUNG............................................................................. xi

LIST OF TABLES AND FIGURES…………………………………………… xv

1 Introduction……………………………………………………………

…

1

1.1 The Mangrove Ecosystem…………………………………………….. 1

1.2 MADAM Project (Mangrove Dynamics and Management)………... 2

1.3 The semi terrestric crab Ucides

cordatus…………………………….

4

1.3.1 Ecological Role…………………………………………………………. 4

1.32 Systematic of Ucides cordatus……………………………………….. X

Xxx Economical Role...............................................................………… 6

1.4 Objectives and

Studies…………………………………………………

9

1.5 DNA Polymorphism……………………………………………………. 10

1.5.1 Microsatellites………………………………………………………….. 13

1.5.2 Stutterbands……………………………………………………………. 15

1.5.3 Mitochondrial DNA…………………………………………………….. 16

1.5.4 Cytochrome Oxidase Subunit I (COI) Coding DNA………………… 17

1.5.5 Mitochondrial Pseudogenes………………………………………...... 19

2 Material and Methods………………………………………………….. 22

2.1 Probe Sampling………………………………………………………… 24

2.2 Isolation and Characterisation of Microsatellites…………………… 24

2.2.1 DNA Extraction………………………………………………………… 24

2.2.2 Microsatellite Screening and Amplification…………………………. 27

2.2.3 DNA Sequencing and Primer Design……………………………….. 27

2.2.4 Analyzing of the Allele Frequencies…………………………………. 27

2.2.5 Genotyping and population analyses of Ucides cordatus…………. 28

2.3 COI Approach.............................................................…………….. 28

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2.3.1 DNA Extraction and Sequencing…………………………………….. 30

2.3.2 Phylogenetic and Population Variability Analyses Using COI

Data……………………………………………………………………… 32

3 Results....................................................................................…….

.

32

3.1 Isolation of Microsatellite Sequences in Ucides cordatus…………. 32

3.2 Characterisation of Selected Microsatellite Loci…………………………… 36

3.3 Diversity of Selected Microsatellite Loci……………………………... 37

3.4 Characterisation of the Partial COI Coding Sequence…………….. 42

3.5 Diversity of the COI Coding DNA…………………………………….. 45

3.6 Demographic Investigation Using the COI Marker…………………. 49

4 Discussion………………………………………………………………. 49

4.1 Isolation and Characterisation of Microsatellite Loci……………….. 53

4.2 Experimental Uncertainties in Using Selected Microsatellite

Loci……………………………………………………………………….

55

4.3 Microsatellite Diversity in Ucides Populations………………………. 56

4.4 Mitochondrial COI Gene in Population Genetics of U.

cordatus………………………………………………………………….

56

4.4.1 Diversity of the COI

Gene……………………………………………...

57

4.4.2 Population Dynamics of Ucides cordatus…………………………… 60

4.4.3 Putative Pseudogenes in Ucides cordatus…………………………. 61

4.5 Comparison of Population Divergence from Mitochondrial COI

DNA and Nuclear Microsatellite Loci………………………………… 62

4.6 Marine dispersal of Ucides cordatus...............................………… 65

5 References…………………………………………………………….. 65

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Acknowledgements

I would like to thank Prof. Dr. Dietmar Blohm for having given me the

opportunity to conduct this thesis, for his support and very helpful advices.

Many thanks go to Prof. Dr. Horatio Schneider at the Laboratório de Genética

e Biologia Molecular- Nucleo de Estudos Costeiros, UFPA, Federal University

of Para Bragança, Brazil for his unresting help, support and fruitful

discussions during my stay in Brazil. Thanks a lot for accepting to be my

second superviser as well as offering the possibility for finishing my PhD in his

group in Brazil.

Many thanks to Prof. Dr. Ulli Saint-Paul for iniciating the scientific question

and for imbedding the study into the MADAM project.

My special thanks go to Prof. Dr. Iracilda Sampaio for supporting my work

during the last months in Brazil, for helping on the practical as well as

theoretical part of this study and supporting to establish myself in an unknown

country.

Many thank to the members of the group of Biotechnology and Molecular

Genetics at the University of Bremen and the members of the Laboratório de

Genética e Biologia Molecular- Nucleo de Estudos Costeiros in Bragança for

a very open and helpful atmosphere and several helpful comments, too.

Substitutional for all nice collegues I would like to thank Dr. Sascha Todt and

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Tawfiq Froukh for discussions and friendship in Bremen, either Dr. Marcello

Vallinoto for supporting my statistical analyses and several proposals to

improve the population genetic work in Brazil.

Further many thanks to my mother Elise and several friends substitutional

Moirah, Stumpi and Christiane who did accompany my path of live over years.

Without you realising my life´s dream would be much more difficult.

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Summary

The mangrove ecosystem has fundamental influences on storm protection of the coast,

erosion control, and wastewater cleanup. In Brazil, one of the key species of this

ecosystem is Ucides cordatus. In the mangrove forests it accounts for up to 84% of

the epibenthic biomass and is of highest importance by fuelling the detritus based

food web by accelerating the disruption of organic matter falling from the trees.

Further, there is a high significance of crustacean fisheries in general and of U.

cordatus especially as a major financial income for rural populations in coastal

regions. In parts of the mangrove forests the same amount of this resource produced

each year is harvested. At the same time, U. cordatus is a slow growing species and

requires 6 to 11 years to reach market size of about 7 cm and needs up to 3 years to be

able to reproduce. Due to this economically and ecologically importance of U.

cordatus this species should be included into a coastal management plan to protect the

mangrove forests and to manage the edible resources like U. cordatus. Therefore

information about distribution and population dynamics is necessary to adequate

elements for sustainable exploitation and managing. Especially because the larvae

dispersal and the remigration mechanism to the mangrove forests is not clear yet and

to what extent the population of U. cordatus in the mangroves could originate from

other regions. The objective of this study is to develop a DNA based marker system to

analyze the following questions. Are there polymorphisms between morphologically

equal individuals in selected potentially variable DNA markers and are they available

to measure gene flow, genetic population structure and exchanges of individuals

between separated geographically locations? Further it should be examined if there

are any indications that the species U. cordatus is still over fished.

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As nuclear genetic marker in this study 110 microsatellite loci were successfully

isolated from different enriched partial libraries of U. cordatus and with 5 of them

population analyzes were done using 135 individuals from Bragança and Paraná. The

microsatellite markers developed here are the first for Ucides and show high

polymorphism with 16 to 47 different alleles, respectively and values of observed

heterozygosity from 0.23 to 0.88 with values of expected heterozygosity from 0.87 to

0.98. Significant deviations from Hardy Weinberg equilibrium (HWE) were detected

for all tests at each locus in the population of Bragança and Paraná with a deficit of

heterozygosity of -0.08 to -0.72 and zero allele estimation with an amount of 0.043 to

0.417. F-statistics detects a low but highly significant variability between the

populations of Bragança and Paraná with Fst values of 0.011 to 0.048 in 4 of 5 loci

and therefore restricted gene flow supported by P values lowers than 0.01. Because of

the possible error rate in genotyping through stutter bands and suggested high

amounts of zero alleles the weak population structure found in U. cordatus was

confirmed using an additional different marker. A part of the mitochondrial gene

coding for the Cytochrome oxidase subunit I (COI), was amplified and 600 bp were

sequenced using 223 individuals pooled from the regions “Upper Amazon”, “Lower

Amazon” and “South Brazil”. A high amount of polymorphism was found with 132

different haplotypes resulting in a diversity of 0.97 within the haplotypes and 0.0063

to 0.0065 within the nucleotides from one individual to the other. In spite of the low

variability with significant �st values of 2.1% between Upper Amazon and Lower

Amazon, 2.2% between Lower Amazon and South Brazil and 3.9% between Upper

Amazon and South Brazil it is shown that between the analyzed populations a

restricted gene flow exists and the null hypothesis of panmixing was rejected with P

values lower than 0.05. The variation between Upper and Lower Amazon was similar

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to the one between Lower Amazon and South Brazil, where the genetic distance does

not correlate with the geographical distance. One reason for this could be the presence

of a barrier like the Amazon and its estuary which is suggested to be responsible for

lower larvae distribution. Studies of the tests of neutrality deviation based on Fs and D

values were negative and significant in the whole population and in populations from

“Upper Amazon”, “Lower Amazon” and “South Brazil”. Therefore in further tests it

was differentiated between events of population expansion, background selection and

hitchhiking. Due to the excess of discrete haplotypes in the sample the hitchhiking

event was excluded and the results of following tests against population expansion

lead to suggest that the hypothesis of this event is the right one. The curves of the

mismatch distribution of expected and observed paiwise differences show an

exponential increase and this result was supported by the test of raggedness of

Harpending, the sum squares of the deviations (SSD) and the comparison between the

values of �0 which reflects the situation in the past when the population started to

grow and �1 which reflects the recent population growth. All these tests show a

population expansion for the overall population and for the local populations. Using

the molecular clock the start of the expansion took place between 479762 and 292029

years ago in the past and is recently still growing. All COI sequences of the 223

individuals fulfilled the requirement of protein coding mitochondrial DNA and

therefore it was suggested that in this study no pseudogenes were amplified. However,

there is no definiete proof for this fact. For a suitable management of the resource U.

cordatus it can be assumed that in none of the analyzed locations any hind of over

fishing was found and to protect the population of U. cordatus big areas should be

taken into account because small protected areas would have just a local effect due to

high dispersal.

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Zusammenfassung

Das Ökosystem Mangrove hat weitgehenden Einfluss auf den Schutz der Küsten, vor

Erosion und Sturmschäden, es trägt zudem zur Abwasser Reinigung bei. Eine der

Schlüssel Spezies dieses Ökosystems ist Ucides cordatus. In den Wäldern der

Mangroven stellt sie bis zu 84% der epibenthischen Biomasse dar. Sie ist von größter

Wichtigkeit, da sie die auf Detritus basierende Nahrungskette speist indem sie den

Zerfall von organischem Material, das von den Bäumen stammt, beschleunigt. Des

Weiteren hat die Fischerei, von Crustacean im Allgemeinen und von U. cordatus im

Besonderen, grö�te Bedeutung für die ärmere Bevölkerung der Küsten Regionen, da

durch sie häufig der Hauptanteil des Einkommens bestritten wird. In Teilen der

Mangroven Wälder ist die Menge dieser Ressource die dort jährlich produziert wird,

gleich der, die jedes Jahr gefangen wird. Demgegenüber ist U. cordatus eine langsam

wachsende Spezies und benötigt 6-7 Jahre um eine Markt Grö�e von etwa 7cm zu

erreichen und 3 Jahre um geschlechtsreif zu werden. Um die Mangroven Wälder zu

schützen und die Nahrungsressource U. cordatus zu bewirtschaften, sollte sie in

einem Bewirtschaftungsplan der Küsten berücksichtigt werden, da sie in ökologischer

und ökomomischer Hinsicht von grö�ter Bedeutung ist. Daher sind Informationen

über Verbreitung und Populationsdynamik notwendige Bestandteile für eine

nachhaltige Nutzung und Bewirtschaftung. Insbesondere, da die Verbreitung der

Larven und die Remigrations-Mechanismen noch ungeklärt sind, könnte die

Population von U. cordatus ihren eigentlichen Ursprung jeweils in anderen Regionen

haben. Das Ziel dieser Studie ist die Entwicklung eines auf DNA basierenden Marker

Systems, um folgende Fragen zu beantworten. Gibt es in ausgesuchten potentiell

variablen DNA Markern eine Vielgestaltigkeit zwischen morphologisch gleichen

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Individuen und sind diese nutzbar um Gen Fluss, genetische Populationsstruktur und

Austausch an Individuen zwischen geographisch getrennten Orten zu analysieren?

Des Weiteren soll untersucht werden, ob bereits Anzeichen für ein Überfischen der

Spezies U. cordatus bestehen.

Aus unterschiedlich angereicherten partiellen Genbanken von U. cordatus wurden in

dieser Studie erfolgreich 110 Mikrosatelliten Loci als genetische Marker der Kern

DNA isoliert. Mit 5 von ihnen wurden innerhalb von 135 Individuen aus Bragança

und Paraná Populations-Analysen durchgeführt. Die Mikrosatelliten, die hier

entwickelt worden, sind die ersten für Ucides. Sie weisen mit 16-47 jeweils

verschiedenen Allelen, hohen Werten an ermittelter Heterozygotie von 0,23 bis 0,88

und errechneter Heterozygotie von 0,87 bis 0,98, eine hohe Vielgestaltigkeit auf. Im

Vergleich der Populationen von Bragança und Paraná weisen alle Loci eine

signifikante Abweichung von dem Hardy Weinberg Gleichgewicht (HWE) auf, mit

Defizit Werten an Heterozygotie von -0,08 bis -0,72 und einer Abschätzung der

Menge an Null Allelen von 0,043 bis 0,417. Mit Fst Werten von 0,011 bis 0,048

wurde mittels F-Statistik ein geringer aber signifikanter Unterschied zwischen den

Populationen von Bragança und Paraná in 4 von 5 Loci ermittelt. Begrenzter Gen

Fluss wurde durch P Werte unterhalb von 0,01 abgesichert. Wegen der möglichen

Fehlerrate in der Genotypisierung, bedingt durch Stotter Banden und den Hinweisen

auf einen hohen Anteil an Null Allelen, wurde das Ergebnis der geringen

Populationsstruktur in U. cordatus durch die Verwendung eines weiteren

andersartigen DNA Markers bestätigt. Ein Teil des mitochondrialen Genes, das für die

Cytochrome Oxidase Untereinheit I (COI) codiert ist, wurde von 223 Individuen

vereinigt aus „Oberer Amazonas“, „Unterer Amazonas“ und „Süd Brasilien“

amplifiziert und über eine Länge von 600 Basen sequenziert. Mit 132

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unterschiedlichen Haplotypen, die in einer Verschiedenheit über 0,97 bezüglich der

Haplotypen und über 0,0063-0,0065 bezüglich der Nukleotide resultiert, wurde ein

hohes Ma� an Vielgestaltigkeit innerhalb der Individuen ermittelt. Trotz der geringen

Verschiedenheit mit �st Werten von 2,1% zwischen „Oberer Amazonas“ und

„Unterer Amazonas“, 2,2% zwischen „Unterer Amazonas“ und „Süd Brasilien“ und

3,9% zwischen „Oberer Amazonas“ und „Süd Brasilien“ wurde aufgezeigt, dass

zwischen den analysierten Populationen begrenzter Gen Fluss herrscht und dass die

Null Hypothese einer einheitlichen Durchmischung mit P Werten niedriger als 0,05

widerlegt werden kann. Die Verschiedenheit zwischen „Oberer Amazonas“ und

„Unterer Amazonas“ war auf dem gleichen Level wie zwischen „Unterer Amazonas“

und „Süd Brasilien“, wobei die genetische Distanz nicht mit der geographischen

übereinstimmt. Ein Grund dafür könnte das Vorhanden einer Barriere, die eine

geringere Verbreitung der Larven ermöglicht, sein. Dieser Umstand ist bei dem

Amazonas und seinem Mündungsgebiet zu vermuten. Die Tests auf Abweichung der

Neutralität basierend auf Fs und D Werten waren negativ und signifikant für die

Population als Ganzes und für die Populationen vom „Oberen Amazonas“, „Unteren

Amazonas“ und „Süden Brasiliens“. Daher wurde in weiteren Tests zwischen den

Ereignissen der Populations-Expansion, der Hintergrund Selektion und des

Hitchhikings differenziert. Durch den Überschuss an separaten Haplotypen in der

Gesamtprobe, wurde das Ereignis des Hitchhikings ausgeschlossen und folgende

Tests gegen das Ereignis Populations-Expansion legen Nahe, dass diese Hypothese

die richtige ist. Die Kurven der Mismatch-Verteilung aus beobachteten und

berechneten Paarweisen Unterschieden zeigen ein exponentielles Wachstum auf.

Dieses Ergebnis wurde durch den Raggedness of Harpending Test, die Abweichung

der Summe der Quadrate (SSD) und den Vergleich von �o welches den vergangenen

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Start des Populations-Wachstums beschreibt mit �1 welches den derzeitigen

Populations-Wachstum beschreibt, bestätigt. Alle Tests zusammen zeigen eine

Populations- Expansion für die gesamte Population und für alle lokalen Populationen

auf. Mittels der molekularen Uhr wurde der Start der Populations-Expansion auf vor

479 762 und 292 029 Jahren datiert und sie hält bis heute stetig an. Alle COI

Sequenzen von den 223 Individuen erfüllen alle Anforderungen an Protein codierende

mitochondriale DNA und soweit wurde angenommen, dass in dieser Studie keine

Pseudogene amplifiziert worden sind, auch wenn dafür kein definitiver Beweis

besteht. Für eine angemessene Bewirtschaftung der Ressource U. cordatus kann

angenommen werden, dass in keiner der analysierten Region jeglicher Hinweis auf

ein Überfischen gefunden wurde und, dass für den Schutz von U. cordatus gro�e

Gebiete in Betracht gezogen werden sollten, da zu kleine geschützte Gebiete durch die

hohe Verbreitung nur einen lokalen Effekt erzielen sollten.

xv

List of Figures and Tables Pg.

Figure 1 Distribution of mangrove forests (green) according to Spalding et

al., (1997) revised by FAO, (2003), along the coast of South America. Blue

arrows: main oceanic currents.

3

Figure 2 Trends in mangrove area of Brazil extent over time estimated by

satellite figures, field work and calculated estimation (FAO, 2003).

4

Figure 3 Distribution of Ucides cordatus cordatus and Ucides cordatus

occidentalis (Türkay, 1970), on the coast of Central and South America.

6

Figure 4 A: Gatherer of the crab “caranguejo uçá” (U. cordatus) in the

mangrove habitat (Photo, Guy Nishida in Alves et al., 2005) B: His prey with

its feed (Photo, Inga Nordhaus, 2003).

7

Figure 5 Overview of selected population models. A: Two Population Model

with population sizes N 1e, N 2e, and migration rates m1, m2. B: Stepping

Stone Model as ring. C: Stepping Stone Model as lattice. D: Island Model.

13

Figure 6 Slippage Process (after Strand, 1993) the amplified DNA product is

missing a repetitive motif, (picture Viguera, 2001).

15

Figure 7 Linearized representation of the mitochondrial gene arrangement for

the swimming crab Portunus trituberculatus. Protein-coding genes are

transcribed from left-to-right except ND1, ND4L, ND4 and ND5 genes

(indicated by underbars). The two rRNA genes encoded by L-strand

(indicated by underbars). tRNA genes are designated by single-letter amino

acid codes, those encoded by the H- and L-strands are shown above and

below the gene map, respectively. L1, L2, S1 and S2 denote for the tRNA

Leu (CUN), tRNA Leu (UUR), tRNA Ser (AGN), and tRNA Ser (UCN)

genes, respectively. (Mitsugu, 2003).

17

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Figure 8 Sampling locations of U. cordatus and the two main ocean currents

along the coast of Brazil, running into opposite directions. Sample points

were pooled as following: Amapá 1 = “Upper Amazon”; Bragança 2 and

Maranhão 3 = “Lower Amazon”; São Paulo 4 and Paraná 5 = “South Brazil”.

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Figure 9 Examples of amplified fragment analyses of locus UCL55 in three

different individuals. The peak area is proportional to the concentration of the

fragment. In the stutter profile the last intense peak was counted as allele

(peak, size, peak high and area in bold). The stutter bands are exclusively

smaller in steps of 2 bp amplifying a dinucleotide microsatellite. Individual A

is counted to be heterozygous with 2 alleles of 132 and 158 bp coloured with

Fam, B to be homozygous with 2 alleles of 126 bp coloured with Hex and C

heterozygous with 2 alleles of 132 bp coloured with Hex.

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Figure 10 Amplification of the mitochondrial gene CO I with different

individuals using the “universal Primer” LCO1490 and HCO2198 published

by Folmer (1994) results in a 710 bp product.

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Figure 11 Alignment of 600 sequenced variable base pair positions and

haplotype distribution of the CO I coding gene within three populations.

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Figure 12 Neighbor joining tree found for 123 COI mtDNA haplotypes in

Ucides cordatus. Bootstraps percentages of 1000 pseudoreplicates greater

than 50% are shown at the nodes.

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Figure 13 Mismatch distribution for all pairwise combinations of 223

individuals for U. cordatus. Observed distribution (interrupted line) coincided

with the expected Poisson distribution (continuous line) under a model of

sudden population expansion.

47

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Table 1 Overview of genetic variability of the cytochrome subunit I coding

DNA in applications of population genetics in crustacean.

19

Table 2 Sequencing Primers for the mitochondrial gene COI of U. cordatus. 29

Table 3 Frequency of microsatellite sequences in the enriched partial libraries

of U. cordatus.

32

Table 4 PCR conditions and amplification sizes of 5 selected microsatellite

loci.

33

Table 5 Genetic diversity and Hardy Weinberg equilibrium of 5

microsatellite loci within individuals from Bragança and Paraná.

36

Table 6 Analyses of Molecular Variance (AMOVA) among U. cordatus of 5

microsatellite loci based on F statistics among and within the populations

from Bragança and Paraná.

37

Table 7 Pairwise �st (below diagonal), Kimura 2 population divergence

within (diagonal) and between populations (above diagonal) among U.

cordatus samples.

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Table 8 Descriptive statistics with diversity and neutrality parameters for the

studied U. cordatus populations.

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Table 9 Descriptive statistics with expansion parameters for the studied U.

cordatus populations.

46

Tab 10 Hierarchically genetic structuring of U. cordatus populations. 48

Table 11 Microsatellite isolation in different crustacean species. 52

Introduction

1

1 Introduction

1.1 The Mangrove Ecosystem

About 60-75% of tropical and subtropical coasts are fringed with mangrove forests,

with a worldwide extension of approximately 181 000 km2 (Spalding et al., 1997).

These ecosystems have fundamental influences on storm protection of the coast,

erosion control, and wastewater cleanup (Siddiqi, 1994; Woodroffe, 1992; Wolanski

et al., 1992).

It was estimated that the area of mangrove forests worldwide has been reduced by

about 35% since the 1980s (Valiela et al., 2001) and the current mangrove area has

fallen below 15 million ha, down from 19.8 million ha in 1980 (FAO, 2003).

However, in Cuba and Bangladesh mangroves are being reforested for protection

against floods and tsunamis (Siddiqi, 1994), and most of the countries with very large

areas of mangroves still have a significant number of protected areas, notably

Australia (180), Indonesia (64) and Brazil (63) (Spalding et al., 1997).

Nevertheless the Brazilian mangroves which fringe the coastline along a length of

6800km (Figure 1) have been in a process of decreasing strongly in the last centuries

up to about 1 million ha recently (Figure 2, FAO, 2003). In Figure 1 it can be

observed that in general the density of the band of mangrove forests in the north of

Brazil is higher and less interrupted than in the south, but even these coastal zones are

subjected to diverse anthropogenic pressure due to exploitation and human occupation

(Szlafstein, 2003). On the northern coast of Brazil, mangroves form a continuous belt

Introduction

2

with about 700 000 ha, which contributes about 85% of the Brazilian mangroves as a

whole (Herz, 1999; Lacerda, 1993). Mangrove areas are impacted by clay extraction,

aquaculture, agriculture, salt extraction and industrial activities (Senna et al., 2002).

Near urban centres pollution affects the ecosystem as well and has recently been

leading to the destruction of mangrove forests (Rebelo-Mockel et al., 2001). Products

like wood, tannin, honey, crabs, fish and mussels are extracted from the mangrove

ecosystem for commercial activities and coastal fisheries is affected as well since

outwelling of nutrients and organic matter lead to fertilisation of coastal waters

(Dittmar, 1999). Mangrove forests on the coastal zones of Brazil, provide several

profitable resources such as timber, medicinal products, natural dye, fish, crustaceans,

and molluscs (Alves et al., 2005).

1.2 MADAM Project (Mangrove Dynamics and Management)

This study resulted from cooperation between the working group of biotechnology

and molecular genetics at the University of Bremen, Germany, the Laboratório de

Genética e Biologia Molecular- Instituto de Estudos Costeiros, UFPA, in Bragança,

Pará, Brazil, and the Center for Tropical Marine Ecology (ZMT), Bremen, Germany.

It is imbedded into the MADAM project, an integrated approach to mangrove

dynamics and management based on economical and physical/ecological studies

emphasized on the estuary of Caeté near Bragança city (Figure 8). This project is

financially supported by the German Ministry of Education, Science Research and

Technology (BMBF) under the code 03F0154A. The goal of this project is the

scientific multipurpose use of the mangrove ecosystem without sacrificing its

integrity. The results of the studies collected in such different areas as socioeconomy,

Introduction

3

biogeochemistry, zoology and botany should be taken into account for a coastal

management plan to save and protect the Brasilian mangroves and to use their

resources sustainably (Schneider and Saint-Paul, 2000).

Figure 1 Distribution of mangrove forests (green) according to Spalding et al., (1997) revised by FAO, (2003), along the coast of South America. Blue arrows: main oceanic currents.

Introduction

4

Figure 2 Trends in mangrove area of Brazil extent over time estimated by satellite figures, field work and calculated estimation (FAO, 2003).

1.3 The semi terrestric crab Ucides cordatus

1.3.1 Ecological Role

Brachyuran crabs are a major economic resource in the northern and northeastern

coast of Brazil. The main species being commercialized are Cardisoma guanhumi,

Callinectes spp and the land crab “caranguejo-uçá”, U. cordatus (Alves and Nishida,

2002; Alves et al., 2005).

U. cordatus plays an important role in the mangrove ecosystem by fuelling the

detritus based food web and accelerating the disruption of organic material falling

Introduction

5

from the trees (Ostrensky et al., 1995; Koch, 1999). Consumption rates of U. cordatus

of litter can exceed up to production rates of exampled areas of mangrove forest

(Nordhaus, 2003). Koch (1999) has shown that U. cordatus accounts for up to 84% of

the epibenthic biomass in the mangrove forests around the city of Bragança, Pará,

Brazil. Abundance and biomass of 1.7 specimens m-2 and 142 g m-2 was registered for

this species in the same area (Diele, 2005) and it could be shown that burrowing

activities of U. cordatus improve the oxygenation of deeper sediment layers which

coincided with an enhanced microbial abundance and biomass (Nordhaus, 2003).

1.3.2 Systematics of Ucides cordatus

Ucides cordatus was first described by Linnaeus (1763) and belongs to the Metazoa;

Eumetazoa; Bilateria; Coelomata; Protostomia; Panarthropoda; Arthropoda;

Mandibulata; Pancrustacea; Crustacea; Malacostraca; Eumalacostraca; Eucarida;

Decapoda; Pleocyemata; Brachyura; Eubrachyura; Heterotremata/Thoracotremata

group; Thoracotremata; Ocypodoidea; Ocypodidae; Heloeciinae; Ucides. The genus

Ucides (Rathburn, 1897) is included into the Heloecinae, but according to

morphological differences the position within the Ocypodidae is still uncertain

(Türkay, 1970). The literature reports two subspecies, Ucides cordatus cordatus, the

Atlantic form and Ucides cordatus occidentalis, which occurs on the Pacific coast of

South America. Ucides cordatus cordatus, the subject of the present study, occurs

along the subtropical and tropical coast of America (Figure 3) (Türkay, 1970) and will

be named with the term U. cordatus for simplicity.

Introduction

6

Figure 3 Distribution of Ucides cordatus cordatus and Ucides cordatus occidentalis(Türkay, 1970), on the coast of Central and South America.

1.3.3 Economical Role

A recent revision on the status and management of Brazilian mangroves has

emphasised the significance of crustacean fisheries as a major financial income for

rural populations in coastal regions (Kjerfve and Lacerda, 1993; Alves et al., 2005).

Adult crabs like U. cordatus have few predators, notably the crab-eating racoon

(Procyon cancrivorous), monkeys (Cebus apella), and hawks (Koch, 1999). However,

humans who harvest this species for food exert a high predation pressure on U.

cordatus (Diele, 2000).

The Caeté estuary near Bragança yields an annual production of 1200 t of the resource

U. cordatus. This equals the amount that is currently harvested (Diele et al., 2005), as

Introduction

7

shown by a recent study of the market in the city of Bragança. Here, up to 1,000,000

individuals from the surrounding mangrove forest are caught and sold each month

(MADAM-Report, 2005).

The semi terrestrial crab U. cordatus lives in the mangrove forests where it burrows

up to 1.6m deep (Nascimento, 1993) and feeds on leaf litter (Figure 4).

Figure 4 A: Gatherer of the crab “caranguejo uçá” (U. cordatus) in the mangrove habitat (Photo, Guy Nishida in Alves et al., 2005) B: His prey with its feed (Photo, Inga Nordhaus, 2003).

In U. cordatus only large males are commercially harvested because of their bigger

sizes and of their bigger pincers in comparison to the females (Diele, 2000). U.

A

B

Introduction

8

cordatus holds particular socio-economic importance since it involves many local

residents, who benefit from both direct and indirect employment (Diele, 2000).

Studies in the Caeté estuary near the city of Bragança, in the north-east of Brazil and

part of the state Pará, showed that U. cordatus constitutes the main income source for

more than 50% of the rural households (Glaser, 1999).

This area is still part of a proposed coastal management plan (Glaser and da Silva,

2004). Currently the capture of females is prohibited during the reproductive season

from December to May in northern and north-eastern Brazil, while male capture is

banned only during the few days of mass mating events. However, the crabs are

harvested never the less because of a lack of law-enforcement (Diele et al., 2005).

Declines of U. cordatus populations have been reported from many coastal regions of

Brazil and were related to habitat destruction, diseases and overfishing (Maneschy,

1993; Boeger et al., 2005). For example, in the mangrove of Paraiba on the north-

eastern coast of Brazil, crab gatherers have observed that the natural stock of U.

cordatus has been decreasing alarmingly since 1998, when an unexpected crab

mortality event occurred (Alves and Nishida, 2003).

Ostrensky et al. (1995) extrapolated, that U. cordatus would require 6 to 11 years to

reach minimum market size of about 7 cm and up to 3 years to start to be able to

reproduce. Their large size suggests a high vulnerability to exploitation as it is

generally correlated with slow growth, high age at maturity and low mortality (Pauly,

1998). Otherwise recent studies have suggested that until now there is no evidence

Introduction

9

from biological data that U. cordatus is overfished in the Caeté estuary near Bragança

(Diele, 2005).

The reproduction of U. cordatus is seasonal following a strict lunar rhythm in each

year (Diele, 2000). Females spawn in the flooded mangrove forest around slack spring

high tide. Larvae are rapidly washed out of the forest into estuarine channels. From

here, ebbing water masses export the larvae to coastal water. The development of the

first megalope stages takes place offshore during a time of 3-4 weeks (Alves et al.,

2005; Diele, 2000; Diele, 2005). The mechanisms of re-invasion to the mangrove

forests remain unknown. Furthermore, the distance of larvae transport which occurs

passively in the coastal water is suggested to be long and needs to be clarified. Data of

the role of the main currents (Figure 1) along the coast of Brazil and the estuary of the

Amazon are still missing as well. Consequently, the population of U. cordatus in the

mangroves could originate from other regions (Diele, 2000).

1.4 Objectives and Studies

The ecological and economical importance of the edible resource of the species U.

cordatus is contrasted with a lack of information on distribution and population

dynamics, which is necessary to define adequate elements for sustainable exploitation

and managing. Presently, a regional costal management plan is under development,

aiming to protect and manage the exploitation of U. cordatus.

The first inspiration of the present investigation was to develop a set of microsatellites

specific to U. cordatus, useful for population genetic studies. A second approach was

Introduction

10

the use of genetic markers from distinct genomic backgrounds: both nuclear

(microsatellites markers) and mitochondrial (COI gene) to compare populations of U.

cordatus from distinct regions aiming to answer the following questions:

• Is there genetic variation within and among populations of U. cordatus?

• How are these populations related?

• What is the magnitude of the gene flow among these populations?

• Are these populations genetically structured?

• If these populations are geographically structured what is the magnitude of the

genetic structure?

• How is the genetic variation, evaluated for genetic markers of so distinct

backgrounds (nuclear and mitochondrial) correlated?

• How can the results of the present study be used for decision makers?

The answers to these questions should help to understand the larval distribution and

population structure of U. cordatus along the different mangrove areas on the

Brazilian coast.

1.5 DNA Polymorphism

DNA sequences offer the possibility to compare information directly and show high

advantages against morphological data, since morphological keys are often only

effective for a particular live stage or gender, and many individuals cannot be

identified (Weising et al., 1994; Felsenstein, 1985). Especially on the intraspecific

level morphological information is often unavailable. In those cases, the use of DNA

Introduction

11

sequences is important because the mutations themselves are subject of analyses.

DNA fingerprinting was originally developed for forensic analyses (Jeffreys et al.,

1985), and based on PCR amplification it offers a high resolution of organism with a

high degree of affinity (Weising et al., 1994).

Among the different molecular techniques, microsatellite analyses and mitochondrial

DNA sequences are currently the most powerful and largely used to assess genetic

variability of organisms. Both approaches find high ranges of applications in

population genetics where one of the principal aims is to measure the amount and

patterns of genetic variation found within and among subpopulations of interbreeding

organisms to study gene flow, genetic drift, system of mating, mutation, and natural

selection (Templeton et al., 1995).

The base for population genetics and subdivisions was set up by Wright (1996). He

developed hierarchical F statistics as a tool to study gene flow, genetic drift, and

mating systems from allele and genotype frequencies and geography. If a population

is subdivided, it means, in genetic terms, that individuals do not mate at random (the

population is not panmitic). This departure from panmixia translates into various

levels of apparent inbreeding when considering the total population and creates a

correlation between homologous genes in uniting gametes relative to a pair of genes

taken at random from two populations (Excoffier, 2001). Therefore, the fixation

indexes Fst as the �st can be defined as the standardized variance of allele

frequencies. It is the ratio of the observed variance of gene frequencies over

subdivisions divided by the maximum possible variance that can be reached when

Introduction

12

alleles have gone to fixation in all subdivisions. It cannot be affected by local

inbreeding (Wright, 1996; Excoffier, 2001).

Taking the fixation indexes from different locations it is possible to calculate

migration rates. This migration process underlay different attributes of dispersal;

therefore several models can be used for description (Figure 5). The most simple is

the “Two Population Model” according to Wright (1931), it takes into assumption that

populations have constant size and exist forever, migration rate is constant through

time, and the genetic markers are neutral. The distribution will be calculated as

follows: �1 is 4Ne(1) � , �2 is 4Ne

(2) � , M21 is m21/� , and M12 is m21/� , where Ne is

the effective population size, � is the mutation rate per generation, and mji is the

migration rate per generation from population j to population i. All existing models

were developed based on this estimation.

The “Stepping Stone Model” takes into consideration that all subpopulations have the

same effective population size, Ne. The migration rate m is constant and defines the

rate of exchange from one neighbour population to another along all possible paths.

Here the individuals can migrate to more than the closest island, they can move within

a predefined "neighborhood distance". Therefore an isolation by distance takes place

(Malecot, 1950; Kimura, 1953).

The “N-Island Model” uses only two parameters: the effective population size Ne and

the immigration rate per generation m. It is assumed that the subpopulation sizes are

the same and that the migration rate is the same between all the subpopulations.

Between the otherwise separated subpopulations infrequent migration takes place

(Wright, 1931).

Introduction

13

Figure 5 Overview of selected population models. A: Two Population Model with population sizes N 1e, N 2e, and migration rates m1, m2. B: Stepping Stone Model as ring. C: Stepping Stone Model as lattice. D: Island Model.

1.5.1 Microsatellites

Eukaryotic genomes contain a large number of short tandem repeats called

microsatellites (Tautz, 1989; Weber and May, 1989). These refer to tandem repeats

with a motif of less than seven base pairs (Winnepenninckx & Backeljau, 1998;

Singer & Berg, 1992). The repeat number of microsatellites has been demonstrated to

be highly variable, providing a source of genetic polymorphisms for population

analyses and paternity patterns (Stalling et al., 1991, Roder et al., 1995).

Microsatellite sequences can be obtained by searching databases such as EMBL

(Beckmann and Weber, 1992) or by screening genomic libraries with synthesised

oligonucleotides and sequencing clones that give positive hybridizations (Cornall et

al., 1991). Simple screening-methods for microsatellites using genomic libraries or

A

B C D

Introduction

14

partial libraries where fragments were randomly cloned were extended by different

enrichment steps, mostly using oligonucleotide probes with the sequences of the

repetitive motif of the microsatellites (Schlötterer, 1998). Primers designed based on

the microsatellite flanking sequences are used to detect microsatellite loci by PCR

(polymerase chain reaction) of genomic DNA. Allelic variants of a microsatellite

locus are codominant and show Mendelian inheritance (Tautz, 1993). High degrees of

polymorphism have been found in microsatellite sequences especially in dinucleotide

markers, which show in general higher polymorphism than tri- or tetranucleotides

(Timsit, 1999). They can reach a mutation rate of 10-2-10-6 per base and generation,

whereas the common rate of mutation is 10-5-10-9 (Chackraborty et al., 1997).

The isolation of microsatellite DNA markers is quite difficult, costly and time

consuming. Due to the limited amount of sequence data available in databases it is

often necessary to screen for usable microsatellite loci de novo. Difficulties have often

been encountered in isolating and developing clean and reproducible single locus

microsatellite DNA markers. Therefore, in crustaceans the knowledge of

microsatellites is quite rudimentary. A limited number of microsatellite loci have been

developed for a few crustacean species, like Procambarus clarkii (Belfiore, 2000),

Austropotamobius pallipes (Gouin, 2000), Cherax quadricarinatus (Baker, 2000),

Meganyctiphanes norvegica (Ostellari, 2000), Chionoecetes opilio (Urbani, 1998) and

Homarus (Tam, 1996). Microsatellite DNA markers developed for Penaeus monodon

were useful for closely related species like P. stylirostris, P. setiferus and P. vannamei

(Whan et al., 2000; Vonau, 1999; Xu et al., 1999; Ball, 1998; Bagshaw and Buekholt,

1997 and Tassanakajon et al., 1998). The specificity of these microsatellite markers

for a given taxon could also limit the cross species utility.

Introduction

15

1.5.2 Stutter Bands on Microsatellites

The susceptibility of microsatellites to insertions and deletions contributes to the

generation of allelic diversity during evolution of organism (Weber et al., 1990). The

evolutionary mutation process caused by mistakes of the DNA polymerase can also

complicate the analyses of PCR products. The most common mutation of deletion of a

repetitive motif due to so called slippage processes can also occur in the PCR

amplification of the microsatellite, resulting in additional PCR amplification products

sometimes difficult to separate from the “real” allele (Strand, 1993) (Fig 6).

Figure 6 Slippage Process (after Strand, 1993) the amplified DNA product is missing a repetitive motif, (picture Viguera, 2001).

The molecular mechanism of slippage processes involves different steps (Viguera et

al., 2001). The polymerase arrest of DNA synthesis within a direct repeat (DR) leads

to its dissociation from the template. The tip of the newly synthesized strand anneals

with another DR and the DNA synthesis is resumed. This leads to the development of

Introduction

16

a heteroduplex molecule composed of a parental strand and a newly synthesized

strand, which lacks one DR and the region situated between two DRs. In model

amplifications of repetitive DNA sequences the possibility to loose one repetitive

motif in each PCR cycle is 14 x higher than gaining one (Walsh, 1996). These stutter

bands can cause problems in genotyping different individuals due to heterozygous

ones being mistakened for homozygote individuals where the stutter bands overlap

and summarize if the alleles are not distanced enough.

1.5.3 Mitochondrial DNA

Mitochondrial DNA sequences are used to study gene flow on different levels of

relationships among organisms (Avise et al., 2000; Avise et al., 1987). Variation in

mtDNA is useful to identify species, genera and populations as well.

Crustacean mitochondrial DNA is circular and has a similar structure to that of other

animals, carrying two ribosomal genes (rRNA 12S and 16S), 22 tRNA and 13 protein

coding genes. The total size is about 15000-17000 base pairs and has maternal

inheritance (Wolstenholme et al., 1992). As an example, in Figure 7 the assembly of

the mitochondrial DNA of Portunus trituberculatus is shown (Mitsugu, 2003). The

animal mitochondrial DNA is haploid and considered as non-recombinant or low-

recombinant (Avise et al., 2000; Sacconeet al., 1999). The mutation rate and genetic

drift is higher than in nuclear loci (Waples et al., 1999).

Introduction

17

Figure 7 Linearized representation of the mitochondrial gene arrangement for the swimming crab Portunus trituberculatus. Protein-coding genes are transcribed from left-to-right except ND1, ND4L, ND4 and ND5 genes (indicated by underbars). The two rRNA genes encoded by L-strand (indicated by underbars). tRNA genes are designated by single-letter amino acid codes, those encoded by the H- and L-strands are shown above and below the gene map, respectively. L1, L2, S1 and S2 denote for the tRNA Leu (CUN), tRNA Leu (UUR), tRNA Ser (AGN), and tRNA Ser (UCN) genes, respectively. (Mitsugu, 2003).

1.5.4 Cytochrome Oxidase Subunit I (COI) Coding DNA

The protein coding gene for Cytochrome oxidase subunit I of the mitochondrial

genome has 1528 base pairs and is one of the longest in the mitochondrial DNA. It

has been used frequently to analyze genetic variability and phylogenetic relationships

on several taxonomic levels such as order, family, genus and species.

The COI gene was recently chosen to be used as a barcode for species identification

(Hebert 2003). The high interspecific variability and the level of intraspecific

divergence makes COI useful as genetic marker for population and phylogeographic

pattern studies as well. In the last years the amount of publications using COI in

population genetics has greatly increased, but very few applications had been done in

crustaceans until now.

An overview of published applications of COI for population genetics in crustaceans

(Table 1) shows that all of the studies were done after the year 2000 and most of them

used the “universal primer” LCO1490 and HCO2918 (Folmer et al., 1994). In all

Introduction

18

studies of different crustacean species COI shows high intraspecific variability

whereas the amount of genetic diversity between individuals fluctuates from species

to species reaching 0.97 in Chelonibia testudinaria and in some subpopulations of

Haptosquilla pulchella (Rawson et al. 2003, Barber et al. 2002 A).

As can be seen in Table 1 the majority of the studies on crustaceans have detected

high diversity. Only in a small part of the analyzed population of Carcinus maenas

Roman and Palumbi (2004) found no variation at all in a part of the analyzed samples.

However, it has to be noted that the sample size of that study with zero variability was

based on 11 individuals from one location only. All the other studies recognized high

amounts of genetic variability and as far as calculated low nucleotide diversity when

analyzing the COI gene within different populations of crustacean species. This

suggests that the variability within the COI gene may potentially be high enough for

population analyses in the crustacean U. cordatus. Especially due to the universal

primer sequences in more conservative regions at the 5´end of the gene, which can be

used for most if not all animal phyla, it seems to be an easily accessible genetic

marker useful to detect fine scale population subdivision in several marine species.

With its lack of introns, haploid mode of inheritance and limited exposure to

recombination paired with higher evolutionary mutation rates than nuclear DNA the

mitochondrial gene for COI has a high diversity potential (Folmer et al., 1994, Zhang

and Hewitt, 1997). Although COI may be matched by the variability of the

mitochondrial control region or cytochrome b for population analyses, it is more

likely to provide deeper phylogenetic insights because changing in the amino acid

composition of COI occurs slower than in the latter two (Lynch and Jarrell, 1993).

Introduction

19

Table 1 Overview of genetic variability of the cytochrome subunit I coding DNA in applications of population genetics in crustacean.

Species bp n S NH H � Reference Echinogammarus ischnus (Malacostraca, Gammaridae)

642 61 160 - 0.89 - Cristescu et al. (2004)

Macrobrachium australiense (Decapoda, Palaemonidae)

505 402 76 98 0.92 - Carini and Hughes (2004)

Daphnia magna(Branchiopoda, Anomopoda)

609 156 48 42 - - Gelas and Meester (2005)

Tigriopus californicus (Copepoda, Harpacticoida)

552 49 - 59 - - Edmands (2001)

Sida crystallina(Branchiopoda, Ctenopoda)

614 47 169 - - Cox and Hebert (2001)

Chelonibia testudinaria (Maxillopoda, Coronulidae)

588 56 116 79 0.97 0.048 Rawson et al. (2003)

Daphnia obtusa (Branchiopoda, Anomopoda)

645 86 222 39 - 0.004-0.021

Penton et al. (2004)

Balanus glândula(Maxillopoda, Balanidae)

386 433 65 - Sotka et al. (2004)

Cyamus ovalis Cyamus gracilis Cyamus erraticus (Malocostraca, Caprellidea)

728 728 728

104 33 21

129 29 38

81 28 16

- - -

0.015 0.008 0.009

Kaliszewska et al. (2005)

Paratya australiensi(Malacostrata, Pleocyemata)

632 242 47 - - - Hurwood et al. (2003)

Carcinus maenas (Malacostraca, Brachyura)

502 230 - 53 0.00-0,95 0.000-0.007

Roman and Palumbi (2004)

Haptosquilla pulchella Haptosquilla glyptocercus (Malacostraca, Stomatopoda)

625 625

382 247

- -

- -

0.96 0.89

0.006 0.009

Barber et al. (2002 B)

Haptosquilla pulchella (Malacostraca, Stomatopoda)

625 393 174 189 0.67-0.97 0.003-0.044

Barber et al. (2002 A)

Euphausia crystallorophias(Malacostraca, Euphausiidae)

665 232 38 82 - - Jarman et al. (2002)

bp = amount of sequenced base pairs, n = sample size, S = variable bp positions, NH = number of haplotypes, H = gene diversity (Nei, 1987), � = nucleotide diversity (Nei, 1987)

1.5.5 Mitochondrial Pseudogenes

Mitochondrial-like DNA sequences present in the nuclear genome are called

pseudogenes and were found in several vertebrates and invertebrates representing

Introduction

20

many major animal taxa (Smith et al., 1992; Zischler, 1995; Sunnucks and Hales,

1996; Hadler et al., 1983). Such insertions seem to be the result of relatively recent

intergenomic transfer that can have occurred up to several million years ago (Zhang

and Hewitt, 1996). Some of the insertions were estimated to have a very high copy

number in the nuclear genome from about a hundred to a thousand (Fukuda et al.,

1985; Kamimura et al, 1989).

These nuclear pseudogenes can be used to estimate relative evolutionary rates of

mitochondrial genes, and can be used as outgroups in phylogenetic analyses

(Vallinoto, 2000). Many mitochondrial regions have been found to be integrated into

the nuclear genome including rRNA regions, the control region, cytochrome b regions

and cytochrome oxidase subunit I and II as well (Zhang and Hewitt, 1996). The

nuclear insertion can be a large mitochondrial fragment. A striking example that has

been fully characterized comes from the domestic cat where an insertion involves

about half of the mitochondrial DNA with 7.9 kb (Lopez et al., 1994). Pseudogenes

show various degree of homology with their mitochondrial counterparts, depending

on taxa and the region involved. Being under different mutation constraints they show

different evolutionary patterns with appearance that nucleotide substitutions in the

pseudogenes occur more randomly with less codon bias and the ratios of transversion

versus transition and replacement versus silent substitutions are higher (Zhang and

Hewitt, 1996). Other mitochondrial features as mutation pressure seem to be reduced

in the mode of inferred amino acid substitution (Zischler, 1995). Pseudogenes can be

co amplified or amplified instead of the mitochondrial target in PCR using conserved

primers and the nuclear insertion can be very recent and not yet fixed in natural

populations. They can confound population genetic analyses when accidentally

included in a mitochondrial data set (Zhang and Hewitt, 1996; Williams and

Introduction

21

Knowlton, 2001). Several examples for pseudogenes were also found in crustaceans.

Schnieder-Broussard and Neigel (1997) showed the presence of a nuclear duplication

of the 16S gene in stone crabs which differed at only 3% of their nucleotide bases and

in length by 2bp. Bucklin et al. (1999) identified a putative COI pseudogene in a

copepod that differed at 36% of the nucleotides examined. Nguyen et al. (2002)

identified a copy of the gene for cytochrome b in the nucleus with a 2 base pair

deletion. Williams and Knowlton (2001) showed pseudogenes in several Alpheus

species with nucleotide differences from 0.2% to 20.6% to the mitochondrial COI

gene. In that study many of the pseudogenes were obviously not functional due to

frameshifts but some were of identical length of the functional copy and did not

include any stop codons. Additionally, in some cases the true mitochondrial sequence

was not obtained at all in PCR from gDNA and amplifications just of the pseudogenes

occurred.

Material and Methods

22

2. Material and Methods

2.1 Sampling

Samples for the microsatellite analyses were taken in 2002 from two different

locations with a geographical distance of about 4500 km, which are influenced by

ocean currents that flow in opposite directions (Figure 1, Figure 8). From Bragança

(Pará State) and Paranagua (Paraná State), 79 and 59 male adults were included in the

analysis, respecticely, with a minimum market size of 7 cm. Therefore according to

Diele et al., (2005) the age of the individuals was estimated from 6 to 11 years.

The mitochondrial COI gene sequencing approach was conducted with the addition of

samples collected in 2005 from the surroundings of Amapá (43 individuals),

Maranhão (56 individuals) and São Paulo (45 individuals). All additional individuals

were also adult males with an estimated age varying between 6 to 11 years (Diele et

al.; 2005).

For the COI population analyses the samples were classified into three different

groups: “Upper Amazon” represented by Amapa, “Lower Amazon” represented by

Pará and Maranhão, and “South Brazil” represented by São Paulo and Paraná (Figure

8). In spite of the proximity between Amapa versus Para-Maranhão (only about 200

km), the split in Upper and Lower Amazon is justified by the fact that the Amazon

River represents the major barrier for terrestrial mangrove crabs in the whole

Brazilian coast (Kjerrfe and Lacerda, 1993). The Amazon is the biggest estuary in

Brazil, and its huge discharge of fresh water in the Atlantic Ocean may represent a

significant barrier for U. cordatus larval dispersion.


23

Figure 8 Sampling locations of U. cordatus and the two main ocean currents along the coast of Brazil, running into opposite directions. Sample points were pooled as following: Amapá 1 = “Upper Amazon”; Bragança 2 and Maranhão 3 = “Lower Amazon”; São Paulo 4 and Paraná 5 = “South Brazil”.

Amapá 1 Bragança 2 Maranhão 3 São Paulo 4 Paraná 5


24

2.2. Isolation and Characterization of Microsatellites

2.2.1 DNA Extraction

0,8 g of muscle tissue from one individual from the north of Brazil near the city

Bragança (Para State) in the mangrove forests at the Caeté Estuary was chosen for

DNA extraction to build the enriched libraries. DNA was extracted using Quiagen

Genomic Tip 500/g following the manufacturer’s instructions. The concentration was

determined spectroscopically to 700 ng/µl and the fragmentation evaluated in 1%

agarose gel electrophoresis to 20 kb. The extraction and controlling procedure for the

DNA samples used for further population analysis was similar but instead of the

Genomic Tip Kit, the Kit DNeasy (Quiagen) was used.

2.2.2 Microsatellite Screening and Amplification

The microsatellite screening is based on building a microsatellite enriched partial

library detected by no radioactive hybridisation against biotinilated oligonucleotide

probes and separation by streptavidin coated paramagnetic beads. (Kandpal et al.,

1994; Kijas, 1994). To screen microsatellite loci of increased length, the stringency of

washing the hybridisated beads was set higher than suggested by Kandpal (Oksana,

1998; Shou-Hsien, 1997). The procedure of digestion of the genomic DNA by Sau

IIIa and religation to a vector with M13 universal primer sequences, before PCR

amplificatin and cloning was done according to Xu (1999) and Reichow (1999). The

published method was modified using a different plasmid-vector cloning system.

Here, instead a “blue white selection” in the TOPO cloning system was used, in which

just cells including both plasmid and insert were able to grow. The membrane blot

was modified by using a microwave for bacterial lysis and fixation of the DNA in one

step (Traxler, 2000).


25

First Enrichment

Thirty-five micrograms of genomic DNA was digested with 125 U Sau IIIa, and

10 µg Vector pZErO 2.1 was digested with 100 U of Bam HI according to the

manufacturers instructions. After digestion, 5.25 µg genomic DNA was ligated into

2.4 µg of the vector pZErO 2.1 using 12 U of T4-ligase by incubation over night at

16oC in a total volume of 40 µl. Inserts were amplified by PCR using 0.5 µl of the

ligation product, 10 pmol M13 universal and reverse primer, 2 µg BSA, 37.5 mM

MgCl2, 5 mM dNTPs and 1 U of T4 DNA polymerase in a volume of 25 µl according

to following cycle profile: 5 min 95oC, 30 x (30 sec 95oC, 1 min 60oC, 2 min 72oC )

10 min 72oC, � 4oC. The size of the products was evaluated on a 1% agarose gel by

electrophoresis.

Capture

Different 10 µl PCR reactions were hybridisated against 10 pmol of different

oligonucleotide probes marked by biotin at the 5´ with the sequence (CA)15, (CT)15

and (TCAC)7 using a temperature profile of 10 min 95oC, 60 min 64oC, � 4oC.

The oligonucleotides were ligated to 1 mg streptavidin particles coated by magnetic

beads and separated magnetically from the supernatant according to the

manufacturer’s instructions, then washed with 100 µl of 2 x SSC, 0.1% SDS buffer 5

times for 10 min under highly stringent conditions in a thermo mixer at 1200 rpm with


26

a temperature of 25oC, 40oC, 50oC, 60oC and 70oC. Finally, the beads were eluted in

15 µl of H2O, heated to 97oC and separated magnetically from PCR products.

Second Enrichment

Half of a microliter was added to the PCR reactions with conditions as explained

below and checked on 1% agarose gels by electrophoresis.

Partial Microsatellite Enriched Library Construction

Forty two micrograms of Vector pZErO 2.1 was digested by 240 U of Nsi I in a total

Volume of 60 �l. 41 �l PCR-fragments were digested by 80 U of Nsi I in a total

Volume of 50 �l according to the manufacturer’s instruction. 16 �l of digested PCR-

fragments were ligated into 5 �l of digested vector by 10 U of T4-Ligase in a total

volume of 30 �l following the manufacturer’s protocol, which confirms to a ratio of

fragments to vector of 1/3. 5 �l of the ligation product were transformed into E. coli

Top 10F´ electrocompetent cells (Invitrogen) following the manufacturer’s protocol.

Transformation rates were detected with 2 x 108 cells per �g DNA. 10 �l of the cell

suspension were plated out to get a concentration of 200 colonies per plate on LB-

Agar with 50 �g/ml Kanamycin and 1 mmol IPTG and incubated over night at 37oC.

Library Screening


27

Colonies were transferred from agar plates to positively charged membranes

BIODYNE N (Pall) and incubated for 2 min at room temperature in 2X SSC, 5% SDS

buffer on whatman paper. The plate was reincubated overnight at 37oC. After, the

DNA was lysed and fixed onto the membrane by total drying which was achieved by

incubation for 8min in a 800 W microwave oven at the highest level . The DNA was

then hybridized to fluorescently marked oligonucleotide probes, each sample with its

corresponding capture probe sequence at 64oC over night according to the instructions

of “Dig Systems User´s Guide for Filter Hybridization” (Boeringer Mannheim) and

washed under highly stringent conditions. Positive clones were identified by using

NBT/BCIP colouring with alkaline phosphatase, picked from reincubated plates and

grown in LB medium.

2.2.3 DNA Sequencing and Primer Design

Plasmid DNA was purified by QUIAGEN Spin Miniprep and sequenced using a

sequencing kit (PE Applied Biosystems) on a PE Applied Biosystems 310 Genetic

Analyser according to the manufacturer’s recommendations. PCR-primers were

designed from the sequences flanking the microsatellite repeat arrays using the Primer

Select software (DNA Star). The PCR-conditions were optimised in annealing

temperature, magnesium concentration, primer and template concentration using the

remaining conditions as outlined below. Amplification products were run on 3%

agarose and 10% nondenaturing polyacrylamid gels to check their quality.


28

2.2.4 Analyzing of the Allele Frequencies

The sizing of the PCR products was evaluated by capillary electrophoresis on a PE

Applied Biosystems 310 Genetic Analyser using Fam, and Hex marked primers

according to the manufacturer’s instructions. Data were analysed using the Genescan

2.1 software (PE Applied Biosystems).

2.2.5 Genotyping and population analyses of Ucides cordatus

The genotyping of the different alleles was done by eye supported by Genescan 2.1.

In case of occurring stutter bands, the allele was set to the last intense product of the

stutter profile. This approach was tested in different individuals more then 15 times

and shown (???) to be highly reproducible.

Genetic indices, Hardy Weinberg equilibrium and population analyses were done by

Arlequin 3.01 (Schneider et al. 2000). This program uses a Markov chain

randomization procedure and Fisher exact test (Guo and Thompson, 1992) which is

used to estimate P values. The amount of null alleles was calculated according to

Chakraborty et al (1992). F-statistics were used for AMOVA analysis according to

(Weir and Cockerham 1984); where data were analyzed as standard data not taking

into account different distances between different genotypes. The significance of the F

values was calculated using the 2 statistics with Bonferroni correction (Rice, 1989).


29

2.3 COI Population Approach

2.3.1 DNA Extraction and Sequencing

DNA extraction was carried out using the DNeasy tissue kit (Qiagen). Muscle tissue

stored in absolute ethanol was used for DNA extraction. DNA amplification of

mitochondrial COI was performed using the protocol described by Barber and

Erdmann (2000). Primer concentration in PCR was changed to 30 pmol/�l instead of

250 pmol/�l. PCR was run in 50 �l volumes with four units of Taq Polymerase

(Promega), 10 X amplification buffer provided by the manufacturer, 2 M of MgCl2

and 10 mM of dNTPs. The temperature profile for the PCR was 15 cycles of 95oC for

1 min, 40oC for 1 min 30 sec and 72oC for 1 min 30 sec, followed by 25 cycles of

95oC for 1 min, 50oC for 1 min 30 sec and 72oC for 1 min 30 sec with a final step of

72oC for 10 min. PCR products obtained from individuals in 2002 from Bragança and

Paraná were sequenced after purification with sodium acetate using the amplification

primer. Internal primers were also designed for sequencing using the Primer Select

software and additionally in further approaches internal primers for sequencing

designed as follows (Table 2) by the software Primer Select with 50oC annealing

temperature during cycle PCR on an ABI 310 using BigDye 1.1 (ABI) terminator

chemistry. Further PCR products from individuals added in 2005 were sequenced

using DYEnamic ET Terminator Cycle chemistry (Amershan Bioscience) run on a

MegaBace 1000 Sequencer. Forward and reverse sequences were aligned and

proofread by the software Sequence Navigator and used for analyses if each bp

position was verified by at least two different sequencing approaches with different

primers.


30

Table 2 Sequencing Primers for the mitochondrial gene COI of U. cordatus.

2.3.2 Phylogenetic and Population Variability Analyses Using COI Data

A sequence alignment of COI sequences was done by the software BioEdit (Hall,

1999) and a datafile was exported to PAUP (phylogenetic analyses) and to DNASP

4.0 to produce Arlequin files for population analyses. Haplotype distribution was

done using the software Collapse 1.2 (©David Posada, 1998–2006)

Phylogenetic relationships were performed with PAUP 4.0b10 (Swofford, 2002) using

Neighbor Joining, Maximum Parsimony and Maximum Likelihood methods of

phylogenetic inferences. Robustness of the resulting phylogenetic trees was tested by

bootstrapping using 1000 replicates (Felsenstein, 1985).

Several programs implemented in Arlequin 3.01 (Schneider et al., 2000) were used to

analyze different aspects of the population structure of U.cordatus. These approaches

and applications are described as follows:

Primer Primer sequence (5´ - 3´) Tm

LCO1490 GGTCAACAAATCATAAAGATATTGG 51.00C

HCO2198 TAAACTTCAGGGTGACCAAAAAATCA 57.10C

UCCOL350 GCTGCCGCTATCGCTCACG 59.20C

UCCOL80 GAACTAAGTCAACCAGGAAGAT 46.30C

UCCOH400 CCGGCTAAATGAAGGGAGAA 53.50C

UCCOH550 GCTCCTGCTAAAACTGGTAAAGAT 52.40C

UCCOH600 TATTTAGGTTACGGTCAGTTA 41.80C

UCCOH650 TTGATATAGAACGGGGTCCAC 50.70C


31

The level of polymorphism of each population was estimated as the gene diversity

(Hexp; Nei, 1987), nucleotide diversity (�; Nei, 1987) and expected heterozygosity per

site (�; Watterson, 1975). � statistics were estimated according to Excoffier et al.

(1992) calculating mitochondrial haplotype frequencies (Weir and Cockerham, 1984)

and genetic distances (Tamura-Nei with gamma correction). Pairwise comparisons

among populations were tested for significance with 1000 permutations, and P value

was estimated using the correction suggested by the Bonferroni test (Rice, 1989) (not

included in the Arlequin package). Tajima´s D (Tajima, 1989) and Fu´s Fs test (Fu,

1997) were used to test for neutrality deviations. AMOVA analyses were used to test

for phylogeographic structure of the populations. Mismatch analyses to further

explore the demographic evolution were done according to Slatkin and Hudson

(1991), Rogers and Harpending (1992), and Schneider and Excoffier (1999), and

tested against the sudden population expansion model based on three parameters, �0,

�1 (before and after population growth), and (date of the growth in units of

mutational time: = 2�t, where � is the mutation rate for the whole sequence and t is

the time of expansion). The raggedness rg statistics (Rogers and Harpending, 1992;

Harpending, 1994), which measures the smoothness of the mismatch distribution,

differs among constant size and growing populations: lower rg values are expected

under the population growth model.

Results

32

3 Results

3.1 Isolation of Microsatellite Sequences in Ucides cordatus

Different microsatellite enriched partial libraries of the repeat CA, CT and TCAC

with a total number of 20 000 clones were created (Table 3). 6200 (CA), 4100 (CT)

and 4200 (TCAC) clones were plated out to a concentration of 200 clones per plate

and screened by the corresponding oligonucleotide probe. The number of positive

hybridization signals ranged from 8% (CA) over 10% (CT) to 7% (TCAC).

Twentyseven inserts of different clones were sequenced from the CA library, 50

inserts from the CT library and 30 inserts from the TCAC library.

Table 3 Frequency of microsatellite sequences in the enriched partial libraries of U. cordatus.

CA library CT library TCAC library Clones containing the corresponding microsatellite 85.2% 96% 90.9% Insert size range 70-480bp 59-752bp 362-650bp Average insert size 187bp 259bp 179bp Repeat size range 22-92bp 16-130bp 18-102bp Average repeat size 45bp 51bp 51bp Different clones containing the same microsatellite locus 7.4% 0% 6.6% Perfect repeats 34.8% 54.2% 30% Imperfect repeats 34.8% 33.3% 3.3% Compound repeats 30.4% 12.5% 66.7% Clones containing suitable flanking sequence 47.8% 58.3% 26.7%

Of the 27 clones sequenced from the CA library 85.2% contained the corresponding

microsatellite sequence, whereas from the 50 CT clones it were 96% and from the 30

TCAC clones it were 90.9%. The insert size of all these clones ranged from 59 to

752 bp, with a repeat size ranging from 16 to 130 bp as determined by sequence

analysis. Alignments using both microsatellite flanking sequences identified 7.4% of

Results

33

the sequenced CA inserts and 6.6% of the TCAC inserts as the same locus sequenced

from different inserts of different clones. The frequency of perfect/ imperfect/ and

compound microsatellites was determined according to Weber (1990). In some clones

additional repeat motifs of [AT]n, [ACT]n, [CAC]n, [GGA]n, [TTCC]n, [CCCA]n,

[GGGCC]n, and [GATTCT]n, were found as additional locus or as compounded

repeat. The microsatellite loci with suitable flanking sequences for primer design of

the CA enriched library was 47.8%, of the CT 58.3% and of the TCAC 26.7%,

respectively.

3.2 Characterisation of Selected Microsatellite Loci

From the large number of microsatellite sequences, 47 were selected for primer design

and PCR conditions were optimized. Five loci were finally selected to investigate the

polymorphism among different individuals and populations of U. cordatus (Table 4).

The others did either not produce a PCR product or did not show polymorphism or did

not amplify valuable products. All loci were perfect dinucleotide repeats in the

original individual where just UCL63 was an imperfect mononucleotide-dinucleotide

compound. UCL49 is suggested to be doubled in the genome, amplifying two

separated loci with a length distance of 180 bp from the first loci to the second. The

amplification products for all loci were highly polymorphic in the material tested.

Table 4 PCR conditions and amplification sizes of 5 selected microsatellite loci.Locus Primer sequence

(5´ - 3´) Repeat type TM

oC MgCl2mM

Expected size (bp)

UCL49I AATTTCCCCTTAGGCTCTTCTTC UCL49II AGTGGATTAAACAGATTGGATGAG

[CT]20/ unknown

59 2 118/ 298

GAAATAGCTCCGACCTCTGG UCL63 CCTGGTGGTCATTAAAGAACGA

[C]5G[C]10[CT]8 59 2 107

GCGCTGAGCAGAGGAAGGAACT UCL74 AAGCCATGGACAGCGACAAACT

[CT]19 60 1,5 107

ATGACTCACTACGGAAAATACAGAAUCL55 AAAAACATACATGCAAACACAAT

[CT]32 48 2,5 147

Results

34

All of the amplified alleles showed stutter bands caused by slippages at the

dinucleotide motif (Figure 9) whereas the size of the last intense product which was

counted as allele was always constant. Corresponding to the repetitive motif of

dinucleotide microsatellites, the stutter bands are smaller exclusively in steps of 2 bp,.

Even with the occurrence of the stutter bands, the measurements of allele size did

show highly reproducible results, showing a deviation with a maximum of 0.3 bp in

exemplary approaches which where more than 10 times repeated in the same

individual. Multiple analyses of the same individual also showed no differences

between Fam and Hex marked amplifications. Individuals with overlapping stutter

bands from one allele reaching the area of the second allele were not taken into the

population analyses. In these cases, due to addition of the intensities of the bands the

correct allele size of the smaller allele could not be easily scored.

Results

35

Figure 9 Examples of amplified fragment analyses of locus UCL55 in three different individuals. The peak area is proportional to the concentration of the fragment. In the stutter profile the last intense peak was counted as allele (peak, size, peak high and area in bold). The stutter bands are exclusively smaller in steps of 2 bp amplifying a dinucleotide microsatellite. Individual A is counted to be heterozygous with 2 alleles of 132 and 158 bp coloured with Fam, B to be homozygous with 2 alleles of 126 bp coloured with Hex and C heterozygous with 2 alleles of 132 bp coloured with Hex.

A

B

C

Results

36

3.3 Diversity of Selected Microsatellite Loci

All of the microsatellite loci show a high variability (Table 5). The amount of

different alleles ranges from 16 to 47 with an average of 35.2. In the populations of

Bragança and Paraná each locus shows an observed heterozygosity (from 0.23 to

0.88) lower than the expected one (from 0.87 to 0.96). All tests of Hardy Weinberg

equilibrium showed a significant (p < 0.05) deviation with D values from -0.08 to -

0.75. In both Bragança and Paraná each locus shows an excess of homozygosity. An

estimation of the amount of zero alleles after Chakraborty et al. (1992) showed that

between 4.3% and 57.3% of the alleles cannot be amplified and fall out of the

population analyses. A correlation between the amount of individuals, the excess of

homozygosity and the origin of the samples is not observed.

Table 5 Genetic diversity and Hardy Weinberg equilibrium of 5 microsatellite loci within individuals from Bragança and Paraná.

Locus Repeat Motif L n Allele Ho He D P Null allele

UCL49I (CT)20 B 32 28 0.88 0.96 -0.08 0.0001 0.043 UCL49I (CT)20 P 28 17 0.79 0.87 -0,09 0.0312 0.048 UCL49II UNKNOWN B 61 47 0.77 0.96 -0,19 0.0224 0.109 UCL49II UNKNOWN P 27 20 0.37 0.90 -0,59 0.0056 0.417 UCL55 (CT)32 B 42 20 0.26 0.96 -0,72 0.0000 0.573 UCL55 (CT)32 P 35 18 0.23 0.95 -0,75 0.0000 0.610 UCL63 (C)5G(C)10(CT)8 B 46 16 0.80 0.88 -0,09 0.0069 0.047 UCL63 (C)5G(C)10(CT)8 P 41 16 0.63 0.88 -0,28 0.0000 0.165 UCL74 (CT)19 B 13 19 0.77 0.98 -0,21 0.0416 0.120 UCL74 (CT)19 P 27 20 0.81 0.95 -0,15 0.0000 0.079 Locality B = Bragança, P = Paraná, n = sample size, Allele = amount of different alleles, Ho = observed heterozygosity, He = expected heterozygosity, D = deficit or excess of heterozygosity (Ho-He)/(He), P = value of probability of significant deviation from HWE (Markov chain procedure, p < 0,05), Null allele = estimated amount of not amplified alleles according to Chakraborty (1992)

An AMOVA analysis based on F statistics of 5 microsatellite loci resulted in

variations from 0.08 to 0.73 with an average of 0.453 within the populations and from

Results

37

0.011 to 0.048 with an average of 0.027 among the populations (Table 6), where just

significant results were taken into calculations.

Table 6 Analyses of Molecular Variance (AMOVA) among U. cordatus of 5 microsatellite loci based on F statistics among and within the populations from Bragança and Paraná.

Locus Fis P.Value Fst P.Value UCL49I 0.08708 0.00782 0.04780 0.00000 UCL49II 0.31152 0.00000 0.03236 0.00782 UCL55 0.73920 0.00000 0.01148 0.00901 UCL63 0.17446 0.00000 0.01471 0.00901 UCL74 0.16798 0.00000 -0.00772 0.82883 Fis = Fixation index within populations, variability of all individuals, Fst = Fixation index among populations, variability between the individuals of Bragança and Paraná

3.4 Characterisation of the Partial COI Coding Sequence

Amplification of the partial COI gene of U. cordatus resulted in a product of 710 bp

(Figure 10). Of this product 600 bp were sequenced and taken into account for further

analysis. The alignment revealed 101 variable base pair positions (Figure 11) with 17

situated at the first codon position, five on the second and 79 on the third position. No

gaps were found in this part of the COI alignment.

Translations according to the mitochondrial code to amino acid sequence did not

show nonsense codons and or stop-codons. Blast search at the web page of NCBI

(National Center for Biotechnology Information) against the DNA databank showed

the highest similarity with partial COI coding sequences of the species Portunus

trituberculatus (Crustacea, Decapoda, Brachyura, accession number: AY303613) with

an identity of 468/578bp (84%). Further similarities were just matched with partial

COI genes of other crustaceans (Celuca pugilator AF466700, Munida sp. AY351029,

Results

38

Gaetice depressus AF317339, Pseudocarcinus gigas AY562127, Hemigrapsus

oregonensis DQ022526) and similarly did not show any gaps in aligned sequences.

Otherwise when aligned with partial mitochondrial COI sequences of the species

Pachygrapsus crassipes (AY952100) two gaps within 576 bp were found.

Figure 10 Amplification of the mitochondrial gene CO I with different individuals using the “universal Primer” LCO1490 and HCO2198 published by Folmer (1994) results in a 710 bp product.

Res

ults

39

Variable base pair position of the 600 bp sequenced PCR product Haplotype distribution

1311355677 7899111111 1111111122 2222222222 2222333333 3333333344 4444444444 4444444444 4555555555 5555555555 5 within individuals

36156103 6247001134 5666678922 2334446667 7889001233 4444567800 0111233345 5567788999 9001225566 7777888899 9 s = sample (232)

065868 1016984303 7281272581 2065466857 0469270203 6025401611 6700817017 9564061358 0457034905 8 UA = Upper Amazon (43)

LA = Lower Amazon (102)

SB = South Brazil (78)

#Consensus AGTTACCCAA TCTATTAACA AGTATGCATA CTTTAAGTAA AACTCCCTTA ATCCTAAAAA AATATAAAAA TGAACTTTCT ATTATAAACC CAGTTTCTCT A s UA LA SB

Hap

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”#H_5 .......... .......... ......T... ......A... .......... .......... .......... .......... .......... .......... . 2 1 0 1

#H_7 .......... .......... .......... .......... .......... .......... .........G .......... .......... .......... . 2 1 0 1

#H_14 .......... C......... .......... .......... .......... .......... .......... .......... .......... .....C.... . 5 2 0 3

#H_16 .......... .......... .....A.... .......... .......... .......... .......... .......... .......... .....C.... . 2 1 0 1

#H_18 .......... .......... .......... .......... .......... .......... .......... .......... .C........ .......... . 2 1 0 1

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#H_1 .......... .......... .......... .......... .......... .......... TT........ .......... ....C..... ..A....... . 1 1 0 0

#H_2 .......... C......... .......... .......... ..A....... .......... .......... .......... .......... .......... . 1 1 0 0

#H_4 .......... .......... .A........ .......... ....T..... .......... .......... .......C.. .......... .....C.... . 1 1 0 0

#H_6 .......... .......... .......... .......... .......... .......... .......G.. .......... ........A. .......... . 1 1 0 0

#H_8 .......... .......... .......... .......... .......... .......... T......... .......... .......... .........C . 1 1 0 0

#H_9 .......... .......... .......... .......... .......... .......... .......... .......... .......C.. .......... . 1 1 0 0

#H_11 ..A....... C......... .......... .......... .......... .......... .......... .......... .......... .....C.... . 1 1 0 0

#H_13 .......... .......... .......... .......... .....T.... .......... .......... .......... ......T... G......... . 1 1 0 0

#H_20 .......... .......... .A........ .......... .......... .......... .......... ....T..... .C........ .......... . 1 1 0 0

#H_21 .......... ..C....... G......... .......... .......... .......... .......... .......... .........T ....C..... . 1 1 0 0

#H_22 .......... .....C.... ....C..... .......... .......... .......... .......... .......... .......... .......... . 1 1 0 0

#H_23 .......... CT........ .......... .......... .......... .......... .......... .......... .......... .....C.... . 1 1 0 0

#H_24 .......... ..C.....T. .......... .......... .......... .......... .......... .......... .........T ........T. . 1 1 0 0

#H_25 ........G. ..C....... .A........ .......... .......... .......... .......... .........C .......... .......... . 1 1 0 0

#H_26 .......... ..C......G .......... .........G .......... .......... .......... .......... .........T .......... . 1 1 0 0

#H_27 .......... .......... .A........ .......... .......... .......... .......... .......... .......... .......... . 1 1 0 0

#H_28 ..A....... .......... .......... .......... .......... .......... .......... .A..T..... .......... .......... . 1 1 0 0

#H_29 .....T.... .......... .......... .......... .......... .......... .......... ........T. .......... .......C.. . 1 1 0 0

#H_30 .......... .......... .......... .......... .......... .......... .......... .......... .......... ...C....T. . 1 1 0 0

#H_31 ....G..... .......... .......... .....G.... .......... .......... .......... ...G...... .......... .......... . 1 1 0 0

#H_32 C......... .......... .......... .......... .......... .......... .......... .A..T..... .......... .......... . 1 1 0 0

#H_34 ......A... ....C.G..T .......... .......... .....G.... .......... .......... .......... .......... .......... . 1 1 0 0

#H_35 .......... .......... .A......C. .......... .......... .......... .......... ....T..... .......... .......... . 1 1 0 0

Figu

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36156103 6247001134 5666678922 2334446667 7889001233 4444567800 0111233345 5567788999 9001225566 7777888899 9 s = sample (232)

065868 1016984303 7281272581 2065466857 0469270203 6025401611 6700817017 9564061358 0457034905 8 UA = Upper Amazon (43)




Haplotypes shared by “Upper Amazon” and “Lower Amazon”

#H_12 .......... .......... ........C. .......... .......... .......... .......... ....T..... .......... .......... . 2 1 1 0

#H_17 .......... .......... .......... .......... .......... .......... .......... .......... .......... .........C . 3 2 1 0

#H_19 .......... .......... .......... T......... .......... .......... .......... .......... .......... .......... . 4 1 3 0

Haplotypes just found in “Lower Amazon”

#H_36 .......... C......... .......... .......... .......... G......... .......... .......... .......... .......... . 1 0 1 0

#H_37 .......... .......... .......... .......... .......... .......... .......... .......... .........G .......... . 1 0 1 0

#H_38 .......... .......... .......... .......... .......... .......... ...G...... .......... .......... .......... . 1 0 1 0

#H_39 .......... .......... .......... ......A... .......... ....C...G. .......... .......... .......... .......... . 1 0 1 0

#H_40 .....T.... .......... .......... .......... .......... .......... .......... ........T. .......... .....C.... . 1 0 1 0

#H_41 .......... .......... .......... .....G.... .......... .......... .......... .......... .......... .......... . 5 0 5 0

#H_42 .......... .......... .......... .....G.... ........C. .......... .......... .......... .......... .....C..A. . 1 0 1 0

#H_44 .......... .......... G......... .......... .......... .......... .......... .......... .......... .....C.... . 1 0 1 0

#H_45 .......... .......... .......... .......... C.T....... .......... .......... G......... G......... .....C.... . 1 0 1 0

#H_46 .......... .......... .......... .......... .......... .......... .......... ....T..... .......... .....C.... . 1 0 1 0

#H_47 .......... .......... ..C....... ........G. .......... .......... .......... .A........ .......... .....C.... . 1 0 1 0

#H_48 .......... .......... ..C....... .......... .......... .......... .......... .A........ .C........ .......... . 2 0 2 0

#H_49 .......... .......... .A........ .......... .......... .......... .......... .A..T..... ..CG...... .......... . 1 0 1 0

#H_50 .......... .......... .A........ .......C.. .......... .......... .......... ....T..... .......... .......... . 1 0 1 0

#H_51 .......... .......... .......... .......... .G........ .......... .......... .A........ .......... .....C.... . 1 0 1 0

#H_52 .......... .......... .......... .......... .......... .......... .......... .......C.. .......... ....AC.... . 1 0 1 0

#H_53 .......... .......... ........C. ......A..G .......... .......... .......... ....T..... ........T. .......... . 2 0 2 0

#H_55 .......... .......... .......... .......... .......... .......... .......... .......... .....G.... .......... . 1 0 1 0

#H_56 .......... .......... .....A.... .......... ....T..... .......... .......... .A.....C.. .......... .....C.... . 1 0 1 0

#H_57 .......... .......... .......... .......... .......... .......... .......... .......... .......... .....C..T. . 1 0 1 0

#H_58 .......... .......... .......... T......... .......... .......... .......... .A........ .......... .......... . 1 0 1 0

#H_59 .......... .......... .......... .......... ..T....... .......... .......... .......... ........T. .....C.... . 1 0 1 0

#H_60 .......... .......... .......G.. .......... .......... ...A...... .......... .......... .......... .......... . 1 0 1 0

#H_61 .......... ......G... .......... .......... .......... .......... .......... .......... .......... .......... . 1 0 1 0

Figu

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.

Res

ults

41



36156103 6247001134 5666678922 2334446667 7889001233 4444567800 0111233345 5567788999 9001225566 7777888899 9 s = sample (232)

065868 1016984303 7281272581 2065466857 0469270203 6025401611 6700817017 9564061358 0457034905 8 UA = Upper Amazon (43)




Haplotypes just found in “Lower Amazon”

#H_62 .......... .......... G......... .....G.... ........C. .......... .......... .......... .......... .......... . 2 0 2 0

#H_63 .......... .......... ........A. ...G...... .......... .......... .......... ....T..... .......... .......... . 1 0 1 0

#H_64 ....G..... .......... .......... .....G.... .......... .......... .......... .......... .......... .......... . 1 0 1 0

#H_65 .......... .......... .......... .........T .......... .......... .......... .......... .C........ .......... . 1 0 1 0

#H_67 .......... .......... .A...A.... .......... .......... .......... .......... .......... .......... .......... . 1 0 1 0

#H_68 .......... .......... .......... .......CG. .G........ .......... .......... .A........ .......... .....C.... . 2 0 2 0

#H_69 .......... .......... .......... ......T... .......... .......... .....G.... .......... .......... .......... . 1 0 1 0

#H_70 .......... ..C....... .......... ..C......G .......... .......... .......... .......... .........T .......... . 1 0 1 0

#H_72 .......... .......... ..C....... .......... .......... .......... .......... .A........ .C........ .....C.... . 1 0 1 0

#H_74 .......... .......... .......... .......... .........G .......... ..C....... .......... .C........ .......... . 1 0 1 0

#H_75 .......... .......... ..C.....C. .......... .......... .......... .......... .A........ .......... .....C.... . 1 0 1 0

#H_76 .......... .......... .A........ .C........ .......... .......... .......... .A........ .......... .....C.... . 1 0 1 0

#H_77 .......... .......... ..C....... .......... .......... .......... .......... .......... .......... .......... . 2 0 2 0

#H_78 ...A...... .......... .......... .......... .......... .......... .......... .......... .......... .........C . 1 0 1 0

#H_79 ....G..... .......... .......... .......... .......... .......... .......... .......... .......... .........C . 1 0 1 0

#H_80 .......... .......... .......... .......... .......... .......... .......... ....TC.... .......... .......... . 1 0 1 0

#H_81 .......... .....C.... .......... .......... ...C...... .......... .......... .......... .......... .......... . 1 0 1 0

#H_82 .......... .......... ..C....... ....G..... .......... .......... .......... .A........ .......... .....C.... . 1 0 1 0

#H_83 .......... .......... G..G...... .......... .......... .......... .......... .......... .......... .......... G 1 0 1 0

#H_84 .......... ..C....... .......... .......... .......... .......... .......... ..G....... .......... .........C . 1 0 1 0

#H_85 .......... .......... .......... .......... .......... .......... .......... .A........ .........T .....C.... G 1 0 1 0

#H_86 .......... ..C....... .A........ .......... .......... .......G.. ......G... .......... .........T .C....G... . 1 0 1 0

#H_87 .......... .......... .......... .......... .......... ....C..... .......... .......... .......... .......... . 1 0 1 0

#H_89 .......... .......... ......T... .......... .......... .......... .......... .......... .......... .......... . 1 0 1 0

#H_90 .......... .......... .......... ......A... .......... .......... .......... .......... .......... .......... . 1 0 1 0

#H_91 .......... .......... .......... .........G .GT....... .......... .......... .......C.. ........T. .....C.... . 1 0 1 0

Haplotypes shared by “Lower Amazon” and “South Brazil”

#H_43 .......... .......... .......... .......... .......... .......... .......... .A........ .......... .....C.... G 9 0 6 3

#H_54 .......... C......... .......... .......... .......... .......... .......... .......... .......... .......... . 3 0 2 1

#H_66 .......... .......... ..C....... .......... .......... .......... .......... .A........ .......... .....C.... . 5 0 4 1

#H_71 .......... .......... .......... .......... .......... .......... .......... .A........ .......... .....C.... . 4 0 2 2

#H_73 .......... .......... .......... .......... .......... ......C... .......... ....T..... .......... .......... . 2 0 1 1

#H_88 .......... .......... .......... .......... .......... .........G .......... .......... .......... .......... . 2 0 1 1

Figu

re 1

1 A

lignm

ent

of 6

00 s

eque

nced

var

iabl

e ba

se p

air

posi

tions

and

hap

loty

pe d

istri

butio

n of

the

CO

I c

odin

g ge

ne w

ithin

thr

ee p

opul

atio

ns

(con

tinua

tion)

.

Results

42

3.5 Diversity of the COI Coding DNA

The 600 bp fragment sequenced in 223 individuals generated 132 distinct COI

haplotypes. Of these 600 sites, 499 are monomorphic while 101 are variables and 47

of these being parsimony informative.

Of the 223 sequences, 103 were singletons, 27 occurred 2-5 times and one nine times.

Haplotype #H_3 was the most frequent in the analyses being found in 35 individuals.

Within the 101 variable base pair positions, 83 are transitions and 32 transversions

with 115 substitutions altogether. In some positions in few individuals a transition and

in other individuals a transversion took place. It is reasonable that the total number of

substitutions is higher than the number of variable bp positions. The mean number of

pairwise nucleotide differences in 600 bp was 3.87 bp.

The distribution of nucleotide composition in different populations was equal with a

high AT content as observed in many mitochondrial DNAs. Cytosine occurs with a

frequency of 20.75%, thymine with 33.10%, adenine with 29.8% and guanine with

16.35%.

The “Upper Amazon” population possesses 24 haplotypes in 43 individuals, the

“Lower Amazon” and “South Brazil” populations, 50 and 41 in 102 and 78,

respectively. “Upper Amazon” and “Lower Amazon” share 3 haplotypes, “Upper

Amazon” and “South Brazil” 5 and “Lower Amazon” and “South Brazil” 6. However,

the three populations share only 4 haplotypes (haplotypes #H_3, #H_10, #H_15 and

#H_33). Only one haplotype (#H_3) was highly significant in the analysis, where 35

individuals share this haplotype.

Results

43

The nucleotide divergences among the haplotypes, using Kimura 2 parameters, varied

from 0% to 1.7%. However, the divergence within each population varied from 0.6%

to 0.7% (Table 7), between the populations it was constant with 0.7%.

Table 7 Pairwise �st (below diagonal), Kimura 2 population divergence within (below diagonal) and between populations (above diagonal) among U. cordatussamples.

Population Upper Amazon Lower Amazon South Brazil

Upper Amazonas 0,007 0,007 0,007

Lower Amazonas 0.0207* 0,006 0,007

South Brazil 0.0393** 0.0223** 0,006

* = P < 0,001; ** = P < 0,0001

The three classic methods (Neighbor Joining, Maximum Parsimony and Maximum

Likelihood) were used for phylogenetic reconstructions coupled with bootstrap

analysis for estimated approximation of branches support. The same basic topology

was obtained and only the Neighbor Joining tree is presented (Figure 12). Basically it

can be noted that there are only few branches highly supported by bootstrap values

and most of them are smaller than 50%. Besides, there is no significant grouping

containing individuals of the same area, highlighting that gene flow is occurring

among these groups. The trees obtained are star-like, which is the kind of tree

commonly observed in cases when low diversity is observed or when a population

expansion event takes place (Templeton, 1996; Alexandrino et al., 2002).

Results

44

Figure 12 Neighbor joining tree found for 123 COI mtDNA haplotypes in Ucides cordatus. Bootstraps percentages of 1000 pseudoreplicates greater than 50% are shown at the nodes.

Results

45

3.6 Demographic Investigation Using the COI Marker

The descriptive population analysis is shown in Table 8 and 9. All three populations,

as well as the whole population show high haplotype and low nucleotide diversity

values,. According to the D and Fs tests, which were negative and significant, all the

populations show deviations from the neutrality. These values are observed in a

situation of population expansion, background selection or hitchhiking (Hahn, 2002;

Stajich and Hahn, 2005).

Table 8 Descriptive statistics with diversity and neutrality parameters for the studied U. cordatus populations.

Population n NH H � D Fs

Upper Amazon 43 35 0.97 +/- 0.02 0.0065 +/- 0.004 -2.3683* -25.921*

Lower Amazon 102 63 0.97 +/- 0.01 0.0063 +/- 0.004 -2.2244* -25.983*

South Brazil 78 56 0.97 +/- 0.02 0.0064 +/- 0.004 -2.1471* -25.989*

Collective 223 132 0.97 +/- 0.01 0.0065 +/- 0.004 -2.3608* -25.605*

n = sample size, NH = number of haplotypes, H = gene diversity (Nei 1987), � = nucleotide diversity (Nei 1987), D = Tajima test and Fs (Fu test), * Significant at level 0.01

To test the population expansion hypothesis three different statistics were used: �0 and

�1, sum of square deviations (SSD), and the raggedness index (Table 9). It can be

observed that according to the SSD (PSSD), for all populations, the expansion process

cannot be rejected. This is in accordance with the raggedness indexes, which are

inferior to 0.05. According to the �0 and �1 values, there is no overlapping between

these parameters in any of the populations analyzed. Therefore, the expansion process

Results

46

is not rejected by any of the tests used (Aris-Brosou and Excoffier, 1996; Ramos-

Onsins and Rozas, 2002).

Table 9 Descriptive statistics with expansion parameters for the studied U. cordatuspopulations.

Population �0 �1 PSSD rg Prg

Upper Amazon 4.067 0.006 (0.000-1,517) 144.688 (28.689-8164.69) 0.87 0.017 0.72

Lower Amazon 3.913 0.000 (0.000-1,616) 80.430 (21.641-7614.18) 0.78 0.018 0.63

South Brazil 4.058 0.000 (0.000-1,426) 790 (45.859-9055) 0.51 0.019 0.53

Collective 4.030 0.027 (0.000-1.301) 121.250 (28.466-8088) 0.67 0.017 0.60

The analysis of the mismatch distribution reveals an exponential curve for all

populations analyzed, as well as for the population as a whole. This kind of curve is

typical for a population in an expansion process (Rogers and Harpending, 1992).

Figure 13 shows the mismatch distribution only for the whole population, since the

others presented the same basic curve. It is worth to notice the small differences

between the expected and observed curves.

On the basis of the parameter ( = 2uT), the time of this population expansion was

calculated on assuming a mutation rate ranging between 1.4% and 2.3% per million

years for the COI gene in crustaceans (Knowlton et al. 1993, Knowlton & Weigt

1998). Thus, the values of � vary from 0.7x10-9 to 1.15x10-8. However, assuming a

generation time of three years for crustaceans (Diele, 2000), these values range from

2.1x10-8 to 3.45x10-8. For DNA sequence data the mutation of the entire DNA

sequence is calculated by u = MT � (Rogers and Harpending, 1992), where MT is the

number of nucleotides assayed per individual and � is the mutation rate. Taking into

account that the sequences analyzed have 600 base pairs, u varied by 1.26x10-5 to

Results

47

2.07x10-5. Therefore, the age of the population expansion possibly began to occur

sometime between 479761.9 and 292029 years ago.

Figure 13 Mismatch distribution for all pairwise combinations of 223 individuals for U. cordatus. Observed distribution (interrupted line) coincided with the expected Poisson distribution (continuous line) under a model of sudden population expansion.

As previously shown, small values of nucleotide divergence between the three

populations analyzed have been observed. Through the �st value it is possible to infer

little differentiation between the populations (Table 7), in which values are below 5%

and thus generally accounted to be very low due to a low structuring in populations

(Wright, (1978) cited by Hartl, (1987)). The highest value observed was found

between the Upper Amazon and South Brazil populations (0.0393).

To quantify the degree of genetic structure within and between the populations of U.

cordatus a hierarchical test for variability AMOVA was performed, using different

group compositions (Table 10). The first includes all populations in one group, which

Freq

uenc

y

Results

48

shows that the majority of the variation is due to the variation within the populations

(97,44%), while between the populations a variability of only 2.56% exists with a

significant �st of 0,0256. The other group comparison combinations disclosed a

similar picture, where all show no significant values of �ct and the highest variation

occurs within all populations. On the base of the Fst values the migration rate was

calculated resulting in 23.61 individuals per generation between “Upper Amazon” and

“Lower Amazon”, 12.21 between “Upper Amazon” and “South Brazil” and 21.93

between “Lower Amazon” and “South Brazil”.

Tab 10 Hierarchically genetic structuring of U. cordatus populations.

Structure tested Variance % total � statistics P

1. One gene pool (Upper Amazon, Lower Amazon and South Brazil

Among Population 10.935 2.56 (�st) 0.026 0.000

Within Populations 422.473 97.44

2. Two gene pools (Upper Amazon) (Lower Amazon and South Brazil)

Among groups 5.157 0.69 (�ct) 0.007 0.338

Among Population 5.778 2.21 (�sc) 0.029 0.001

Within Populations 422.473 97.10 (�st) 0.022 0.000

3. Two gene pools (Upper Amazon and Lower Amazon) (South Brazil)

Among groups 6.571 0.70 (�ct) 0.007 0.330



4. Two gene pools (Lower Amazon) (Upper Amazon and South Brazil)

Among groups 4.607 -1.89 (�ct) -0.02 0.662



Discussion

49

4 Discussion

4.1 Isolation and Characterisation of Microsatellite Loci

In this study microsatellites were successfully isolated from different enriched

libraries of U. cordatus. The microsatellite markers developed here are the first for

Ucides up to now in which just 16S and 18S RNA genes are published, but these

markers are not useful as genetic markers for intraspecific DNA analyses.

A microsatellite enrichment strategy was approached with success in the different

partial libraries resulting in 7% to 10% positive clones in which the corresponding

screening sequence of CA, TC, and TCAC were found from 85.2% to 96%. A

conclusion about the general abundance of the corresponding repetitive motif in the

genome cannot be made because the partial library was enriched before screening and

screening approaches without enrichment were not done. Comparing to the amount of

traditional microsatellite screening procedures without enrichment, CA dinucleotide

repeat microsatellites can be expected in crustaceans with an amount of 2.6% in

partial libraries.

The average of positive clones in different non-enriched microsatellite isolations in

crustaceans was reviewed by Zane et al. (2002). Invertebrates are generally

characterized as having relatively low microsatellite abundance (Chambers and

MacAvoy 2000). In taxa as diverse as mammals, vertebrates and arthropoda, CA

microsatellite motifs occur mostly with 825 to 1496 bp per megabase within the

whole genome. By contrast, tetranucleotide microsatellites occur 120 to 2100 times

Discussion

50

less frequently (Tóth et al. 2000). Assuming that the abundance of different

microsatellite repeats in the genomic DNA is the same in Ucides as in other

crustaceans, the CT and CA dinucleotide motifs are the most common. The

occurrence of TCAC tetranucleotide motif is much rarer (Tassanakajon, 1998;

Brooker, 2000). The amount of positive clones carrying microsatellites with the

corresponding repeat in this study did not differ remarkably between the CA and

TCAC enriched libraries. This frequency indicates that the method is suitable to

isolate microsatellite repeats in a sufficient quantity and that even rare motifs can be

isolated. The fact that the same microsatellite locus was isolated in very few different

clones (110 were sequenced and additional repeat motifs were found), indicates that

many more loci exist in the genome of U. cordatus. Many more different repeat

motifs from dinucleotides to hexanucleotides are available for marker development.

An average repeat size higher than 45 in the different libraries of Ucides cordatus

suggests that longer microsatellite loci were isolated preferentially to shorter ones in

spite of the fact that smaller loci are much more abundant in the genome of

crustaceans (Pongsomboom et al., 2000). The low amount of clones carrying inserts

with suitable flanking sequences indicates that inserts smaller than 250 base pairs

were too small and their size should be increased in future approaches for this species.

In the microsatellite isolation procedure in general and from several crustacean

species especially, there are two explanations for the loss of potential usable loci.

First, the high amount of generated sequences with regions flanking repeats that are

not suitable for primer design; and second the high amount of loci with designed

primers which are not usable for population studies, due to the lack of clearly

Discussion

51

analysable amplification results or the lack of polymorphism (exampled in Table 11).

Therefore, if just a very low amount of microsatellite loci in the genome of U.

cordatus will fullfil the requirements of genetic markers for population analyses or if

recently used isolation procedures generates DNA sequences which do not exist in the

genome, has to be taken into account. Unfortunately, this study was not able to answer

this question.

Using the categorization of microsatellite loci according to Weber (1990), the

distribution of perfect, imperfect and compound microsatellites was homogeneous in

the CA motif enriched library of U. cordatus. In the CT motif enriched library,

however, perfect repeats were dominant and compound repeats were found more

rarely. By contrast, in the TCAC motif enriched library compound repeats were

dominant and imperfect repeats were very rarely isolated. This could indicate that the

majority of different repeat motifs in U. cordatus underlie different molecular

processes during evolution or that the distribution of perfect, imperfect and compound

loci is not detectable with low sample sizes regarding to the thousands of different

loci suggested in the whole genome.

Discussion

52

Table 11 Microsatellite isolation in different crustacean species.

Species Pos.

clones

Sequenced

clones

Primer

pairs

Loci for

population

Reference

Ucides cordatus

(Crustacea, Decapoda)

1700 107 47 5 This study

Farfantepenaeus notialis


271 89 15 7 Robainas et al.

(2002)

Porcellionides pruinosus

(Crustacea Isopoda)

95 30 10 6 Grandjean et al.

(2005)

Portunus pelagicus

(Crustacea, Portunidae)

42 42 19 7 Yap et al.

(2002)

Triops cancriformis

(Crustacea, Branchiopoda)

180 58 55 5 Cesari et al.

(2004)

Chthamalus montagui

(Crustacea, Cirripedia)

271 68 16 7 Pannacciulli et

al. (2005)

Eriocheir sinensis


87 71 20 12 Haenfling and

Weetman (2003)

The number of different alleles of the five microsatellite loci selected in this study

differs from 16 to 47 and results in a high variability with a lower amount of observed

heterozygosity and higher amount of expected heterozygosity, respectively.

Comparing to other crustaceans, high polymorphism was found in other dinucleotide

microsatellite loci: 34-84 alleles within three loci of Penaeus monodon in Australia

(Brooker et al., 2000), 10-76 alleles within 6 microsatellite loci of Litopenaeus

setiferus in America (Ball and Chapman, 2003), or 13-70 alleles within six

microsatellite loci of Litopenaeus schmitti in Brazil (Maggioni et al., 2003).

In comparison of the parameters of genetic diversity between populations from

Bragança and in Paraná, the number of alleles, the Ho and the He were lower in locus

ULC49I, ULC49II and ULC55. At locus ULC63 just the Ho was lower whereas the

Discussion

53

number of alleles and the He were equal. Locus ULC74 showed slightly higher

variability in Paraná than in Bragança but this estimation is just based on 13

individuals against the other loci, which are based on 27 to 61 individuals from each

location. Therefore, it is indicated that in Paraná the diversity seems to be lower than

in Bragança but due to the low number of microsatellite loci analysed this conclusion

cannot be generalized. Only an analysis including additional loci could confirm this

assumption. Nevertheless, the high allele variation of the microsatellite loci observed

in this study showed enough resolution to detect a differentiation of populations.

4.2 Experimental Uncertainties in Using Selected Microsatellite Loci

Highly significant deviations from the Hardy-Weinberg equilibrium were detected for

all tests at each locus in the population of Bragança and Paraná, with a deficit of

heterozygosity of -0.08 to -0.72. This phenomenon has also been reported for other

crustaceans. In Penaeus monodon, Supungul et al. (2000) found an excess of

homozygosity in 19 of 25 tests possible. Ball et al. (2003) found an excess of

homozygosity in Litopenaeus setiferus. Similar results were detected by Robainas et

al. (2002) in Farfantepenaeus notialis at 3 of 5 loci. HWE disequilibrium observed in

U. cordatus may be due to many reasons like mating of close relatives (inbreeding),

population mixing (Wahlund effect), technical artefacts, zero null alleles or due to the

lack of selective neutrality of the loci (Castric et al., 2002). Strongly different values

of D for the deficit of heterozygosity within the five loci where observed in both

populations. Therefore the Wahlund effect as the only reason for the excess of

homozygous individuals would be unlikely because this would affect all different loci

Discussion

54

in the same way, and at least a trend, such as higher values in one population, should

be recognized

Another explanation for the Hardy-Weinberg desequilibrium in microsatellites of U.

cordatus could be the presence of null alleles, i.e., the failure to amplify one of the

alleles in an individual due to mutations in the flanking regions for example. The

estimation of the amount of null alleles after Chakraborty (1992) ranged in all

microsatellite loci from 0.043 to 0.417 where differences of up to 0.306 between

Bragança and Paraná in locus UCL49II were suggested. Additionally, the fact that

some individuals were easily amplified in four of the five loci, but not in one, suggests

the presence of null alleles. More importantly, null alleles can distort population

analysis. Estimation of relatedness, for example, is particularly vulnerable to null

alleles (e.g. Avis and Dakin 2004).

An additional explanation for the excess of homozygosity could be the individual

misscoring of genotype due to stutter bands (Pemberton et al., 1995). The presence of

technical artefacts due to stutter bands could cause a misclassification of heterozygous

individuals for alleles closely matched in size as homozygous. This effect is normally

present in dinucleotide loci as a result of slipped strand mispairing during PCR. In the

present study it was observed, that the number of stutter bands is variable among loci

and individuals, but the normal pattern was a stronger last band in stutter profiles with

weak stutter bands. Thus, the alleles of the present work were scored according to the

recommendations of Xu et al. (2001).

Discussion

55

4.3 Microsatellite Diversity in U. cordatus Populations

F statistics detected a low but highly significant variability between Bragança and

Paraná, with Fst values varying from 0.011 in locus UCL55 to 0.048 in locus

UCL49I.

The Fixation Index can also be defined as the standardized variance of allele

frequencies. It is the ratio of the observed variance of gene frequencies over

subdivisions divided by the maximum possible variance that can be reached when

alleles have gone to fixation in all subdivisions (Excoffier, 2001). For U. cordatus,

four of five loci showed restricted gene flow between the two populations of Bragança

and Paraná, and this is demonstrated by significant P values lower than 1%. Only

locus UCL74 did not show significantly restricted gene flow.

The Fst value over four loci is 0.027 which was averaged after analysing each locus

on its own as recommended by Excoffier (2001). The loci were not analysed together

because different individuals from each location were genotyped. The lack of a

substantial population structure was not due to a lack of polymorphism at the loci

studied because the fixation indexes within all individuals (Fis) show a high and

significant variability varying from 0.09 to 0.73.

Finally, the possible error rate in genotyping individuals through stutter bands and the

suggested high amount of null alleles could be a reason for the H-W disequilibrium.

This would make the significance of the data for population discrimination debatable

resulting in the lack of testing the loci of selective neutrality and of being unlinked.

Discussion

56

The weak population structure found in U. cordatus was therefore confirmed using an

additional analysis using mitochondrial DNA sequences of the Cytochrome oxidase

subunit I.

4.4 Mitochondrial COI Gene in Population Genetics of U. cordatus

4.4.1 Diversity of the COI Gene

DNA sequences of a 600 bp fragment of COI were generated from 223 U. cordatus

individuals. High diversity was found for this mtDNA fragment, with a total of

132132 different haplotypes being observed. The haplotype diversity of 0.97 was

similar in all three populations (Upper Amazon, Lower Amazon and South Brazil).

However, the nucleotide diversity was very low, with a very small range from 0.0063

to 0.0065 (Table 8).

Similarly, high haplotic diversity and low nucleotide diversity have been described for

the COI gene in other crustaceans. Populations of the shrimp Haptosquilla pulchella

from the Indo-West Pacific showed the haplotype diversity varying from 0.67 to 1.0,

while the range of the nucleotide diversity was 0.0023 - 0.0442 in 24 different

populations (Barber et al., 2002). The haplotype diversity of COI in the European

green crab Carcinus maenas was found to vary from 0.56 to 0.96, while nucleotide

diversity ranged from 0.0033 to 0,010 (Roman and Palumbi, 2004).

The moderately higher AT content (62.9%) in the COI gene is not specific for U.

cordatus, as other COI genes in other crustacean show similar values, ranging from 59

to 62% (Cristescu et al., 2003). The high amount of transitions (83 out of 115

substitutions) is characteristic for the COI gene and is found in many crustacean

Discussion

57

species (Barber et al., 2002 B). In the current study, this value is almost equal in all

populations.

Considering all 132 different COI haplotypes of U. cordatus, a small number of four

haplotypes is shared among the three populations, and just 14 haplotypes occur in two

populations. However, of the 223 individual genotypes, 94 shared haplotypes

occurred in at least two different populations (Figure 11). This level of similarity can

be clearly evidenced by low �st values (Tables 7 and 10), as well as demonstrated in

the phylogenetic tree (Figure 12), where no phylogeographic structure is observed. It

is further supported by the fixation indexes among and within populations as

calculated by the AMOVA (Table 10).

In the AMOVA, all of the analyses with different population combinations show no

essential differences and structure between the populations. Here, �st values of 2% or

4% show that two randomly chosen individuals from two populations are equal in 98

or 96 out of 100 cases. This is defined in agreement with Hartl (1987) with less than

10 % as a very low structuring and high genetic exchange between the populations.

However, all of these low variations are highly significant and the lack of variation is

not due to the lack of resolution power of the marker because variability in all

populations together was always very high.

4.4.2 Population Dynamics of Ucides cordatus

All three populations (“Upper Amazon”, “Lower Amazon” and “South Brazil”), as

well the population as a whole, are showing high indexes of genetic and low

Discussion

58

nucleotide diversity (Table 8). This pattern of haplotypes, according to data of an

analysis of mitochondrial DNA in fishes (Grant & Bowen, 1998), can be interpreted

as a population that went through a bottleneck event in the past and recently is in an

expansion process. However, this conclusion is a direct consequence of the � value

and could be due to the peculiar mutation rate of the COI gene. So, studies using other

mitochondrial genes will be required to corroborate this hypothesis. Indeed, such

results need to be interpreted taking into consideration further population analyses,

since the detection of population expansion processes require powerful statistical

tests. As previously mentioned, the neutrality test deviation was negative and

significant, however the Fs values differed from D values in magnitude, being higher

in all populations as well as in the population as a whole (Table 8). This is due to the

fact that different tests of neutrality deviation are more or less precise than others (Fu,

1997). Fu`s Fs is one of the most powerful tests to detect population expansion, which

results in high negative values (Ramos-Onsins and Rozas, 2002). If both tests result in

a negative value, one of following possibilities of population events is confirmed:

first, a demographic expansion event, the effective population size is growing; second,

a background selection event, the elimination of deleterious mutations is segregating

in a population (Charlesworth et al., 1993), and third, a hitchhiking event, when a

favourable mutation arises, and increases to fixation, it gives a fortuitous advantage to

all the genes with which it was originally associated (Maynard Smith & Haigh, 1974).

The first two processes result in an excess of discrete haplotypes, while hitchhiking

does not. As numerous singletons were found in all three populations analyzed

(Figure 11), the hitchhiking event can be excluded (Fay and Wu, 2000; Barton, 2000).

Therefore, it becomes important to use further tests to differentiate between

population expansion events and background selection. However, to do this, it would

Discussion

59

be required to increase the number of loci analyzed in the U. cordatus genome,

because a demographic expansion phenomenon will result in an excess of rare

haplotypes in all loci, independent of the selection processes, respectively (Hahn et

al., 2002). However, in this study just the mitochondrial COI gene was analyzed and

different tests were applied to detect the process of a population expansion according

to the other processes that are expected for negative values of neutrality deviation.

The mismatch distribution of expected and observed pairwise differences within 232

individuals (Figure 13) revealed basically the same kind of curve, which is typical of a

population under the same kind of exponential population growth (Harpending &

Roger, 1991).

It was observed that in all three populations and in the population as a whole, values

smaller than 0.05 were obtained for the Harpending´s raggedness test (Rogers and

Harpending, 1991; Harpending, 1994) (Table 9), which characterizes populations

undergoing an expansion process.

An additional test to reject the population growth expansion hypothesis is based on

the sum of the square deviations (SSD), where P values (PSSD) inferior to 0.05

indicate a rejection of the population expansion hypothesis (Excoffier & Schneider,

1999). As can be seen in Table 9 in all three groups, and in the population as a whole,

the PSSD values were larger than 0.05

Finally, the comparison among the � values reflecting the state before (�0) and after

the expansion (�1) in each population and in the population as a whole, did not show

Discussion

60

overlapping values around the confidence intervals (Table 9). Therefore, the � values

are statistically different, which again favours the hypothesis of an expansion process.

This test is often not considered, but it is highly recommended to reject population

expansion models (Excoffier & Schneider, 1999). In summary, mtDNA analyses

suggest that U. cordatus from Brazilian mangroves are in the process of an expansion

of the population. It is important to notice that this result is observed for the three

regions considered in the present work. (Upper Amazon, Lower Amazon and South

Brazil). Furthermore, the reconstructed scenario depicted by COI sequences suggests

that this expansion took place between around 479,762 and 292,029 years ago.

4.4.2 Putative Pseudogenes in Ucides cordatus

One critical point in using mitochondrial DNA as a genetic marker is the fact that

those sequences may integrate into the nuclear DNA. These additional loci will be

subject to different mutational processes, as well as a different genetic code (Zhang

and Hewitt, 1996). To eliminate the possibility that in this study nuclear DNA was

analyzed the coding sequence characteristics were tested in all sequences with the

following results. No sequence showed any evidence of deletion or insertion of base

pairs in the alignment of the 600 nucleotides and the amplification products were

apparently of the same size, resulting in one single band (Figure 10). In the translated

sequence, no nonsense or stop codons were found. The blast search showed matches

with the COI genes of other crustaceans and the sequence aligned to these sequences

did not show any gaps to the major part of them. However, in the sequence of

Pachygrapsus crassipes (Accession number: AY952100) two gaps were found within

576 base pairs, which could possibly be due to a pseudogene sequence.

Discussion

61

According to Zhang and Hewitt (1996), Nguyen et al. (2002) and Schneider-

Broussard and Neigel (1997) most of the pseudogenes integrated in the nuclear

genome can fulfil one criterion of the characteristics of mitochondrial DNA cited

above, but not all of them. Therefore, in the present study it is assumed that the

mitochondrial gene coding for COI was correctly amplified and sequenced.

4.5 Comparison of Population Divergence from Mitochondrial COI DNA

and Nuclear Microsatellite Loci

Both genetic markers showed very high polymorphism calculated for the whole

population of U. cordatus, notably the PIC (polymorphism information content) of up

to 0.98 and the haplotype diversity of 0.97. Therefore, both methods seem to be

suitable for population analyses to detect genetic differences up to a fine scale of

variability.

The diversity of the microsatellites from different geographical locations exhibited the

same low structure as the mtDNA data exhibited, which indicates the existence of low

genetic subdivision, structure and high gene flow between the populations. The

significant averaged Fst value within four microsatellite loci between Bragança and

Paraná reflects the same low structure of the �st values between all the possible

comparisons between the three populations. However, it is still questionable if the

origin of this low genetic diversity between populations is caused by the same

mechanism or events, because different individuals from different locations were used

for the different population analyses. Besides, the different inheritance mode should

Discussion

62

be taken into account, which could influence the comparability of population

divergence (Scribner et al., 1994). Microsatellites are biparentally inherited and

undergo more frequent recombination. On the other hand, mitochondrial DNA is

maternally inherited and haploid.

Microsatellites are useful to detect recent population separations. Conversely, most

ancient separations are frequently masked by recombination and back mutation of

microsatellite alleles (DiRienzo et al., 1994). Mutations in microsatellite loci are more

likely to produce an allele that is already present in the population (and therefore go

undetected), unlike mtDNA, in which a mutation often results in a new haplotype

being formed and established in a population (Burg et al., 1999). In the present study

both kinds of genetic markers showed the same amount of population subdivision and

structure, however this kind of congruence is not common. For example ten fold �st

values were detected between populations of marine silverside fish (Odontesthes

argentinensis) and harbour seal (Arctocephalus gazelle) using mitochondrial DNA in

the control region regarding to Fst values of microsatellite loci (Burg et al., 1999;

Beheregaray and Sunnucks, 2001).

4.6 Marine dispersal of Ucides cordatus

The low genetic structure and high gene flow with migration rates of more than 20

individuals per generation between “Upper Amazon” and “Lower Amazon” as well as

between “Lower Amazon” and “South Brazil”, and more than 10 between “Upper

Amazon” and “South Brazil” (according to the COI data) suggest that the gene flow

between adjacent populations leads to a homogenization of the populations, as a

Discussion

63

consequence of larvae dispersal. If Nm is greater than 5 to10, then little geographic

genetic structure will be apparent. Such high values of gene flow are typically seen in

marine organisms with long distance larval exchange (Doherty et al., 1995; Palumbi,

1994). Interestingly, the genetic structure between “Upper Amazon” and “Lower

Amazon” is in the same area as between “Lower Amazon” and “South Brazil”.

Consequently, much effort should be concentrated on the question if the Amazon is an

effective barrier or could bring some kind of difficulties to larval flow between U.

cordatus populations.

A comparably weak genetic structure due to high larvae dispersal was also shown in

other marine organism at the coast of Brazil. Maggioni et al. (2003) showed that the

overall Fst value, according to six microsatellite loci of Litopenaus schmitti

(Decapoda, Penaeidae) on the Brazilian coast was 0.006, which leads to a high genetic

exchange over long distances. Brenden and Holland (2001) calculated migration

values of 6 to 36 Perna perna individuals per generation between north and south

Brazil with Fst values of 0.02.

This high dispersal is surprising because it is expected that the Southern Equatorial

Current, which splits into two branches, the North Brazil Current and the South Brazil

Current, could separate the northern and southern marine populations more strongly.

Otherwise in some cases expanding populations increase 10-100s of kilometers a year

(Palumbi 1996). For example the green crab Carcinus maenas has spread up the west

coast of the U.S. from an invasion originally detected in San Francisco Bay and

expanded its spread to the Pacific coast of Washington State in about a decade,

despite prevailing currents running from North to South (Geller, 1996).

Discussion

64

Concerning the recent larvae dispersal of U. cordatus between different locations on

the Brazilian coast, the genetic data have to be interpreted carefully as they are based

on calculations on an evolutionary time scale and address issues of long-term genetic

exchange across a species. Therefore, larvae dispersal over short time scales, like

some generations, can be more limited than the present data suggest. Botsford et al.

(1997) estimated a mean dispersal distance of about 50 km for crab larvae based on

their migration patterns and the correlations of recruitment variation along the western

coast of the U.S. A stepping stone model simulation of Palumbi (2003) showed that

even low levels of genetic differentiation are a signal of limited larval exchange.

Several marine populations of 10 km width were arrayed continuously along a

2000 km coastline. In this study, populations separated as far as 500 km apart were

monitored for genetic homogeneity by simulating gene flow and random genetic drift

at a single nuclear locus under a wide variety of dispersal regimes.

Even a structure so slight that only 1% of the genetic variation is distributed

geographically (e.g. Fst = 0.01) required this restricted larval dispersal. Certainly the

distribution in this model cannot be directly compared to the larvae dispersal of U.

cordatus at the Brazilian coast, because it is not known if this species distributes

according to a step stone model of isolation by distance or an island model. At the

same time these models cannot be properly tested because there are not enough

different geographical localities investigated in this study.

The linear character of the mangrove forest along the coast and the higher distance

between “Upper Amazon” and “South Brazil” would make the step stone model

Discussion

65

preferable to the island model. Otherwise, a correlation between geographic and

genetic distance is still not clear, because only few locations were analyzed including

the theoretical barrier of the Amazon between the “Upper Amazon” and “Lower

Amazon” locations. Additionally just one population was added to the current study

and data between “South Brazil” and “Lower Amazon” are still missing to create a

population model. Deeper studies under the aspect of detecting gene flow on a scale

of lower geographic distance using the genetic marker described in this study would

help to answer the questions of connectivity and dispersal.

For a suitable management of the U. cordatus resource, it can be assumed that in none

of the analyzed locations any kind of over exploitation was found. On the contrary,

the data suggest that within an evolutionary time scale the populations are expanding.

On the other hand, recent damages on the population could exist without being

detected, as they do not show changes in an ecological time scale. All local

populations show weak genetic differences and high exchanges even over thousands

of kilometres. Independent of whether or not this low structure is due to migration or

spatial expansion events, a management plan should cover large areas. Small-

protected areas could just have local effects since the larvae output would not help to

increase the whole population due to the high dilution factor and the high connectivity

of the different locations.

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