Download Correlations between sex rate estimates and fitness across

doi: 10.1111/j.1420-9101.2007.01446.x
Correlations between sex rate estimates and fitness across
predominantly parthenogenetic flatworm populations
T. G. D’SOUZA & N. K. MICHIELS
Animal Evolutionary Ecology, Zoological Institute, Faculty of Biology, University of Tuebingen, Tuebingen, Germany
Keywords:
Abstract
evolution of sex;
fitness;
genetic diversity;
heritability;
natural selection;
occasional sex;
parthenogenesis;
Platyhelminthes;
pseudogamy;
reproduction.
One explanation for the success of sexual reproduction is that sex increases the
efficacy of natural selection. Recombination and segregation lead to fitness
variance among offspring which then offers a wider target for natural
selection. Consequently, adaptation to changing environments is accelerated
and population mean fitness will increase.We investigated whether low levels
of sex are associated with increased fitness variance and mean in parthenogenetic biotypes of the planarian flatworm Schmidtea polychroa. Parthenogenetic S. polychroa are triploid and reproduce clonally with occasional sexual
reproduction. By-products and measures of occasional sex are the local
presence of tetraploids and elevated levels of genotypic diversity. We
correlated the proportion of tetraploids and genotypic diversity with fitness
attributes of six genetically differentiated locations within one meta-population. Results indicate strong, positive correlations with variance and with
mean offspring number produced during a 5-week period. The ecological and
evolutionary implications for the maintenance of parthenogenetic S. polychroa
are discussed.
Introduction
Sexual reproduction is believed to be beneficial because it
creates genetic variation in fitness among offspring and
therefore increases the efficacy of natural selection. This
hypothesis originally dates back to Weismann (1886).
Several theories explaining the maintenance of sex are
based on Weismann’s principle, such as the Fisher–
Muller hypothesis, Muller’s ratchet and the deterministic
mutation hypothesis (Kondrashov, 1993; Burt, 2000).
For instance, through recombination and segregation,
independently arisen beneficial mutations can be united
in the same genome and therefore offspring with above
average fitness can be produced (Fisher–Muller hypothesis, Bell, 1982). Moreover, sex enhances the fixation of
beneficial mutations by separating them from deleterious
background (‘Ruby in the Rubbish’ hypothesis, Peck,
1994). As with beneficial mutations, sex also concenCorrespondence: Thomas D’Souza, Animal Evolutionary Ecology, Zoological Institute, Faculty of Biology, University of Tuebingen, Auf der
Morgenstelle 28, D-72076 Tuebingen, Germany.
Tel.: +49 (0)7071 2974842; fax: +49 (0)7071 295634;
e-mail: [email protected]
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trates deleterious mutations (Deterministic mutation
hypothesis). Offspring carrying deleterious mutations of
both parents will be negatively selected. Hence, sex
allows for the more efficient elimination of deleterious
mutations from the population (Kondrashov, 1984,
1988).
In purely clonal populations variability among offspring can be created only by mutations. Moreover, in
the absence of recombination and segregation the ability
to concentrate beneficial or harmful mutations into
single offspring is lacking. In addition, beneficial mutations can be trapped in a deleterious genetic background,
which reduces the likelihood of fixation (Peck, 1994;
Rice, 2002). Hence, adaptability of asexuals can only be
achieved under restricted conditions such as high rates of
beneficial mutations or large population sizes (Colegrave,
2002; De Visser & Rozen, 2005). Thus the response to
natural selection should be low in asexuals relative to
sexuals and, consequently, adaptation should be hampered (but see Doroszuk et al., 2006).
In a strictly Weismannian sense, the benefit of sex is an
increase in fitness variance, not mean, allowing a more
effective response to selection in the long term (Burt,
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Sex rate estimates and fitness in parthenogens
2000; Agrawal, 2006). However, in order for this to work
negative fitness correlations across loci are required
(Kondrashov, 1993; Barton & Charlesworth, 1998; Burt,
2000). In the presence of positive correlations, sex
actually causes decreased variance (Agrawal, 2006).
Moreover, destroying positive associations (e.g. favourable gene combinations) typically reduces mean fitness
(Barton & Charlesworth, 1998). Hence, the advantage of
sex is that it breaks up negative associations among loci,
which results in increased fitness variation (Burt, 2000;
Agrawal, 2006). Negative associations may be caused
deterministically by epistatic interactions between loci or
stochastically by genetic drift in finite populations (Kondrashov, 1993; Peters & Otto, 2003; De Visser & Elena,
2007). The effect of sex to increase genetic variance in
fitness is beneficial under constant selection if epistasis is
negative. Alternatively, fluctuating selection and ⁄ or
random genetic drift in finite populations may also create
those benefits of sex (Peters & Otto, 2003 and references
therein). Especially negative associations arising stochastically slow down natural selection (Hill–Robertson
effect), and therefore are likely to be longer preserved
than positive associations (Peters & Otto, 2003). Theoretical models including genetic drift as a source of
negative associations seem less restrictive and hence
more broadly applicable in explaining the ubiquity of sex
than models with negative epistasis (Otto & Gerstein,
2006).
Assuming negative associations among loci, the benefit of sex in increasing the efficiency of natural
selection applies both to individual and group selection
(Barton & Charlesworth, 1998; Burt, 2000). However,
in order to be strong enough to offset a twofold cost of
sex (Williams, 1975; Maynard Smith, 1978), group
selection is more important in Weismann’s argumentation: The selective advantage of a modifier gene that
increases the rate of recombination is much smaller
compared to effect of sexual clade competing with an
asexual clade (Burt, 2000; but see Holmström & Jensen,
2004).
Most evidence for Weismann’s principle focuses on the
increased adaptation rate of recombining compared with
nonrecombining populations. A faster response to selection is seen as an indicator for an increased genetic
variance in fitness by sex. Indications for faster adaptation has been shown for recombining regions ⁄ chromosomes compared with nonrecombining ones in several
Drosophila species (Rice & Chippindale, 2001; Bachtrog &
Charlesworth, 2002; Betancourt & Presgraves, 2002;
Bachtrog, 2003; Presgraves, 2005). Induction of sexual
episodes increased adaptation to novel environments in
yeast (Zeyl & Bell, 1997; Grimberg & Zeyl, 2005) and in
the green alga Chlamydomonas reinhardtii (Colegrave,
2002; Colegrave et al., 2002; Kaltz & Bell, 2002). However, direct evidence of how sex affects the mean and
variance of fitness in natural systems is scarce (Burt,
2000; Agrawal, 2006). Furthermore, it is difficult to draw
277
any general conclusions about the benefits of sex from
these few studies (Agrawal, 2006).
In the present study we ask whether rare sex is
accompanied by increased fitness variation and mean
fitness in sperm-dependent parthenogenetic biotypes of
the freshwater planarian Schmidtea (formerly Dugesia)
polychroa. We correlated the proportion of tetraploids and
genotypic diversity, used as estimates for the rate of sex
(see below), with mean fitness and fitness variance of six
highly genetically differentiated locations of the same
lake. In addition, further correlations and path analyses
were performed to show whether the putative effect of
rare sex on fitness is mediated by fertility (a relative
measure of embryo survival) or fecundity (an absolute
measure of female investment in cocoons).
Materials and methods
Model organism
Schmidtea polychroa is a nonselfing, simultaneously hermaphroditic flatworm with diploid, obligate sexual and
polyploid (mostly triploid or tetraploid) parthenogenetic
biotypes. The investigated meta-population exclusively
consists of parthenogenetic biotypes that produce their
eggs meiotically after premeiotic doubling, which restores
the maternal ploidy level. Crossing over does not lead to
genetic recombination as identical, duplicated sister
chromatids pair (Benazzi Lentati, 1970). Parthenogenetic
S. polychroa are sperm-dependent (pseudogamous), i.e.
allosperm is required to trigger zygote development, but
paternal genetic contribution to offspring is generally
suppressed (Benazzi Lentati, 1970; Fig. 1A,B [P]). Because parthenogens produce haploid, fertile sperm (Storhas et al., 2000), they do not rely on sexual spermdonors, which are absent in Central and Western Europe
(Beukeboom et al., 1996; Pongratz et al., 2003). This is
important as the production of fertile sperm allows for
occasional sex in otherwise parthenogenetic populations
(D’Souza et al., 2004, 2006). Sexual processes in parthenogenetic individuals result from a combination of at
least three mechanisms. First, triploid eggs can fail to
expel the triggering sperm leading to genome addition
and increase of offspring ploidy (3x fi 4x, Fig. 1A [S1]).
Second, tetraploid eggs can undergo meiosis without
premeiotic doubling resulting in diploid oocytes which
then fuse with haploid sperm resulting in triploid
offspring (4x fi 3x, Fig. 1B [S2]). This ploidy cycle from
triploidy to tetraploidy and back represents a two-step
form of sexual reproduction (Fig. 1C) and leads to stable
ploidy frequencies, despite low fitness of tetraploids
(D’Souza et al., 2005). Triploid karyotypes represent the
original parthenogenetic forms in S. polychroa as they
arose from diploid sexuals most probably after fertilization of unreduced eggs (Benazzi & Benazzi Lentati,
1976). Thus, tetraploids are considered a by-product of
this two-step sexual cycle and indicate the presence of
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T. G. D’SOUZA AND N. K. MICHIELS
(a)
(b)
BU
S1
S3
P
S1
S3
3x (c)
S2
BB
4x S3
P
S2
S3
LS
W
Fig. 1 Mating system in sperm-dependent parthenogenetic, triploid (a) and tetraploid (b) Schmidtea polychroa. The number of bars
indicates the ploidy level. Four different outcomes of sperm–egg
interaction are shown: (P) Pseudogamy: Sperm is used to trigger
zygote development and resulting offspring are clonally produced.
This applies both to triploids and tetraploids. The other mechanisms
include syngamy of polyploid eggs (filled bars) and haploid sperm
(open bars). (S1) Chromosome addition: Sperm pronucleus fuses
with triploid egg and fails to be expelled. Resulting offspring is
tetraploid. (S2) Chromosome loss: Tetraploid individual produces
diploid, reduced egg, which fuses with haploid sperm nucleus. The
resulting zygote then develops into triploid offspring. (S3) Chromosome displacement: Instead of paternal chromosomes one maternal
chromosome set is expelled from the zygote which results in
offspring with a mixture of paternal and maternal alleles, but
unaltered ploidy level. (c) The unique two-step cycle of occasional
sex including ploidy alterations from triploidy to tetraploidy and
back to triploidy. Alternatively, but more rarely sex may occur
without ploidy changes.
occasional sex in parthenogenetic populations (D’Souza
& Michiels, 2006). A third mechanism involves egg and
sperm fusion without ploidy change. In such cases, one
maternal chromosome set instead of a paternal one is
expelled from the zygote, thus restoring ploidy (D’Souza
et al., 2004, 2006; Fig. 1A,B [S3]).
SR
N
E
S
HE
5 km
WW
Fig. 2 Sample locations. All sample locations are situated on the
East shore of the lake Ammersee, a 46 km2, eutrophic lake in
Southern Germany. Location abbreviations: Buch (BU), Breitbrunn
(BB), Schloss Ried (SR), Lochschwaben (LS), Herrsching (HE),
Wartaweil (WW).
dark cycle) and temperature (16 C) conditions. Schmidtea polychroa produces spherical cocoons from which up
to 10 offspring hatch. Cocoons were collected daily for
35 days and kept isolated in compartments of ice-cube
trays under constant 20 C. Cocoons were checked
daily for offspring and were defined as sterile when
no offspring hatched after 45 days (ntotal = 1004,
nsterile = 141). Average hatching time (±SD) was 13.84 ±
1.79 days (noffspring = 3302).
Sampling and collection sites
A total of 254 flatworms were collected from six locations
(19–59 individuals per location) of the eastern shore of
the Ammersee, a eutrophic lake in Bavaria, Germany in
July 2004 (Fig. 2). Animals were sampled from stones
and transported to the laboratory. Sampling locations
had been analysed previously and found to be genetically
isolated as shown by significant differentiation and little
overlap in genotype composition (see also this study).
Sites differed in genotypic diversity and genotypic evenness, which is likely to be caused by varying degrees of
occasional sex (D’Souza & Michiels, 2006).
Culture conditions
Individuals were randomized and kept isolated in
200 mL plastic vials under constant light (12 : 12 light ⁄
Fitness measurements
Total number of offspring per individual (produced over
35 days) was used as the main fitness parameter.
Fecundity was defined as the total number of (fertile
and sterile) cocoons per individual and fertility as the
mean number of offspring per cocoon. Thus, individual
fitness is the product of fertility and fecundity per
individual. These parameters have been used as standard
measures of fitness before (Weinzierl et al., 1999; Storhas
et al., 2000; D’Souza et al., 2005). Importantly offspring
number and cocoon number show highly significant,
interclonal variation indicating a genetic basis of fitness
(D’Souza et al., 2005). For all further analyses fitness
parameters were determined for triploids only to exclude
any confounding effects resulting from ploidy differences
among locations.
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Sex rate estimates and fitness in parthenogens
Body size measurements
As body size is often correlated with fitness, we measured
planar body area. Digital images were taken from slowly
moving animals. Body area was then determined using
image-analysis software (ImageJ v1.34s, National Institutes of Health, Bethesda, Maryland, USA).
Karyology
To determine ploidy level, a modified protocol of Redi
et al. (1982) was used (Beukeboom et al., 1996). Briefly,
partially regenerated individuals were treated with
colchicine for 10 h to arrest cell cycle in metaphase.
Chromosomes were then counted using phase contrast
microscopy. As expected, only triploid (3x = 12) and
tetraploid (4x = 16) parthenogens were found.
Genotyping and genotypic diversity
Two highly polymorphic trinucleotide microsatellite loci
(SpATT12 and SpATT20) were used to determine twolocus genotypes. In the present study, the number of
alleles for SpATT12 and SpATT20 was 15 and 19
respectively. For details on DNA isolation, PCR conditions and fragment size analysis see Pongratz et al. (2001)
and D’Souza et al. (2004). In order to avoid that genetic
differences may be due to de novo mutations, genotypes
were pooled, when differing by fewer than three trinucleotide repeat units across all loci, leading to conservative diversity estimates (Bruvo et al., 2004; D’Souza &
Michiels, 2006).
Genotypic differentiation among locations was tested
by applying log-likelihood G-statistics (Goudet et al.,
1996) as described in D’Souza & Michiels (2006). For
this, multilocus genotypes were coded as different alleles
of a single locus. We used h, the Weir and Cockerham
estimator, for overall FST (Weir & Cockerham, 1984). For
further analysis of population differentiation we counted
the number of private genotypes (genotypes that are
restricted to one location) and unique genotypes (genotype that is represented by one individual) (Menken
et al., 1995).
Simpson’s index D for genotypic (or clonal) diversity
was used to characterize the genetic diversity of the
locations. D expresses the probability, that two randomly
sampled individuals are genotypically different. To correct for sampling size differences the following formula
was used:
!
m
X
n
2
Dg ¼
pi
1
n1
i¼1
where n = sampling size, pi = relative frequency of ith
genotype, m = number of multilocus genotypes. D ranges
from 0 (i.e. all individuals show the same genotype) to 1
(i.e. all individuals have different genotypes). In contrast
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to genotypic diversity, allelic diversity (also known as
genetic diversity or heterozygosity) was also calculated
but revealed only little variation across locations (mean
of both loci ranged from 0.733 to 0.880).
Estimates of sex rate
Occasional sex in S. polychroa includes the creation of
tetraploids from triploids and vice versa. These ploidy
transitions lead to a cyclic gene flow from the more
ancestral triploids to tetraploids and back (D’Souza et al.,
2004; Fig. 1C). Without these ploidy transitions triploids
will displace tetraploids within few generations as a
consequence of increased fitness of triploids compared
with tetraploids. Especially the recurrent production of
tetraploids leads to stable proportions of both ploidy types
(D’Souza et al., 2005). Thus tetraploids originate and are
maintained as a result of occasional sex. For that reason
tetraploids emerge as a by-product of occasional sex in
S. polychroa. That tetraploids indicate the rate of sex is
especially reflected by the strong, positive correlation
between tetraploid proportion and triploid genotypic
diversity (D’Souza & Michiels, 2006; this study). This
suggests that the production of tetraploids leads to an
increase of genotypic diversity among triploids. Hence,
especially the proportion of tetraploids can be used as a
reliable estimate of the rate of (rare) sex in S. polychroa.
The association between genotypic diversity (in contrast to genetic or allelic diversity) and fitness is less often
studied, but may provide valuable insights into the
ecological and evolutionary importance of genotypic
diversity (Reusch & Hughes, 2006). Genotypic diversity
is typically increased by sexual reproduction (Balloux
et al., 2003; Bengtsson, 2003), but is also affected by
other factors. For example, besides rare sex, mutations
and multiple origins from sexual ancestors are known to
influence genotypic diversity (Parker, 1979). Moreover,
migration and population size may also alter genotypic
diversity (Leimu et al., 2006). For S. polychroa we can
exclude mutations, multiple origins from sexuals and
migration as central sources of diversity: in S. polychroa
microsatellite mutation rate is low (D’Souza et al., 2006),
sexual conspecifics presumably have never been present
since the emergence of the investigated meta-population
(Beukeboom et al., 1996; Pongratz et al., 2003), and
migration is virtually absent (Pongratz et al., 2002;
D’Souza & Michiels, 2006). However, as population size
is difficult to determine in S. polychroa we cannot exclude
that locations differ in population size. Therefore, we
concentrate on the proportion of tetraploids as an
estimate of rare sex and use triploid genotypic diversity
to support the findings.
Statistical analysis
One major assumption of Weismann’s principle is that
fitness must be strongly heritable (Burt, 2000). For this
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T. G. D’SOUZA AND N. K. MICHIELS
we estimated genetic variation for offspring number
using a mixed-model A N O V A with genotype as a random
factor and location as a fixed factor, while genotype is
nested within location. Only genotypes with at least
four representatives were considered for the analysis.
Splitting phenotypic variance into genetic and environmental variance was performed according to Becker
(1992) and Vorburger (2005). Variance among genotypes served as an estimate for genetic variance and the
residual variance for environmental variance. The ratio
of genetic to phenotypic variance was used to estimate
broad-sense heritability, H2. An approximate standard
error for H2 was calculated using a formula taken from
Becker (1992), which corrects for unequal numbers of
individuals per genotype (Vorburger, 2005). The F-test
for the effect of the factor genotype resulting from the
mixed-model A N O V A was used to indicate whether
heritability of offspring number differed significantly
from zero.
The main goal of the study was to determine whether a
relationship exists between sex rate estimates (proportion
of tetraploids and genotypic diversity of triploids) and
fitness of triploids (expressed as offspring produced in
5 weeks). This effect was broken down into effects of sex
rate on fertility, fecundity and body size. For this we used
nonparametric Spearman rank correlations. For each
correlation the mean and variance of fitness, fertility,
fecundity and body size were taken per location to
correct for sample size differences and to avoid pseudoreplication.
Path analysis was applied to calculate the extent of
the effect of sex rate on triploid fitness via fertility or
fecundity. For this, path coefficients were estimated
as standardized partial regression coefficients using
maximum likelihood (Sokal & Rohlf, 2003). As there
is no nonparametric alternative to regression analysis,
coefficients were calculated although the formal
assumptions were not fulfilled. Therefore corresponding
P-values have to be taken with care. We used sex rate
as an exogenous, independent variable and fitness as a
dependent, endogenous variable. Fecundity, fertility and
size were endogenous, intermediary variables. See path
diagram for relationships (Fig. 3). Note, as fitness
(offspring number) is the product of fertility (offspring
number per cocoon) and fecundity (cocoon number),
there is no direct path leading from genotypic diversity
to fitness in the model. The unexplained variance (U) of
the dependent variable fitness was estimated as one
minus the squared total effect of genotypic diversity on
fitness (Sokal & Rohlf, 2003). Path analysis was separately performed for mean and variance of the endogenous variables. The reliability of both models was
tested with a goodness-of-fit v2-test. As the path model
with variances differed significantly from the observed
data (v23 = 17.997, P < 0.001), we only refer to the
results from the path analysis of means (v23 = 3.079,
P = 0.38).
Fecundity
0.751*
0.384***
0.296
–0.179
Proportion of
tetraploids
Size
Fitness
0.342
0.572
0.678***
0.784***
Fertility
U = 0.328
Fig. 3 Path diagram. The effect of genotypic diversity on mean
fitness of triploids mediated by mean fecundity, mean fertility and
mean body size of six locations. Arrows indicate the extent and
direction of a causal relationship between two variables. Path
coefficients are estimated as partial regression coefficients using
maximum likelihood. Significant relationships are indicated with
***P < 0.001 and *P < 0.05. See Methods for statistical analysis. U is
the proportion of variance of mean fitness which is not explained by
the model. Model and observed data do not significantly differ
(v23 = 3.079, P = 0.38). Approximately 67% of the variance in mean
fitness can be explained by genotypic diversity.
Genotypic diversity was calculated with G E N O D I V E
(Meirmans & Van Tienderen, 2004). F S T A T (v 2.9.3) was
used to test population differentiation (Goudet, 1995,
2001). Path analysis was performed using A M O S 5 and all
other analyses with J M P I N (v 5.1). Scatter plots were
created with Sigma Plot (v 9.0) (Systat Software Inc., San
Jose, California, USA). Means are given (± standard
deviation) unless stated otherwise.
Results
Genotypic diversity
We identified a total of 57 triploid and 19 tetraploid
genotypes from 254 individuals. Overall genotypic diversity of the six locations ranged from 0.476 to 0.924
(Table 1). When excluding tetraploids, the diversity
indices of triploids were slightly smaller. As predicted,
genotypic diversity of triploids increased significantly
with the proportion of tetraploids across sites (Spearmann, rs,6 = 0.943, P = 0.005).
Population differentiation
Highly significant genotypic differentiation indicates
strong sub-structuring of the meta-population (G-test,
P = 0.0001, h = 0.206). Approximately 84% of the 76
observed genotypes were private to a single location.
Hence, only 16% of the genotypes occurred in more than
one location. In addition, 70% of all observed genotypes are represented by a single individual (unique
genotype). The high proportion of private and unique
genotypes implies little overlap in clonal composition and
highlights the extreme genotypic differentiation among
locations, despite the fact that they were all along the
shoreline of the same lake.
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Sex rate estimates and fitness in parthenogens
Location
Sample
size
Proportion
tetraploids
Number of
genotypes
Private
genotypes
Unique
genotypes
Total
genotypic
diversity
Triploid
genotypic
diversity
BU
BB
SR
LS
HE
WW
Total
46
19
39
51
40
59
254
0.130
0.158
0.154
0.098
0.075
0.102
0.110
16
12
20
15
9
20
76
12
8
16
9
5
14
64
8
8
14
8
3
12
53
0.894
0.924
0.872
0.671
0.474
0.749
0.907
0.878
0.892
0.820
0.600
0.387
0.700
0.883
Table 2 Results from mixed-model A N O V A on offspring number as
response variable and factor genotype (random) nested within factor
location (fixed). The significant effect of genotype shows strong
heritability of offspring number (H2 = MSgenotype ⁄ (MSgenotype +
MSresidual) = 0.755 ± 0.082.
Source of variation
df
SS
MS
F-ratio
P
Genotype
Location (genotype)
Residual
Total
10
4
147
161
5761.650
3505.570
27468.044
35989.809
576.165
876.393
186.857
3.083
4.690
0.001
0.001
HE
Mean fitness of triploids ± sd
Table 1 Sample sizes and genetic characteristics of each location. Position of sampling
locations is depicted in Fig. 1.
LS WW
BU
SR BB
40
30
20
10
0
0.08
0.10
0.12
0.14
0.16
Proportion of tetraploids
Heritability of fitness
Mixed-model A N O V A revealed substantial variation
among locations and among genotypes for offspring
number (Table 2). The factors location as well as genotype contribute significantly to the variation in fitness
(both P = 0.001). The significant effect of genotype also
indicates that broad-sense heritability of trait offspring
number differs significantly from zero. Fitness exhibits a
high heritability value of 0.755 ± 0.082 (H2 ± SE).
Proportion of tetraploids and fitness attributes of
triploids
The variance and mean of offspring number of triploids
increased with the proportion of tetraploids (Variance:
Spearman, rs,6 = 0.886, P = 0.019; Mean: Spearman,
rs,6 = 0.886, P = 0.019; Fig. 4). To verify that fertility or
fecundity accounted for the relationship between proportion of tetraploids and fitness of triploids, we also
correlated fertility and fecundity with proportion of
tetraploids. Neither mean nor variance of fertility and
fecundity was significantly correlated with proportion of
tetraploids (Table 3a). Moreover, there was no significant
relationship between proportion of tetraploids and (mean
and variance of) body size (Table 3a). Considering
triploids and tetraploids for the calculation of population’s fitness attributes does not change significances
(results not shown).
Fig. 4 Correlation between proportion of tetraploids and fitness of
triploids. Proportion of tetraploids, an estimate for occasional sex, is
significantly, positively correlated with mean fitness (Spearman,
rs,6 = 0.886, P = 0.019) and fitness variance (Spearman, rs,6 = 0.886,
P = 0.019). Names of the locations are given in the upper part of the
diagram.
Triploid genotypic diversity and fitness attributes of
triploids
Correlations between triploid genotypic diversity and
mean ⁄ variance of fitness, fertility, fecundity and body
size of triploids revealed similar results as with proportion
of tetraploids and fitness attributes: only the mean and
variance of fitness correlates significantly with triploid
genotypic diversity (Table 3b).
Path analysis
We used path analysis to partition the effect of proportion of tetraploids on mean fitness of triploids through
effects mediated by the mean of fertility, fecundity and
body size. The path model (Fig. 3), explained approximately 67% of the variance in mean fitness across the six
populations (R2 = 0.672, U = 0.328). Observed data and
path model did not differ significantly (v23 = 3.079,
P = 0.38) suggesting a good fit of the model. The total
effect (direct + indirect via body size) of tetraploid
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Table 3 Results of the Spearman rank correlations between sex
rates estimates, (a) proportion of tetraploids, (b) triploid genotypic
diversity and fitness parameters of triploids. Only correlations with
mean fitness and fitness variance revealed significant results (n = 6).
Correlation coefficient (rs)
(a)
Fitness
Variance
Mean
Fertility
Variance
Mean
Fecundity
Variance
Mean
Body size
Variance
Mean
(b)
Fitness
Variance
Mean
Fertility
Variance
Mean
Fecundity
Variance
Mean
Body size
Variance
Mean
P-value
0.886
0.886
0.019
0.019
0.771
0.771
0.072
0.072
0.486
0.600
0.329
0.208
)0.086
0.257
0.872
0.623
0.943
0.886
0.005
0.019
0.771
0.771
0.072
0.072
0.543
0.486
0.266
0.329
)0.143
0.0857
0.787
0.872
proportion on fecundity is R = 0.751 and on fertility
R = 0.784. Combined with the effect of fecundity (R =
0.384) and fertility (R = 0.678) on fitness, this indicates
that the impact of tetraploid proportion on fitness via
fertility (R = 0.784Æ0.678 = 0.531) is stronger than the
effect via fecundity (R = 0.751Æ0.384 = 0.288). In other
words, 28% (R2 = 0.282) of the variation in mean
fitness can be explained by tetraploid proportion via
fertility and 8.3% (R2 = 0.083) by tetraploid proportion
via fecundity. Path analyses with triploid genotypic
diversity as the exogenous, independent variable
revealed similar results and trends (data not shown).
Discussion
Indications for increased efficacy of natural selection
We showed that increased presence of tetraploids, a byproduct of occasional sex, is associated with increased
fitness variance and mean fitness across six genetically
isolated subpopulations of parthenogenetic S. polychroa.
This pattern is in accordance with Weismann’s principle
as it shows that (occasional) sex increases fitness variance
and mean fitness, making natural selection more
effective.
To our knowledge the present study provides the first
empirical support to validate Weismann’s principle in
natural subpopulations with variable degrees of sex.
However, describing correlative effects in ‘natural experiments’ like these, does not exclude other differences
affecting fitness traits between locations. Local subpopulations may differ in age, food quality, resource availability and other ecological or genetic factors.
One alternative explanation for the significant relationship between proportion of tetraploids and fitness
could be that tetraploids may show a higher fitness mean
and variance compared with triploids. However, we can
exclude this possibility for the following reasons: First,
contrary to other systems (for a review see Otto &
Whitton, 2000), higher ploidy level is not associated with
increased fitness in S. polychroa, as tetraploids exhibit
reduced fitness compared with triploids (D’Souza et al.,
2005). Secondly, we considered only triploids in the
fitness calculation making the proportion of tetraploids as
an estimate of sex doubtless independent from the
populations’ fitness parameters. Hence, fitness effects
caused by different ploidy levels do not confound the
results.
Locations may vary in mutation rates caused, e.g. by
different levels of stress, mutagenic substances, or
temperature. Increased mutation rates may lead to
increased defects in gametogenesis causing the formation of more tetraploid individuals, and increased
fitness variance. Failures during oogenesis in triploid
S. polychroa should also lead to the production of
aneuploid or hexaploid offspring after meiotic ⁄ mitotic
dysfunctions or chromosome doubling respectively.
However, as such ploidy types have been never
observed in the field (Beukeboom et al., 1996; D’Souza
& Michiels, 2006) nor in laboratory experiments
(Benazzi Lentati, 1970, 1979), they are either not
produced or not viable. In the case of an early
mortality mean fitness of those populations with
increased mutations rates (and therefore high tetraploid
proportion) should be reduced, which contradicts our
findings.
Therefore, the most parsimonious explanation of the
observed fitness pattern in S. polychroa is indeed the
proportion of tetraploids and other sex-related features.
Although we did not experimentally control the
amount of sex, the strength of this study is that we
used a system of naturally varying degrees of sex
within a single meta-population. Contrary to other
systems, we did not artificially induce sex, which may
cause other confounding effects. For instance, in
Chlamydomonas reinhardtii and yeast, sex induction by
starvation leads to higher mutation rates (Marini et al.,
1999; Goho & Bell, 2000). For C. reinhardtii it has been
shown that higher mutation rates already lead to an
increased variance in fitness, which is also expected to
be the result of sexual reproduction (Goho & Bell,
2000).
ª 2007 THE AUTHORS. J. EVOL. BIOL. 21 (2008) 276–286
JOURNAL COMPILATION ª 2007 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Sex rate estimates and fitness in parthenogens
Weismann’s principle and occasional sex
Weismann’s principle and other theories of sex were
originally developed to compare obligate sexuals and
obligate asexuals. A theoretical model by Burt (2000)
extends this limitation by showing that Weismann’s
principle is also valid for species that only have sex
occasionally. Low levels of sex and recombination are
sufficient to increase mean fitness by enhancing the
efficacy of natural selection in predominantly clonal
populations (Burt, 2000). Moreover, even single episodes
of recombination after long phases of asexuality may
release most of the hidden genetic variation. Consequently, the rate of phenotypic evolution after sex may
increase to an extent comparable with continuously
sexuals (Lynch & Gabriel, 1983). This allows parthenogens to rapidly adjust to new selection pressures and lead
to an increased probability of long-term survival (Lynch
& Gabriel, 1983).
Mutations or environmental factors explaining sex?
Many models explaining the maintenance of sex rely on
the diversifying character of recombination and segregation. They can be classified as either mutational models
(Deterministic mutation hypothesis, Muller’s ratchet) or
environmental models (Fisher–Muller hypothesis, Red
Queen) (Hurst & Peck, 1996; West et al., 1999). Comparisons between sexual and parthenogenetic individuals
revealed that major predictions of both models are found
in S. polychroa. Parthenogens showed both indications for
increased mutational load (Storhas et al., 2000) as well as
parasite load (Michiels et al., 2001). Moreover, parthenogenetic lineages show significant correlation between
mutation and parasite load giving evidence to the
so-called pluralistic approach (West et al., 1999; WestEberhard, 2005), which combines both mutational and
environmental models (Bruvo et al., 2007).
Reduction in fertility most likely results from developmental problems and increased embryo mortality which
in turn was used as an indicator for the accumulation of
deleterious mutations in previous studies (Storhas et al.,
2000; Bruvo et al., 2007). However, we could not identify
any significant correlation between rate of sex and
fertility. This indicates that either the sex rate is too
low to yield a clear effect on mutational load or that
deleterious mutations are not the only factor maintaining
occasional sex.
The interplay of occasional sex and fitness
The effect of proportion of tetraploids on fitness traits is
only significant for total number of offspring, which was
used as the primary fitness estimate. Compared to
published accounts, broad-sense heritability of total
offspring number is extremely high in S. polychroa (e.g.
Vorburger, 2005). This stresses the genetic basis of fitness
283
which is supported by our previous finding of significant
interclonal differences in several fitness traits (D’Souza
et al., 2005). The mixed-model A N O V A revealed not only
significant fitness differences between clones, but also
between locations. However, total number of offspring
depends on the number of cocoons an individual
produces (fecundity) and the number of offspring per
cocoon (fertility). A previous study revealed that triploid
and tetraploid clonal lineages differ in fecundity, but not
in fertility, resulting in a higher total offspring production
of triploids (D’Souza et al., 2005). Hence, one would
expect that locations with large proportions of tetraploids
show a reduced fecundity. However, there was no
evidence for such a relationship in the present study
(Table 3a), indicating that the benefits of occasional sex
may compensate for the fecundity disadvantage of
tetraploids.
Fertility is largely determined by the reproductive
mode of the sperm donor in S. polychroa: sperm from
obligate sexuals increases fertility of parthenogenetic
sperm receivers (Storhas et al., 2000). Additionally,
sperm from occasionally sexual parthenogens increases
fertility of more clonal receivers (D’Souza et al., 2007).
Although no significant relationship between both sex
estimates and fertility was found, the importance of
fertility on the sex–fitness relationship is indicated by
results of the path analysis. The relative contribution of
fertility is high, while fecundity merely plays a minor role
(Fig. 3).
Ecological implications of genotypic diversity
The relationship between genetic diversity (in the sense of
allele diversity, population heterozygosity) and fitness is
commonly investigated. Genetic diversity is used as an
indicator of inbreeding and reduced fitness is expected
when genetic diversity is low due to inbreeding depression, genetic drift, fixation of deleterious mutations and
other processes (David, 1998; Booy et al., 2000; Hansson
& Westerberg, 2002; Reed & Frankham, 2003; Field et al.,
2007). However, the ecological and evolutionary significance of genotypic diversity is less often studied. Using
manipulative field experiments, it was demonstrated that
genotypic diversity of the seagrass Zostera marina enhances ecosystem stability and therefore buffers against
biotic or abiotic disturbances (Hughes & Stachowicz,
2004; Reusch et al., 2005; Reusch & Hughes, 2006).
Transects with high genotypic diversity recovered faster
from grazing (Hughes & Stachowicz, 2004) and after a
high temperature period compared with monoclonal
transects (Reusch et al., 2005). Moreover, genotypic
diversity increased resistance against parasites in leafcutting ants (Hughes & Boomsma, 2004). Similarly, a
theoretical model showed that the presence of parasites
selects for clonal diversity and that genetically diverse
clones can outcompete sexual populations in the absence
of deleterious mutations (Lively & Howard, 1994).
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T. G. D’SOUZA AND N. K. MICHIELS
Genotypically diverse populations also bear a competitive
advantage towards monoclonal populations in Daphnia
(Tagg et al., 2005a,b). Genotypic diversity increases
competitiveness in invading and resisting invasions of
monoclonal populations (Tagg et al., 2005b). In summary, high genotypic diversity serves as a buffer against
interfering biotic and abiotic disturbances and may also
aid in the persistence of parthenogenetic populations of
S. polychroa. Through increased competitive ability,
genotypically diverse subpopulations may resist displacement by the immigrant planarian Girardia (Dugesia)
tigrina, which has expanded its distribution across Britain
during the last 50 years (Young & Reynoldson, 1999) and
has also recently been found in lake Ammersee (T.G.
D’Souza, personal observation).
Conclusions
In summary, we found indications that occasional sex in
parthenogenetic S. polychroa leads to an increase in fitness
variance at the local population level, which in turn
increases mean fitness, which can be interpreted as a
signature of a more effective natural selection. Consequently, occasional sex may prevent the extinction of
parthenogenetic subpopulations and explain the success
of this particular type of parthenogenesis in this species.
Acknowledgments
We thank Rebecca Schulte and Vera Bellenhaus for help
in collecting flatworms and Gaby Niester and Barbara
Hasert for technical assistance in the laboratory. We are
grateful to Claudia Böhnisch, Beatriz Sanchez Navarro,
Rebecca Schulte Nadine Timmermeyer and Hinrich
Schulenburg for fruitful discussions. Thanks to Christoph
Vorburger for providing advice in heritability analysis.
Paul Sunnucks, Stu Field, Beatriz Sanchez Navarro and
two anonymous referees gave valuable comments to
improve earlier versions of the manuscript. This study
was supported by a grant from the German Science
Foundation (DFG) no. MI 482 ⁄ 11-1.
References
Agrawal, A.F. 2006. Evolution of sex: why do organisms shuffle
their genotypes? Curr. Biol. 16: R696–R704.
Bachtrog, D. 2003. Adaptation shapes patterns of genome
evolution on sexual and asexual chromosomes in Drosophila.
Nat. Genet. 34: 215–219.
Bachtrog, D. & Charlesworth, B. 2002. Reduced adaptation of a
non-recombining neo-Y chromosome. Nature 416: 323–326.
Balloux, F., Lehmann, L. & de Meeus, T. 2003. The population
genetics of clonal and partially clonal diploids. Genetics 164:
1635–1644.
Barton, N.H. & Charlesworth, B. 1998. Why sex and recombination? Science 281: 1986–1990.
Becker, W.A. 1992. Manual of Quantitative Genetics. Academic
Enterprises, Pullman, WA.
Bell, G. 1982. The Masterpiece of Nature. The Evolution and Genetics
of Sexuality. University of California press, Berkely and Los
Angeles, CA.
Benazzi, M. & Benazzi Lentati, G. 1976. Platyhelminthes.
Gebrueder Borntraeger, Berlin, Stuttgart.
Benazzi Lentati, G. 1970. Gametogenesis and egg fertilization in
planarians. Int. Rev. Cytol. 27: 101–179.
Benazzi Lentati, G. 1979. Polypoidy and types of development in
the Triclad Dugesia lugubris s.l.: interaction between the ploidy
level and the origin of amphimixis or pseudogamy. Caryologia
32: 247–263.
Bengtsson, B.O. 2003. Genetic variation in organisms with
sexual and asexual reproduction. J. Evol. Biol. 16: 189–199.
Betancourt, A.J. & Presgraves, D.C. 2002. Linkage limits the
power of natural selection in Drosophila. Proc. Natl. Acad. Sci.
USA 99: 13616–13620.
Beukeboom, L.W., Weinzierl, R.P., Reed, K.M. & Michiels, N.K.
1996. Distribution and origin of chromosomal races in the
freshwater planarian Dugesia polychroa (Turbellaria: Tricladida). Hereditas 124: 7–15.
Booy, G., Smulders, M.J.M., Vosman, B., Hendriks, R.J.J. & Van
Groenendael, J.M. 2000. Genetic diversity and the survival of
populations. Plant. Biol. 2: 379–395.
Bruvo, R., Michiels, N.K., D’Souza, T.G. & Schulenburg, H. 2004.
A simple method for the calculation of microsatellite genotype
distances irrespective of ploidy level. Mol. Ecol. 13: 2101–2106.
Bruvo, R., Schulenburg, H., Storhas, M. & Michiels, N.K. 2007.
Synergism between mutational meltdown and Red Queen in
parthenogenetic biotypes of the freshwater planarian Schmidtea polychroa. Oikos 116: 313–323.
Burt, A. 2000. Perspective: Sex, recombination, and the efficacy
of selection - Was Weismann right? Evolution 54: 337–351.
Colegrave, N. 2002. Sex releases the speed limit on evolution.
Nature 420: 664.
Colegrave, N., Kaltz, O. & Bell, G. 2002. The ecology and
genetics of fitness in Chlamydomonas. VIII. The dynamics of
adaptation to novel environments after a single episode of sex.
Evolution 56: 14–21.
D’Souza, T.G. & Michiels, N.K. 2006. Genetic signatures of
occasional sex in parthenogenetic subpopulations of the
freshwater planarian Schmidtea polychroa. Freshw. Biol. 51:
1890–1900.
D’Souza, T.G., Storhas, M., Schulenburg, H., Beukeboom, L.W.
& Michiels, N.K. 2004. Occasional sex in an ‘asexual’
polyploid hermaphrodite. Proc. R. Soc. Lond. B Biol. Sci. 271:
1001–1007.
D’Souza, T.G., Storhas, M. & Michiels, N.K. 2005. The effect of
ploidy level on fitness in parthenogenetic flatworms. Biol. J.
Linn. Soc. 85: 191–198.
D’Souza, T.G., Schulte, R.D., Schulenburg, H. & Michiels, N.K.
2006. Paternal inheritance in parthenogenetic forms of the
planarian Schmidtea polychroa. Heredity 97: 97–101.
D’Souza, T.G., Bellenhaus, V., Wesselmann, R. & Michiels, N.K.
2007. Sperm length and quality in sperm-dependent parthenogens. Biol. J. Linn. Soc. 92, in press.
David, P. 1998. Heterozygosity-fitness correlations: new perspectives on old problems. Heredity 80: 531–537.
De Visser, J.A.G.M. & Elena, S.F. 2007. The role of sex: empirical
insights into the roles of epistasis and drift. Nat. Rev. Genet. 8:
139–149.
De Visser, J.A.G.M. & Rozen, D.E. 2005. Limits to adaptation in
asexual populations. J. Evol. Biol. 18: 779–788.
ª 2007 THE AUTHORS. J. EVOL. BIOL. 21 (2008) 276–286
JOURNAL COMPILATION ª 2007 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
Sex rate estimates and fitness in parthenogens
Doroszuk, A., Wojewodzic, M.W. & Kammenga, J.E. 2006.
Rapid adaptive divergence of life-history traits in response to
abiotic stress within a natural population of a parthenogenetic
nematode. Proc. R. Soc. Lond. B Biol. Sci. 273: 2611–2618.
Field, S.G., Lange, M., Schulenburg, H., Velavan, T.P. &
Michiels, N.K. 2007. Genetic diversity and parasite defense
in a fragmented urban metapopulation of earthworms. Anim.
Conserv. 10: 162–175.
Goho, S. & Bell, G. 2000. Mild environmental stress elicits
mutations affecting fitness in Chlamydomonas. Proc. R. Soc. Lond.
B Biol. Sci. 267: 123–129.
Goudet, J. 1995. FSTAT (vers.1.2): a computer program to
calculate F-statistics. J. Hered. 86: 485–486.
Goudet, J. 2001. FSTAT, a program to estimate and test gene
diversities and fixation indices (version 2.9.3). Available from
http://www.unil.ch/izea/softwares/fstat.html.
Goudet, J., Raymond, M., Rousset, F. & De Meeüs, T. 1996.
Testing differentiation in diploid populations. Genetics 144:
1933–1940.
Grimberg, B. & Zeyl, C. 2005. The effects of sex and mutation
rate on adaptation in test tubes and to mouse hosts by
Saccharomyces cerevisiae. Evolution 59: 431–438.
Hansson, B. & Westerberg, L. 2002. On the correlation between
heterozygosity and fitness in natural populations. Mol. Ecol.
11: 2467–2474.
Holmström, K. & Jensen, H.J. 2004. Who runs fastest in an
adaptive landscape: sexual versus asexual reproduction. Physica A Statist. Mech. Appl. 337: 185–195.
Hughes, W.O.H. & Boomsma, J.J. 2004. Genetic diversity and
disease resistance in leaf-cutting ant societies. Evolution 58:
1251–1260.
Hughes, A.R. & Stachowicz, J.J. 2004. Genetic diversity
enhances the resistance of a seagrass ecosystem to disturbance. Proc. Natl. Acad. Sci. USA 101: 8998–9002.
Hurst, L.D. & Peck, J.R. 1996. Recent advances in understanding
of the evolution and maintenance of sex. Trends Ecol. Evol. 11:
46–52.
Kaltz, O. & Bell, G. 2002. The ecology and genetics of fitness in
Chlamydomonas. XII. Repeated sexual episodes increase rates of
adaptation to novel environments. Evolution 56: 1743–1753.
Kondrashov, A.S. 1984. Deleterious mutations as an evolutionary factor. I. The advantage of recombination. Genet. Res. 44:
199–217.
Kondrashov, A.S. 1988. Deleterious mutations and the evolution of sexual reproduction. Nature 336: 435–440.
Kondrashov, A.S. 1993. Classification of hypothesis on the
advantage of amphimixis. J. Hered. 84: 372–387.
Leimu, R., Mutikainen, P., Koricheva, J. & Fischer, M. 2006.
How general are positive relationships between plant population size, fitness and genetic variation? J. Ecol. 94: 942–952.
Lively, C.M. & Howard, R.S. 1994. Selection by parasites for
clonal diversity and mixed mating. Philos. Trans. R. Soc. Lond.
B Biol. Sci. 346: 271–281.
Lynch, M. & Gabriel, W. 1983. Phenotypic evolution and
parthenogenesis. Am. Nat. 122: 745–764.
Marini, A., Matmati, N. & Morpurgo, G. 1999. Starvation in
yeast increases non-adaptive mutation. Curr. Genet. 35: 77–81.
Maynard Smith, J. 1978. The Evolution of Sex. Cambridge
University Press, Cambridge, London, New York, Melbourne.
Meirmans, P.G. & Van Tienderen, P.H. 2004. GENOTYPE and
GENODIVE: two programs for the analysis of genetic diversity
of asexual organisms. Mol. Ecol. Notes 4: 792–794.
285
Menken, S.B.J., Smit, E. & Den Nijs, H.C.M. 1995. Genetical
population structure in plants: gene flow between diploid
sexual and triploid asexual dandelions (Taraxacum section
Ruderalia). Evolution 49: 1108.
Michiels, N.K., Beukeboom, L.W., Pongratz, N. & Zeitlinger, J.
2001. Parthenogenetic flatworms have more symbionts than
their coexisting, sexual conspecific, but does this support the
Red Queen? J. Evol. Biol. 14: 110–119.
Otto, S.P. & Gerstein, A.C. 2006. Why have sex? The populations
genetics of sex and recombination Biochem. Soc. Trans. 34: 519–
522.
Otto, S.P. & Whitton, J. 2000. Polyploid incidence and evolution. Annu. Rev. Genet. 34: 401–437.
Parker, E.D. 1979. Ecological Implications of clonal diversity in
parthenogenetic morphospecies. Am. Zool. 19: 753–762.
Peck, J.R. 1994. A ruby in the rubbish - Beneficial mutations,
deleterious mutations and the evolution of sex. Genetics 137:
597–604.
Peters, A.D. & Otto, S.P. 2003. Liberating genetic variance
through sex. Bioessays 25: 533–537.
Pongratz, N., Gerace, L., Alganza, A.M., Beukeboom, L.W. &
Michiels, N.K. 2001. Microsatellite development and inheritance in the planarian flatworm Schmidtea polychroa. Belg. J.
Zool. 131: 71–75.
Pongratz, N., Gerace, L. & Michiels, N.K. 2002. Genetic differentiation within and between populations of a hermaphroditic
freshwater planarian. Heredity 89: 64–69.
Pongratz, N., Storhas, M., Carranza, S. & Michiels, N.K. 2003.
Phylogeography of competing sexual and parthenogenetic
forms of a freshwater flatworm: patterns and explanations.
BMC Evol. Biol. 3.
Presgraves, D.C. 2005. Recombination enhances protein adaptation in Drosophila melanogaster. Curr. Biol. 15: 1651–1656.
Redi, C.A., Garagna, S. & Pellicciari, C. 1982. Chromosome
preparation from planarian blastemas: a new procedure
suitable for cytogenetic and cytochemical studies. Stain Technol. 57: 190–192.
Reed, D.H. & Frankham, R. 2003. Correlation between fitness
and genetic diversity. Conserv. Biol. 17: 230–237.
Reusch, T.B.H. & Hughes, A.R. 2006. The emerging role of
genetic diversity for ecosystem functioning: Estuarine macrophytes as models. Estuar. Coast 29: 170–175.
Reusch, T.B.H., Hämmerli, A., Ehlers, A. & Worm, B. 2005.
Ecosystem recovery after climatic extremes enhanced by
genotypic diversity. Proc. Natl. Acad. Sci. USA 102: 2826–
2831.
Rice, W.R. 2002. Experimental tests of the adaptive significance
of sexual recombination. Nat. Rev. Genet. 3: 241–251.
Rice, W.R. & Chippindale, A.K. 2001. Sexual recombination and
the power of natural selection. Science 294: 555–559.
Sokal, R.R. & Rohlf, F.J. 2003. Biometry, 3d edn. W.H. Freeman
and Company, New York.
Storhas, M., Weinzierl, R.P. & Michiels, N.K. 2000. Paternal sex
in parthenogenetic planarians: a tool to investigate the
accumulation of deleterious mutations. J. Evol. Biol. 13: 1–8.
Tagg, N., Doncaster, C.P. & Innes, D.J. 2005a. Resource competition between genetically varied and genetically uniform
populations of Daphnia pulex (Leydig): Does sexual reproduction confer a short-term ecological advantage? Biol. J. Linn.
Soc. 85: 111–123.
Tagg, N., Doncaster, C.P. & Innes, D.J. 2005b. Outcomes
of reciprocal invasions between genetically diverse and
ª 2007 THE AUTHORS. J. EVOL. BIOL. 21 (2008) 276–286
JOURNAL COMPILATION ª 2007 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY
286
T. G. D’SOUZA AND N. K. MICHIELS
genetically uniform populations of Daphnia obtusa (Kurz).
Oecologia 143: 527–536.
Vorburger, C. 2005. Positive genetic correlations among major
life-history traits related to ecological success in the aphid
Myzus persicae. Evolution 59: 1006–1015.
Weinzierl, R.P., Schmidt, P. & Michiels, N.K. 1999. High
fecundity and low fertility in parthenogenetic planarians.
Invertebr. Biol. 118: 87–94.
Weir, B.S. & Cockerham, C.C. 1984. Estimating F-statistics for
the analysis of population structure. Evolution 38:
1358–1370.
Weismann, A. 1886. The significance of sexual reproduction in
the theory of natural selection. In: Essays Upon Heredity and
Kindred Biological Problems (E. B. Poulton, S. Schönland & A. E.
Shipey, eds), pp. 251–332. Clarendon Press, Oxford.
West, S.A., Lively, C.M. & Read, A.F. 1999. A pluralist approach
to sex and recombination. J. Evol. Biol. 12: 1003–1012.
West-Eberhard, M.J. 2005. The maintenance of sex as a
developmental trap due to sexual selection. Q. Rev. Biol. 80:
47–53.
Williams, G. 1975. Sex and Evolution. Princeton University Press,
Princeton, NJ.
Young, J.O. & Reynoldson, T.B. 1999. Continuing dispersal of
freshwater triclads (Platyhelminthes; Turbellaria) in Britain
with particular reference to lakes. Freshw. Biol. 42: 247–262.
Zeyl, C. & Bell, G. 1997. The advantage of sex in evolving yeast
populations. Nature 388: 465–468.
Received 6 August 2007; revised 13 September 2007; accepted 14
September 2007
ª 2007 THE AUTHORS. J. EVOL. BIOL. 21 (2008) 276–286
JOURNAL COMPILATION ª 2007 EUROPEAN SOCIETY FOR EVOLUTIONARY BIOLOGY