Download the quantitative genetics and coevolution of male and female

O R I G I NA L A RT I C L E
doi:10.1111/j.1558-5646.2010.00958.x
THE QUANTITATIVE GENETICS AND
COEVOLUTION OF MALE AND FEMALE
REPRODUCTIVE TRAITS
Rhonda R. Snook,1,2 Leonardo D. Bacigalupe,1,3,4 and Allen J. Moore5,6
1
5
Department of Animal and Plant Sciences, University of Sheffield, Sheffield S10 2TN, United Kingdom
2
E-mail: [email protected]
4
E-mail: [email protected]
Centre for Ecology and Conservation, School of Biosciences, University of Exeter, Cornwall Campus, Penryn TR10 9EZ,
United Kingdom
6
E-mail: [email protected]
Received August 3, 2009
Accepted December 18, 2009
Studies of experimental sexual selection have tested the effect of variation in the intensity of sexual selection on male investment
in reproduction, particularly sperm. However, in several species, including Drosophila pseudoobscura, no sperm response to
experimental evolution has occurred. Here, we take a quantitative genetics approach to examine whether genetic constraints
explain the limited evolutionary response. We quantified direct and indirect genetic variation, and genetic correlations within
and between the sexes, in experimental populations of D. pseudoobscura. We found that sperm number may be limited by low
heritability and evolvability whereas sperm quality (length) has moderate V A and CV A but does not evolve. Likewise, the female
reproductive tract, suggested to drive the evolution of sperm, did not respond to experimental sexual selection even though there
was sufficient genetic variation. The lack of genetic correlations between the sexes supports the opportunity for sexual conflict
over investment in sperm by males and their storage by females. Our results suggest no absolute constraint arising from a lack
of direct or indirect genetic variation or patterns of genetic covariation. These patterns show why responses to experimental
evolution are hard to predict, and why research on genetic variation underlying interacting reproductive traits is needed.
KEY WORDS:
Experimental evolution, female reproductive tract, genetic architecture, indirect genetic effects, interacting
phenotype, quantitative genetics, sperm.
The evolutionary trajectories of male and female reproductive traits, including coevolution between them, are potentially
affected by the postcopulatory sexual selection processes of
sperm competition and cryptic female choice (for reviews see:
Eberhard 1996; Simmons 2001; Pitnick et al. 2009a,b; Pizzari
and Parker 2009). For example, both sperm quantity (Simmons
2001; Pizzari and Parker 2009) and quality (Snook 2005) are im3Current
address: Instituto de Ecologı́a y Evolución, Facultad de
Ciencias, Universidad Austral de Chile, Casilla 567, Valdivia, Chile.
C
1926
portant determinants of male fertilization success. There is also
substantial evidence of coevolution between sperm and the morphology of the female reproductive tract (for review see Pitnick
et al. 2009a) such that these general classes of traits are an interacting phenotype in which male reproductive success depends on
the social environment; that is, the rival male sperm phenotypes
and the female reproductive tract phenotype (Moore et al. 1997;
Moore and Pizzari 2005; Simmons and Moore 2009). The importance of an interaction is demonstrated by recent studies showing
that male reproductive success during postcopulatory selection is
C 2010 The Society for the Study of Evolution.
2010 The Author(s). Journal compilation Evolution 64-7: 1926–1934
M A L E A N D F E M A L E C O E VO L U T I O N
nontransitive. Within a male genotype, the outcome of sperm
competition is not repeatable if the rival male and/or female is
altered (e.g., Clark et al. 2000; Bjork et al. 2007; Tregenza et al.
2009). Defining ejaculates as interacting phenotypes is valuable
because such phenotypes influence the direction, magnitude, and
rate of evolution along with the underlying genetic architecture of
the focal traits differently than noninteracting traits (Moore et al.
1997; Simmons and Moore 2009).
Experimental evolution, in which populations are allowed to
evolve under manipulated mating systems or social interactions,
has been used to test the patterns of ejaculate investment as a consequence of variation in the intensity of sexual selection (Snook
et al. 2009). Experimental evolution should be especially effective
for interacting phenotypes and traits targeted by sexual selection,
as these are among those expected to respond most quickly and
dramatically (West-Eberhard 1979, 1983; Moore et al. 1997). Experimental sexual selection studies allows evolution to operate
within a species in multivariate space (i.e., without targeting any
specific trait a priori, and without limiting the traits that may
be targeted) and can be replicated, providing a more complete
test of the traits that sexual selection consistently targets. Snook
et al. (2009) review studies in which either the population sex
ratio and/or population density is manipulated to establish treatments in which either monogamy is enforced with random mate
assignment (which eliminates all forms of sexual selection) or
the intensity of sexual selection is increased through male-biased
sex ratio populations or large population sizes (which exaggerates
pre- and postcopulatory sexual selection). Using this experimental
protocol, males subjected to increased intensity of sexual selection
treatment are predicted to invest more in sperm quantity and/or
quality compared with males from the enforced monogamy treatment and to garner greater reproductive success as a consequence.
Perhaps surprisingly, such experimental sexual selection studies
have provided mixed results on the consistency with which sperm
and ejaculate traits have been targeted (Hosken et al. 2001; Pitnick
et al. 2001; Wigby and Chapman 2004; Crudgington et al. 2009).
The unanswered question is why there should be unpredictable
results with respect to sperm evolution.
Patterns of genetic (co)variation can constrain evolution, but
these are rarely studied with respect to reproductive traits and
experimental evolution. There are multiple points where genetic
variation could influence and constrain sperm evolution. The most
fundamental is a lack of additive genetic variation (Blows and
Hoffmann 2005). However, in a recent review of quantitative genetics studies on ejaculate evolution, the coefficients of additive
genetic variation (CV A s; “evolvability,” Houle 1992) of sperm
number (e.g., testes size) was relatively high compared to other
ejaculate traits, such as sperm viability and sperm length, traits
that also may influence male fertilization success (Simmons and
Moore 2009). These results suggest that testes size may evolve
more readily than sperm length. Genetic correlations between
traits within a sex could also constrain evolution. For example, in
the cockroach Nauphoeta cinerea, sperm number was genetically
negatively associated with testes mass (Moore et al. 2004), a result that would not have been predicted a priori. Such significant
genetic covariances between traits within a functional unit may
limit responses to selection but we have no information on these
general patterns. Indirect genetic effects may also matter. If the female environment influences the evolution of sperm (e.g., Pitnick
et al. 2009a), a lack of genetic variation for female reproductive
tract traits reduces indirect genetic effects and could slow sperm
evolution. To date only one experimental sexual selection study
has shown that changes in the intensity of sexual selection alter
the female reproductive tract (Hosken et al. 2001) but this study
did not examine the genetic architecture of these traits. Genetic
correlations between the sexes may also constrain the evolution
of reproductive traits. For example, artificial selection on the primary female sperm storage organ in Drosophila melanogaster,
the ventral (seminal) receptacle, found that males from the elongated receptacle line showed a weak correlated change in sperm
length (Miller and Pitnick 2002). A quantitative genetics study in
the dung beetle, Onthophagus taurus, found that sperm length and
spermathecal size are negatively genetically correlated whereas
sperm length and spermathecal shape are not genetically correlated (Simmons and Kotiaho 2007). The paucity of quantitative
genetics studies on such male and female traits means that we
cannot develop generalizations regarding patterns of genetic architecture for the interacting phenotype that is reproduction. Such
studies are needed to understand constraints and limitations to selection, particularly for experimental evolution.
Here, we examine the genetic architecture of interacting male
and female reproductive traits to test the extent to which evolution is constrained by the genetic (co)variance of sperm number and length and the morphology of the female reproductive
tract. We perform this study in Drosophila pseudoobscura that
has been subjected to experimental sexual selection and in which
sperm quantity and quality have not responded to this selection
(Crudgington et al. 2009). Understanding the genetic architecture of the ejaculate and female reproductive tract in this species
is also of interest because D. pseudoobscura is sperm heteromorphic. Males produce two distinct sperm morphologies each
having a specific role during fertilization; long sperm that fertilize eggs (Snook et al. 1994; Snook and Karr 1998; Snook and
Markow 2001) and short sperm that protect their brother fertilizing sperm from the effects of female spermicide (Holman and
Snook 2008). Sperm heteromorphism is widely distributed across
taxa (Till-Bottraud et al. 2005) yet there have been no quantitative
genetic analyses of this phenomenon. Such a study will inform
our understanding of the extent of heritable genetic variance for
sperm heteromorphism, and whether, and the extent to which,
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R H O N DA R . S N O O K E T A L .
trade-offs between either sperm numbers of each type, sperm size
of each type, or sperm size and number constrain the evolution
of this phenomenon. Moreover, by concurrently incorporating the
genetic (co)variance with the female reproductive tract, we can
elucidate the extent to which females might influence the evolution of this phenomenon.
Materials and Methods
EXPERIMENTAL REMOVAL AND ELEVATION OF
SEXUAL SELECTION
We manipulated opportunities for sexual selection by establishing
three experimental evolution treatments: (1) enforced monogamy
(M: one female and one male), (2) control promiscuity (C: one
female and three males), and (3) elevated promiscuity (E: one
female and six males). The establishment and maintenance of
these lines has previously been described in full in Crudgington
et al. (2005; 2009). Importantly, we have successfully controlled
for variation in effective population size by increasing the number
of families in the M treatment relative to C and E (Crudgington
et al. 2005; Bacigalupe et al. 2008; Snook et al. 2009).
BREEDING DESIGN
We used a standard paternal half-sibling breeding design to quantify the genetic variance–covariance matrices for reproductive
traits in replicate one of our experimentally evolved populations.
Previous work (Crudgington et al. 2009) has shown that experimental evolution has not resulted in changes in male sperm traits
and so we used individuals from a single replicate of each population (E, M, and C) and included experimental treatment as a fixed
effect in a mixed model design in all of our analyses. Treatment
was significant for many traits given the sample sizes of our studies, but there was no pattern as to which line differed for each trait
and, as Crudgington et al. (2009) show, no biological importance
of this effect.
For each treatment, virgin flies used as parents in the breeding
design were collected by CO 2 anesthesia and housed in single-sex
groups, 10 flies per food vial for five days until reproductive maturity. At maturity, a breeding design was implemented in which
sires were each housed with three dams for 24 h. The following
day, sires were discarded and each female was transferred to an
individual fresh food vial for five days to allow oviposition, after
which they were also discarded. We set up 20 sires per treatment,
for a total of 60 sires and 180 dams. On emergence, up to 10 randomly selected daughters and sons per dam were collected and
housed together in single-sex vials for five days until reproductive
maturity. After that period, daughters were frozen at −20◦ C and
sons were mated with random virgin females from the same treatment population (see below). Males were then frozen (for wings),
and sperm collected from their mates (see below). Morphological
reproductive traits were measured on four sons and four daughters
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randomly chosen per dam. Because of logistic reasons, we spread
out the number of paternal half-sibling families implemented
across seven months representing flies collected from generations
45–51 of our selection study to contribute individuals that formed
our breeding design. Flies from these collections were randomly
mated to produce the sires and dams used. For each generation,
three half-sibling families per treatment were set up. Therefore
generation was also entered as a fixed effect in the model.
REPRODUCTIVE TRAITS
Male sperm numbers and length
To measure sperm number and length, sons were mated to virgin unrelated females from the same experimental sexual selection
treatment and the sperm within the females subsequently dissected
for analysis. Following mating, sons were individually housed in
fresh vials for 24 h and subsequently frozen at −20◦ C. Drosophila
pseudoobscura is sperm heteromorphic, meaning males produce
two types of sperm, short and long. We measured both sperm types
as previously described (Crudgington et al. 2009) with mated females being ether-anaesthetized 2–4 h after mating and subsequently processed for sperm dissections. We controlled for any
potential scaling effects by quantifying wing size (wing vein IV),
a surrogate of body size, as previously described (Crudgington
et al. 2009).
Female reproductive tract morphology
The reproductive tract of Drosophila consists of two types of
sperm storage organs; two paired mushroom-shaped spermathecae and a ventral (seminal) receptacle that is an elongate blind-end
sac. The reproductive tracts of female offspring from the halfsibling design were each dissected in 20 μL phosphate-buffered
saline solution (PBS) on a glass slide. A glass coverslip was
placed over the sample and a digital picture of one spermatheca
was captured at 400× magnification (Leica DMLB Optics, Leica
Microsystems, Wetzlar, Germany). This procedure allowed us to
get intact spermathecae; we did not measure any spermatheca that
was ruptured. To capture images of the ventral receptacle, slight
pressure was applied to the corners of the coverslip, which allowed
flattening of both structures without stretching them (Miller and
Pitnick 2002; Holman et al. 2008). A digital image of the ventral
receptacle was also captured at 200× magnification. Spermathecal area and ventral receptacle length (from its blind-end to the
point where it joins the uterus) were obtained using the public
software Image-J (http://rsb.info.nih.gov/ij/). A single researcher
carried out all observations. We evaluated potential scaling effects on female reproductive tracts by measuring wing vein IV as
described for males.
QUANTITATIVE GENETIC ANALYSIS
We analyzed our data with ASREML. We obtained the different
variance components in the full model and nested submodel for
M A L E A N D F E M A L E C O E VO L U T I O N
each trait separately and between them (i.e., univariate and bivariate analysis, respectively) to determine significance of variance
components. Nested submodels were obtained by constraining a
variance (univariate) or covariance (bivariate) of the full model to
zero, which gives a new likelihood value. The statistical significance was assessed through likelihood ratio tests (LRTs) between
the models. The asymptotic null distribution of this test is a chisquare with one degree of freedom (i.e., the number of parameters
constrained to zero in the nested submodel).
Genetic correlation between the sexes
Genetic correlations between sex-limited traits were estimated
using the same procedure as cross-environmental genetic correlations, treating “sex” as an environment (Astles et al. 2006). We
used ASREML as above to calculate variances, covariances, and
significance.
Results
MALE TRAITS
The sample sizes, means, and SD of the four male traits are
presented in Table 1. Wing size and the lengths of both sperm types
all had moderate-to-high narrow-sense heritabilities (Table 2a).
The narrow-sense heritabilities of the numbers of both sperm types
were low. Evolvabilities, calculated as CV A of each trait, followed
a similar pattern to that of heritability. Coefficients of additive
genetic variation were modest for wing size and the lengths of
long and short sperm, but very low for the numbers of both sperm
types.
There were relatively few significant phenotypic and genetic
correlations among male traits (Table 3a). The only significant genetic correlations were a negative correlation between the length
of long sperm and wing length, a positive correlation between
length of short sperm and wing length, and a positive correlation
between numbers of both sperm types. This does not suggest any
pattern of functional integration or obvious constraints arising
from genetic correlations among any of the male traits. Of course,
correlations between numbers of sperm and other traits would
have low power given the low heritabilities of these traits.
FEMALE TRAITS
To ensure that we were justified in performing our analysis on the
combination of the lines, we first compared our two most extreme
lines, E and M, for response to experimental sexual selection.
There was no significant difference between treatments for the
size of the spermathecal area (F 1,504 = 0.8632, P = 0.3533)
or the ventral receptacle length (F 1,472 = 0.6341, P = 0.4262).
Therefore, as with sperm traits, we analyze and present combined
quantitative genetic data for female traits across all treatments.
Unlike sperm traits, there are no previous quantitative genetic
studies examining differences in female reproductive tract in response to experimental evolution. The sample sizes, means, and
SD for the three female traits are presented in Table 1. Females
are somewhat larger than males but not more variable. A significant component of the variation in female traits reflects additive
genetic variation (Table 3b), with very high and significant heritabilities for wing size and spermathecal area, and moderate and
significant heritability for ventral receptacle length. Evolvability
was modest for wing size and receptacle length and very low for
spermathecal area.
In contrast to male traits, female reproductive morphology
showed reasonable integration with significant positive phenotypic and genetic correlations among all traits (Table 4b). Thus
bigger females would be expected to have bigger reproductive
tracts, and selection for larger size could result in correlated
changes in the same direction in reproductive tract traits.
INTERSEX CORRELATIONS
Intersex genetic correlations suggest few shared genetic influences between male and female reproductive morphology. There
were few significant genetic correlations (Table 4). There was a
significant genetic correlation between female size and length of
Sample sizes and descriptive data for male and female traits. All analyses included 60 sires mated to three dams each. Total
number of offspring measured varied for each trait and is provided.
Table 1.
Sex
Trait
Offspring
Mean
SD
Males
Wing (mm)
Number of short sperm
Number of long sperm
Length of short sperm (μm)
Length of long sperm (μm)
689
712
712
716
715
2.11
20,583.10
10,983.40
91.58
314.81
0.07
6901.79
3117.99
11.68
12.96
Wing (mm)
Spermathecal area (μm2 )
Length of ventral receptacle (μm)
779
764
708
2.36
5264.26
683.39
0.06
523.27
77.03
Females
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Table 2.
Additive genetic variances (V A ), phenotypic variances, heritabilites (h2 ), coefficient of additive genetic variation (CV A ), and
residual coefficient of variation (CV R ) for (A) male traits and (B) female traits. Significance determined by a likelihood ratio test and
denoted by bold (P < 0.05). Asymptotic standard errors are presented in parenthesis. Variance estimators for sperm numbers were
obtained from raw data divided by 100. This procedure leaves unchanged estimators as a proportion of phenotypic variances.
(A) Male reproductive traits
VA
VP
h2 (SE)
CV A
CV R
0.0022
773.79
107.87
44.51
73.73
0.0026
3532.00
963.72
121.20
143.74
0.85 (0.23)
0.22 (0.15)
0.11 (0.14)
0.37 (0.14)
0.51 (0.20)
2.22
0.135
0.095
7.28
2.73
0.95
0.255
0.266
9.56
2.66
Trait
VA
VP
h2 (SE)
CV A
CV R
Wing (mm)
Spermathecal area (μm2 )
Length of ventral receptacle (μm)
0.0023
15.89
988.86
0.0024
23.59
4850.97
0.93 (0.25)
0.67 (0.18)
0.20 (0.12)
2.03
0.076
4.60
0.42
0.053
9.09
Wing (mm)
Number of short sperm
Number of long sperm
Length of short sperm (μm)
Length of long sperm (μm)
(B) Female reproductive traits
long and short sperm, with an identical pattern to the relationship
between male size and these traits. There was a significant negative correlation between spermathecal area and length of long
sperm. No other genetic correlations were significant, although
the correlation between female size and number of short sperm
approached significance. Surprisingly, we found no genetic correlation between male and female size indicating they could evolve
independently.
Discussion
Sexual selection theory predicts, and both macro- and microevolutionary studies generally support, that males should invest in the quantity and/or quality of sperm. Yet, experimental evolution studies provide mixed results on the response of
these traits when selection operates in a multivariate environment
(Crudgington et al. 2009). For example, neither long nor short
sperm numbers, nor lengths, respond to differences in the intensity
Phenotypic correlations (above the diagonal) and genetic correlations (below the diagonal) for (A) male traits and (B) female
traits. Significant estimators are denoted in bold. Level of significance of pairwise phenotypic correlations are provided parenthetically
below the estimate. Significance of genetic correlations (P<0.05) is determined by a likelihood ratio test in ASREML and denoted by bold.
Table 3.
SE of genetic correlations is given in parentheses below estimates.
(A) Phenotypic and genetic correlations among male reproductive traits
Wing (mm)
Wing (mm)
Number of short sperm
Number of long sperm
Length of short sperm (μm)
Length of long sperm (μm)
0.18 (0.30)
0.42 (0.31)
0.40 (0.18)
−0.40 (0.19)
Number of
short sperm
Number of
long sperm
0.27 (<0.001)
0.68 (0.31)
0.46 (0.30)
−0.07 (0.30)
−0.01 (0.775)
0.45 (<0.001)
−0.10 (0.30)
−0.32 (0.35)
Length of
short sperm (μm)
−0.04 (0.365)
0.04 (0.232)
−0.04 (0.292)
0.14
Length of
long sperm (μm)
−0.06 (0.090)
0.13 (<0.001)
−0.08 (0.040)
0.13 (<0.001)
-
(B) Phenotypic and genetic correlations among female reproductive traits
Wing (mm)
Spermathecal area (μm2 )
Length of ventral receptacle (μm)
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Wing (mm)
Spermathecal
area (μm2 )
Length of ventral
receptacle (μm)
0.39 (0.16)
0.29 (0.17)
0.24 (<0.001)
0.53 (0.16)
0.10 (<0.001)
0.24 (<0.001)
-
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Table 4. Genetic correlations between traits across the sexes determined by ASREML. Significance of genetic correlations (P<0.05) is
determined by a likelihood ratio test in ASREML. SE of genetic correlations is given in parentheses below estimates.
Female traits
Wing (mm)
Male traits
Wing (mm)
Number of short sperm
Number of long sperm
Length of short sperm (μm)
Length of long sperm (μm)
0.20 (0.18)
0.45 (0.28)
0.32 (0.28)
0.49 (0.16)
−0.39 (0.18)
of postcopulatory sexual selection in D. pseudoobscura (Crudgington et al. 2009). Here, we examined the genetic parameters that
might influence the evolution of sperm investment in this sperm
heteromorphic species and test the hypothesis that experimental
evolution is constrained by patterns of genetic variation. Importantly, we also considered sperm evolution from an interacting
phenotype perspective and quantify the indirect genetic variation of the female reproductive tract and the genetic correlations
between the sexes. There does not appear to be much genetic constraint to sperm evolution in our D. psuedoobscura populations.
Overall, we found that sperm and its components could evolve
independently both within and between the two types, whereas
the evolution of sperm number may be slowed due to low heritability and evolvability but these values were still nonzero. There
is no evidence that genetic constraints arise from indirect genetic
contributions of the female reproductive tract, or that intersexual
genetic correlations might constrain sperm evolution. We discuss
these results and their implications in detail below.
Numbers of both short and long sperm have relatively low
heritabilities and evolvabilities (Table 2a). Most other quantitative
genetic studies in insects have used testes size as a proxy for
sperm number (Simmons and Moore 2009), with the exception
of a study of N. cinerea, which estimated both testes size and
sperm number (Moore et al. 2004). Our heritability estimates of
both short and long sperm number are at the low end of the range
of values presented in these earlier studies. Likewise, CV A s in
these other studies on testes size were substantially larger (15.15–
18.85; Simmons and Moore 2009) than what we report, but note
that these values measure different aspects of sperm production.
In the one quantitative genetic study in which both testes mass and
sperm number have been examined, there was a negative genetic
correlation between testes mass and sperm number in N. cinerea
(Moore et al. 2004). Although CV A s of both traits were relatively
high in this species, the negative genetic correlation between these
traits indicates that if postcopulatory sexual selection targeted
these traits, then they would evolve in opposite directions (Moore
et al. 2004).
Spermathecal
area (μm2 )
−0.09 (0.20)
0.16 (0.31)
0.12 (0.31)
−0.02 (0.20)
−0.49 (0.19)
Length of ventral
receptacle (μm)
−0.22 (0.19)
−0.15 (0.29)
0.31 (0.31)
−0.07 (0.19)
−0.06 (0.21)
In contrast with sperm number, our estimated heritabilities
and CV A s of dimorphic sperm lengths are more commensurate
with data from sperm monomorphic species (Simmons and Moore
2009). Thus, the extent to which sperm length could evolve in our
populations of D. pseudoobscura, while limited, is greater than
that of sperm number. Overall, our results suggest that sperm traits
in D. pseudoobscura are closely associated with male fitness, perhaps associated with success in postcopulatory sexual selection,
and are at or near their phenotypic optimum. One caveat, which
is a common design element to other studies, is that we evaluated
the phenotypic and quantitative genetic parameters of only the
first ejaculate of reproductively mature but sexually naı̈ve males.
In most species, including D. pseudoobscura (Snook et al. 1994;
Snook and Markow 2001), males transfer many more sperm than
females store and this pattern may be particularly pronounced in
the first ejaculate in which the male has had time to accumulate
ejaculate resources. As the number of ejaculates increases for a
male, phenotypically the quantity (Montrose et al. 2004) and perhaps quality (Morrow and Gage 2001; Green 2003; Harris et al.
2007) of his ejaculate may change. Future studies should consider
examining the patterns of genetic (co)variance across ejaculates,
which will add tremendous insight into episodes of selection that
may influence sperm evolution and test the assumption that all
ejaculates are equal.
Genetic correlations between sperm traits also could constrain evolution. Sexual selection theory predicts that, because
ejaculates are expensive to produce, (Pitnick et al. 2009b; Pizzari
and Parker 2009), there should be phenotypic trade-offs between
sperm number and size (Parker 1982). For evolutionary trade-offs
to such selection to occur, patterns of genetic correlations need
to reflect this. Evidence is mixed on this point (Snook 2005).
The one quantitative genetic study that addresses this found no
genetic correlation between sperm length and either ejaculate volume or testis weight (Simmons and Kotiaho 2002). In this sperm
heteromorphic species, we found no significant genetic correlations among sperm traits other than numbers of the two types
(Table 3a).
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R H O N DA R . S N O O K E T A L .
The female reproductive tract can influence ejaculate evolution and coevolve (Presgraves et al. 1999; Miller and Pitnick
2002; Pitnick et al. 2009a) and it is therefore possible that indirect genetic effects might constrain sperm evolution. We found
that both spermathecal area and ventral receptacle length exhibited high-to-moderate heritabilities, similar to D. melanogaster
(Miller et al. 2001). Thus, there is no obvious constraint arising
from a lack of indirect genetic variation in female traits providing
the environment for sperm (Table 2b).
Genetic correlations between the sexes might also act as a
constraint, but again the patterns of correlations do not support
this hypothesis (Table 4). It is interesting that length of long sperm
was negatively genetically correlated with spermathecal area. This
result is consistent with the intraspecific pattern found in the
sperm monomorphic O. taurus (Simmons and Kotiaho 2007), but
differs from comparative patterns in both the sperm heteromorphic
Drosophila obscura group (Holman et al. 2008) and diopsid stalkeyed flies (Presgraves et al. 1999). In the obscura group, long
sperm length positively covaries with the ventral receptacle length
but does not with spermathecal area, and short sperm do not covary
with either female sperm storage organs (Holman et al. 2008). In
diopsids, long sperm positively covary with both spermathecal
area and ventral receptacle length whereas short sperm positively
covary only with spermathecal area (Presgraves et al. 1999). The
intraspecific pattern suggests that long sperm are sexually selected
(Simmons and Kotiaho 2007), but given that in our study we
find few significant correlations, the genetic relationship between
long sperm length and spermathecal length we find here requires a
cautious interpretation, especially as we see no phenotypic change
in our experimental evolution lines. As Houle and Rowe (2003)
point out, understanding patterns of evolution from experimental
evolution lines requires knowledge of selection as well as genetics.
In our lines, selection does not appear to target sperm length
(Crudgington et al. 2009).
Overall, our results suggest few genetic constraints arising
from genetic correlations within and between males and female
traits exist in this species, but sperm numbers do show low levels of genetic variation. This pattern differs from many other
sexually selected traits in which substantial genetic variation remains (Pomiankowski and Møller 1995) on which evolution may
act. Why? Additionally, why would genetic variation for sperm
components be greatly depleted in this species and not in other
species in which responses to either experimental or artificial
selection were found? Moreover, even within this species, why
is the response of some, but not all, ejaculate traits evolutionarily constrained? We have previously found that male accessory
gland size, but not sperm, responds to experimental sexual selection (Crudgington et al. 2009). Unfortunately, we did not measure
accessory gland size here, as this study was begun before we had
the data of Crudgington et al. (2009).
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EVOLUTION JULY 2010
The most obvious difference between our study and those
of other species in which quantitative genetics of sperm have
been examined is that D. pseudoobscura is sperm heteromorphic
whereas all other species examined are sperm monomorphic. But
why sperm heteromorphism would be more susceptible to loss
of genetic variation when the ejaculate is not well-integrated is
a conundrum. One popular explanation for the high levels of
genetic variation associated with sexually selected traits is that
they tend to be highly condition sensitive (e.g., Rowe and Houle
1996; Cotton et al. 2004). There are only two studies showing
condition dependence (measured as male body size) of sperm in
sperm monomorphic species (Amitin and Pitnick 2006; Skinner
and Watt 2007), but there are no such studies for sperm heteromorphic species. However, a number of studies on diverse taxa
report either no or a negative relationship between male body
size and sperm length (Pitnick et al. 2009b). It would be valuable to examine whether heteromorphic sperm are less sensitive
to condition than other species and whether the different sperm
types differ in respect to such a response. Given that we found
no genetic relationship between male size (measured by wing
length) and either number or length of either sperm type, sperm
in this species indeed may be less sensitive to condition dependence and therefore may be more susceptible to loss of genetic
variation.
In summary, our results show that extrapolating expected
evolution from purely phenotypic studies, or directly from studies of selection, should be made with caution. Patterns of genetic variation are complex, and there are multiple ways that
constraints can arise as a result of the multivariate nature of reproductive traits (Blows and Hoffmann 2005; Blows 2007), and
as a result of potentially complicated responses to sexual conflict
arising from indirect genetic effects (Moore and Pizzari 2005).
The patterns reported here are not necessarily ones we would
have predicted a priori, as has been true in other studies of genetics of male reproductive traits when their multivariate nature is
considered (Moore et al. 2004). We iterate Simmons and Moore’s
(2009) call for more studies of the genetic influences on male
and female reproductive traits that may experience sexual selection. Experimental evolution studies are useful in defining what
may happen, but not necessarily why something did not happen.
For this we need quantitative genetics combined with studies of
selection.
ACKNOWLEDGMENTS
We thank H. Crudgington, T. Turner, K. Hutchence, N. Badcock, and
the Snook laboratory for help during the experiment and T. Moore for
comments on the manuscript. We are especially grateful to J. Hunt, who
ran all the ASREML analyses. Comments from two anonymous reviewers
helped us to clarify our work. Grants from NSF (USA) to RRS and NERC
(UK) to RRS and AJM funded this work.
M A L E A N D F E M A L E C O E VO L U T I O N
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Associate Editor: P. Stockley