Download THE VARIABILITY IS IN THE SEX CHROMOSOMES

B R I E F C O M M U N I C AT I O N
doi:10.1111/evo.12224
THE VARIABILITY IS IN THE SEX
CHROMOSOMES
Klaus Reinhold1 and Leif Engqvist1,2
1
Evolutionary Biology, Bielefeld University, Bielefeld, Germany
2
E-mail: [email protected]
Received December 19, 2012
Accepted July 16, 2013
Sex differences in the mean trait expression are well documented, not only for traits that are directly associated with reproduction.
Less is known about how the variability of traits differs between males and females. In species with sex chromosomes and dosage
compensation, the heterogametic sex is expected to show larger trait variability (“sex-chromosome hypothesis”), yet this central
prediction, based on fundamental genetic principles, has never been evaluated in detail. Here we show that in species with
heterogametic males, male variability in body size is significantly larger than in females, whereas the opposite can be shown for
species with heterogametic females. These results support the prediction of the sex-chromosome hypothesis that individuals of the
heterogametic sex should be more variable. We argue that the pattern demonstrated here for sex-specific body size variability is
likely to apply to any trait and needs to be considered when testing predictions about sex-specific variability and sexual selection.
KEY WORDS:
Body size, dosage compensation, genetic sex determination, phenotypic variability, sexual dimorphism, sexual
selection.
Since Darwin’s second most famous book (Darwin 1871), biologists have been captivated by describing and explaining differences between the sexes. In many species with separate male and
female sexes, the composition of sex chromosomes within zygotes
determines offspring sex (Bell 1982). One sex, the heterogametic
sex, has two different sex chromosomes and one of them is often
degenerated, whereas the homogametic sex has two identical sex
chromosomes. In most cases, the sexes differ not only in primary
sexual traits but also in many other traits. These characters may
for example encompass morphological, physiological, or behavioral traits. Research on such sex-differential traits has led to a
large number of studies in different disciplines demonstrating sex
differences and examining the proximate and ultimate causes of
sexual dimorphism (Hedrick and Temeles 1989; Andersson 1994;
Halpern 2000; Morris et al. 2004; Fairbairn et al. 2007). Although
the sex chromosomes are involved in sex determination, it is not
necessary that sex-specific traits are under the control of sex chromosomal genes (Andersson 1994; Mank 2009a). However, for
traits related to human brain function, animal reproduction, and
sexual selection, the X-chromosomes seem to play an especially
C
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important role (Reinhold 1998; Saifi and Chandra 1999; Zechner
et al. 2001; Gibson et al. 2002).
With regard to sex-differential trait variability, the sex chromosomes have been proposed to play an important role, too (James
1973; Cowley et al. 1986; Cowley and Atchley 1988; Lynch and
Walsh 1998, p. 715 ff; Long and Rice 2007). The Y-chromosome
in mammals is almost devoid of genes besides the male sexdetermining factors, whereas the X-chromosome has about its
fair share of genes. Binomial sampling of the large X chromosomes leads to the intuitive prediction that males should show
larger variation. In females, the traits that are influenced by Xchromosomal genes will be under the average influence of the
two parental copies, whereas in males, the effect of the single
X-chromosome will not be averaged. As a result, male mammals
are expected to show larger variability than females in all traits
that are, at least to some extent, influenced by X-chromosomal
alleles.
Theoretical considerations reveal a slightly more complicated picture (illustrated in Fig. 1). Under the simplest genetic
assumptions—alleles contribute additively to trait expression
C 2013 The Society for the Study of Evolution.
2013 The Author(s). Evolution Evolution 67-12: 3662–3668
sex specific genetic variance
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0.4
heterogametic
homogametic (additive effects)
homogametic (with dominance)
0.3
h=1.0
0.2
h=0.75
0.1
h=0.5
0.0
0.0
0.2
0.4
0.6
0.8
1.0
allele frequency [q]
Figure 1.
Expected sex-specific genetic variability for a trait de-
termined by a single sex-chromosomal polymorphic locus, segregating for two alleles a and A in Hardy–Weinberg equilibrium. For
this model, the genotypic values can be described as follows—
aa : ωhom , aA : ωhom + hα, AA : ωhom + α in the homogametic and
a : ωhet , A : ωhet + β in the heterogametic sex. For the homogametic sex, the expected genetic variance can be calculated as
2
σhom
= α 2 q(1 − q)γ, where γ = q2 (1 − 2h)2 + q (1 − 2h) (1 + 2h) +
2 =
2
2h . The corresponding value for the heterogametic sex is σhet
2
β q(1 − q). The allele frequency q is referring to the frequency of
A. The parameter h gives the degree of dominance and α and
β the values of substitutions in the heterogametic and homogametic sex, respectively. In this figure, it is as often assumed that
α = β(= 1), indicating complete dosage compensation. Note that
for complete additive effects (i.e., h = 0.5), γ = 0.5. Hence, the
genetic variance in the homogametic sex is exactly half of the
genetic variance in the heterogametic sex (see also James 1973,
for similar derivations). Nevertheless, this is only accurate when
assuming complete dosage compensation; only then the effect of
the two chromosomes will be averaged in the homogametic sex.
Based on the above results, it is straightforward to show that
in the absence of dominance and epistatic effects, the heterogametic:homogametic ratio of sex chromosome–linked genetic variation will equal 2 × (α/β)2 . Here α/β signifies the heterogametic:
homogametic sex-chromosomal gene expression ratio (e.g., 1 for
complete dosage compensation, and 1/2 for a complete lack of
dosage compensation).
(heterozygotes are intermediate to homozygotes), and they have
equal hemizygous and homozygous effects on trait expression (e.g., due to dosage compensation; Cowley et al. 1986;
Charlesworth 1996)—a polymorphic sex chromosome–linked locus will contribute twice as much to trait variance in the heterogametic sex, as it will to variance in the homogametic sex (see also
James 1973; Lynch and Walsh 1998, p. 715 ff). Quantitative traits
are of course polygenic and are likely influenced by genes spread
across the sex chromosome and the autosomes. The contribution
of the sex chromosome to trait variance should therefore depend
on its relative size within the genome (i.e., the proportion of genes
that it carries), with trait variance differences between the sexes
being less pronounced in species with small sex chromosomes,
and more pronounced in species with large sex chromosomes.
In addition, differences will be dampened by environmental effects (i.e., will be lower for traits with low heritability). Even
so, qualitative predictions of the model remain valid for any trait
that is to some extent heritable irrespective of sex chromosome
sizes. Incomplete dosage compensation and/or dominance of the
minor (less frequent) allele can also reduce, or in some cases
reverse, predicted patterns of variance within males versus females (see Fig. 1). Nevertheless, plausible evolutionary models
for the maintenance of genetic variation predict partial recessivity among minor alleles (e.g., Mukai 1969; Simmons and Crow
1977). In such cases, variance of the heterogametic sex will be
highly sensitive to sex chromosome–linked polymorphism, and
the qualitative predictions involving heterogametic and homogametic trait variances are robust. Thus, overall the phenotypic variance of traits is expected to be higher in the heterogametic sex,
but the exact predicted magnitude is difficult to assess without
knowing, for instance, trait heritability and underlying genetic
architecture.
Surprisingly, even though this is a general prediction concerning differences in phenotypic variation between the heterogametic and the homogametic sex, it has never been formally tested
and its application has largely been limited to humans and within
humans it has most often been used with respect to variation in
intelligence (Lehrke 1997; Johnson et al. 2009; for exceptions see
Lehre et al. 2009). Furthermore, even though there is some evidence for a sex difference in variability of IQ and mental abilities
in humans (Hedges and Nowell 1995; Lehre et al. 2009), the role
of genetics in causing it is still a matter of controversy and debate
(Brockmann 2005; Irwing and Lynn 2005; Shell 2005; Summers
2005; Craig et al. 2009; Mills 2011). Nevertheless, the above argument should be applicable to other taxa, for example to insects
with heterogametic males, and also to groups with heterogametic
females, such as birds and butterflies. If it was possible to show
that the pattern of sex-specific variation is reversed in these two
groups, this would make a strong case in favor of the sex- chromosome hypothesis. Because the variability is expected to be larger
in the heterogametic sex, phylogenetic differences in the mode of
sex determination constitute natural experiments that can be used
for scrutinizing the sex-chromosome hypothesis.
Here, we examine the proposed effect of sex chromosomes
on the variability of a less debated trait, body size. With the
aim to determine whether the heterogametic sex shows the larger
variability predicted by the sex-chromosome hypothesis, we collected data on male and female body size in animal groups differing in the mode of genetic sex determination (i.e., male or
female heterogamety). For each sex, we then calculated the coefficients of variation (CV) in body size and compared the extent
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of variation between males and females in the different groups by
using the following index of sex-differential size variation:
Ivar = LOG(CVmale size /CVfemale size ).
Methods
We collected data on CVs of body size from the literature for
the following four animal groups: mammals, insects (taxa with
heterogametic males), birds, and butterflies. The first two groups
have heterogametic males and the last two groups have heterogametic females. We chose not to include other potentially interesting taxa with frequent sex-chromosome transitions, such as fish,
amphibians, and reptiles (Ezaz et al. 2006; Mank et al. 2006), as
these groups have indeterminate growth, and thus sex differential
variability in body size will be confounded by sex differences in
life span and/or growth rate. Various combinations of keywords
([(sexual dimorphism OR coefficient of variation) AND (body
size and male and female) AND (bird OR mammal OR insect
OR butterfl∗)]) were used to search Biological Abstracts, Web of
Science, and Google Scholar for available data. Certainly many
manuscripts have escaped our attention. However, the search was
random with regard to animal species and unbiased with regard to
size variation and trait type. If CV values were not given, but could
be calculated from the presented statistical data, for example from
standard deviation or standard error, these data were also used.
To avoid using biased CV values (Sokal and Rohlf 1995), all CVs
were adjusted by the factor 1 + (1/4n). Data were only used if
sample size and mean trait value were available in addition to the
CV and if CVs for both sexes could be ascertained on the same
traits within the same publication. To ensure accurate estimates
for CVs, data were only used if CVs or the statistical data on body
size used to calculate the CV were given with at least two digits
accuracy and if sample size was at least 10.
Only total body mass or length, or the length or area of
large body parts (in birds wing and culmen size, in mammals leg
or head length, in butterflies wing area or size, and in the other
insects leg, body, wing, or head size) were used as smaller parts of
the body might vary independently of body size and might have
much higher measurement errors. Sex-differential variation in
size is likely to be influenced by temporal or spatial heterogeneity
in body size or by animal age or reproductive status. All data
points where evidence suggested that one of these conditions was
fulfilled were not used for further analyses to avoid that biased
values for the variation of body size were used. Overall, we found
292 articles that contained sufficient data to be included in our
analysis (Appendix S1).
If several values were given for the same trait in a single
manuscript, for example for different years or populations, average values for trait size and CV were calculated by weighting
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the individual values with the square root of the sample size. To
compare the extent of variation between males and females, we
used the index of sex-differential size variation, Ivar , given above.
If for the same species several values could be calculated from
different traits or different manuscripts, the indices were averaged by weighing the individual values with the square root of
the geometric mean sample size for males and females to avoid
pseudo-replication. In total, we were able to analyze data on variability in body size for both males and females for 385 different
species (mammals: 97, birds: 109, insects: 104, butterflies: 75;
Appendix S1). In addition, we included one Trichopteran species
to the butterfly data set, as this is the phylogenetic sister group of
butterflies and also has heterogametic females. (Thus, the accurate
term for this taxon should rather be Amphiesmenoptera.)
To compare whether variation in body size differs between
the homogametic and the heterogametic sex, male or female heterogamety was entered as fixed factor in a mixed model with
taxonomic group as random factor. The index of sex-differential
size variability was entered as dependent variable, and the sexual
dimorphism index (SDI = LOG[male size/female size]) was entered as a covariate. This was done to statistically control for the
possibility that the sex with the larger mean trait size also has the
larger trait variability. To also control for potential phylogenetic
nonindependence of data points, subgroups (families in butterflies, orders in the other insects, mammals, and birds) were used
as random factors nested within each of the four main taxonomic
groups. All statistical tests were performed with R 2.14.1 (R
Development Core Team 2011) using linear mixed effects models
(R function lme in library nlme; Pinheiro et al. 2006).
Results
In all four groups of animals, the indices of sex differential variation in body size differed significantly from equality in the expected direction (see Fig. 2). In butterflies and birds in which
females are the heterogametic sex, males showed significantly
lower variability (mean ± SE Ivar for butterflies: −0.0370 ±
0.0094, likelihood-ratio test [LRT]: χ21 = 11.2, P < 0.001; birds:
−0.0176 ± 0.0078, LRT: χ21 = 5.64, P = 0.018), and the mean
indices are equivalent to 8.2% and 4.0% lower coefficients of variation in males compared to females. In contrast, male variation in
body size was larger in mammals and insects with heterogametic
males (mean ± SE Ivar for mammals: 0.0194 ± 0.0088, LRT: χ21 =
4.72, P = 0.03; insects: 0.0230 ± 0.0082, LRT: χ21 = 5.33, P =
0.021), and the mean indices are equivalent to an increase in
male CV of 4.6% and 5.4%. A mixed model controlling for taxonomic group showed that the effect of male or female heterogamety is highly significant (male heterogametic: 0.0213 ± 0.0059,
female heterogametic: −0.0256 ± 0.0059; estimated difference:
0.06
male heterogametic
female heterogametic
0.04
10
0.02
5
0.00
0
−0.02
−5
−0.04
% larger variation in males
index of variation difference [mean ± SE]
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−10
−0.06
mammals
insects
birds
butterflies
Sex differential variability in body size in four animal
taxa. The sex difference in size variation given in log-scale on the
Figure 2.
Y-axis was calculated as Ivar = LOG(CVmale size ) − LOG(CVfemale size ).
0.0470 ± 0.0083; LRT: χ21 = 10.2; P = 0.0014) and that there was
no significant effect of sexual size dimorphism on sex-differential
variability in body size (0.109 ± 0.089, LRT: χ21 = 1.52; P =
0.22). In none of the four groups a difference between the subgroups could be found (in all cases P > 0.1), further indicating
that it is the mode of sex determination that is causal rather than
some other phylogenetic signal. More specifically, the standard
deviation of the calculated variation index across all subgroups
was estimated as σB = 0.020 compared to σW = 0.080 within
taxonomic subgroups. When the mode of sex determination was
statistically controlled for, the standard deviation of Ivar across all
subgroups dropped drastically to σB = 1.5E − 6, indicating only
weak scope for additional phylogenetic dependencies within the
four main groups. Furthermore, when accounting for the effect of
male or female heterogamety, no significant difference between
the four main groups in size variability remained (LRT: χ21 =
0.086, P = 0.77). Similarly, no significant difference between the
four groups could be detected if sex-differential variability in size
was estimated as Ivar = LOG(CVheterogametic sex /CVhomogametic sex )
(LRT: χ21 = 0.238, P = 0.63), implying that the magnitude of sex
differential variability in body size was equivalent for the four
animal taxa.
Discussion
The results shown here are consistent with the sex-chromosome
hypothesis predicting sex differential variation in phenotypes. We
could only analyze data from four independent taxonomic groups,
because the number of well-studied clades with female heterogamety and determinate growth is limited. Nevertheless, the pattern
was remarkably clear and unambiguous. Furthermore, there was a
surprisingly homogenous effect across the major taxa, indicating
only weak phylogenetic dependencies. Thus, in addition to the
common observation that the two sexes differ in the average size
of traits, this study shows for the first time that the sexes also
differ in trait variability in a predictable way.
We here used body size for which substantial high-quality
data on intrasexual phenotypic variation is available, but the hypothesis is sufficiently general and should be applicable to any
conceivable trait in all species with sex chromosomes. There
should be two notable exceptions: (i) if the sex chromosomes
do not contribute to trait variability and (ii) if sex chromosome
dosage compensation would be achieved by a mechanism involving a completely imprinted inactivation of one of the two sex
chromosomes in the homogametic sex (candidate taxa: marsupials; Graves 1996; Huynh and Lee 2005). Dependent on the
genetic details, it should also be possible to make more detailed
predictions than we have attempted here. Crucially, the magnitude of the between-sex variance difference will depend on the
proportion of variability attributed to heritable variation on the
nondegenerate sex chromosome, and the completeness of dosage
compensation. Here, our results are not as conclusive as our main
results. Although achieved by means of entirely different mechanisms, mammals, and insects with XY/0 sex determination both
seem to display global dosage compensation (see Charlesworth
1996); to counteract the halving of sex chromosomal gene dosage
in the heterogametic sex, the expression level of all sex chromosomal genes are on average 50% lower in the homogametic
compared to the heterogametic sex (see Prince et al. 2010 for
an exception). Birds and butterflies, however, seem to lack a
global mechanism, and instead dosage compensation is regulated
locally, resulting in higher average levels of sex chromosomal
gene products in the homogametic sex (Mank 2009b; Mank and
Ellegren 2009; Walters and Hardcastle 2011). Based on the reported male:female gene expression ratios in these groups, trait
variance should still be larger in the heterogametic sex, but the
difference in genetic and phenotypic variance between the sexes
should be lower than in groups with full dosage compensation.
Indeed our smallest effect size was found in birds, but the conspicuously largest effects size was found in butterflies. All else being
equal, species with large sex chromosomes should exhibit larger
differences of variance between the heterogametic and homogametic sexes than species with small sex chromosomes. However,
the sex chromosomes in butterflies are in fact relatively small (ca.
3–5% of the genome, see Presgraves 2002), at least not larger
than in the other taxa. Thus taken together, for butterflies our
obtained estimate for sex differential body size variability was
unexpectedly large. Nevertheless, these considerations also indicate that it should be worthwhile to look at sex-specific genetic
variance in species where the relative contribution of sex chromosomal genes are well known. In strong concordance with the
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sex-chromosome hypothesis, male X-linked variance is roughly
twice as large as the female X-linked variance for several wing
traits in Drosophila melanogaster (Cowley et al. 1986) and male
X-linked variance exceeds female X-linked variance for 20 of 22
morphological traits (Cowley et al. 1986; Cowley and Atchley
1988). Similarly, in the same species, genetic variance for adult
locomotary activity attributed to the X-chromosome is roughly
two to three times larger in males than in females (Long and
Rice 2007). Furthermore, an initial assessment of the literature
on sex-specific genetic variances and heritiabilities (studies cited
in Poissant et al. 2010) reveal patterns that both conform with
the sex-chromosome hypothesis and the data obtained for phenotypic variances here. In the handful of bird species for which
genetic variances and/or trait heritabilities have been estimated
separately for males and females, these are with very few exceptions larger in females (collared flycatcher: Brommer et al. 2007;
turkey: Chapuis et al. 1996; house sparrow: Jensen et al. 2003;
pigeon: Mignon-Grasteau et al. 2000; barn swallow: Møller 1993;
red junglefowl: Parker and Garant 2004; zebra finch: Price and
Burley 1993; Darwin’s finches: Price 1984). In insects and mammals, there are more exceptions, but the higher number of studies
also makes it more probable to find nonconformities. Nevertheless, on a first glance there are conspicuously more species with
larger genetic variances in the males (see, e.g., Eisen and Legates
1966; Preziosi and Roff 1998; Blanckenhorn 2002; Brown et al.
2004; Rolff et al. 2005; Pan et al. 2007; Poissant et al. 2008) than
in females (e.g., Havill et al. 2004; Foerster et al. 2007). Yet at
present, the amount of quantitative data on sex differences in genetic variability that can be assigned to the sex chromosome is still
limited and restricted to few groups, and it thus seems premature
to draw any definite conclusions.
Despite its general implications, the phenomenon of larger
variability in the heterogametic sex has received only limited attention, and it would be interesting to investigate more traits in additional taxa. Until now, the implications of the sex-chromosome
hypothesis predicting sex differences in trait variability has
mainly been used in psychology to explain the higher variability
in mental scores and IQ of men compared to women. Yet both
the explanation for this and its implications have been very controversial (Hedges and Nowell 1995; Lehrke 1997; Brockmann
2005; Irwing and Lynn 2005; Shell 2005; Summers 2005; Craig
et al. 2009; Lehre et al. 2009; Mills 2011). Our results here reemphasize that in humans greater variability in men compared to
women could be a by-product of the mode of sex determination in
humans.
The sex-chromosome hypothesis is not the only one that has
been proposed for explaining sex differences in trait variability.
It has also been argued that sexual selection can play an important role (Pomiankowski and Møller 1995). This is so because
potential modifier genes that would increase the variability of a
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sexually selected trait in one of the sexes will be beneficial, given
that directional selection on the trait is greater than linear (Shnol
and Kondrashov 1993). Our results do not support this hypothesis, because the variability in body size (frequently a sexually
selected trait) was not universally larger in males. Instead our
results highlight that greater trait variability in one of the sexes
does not necessarily require any additional adaptive explanation
if the mode of sex determination is taken into account. Our results
demonstrate the existence of constraints imposed by the genetic
architecture and implies that predictions about sex-specific variance need to consider the mode of sex determination.
ACKNOWLEDGMENTS
The authors thank M. Greenfield, H. Schielzeth, and two anonymous
reviewers who gave valuable comments on previous versions of this
manuscript.
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Associate Editor: J. Mank
Supporting Information
Additional Supporting Information may be found in the online version of this article at the publisher’s website:
Appendix S1. List of species and measurements included in the study.
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