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Botanical Journal of the Linnean Society, 2013, 173, 64–76. With 3 figures
The phylogeographical and population genetic
approach to the investigation of the genetic diversity
patterns in self-incompatible clonal and polyploid
Linnaea borealis subsp. borealis
ADA WRÓBLEWSKA*
Department of Botany, Institute of Biology, University of Białystok, 20B Świerkowa Street, 15-950
Białystok, Poland
Received 14 August 2012; revised 10 January 2013; accepted for publication 7 June 2013
Surveys of genetic diversity patterns of self-incompatible clonal polyploid plant species are still scarcer than those
of diploid plant species. Therefore, I studied the phylogeographical history of Linnaea borealis subsp. borealis to shed
light on the colonization history of this clonal self-incompatible polyploid plant in Eurasia using selected regions of
plastid DNA and genetic diversity patterns of 22 populations of this species employing AFLP markers. I also
addressed the question of whether the genetic diversity patterns in L. borealis subsp. borealis in Eurasia are similar
to those of earlier published studies of clonal self-incompatible diploid or polyploid plants. This survey revealed that
the shallow phylogeographical history (six plastid haplotypes forming one haplogroup, 100% bootstrap support)
and moderate genome-wide diversity estimated using AFLP markers (Fragpoly = 10.8–38.9%, I = 0.060–0.180,
FST = 0.289) were general characteristics of L. borealis subsp. borealis in its Eurasian range. The sampling strategy,
in most cases at 1–2-m or even 3–5-m intervals, showed that a balance between vegetative and sexual reproduction
and limited pollen dispersal among compatible mates can be important for genetic diversity patterns in populations
of this taxon. Despite the fact that one-half of the investigated populations were strongly isolated, they still preserved
similar levels of genetic diversity across the geographical range. I found no support for the hypothesis that a
bottleneck and/or inbreeding had accompanied habitat fragmentation as factors shaping genetic diversity. © 2013
The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76.
ADDITIONAL KEYWORDS: AFLPs – cpDNA – isolation – small population area –twinflower.
INTRODUCTION
Surveys of genetic diversity patterns of selfincompatible clonal polyploid plants are still scarcer
than those of diploid species (Brown & Young, 2000;
Willerding & Poschlod, 2002; Honnay, Jacquemyn &
Roldan-Ruiz, 2006; Vandepitte et al., 2010; Kloss,
Fischer & Durka, 2011). Despite this, clonality has
been frequently reported as one of the main factors
influencing sexual reproduction within populations in
self-incompatible diploid and in polyploid plants. Low
rates of fruit set and recruitment may become more
evident in spatially isolated small populations of selfincompatible plant species because of a low number of
genets. In this case, gene flow among populations is
*E-mail: [email protected]
64
not sufficient to enrich genetic and genotypic diversity
through pollen and/or seeds. Leimu et al. (2006) found
that male fitness tended to decrease more markedly
in small populations of self-incompatible species
than in self-compatible species, suggesting greater
pollinator limitation in small populations of selfincompatible species. These authors also showed
significant positive associations between withinpopulation genetic diversity and population size in
self-incompatible species, stressing that they were
more prone than self-compatible species to the negative effects of habitat fragmentation.
However, in self-incompatible clonal plants, vegetative reproduction allows the existence of populations
subject to pollen limitation conditions and/or when
sexual reproduction is completely absent. VallejoMarı́n & O’Brien (2007) and Vallejo-Marı́n (2007)
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
GENETIC DIVERSITY IN LINNAEA BOREALIS
addressed the question of a general association
between clonality and sexual systems in the majority
of diploid species of Solanum L. Explaining the correlation between self-incompatibility and clonality in
this genus, they stated that obligatory outcrossing
could often be associated with the ability to reproduce
clonally in a colonizing plant species when the cost of
geitonogamy is strong. They concluded that the avoidance of geitonogamous selfing has a significant role in
the evolutionary maintenance of self-incompatibility
in clonal plants.
The association of self-incompatibility and polyploidy has also been considered in other Solanaceae
(Robertson, Goldberg & Igíc, 2011) and in Brassicaceae (Okamoto et al., 2004; Mable et al., 2005;
Paetsch, Mayland-Quellhorst & Neuffer, 2006;
Koelling, Hamrick & Mauricio, 2011; Tsuchimatsu
et al., 2012), but not in the light of clonality.
Nasrallah et al. (2007) pointed out that, in selfincompatible systems, such as those of Brassicaceae,
dominance interactions among S haplogroups
might have played an important role in the loss
of self-incompatibility in polyploids and hybrids.
In addition, quantitative variation in the strength
of self-incompatibility within a single species of
Brassicaceae may be an important transition to
self-compatibility (Nielsen, Siegismund & Philipp,
2003); this means that self-incompatibility in selfincompatible plants is leaky and that these plants
exhibit
partial
self-compatibility.
Associations
between breeding system, polyploidy and genetic
diversity have also been explored in more detail by
Stebbins (1971), Ramsey & Schemske (1998), Soltis &
Soltis (2000) and Vamosi et al. (2007), and by
Husband et al. (2008), who argued that, in polyploid
self-incompatible plants, generally high levels of heterozygosity were observed.
To bridge the gap in the surveys of genetic diversity
patterns within self-incompatible clonal polyploid
plants, Linnaea borealis L. subsp. borealis was
selected as the study taxon. I describe: (1) the phylogeographical history using selected genes of plastid
DNA to shed light on the colonization history of this
taxon in Eurasia; and (2) the genetic diversity patterns within the geographical range of this taxon
using AFLP markers. I also address the question of
whether the genetic diversity patterns of L. borealis
subsp. borealis in Eurasia are similar to those of
other self-incompatible clonal diploid or polyploid
plant species. Despite the clonal reproduction, I
expect that a high level of genetic diversity should be
detected in L. borealis subsp. borealis because of the
polyploid character of this species, the presence of a
self-incompatible breeding system and sexual reproduction. I compare my results with reports on genetic
and genotypic diversity in self-incompatible clonal
65
diploid and polyploid (mainly tetraploid) species to
identify general patterns.
MATERIAL AND METHODS
STUDY SPECIES
Three subspecies are recognized in L. borealis. These
differ in morphological characters (Hultén, 1968;
Munz & Keck, 1975), but have overlapping geographical ranges: L. borealis subsp. borealis is a circumboreal plant in Eurasia and in part of north-western
North America (Fig. 1A); L. borealis subsp. americana
(Forbes) Hultén ex R.T.Clausen occurs in the boreal
zone of North America; and L. borealis subsp. longifolia (Torr.) Hultén has a restricted distribution in the
Pacific Northwest region. All investigated samples
belong to L. borealis subsp. borealis.
Linnaea borealis subsp. borealis, twinflower (Caprifoliaceae), is associated with coniferous forest, occurring from sea level to well above the tree line,
reaching 1320 m a.s.l. in the mountains of southern
Norway (Torbjørn, 2006) and 1600–1800 m a.s.l. in
the Alps (L. Poggio and T. Delahaye, pers. observ.).
According to Hagerup (1944) and Löve & Löve (1975),
this taxon is tetraploid with 2n = 4x = 32; no other
ploidies have been reported.
Twinflower is a shade-tolerant, evergreen dwarf
shrub. Linnaea borealis subsp. borealis is selfincompatible with a gametophytic self-incompatibility
system, but leaky self-incompatibility cannot be ruled
out completely because of limited treatments of the
breeding system in other populations throughout the
geographical range (Wilcock & Jennings, 1999). Pollinators are Diptera and Hymenoptera (Scobie &
Wilcock, 2009). The population biology and spatial
genetic structure of this species have only been investigated in detail in peripheral Scottish populations
(Wilcock & Jennings, 1999; Kohn & Ennos, 2000;
Scobie & Wilcock, 2009). Different biological features
have been studied in Swedish populations (Eriksson,
1988; Niva, 2003). In both cases, the authors pointed
out the extensive vegetative reproduction by stolons
and the extremely low genotypic diversity (patches
containing one or rarely a few clones). In the natural
Swedish populations, L. borealis subsp. borealis
reproduces vegetatively, mainly by stolons, forming
large clones up to 10 m (Eriksson, 1988; Niva, 2003).
In Scotland, the low seed set has been attributed to
reproductive isolation caused by a lack of compatible
mate availability within populations and limited
pollen movement between them (Ross & La Roi, 1990;
Wilcock & Jennings, 1999; Scobie & Wilcock, 2009).
The twinflower fruit is a small, dry, one-seeded
capsule, and apparently does not persist in seed
banks (Granstrom, 1986). The seed has a small hook
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
66
A. WRÓBLEWSKA
A
ATU
ETR
EA1
EA3
EK2
EK1
EÖL
EBT
EKA
EW2 ESW
EFR
EW1
AJA
EA2
EBA
ECW
AYE
AAL
ERO
ETA
ESZ
Abelia corymbosa
Haplotype
A
B
C
D
E
F
100
0
B
1000 km
500
L
JA
A
A
A
2
EA
3
AY
E
AT
U
1
EA
EA
ET
R
A
EB
T
EK
1
EK
2
EK
L
ET
A
ER
O
Z
EÖ
ES
EC
W
EB
A
EF
R
EW
1
EW
2
ES
W
C
A
L
A
JA
A
2
EA
3
AY
E
AT
U
EA
1
EA
R
ET
T
1
EK
2
EK
EB
A
EK
L
ET
A
ER
O
EÖ
Z
ES
R
EW
1
EW
2
ES
W
EF
EC
W
EB
A
D
Figure 1. A, Geographical range of Linnaea borealis subsp. borealis (dark shading, continuous range; point, group of
marginal isolated populations outside continuous range). B, Sample localities of populations, phylogenetic relationships
and distribution of plastid DNA haplotypes (codes: A–F, see Table 1), the relationships of which (inferred from BEAST) are
shown in the inset. Genetic groups identified by STRUCTURE for all populations for K = 2 (C) and for K = 3 (D); colours
represent the groups identified; each population is represented by one chart, showing the relative proportion of
membership to the different clusters.
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
GENETIC DIVERSITY IN LINNAEA BOREALIS
67
Table 1. Characteristics of Linnaea borealis subsp. borealis populations at plastid DNA and AFLP loci. No., population
number; Pa, population area (m2); N, number of samples analysed; Fl./Fr., flowering and fruiting in populations (+,
observed; –, absent; ?, data not collected); Hc, cpDNA haplotype code; h, haplotype diversity; π, nucleotide diversity; MLG,
number of multilocus genotypes; Fragpoly, proportion of polymorphic loci; H, Nei’s gene diversity; DW, rarity index; #, sum
of parameter
Plastid DNA
No.
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
Fl./
Fr.
Hc
h
π
Fragpoly
(%)
H
DW
8
+/+
A, E
0.4285
0.0002
8
27.1
0.105
1.61
700
10
+/+
A, B
0.2222
0.0001
8
18.5
0.064
0.81
EFR
700
10
+/?
A, C
0.3555
0.0002
10
30.9
0.112
1.49
ESZ
ESW
EBA
ECW
ETA
100
500
3000
–
50
9
11
13
4
10
+/+
+/+
+/+
+/+
–/–
A
D
A
A
F
0
0
0
0
0
0
0
0
0
0
7
9
13
4
4
16.6
26.4
33.7
17.5
18.8
0.057
0.088
0.104
0.093
0.083
1.31
1.31
1.95
1.71
1.02
EBT
50
9
+/?
A
0
0
7
22.2
0.091
1.41
ERO
70
9
+/+
A
0
0
8
21.9
0.085
1.37
EKA
100
9
+/−
A
0
0
5
10.8
0.041
1.09
EÖL
100
10
+/?
A
0
0
8
18.8
0.073
1.21
EK1
EK2
ETR
EA1
300
230
400
>10 000
7
10
10
10
+/+
+/+
+/?
+/+
A
A
B
A
0
0
0
0
0
0
0
0
4
8
10
10
21.2
28.4
27.7
25.8
0.090
0.101
0.093
0.082
1.61
1.35
1.59
1.38
EA2
EA3
AJA
ATU
AYE
400
30
>10 000
>10 000
>10 000
9
6
9
8
5
+/+
+/+
+/+
+/+
+/+
A
A
A
A
A
0
0
0
0
0
0
0
0
0
0
9
6
9
7
5
26.4
25.2
38.9
25.8
23.9
0.097
0.112
0.129
0.097
0.111
1.59
1.62
2.76
1.92
2.33
AAL
15
10
+/+
A, C
0.3555
0.0002
10
22.6
0.066
3.22
169#
23.7
0.093
Location
Code
Pa (m2)
Italy, Aosta Valley,
Gran Paradiso
National Park
Italy, Aosta Valley,
Gran Paradiso
National Park
France, Les Allues,
Vanoise
Switzerland, Zermez
Switzerland, Zermez
Scotland, Balmoral
Scotland, Curr Wood
Poland, Tatra
National Park
Poland, Bory
Tucholskie
National Park
Poland,
Roztoczański
National Park
Poland, Kampinos
National Park
Sweden, Öland
Island
Finland, Kuhmo
Finland, Kuhmo
Nowary, Tromsø
Russia,
Kandalaksha
Russia, Arkhangelsk
Russia, Arkhangelsk
Russia, Jaroslaviec
Russia, Turukhansk
Russia,
Yekaterinburg
Russia, Altai
Mountains
Species level
EW1
700
EW2
N
196#
that adheres to animal fur and bird feathers, allowing
ectozoochoric dispersal.
STUDY
SITES AND
AFLP
DNA
EXTRACTION
One hundred and ninety-six samples from
22 L. borealis subsp. borealis populations located in
MLG
Eurasia were sampled during 2007–2009, spanning
the geographical range from 32°03′N to 69°41′N and
from 50°51′E to 85°51′E (Table 1, Fig. 1B). Leaves
from shoots growing at least 3–5 m apart in populations > 100 m2 and 1–2 m apart in populations
< 100 m2 were taken to prevent the collection of duplicate samples from the same genet, and then dried in
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
68
A. WRÓBLEWSKA
silica gel. In each of the populations studied, an
approximate area of population (m2) and information
about observed flowering and fruiting were noted in
the year of collection. Genomic DNA was extracted
from dry leaf tissues with a Genomic Mini AX Plant
kit (A & A Biotechnology, Poland).
SEQUENCING
AND DATA ANALYSES
Three fragments of 15 noncoding and coding regions
of plastid DNA were analysed. Polymorphism was
observed only in the intergenic spacers of trnL-trnF,
amplified with primers e and f (Taberlet et al., 1991),
and rpl32-trnL(UAG) and psbD-trnT(GGU), both amplified
with primers from Shaw et al. (2007). Fragments
were amplified by PCR in a 10 μL volume containing
2 μL of DNA, 5 μL of QIAGEN Multiplex PCR Master
Mix (with HotStarTaq® DNA polymerase, Qiagen),
2 μL of H2O and 1 μL of 2 pmol of each primer. PCR
profiles comprised: initial denaturation at 94 °C for
15 min, followed by 30 amplification cycles of denaturation at 94 °C for 30 s, annealing at 57 °C for
1 min and 30 s, extension at 72 °C for 1 min, ending
with a final extension of 30 min at 60 °C. Sequencing
was performed using BigDye Terminator V 3.1
(Applied Biosystems) according to the manufacturer’s
instructions. Samples were run on an ABI 3130
Genetic Analyzer (Applied Biosystems). Sequences
were assembled and edited using BIOEDIT 7.04 (Hall,
1999).
Nucleotide (π) and haplotype (h) diversity, and
Tajima’s D (Tajima, 1989), Fs (Fu, 1997) and R2
(Ramos-Onsins & Rozas, 2002) statistics were calculated with DNASP 4.90.1 (Rozas & Rozas, 1999).
Ramos-Onsins & Rozas (2002) demonstrated that Fs
and R2 statistics have the greatest power to detect
population expansion for non-recombining regions of
the genome under a variety of different circumstances, especially when population sample sizes are
large (∼50, Fu’s Fs) or when sample sizes are small
(∼10, R2). They also found that the power of the R2
statistic is relatively high when the number of segregating sites is low (e.g. ∼20). The significance of Fu’s
Fs and R2 was obtained by examining the null distribution of 1000 coalescent simulations of these
statistics using DNASP 4.0 (Rozas et al., 2003). Significantly negative Fu’s Fs and significantly positive
R2 values were taken as evidence of a population
expansion.
To investigate the relationships between haplotypes, phylogenetic analyses were carried out using a
Bayesian approach implemented in BEAST 2.0
(Drummond et al., 2012) with Abelia corymbosa Regel
& Schmalh. as outgroup (Jacobs et al., 2010). Because
of discordance between individual gene trees that
share a phylogenetic history, Bayesian species tree
analysis using a multispecies coalescent model with
linear and constant root prior was conducted (Heled
& Drummond, 2010). The term ‘species’ is not the
same as the taxonomic rank and instead designates a
group of individuals that probably have no history of
breeding with individuals outside that group (Heled
& Drummond, 2010). The BEAUTI program was used
to unlink the substitution models of the data partitions and to implement the models of sequence evolution identified as optimal by JMODELTEST 0.1.1
(Posada, 2008). The model fit of nucleotide substitution models was assessed via the Akaike Information
Criterion (AIC). Simulations were run using Markov
chain Monte Carlo (MCMC) for 10 000 000 generations, with a store of 10 000 in the program BEAUTI.
Finally, I discarded the trees as burn-in and summarized the trees using TREEANNOTATOR 1.7.2. The tree
was visualized with FIGTREE 1.3.1 (Rambaut, 2010).
AFLP
FINGERPRINT AND DATA ANALYSIS
The AFLP procedure followed Vos et al. (1995), but
was modified according to the Applied Biosystems
protocol (AFLP™ Plant Mapping). First, 32 primer
pair combinations were tested on four selected
samples. The fluorescence-labelled selective amplification products were mixed with 500 Liz labelled size
standard (Applied Biosystems) and run on an ABI
3130 Genetic Analyzer. Then, from this analysis,
two primer combinations (EcoR1-AGC/MseI-CAT and
EcoR1-AGG/MseI-CAC) that gave polymorphic, clear,
reproducible fragments of homogeneous intensity
were chosen. Variable fragments in the 70–500-bp
size range were scored as present (1) or absent (0)
using GENEMAPPER 4.0 (Applied Biosystems). To test
the repeatability of AFLP results, two individuals
from each population were completely replicated
starting from the restriction/ligation reaction of
AFLP. Potential resampling of clones was checked
with AFLPDAT R-SCRIPT (Ehrich, 2006).
To infer population structure and assign individuals to populations, the model-based clustering method
described by Pritchard, Stephens & Donnelly (2000)
was used, as implemented in STRUCTURE ver. 2.3.3.
The AFLP datasets were coded with a top row indicating 1 as the recessive allele in STRUCTURE 2.3.3
also available for studies using dominant markers
(Falush, Stephens & Pritchard, 2007). Data were analysed with an admixture model with correlated allele
frequencies elaborated by Falush, Stephens &
Pritchard (2003). Ten replicates were run for all possible values of the number of clusters (K) up to K = 22.
Following the recommendations by Evanno, Regnaut
& Goudet (2005), the ad hoc statistic ΔK, based on the
rate of change in the log likelihood of data between
consecutive K values, was calculated. All runs were
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
GENETIC DIVERSITY IN LINNAEA BOREALIS
based on 500 000 iterations after a burn-in of 100 000
iterations.
In order to assess levels of genetic diversity, the
percentage of polymorphic fragments (Fragpoly) and
Nei’s gene diversity (H, applied regardless of ploidy;
Nei, 1973), were computed for each population with
AFLPDAT R-SCRIPT. Correlations between Fragpoly and
H values, between genetic diversity parameters and
population areas, and between longitude and latitude
were tested (pairwise Spearman’s rank correlations
and quadratic regression; StatSoft, 1997). The rarity
index for each population, which corresponds to the
‘frequency-downweighted marker values’ (DW,
Schönswetter & Tribsch, 2005), was calculated using
AFLPDAT R-SCRIPT. The rarity index is expected to be
high in long isolated populations in which rare
markers should have accumulated as a result of
mutations, whereas newly established populations
are expected to show low values.
The F statistic was determined by analysis of
molecular variance (AMOVA) using the program
ARLEQUIN 3.11 (Excoffier, Laval & Schneider, 2005).
The F statistic was calculated on the basis of data
identified by STRUCTURE software. The significance of
variance components was determined using 1000 permutation runs. The relationships between genetic and
geographical distances (isolation by distance, IBD)
among all populations were estimated (Slatkin, 1987)
by correlating FST/(1 − FST) with ln(geographical distance) (km) in a Mantel test with 9999 permutations
using GENALEX 6 (Peakall & Smouse, 2005). Genetic
relationships between 169 individuals (excluding
clones, Table 1) were identified by principal coordinate analysis (PCoA, based on Dice similarity) plotted
with MVSP 3.0 (Kovach, 1999). The differences in
average values of principal component 1 (PC1) and
PC2 between populations were tested by one-way
ANOVA in StatSoft (1997).
Comparison of genetic and genotypic diversity in
self-incompatible clonal diploid and polyploid plants
with division on genetic markers [allozymes, microsatellites, AFLP, random amplification of polymorphic
DNA (RAPD) and inter-simple sequence repeat
(ISSR)] from 29 published papers was conducted
(Supporting Information Table S3). Information about
the number of samples and populations, genetic and
genotypic diversity parameters, such as P (%) (percentage of polymorphic loci), G/N (clonal diversity),
HE/HO
(expected/observed
heterozygosity),
FIS
(inbreeding coefficient), H (Nei’s gene diversity) and I
(Shannon diversity index), and FST (GST) (coefficient of
genetic differentiation among populations) was
included. The average and/or range (where available)
of genetic and genotypic diversity parameters was
presented for each species. The averages of the
genetic and genotypic diversity for molecular markers
69
were classified as: (1) allozymes; (2) microsatellites; or
(3) AFLP, RAPD and ISSR. The statistical significance
of the difference of each genetic diversity measure
between diploids and polyploids was determined
using the Mann–Whitney U-test (StatSoft, 1997).
RESULTS
PLASTID DNA SEQUENCING
The final matrix consisted of concatenated sequences
from trnL-trnF, rpl32-trnL(UAG) and psbD-trnT(GGU)
from 196 individuals. The length of the trnL-trnF
spacer sequences was 351 bp, with one substitution;
the rpl32-trnL(UAG) spacer was 897 bp in length with
one indel of 7 bp; three substitutions were detected in
psbD-trnT(GGU), which was 569 bp in length (Supporting Information Table S1). Six haplotypes were identified in the dataset. Of these, haplotype A had the
widest distribution and was found in formerly glaciated and non-glaciated areas in Europe in 20 populations. The distribution of the five other haplotypes
across the range revealed a higher haplotype diversity in the south; haplotype B was detected in two
populations located in northern and in southern
Europe (Alps), haplotype C in southern Europe and
the Alps, and three unique haplotypes D, E and F in
the Alps and the Carpathians (Fig. 1B).
Because only one plastid haplotype was represented in almost all populations, h and π values were
0 (Table 1). In four populations with two haplotypes
(EW1, EW2, EFR and AAL), the h values ranged from
0.2222 to 0.4285 and π from 0.0001 to 0.0002. Estimates of Tajima’s D (−1.49) and Fu’s Fs (−3.49) were
both non-significant (P > 0.1). Only the R2 statistic
was positive and significant (0.05, P < 0.001), indicating a departure from neutrality and therefore population expansion. The observed mismatch distribution
closely matches that of an expected recent population
expansion (Supporting Information Fig. S1). All the
haplotypes of L. borealis subsp. borealis formed one
group with 100% posterior probabilities (Fig. 1B).
AFLP
ANALYSIS
Three hundred and fourteen polymorphic bands in 22
populations of L. borealis subsp. borealis were scored.
Repeatability was high (97.3%). This means that, on
average, 2.7% of the marker differences found in the
present study between two randomly chosen samples
can be explained by scoring and laboratory analysis.
Considering the error rate and allowing for three
differences within a genotype, 27 of 196 samples may
represent clones. In 11 populations, all samples represented distinct multilocus genotypes, but, in the
ETA, EKA and EK1 populations, almost half of the
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
70
A. WRÓBLEWSKA
explained 11.2% and the second 6.8% of the overall
variance, but only PC1 was significant by one-way
ANOVA (P < 0.05, Fig. 3).
r 2 = 0.02, ns
FST/(1-FST)
2.0
1.5
1.0
DISCUSSION
0.5
0
0
2
4
6
ln (geographic distance, km)
8
10
Figure 2. Isolation by distance pattern among 22
Linnaea borealis subsp. borealis populations from Eurasia
based on AFLP data.
multilocus genotypes were clones (Table 1). Therefore,
27 duplicated multilocus genotypes were deleted from
the dataset.
After removal of clonal replicates, ΔK (Evanno
et al., 2005) showed the highest peak at K = 2 (Supporting Information Fig. S2), but, alternatively, model
K = 3 might also be supported. Neither the two nor
three clusters showed clear geographical structure,
and almost all individuals represented a mixture of
two or three diverse genetic backgrounds, respectively
(Fig. 1C, D). Only in populations EA2 and EKA
(Europe) did one gene pool dominate and, in AAL
(central Asia), the other (Fig. 1C, D). Low to moderate
percentages of polymorphic fragments (Fragpoly = 10.8–38.9%) and Nei’s gene diversity (H = 0.041–
0.129) were detected (Table 1). No multilocus
genotypes were shared between populations. Significant positive relationships of Fragpoly with H and of
Fragpoly and H with population area were found
(Spearman’s rank correlation: r = 0.54, P < 0.01;
r = 0.47, P < 0.05; r = 0.31, P < 0.05, respectively).
Weak and non-significant correlations between Fragpoly and H values and longitude and latitude were
noted (P > 0.05, quadratic regression). The rarity
value index was highest and statistically significant
in AAL, AJA, AYE and ATU (central and northern
Asia, DW = 3.21, 2.76, 2.33 and 1.92, respectively).
The overall FST was moderate (0.289). Almost all
pairwise FST values were significant, ranging from
0.001 to 0.098 between the Scottish populations and
between populations ECW and EA1, and 0.598
between populations ESZ and AAL (Supporting Information Table S2). The amount of molecular variance
was highest within populations (AMOVA, 71.1%;
P < 0.001). The Mantel test of IBD was weak and not
significant (r2 = 0.02; P = 0.09) (Fig. 2). The PCoA
diagram showed that the individuals from different
populations mixed slightly with each other (Fig. 3);
the multilocus genotypes from population AAL
(central Asia) were identified as the most distinct
group on the PCoA diagram. In PCoA, the first factor
This survey has revealed that weak phylogeographical structure, inferred from plastid DNA, and
moderate genome-wide diversity, estimated from
AFLP markers, are general characteristics of selfincompatible clonal and tetraploid L. borealis subsp.
borealis in Eurasia. A shallow evolutionary history
(six closely related haplotypes) and/or rapid population expansion and life history traits, i.e. clonality
and breeding systems, may explain the genetic diversity patterns of this species across its range. Low
polymorphism of plastid DNA (Table 1, S1) and phylogeographical patterns similar to those observed in
L. borealis subsp. borealis have been described from
other clonal, but self-compatible, plant species with
a northern distribution (circumpolar, circumboreal
or arctic; Ehrich, Alsos & Brochmann, 2008;
Westergaard et al., 2010; Wróblewska, 2012). The distribution of plastid DNA haplotype diversity showed a
pattern of ‘northern purity’ (at high latitudes, two
haplotypes) versus ‘southern richness’ (at low latitudes, six haplotypes) within the geographical range.
There were also pronounced inconsistencies between
plastid DNA and AFLP within populations east of the
Ural Mountains, which contained more rare AFLP
fragments than did the southern populations from
Europe (Table 1). This may indicate that the putative
refugial areas of this circumboreal plant species were
present both in southern Europe (i.e. the Alps) and/or
in central Asia (Hedberg, 1992). The Alps are often
recognized as areas of persistence of populations as
relicts during the Last Glacial Maximum (LGM)
(Huntley & Birks, 1983; Habel et al., 2010). The populations and individuals with distinct plastid haplotypes were not strongly genetically differentiated by
AFLP data in the same areas in Eurasia. These
patterns can be explained by the recent plastid DNA
sequence divergence in this taxon, rapid population
expansion and/or episodes of multidirectional nuclear
long-distant gene flow among populations (Eidesen
et al., 2007). Differentiation in L. borealis subsp.
borealis may also be a result of multiple pathways of
genome evolution after polyploidization. So far, only
tetraploid populations have been observed within its
range (Hagerup, 1944; Skalinska & Pogan, 1973;
Löve & Löve, 1975; Krogulevich, 1976, 1978;
Arohonka, 1982; Semerenko, 1990; Benko-Iseppon,
1992; Qiner & Landrein, 2011). Although no diploid
progenitor of L. borealis subsp. borealis has been recognized to date and located, it cannot be excluded
that, within the range, particularly in southern
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
GENETIC DIVERSITY IN LINNAEA BOREALIS
71
2.5
1.9
PC2 (6.8%, P < 0.05)
1.2
0.6
-3.1
-2.5
-1.9
-1.2
-0.6
0.6
1.2
1.9
2.5
-0.6
-1.2
-1.9
-2.5
-3.1
L
A
A
E
AT
U
A
JA
AY
1
2
EA
3
EA
EA
L
ET
A
ER
O
EK
A
EB
T
EK
1
EK
2
ET
R
Z
W
EÖ
ES
ES
1
2
EW
R
W
EW
EF
EB
EC
A
PC1 (11.2%, P < 0.05)
Figure 3. Principal coordinate analysis (PCoA) plot of 169 Linnaea borealis subsp. borealis individuals in the Eurasian
group based on AFLP data. P values for PC1 and PC2 axes were obtained by one-way ANOVA.
Europe, central Asia or north-western North America,
other ploidies (diploids or polyploids) may still exist.
Therefore, future research to identify the origin of
polyploidy in this taxon and between its sister taxa is
central not only to describe correctly the phylogenetic
position of L. borealis subsp. borealis, but also to
interpret its population genetic structure.
The lack of a strong genetic diversity gradient over
latitude and longitude between non-glaciated and
formerly glaciated areas is the result of similar patterns of genetic diversity (Fragpoly = 10.8–38.9%;
H = 0.041–0.129) over a continental spatial scale (c.
20–5800 km). Genetic differentiation among clonal
and outbreeding L. borealis subsp. borealis populations was moderate (FST = 0.289). Genetic diversity in
L. borealis subsp. borealis was slightly lower than the
results obtained for the long-lived perennials, outcrossers and widespread species reported by Nybom
(2004). Estimates of within-population genetic diversity derived from co-dominant and dominant markers
(Table S3; Brown & Young, 2000; Willerding &
Poschlod, 2002; Honnay et al., 2006; Vandepitte et al.,
2010; Kloss et al., 2011) ranged from low values
in diploid plants to high values in polyploid plants.
The genetic diversity of L. borealis subsp. borealis
was similar to that of 24 self-incompatible clonal
and diploid plants, but lower than that of five
self-incompatible, clonal, polyploid plant species
(Table S3). However, these surveys described patterns
of genetic diversity on a small scale (within regions)
and inferences must be interpreted with caution.
Almost all authors have stressed that clonal reproduction and limitation of pollinators appear to have a
strong effect on sexual reproduction and the genetic
diversity level within populations (Table S3). Guan
et al. (2010) and Young et al. (2002) mentioned
restricted gene flow by pollen as a result of low
visitation rates of pollinators. In addition, in small
and isolated populations, clonal growth will cause
most neighbours of any given flowers to be genetically
incompatible mates. Other authors have emphasized
the importance of historical random loss of alleles as
a result of habitat fragmentation and a leptokurtic
distribution of seed dispersal, rather than inbreeding
(Franks et al., 2004). In the case of self-incompatible
clonal and polyploid plants, higher genetic diversity
than in diploid species may be conditioned by ploidy
and breeding system (Table S3; Brown & Young,
2000; Willerding & Poschlod, 2002; Kloss et al.,
2011; Palop-Esteban, Segarra-Moragues & GonzálezCandelas, 2011). These authors have also confirmed
that, within self-incompatible, clonal, polyploid
species, effective dispersal of pollen and seed, weak
spatial isolation of populations and the large geographical range may contribute to a high level of
genetic diversity. AFLP data indicate that, despite the
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
72
A. WRÓBLEWSKA
clonal spread of L. borealis subsp. borealis by means
of long stolons, the majority of individuals surveyed
produced different AFLP profiles (86% of all individuals; Table 1). In L. borealis subsp. borealis, guerilla
clonal growth and sexual reproduction counterbalance each other and, even if sexual reproduction is
low within populations, it may be sufficient to maintain or even increase slightly the genetic diversity of
populations (Stehlik & Holderegger, 2000; Dietz &
Steinlein, 2001). Only in populations ETA, EKA and
EK1 were half of the collected plants repeated multilocus genotypes; in population EKA (Central
Europe, 100 m2), with one predominating genome, a
considerably low level of genetic variation was
observed (Fragpoly = 11.5%, H = 0.041). For this population, a founder effect cannot be excluded (H. Zacharczuk, pers. comm.). In Scottish populations, higher
genetic diversity was observed in Balmoral relative to
Curr Wood (Scobie & Wilcock, 2009), in agreement
with the present study (populations EBA and
ECW, respectively; Fragpoly = 33.7%, H = 0.104 versus
Fragpoly = 17.5%, H = 0.093). Higher genetic diversity
in patches 2 and 3 from Balmoral coincides with
higher variability of flower colour and high natural
fruit set, indicating high clonal diversity.
In clonal plants, the guerrilla type exhibits a dispersive growth form, distributing its ramets at larger
distances. Populations with intermingled genotypes
are more likely to successfully outcross (attract more
pollinators) and set seed. Levin & Kerster (1971) and
Young et al. (2002) have suggested that such mixing
of genets decreases the likelihood of genet death and
increases the probability of sexual reproduction by
interclone pollen transfer, particularly important in
self-incompatible species. In L. borealis subsp. borealis, it was difficult to assess population size because
well-branched often overlapping individuals can
reach up to several metres. In this case, the relationship between population area and genetic diversity
may be more adequate. The majority of L. borealis
subsp. borealis populations occupied rather small
areas (15–100 m2, rarely 500–700 m2, Table 1) both
outside and inside of the continuous geographical
range, and generally flowers and fruits were observed
within them (collectors of L. borealis subsp. borealis;
pers. comm.), but there was evidence of lower genetic
diversity within populations with the smallest population sizes. These data also correspond to the generally positive relationship between population size/
area and genetic diversity often found in selfincompatible species (Leimu et al., 2006). I found no
strong support for the hypothesis that a bottleneck
and/or inbreeding shaped genetic diversity, because of
clear and strong associations between the number
of polymorphic fragments and Shannon diversity
indices. It seems likely that the tetraploid character
of L. borealis subsp. borealis might be associated with
self-incompatibility and outcrossing, as in other tetraploid plant species, but this phenomenon requires
more treatments of breeding systems in populations
across the range (Soltis & Soltis, 2000; Husband
et al., 2008). Theoretically, polyploidy may reduce the
rates of homozygote formation and can buffer inbreeding depression because of the masking of deleterious
mutations by multiple copies of the genome
(Schemske & Lande, 1985; Barringer, 2007). Furthermore, prolonged clonal growth may save the individuals during relatively short periods of unfavourable
conditions, and may also buffer against genetic drift.
Based on AFLP data and the pollination biology of
this species, it can be concluded that contemporary
fragmentation of populations and limited pollen dispersal among them (L. borealis subsp. borealis pollinators usually transfer pollen between compatible
mates situated close to each other; Scobie & Wilcock,
2009) have influenced genetic subdivision (FST =
0.289). This variation is expected to be large when
genetic drift is strong, relative to gene flow, as in
cases in which habitat discontinuity has led to extensive population isolation (case III of Hutchinson &
Templeton, 1999). Alternative to this scenario, a
species may rapidly colonize a newly available geographical region, and multidirectional gene flow
among its populations can appear because the seeds
have a morphological adaptation to long-distance dispersal by animals.
CONCLUSIONS
In summary, the risks associated with the loss of
genetic diversity might be high for L. borealis subsp.
borealis in the future. Because sexual reproduction is
dependent on pollinators and the number of compatible mates, a reduction in genetic diversity will have
huge consequences. Investigations of reproductive
ecology in other Eurasian populations allow the prediction of genetic diversity patterns and the assessment of current effects on reproduction and the risks
of future loss of genetic diversity. Therefore, the proposed re-introduction of compatible mates to populations characterized by low levels of genetic diversity
and a detailed investigation of spatial genotypic
structure are required to ensure conservation, not
only in Scotland, but also in countries in which this
species is strongly threatened. The L. borealis subsp.
borealis populations should also be chosen with great
care in the re-introduction, taking into account the
phylogeographical approach. In this case, the conservation strategies proposed by Scobie & Wilcock (2009)
seem to be appropriate and should be concerned with
seeds, seedlings and/or adult plants between carefully
selected cross-compatible populations.
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
GENETIC DIVERSITY IN LINNAEA BOREALIS
ACKNOWLEDGEMENTS
I would like to thank Ulla-Britt Andersson, Igor
Artemov, Alexander Batalov, Thierry Delahaye, Arve
Elvebakk, Edyta Jermakowicz, Natalia Koroleva,
Patrick Kuss, Anna Otre˛ba, Laura Poggio, Michał
Ronikier, Izabela Tałałaj, Irina Tatarenko, Andrew
Scobie, Vladimir Semerikov, Przemysław Stachyra,
Gergely Várkonyi, Christopher C. Wilcocks and
Hanna Zacharczuk for help with collecting samples
in Eurasia, Maja Graniszewska who shared the
herbarium voucher of Abelia corymbosa, and Beata
Ostrowiecka for technical assistance in the laboratory.
I am especially grateful to two anonymous referees
who provided insightful comments on an earlier
version of the manuscript. This research was funded
by a grant from the Polish Ministry of Science and
Higher Education (NN303 366135).
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SUPPORTING INFORMATION
Additional Supporting Information may be found in the online version of this article at the publisher’s web-site:
Figure S1. Expected and observed mismatch distribution under population expansion model for Linnaea
borealis subsp. borealis based on plastid DNA data.
Figure S2. Estimated number of populations from STRUCTURE for 22 Linnaea borealis subsp. borealis populations. ΔK was calculated according to Evanno et al. (2005) and averaged over ten STRUCTURE runs for each
K.
Table S1. Variable nucleotide sites found in trnL-trnF, rpl32-trnL(UAG) and psbD-trnT(GGU) of Linnaea borealis
subsp. borealis. Nucleotides that are identical to those in the first listed haplotype are indicated by dots (.),
whereas the dashes (−) represent similar deletions in sequence.
Table S2. Genetic differentiation (FST values) between 23 populations of Linnaea borealis subsp. borealis based
on AFLP loci (bold, values not statistically significant).
Table S3. Comparative studies of 29 self-incompatible, clonal, diploid (A) and polyploid (B) species using
co-dominant (allozymes and microsatellites) and dominant (AFLP, RAPD and ISSR) markers; ALL, allozymes;
SSR, microsatellites; AFLP, amplified fragment length polymorphism; RAPD, random amplification of polymor© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76
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A. WRÓBLEWSKA
phic DNA; ISSR, inter-simple sequence repeat; n, number of samples; N, number of populations; P (%),
percentage of polymorphic loci; G/N, clonal diversity; HE/HO, expected/observed heterozygosity; FIS, inbreeding
coefficient; H, Nei’s gene diversity; I, Shannon diversity index; FST (GST), coefficient of genetic differentiation;
*P < 0.05, **P < 0.01, ***P < 0.001. In several cases, the average values of parameters and/or their ranges
estimated in the article were included. –, value not present in the article; ± SE, standard error; ∧, statistically
significant differences between diploid and polyploid species: allozymes: HE, U = 3.5, P < 0.001; HO, U = 49,
P < 0.001; microsatellites: HE, U = 12, P < 0.001; HO, U = 18, P < 0.001.
© 2013 The Linnean Society of London, Botanical Journal of the Linnean Society, 2013, 173, 64–76