Molecular Ecology (2010) 19, 1147–1161 doi: 10.1111/j.1365-294X.2010.04553.x

History vs. habitat type: explaining the genetic structureof European nine-spined stickleback (Pungitiuspungitius) populations

TAKAHITO SHIKANO, YUKINORI SHIMADA, GABOR HERCZEG and JUHA MERILA

Ecological Genetics Research Unit, Department of Biosciences, University of Helsinki, PO Box 65, FI-00014, Helsinki, Finland

Corresponde

E-mail: takah

� 2010 Black

Abstract

The genetic structure of contemporary populations can be shaped by both their history

and current ecological conditions. We assessed the relative importance of postglacial

colonization history and habitat type in the patterns and degree of genetic diversity and

differentiation in northern European nine-spined sticklebacks (Pungitius pungitius),

using mitochondrial DNA (mtDNA) sequences and 12 nuclear microsatellite and

insertion ⁄ deletion loci. The mtDNA analyses identified – and microsatellite analyses

supported – the existence of two historically distinct lineages (eastern and western). The

analyses of nuclear loci among 51 European sites revealed clear historically influenced

and to minor degree habitat dependent, patterns of genetic diversity and differentiation.

While the effect of habitat type on the levels of genetic variation (coastal > freshwater)

and differentiation (freshwater > coastal) was clear, the levels of genetic variability and

differentiation in the freshwater sites were independent of habitat type (viz. river, lake

and pond). However, levels of genetic variability, together with estimates of historical

effective population sizes, decreased dramatically and linearly with increasing latitude.

These geographical patterns of genetic variability and differentiation suggest that the

contemporary genetic structure of freshwater nine-spined sticklebacks has been strongly

impacted by the founder events associated with postglacial colonization and less by

current ecological conditions (cf. habitat type). In general, the results highlight the strong

and persistent effects of postglacial colonization history on genetic structuring of

northern European fauna and provide an unparalleled example of latitudinal trends in

levels of genetic diversity.

Keywords: bottleneck, colonization history, founder effect, genetic diversity, phylogeography,

Pungitius

Received 30 March 2009; revision received 21 December 2009; accepted 22 December 2009

Introduction

Understanding the relative importance of historical and

ecological factors that influence the genetic structure of

natural populations is a topic central to contemporary

evolutionary biology (Vucetich & Waite 2003; Johansson

et al. 2006; Sagarin et al. 2006; Eckert et al. 2008). In the

Northern Hemisphere, the Pleistocene climate oscilla-

tions have had a large impact on the genetic structuring

nce: T. Shikano, Fax: 358 9 191 57694;

ito.shikano@helsinki.fi

well Publishing Ltd

of its fauna and flora (Hewitt 1996, 1999, 2004;

Bernatchez & Wilson 1998; Schmitt 2007). During the

last glacial maximum, most species were forced into

southern refugia from which they expanded north

when the climate warmed (Hewitt 1996). Since the north-

ward expansion from southern refugia was performed

by a limited number of individuals, postglacial coloni-

zation is expected to have lead to founder effects and

thereby also to the loss of genetic diversity in northern

populations (Hewitt 1996). Significant consequences of

postglacial colonization on population genetic structure

have been demonstrated in several organisms (e.g.

1148 T. SH IKANO ET AL.

Hewitt 1996; Merila et al. 1997; Schmitt & Seitz 2002;

Adams et al. 2006; Muller et al. 2008).

In addition to colonization history, contemporary

genetic population structure can be strongly influenced

by ecological factors through their effects on gene flow,

genetic drift and selection. For instance, habitat type is

known to be an important determinant of genetic diver-

sity within and among fish populations (Gyllensten

1985; Ward et al. 1994; DeWoody & Avise 2000). Open

marine habitats can sustain large effective population

sizes and facilitate gene flow among populations over

large geographic distances. In contrast, physical isola-

tion of freshwater habitats prevents gene flow between

localities and leads to substantial genetic subdivision

among populations. As a result, freshwater fish gener-

ally show higher degree of genetic differentiation than

marine fish (Gyllensten 1985; Ward et al. 1994). In addi-

tion, freshwater fish populations confined to particular

lakes or river drainages for long periods of time tend to

have lower levels of genetic variation than marine pop-

ulations due to their smaller effective population sizes

(e.g. Gyllensten 1985; Ward et al. 1994; Tonteri et al.

2007).

The nine-spined stickleback (Pungitius pungitius) is a

cold-water adapted fish having a circumpolar distribu-

tion in the Northern Hemisphere and is found in a

wide variety of habitats (Wootton 1976). In Europe,

nine-spined sticklebacks are distributed primarily in

freshwater environments in the north, but they occur

also in saline environments along coastal areas of the

Arctic Ocean, the White Sea and the Baltic Sea (Paepke

2001). As northern Europe was covered by the continen-

tal ice sheet until approximately 12 000 years ago, nine-

spined sticklebacks of this area should originate from

ancestors formerly resident in non-glaciated areas. In

Fennoscandia, postglacial colonization by terrestrial

organisms occurred typically from the east and ⁄ or from

the south (Hewitt 1999; Pamilo & Savolainen 1999), but

colonization patterns of fish fauna are more variable

(reviewed in Makhrov & Bolotov 2006).

In the case of the three-spined stickleback (Gasteros-

teus aculeatus) – a sister species to the nine-spined stick-

leback – freshwater habitats of northern Europe were

colonized by ancestral marine fish (Makinen et al. 2006;

Makinen & Merila 2008). As these stickleback species

exhibit similar ecological and morphological characteris-

tics (Bell & Foster 1994), comparison of their coloniza-

tion histories and population structures in the same

area is of particular interest. Fennoscandia is especially

interesting in this perspective since it was colonized by

these species relatively recently, most likely after the

last glacial maximum. Furthermore, in contrast to their

restricted occurrence in coastal habitats elsewhere in the

world (McPhail 1963; Takata et al. 1987; Paepke 2001),

nine-spined sticklebacks are common in coastal sites of

Fennoscandia. In eastern Asia, coastal nine-spined stick-

lebacks are genetically so divergent from freshwater

conspecifics that they can be considered as biologically

different species (Takata et al. 1987). Yet, little is known

about the evolutionary history and genetic population

structure of nine-spined sticklebacks in Europe (but see

Haglund et al. 1992).

The main aim of this study was to investigate the

phylogenetic relationships and genetic population struc-

ture of the nine-spined stickleback in northern Europe.

In particular, we were interested in assessing the rela-

tive importance of postglacial colonization history and

habitat type (viz. coastal, river, lake and pond) in the

levels of genetic variability within sites, as well as in

the degree of genetic differentiation among sites. We

hypothesized that if northern European nine-spined

sticklebacks have colonized from freshwater refugia

and experienced severe bottlenecks during this process

(cf. Hewitt 1996), strong geographically (e.g. latitudi-

nally) ordered effects can be found in contemporary

population genetic structure. For instance, the estimates

of genetic variability and historical effective population

size should decline towards the edge of colonization

range independent of habitat type. In contrast, if ecolog-

ical factors override historical factors, habitat-type

effects should be apparent in the patterns of genetic

variability and differentiation. For instance, one would

expect to see genetic variability to be highest in coastal

populations, lower in river and lake populations and

lowest in small and isolated pond populations. We

tested these expectations by analysing variation in

mitochondrial DNA (mtDNA) and 11 microsatellite and

one insertion ⁄ deletion loci in a large number (51) of

sites. Large-scale phylogeographic patterns were inves-

tigated using mtDNA cytochrome b sequence data from

25 sites, followed by analyses of population genetic

structure using nuclear loci. The results were contrasted

with those from ecologically and morphologically

similar three-spined sticklebacks inhabiting the same

area.

Materials and methods

Samples

A total of 1754 adult or juvenile fish were collected with

seine nets, minnow traps or electric fishing from 51

locations in Europe and one river in Japan during

2002–2008 (Fig. 1, Table S1, Supporting Information).

The average sample size per site was 34 (range = 3–84)

individuals (Table S1, Supporting Information). The fish

or fin clips were stored in 70–99% ethanol for DNA

extraction. Sampling sites were classified according to

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Fig. 1 Location of 51 European nine-spined stickleback sam-

pling sites. Inverted triangle: coastal, circle: lake, square: river,

triangle: pond. NF = northern Finland, MF = middle Finland,

MS = middle Sweden, SF = southern Finland, SN = southern

Norway, WE = Western Europe. For abbreviations of site iden-

tity codes, see Table S1 (Supporting information). Gray shading

indicates geographical distribution of nine-spined sticklebacks

in Europe according to Paepke (2001).

GENETICS OF STICKLEBACK POPULATIONS 1 14 9

their habitat type as coastal (n = 10), river (n = 8), lake

(n = 19) and pond (n = 14) sites (Table S1, Supporting

Information). For a fine scale analysis with nuclear

markers, European samples were categorized geograph-

ically into six groups: northern Finnish (NF), middle

Finnish (MF), middle Swedish (MS), southern Finnish

(SF), southern Norwegian (SN) and western European

(WE; Fig. 1) sites.

mtDNA sequencing and nuclear marker genotyping

Total DNA was extracted from fin clips with a silica-

fine based purification (Elphinstone et al. 2003) or a

phenol–chloroform method (Taggart et al. 1992) follow-

ing proteinase K digestion. A total of 96 individuals

from 25 sites covering a wide geographic range were

used for cytochrome b sequencing. Two slightly over-

lapping regions of cytochrome b gene were amplified

using primers L14724 (Kocher et al. 1989) and PP14959

(this study; 5¢-TGGTGGAGGAAMAGAAGGTG-3¢),as well as PP14896 (this study; 5¢-CTAACCC-

GATTCTTTGCCTT-3¢) and CB6Thr (Palumbi 1996).

As PCR amplification was not obtained for the latter

region in a few individuals, PP15469 (this study;

5¢-CTATTGCTGCTCCTGGGTAA-3¢) instead of CB6Thr

was used for them. The newly designed primers were

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developed based on conserved regions of the cyto-

chrome b sequences of Pungitius pungitius (Mattern

2004). PCR amplifications were carried out in 15 lL

reaction volumes consisting of 1 · PCR buffer (Bioline),

1.5 mM MgCl2, 0.25 mM dNTP (Finnzymes), 0.15 U

BIOTAQ DNA polymerase (Bioline), 5 pmol of each pri-

mer and approximately 20 ng of genomic DNA. The

reactions were performed as follows: an initial degener-

ation step at 95 �C for 2 min, followed by 30 s at 95 �C,

30 s at 52 �C and 30 s at 72 �C for 35 cycles with a final

extension at 72 �C for 10 min. PCR products were puri-

fied using exonuclease I (New England Biolabs) and

shrimp alkaline phosphatase (Roche) and directly

sequenced in both forward and reverse directions with

the same primers as those used in the PCRs. The

sequencing reactions were performed in 10 lL volumes

using the BigDye Terminator v1.1 Cycle Sequencing Kit

(Applied Biosystems) according to manufacture’s

instructions. Cycle sequencing products were purified

by the Montage SEQ96 Sequencing Reaction Cleaning

Kit (Millipore) and analysed on a MegaBACE 1000

automated sequencer (Amersham Biosciences).

Allelic variation in nuclear markers was asses-

sed using 11 microsatellite loci, Gac1125PBBE,

Gac4174PBBE, Gac7033PBBE (Largiader et al. 1999;

Makinen et al. 2007), Stn49, Stn96, Stn100, Stn130,

Stn163, Stn173, Stn196 and Stn198 (Peichel et al. 2001;

Makinen et al. 2007) and an insertion ⁄ deletion locus,

Stn380 (Colosimo et al. 2005). Each forward primer was

labelled with a fluorescent dye (FAM, HEX or TET) for

visualization of PCR products, and the 5¢-end of each

reverse primer was modified with a GTTT-tail to

enhance the 3¢-adenylation (Brownstein et al. 1996). The

12 loci were arranged in multiplex PCR panels with

non-overlapping size ranges in each dye. PCRs were

carried out using the Qiagen Multiplex PCR Kit (Qia-

gen) in 10 lL reaction volumes containing 1 · Qiagen

Multiplex PCR Master Mix, 0.5 · Q-Solution, 2 pmol of

each primer and 10–20 ng of template DNA. The reac-

tions for all loci were performed by the following cycle:

an initial activation step at 95 �C for 15 min, followed

by 30 s at 94 �C, 90 s at 53 �C and 60 s at 72 �C for 30

cycles with a final extension at 60 �C for 5 min. PCR

products were visualized with a MegaBACE 1000 auto-

mated sequencer (Amersham Biosciences) and their

sizes were determined with ET-ROX 550 size standard

(Amersham Biosciences). Alleles were scored using

Fragment Profiler 1.2 (Amersham Biosciences) with

visual inspection and manual corrections of alleles.

Data analyses of mtDNA

The two regions of cytochrome b gene sequenced were

aligned using MEGA 4 (Tamura et al. 2007) and combined

1150 T. SH IKANO ET AL.

to obtain a 1104 base pair (bp) sequence, which corre-

sponds to 96.8% of the gene. Sequences were deposited

in GenBank under accession numbers GU227740–

GU227783. Number of haplotypes, haplotype diversity

(h), average number of nucleotide differences (k) and

nucleotide diversity (p) were calculated using DnaSP

4.1 (Rozas et al. 2003). Phylogenetic analyses were

conducted using MrBayes 3.1.2 (Ronquist & Huelsen-

beck 2003). A MrBayes setting for the best fit model

(GTR + G) was selected by the hierarchical likelihood

ratio tests with MrModeltest 2.3 (Nylander 2004) in con-

junction with PAUP 4.0b10 (Swofford 2002). Markov

chains were run for 3 · 106 generations (the average SD

of split frequencies <0.01) with four chains starting

from a random tree. Sampling frequency was set at 100

generations and the first 7500 samples (25%) were

excluded as burn-in. The phylogenetic tree was rooted

using Japanese nine-spined sticklebacks, as they are

genetically divergent from European nine-spined stick-

lebacks (Haglund et al. 1992).

Data analyses of nuclear markers

Locus and population (sampling site) specific gene

diversities (HE, Nei 1987) were estimated using FSTAT

2.9.3 (Goudet 2001). Allelic richness was estimated

using a rarefaction procedure in HP-RARE 1.0 (Kalinowski

2005) with a rarefaction sample size of six genes. Com-

parison of the estimates of allelic richness with rarefac-

tion sample sizes of six and 20 genes using sites with

more than 10 individuals confirmed that estimates

based on different rarefaction sample sizes were virtu-

ally identical (r = 0.981), justifying the inclusion of sites

with small sample sizes into the analyses. The presence

of null alleles was tested using MICRO-CHECKER (Van Oo-

sterhout et al. 2004). Within population and locus spe-

cific FIS were estimated (10 000 permutations) for each

site to detect possible deviations from Hardy–Weinberg

equilibrium. A linkage disequilibrium test was per-

formed between all loci over all samples. The degree of

population differentiation was quantified using the

standardized variance in allele frequencies (FST) as esti-

mated by h (Weir & Cockerham 1984). Standard errors

of FST were obtained by jackknifing over loci and signif-

icance tests were performed by 1000 permutations. The

genetic parameters and significance tests were esti-

mated using FSTAT 2.9.3.

Genetic signatures of recent population size reduc-

tions were searched for by using the approach of Corn-

uet & Luikart (1996) with the two-phase model

(Di Rienzo et al. 1994), as implemented in BOTTLENECK

(Piry et al. 1999). The parameters were set to 90%

stepwise mutations and 10% multistep mutations with

a variance among multiple steps of 12, as recommended

by Piry et al. (1999). This analysis tests for a relative

heterozygote excess that is apparent for a few genera-

tions after a population bottleneck. The significance of

heterozygote excess was assessed by the Wilcoxon

signed rank test with 10 000 iterations. In addition, his-

torical effective population sizes and migration rates

were estimated using the coalescent-based maximum-

likelihood method implemented in MIGRATE 3.0.3 (Beerli

& Felsenstein 2001). Theta (h = 4Nel, where Ne is effec-

tive population size and l mutation rate) and the

migration parameter M (m ⁄ l, where m is migration

rate) were calculated simultaneously under a stepwise

mutation model with a Markov chain Monte Carlo

(MCMC) repetition of 20 short chains of 20 000 steps

and three long chains of 200 000 steps. FST-based esti-

mates were used as the starting parameters and the

burn-in was set to 10 000. We applied the Gelman’s

convergence criterion to extend the long chains until

the criterion was satisfied. To ensure convergence, we

repeated the analysis twice and confirmed that results

were consistent between independent runs. The analyses

were performed within the six geographically catego-

rized areas (Fig. 1, Table S1, Supporting Information)

to minimize the effects of ‘ghost’ populations (Beerli

2004). Since no significant differences in the migration

parameter M were observed among freshwater habitat

types (river, lake and pond) or between coastal-to-fresh-

water and freshwater-to-coastal sites (ANOVA or paired

t-tests, P > 0.05), we combined the data and compared

the estimates within freshwater or coastal sites, as well

as among them in the six areas (cf. Fig. 1). We also note

that since three loci (Stn49, Stn198 and Stn380) did not

follow a stepwise mutation pattern due to an insertion

of 1 bp variation, these loci were excluded from the

analyses conducted with BOTTLENECK and MIGRATE.

Hierarchical genetic structuring was analysed by

assessing the relative contribution of among group,

among site and within site components for partition of

total molecular variance (AMOVA, Excoffier et al. 1992)

using Arlequin 3.11 (Excoffier et al. 2005). Significances

of different hierarchical levels were tested with 1000

permutations. The contributions of mtDNA lineage (see

‘Results’), habitat type (Table S1, Supporting Informa-

tion) and geographical area (Table S1, Supporting

Information) were analysed in all European sites and

also separately for all European freshwater sites.

Genetic relationships among sites were investigated

by using DA distances (Nei et al. 1983), which have

proven to be useful for reconstructing phylogenies

(Takezaki & Nei 1996). A neighbour-joining (NJ) tree

constructed from the DA matrix was used to visualize

the relationships by bootstrapping (1000 replicates)

across loci to test the stability of the tree-branching

pattern using Populations 1.2 (Langella 2002). Japanese

� 2010 Blackwell Publishing Ltd

GENETICS OF STICKLEBACK POPULATIONS 1 15 1

nine-spined sticklebacks were used as the outgroup. In

addition to a NJ tree, the pattern of population differen-

tiation was investigated using a two-dimensional

scaling plot of DA distances with SPSS 13.0 (SPSS Inc.).

To further evaluate the genetic relationships, allele

frequencies were subjected to principal component

analysis (PCA) based on the correlation matrix of allele

frequencies between sites. PCA was performed using

PCA-GEN 1.2 (www2.unil.ch/popgen/softwares/pca-

gen.htm) with 10 000 randomizations. We also applied

a Bayesian approach for population structure estimation

using STRUCTURE 2.2 (Pritchard et al. 2000). Assuming

that each individual comes from one of the K popula-

tions, a no-admixture model of correlated allele fre-

quencies was run with 50 000 burn-in length periods

and 100 000 MCMC repetitions, with values of K = 2–20

and five parallel chains for each K. While DK (Evanno

et al. 2005) has been suggested to be useful to deter-

mine K, a clear peak of DK was not found in our analy-

ses. As the log likelihood reached the maximum at

K = 8 and the variance increased at K ‡ 9 (data not

shown), we used K = 8 in the further analyses.

Sequential Bonferroni corrections (Rice 1989) were

applied for all multiple comparisons to minimize type I

errors. Only an infinite-allele model was used for popu-

lation differentiation and phylogeny analyses, as this

model is considered more reliable than a stepwise

mutation model for phylogenetic analyses of bottlenec-

ked populations (as in our case; see below; Takezaki &

Nei 1996; Tomiuk et al. 1998). We also note that there

were no significant differences in observed allele num-

ber, allelic richness, heterozygosity and FST between

microsatellite and insertion ⁄ deletion loci (Mann–Whitney

U-tests, P > 0.05 in all comparisons). In addition, inclu-

sion or exclusion of the insertion ⁄ deletion locus did not

qualitatively affect neither population comparisons nor

phylogenetic relationships (data not shown). Hence,

microsatellite and insertion ⁄ deletion data were combined

for population comparisons and phylogenetic analyses.

Geographic trend tests at nuclear markers

The impact of postglacial population expansion on

genetic variation and differentiation in nuclear markers

was investigated by inspecting patterns in these mea-

sures, in respect to latitude and longitude, within the

lineages identified by cytochrome b sequences and

nuclear markers (see ‘Results’). These analyses were

performed separately using data from (i) all sites; and

(ii) freshwater sites, as high rates of gene flow ⁄ migra-

tion were expected among the coastal sites (see

‘Results’).

A rapid postglacial population expansion would be

expected to appear as a negative trend in diversity

� 2010 Blackwell Publishing Ltd

measures towards the direction of the expansion (He-

witt 1996, 1999). This was tested by regressing intra-

population genetic variability measures (allelic richness

and heterozygosity) against latitude and longitude.

Prior to this test, the effects of different habitat types on

levels of genetic variation were evaluated, since current

levels of genetic variability can also be affected by

habitat type if they differ systematically in their effective

population sizes. This was done by using general linear

models (GLMs) where allelic richness or heterozygosity

was treated as a dependent variable, lineage and habitat

type as factors and latitude and longitude as covariates.

Isolation by distance was tested by correlating the

genetic distance measures (FST and DA) with geographic

distances between sites. To investigate population

expansion patterns, we evaluated latitudinal and longi-

tudinal trends in different genetic differentiation param-

eters (FST, DA, dimensional measures of DA and

principal component scores). A stronger association

with latitudinal than longitudinal distances would be

expected if a population expansion trend is in a latitu-

dinal direction (e.g. northward expansion) and vice

versa. This trend was tested by using correlations

between pairwise matrices of FST or DA and latitudinal

or longitudinal differences among sites. To further eval-

uate genetic differentiation patterns, the dimensional

measures of DA or principal component scores were

correlated with latitudinal and longitudinal coordinates.

Statistical significance of (Pearson) correlations was

evaluated by Mantel tests using Isolde (in Genepop,

Rousset 2008) with 1000 permutations in matrix correla-

tions.

Results

Mitochondrial DNA phylogeny

The 1104 bp fragment of cytochrome b contained 50

polymorphic sites defining 39 haplotypes in the 90

European individuals sequenced (haplotype diver-

sity = 0.890; Table S2, Supporting Information). The

overall nucleotide diversity (p) and average number of

nucleotide differences (k) were 0.0051 and 5.637, respec-

tively. The most common haplotype (E3) was found in

29 individuals and widely distributed in Fennoscandia

(14 out of 20 sites; Table S1, Supporting Information).

The Bayesian phylogeny was constructed using the

39 European haplotypes and rooted by the five Japanese

haplotypes identified in a river site. The European

mtDNA haplotypes clustered into distinct eastern

(E1–27, E39) and western (E28–38) lineages supported

by a high posterior probability (1.00; Fig. 2). The east-

ern lineage consists of all the haplotypes collected in

the Fennoscandian (NF, MF, MS and SF) sites except for

J1J2

J3J4

J5E36

E34E31

E33E32

E28E35

E29E30

E37E38

E24E12

E22E8

E19E18E2

E1E10

E9E15E14

E13E27E26E25E17E16

E21E6E5E20E7

E11E39

E4E23

E3

0.1

1.00

1.00

1.00

1.00

0.98

Westernlineage

Easternlineage

JapanFig. 2 Bayesian phylogeny of 39 cyto-

chrome b haplotypes in European

nine-spined sticklebacks. Posterior prob-

abilities >0.95 are indicated.

1152 T. SH IKANO ET AL.

the SN sites. This lineage also includes the haplotype

(E39) found at a Polish site (PL-PAS). Accordingly, the

most common haplotype (E3) was shared by 44.6% of

the individuals in the eastern lineage. The western line-

age consists of all the haplotypes found in the WE and

SN sites. Within this lineage, two subgroups of haplo-

types were identified with a high posterior probability

(1.00), one of which consists of the haplotypes (E37–38)

found at a French site (FR-MON; Fig. 2).

Within each main lineage, haplotype diversity was

lower in the eastern lineage (h = 0.799, SD = 0.052) than

in the western lineage (h = 0.923, SD = 0.025). Similarly,

the eastern lineage exhibited lower nucleotide diversity

(p = 0.00147 vs. 0.00428) and k (k = 1.620 vs. 4.727) as

compared to the western lineage. The same trend was

obtained even if the French samples were excluded

from the analyses of the western lineage (h = 0.908,

p = 0.00270, k = 2.980).

Based on these results (see also Fig. 4), samples from

NF, MF, MS and SF sites were treated as the eastern

lineage, and those from SN and WE sites as the western

lineage for the remainder of this paper.

Genetic variability at nuclear loci

All nuclear loci were amplified successfully in all

sites except in PL-PAS where Gac4174PBBE and

Gac7033PBBE completely failed even after retrials.

Hence, this site was excluded from further analyses.

A total of 280 alleles were observed in European

samples across the 12 loci with an average of 23.3

alleles per locus (range = 7–90). No linkage disequilib-

rium was detected between the 12 loci. MICRO-CHECKER

analyses did not indicate the presence of null alleles,

with the possible exceptions of the locus Stn163 in the

RU-LEV, the locus Gac4174PBBE in the SE-NAV and

the loci Stn100, Stn130, Stn163 and Stn198 in the

NO-OXN. Coupled with the indication of possible null

alleles at multiple loci, a relatively high FIS (0.123) in

the NO-OXN suggested the effect of inbreeding rather

than null alleles. There was no evidence for deviations

from Hardy-Weinberg equilibrium at any locus in any

of the sites. BOTTLENECK tests did not reveal any evidence

for recent population size bottlenecks in any of the sites.

In addition, FIS values were homogenous across differ-

ent habitat types (Table S1, Supporting Information).

Levels of genetic variability – whether measured by

allelic richness or expected heterozygosity – varied sig-

nificantly among sites (Table S1, Supporting Informa-

tion). Allelic richness (±SE) within sites varied from

1.01 (±0.01) to 2.94 (±0.28) and heterozygosity from

0.004 (±0.003) to 0.604 (±0.063). Genetic variability was

very low and close to zero in the FI-PYO (Table S1,

Supporting Information). On average, the freshwater

sites exhibited significantly lower allelic richness (1.96

vs. 2.81) and heterozygosities (0.332 vs. 0.578) than the

coastal sites (Mann–Whitney U-tests, P < 0.001). In the

freshwater sites, genetic variation was generally lower

in northern and mid-Fennoscandia as compared to the

southern areas, although relatively high levels of

genetic variation were observed also in the three Rus-

sian pond sites (RU-MAS, BOL and KRU) and the

Swedish lake site (SE-KRO), which are all closely

located to the sea (Fig. 1, Table S1, Supporting Infor-

mation). A hierarchical analysis of genetic variation

indicated significant effects of habitat type, latitude and

longitude on both allelic richness and heterozygosity

(Table 1). However, once the analysis was restricted to

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0.1

0.2

0.3

0.4

0.5

0.6

45 50 55 60 65 70

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1.5

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2.5

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45 50 55 60 65 70Latitude (°N)

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Latitude (°N)

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GENETICS OF STICKLEBACK POPULATIONS 1 15 3

the freshwater sites, the effect of habitat type was no

longer significant (Table 1). Therefore, the effect of hab-

itat type appears to be strongly influenced by the differ-

ence between coastal and freshwater sites.

In the eastern lineage, both allelic richness (r2 = 0.440,

n = 42, P < 0.001) and heterozygosity (r2 = 0.455, n = 42,

P < 0.001) decreased with increasing latitude (Fig. 3A

and B). These trends were significant even when the

analyses was restricted to the freshwater sites (allelic

richness, r2 = 0.359, n = 32, P < 0.001; heterozygosity,

r2 = 0.358, n = 32, P < 0.001). In contrast, no significant

longitudinal trends were found among all sites or

among the freshwater sites of this lineage (P > 0.05). In

the western lineage, allelic richness and heterozygosity

were unrelated to latitude or longitude (P > 0.05;

Fig. 3A and B).

The estimates of historical effective population size as

represented by theta varied from 0.17 to 11.35 among the

sites and relatively high values were observed in south-

western Europe (area WE; Table S1, Supporting Informa-

tion). Assuming a microsatellite mutation rate of 5 · 10)4

(Estoup & Angers 1998; Lippe et al. 2006), these corre-

spond to effective population sizes of Ne = 86–5674. A

hierarchical analysis of theta indicated significant effects

of lineage and latitude (Table 1). Within lineages, theta

decreased significantly with increasing latitude (Fig. 3C;

eastern lineage, r2 = 0.247, n = 42, P < 0.001; western

lineage, r2 = 0.607, n = 8, P < 0.05), while no significant

correlation was observed between longitude and theta

(P > 0.05). The same trends were obtained in the analyses

of freshwater sites of the eastern lineage (latitude,

r2 = 0.311, n = 32, P < 0.001; longitude, P > 0.05).

The effects of geographic area and habitat type on the

estimates of the migration parameter M were significant

(GLMs, P < 0.001). In the comparison of freshwater

sites, the average value was relatively high in the NF,

SF and SN sites as compared to other areas (Table S3,

Supporting Information). In the MS and SF sites, the

estimate was higher among coastal sites as compared to

that among freshwater sites (Table S3, Supporting

Information).

0

2

45 50 55 60 65 70Latitude (°N)

Fig. 3 Relationship between latitude and allelic richness (a),

heterozygosity (b) or theta (c) in European nine-spined stickle-

backs. Inverted triangle: coastal, circle: lake, square: river,

triangle: pond. Eastern lineage (closed symbols), r2 = 0.440,

n = 42, P < 0.001 (A), r2 = 0.455, n = 42, P < 0.001 (B),

r2 = 0.247, n = 42, P < 0.001 (C); western lineage (open sym-

bols), r2 = 0.213, n = 8, P = 0.250 (A), r2 = 0.146, n = 8,

P = 0.350 (B), r2 = 0.607, n = 8, P = 0.023 (C).

Genetic differentiation at nuclear loci

The degree of genetic differentiation among all Euro-

pean sites was very high with an average FST = 0.415

(SE = 0.031, P < 0.001). The degree of differentiation

among the coastal sites was low (FST = 0.038 ± 0.009,

P < 0.001), especially within the Baltic Sea (FST = 0.011

± 0.003, P < 0.001). In contrast, freshwater sites were

more differentiated than coastal sites and the degree of

genetic differentiation was high in Europe (FST = 0.492

± 0.034, P < 0.001) and also within the eastern lineage

(FST = 0.494 ± 0.035, P < 0.001).

� 2010 Blackwell Publishing Ltd

JP-FOBDK-GUD

UK-HAR

BE-LEUFR-MON

NO-ORRNO-OXN

NO-ENGNO-AVE

FI-KOTSE-LIL

SE-TARSE-BOL

FI-KIV

FI-HEL

SE-FORFI-TUR

FI-PYH

FI-MONEE-PUR

SE-KROFI-MAT

FI-SAI

RU-ONE

RU-LEVRU-BOL

RU-MASRU-KRU

SE-L5

SE-STUSE-L2SE-L1

SE-HANFI-POR

SE-NAVSE-ABB

SE-BYN

SE-SKA

FI-PYOFI-KRK

FI-RYTFI-ONK

FI-RAHNO-FIN

FI-PULFI-TUOFI-PAA

FI-KEVFI-KEN

Westernlineage

Easternlineage

NO-PORNO-ROP

0.1 (DA)

96

74

93

59

54

94

55

53

x Fig. 4 A neighbour-joining tree based

on nuclear markers for 50 European

nine-spined stickleback sites. Inverted

triangle: coastal, circle: lake, square:

river, triangle: pond. Closed symbols =

eastern lineage, open symbols = western

lineage, x = Japanese sample. Bootstrap

supports >50% are indicated.

Table 1 Hierarchical analysis of genetic variation and theta in European nine-spined sticklebacks

Estimate Source

All sites (n = 50) Freshwater sites (n = 40)

Type III SS df MS F P Type III SS df MS F P

Allelic richness

Lineage 0.443 1 0.443 3.074 0.087 0.434 1 0.434 2.626 0.114

Habitat type 5.357 3 1.786 12.381 0.000 0.894 2 0.447 2.704 0.081

Latitude 1.836 1 1.836 12.730 0.001 2.116 1 2.116 12.792 0.001

Longitude 1.265 1 1.265 8.774 0.005 1.504 1 1.504 9.096 0.005

Error 6.202 43 0.144 5.623 34 0.165

Expected heterozygosity

Lineage 0.033 1 0.033 2.512 0.120 0.035 1 0.035 2.283 0.140

Habitat type 0.437 3 0.146 11.034 0.000 0.085 2 0.042 2.738 0.079

Latitude 0.189 1 0.189 14.309 0.000 0.207 1 0.207 13.335 0.001

Longitude 0.096 1 0.096 7.260 0.010 0.119 1 0.119 7.665 0.009

Error 0.568 43 0.013 0.527 34 0.016

Theta (4Nel)

Lineage 12.025 1 12.025 5.490 0.024 6.958 1 6.958 3.881 0.057

Habitat type 18.246 3 6.082 2.777 0.053 0.684 2 0.342 0.191 0.827

Latitude 22.809 1 22.809 10.413 0.002 32.681 1 32.681 18.227 0.000

Longitude 8.241 1 8.241 3.762 0.059 8.258 1 8.258 4.606 0.039

Error 94.185 43 2.190 60.962 34 1.793

1154 T. SH IKANO ET AL.

AMOVA analyses revealed that 49.1–58.0% of the total

genetic variance resided within sites (Table 2). A signif-

icant proportion of the variance resided between lin-

eages (19.6%, P < 0.001) or among geographical areas

(11.1%, P < 0.001), but habitat type explained only a

very low proportion of the variance (3.7%, P < 0.001).

When the analysis was restricted to freshwater sites,

the contribution of habitat type was not significant

� 2010 Blackwell Publishing Ltd

Table 2 Hierarchical analysis of genetic divergence in European nine-spined sticklebacks

Group

No. of groups Among groups Among sites Within sites

(sites) % FCT P % FST P % FSC P

Lineage 2 (50) 19.6 0.196 *** 31.3 0.510 *** 49.1 0.390 ***

Eastern lineage 1 (42) 40.7 0.407 *** 59.3 0.593

Western lineage 1 (8) 24.0 0.240 *** 76.0 0.760

Geography 7 (50) 11.1 0.111 *** 31.3 0.427 *** 57.3 0.355 ***

NF 1 (13) 51.2 0.512 *** 48.8 0.488

MF 1 (9) 44.0 0.440 *** 56.0 0.560

MS 1 (11) 39.7 0.397 *** 60.3 0.603

SF 1 (9) 7.0 0.070 *** 93.0 0.930

SN 1 (4) 12.5 0.125 *** 87.5 0.875

WE 1 (4) 34.9 0.349 *** 65.1 0.651

Habitat type (all) 4 (50) 3.7 0.037 *** 38.3 0.420 *** 58.0 0.398 ***

Coastal 1 (10) 3.8 0.038 *** 96.2 0.962

River 1 (7) 25.5 0.255 *** 74.5 0.745

Lake 1 (19) 44.8 0.448 *** 55.2 0.552

Pond 1 (14) 58.3 0.583 *** 41.7 0.417

Habitat type (FW) 3 (40) 1.7 0.017 NS 47.7 0.494 *** 50.6 0.486 ***

For abbreviations of geographic regions, see Fig. 1. FW, freshwater sites. NS, not significant; *** P < 0.001.

GENETICS OF STICKLEBACK POPULATIONS 1 15 5

(Table 2). Within lineages, an average FST was higher in

the eastern lineage (0.407) than in the western lineage

(0.240; Table 2). Similarly, the degree of genetic differ-

entiation varied among geographical areas (Table 2).

An average FST was relatively low in southern

Fennoscandia (0.070–0.125), but higher in the mid-

latitude and northern areas (0.397–0.512).

In the NJ tree obtained from DA distances, the root

for the European samples was located in the branch

separating the western and eastern lineages identified

by the mtDNA analysis (Fig. 4). Although bootstrap

support for basal nodes was low, the topology of tree

suggests clustering of sites within the two main lineages

roughly according to their geographic proximity. The

samples of SN sites clustered together with those of WE

sites belonging to the same lineage (Fig. 4). In the east-

ern lineage, two main branches were apparent. One

included the Baltic Sea sites and freshwater sites from

southern and mid parts of Fennoscandia, the other

included the White Sea and mid- and northern

Fennoscandian freshwater sites (Fig. 4). Within the

eastern lineage, the branches including Finnish and

Swedish pond and lake sites exhibited higher degrees

of genetic divergence (cf. branch lengths) than others

(Fig. 4). In a dimensional analysis of DA distances, the

dimension one clearly discriminated the two lineages

(Fig. S1A, Supporting Information). Rather than clusters,

continuous variation along the respective dimensions

was observed among sites within each lineage

(Fig. S1A, Supporting Information).

In a principal component analysis, the first two prin-

cipal components were significant (P < 0.05) and

� 2010 Blackwell Publishing Ltd

explained 35.1% of the variation in allele frequencies

(Fig. S1B, Supporting Information). A combination of

the two axes revealed three clusters: one cluster for the

western lineage and two clusters for the eastern lineage

(Fig. S1B, Supporting Information). In the latter, one

corresponds to part of the NF sites and the other con-

sists of other Fennoscandian sites.

The Bayesian analysis with the program STRUCTURE

assigned the majority of individuals from each site to

the same cluster, except for the FI-SAI, in which indi-

viduals were assigned mainly to two clusters (Table S1,

Supporting Information). While the individuals of the

western lineage were assigned to a single cluster, those

of the eastern lineage were divided into seven clusters

(Table S1, Supporting Information). One large cluster

consisted of individuals from most SF sites and several

MS sites. Each of other clusters consisted of individuals

from geographically close sites. For instance, one cluster

contained individuals exclusively from some MF sites.

Likewise, two clusters consisted of individuals from

most NF sites according to their geographic proximity.

In coastal sites, the individuals of the Baltic Sea were

assigned to a single cluster whereas those of the White

Sea were assigned to a different cluster.

Geographic trends in genetic differentiation at nuclearloci

A significant isolation by distance effect was found in

the western lineage (FST, r2 = 0.409, n = 28, P = 0.020;

DA, r2 = 0.636, n = 28, P = 0.001; Table 3). In the eastern

lineage, DA distances were significantly, but weakly,

Table 3 Association between genetic differentiation measures

and geographic variables. Distance refers to geographic

distances separating pairs of sites, latitude and longitude to

coordinate differences separating pairs of sites (FST and DA) or

respective coordinates (DM and PC). Values refer Pearson cor-

relation coefficients and number of comparisons is given in

parentheses. Significance levels determined with Mantel’s test

(FST and DA) or with standard statistical tests (DM and PC).

Comparison

Eastern lineage Western

lineage

All Freshwater All

Distance

FST 0.000 (861) 0.013 (496) 0.409 (28)*

DA 0.090 (861)*** 0.044 (496) 0.636 (28)**

Latitude

FST 0.001 (861) 0.012 (496) 0.205 (28)

DA 0.098 (861)*** 0.039 (496)* 0.382 (28)*

DM1 0.530 (42)*** 0.424 (32)*** 0.519 (8)*

DM2 0.000 (42) 0.013 (32) 0.818 (8)**

PC1 0.565 (42)*** 0.474 (32)*** 0.655 (8)*

PC2 0.016 (42) 0.069 (32) 0.323 (8)

Longitude

FST 0.001 (861) 0.000 (496) 0.218 (28)*

DA 0.008 (861) 0.007 (496) 0.227 (28)*

DM1 0.100 (42)* 0.043 (32) 0.442 (8)

DM2 0.121 (42)* 0.220 (32)** 0.170 (8)

PC1 0.151 (42)* 0.087 (32) 0.224 (8)

PC2 0.040 (42) 0.087 (32) 0.006 (8)

DM, dimentional measure of DA; PC, principal component

score.

* P < 0.05, P < 0.01, *** P < 0.001.

1156 T. SH IKANO ET AL.

correlated with geographic distances across all sites

(r2 = 0.090, n = 861, P < 0.001), but no isolation by dis-

tance was identified when the analysis was restricted to

the freshwater sites (P > 0.05).

Geographical trends in genetic differentiation were

better explained in terms of latitude than longitude

(Table 3). For instance, DA distances correlated signifi-

cantly with latitudinal differences between sites in the

eastern lineage (r2 = 0.098, n = 861, P < 0.001), with no

significant associations to longitudinal differences

(P > 0.05). The same trend was observed among the

freshwater sites of this lineage (Table 3). Moreover,

geographical trend tests using the dimensional mea-

sures of DA (DM) and the principal component scores

(PC) revealed that DM1 and PC1 exhibited strong latitu-

dinal clines across all sites (DM1, r2 = 0.530, n = 42,

P < 0.001; PC1, r2 = 0.565, n = 42, P < 0.001) as well as

across the freshwater sites (DM1, r2 = 0.424, n = 32,

P < 0.001; PC1, r2 = 0.474, n = 32, P < 0.001). In contrast,

no or weak associations were detected in respect to lon-

gitude (Table 3). Similarly, the geographic patterns of

population differentiation depended more on latitude

than longitude in the western lineage (Table 3).

Discussion

Our results suggest a strong historical component to the

patterns of genetic variation within and among north-

ern European nine-spined stickleback sites. These his-

torical effects appear to override the impact of

contemporary ecological factors – as reflected in habitat

effects – as determinants of genetic variability patterns.

Firstly, two divergent groups or clades of populations

(western and eastern lineages) were found. Secondly,

although there was a clear effect of habitat type on

genetic diversity and the degree of genetic differentia-

tion within the eastern lineage, this effect was confined

to the difference between coastal and freshwater sites.

However, the levels of genetic variation within the

freshwater sites were independent of habitat type, but

strongly impacted by historical factors as reflected in

the significant effects of latitude on the levels of genetic

variability within sites. The strong decline in the levels

of genetic diversity within sites as a function of latitude

in the eastern lineage suggests that the Fennoscandian

nine-spined sticklebacks have suffered from the reduc-

tion of genetic variation due to founder effects associ-

ated with the postglacial recolonization process. While

similar examples of latitudinal decline in the levels of

genetic variability are available from several terrestrial

species (e.g. Hewitt 1996; Merila et al. 1997; Palo et al.

2004), we are not aware that this clear pattern would

have been described earlier for any freshwater taxa. The

strong influence of population history on genetic vari-

ability highlights the long lasting influence of Pleisto-

cene events on genetic structuring of northern

European fauna (Hewitt 2000). In what follows, we will

discuss these and related issues in light of the results

obtained.

Phylogeography

The mtDNA analyses identified two major lineages of

nine-spined sticklebacks in northern Europe: one occu-

pying the eastern and northern parts of Fennoscandia

and the other occurring in southern Norway and south-

western continental Europe. The observed geographic

distribution of the two distinct lineages is similar to that

typically found among terrestrial animal and plant taxa

(reviewed in Hewitt 2000). While the recolonization

routes of different lineages of fishes to Fennoscandia

are more heterogeneous and complex than those of ter-

restrial organisms (reviewed in Makhrov & Bolotov

2006), a similar pattern to that found here has been

reported for European grayling (Thymallus thymallus;

Koskinen et al. 2000). The deep divergence and largely

non-overlapping distributions of the two lineages

suggest distinct postglacial colonization histories and

� 2010 Blackwell Publishing Ltd

GENETICS OF STICKLEBACK POPULATIONS 1 15 7

two postglacial dispersal routes into Fennoscandia. The

analyses of nuclear loci supported the inference based

on mtDNA data, but the resolution they provided was

low, perhaps due to strong bottleneck effects (Takezaki

& Nei 1996; see also below). A notable finding in our

mtDNA analyses was that the genetic diversity in the

eastern lineage was much lower as compared to the

western lineage. The fact that one haplotype (E3) was

widely distributed throughout the eastern lineage sug-

gests that the individuals of the eastern lineage share a

common ancestry. Nevertheless, given the sparse sam-

pling in the western Fennoscandia, further sampling

and studies are required to assess levels of genetic

diversity in the western lineage.

Genetic structure and colonization pattern

The analyses of nuclear loci provided further

insights into the population history and structure of

Fennoscandian nine-spined sticklebacks. The most

interesting finding was that genetic variation in the

eastern lineage decreased dramatically and systemati-

cally with increasing latitude independently of habitat

type. The pattern is in agreement with the theoretical

expectation that northward expansion from southern

refugia disposes populations to serial founder effects

leading to gradual loss of genetic variation towards the

north (Hewitt 1996; Austerlitz et al. 1997). Northward

reduction in genetic variation has been also demon-

strated in some other – mainly terrestrial – organisms

in Fennoscandia (Merila et al. 1996, 1997; Palo et al.

2004; Johansson et al. 2006; Tollefsrud et al. 2009) and

elsewhere (Schmitt & Seitz 2002; Gysels et al. 2004;

Adams et al. 2006; Rowe & Beebee 2007). Despite their

low genetic variability, no consistent and significant

signatures of transient population bottlenecks were

identified neither in the case of (small) pond sites, nor

in the case of mid- and northern Fennoscandia sites. In

fact, according to our own observations, nine-spined

sticklebacks are abundant and occur in high densities in

these sites. The interpretation that the northward reduc-

tion of genetic variability is caused by historical rather

than contemporary factors was further supported by

the fact that the estimates of historical effective popula-

tion sizes decreased – parallel to within population

genetic variability – with increasing latitude, indepen-

dent of habitat type. Hence, the observed patterns of

latitudinally ordered genetic diversity are difficult to

understand other than in the light of sequential reduc-

tion of genetic variability during the recolonization

process that has taken place from south to north.

Despite a recent origin of Fennoscandian nine-spined

sticklebacks, the degree of genetic differentiation within

the eastern lineage was very high and estimated FST

� 2010 Blackwell Publishing Ltd

values (freshwater average FST = 0.49; maximum FST =

0.97) are among the highest reported for any fish

species so far (e.g. Hanfling et al. 2002; Jacobsen et al.

2005; Vonlanthen et al. 2007; Barson et al. 2009). In

particular, strong population subdivision was found in

mid- and northern Fennoscandian freshwater sites, as

expected in bottlenecked populations due to founder

effects (Chakraborty & Nei 1977; Le & Kremer 1998;

Hedrick 1999). In line with this trend, a Bayesian clus-

tering analysis assigned the individuals of mid- and

northern Fennoscandia to several different clusters,

while most individuals from southern Fennoscandia

were included in a single cluster. These align with the

observed lack of isolation by distance in eastern lineage

to support the resolution that these populations have

been subject to strong genetic drift in the past (Hutchison

& Templeton 1999; Koizumi et al. 2006). Hence, the

facts reviewed above suggest that the nine-spined stick-

lebacks of the eastern lineage have colonized Fenno-

scandia from the south and have become genetically

fragmented due to founder events associated with this

colonization process.

The levels of genetic variability in all sites belonging

to the western lineage were relatively high and compa-

rable to that in the most southern Fennoscandian sites

belonging to the eastern lineage. No geographic trends

in levels of genetic variability were found in western

lineage, but data was limited both in terms of number

of sites and their coverage. Hence, more detailed infer-

ence about history and variability of the western lineage

should await denser sampling and samples from south-

ern Sweden and mid-Norway would be particularly

interesting for investigations to come: especially in the

view that the estimated historical effective population

sizes were relatively large for the French and Belgian

sites, which were non-glaciated during the Pleistocene

glaciations. Hence, they may represent refugial areas of

the western lineage.

Differentiation in coastal vs. freshwater habitats

The degree of genetic differentiation among freshwater

sites exceeded that among coastal sites, conforming to

the typical pattern among fishes (Gyllensten 1985; Ward

et al. 1994; DeWoody & Avise 2000). Higher rates of

gene flow or larger effective population sizes in marine

environments, are possible explanations for this differ-

ence. In fact, historical migration rates were suggested

to be higher among the coastal than among the fresh-

water sites, but historical effective population sizes

were suggested to be similar in both habitat types.

Interestingly, the degree of genetic differentiation

between the Baltic and the White Sea sites was

relatively low (FST = 0.122), but still much higher than

1158 T. SH IKANO ET AL.

that among the Baltic Sea sites (FST = 0.011). The low

degree of genetic differentiation between the Baltic and

the White Sea sites in both nuclear and mtDNA data

suggests that the divergence is of postglacial origin,

rather than due to colonization from different refugial

areas.

In contrast to coastal sites, freshwater sites are con-

fined to physically finite habitats. As such, we expected

to observe reduced intrapopulation diversity and

increased interpopulation differentiation in ponds as

compared to lakes and rivers. However, no clear-cut

habitat dependent patterns were discovered neither in

genetic variability or degree of genetic differentiation,

nor in historical effective population sizes. While we

acknowledge the small number of replicate sites within

different categories of freshwater habitats, it appears

that historical events, rather than contemporary habitat

type effects, have been driving the patterns of genetic

population structure in our data. This is in contrast

with results of some recent studies where the impacts

of contemporary eco-demographic factors were sug-

gested to override the historical effects on genetic vari-

ability (e.g. Johansson et al. 2006).

Nine-spined vs. three-spined sticklebacks

In most parts of their European distribution, nine-spined

sticklebacks occur in sympatry with three-spined stickle-

backs (Paepke 2001). Both species inhabit coastal waters,

but the distribution of the nine-spined sticklebacks

extends further inland than that of the three-spined stick-

leback (Paeple 2001). In contrast to nine-spined stickle-

backs, a single ancestral marine lineage of three-spined

sticklebacks appears to have colonized the freshwater

habitats of Fennoscandia (Makinen et al. 2006; Makinen

& Merila 2008). Our results suggest that in the case of

nine-spined sticklebacks, Fennoscandia has been colo-

nized by at least two different lineages of nine-spined

sticklebacks, possibly of freshwater origin. Indirect – and

yet largely hypothetical – support for the freshwater

origin is provided by their widespread occurrence in

inland areas, as well by their genetic characteristics.

In a review of microsatellite polymorphisms in fish,

DeWoody & Avise (2000) reported that an average het-

erozygosity for marine, anadromous and freshwater fish

was 0.77, 0.68 and 0.54, respectively. In the Baltic and

White Sea sites of three-spined sticklebacks, heterozy-

gosity was high (HE = 0.80; Makinen et al. 2006) as is

typical for marine fish species. However, heterozygosity

in the Baltic and White Sea sites of nine-spined stickle-

backs is lower (HE = 0.58), and appears to correspond

more closely to that of freshwater rather than marine

fish species. Hence, the relatively low genetic variation

in the coastal nine-spined sticklebacks might be due to

their freshwater origin. Alternatively, the low genetic

variation in nine-spined sticklebacks might reflect ascer-

tainment bias since the loci used in this study were

originally developed for three-spined sticklebacks

(Makinen et al. 2007). Hence, while the question about

the freshwater vs. marine origin of the nine-spined

sticklebacks cannot yet be conclusively resolved, it is

nevertheless clear that the differences in present-day

levels and distribution of genetic variability between

three-spined and nine-spined sticklebacks owe to dif-

ferences in their colonization history of the northern

Europe.

Conclusions

In summary, our study demonstrates how postglacial

colonization can influence the contemporary population

genetic structure of a species, indicating a strong

historical component to the patterns of genetic variation

and differentiation in northern European nine-spined

sticklebacks. As expected, the levels of genetic variation

and differentiation were significantly different between

the coastal and freshwater sites. However, the genetic

structure of the freshwater sites was not much influenced

by habitat type effects, but strong negative association

between latitude and intrapopulation genetic variability

was observed. Historical northward expansions of this

species were most likely the cause of low genetic varia-

tion and strong genetic subdivision in mid and northern

Fennoscandia. The geographically structured pattern of

genetic diversity suggests that the contemporary genetic

structure of freshwater nine-spined sticklebacks has been

strongly impacted by the founder events associated with

postglacial recolonization of the northern Europe.

Acknowledgements

We thank Abigel Gonda, Kjartan Østbye, Tom Olav Klepaker,

Jorg Freyhof, Tuomas Leinonen, Jaakko Lumme, Hannu

Makinen, Kimmo Kahilainen, Henri Persat, Anti Vasemagi, Akira

Goto, Tom Pike, Arne Levsen, Joost Raeymaekers, Taina Kojola,

Leena Eerola, Aki Hirvonen, Lennart Persson, Jarmo Saarikivi,

Pirkko Siikamaki, Victor Berger, Goran Englund, Daniel Lussetti

and Kalevi Kuusela for help in obtaining samples. Special thanks

to the Oulanka Research Station and the White Sea Biological

Station in helping us with sampling some remote areas. Thanks

are also due to Hannu Makinen for his comments and Jacquelin

DeFaveri for correcting the English. Our study was supported

by the Academy of Finland, the Baltgene-project of the BONUS-

program and the Japan Society for the Promotion of Science.

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T.S. and Y.S. are broadly interested in fish population genetics

and genomics, and those in three- and nine-spined sticklebacks

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of nine-spined sticklebacks. J.M. is interested in evolutionary

and population genetics of wild vertebrate populations with

increasing curiosity directed towards the study of sticklebacks.

Supporting Information

Additional supporting information may be found in the online

version of this article.

Fig. S1 Multidimensional scaling plot of pairwise DA distances

(A) and distribution of PC1 and PC2 scores in principal com-

ponent analysis of the allele frequencies (B) in nine-spined

sticklebacks. Inverted triangle: coastal, circle: lake, square:

river, triangle: pond. Closed symbols: eastern lineage, open

symbols: western lineage, x: Japanese sample.

Table S1 Sampling sites, sample sizes (n), number of observed

alleles (A), allelic richness (Ar), expected heterozygosity (HE)

and FIS in nine-spined sticklebacks

Table S2 Variable nucleotide sites across 1104 bp sequences of

cytochrome b in nine-spined sticklebacks. Complete sequences

have been deposited in GenBank under accession numbers

GU227740–GU227783.

Table S3 Estimates of migration parameter M within freshwa-

ter or coastal sites and between them in nine-spined stickle-

backs

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or functionality of any supporting information supplied by the

authors. Any queries (other than missing material) should be

directed to the corresponding author for the article.