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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 3662 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 B R I E F C O M M U N I C AT I O N 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 EVOLUTION DECEMBER 2013 3663 B R I E F C O M M U N I C AT I O N 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 3664 EVOLUTION DECEMBER 2013 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] B R I E F C O M M U N I C AT I O N −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 EVOLUTION DECEMBER 2013 3665 B R I E F C O M M U N I C AT I O N 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 3666 EVOLUTION DECEMBER 2013 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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