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J Evol Biol. 2020;00:1–12.
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1wileyonlinelibrary.com/journal/jeb
Received: 30 October 2018
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Accepted: 22 M ay 2020
DOI : 10.1111/j eb.13658
RESEARCH PAPER
Antagonistic species interaction drives selection for sex in a
predator–prey system
Hanna R. Koch | Sophia Wagner | Lutz Becks
This is an op en access arti cle under the ter ms of the Creative Commons Attribution L icense, which pe rmits use, dis tribu tion and reprod uction in any med ium,
provide d the original wor k is properly cited.
© 2020 The Authors. Journal of Evolutionary B iology publish ed by John W iley & Sons Ltd on behalf of European So ciety f or Evoluti onar y Biolog y
The pee r review histor y for this arti cle is available at h ttps://publo ns.com/publ o n/10.1111/jeb.13658
Community Dy namic s Group, D epar tment
of Evolutionary Ecology, Max Planck
Instit ute for Evolutionary Biology, D-Plön,
Germany
Correspondence
Hanna Koch, Community D ynamics Group,
Depar tment of Evolutionary Ecology, Max
Planck Institu te for Evolutionar y Biology,
D-Plön, Germany.
Email: hkoch@evolbio.mpg.de
Abstract
The evolutionary maintenance of sexual reproduction has long challenged biologists
as the majority of species reproduce sexually despite inherent costs. Providing a gen-
eral explanation for the evolutionary success of sex has thus proven difficult and
resulted in numerous hypotheses. A leading hypothesis suggests that antagonistic
species interaction can generate conditions selecting for increased sex due to the
production of rare or novel genotypes that are beneficial for rapid adaptation to re-
current environmental change brought on by antagonism. To test this ecology-based
hypothesis, we conducted experimental evolution in a predator (rotifer)–prey (algal)
system by using continuous cultures to track predator–prey dynamics and in situ rates
of sex in the prey over time and within replicated experimental populations. Overall,
we found that predator-mediated fluctuating selection for competitive versus de-
fended prey resulted in higher rates of genetic mixing in the prey. More specifically,
our results showed that fluctuating population sizes of predator and prey, coupled
with a trade-off in the prey, drove the sort of recurrent environmental change that
could provide a benefit to sex in the prey, despite inherent costs. We end with a dis-
cussion of potential population genetic mechanisms underlying increased selection
for sex in this system, based on our application of a general theoretical framework for
measuring the effects of sex over time, and interpreting how these effects can lead
to inferences about the conditions selecting for or against sexual reproduction in a
system with antagonistic species interaction.
KEY WORDS
Chlamydomonas, effects of sex, evolution of sexual reproduction, experimental evolution,
fluctuating selection, predator–prey, trade-off
1 | INTRODUCTION
Despite inherent costs (Bell, 1982; Maynard Smith, 1978;
Williams, 1975), sexual reproduction has been shown to be advan-
tageous in the face of selection by interacting or coevolving species
(Brockhurst et al., 2014; Busch, Neiman, & Koslow, 2004; Ellison,
Cable, & Consuegra, 2011; Greeff & Schmid-Hempel, 2010; Haafke,
Abou Chakra, & Becks, 2016; Jokela, Dybdahl, & Lively, 2009;
Lively, Craddock, & Vrijenhoek, 1990; Lively & Morran, 2014;
Morran, Schmidt, Gelarden, Parrish, & Lively, 2011; Vergara, Jokela,
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KOCH et al .
& Lively, 2014). If species interactions are antagonistic and recur-
rent, as may occur in predator–prey or host–parasite systems, the
ensuing fluctuating environment can cause populations to be con-
tinuously moved away from local fitness optima where their genetic
associations already match the current environmental conditions.
Organisms must then rapidly adapt to the novel conditions which
can provide a benefit to sex (Barton, 1995; Becks & Agrawal, 2010;
Charlesworth, 1993; Haafke et al., 2016; Korol & Iliadi, 1994; Lynch
& Deng, 1994; Otto & Nuismer, 2004; Peters & Lively, 1999).
This idea has been formalized into the Red Queen hypothesis
(RQH). It suggests that coevolution of host and parasite can drive the
evolution of sex through negative frequency-dependent selection
where common genotypes evoke a genetic response in the antag-
onist, resulting in a fluctuating environment composed of continual
biotic interaction (Bell, 1982; Jaenike, 1978). Related to the RQH are
early population genetic models considering species interactions for
the maintenance of sex, which suggest that interactions without co-
ev olu t iona r y cha nge ca n also se lect fo r sex wh en fl uctua t ion s in pop-
ulation sizes of interacting species generate a continuously changing
environment (Bell, 1982; Jaenike, 1978). Within a predator–prey sys-
tem, changing predator densities and predation pressure can lead
to fluctuations in selection for prey defence when predation pres-
sure is high, and for prey competition when it is low, given the fre-
quently observed trade-off in these two traits (Kasada, Yamamichi,
& Yoshida, 2014; Lind et al., 2013; Yoshida, Hairston, & Ellner, 2004).
Even tho ugh fluctuation s in predator–pr ey popula tion sizes are com-
mon in nature (Kendall, Prendergast, & Bjornstad, 1998), can lead
to rapid adaptation in prey (A grawal, Hastings, Johnson, Maron, &
Salminen, 2012; Friman, Jousset, & Buckling, 2014) and to fluctuat-
ing selection de pe nding on pr edato r densi ties, there is still no em pir-
ical test for the hypothesis that cyclic predator–prey dynamics and
selection can provide the conditions selecting for sex in the prey.
Such a test would add to our understanding of the evolution of sex
by considering antagonistic species interaction, but without victim–
exploiter coevolution.
For considering species interaction and fluc tuating population
densities, there are at least two population genetic mechanisms that
could drive selection for sex (Gandon & Otto, 2007). Theor y predicts
that changes in selection can lead to changes in the sign of fitness
interaction (epistasis and dominance) followed by the generation of
genetic associations of the same sign (Barton, 1995). These changes
in fitness interaction and genetic association continuously result in
mismatches between which genotypes are currently most fit and
which are most common (i.e. a situation of rare advantage) (Lively &
Mo rra n , 20 14). Thes e con dit ion s can sele c t for sex th rou gh an imme -
diate short-term benefit by increasing the frequency of fit genotypes,
as well as through an intermittent long-term benefit by increasing
variance in fitness (Bar ton, 1995). Under these conditions, we would
expect to see cyclic changes in the mean fitness (short-term effect)
and variance in fitness (long-term effect) of sexually versus asexually
derived offspring from within the same population. The alternative
population genetic mechanism is if epistasis is weak and/or invari-
able and there are sustained changes in directional selection; sex can
be beneficial for increasing fitness indirectly by accelerating the rate
of response to selection (long-term benefit) (Barton & Otto, 2005;
Maynard Smith, 1978). Despite theoretical predictions for short- and
long-term effects of sex, there remains a dearth of empirical studies
aiming to link current ecological and population genetic theory for
the evolution of sex.
Herein, we tested the idea that predator–prey cycles can lead
to fluc tuating selection and that recurrent, antagonistic species
interaction can select for increased rates of sex in the prey. We
conducted an experimental evolution study using an obligate
asexual predator (rotifer, Brachionus calyciflorus) and facultative
sexual prey (unicellular alga, Chlamydomonas reinhardtii), both of
which can be commonly found within freshwater plankton com-
munities. Planktonic herbivores encounter a broad range of algal
prey and can apply strong selective pressures on phytoplankton
(Franks, 2001; George, Lonsdale, Merlo, & Gobler, 2015; Jones &
Ellner, 2004; Lewis, Breckels, Steinke, & Codling, 2013; Muylaert
et al., 2010; Reichwaldt, Wolf, & Stibor, 2004; Sommer, 1989; Sunda
& Hardison, 2010). Both species are facultative sexual, but we used
here rotifers from a monoclonal, obligate asexual laboratory stock to
constrain predator (co)evolution, as we were only interested in in-
vestigating selection for sex in the prey. C. reinhardtii is heterothallic
with two mating typ es, + and -, and although the frequency of sex in
natural populations of C. reinhardtii is unknown, both mating types
are found in nature (Harris, 20 09).
We formulated and tested several predictions relevant to our
system and experimental design. First, in accordance with previ-
ous results, we predict fluctuating selection for competitive ver-
sus defended prey (Becks & Agrawal, 2010; Becks, Ellner, Jones, &
Hairston, 2010, 2012; Yoshida et al., 2004). Specifically, changes in
traits determining defence and competition are expected to fluctu-
ate over time, with prey defensiveness selected for and competitive-
ness selected against when predation pressure is maximized (Ellner
& Becks, 2011). Prey defence is assessed via cell morphology and
predator growth rates; increases in prey defence will lead to reduced
predator growth rates (Becks, Ellner, Jones, & Hairston, 2010), as
will the increased handling time of defended prey types that lose
motility (Koch & Becks, 2016) or evolve to grow as colonies instead
of single, motile cells (Becks, Ellner, Jones, & Hairston, 2012).
Second, we predict that fluctuating selection can drive in-
creased rates of sex in the prey. This prediction is based on pop-
ulation genetic theory and modifier models that help explain the
conditions under which sex (and recombination) can evolve by
consid er ing the dy nam ic s at gen es that mo dif y rep rod uc tion mode
and the frequency of crossover events (Gandon & Otto, 2007;
Nei, 1967). We also predict changes in the rate of sex will lag be-
hind cha nges in sele cti on be cause it t ak es time for th e prey to pro-
duce zygospores as a result of sexual reproduction (Harris, 2009).
In C. reinhardtii, populations grow via asexual (vegetative) repro-
duction, whereas the switch to sexual reproduction is typically
induced by nitrogen starvation (Harris, 2009). Previous studies
using C. reinhardtii showed, however, that the switch from dif-
ferentiating as a vegetative cell to a sexual cell can be altered by
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KOCH et al.
selection and occur when nitrogen is replete (Bell, 2005; Koch &
Becks, 2016). Previous work also showed that the presence of ro-
tif er pre da tors alo ne was not suf ficien t to ind uc e th e switch to sex
as spontaneous sexual reproduction occurred only in C. reinhardtii
populations with predators when the cost s of sex were experi-
mentally removed (Koch & Becks, 2016).
Third, we expect that patterns for the effec ts of sex (short/
long term) over time correlate with changes in selection over time,
based on population genetic predictions (Barton, 1995; Barton &
Otto, 2005; Gandon & Otto, 2007; Maynard Smith, 1978). For ex-
ample, we would expect changes in the direction of selection to be
in synchrony with changes in the mean (hereaf ter: short-term effect)
and/or variance of fitness (hereafter: long-term effect) of sexually
produced offspring when changes in selection lead to changes in
the sign of fitness interaction. Finally, we present a discussion on
inferring the underlying population genetic mechanism providing a
benefit to sex under the conditions in the present experiment.
2 | METHODS
2.1 | Model system and experimental evolution
Our model system consisted of the haploid algal prey, Chlamydomonas
reinhardtii, and rotifer predator, Brachionus calyciflorus. From the
Chlamydomonas Resource Center at the University of Minnesota
(Laudon, 2013), we obtained isogenic C. reinhardtii strains for each
mating type, CC-1010 (+ mating type) and CC-1009 (- mating type),
which are complementary descendants of a single wild-collected
zygote (Proschold, Harris, & Coleman, 2005). Rotifers were taken
from an asexual, monoclonal laboratory stock culture. This culture
descends from a single natural source that was shown to have sub-
stantial genetic variation in the strength of the stimulus needed to
induce sex, but has subsequently lost the stimulus for sex and is now
laboratory-adapted (Becks & Agarwal, 2010).
We conducted an experimental evolution study that used con-
tinuous cultures (chemostats) for evolving replicate (n = 3) algal
populations with and without (control) predators in order to follow
predator–prey dynamics, predation intensity (predator/prey ratios)
and the rate of sex in algal prey populations over time (Figure 1a,b).
Each chemostat had a volume of 850 ml, was continuously stirred,
ventilated, and fresh media [80 μM nitrogen] supplied at a constant
flow through rate of 0.11 d−1. Cultures were maintained at 26°C. To
allow zygospore maturation (Harris, 2009), we set the cultures to
an 8h L:16h D cycle. We inoculated all 6 chemostats with 1 × 106
cells of each mating type, followed by 300 rotifers in 3 of the che-
mostats 3 days later. Chemostat sampling began 4 days after rotifer
inoculation.
The experimental evolution study lasted for 62 days, and each
chemostat was subsampled (a) every other day (with a 9-day gap
FIGURE 1 Experimental set-up and prey life cycle. (a) Replicate algal prey populations with and without rotifer predators were
experimentally evolved over 62 days using continuous cultures (chemostats). (b) All chemostats (n = 6) were sampled every other day
to track predator–prey population dynamics, predation intensit y (predator/prey ratios) and the rate of sex in algal prey populations over
time (predators were absent within controls and zygospores were never observed). (c) All replicate algal populations (n = 6) were sampled
weekly to track the frequency of mating type alleles in each population over time, using ddPCR , which served as another estimate of the
in situ rate of sex. (d) Prey populations (n = 3) from the predation treatment were sampled every 4 days (15 time points) to isolate replicate
sexual and asexual algal clones for fitness assays. One set of assays tested for changes in selection for competitive and defended prey over
time; competitiveness in the prey was measured using absolute growth rates, whereas predator growth rates were used as a proxy for
prey defensiveness. The other set of assays tested the short- and long-term effects of sex by measuring fitness of sexually and asexually
produced offspring in the environment that they were produced in; to account for fluctuations in selection for defence and competition,
algal grow th rates were measured under low or high predation pressure, which simulates the selection conditions that the clones evolved
under (see Supplementar y Methods). (e) An asexual generation in the algal pray herein lasts 1–2 days, whereas the sexual cycle requires at
least 5 days, representing a significant cost of sex in this system
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KOCH et al .
between the last two sampled time points) by ex tracting 50 ml sam-
ples to enumerate predators, prey and zygospores using a Neubauer
haemocytometer and compound microscope (Figure 1b), (b) every
week to track the frequency of mating types over time in each algal
population using ddPCR (Figure 1c) and (c) every 4 days by streaking
out subsamples onto agar plates to isolate algal clones for subse-
quent fitness assays to test for changes in selec tion and the effects
of sex (Figure 1d). These subsequent assays, however, could not be
performed for the control group since sex was never obser ved in
the algal populations without predators (see section 3). Zygospores
are thickly walled zygotes with a distinct size and orange colour that
makes them a clearly visible product of mating following the fusion
of two (±) gametes (Harris, 2009). Herein, zygospore counts are used
to estimate the in situ rate of sex in the prey.
C. reinhardtii is an isogamous species; therefore, the classic ‘cost
of males’ does not exist here (Lehtonen, Jennions, & Kokko, 2012;
Maynard Smith, 1971, 1978). Under the experimental conditions
herein, an asexual generation of C. reinhardtii and B. calyciflorus takes
1–2 days, whereas the C. reinhardtii sexual cycle requires at least
5 days (Figure 1e). Thus, one major cost of sex in this system is the
time necessary for completing the sexual cycle (population grow th
does not occur during the zygospore stage of the sexual cycle), in
addition to the potential for recombination load.
2.2 | Assays measuring changes in selection and the
effects of sex
The following assays were conduc ted for 15 time points, over
62 days, and each replicate chemostat (n = 3) of the predation
treatment to test for changes in selec tion, as well as the effects of
sex. First, we randomly isolated 10 asexual and 10 sexual clones to
serve as a representative population subsample (see Supplementary
Methods). Then, we measured the fitness (growth rate) of these 900
clones in the absence of predators (0 rotifers), under low predation
(5 rotifers), under high predation (10 rotifers), as well as their de-
fence against predation. The first and last measurements are used
as proxies for traits related to competitiveness and defensiveness,
respectively. The growth rate measurement s under low and high
predation are used as prey fitness measurements under the experi-
mental con ditions the al gae exp er ience d over time as roti fer pop ula-
tion density, and thus predation intensity, fluctuated over time (see
Supplementary Methods). A common garden experimental design
was used for all assays, which were conducted at the same time and
after several generations in the absence of predation (i.e. the time
bet ween sa mp li ng the las t se t of clones from the ch em os tat s an d as-
saying them was about a month, ~30–90 additional asexual genera-
tions). Thus, observed differences in all fitness assays are predicted
to be heritable. We determined algal growth rates from optical den-
sity measurements, and predator fitness was used as a proxy for es-
timating algal defence (see Supplementary Methods).
We tested for changes in selection for competitive and defended
prey using the absolute population growth rate (no predation) and
defence data. We also determined the frequency of defended phe-
notypes out of these 20 clones, based on their morphology and be-
haviour. Phenotypes that grow in colonies or lose motility increase
prey handling time for the predator and lead to reduced predator
growth rates (Figure S1) (Becks et al., 2010). They are thus consid-
ered defended, whereas motile single-celled phenotypes (wildtype)
are considered undefended; undefended prey are more competitive
(grow faster) compared to defended phenotypes (Becks et al., 2010;
Yoshida et al., 20 04).
We used the same set of sexual and asexual offspring (n = 10
each) to estimate the effects of sex by comparing the mean fitness
(short-term effect) and variance in fitness (long-term effect) of of f-
spring in the environment that they were produced in. Therefore,
to account for fluctuations in selec tion for growth and defence, we
used the growth rate data from the low (L) and high (H) predation
environments, respectively, which simulates the selection condi-
tions that the clones evolved under. We then matched each time
point to either environment based on predator–prey ratios (see
Supplementary Methods). We used these designations to determine
from which assay environment (L, H) data would be plotted for the
short- and long-term effects of sex.
To estimate selection differentials, we first plotted a linear re-
gression of the phenotypic data (fitness: growth rate versus defence)
for each of the 20 clones to obtain a slope for each time point. These
selection differentials (absolute values) were then plotted over time
to show the changes in selection for each replicate chemost at, along
with the frequency of zygospores (in situ rate of sex).
2.3 | Wavelet analyses
We used wavelet analyses to estimate the period of cycles in the (a)
alga l prey po pu lat io ns, (b) pre dator–p rey rat io s, (c) cha nge s in sel e cti on ,
and (d) short- and long-term effects of sex (WaveletComp package in
R (Roesch & Schmidbauer, 2014)) (see Supplementary Methods). For
all wavelet analyses, we followed standard time series analysis prac-
tices and used smoothed time series data (spline function in R) after
detrending (pracma package (Borchers, 2015)). Generally, wavelet
analysis decomposes a time series into time/frequenc y space simul-
taneously and provides information on both the amplitude of any
periodic signal within the series and how this amplitude varies with
time. Significances of periodicity were assessed by testing the null
hypothesis that a period is not relevant at a certain time of the time
series by using a simulation algorithm representing white noise (default
methods in the WaveletComp package (Roesch & Schmidbauer, 2014).
We further tested for a significant relationship between oscillations in
the predator–prey ratios and (a) population mean defence, (b) popu-
lation mean growth (competitiveness), (c) the frequency of defended
phenotypes and (d) the short- and long-term effects of sex. We did
this by identifying the dominant and significant phase shifts between
these time series. Next, we used wavelet coherence analyses to meas-
ure the local correlation between two series over a specific period
(WaveletComp package in R (Roesch & Schmidbauer, 2014; Torrence
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KOCH et al.
& Compo, 1998)). We extracted from these analyses the significant
phase shif ts, which are express ed in days an d sh ow the num be r of days
the defence, competition, or frequency of defended types is lagging
behind the predator–prey ratio.
2.4 | Estimating rates of sex
To quantify sex, we measured (a) in situ rates of sex, (b) allele frequen-
cies of mating types and (c) conducted a test for evolutionary changes
in the rate of se x. The firs t two measu re ments wer e do ne for all con tr ol
and experimental populations (n = 6), whereas the last test was only
conducted for the prey populations within the predation treatment.
Zygospore counts and changes in the frequency of mating t ypes over
time were used as estimates of the in situ rate of sex, with the latter
using the weekly population subsamples and digital droplet polymerase
chain reaction (ddPCR) (see Supplementar y Methods) (Koch, Jeschke,
& Becks, 2015). We conducted an additional ass ay under standardized
conditions testing for the time that is required for the production of a
mating reaction (pellicle formation) comparing algal populations from
day 62 to the ancestors (see Supplementary Methods). We used the
time that is required for the production of a mating reaction (pellicle
formation) based on the assumption that the ancestor switches only
in a nitrogen-free environment or when all nitrogen is consumed. In
contrast, the genotypes isolated from the predation treatment, which
likely evolved to switch in the absence of the trigger, were predicted
to switch earlier as compared to the ancestors. Pellicle assays can be
used as an end-point detection method for quantif ying a rate of sex
in Chlamydomonas because gametes are too difficult to distinguish,
visually, from vegetative cells (Harris, 2009). Pellicles are the result of
aggr eg at ed zygot es for ming a fil m on the air-water surf ace an d ar e ea s-
ily seen by the naked eye, which eliminates the need to continuously
sample and dis turb the mati ng reaction to look for ga metes or zygotes.
Rotifers were not included in this assay.
3 | RESULTS
3.1 | Predator–prey population sizes fluctuate over
time
Over the course of 62 days, we found that prey densities
(Figure 2d–f) and predation intensit y (Figure 2g–i) fluctuated
significantly over time in the predator–prey treatment (wavelet
analysis (Figure S2): algal prey = 8.6 ± 0.6 days; predator–prey
r a t io = 7. 8 ± 1 d a y s ) . In c on tr as t, a lg al po pu l at io n s we re si gn if i ca nt ly
more stable in the controls (Figure 2a–c; coefficient of variation
for days 10–62: predation = 0.41 ± 0.0 47, control = 0.17 ± 0.045;
Kruskal-Wallis test: χ2 = 3.86, df = 1, p < .05) and maintained
higher densities at carrying capacity (control vs. predation treat-
ment: maximum population density, Wilcoxon-Mann-Whitney U
test: W = 7,535, p < .0001).
3.2 | Predation pressure and selection changes
over time
Across all prey populations, algal competitiveness (grow th rates)
and defence levels fluctuated continuously with a significant pe-
riod of 9.3 ± 1 days, indicating that selection for competitive abil-
ity and defence changed over time (Figure 3a-f). Furthermore, we
found that the predator–prey ratio (Figure 2g–i) and prey population
mean defence (Figure 3a–c) cycled in-phase (i.e. the maximum in
the prey defence trait and the predator–prey ratio occurred simul-
taneously) (phase shift: 0.5 ± 1.5 days, Figure 3d–f). We also found
that changes in the predator–prey ratio and frequency of defended
types oscillated in-phase (phase shift: 0.3 ± 1.7 days, Figure 3d–f).
In contrast, the predator–prey ratio (Figure 2g–i) and prey competi-
tiveness (mean population growth rate, Figure 3a–c) cycled in anti-
phase where changes in the growth rate lagged behind changes in
the predator–prey ratio by 6.1 ± 0.6 days (Figure 3d–f). Taken to-
gether, these results indicate that oscillations in predation pressure
drove oscillations in selection for prey defence and competition with
a period of 2–9 algal generations depending on the number of sexual
and asexual reproduction cycles (9 asexual generations at the most
and ~2 sexual generations at the least).
3.3 | Increased selection for sex in the algal prey
populations
Zygospores were never observed in the controls during the experi-
mental evolution study (Figure 2a–c), whereas zygospores, and thus
sex, were observed at several time points in the predation treat-
ment (Figure 2d–f). These changes in the in situ rate of sex lagged
behind the changes in selection (Figure 5a–c). Using chemostat
systems where fresh medium was supplied at a constant rate, C. re-
inhardtii did not experience nitrogen starvation in our study. Since
Chlamydomonas did not experience the trigger of nitrogen starva-
tion to switch to sexual reproduction, and since it was previously
shown that the switch to sexual reproduction is not a stress-induced
response (Koch & Becks, 2016), this observation suggests selection
for sexual reproduction.
We also tracked mating type frequencies over time using ddPCR
and found that one mating type quickly moved towards fixation
across all three control populations (Figure 4a–c). We found a similar
decline in one mating type for the populations from the predation
treatment, but frequencies of the lower type started to increase to
similar frequencies as the other type around week 4 (Figure 4d–f).
Import antly, an almost equ al frequenc y of the two mating t yp es sug-
gests high frequencies of sex; a germinating zygospore releases an
equal number of progeny based on mating type.
To test for heritable and evolutionary changes in the rate of
sex, we compared the time required to form mating reactions be-
tween the ancestor and evolved populations from the end of the
experiment. We found that sex occurred significantly faster in the
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KOCH et al .
evolved algal populations than in the ancestors, under the nitrogen
conditions that the populations evolved in (80 μM nitrogen; evolved,
315 ± 45 min; ancestors, 450 ± 0 min: Wilcoxon-Mann–Whitney U
test: W = 48, p < .001) but not control conditions (0 μM nitrogen;
evolved, 180 ± 30 min; ancestors, 180 ± 0 min: Wilcoxon-Mann–
Whitney U test: W = 24, p = 1; Figure 4g). Mating reac tions from
the last chemostat replicate (Figures 2f and 4f ) produced zygotes,
under both conditions (0 and 80 μM nitrogen), but pellicles did not
form. These populations were tested a second time, under the same
conditions and densities as the previous mating reactions, and the
same result was obtained. Again, we sampled the reactions and
fou nd zygotes , bu t th ey did not aggregate to for m a pe ll icle. We con-
firmed the presence of both mating types in each mating reaction
using PCR (data not shown; see Supplementary Methods). Thus, the
populations turned sexual, but because pellicles were not formed,
an accurate end-point time could not be recorded, and this replicate
was therefore dropped from the statistical analysis.
Finally, we used the data from Figure 3a–c (prey competition
and defence) to calculate selec tion differentials for each time point
and replicate population and correlated the estimates of selection
streng th with the change in the in situ rate of sex (frequency of zy-
gospores, Figure 5a–c; see Supplementary Methods). We found a
significant lag between the change in selection and change in the
rate of sex of 11.2 ± 2.4 days (2.8 time points ± 0.6). This is consis-
tent with our prediction that changes in selection drove selection
for sex and also consistent with the biology of the organism, where
a time lag would occur between when sex is selected for and when
the products of sex (zygospores) can be obser ved.
FIGURE 2 Predator–prey population dynamics and in situ rate of sex. Predator (black) and prey (green) population dynamics, and rate
of sex (zygospores, orange) for replicate populations without (a–c, controls) and with predation (d–f). Predation intensity (g–i) calculated as
the ratio of predator/prey densities and scaled to the maximum value for each corresponding population of the predation treatment (d–f).
Dashed ver tical lines (d–i) correspond to the 15 time points when prey populations were sampled for subsequent testing
(a) (b) (c)
(d) (e) (f)
(g) (h) (i)
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KOCH et al.
3.4 | Short- and long-term effects of sex fluctuate
over time in the prey populations
We next compared the mean and variance in fitness of sexual to
asexual of fspring in their selected environment (i.e. high or low roti-
fer densities corresponding to the rotifer densities when algal cells
were isolated) at 15 time point s (see Section 2; Table S1). As we did
not observe sexual reproduction in control populations without
predators (Figure 2a-c), we did this only for the predation treatment.
Our results showed that the short- and long-term effects of sex
fluctuated as having costs and benefits over time with a significant
period of ~9 days or 2–9 generations (Figure S3, short-term effect:
8.58 ± 2.4 days; long-term effect: 9.96 ± 3.8 days) (Figure 6).
4 | DISCUSSION
We tested the hypothesis that cyclic predator–prey dynamics can
select for sex in the prey by comparing Chlamydomonas populations
evolving in the presence and absence of predation. We found signifi-
cant fluctuations in prey population density and predation intensity,
over time, leading to significant fluctuations in selection for defended
and competitive prey with a period of ~ 8–9 days (= 2–9 genera-
tions). We also found that sexual reproduction occurred in the prey
populations but never in the controls without predators. Indeed, when
te sti ng for he rit abl e ch ang es in the rate of sex, we fo und a fas ter switch
to sexual reproduction in the evolved prey populations compared to
the ancestors. Since this test was conducted after several asexual
generations in the absence of predation (i.e. from stored populations),
and in a controlled environment that also lacked predators, this result
indicates selection for increased rates of genetic mixing in the prey
populations. Herein, we fur ther examined the ef fects of sex and found
that the short- and long-term effects of sex fluctuated significantly
over time an d wit h a period ici ty similar to that of the change s in preda-
tion intensity and selection (~9 days, or 2–9 generations). This shows
that the fitness effects of sex not only changed over time, but with a
consistent pattern, and continually led to time points where sex had a
selective advantage depending on the direction of selection and likely
underlying genetic associations.
We did consider, however, the possibility that the phenotypic
changes in defence and competition were plastic. Although, in the
time between when clones were sampled from the chemostats
(Figure 2d–f, dashed vertical lines) and tested in the fitness assays
(Figure 3a-c), which was more than 30 asexual generations, preda-
tors were absent. Additionally, in the chemostat environment where
selection continuously changed, plastic responses lasting more
generations than what occurred in that 9-day cycle would not be
beneficial. Finally, sexual offspring, used in the assays measuring
FIGURE 3 Changes in selection for competitive and defended prey. (a–c) Competitiveness (prey population mean growth rate without
predators [day−1], green) and defensiveness (predator population mean growth rate, where low predator growth rates indicate high prey
defence levels [1/final predator number], purple) of 20 algal clones per time point for each replicate population of the predation treatment
(± SEM). Across all replicate populations, competition and defence fluctuated significantly over time (9.3 ± 1 days, wavelet analysis). (d–f)
Smoothed and detrended time series data to estimate periodicity and phase shif ts between the predator–prey ratio (black) and changes
in the trait value for prey population mean defence (purple), prey population mean competitiveness (green) and frequency of defended
phenotypes (grey). The predator–prey ratio cycled in-phase with the mean defence trait and frequency of defended phenotypes, but
cycled in anti-phase with mean competitiveness (see main tex t for wavelet statistics). Grey boxes indicate matching data sets. (a–c and d–f
correspond to order of replicate populations in Figure 2d–f).
(a)
(d)
(b)
(e)
(c)
(f)
8
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KOCH et al .
the short- and long-term ef fect s of sex (Figure 6), were propagated
under standardized conditions and forced to undergo an additional
round of sex (see Supplementary Methods). Together, these points
indicate that all measured phenotypic differences were heritable.
4.1 | Rates of sex
Although rates of sex were low overall in the prey populations
exposed to predators, this is attributable to the strength of selec-
tion for sex mainly depending on the net benefit of sex, as well as
the costs of sex in the system. Here, the major costs of sex are the
time needed to complete the sexual cycle (at least 5 days), which is
substantial compared to an asexual cycle (1–2 days), as well as the
inhibition of population growth during the sexual cycle. These costs
still have to be overcome, and although short-term benefits of sex
appear to exist, they are intermittent (cyclic).
Regarding th e mat ing type allele fre quencies, it is import ant to
note that our ddPCR results are consistent with previous work on
intraspecific competition in C. reinhardtii populations composed of
both mating types where the loss of one mating type, via natural
selection, occurred during asexual reproduction; ultimately, these
populations became sexually sterilized (Bell, 2005; Collins, 1993).
In the literature on the evolution of sex and geographic partheno-
gene sis, it has be en argu ed that for many heterothallic, facultative
sexual populations, the loss of sex—or the loss of the potential for
FIGURE 4 Selection for sex in the ancestors and evolved prey populations. (a–f) Changes in the frequencies of mating types in algal
populations with and without predation over time measured using multiplex ddPCR. As an additional measure of selection for sex, we used
ddPCR to track the frequencies (± 2σ) of both mating types in replicate populations without predation (a–c, controls) and with predation
(d–f). In control populations, the (+) mating t ype (grey) rapidly moved towards fixation, essentially eliminating the (-) mating type (black)
and potential for sex, whereas both mating types were maintained at more similar frequencies in the predation treatment. ( g) The time
(in minutes) to complete a mating reaction, in the absence of predators, in control (0 μM nitrogen, black bars) and evolved conditions
(80 μM nitrogen, grey bars) for ancestors and replicate evolved populations of the predation treatment (d–e refer to chemostat replicates
corresponding to Figure 2d–e, 3a–b, d–e; see Supplementary Methods). Sex occurred significantly faster (***p < .00 01) in the evolved algal
populations (from day 62) than in the ancestors under evolved conditions (grey bars), but there was no significant dif ference in sex rates of
ancestors and evolved populations under control conditions (black bars; st atistics in text). There was no variation among technical replicates;
therefore, error bars are imperceptible. Replicate ‘F’ was dropped because a pellicle did not form (see main text)
FIGURE 5 Selection differentials. (a–c) Selection differentials (absolute values, grey) of 20 clones per time point for each replicate
population of the predation treatment, showing changes in selection for competitive and defended prey over time, and the in situ rate of
sex (frequency of zygospores, orange; see Supplement ary Methods). Across replicate populations, there was a significant lag between the
change in selection and change in rate of sex of 2.8 ± 0.6 time points. (a–c correspond to order of replicate populations in Figure 2d–f)
(a) (b) (c)
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9
KOCH et al.
sex—may occur frequently, as a result of the loss of one mating
type allele (Collins, 1993; Schön , Mar tens, & Dijk, 2009). Here, we
have seen this for populations without predation (Figures 2a-c and
4a-c). Whether fixation of the same mating type (+) across control
populations was due to stochastic (e.g. random mutation confer-
ring a fitness advantage), or deterministic causes (e.g. an inher-
ent competitive advantage), is however unknown; the (+) mating
type did not dominate in all experimental populations (Figure 4f).
Regardless, the loss of a mating type independently across all
control populations precluded the abilit y to test for evolution-
ary changes in the rate of sex between ancestors and end-point
clones.
4.2 | Potential underlying population genetic
mechanisms selecting for sex
In a landmark paper, Barton (1995) outlined the contributions of
sh o r t- and lo n g-ter m eff e c t s to th e evo lut ion of sex in a ge ner al th eo-
retical framework. This framework can be used to evaluate the pop-
ulation genetic mechanisms by which sex is favoured under different
hypotheses. For considering species interaction via fluctuating pop-
ulation densities (or coevolution), there are at least t wo population
genetic mechanisms that could drive selection for sex, fluctuating
epistasis and directional selection (Gandon & Otto, 2007). For the
fluctuating epistasis hypothesis, theor y predicts that changes in se-
lection can lead to changes in the sign of epistasis, followed by the
generation of genetic associations (i.e. ‘linkage disequilibria’, in hap-
loids) of the same sign (i.e. positive or negative) (Barton, 1995). Since
it takes time to build genetic associations, a lag between epistasis
and linkage disequilibria occurs, leading to opposing signs and a
mismatch at points in time between which genotypes are currently
most fit and which are most common (Barton, 1995). This is crucial,
because these particular conditions can select for sex through an
immedi ate short-term benefit by increasing the frequen cy of fit gen-
otypes or decreasing the frequency of unfit genotypes, as well as
through an intermittent long-term benefit by increasing variance in
fitness (Bar ton, 1995). As selection continues to change, so will the
underlying state of fitness interaction and genetic association, lead-
ing to changes in selection for or against sex over time. Therefore,
the expectation is that if fluctuating epistasis is operating, it would
be evidenced by fluctuations in the short- and long-term effects of
sex over time, which is indeed what we find here (Figure 6) (Gandon
& Ot to, 200 7; Ott o & Lenor mand, 20 02 ; Pe te rs & Li ve ly, 199 9, 20 07;
Salathé, Kouyos, & Bonhoeffer, 2009).
This hypothesis requires that selection changes rapidly enough so
th at the sign of epis t asis chan ges wit h a per io d of 4–10 gene r at ion s an d
combinations of alleles advantageous in one generation quickly become
disadvantageous in the following generation and so on (Barton, 1995;
Mayn ard Smit h, 1978; Peters & Lively, 1999). It has been shown, mat h-
ematically in haploid models, that high rates of recombination can also
evolve with shor ter periods (i.e. 2–7 or 2–9 generations depending on
how tightly linked the modifier locus is), which determine higher rates
of genetic mixing (Gandon & Otto, 2007). Our data match the theo-
retical prediction where the effects of sex fluctuated over time with
a significant period of ~9 days (i.e. 2–9 generations) (Figure S3). This
timing is also consistent with our data showing that selection changed
every 4–5 days (~9-day period), followed by a change in the rate of
sex ~9–13 days later (Figure 5). Furthermore, under these conditions,
changes in the short-term ef fect are expected to occur in-phase with
the cha nges in the predat or–prey rat io and se le ction. Ind ee d, we fou nd
that changes in the short-term effect were immediate and in-phase
with changes in the predator–prey ratio (i.e. they cycled with similar
timing ) (0. 05 ± 0.12 of a period; 0.43 ± 1 days), but ch anges in the long-
term effect of sex lagged behind the predator–prey ratio (0.31 ± 0. 22
of a period; 2.5 ± 1.8 days).
Alternatively, slower fluctuations in selection will create sus-
tained directional selection, causing changes in the mean phenotype
over time and selection for sex if there is weak negative epistasis, and
if fitness costs are high (Barton & Otto, 2005; Maynard Smith, 1978).
In the case of very rapid fluctuations, there would be little sustained
directional selection and sex would not be advantageous. Moreover,
FIGURE 6 Fluctuations in the short- and long-term effects of sex under fluctuating predation pressure. (a–c) The effects of sex
fluctuated significantly over time (statistics in main text; Fig. S3). Log10-transformed ratios of sexual to asexual offspring fitness (growth
rate, day-1) from replic ate populations of the predation treatment were used to determine the short-term (mean fitness, dark green) and
long-term (variance in fitness, light green) effects of sex over time in their selec ted environments (Low or High predation, see Supplementary
Methods and Table S2). Equal fitness is represented by the grey line at ‘0’, with a benefit of sex indicated above the line and cost of sex
below it. Day 1 represents the first day of the experiment, and thus the cross of ancestral isolates. Asterisks indicate signific ant differences
between asexual and sexual offspring (Table S1). (a–c correspond to order of replicate populations in Figure 2d–f, 3a–c)
(a) (b) (c)
10
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KOCH et al .
directional selection only selects for sex when negative genetic as-
sociations (disequilibria) are present (i.e. beneficial alleles tend to be
found with unfavourable ones more often than expected) because
fitness variance is low. In this case, sex is beneficial for increasing
fitness indirectly by accelerating the rate of response to selec-
tion by increasing genetic variance (long-term benefit) (Barton &
Otto, 2005; Maynard Smith, 1978). Under a scenario of selection for
sex via sustained directional selection, we would not expect to see
fluctuations in the effects of sex, but instead the presence of only
long-term benefits, which is not what we find here.
Although the pat terns obser ved for the ef fect s of sex, the
changes in selection, as well as the population dynamics, appear
inconsistent with alternative hypotheses, we cannot exclude them
entirely. Biotic fluctuations imposed by antagonistic coevolution
can also lead to fluctuations in epistasis and genetic associations
of the type necessary to continuously favour sex (i.e. RQH). Under
this scenario, one would also expect to observe fluctuations in the
short- and long-term ef fects of sex (Gandon & Otto, 2007; Peters &
Lively, 1999). While we argue that biotic fluctuations are, indeed, a
source of fluctuating selection in our experiment, we exclude pred-
ator coevolution here, which distinguishes our study from other
tests of the RQH. Predator populations were monoclonal (no initial
standing genetic variation) at the start of the experiment and had
relatively small population sizes (20 00 individuals on average) and
only ~30 asexual generations, which greatly reduces the potential
for novel mutations and, thus, coevolution.
Another set of hypotheses considers the conditions that may
generate negative genetic associations (disequilibria) and long-
te rm be n ef its of sex . A movi ng fit nes s opti mum , wher e t he op tim al
phenotype constantly changes and leads to sustained directional
selection in the population, can repeatedly lead to negative dis-
equilibria and therefore provide an advantage to sex via a long-
te rm b e n efit (Bar ton, 199 5; Mayna rd S mith, 197 8). Th i s me c h a nism
requires, however, that there is relatively little variation in the
sign and magnitude of epistasis and that the strength of epista-
sis is weak (Barton, 1995; Otto & Feldman, 1997). Genetic drift
and selection can also generate negative disequilibria and lead to
the evolution of sex via a long-term benefit (Barton & Otto, 2005;
Hill & Robertson, 1966). It has been suggested that although a
drift-based advantage to sex is more likely in finite populations
(Ga ndon & Ot to, 20 07), it ca n occur even in very large pop ul ations
if they are spatially structured (Martin, Otto, & Lenormand, 2006)
and/or selection acts on a large number of loci (Iles, Walters, &
Cannings, 2003). However, with either scenario of directional se-
lection combined with negative epistasis or drift, we would not
expe c t to ob se r ve an adva nt age of sex thr oug h a sho r t-ter m eff ect
or fluctuations in the effects of sex over time.
5 | CONCLUSION
Herein, we used a general theoretical framework to test predic-
tions made by early population genetic models considering species
interaction for the evolution and maintenance of sexual reproduc-
tion, which suggest that interactions without coevolutionary change
can also select for sex when fluctuations in population sizes of in-
teracting species generate a continuously changing environment
(Bell, 1982; Jaenike, 1978). Taken together, our results suggest that
predator-mediated fluctuating selection can generate conditions
leading to selection for sex in prey populations. We propose that
selection for competitive versus defended prey changed every few
generations, leading to changes in the sign of epistasis and recurring
situations where prey were no longer matched to their environment
because an excess of previously advantageous but now disadvan-
tageous genotypes existed. Sex could then be selected for (inter-
mittently) as recombination offered an immediate fitness benefit by
increasing the frequency of advantageous genotypes that were dis-
propor tionately rare. Even though epistasis has been implicated as
an essential factor in theoretical models of the evolution and main-
tenance of sex, there remains a dearth of experimental evidence.
Therefore, in light of recent advancements in sequencing technolog y
and genomic analyses (e.g. McDonald, Rice, & Desai, 2016), alterna-
tive approaches to studying the maintenance of sex and epistasis still
need to be tested (e.g. Kouyos, Silander, & Bonhoeffer, 20 07), and
as we have done here using the short- and long-term effects of sex
(e.g. Becks & Agrawal, 2011). Finally, our results further underline
the importance of investigating the role of predator–prey interaction
in driving the evolution and maintenance of sexual reproduction.
Although we observed an increase in sex in the prey populations,
it was only to low rates which is attributable to the costs of sex and
biology of the organism, but it could also indicate that the selection
dynamic s within this system are insuf ficient to observe the evolu-
tion of higher rates. Furthermore, additional testing—and on a finer
timescale—is necessary to determine whether conditions of fluctu-
ating population sizes and selec tion are strong enough to maintain
sex over the long term.
ACKNOWLEDGMENTS
We are grateful to Aneil Agrawal and Manfred Milinski for helpful
comments on the manuscript, and Alina Jeschke for collecting the
ddPCR results.
CONFLICT OF INTERESTS
The authors declare no financial interests.
DATA AVA ILAB ILITY STATE MEN T
The relevant data sets will be deposited in Dryad. Dryad DOI:
doi:10.5061/dryad.gtht76hj4
ORCID
Hanna R. Koch https://orcid.org/0000-0002-1776-9487
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SUPPORTING INFORMATION
Additional supporting information may be found online in the
Supporting Information section.
How to cite this article: Koch HR, Wagner S, Becks L.
Antagonistic species interaction drives selection for sex in a
predator–prey system. J Evol Biol. 2020;0 0:1–12. ht t p s: //d o i .
org /10.1111/jeb.13658
