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Evolution, 58(11), 2004, pp. 2584–2590
EVIDENCE FOR MAINTENANCE OF SEX BY PATHOGENS IN PLANTS
JEREMIAH W. BUSCH,1 MAURINE NEIMAN,2 AND JENNIFER M. KOSLOW3
Department of Biology, Indiana University, 1001 East Third Street, Bloomington, Indiana 47405
1 E-mail: jbusch@bio.indiana.edu
2 E-mail: mneiman@bio.indiana.edu
3 E-mail: jkoslow@bio.indiana.edu
Abstract. The predominance of outcrossing despite the substantial transmission advantage of self-fertilization remains
a paradox. Theory suggests that selection can favor outcrossing if it enables the production of offspring that are less
susceptible to pathogen attack than offspring produced via self-fertilization. Thus, if pathogen pressure is contributing
to the maintenance of outcrossing in plants, there may be a positive correlation between the number of pathogen
species attacking plant species and the outcrossing rate of the plant species. We tested this hypothesis by examining
the association between outcrossing rate and the number of fungal pathogen species that attack a large, taxonomically
diverse set of seed plants. We show that plant species attacked by more fungal pathogen species have higher outcrossing
rates than plants with fewer enemies. This relationship persists after correcting for study bias among natural and
agricultural species of plants. We also accounted for the nested hierarchy of relationships among plant lineages by
conducting phylogenetically independent contrasts (PICs) within genera and families that were adequately represented
in our dataset. A meta-analysis of the correlation between pathogen and outcrossing PICs shows that there is a positive
correlation between pathogen species number and outcrossing rates. This pattern is consistent with the hypothesis that
pathogen-mediated selection may contribute to the maintenance of outcrossing in species of seed plants.
Key words.
Cross-fertilization, mating system, parasites, recombination, sexual reproduction.
Received March 4, 2004.
In hermaphroditic plants, self-fertilization enjoys a strong
transmission advantage over outcrossing that should lead, all
else being equal, to the selective elimination of biparental
reproduction (Fisher 1941; Williams 1971; Maynard Smith
1978). However, outcrossing is the predominant mode of
reproduction in the plant kingdom (Yampolsky and Yampolsky 1922; Schemske and Lande 1985; Vogler and Kalisz
2001), suggesting that there are substantial benefits of crossfertilization. Although there are many theories explaining the
benefits of producing genetically variable progeny and thus
the maintenance of outcrossing, few have found consistent
empirical support (West et al. 1999).
In an attempt to identify the factors maintaining outcrossing in plant species, biologists have long examined its ecological correlates. One recurring finding in these studies is
the predominance of outcrossing in undisturbed, biologically
complex habitats where disease and other ‘‘natural enemies’’
might be expected to be prevalent (Levin 1975; Lloyd 1980;
Bell 1982). Levin (1975) proposed that this ecological pattern
might result from pathogen-mediated selection for outcrossing in natural plant populations. In theory, an outcrossing
strategy may be selectively favored if the genetically novel
(Levin 1975) and/or rare (Clarke 1976; Jaenike 1978) offspring produced via outcrossing have higher fitness than common genotypes. This situation may occur if common genotypes are disproportionately attacked by coevolved pathogens
(Hamilton et al. 1990). Similarly, selection for genetically
variable progeny by pathogens may also explain variation in
outcrossing rates among taxa that reproduce through varying
amounts of cross-fertilization (Lively and Howard 1994;
Agrawal and Lively 2001).
Infection by multiple pathogen species can favor recombination when (1) competition between pathogen species or
Accepted August 25, 2004.
genotypes favors more virulent species/genotypes than when
hosts are singly infected (Nowak and May 1994; May and
Nowak 1995; Davies et al. 2002) or (2) the cumulative virulence effects of multiple pathogen species are greater than
the virulence of any one pathogen species (Hamilton et al.
1990). Even if simultaneous infection by multiple pathogen
species per se does not favor outcrossing, selection for outcrossing may be more common in host species with many
natural enemies because the probability of infection by a
single, highly virulent pathogen is likely to increase with
pathogen species number (sensu Huston 1997; Tilman et al.
1997). Regardless of the underlying mechanism, there should
be a positive relationship between outcrossing rate and the
number of pathogen species infecting each plant species
whenever pressure from pathogens favors recombination. We
examined this possibility by compiling data on outcrossing
rates and pathogen species abundance across a wide array of
seed plant species and analyzing the correlation between
these two variables.
METHODS
Compilation of Outcrossing Rate Data
The majority of species in the dataset were originally compiled by Barrett and Eckert (1990). These data were analyzed
previously to estimate the distribution of natural outcrossing
rates in seed plants (Vogler and Kalisz 2001). This dataset
is current up to and including 1998. Consequently, we added
all reported studies up to and including May 2003. For each
species in the dataset, the outcrossing rate is an average across
all separate studies reported in the scientific literature. Outcrossing rates are measured in natural populations by using
statistical models to infer the parentage of offspring through
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q 2004 The Society for the Study of Evolution. All rights reserved.
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observed in earlier studies of plant outcrossing (Fig. 1; Vogler
and Kalisz 2001). A Kolmorov-Smirnov test shows that the
distribution of outcrossing rates in our study does not differ
in location, dispersion, or skew from the most recently published distribution of outcrossing rates in plants (Dobs 5 0.049
K 0.138 5 Dcrit(a50.05); Sokal and Rohlf 1995). This means
that the distribution of outcrossing rates in the present study
is likely to be an unbiased sample of the reproductive systems
found in species of seed plants (Schemske and Lande 1985;
Vogler and Kalisz 2001).
Estimation of the Number of Pathogen Species
Attacking Plants
FIG. 1. Distribution of outcrossing rates among sexually reproducing plant species for which the number of fungal pathogen species was estimated. This histogram describes variation in the amount
of outcrossing within the 182 sexual plant species included in the
study.
the use of polymorphic genetic markers. Whenever possible,
we used multilocus estimates of outcrossing rate in this study
because these estimates have lower error variance and greater
adherence to model assumptions than estimates taken from
single loci (Ritland and Jain 1981). We did not include any
apomictic plant species in our analyses because the lack of
recombination per se in asexual lineages cannot be adequately
translated into an outcrossing rate.
The distribution of outcrossing rates in the 182 plant species that we surveyed closely matches the bimodal pattern
FIG. 2. Bivariate plot of the residual outcrossing rate versus a plant
species’ residual log transformed number of fungal pathogen species infecting it. The residuals represent the variation not explained
by possible study bias. Residuals were computed from univariate
regressions of each variable against the number of Web of Science
citations for each plant species from 1987 to 2003. The line segment
represents the relationship predicted by linear regression. The outlying point represents Arabidopsis thaliana, which has the largest
number of citations in the database.
We cross-referenced plant species against a database listing
all fungal pathogens documented to infect many species of
natural and agricultural plants (Farr et al. 1989, 2003). This
database lists all of the fungal species known to infect both
living plant species and their agriculturally important products. To avoid counting single fungal species more than once,
we only tallied pathogen species for which a species epithet
was listed. Before conducting our analyses, the number of
pathogen species was natural log-transformed so that this
variable was normally distributed. There were significant differences between the number of fungal pathogen species
known to attack wild and agricultural species (mean agricultural species 5 43.1, wild species 5 6.3; independent
samples t-test, t 5 10.249, df 5 212, P , 0.001). These
reported means are back-transformed marginal means taken
from a one-way ANOVA.
Removal of Study Biases
It is important to account for the likelihood that the significant difference in mean fungal pathogen species number
between agricultural and wild species is driven by the in-
FIG. 3. Bivariate plot of the average residual outcrossing rate and
residual log transformed pathogen species number in five wellstudied plant families. Residuals were computed from the univariate
regressions of each variable against the number of Web of Science
citations for each plant species from 1987 to 2003 and averaged
within families. The line segment represents the relationship predicted by linear regression.
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FIG. 4. Bivariate plots of residual outcrossing rate and residual log-transformed pathogen species numbers obtained from phylogenetically
independent contrasts. Contrasts for both variables are standardized by the sum of the branch lengths separating taxa (A, Pinaceae; B,
Pinus; C, Poaceae; D, Asteraceae; E, Eucalyptus; F, Fabaceae; G, supertree). The correlation for each group is shown along with the Pvalue associated with testing the null hypothesis that the correlation equals zero. Although all of the correlations are positive, none of
them are significantly different from zero. The line segments represent the relationships predicted by linear regression.
herent biases in study effort toward species that are important
to humans (e.g. Gregory 1990; Nunn et al. 2003). We dealt
with this issue by using a statistical approach, partial correlations, that accounts for the positive correlation expected
between study effort and pathogen number. By removing the
influence of study effort on the number of pathogen species
recorded for each plant species, we were able to compute an
unbiased correlation between outcrossing rate and the number
of pathogens known to attack a diverse group of plants. We
removed the study bias from our data by counting the number
of Web of Science citations found for each plant’s Latin
binomial species name from 1987 to 2003 and removing correlations between this variable and the two variables of interest, pathogen species number and outcrossing rate (Zar
1996). More specifically, we performed separate linear regressions of pathogen species number and outcrossing rate
on citation number and saved the unstandardized residuals,
which represent the variation in pathogen species number
and outcrossing rate not explained by citation biases. There
was a significant negative relationship between outcrossing
rate and study effort (F 5 8.297; df 5 181; P , 0.004; R2
5 0.044; b 5 20.21), and a significant positive relationship
between pathogen species number and study effort (F 5
11.199; df 5 181; P , 0.001; R2 5 0.059; b 5 0.242). We
used the residuals from these regressions to compute a nonparametric rank correlation between these unbiased measures
of pathogen species number and outcrossing rate. We used
a nonparametric test because the bimodal distribution of outcrossing rates (Fig. 1) violated assumptions of bivariate normality necessary for interpretation of hypothesis tests (Zar
1996).
Accounting for Phylogenetic Nonindependence
Another potentially confounding factor is phylogenetic
nonindependence. More specifically, because species exhibit
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FIG. 4.
varying amounts of relatedness, one must control for the
possibility that relatedness may contribute to similarity between closely related species, thereby violating the assumption that outcrossing values or pathogen species numbers
estimated for different species are independent datapoints
(Felsenstein 1985). We attempted to control for phylogenetic
nonindependence in several ways. First, we computed the
mean residual outcrossing rate and mean residual pathogen
number within the five plant families with an adequate sample
of species (N . 10; Pinaceae, Poaceae, Asteraceae, Myrtaceae
[all species of Eucalyptus], and Fabaceae) and examined the
correlation between these variables. This analysis between
families corrects for the nonindependence of datapoints within these families.
To more adequately test the idea that pathogens may favor
outcrossing, it is necessary to examine changes in both pathogen susceptibility and outcrossing between plant lineages
that are not a product of shared recent ancestry (Harvey and
Pagel 1991). To remove potentially confounding variation
caused by shared inheritance among groups, we conducted
formal phylogenetically independent contrasts (PICs) using
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Continued.
the method described by Felsenstein (1985). This method is
based upon the assumption that traits evolve by a process of
Brownian motion along the branches of phylogenetic trees.
Under such a model, trait evolution occurs independently
within each lineage, such that the expected difference between two taxonomic units has a mean of zero and a variance
proportional to time, or the sum of the branch lengths separating the two groups (Felsenstein 1985). As a consequence,
the observed differences between taxa can be standardized
by their divergence times. Once all of the possible independent comparisons are conducted along the topology of a tree,
it is possible to test hypotheses using standard parametric
statistics because the changes observed along more terminal
branches are independent of those occurring on more basal
branches (Felsenstein 1985).
Phylogenetic Analyses and Meta-Analysis
We constructed phylogenetic trees describing relationships
at both the family and genus level (Pinaceae, Pinus, Poaceae,
Asteraceae, Eucalyptus, Fabaceae), and then generated a su-
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pertree connecting the five plant families (Pinaceae, Poaceae,
Asteraceae, Myrtaceae, Fabaceae). In light of the fact that
different sequences evolve at different rates and are informative only at certain levels of genetic divergence, not all
phylogenetic trees were based upon the same loci. Sequence
data were obtained from the NCBI website (www.
ncbi.nlm.nih.gov) for the species or genera represented in the
dataset. The following genes were used to estimate relationships: matK (Asteraceae, Fabaceae, and Pinus); NdhF (Poaceae); the 18S rRNA subunit (Pinaceae); and the 18S, 5.8S,
and 26S rRNA subunits along with two internal transcribed
spacer regions (Eucalyptus), and matR (supertree). The relationships among taxa in these groups were estimated using
the neighbor-joining algorithm in PAUP (Swofford 1998).
Once the topology of the tree and the branch lengths were
estimated, the residual number of pathogens and outcrossing
rate for a plant species or genus were then computed and
mapped onto the phylogenetic tree. Phylogenetically independent contrasts were conducted in Mesquite (Maddison and
Maddison 2003). In particular, pathogen and outcrossing contrasts were computed using the PDAP:PDTree module (Midford et al. 2003). The correlation between outcrossing and
pathogen species number contrasts was then computed in
SPSS (Rel. 11.5.2.1, SPSS Inc. 2003). For the PIC analysis
conducted on the supertree, the estimates of pathogen and
outcrossing for each family were obtained by inferring the
ancestral state of both variables within each plant family
using a model of squared-change parsimony (Maddison
1991).
A meta-analysis was conducted on the correlation observed
between the PICs of residual pathogen species number and
outcrossing rate taken from each level of analysis. Metaanalyses were conducted using MetaWin (Rosenberg et al.
2000). The within-family correlations (ri) were z-transformed
to normalize the distribution of coefficients and to make the
variance independent of the common coefficient: zi 5 1/2
ln(1 1 ri/1 2 ri). These normalized coefficients were then
weighted by their relative sample size and summed together
(Hedges and Olkin 1985). We compared the test statistic
obtained from the Fisher’s z-test to the two-sided critical
value of the standard normal distribution. In light of the fact
that the z-transformed correlation coefficients were not normally distributed (Shapiro-Wilk statistic 5 0.735; df 5 7; P
TABLE 1. Results of the meta-analysis conducted on results of the
seven groups of phylogenetically independent contrasts. The correlation coefficient was estimated through the use of z-transformations weighted by the sample size of each correlation. The combined z-statistic was compared against the standard normal distribution. The P-value of this statistical test is shown next to the
parametric confidence interval (CI) of the correlation. A nonparametric resampling test was conducted because the sample correlations were not normally distributed. The bootstrapped 95% confidence interval was computed by sampling with replacement 1000
times from the seven correlations. This test showed that the 95%
confidence interval did not include zero, suggesting that the positive
correlation between plant outcrossing rate and fungal pathogen
number is significantly different than zero.
Correlation
coefficent
Parametric 95% CI
P-value
Bootstrapped 95%
CI
0.2537
20.2800–0.7755
0.310
0.1032–0.6436
5 0.009), the results of this statistical test must be interpreted
with caution. As an alternative, we used resampling methods
to directly evaluate the significance of the correlation given
the data. We performed 1000 bootstrap replicates by randomly sampling with replacement from the seven correlations
to generate a distribution of possible values. If the 95% confidence interval of the bootstrapped correlation failed to overlap zero, then the correlation was judged to be significantly
different than zero (Sokal and Rohlf 1995).
RESULTS
AND
DISCUSSION
Once the potentially confounding effects of study effort
were removed, we found a strong positive partial correlation
between the number of fungal pathogen species attacking
each plant species and its outcrossing rate (Fig. 2; Spearman
r 5 0.234, P , 0.001, N 5 182). We also found that there
was a significant positive correlation between pathogen species number and outcrossing rate across the Asteraceae, Fabaceae, Myrtaceae, Pinaceae, and Poaceae (Pearson r 5
0.975; P 5 0.005; Fig. 3). However, both of these correlations
suffer from a large amount of phylogenetic nonindependence.
For example, there is a large degree of recent shared ancestry
between angiosperm families (e.g. Asteraceae, Fabaceae,
Myrtaceae, and Poaceae) that separates them from gymnosperms (Pinaceae), such that the datapoints contributed by
angiosperm families are not statistically independent of each
other.
From a comparative standpoint, is also important to consider the timescale over which pathogen-mediated selection
may favor higher outcrossing rates (Felsenstein 1985). Since
taxonomic treatments of plant groups suggest that outcrossing rates are often highly variable within plant genera and
families (Stebbins 1950; Barrett et al. 1996), it was imperative to account for shared inheritance over these relatively
short timescales. In all of the PIC analyses, the correlation
between outcrossing rate and susceptibility to pathogens was
positive, though not significantly greater than zero (Fig. 4A–
G). To conduct a more general test of the idea that pathogens
may selectively favor outcrossing in plants, we performed a
meta-analysis combining the correlations observed at each of
the seven taxonomic levels. Results of the meta-analysis suggest that there is a significant and positive correlation between
outcrossing rate and fungal pathogen number in seed plants
(Table 1). This finding is consistent with the idea that there
may be a link between pathogen attack and the maintenance
of outcrossing.
Both in the genus Pinus and within the family Pinaceae,
the correlation coefficient between outcrossing rate and pathogen number exceeds 0.85 with a sample size of only four
datapoints. In contrast, the correlation coefficients for other
plant groups were of a much lower magnitude (Fig. 4). Interestingly, Pinus and Pinaceae represent two of the three
groups characterized primarily by woody and relatively longlived organisms. This trend for a tighter correlation between
outcrossing rates and pathogen attack in longer-lived organisms is consistent with the pattern expected if pathogen pressure favors outcrossing in natural populations. In particular,
whenever pathogens have much shorter generation times than
their hosts, pathogen populations may adapt to individual
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host genotypes as they age (Rice 1983). Closer adaptation of
pathogen populations to individual host genotypes also increases the chances that one or more pathogen genotypes will
be highly virulent on any given host (Mutikainen et al. 2000;
Thrall et al. 2002). In such a situation, the production of rare
or novel genotypes by outcrossing may generate offspring
that are capable of evading locally adapted pathogens. The
trend for tighter correlations between outcrossing rates and
pathogen attack in long-lived organisms is similar to the observation that longer-lived mammals have higher rates of
recombination (Burt and Bell 1987). Continued combat with
antagonists over evolutionary time should favor high levels
of recombination whenever hosts have much longer generation times than their pathogens (Hamilton 1982), and may
help to explain the well-documented correlation between outcrossing and the perennial habit in seed plants (Stebbins
1950; Barrett et al. 1996).
An alternative explanation for the positive correlation between outcrossing and the number of pathogen species attacking plants is that self-fertilizing taxa may have smaller
range sizes and thus encounter fewer pathogen species. In
this case, a positive correlation between outcrossing rate and
pathogen species number would not clearly implicate pathogen-mediated selection for outcrossing. Although self-fertilizing populations may often be effectively small (Schoen
and Brown 1991), the demographic flexibility associated with
self-fertilization allows such species to successfully found
new populations following long-distance dispersal, thereby
allowing them to spread over greater geographical distances
(Baker 1955, 1967). If inbreeding taxa have larger ranges,
then we would have observed a negative relationship between
outcrossing rate and pathogen species number. Currently
there is no consensus on the differences in range size between
inbreeding and outcrossing plant species because this pattern
has been studied in relatively few taxonomic groups (Stebbins
1957; Lloyd 1980).
It is possible that other factors unrelated to parasite-mediated selection may also contribute to the detected correlation between outcrossing rate and attack by fungal pathogen
species. Although we are unable to eliminate all potentially
confounding factors, our results support the idea that high
rates of outcrossing in seed plants may be favored by pathogen-mediated selection in natural populations. The conclusion that outcrossing is favored by pathogen pressure is
strengthened in light of the fact that short-term field experiments have shown that outcrossing is favored when pathogen
or parasite pressure is intense (Schmitt and Antonovics 1986;
Kelley 1994), and by field surveys showing that asexuality
may be more common in regions where parasites are rare or
absent (Lively 1987, 1992; Schrag et al. 1994; Kumpulainen
et al. 2004).
Conclusions
In general, the results of these analyses demonstrate that
there is a positive correlation between outcrossing rate and
the number of fungal pathogens known to attack species of
seed plants. We showed that this correlation is not driven by
biases resulting from the disproportionate study of species
important to humans. Moreover, the fact that the correlation
between outcrossing and pathogen number remains after controlling for phylogenetic nonindependence suggests that this
pattern is most likely not an artifact of shared inheritance.
We also discussed the possibility that differences in range
size between species using different reproductive strategies
may confound this correlation, and tentatively conclude that
outcrossing and self-fertilizing plant species are not likely to
encounter natural enemies at consistently different rates. Taken together, these results provide evidence in support of the
hypothesis that pathogen pressure may contribute to the
maintenance of outcrossing in natural plant populations.
ACKNOWLEDGMENTS
The authors thank S. Barrett and C. Eckert for generously
providing access to their data on outcrossing rates in seed
plants. A copy of our dataset is available upon request to C.
Eckert via e-mail: eckertc@biology.queensu.ca. The authors
also thank G. Burleigh, S. Mathews, J. Palmer, and A. Richardson for providing relevant sequence data and advice on
phylogenetic analyses. We thank A. Agrawal, J. Antonovics,
K. Clay, L. Delph, F. Frey, S. Hamm, B. Koskella, C. Lively,
E. Osnas, J. Rudgers, J. Webster, and members of the Clay
and Delph-Lively labs for comments on drafts of the manuscript. We also thank A. Peters for his suggestions and help
throughout the review process, and an anonymous reviewer
for helpful criticisms of earlier versions of our paper. This
research was funded by the National Science Foundation
(JWB), the Graduate School at Indiana University (MN), and
the Indiana University Department of Biology (JMK).
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Corresponding Editor: S. Kalisz