embryonic development, coinciding with female meiosis. Conversely male-biased genes

Abstract

Classical sexual selection theory has been used to explain some of the very common sexual dimorphisms in the animal kingdom. It is well known that sexually selected traits experience strong selection pressures from processes such as sperm competition and female choice, and therefore evolve at accelerated rates. To date most studies of sexual selection theory have been ecology-based focusing on phenotypes. It is currently unclear how and if sexual selection operates on the molecular level. In this study I used gene expression data for chicken to determine what types of selectional processes operate in genes which experience sex-biased expression in both gonad and brain tissue. Mean d

/d

as well as the M-K test were used to determine the types of selection acting upon these genes. I found increased signatures of selection for female-biased genes during

embryonic development, coinciding with female meiosis. Conversely male-biased genes

showed higher selective signatures during adulthood, during which male spermatogenesis

occurs. Positive selection on genes implicit in the reproductive tract of chicken could not

be determined due to the lack of a comprehensive polymorphism database for chicken. I

argue that sex-biased genes in chicken gonad experience accelerated rates of evolution

due to sexual selection. No obvious distinction in evolutionary rates between male and

female-biased genes expressed in the brain could be detected.

Introduction

Sexual dimorphisms are abundant in the animal kingdom, ranging from the most visually evident, morphological and behavioural, to more inconspicuous, physiological and gametic. Classically, sexual dimorphisms are explained by sexual selection theory whereby certain traits related to reproduction are selected for during mating. Sexually selected traits such as tail length, colour, and size are under strong directional selection and therefore experience faster rates of evolution than non-sexually selected traits (Zhang et al. 2004). Most tests to date of the role that sexual selection plays on the evolution of morphological traits have been on the level of the phenotype, and involved mating assays. It is however important to understand the underlying genetic changes which produce morphological variation during the evolution of a species (Carroll 2000), particularly the genetic mechanism underlying sexually selected traits. Thus, an interesting question that arises is whether or not sexual selection can be detected at the molecular level.

A surprising fact of sexual dimorphisms is that sexual differences persist only on the phenotypic level whereas at the coding level, males and females are nearly identical (Ellegren & Parsch 2007). Thus differences which do occur do so because of cis-

regulatory changes affecting the expression of genes (Carroll 2000). That is, the same set of genes is regulated differentially such that expression levels between males and females vary leading to distinct sexual dimorphisms. Candidate genes which could shed light on the evolution of sexual dimorphisms are those genes which exhibit sex-biased expression (Connallon & Knowles 2005). Genes with sex-biased expression, i.e. produce sexually dimorphic expression profiles, are commonly referred to as sex-biased genes (Ellegren &

Parsch 2007). Furthermore, these dimorphic expression patterns are frequently due to up-

regulation of sex-biased genes one sex, and, to a lesser extent down-regulation in the

other sex (Connallon & Knowles 2005 and Zhang et al. 2004). Therefore, studying

changes in sex-biased genes could shed light into how sexual dimorphisms persist in

nature.

Sex-biased genes often result when a single gene develops antagonistic selection

pressures in males and females (Ellegren & Parsch 2007). This occurs because males and females often differ in fitness optima for a particular trait. For example, testosterone expression optima are different between males and females since it is essential for male reproduction and detrimental to female reproduction (Moller et al. 2005). Traits, such as testosterone levels, which are beneficial to one sex and detrimental to the other sex, are termed sexually antagonistic (Rice & Chippindale 2002), and the conflict which arises between the sexes is resolved through sex-biased gene expression (Connallon & Knowles 2005). Typically, sex-biased gene expression results from sexual antagonism and the accumulation adaptive mutations which occur predominantly in the male lineages, implying that male traits evolve at a faster rate than females (Connallon & Knowles 2005, and Zhang et al. 2004) This process is further complicated by the location and number of tissues a particular gene is expressed in.

Expression in multiple tissues, a process we refer to here as pleiotropy, has been shown to constrain the resolution of sexual antagonism in chicken and mouse (Mank et al.

2007), as well as Drosophila (Zhang et al. 2007 and Larracuente et al. 2008). It has been suggested that as a gene is expressed in more tissues, negative selection becomes stronger and the gene thus becomes constrained (Khaitovich et al. 2008). This arises because each tissue has different selection pressures, which leads to constraints on the possible changes which can occur in gene expression in order for that gene to be functional in a particular tissue, this in turn constrains divergence of that gene. By this mechanism sex-biased gene expression is expected to be highest in genes expressed in fewer tissues because they will not be constrained and can thus develop differential expression.

It is well known that genes involved in sex related processes experience faster rates of change in their coding sequences than genes which are not related to sex (Zhang et al.

2004). Thus sexual selection theory may be an ideal construct with which we can use to

explain the evolution of sex-biased genes. Two classical components of sexual selection

which can affect the evolution of phenotypes are female choice and sperm competition.

other potential mates, which directly skews the allele frequency in the next generation (Wigby & Chapman 2004). Furthermore, the environment created by a female when she mates multiply encourages competition between sperm for fertilization success;

promoting evolution of adaptive traits (Wigby & Chapman 2004).

Several types of tests have been adopted in order to distinguish forces influencing the allele frequency spectrum, including the d

/d

test (Miyata & Yasunaga 1980),

McDonald-Kreitman test (McDonald & Kreitman 1991), Tajima’s D (Tajima 1989), and Fay and Wu’s H ( Fay & Wu 2000). Two common forms of natural selection are positive and purifying selection; several studies have shown that these types of selection affect gene expression (Eyre-Walker 2006, Shapiro et al. 2007, Larracuente et al. 2008, Singh et al. 2007, Khaitovich et al. 2008). The d

/d

test is probably the most informative of these tests to predict the type of selection, as the other aforementioned population genetic tests measure only departures from neutrality (Yang & Bielawski 2000).

The magnitude of sexual dimorphisms in birds makes this an interesting clade with which to study the evolution of sex-biased gene expression. Furthermore, females are the

heterogametic sex which provides an interesting contrast to studies on mammals and Drosophila which are male heterogametic. Additionally it has been noted that female heterogamety is under different selective forces than male heterogamety (Axelsson et al.

2004). In this paper I will try to determine whether or not the evolution of sex-biased genes can be explained by classical sexual selection theory. I use chicken microarray data to study the evolution of sex-biased gene expression in a female heterogametic system.

Microarray data allows for the unique opportunity to determine which ‘evolutionary

processes shape the genome’ (Connallon & Knowles 2005). I calculated divergence

estimates in genes expressed in brain and gonad. This along with analysis of chicken

polymorphisms should allow me to determine which processes, either positive selection

or genetic drift, influence the pattern of evolution for sex-biased genes in chicken.

Materials and Methods

15 male and 15 female white leghorn chickens were euthanized at each of embryonic days (ED) 10, 15, 19 and reproductive adulthood. Rinn et al. (2005) found that sex-biased gene expression occurs in mouse embryos at day 10.5 after fertilization, and sex

differences persist into adulthood. Therefore expression profiles during development have the potential to change intensity throughout development, and as such a study incorporating changes throughout development could be interesting. Animals were immediately dissected and whole brain samples were taken from all time points, and gonad samples from the latter three time points. Gene expression profiles were obtained using the Affymetrix microarray genechip platform. Complete details of the sample preparation and microarray methods can be found in Mank & Ellegren (2009).

The degree of sex-bias was calculated as the log

(male/female). Fold-change cutoffs were used to define the type of bias for each gene; male, female or unbiased. Fold-change refers to the degree of difference in expression of a gene between the sexes. Because gonadal tissue is highly sexually dimorphic, we used higher fold change levels to

compensate for the increased degree of sex-bias seen in this tissue compared to brain, as previously implemented (Mank et al. 2007). Brain fold-change values were 125%, 133%

and 150%, while 200%, 250% and 300% were used for gonad. Genes which did not meet these cutoff values were classified as unbiased.

Divergence analysis

Divergence in protein sequence between two species is commonly measured as the ratio

(ω) of nonsynonymous (d

) and synonymous (d

) mutations (Yang & Bielawski 2000),

where a nonsynonymous mutation has the effect of changing the amino acid, while a

synonymous mutation, a product of the redundancy of the genetic code, is silent. d

and

d

are defined as the number of mutations divided by the total possible mutational sites of

the same type. In this type of analysis the nature of selection driving protein evolution

can be deduced. The following inferences can be made (Yang & Bielawski 2000): ω >1

is an indication of positive selection since there are more selectively advantageous

mutations are being purged due to purifying selection there are fewer nonsynonymous than synonymous mutations and ω < 1. In the neutral case (ω = 1), nonsynonymous mutations are fixed at the same rate as synonymous mutations.

In this study we estimated values of d

and d

for chicken using a phylogenetic approach.

This was accomplished by first identifying 1:1 orthologs for significantly expressed chicken genes based on the ENSEMBL chicken predicted coding regions with reciprocal BLAST to the zebra finch (Taeniopygia guttata) genome draft sequence. For all resulting 1:1 orthologs, PAML (Yang 1997) was used to estimate the number of synonymous and nonsynonymous sites and changes between species. The resulting data were then filtered;

all genes which were mutationally saturated (d

>2) were removed from further analysis to reduce to problems with mutational saturation. Transcripts with coding alignments

<100bp or which had premature stop codons were also eliminated. Finally, due to the confounding effects of the accelerated rate of evolution for Z-linked genes (Mank et al.

2007), in combination with the overall male-bias of the chromosome due to lack of complete dosage compensation (Ellegren et al. 2007), I focused all further analysis solely on the autosomes.

For each class of genes, average d

and d

were calculated by dividing the total sum of substitutions by the sum of the number of possible sites for each class of genes (male- biased, female-biased, and unbiased). Mean values of d

/d

were then calculated from these values. Measurements of d

/d

were calculated in this manner because this

methodology weighs divergence estimates by the alignment length and at the same time allows for the inclusion of loci with d

equal to zero (Mank et al. 2007).

Significant differences in divergence estimates among expression classes were assessed

with permutation tests of 1000 replicates, comparing sex-biased categories to the

unbiased estimates.

Tissue of maximal expression

Genes expressed in the brain or gonad are not necessarily limited to that tissue, as genes may have many functions throughout the body, and may therefore be expressed in many tissues and organs. In order to ensure my estimates of divergence reflect either gonad or brain related evolutionary paths, I determined the tissue that each gene was maximally expressed in.

Chicken expressed sequence tags (EST) were collected for chicken from the UniGene library (ftp://ncbi.nlm.nih.gov/repository/unigene/). The tissue of maximal expression for each gene was calculated by

where TPM

is the number of transcripts per million per tissue, library

is the total number of unique ESTs per library. A complete description of these methods can be found in Mank et al. (2007).

Estimates of d

, d

and d

/d

were calculated for genes maximally expressed in either brain or gonad. Permutations tests (1000 replicates) were once again carried out to compare the sex-biased categories to the unbiased estimates.

Gene ontology

Some classes of genes experience stronger selection pressures than others; therefore I

tested whether or not different functional classes of genes may have introduced biases in

our results. Gene function was determined from the Gene Ontology (GO) Consortium

(Gene Ontology Consortium 2000). ONTOLOGIZER 2.0 (Robinson et al. 2004) was

used to identify if any GO terms were overrepresented in each expression class of the

analysis, using term-for-term comparison and the westfall-young-step-down correction.

Polymorphism analysis

As a compliment to the divergence test above, a polymorphism analysis was also performed. This test, called the McDonald-Kreitman test (MK test), compares the numbers of synonymous and nonsynonymous substitutions which occur either as polymorphisms or are fixed within the species. The MK test can distinguish between relaxed constraint acting upon sex-biased genes resulting in neutral accumulation of substitutions or positive selection of adaptive substitutions in sex-biased genes (Zhang et al. 2004). If the ratio of nonsynonymous to synonymous polymorphisms is greater than that for fixed differences i.e. d

/d

> p

/p

, than you can conclude that positive selection has occurred (McDonald & Kreitman 1991, Eyre-Walker 2006, Axelsson & Ellegren 2009). This type of test is more effective than tests of divergence in disentangling purifying and positive selection (Shapiro et al. 2007). Instead of comparing

polymorphism estimates on a gene-by-gene basis, here, a variation of the MK test was carried out whereby pooled polymorphism estimates for each sex-bias category were used.

SNPs (single nucleotide polymorphisms) were obtained for chicken from ChickVD (http://chicken.genomics.org.cn/), which houses variation data for broiler, silkie and layer chickens sequenced to ~25% coverage (Wang et al. 2005). Using SNPs which map to the loci used in the divergence analysis, numbers of nonsynonymous and synonymous polymorphisms were calculated. This allows for direct comparison of divergence and polymorphism data.

Estimates of p

, p

and p

/p

were calculated by dividing the sum of the number of mutations divided by the sum of mutational sites per each expression class. As mentioned above, this provides a more realistic calculation of these values. Significance testing for the difference between sex-biased and unbiased classes was evaluated through

permutations tests with 1000 replicates.

Results

Due to the sheer volume of analyses, only a sub-set of the results are presented and discussed in the body of the paper. Unless otherwise stated all results pertain to fold change cutoff 200% or 125%. Full results for all fold change levels and time points can be found in the appendix of the paper. The absence of these results from the discussion, should in no way affect the interpretation of this paper.

Divergence analysis

There were significant differences between estimates of divergence for chicken gonad

sex biased genes throughout development (Figure 1). Adult chicken male biased genes

show the highest divergence (d

/d

=0.120, P<0.05). However, during embryonic

development, it is the female biased genes which are more highly diverged. At ED 19

there is a large, significant difference in female divergence rates compared with unbiased

genes (d

/d

= 0.146, P<0.05). This pattern was not apparent in sex biased brain genes.

A

Adult gonad fc>2

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

unbiased mb fb

dN/dS

*

B

Embryo day 19 Gonad fc>2

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

unbiased mb fb

dN/dS

*

C

Em bryo day 15 fc>2 and 2.5

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

Unbiased mb fb

dN/dS

Figure 1. Comparison of average divergence estimates for chicken sex biased gonad genes during development (A=Adult, B=ED 19, and C=ED 15). Mb = male bias, fb = female biased. Significant differences of sex biased genes from unbiased genes are marked by * (permutation test with 1000 replicates, P<0.05).

There was no significant difference between sex-biased categories across all time points

for brain expressed genes (See appendix for actual values). Generally, there were not

many brain genes which were sex-biased across all time points. This results in low

statistical power of the data. Thus, permutations tests were not conducted when there

were less than 50 sex-biased genes, as results are non-interpretable. For those classes

where there were enough sex-biased genes, there was no significant differences between

divergence values for the sex biased classes (P>0.05).

A pattern in the expression data for brain (Figure 2), although insignificant, did immerge, which is different from that of the gonad expressional divergence analysis. In embryonic chickens female-biased genes show the greatest divergence and this pattern persists into adulthood. Thus there appears to be no change in the expressional differences of brain genes through development in chicken.

A

Adult Brain fc>1.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

unbiased mb fb

B

Em bryo day 19 Brain fc>1.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

unbiased mb fb

dN/dS

C

Em bryo day 15 Brain fc>1.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

unbiased mb fb

dN/dS

D

Em bryo day 10 brain fc>1.25

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14

unbiased mb f b

dN/dS

Figure 2. Comparison of average divergence estimates for chicken sex-biased brain genes during development (A=Adult, B=ED 19, C=ED 15, and D=Ed 10). Mb = male bias, fb = female biased.

Significant differences of sex biased genes from unbiased genes are marked by * (permutation test with

1000 replicates, P<0.05).

Tissue of maximal expression

Mean divergence estimates of sex-biased gene classes were calculated for those genes which have primary expression in gonad only (Figure 3). The resulting dataset was a subset of the autosomal data used in the above analysis. Mean divergence estimates for tissue specific sex biased genes differ from the autosomal estimates of d

/d

. Adult estimates of d

/d

did not vary between the autosomal and tissue specific analyses; with female biased classes being more diverged. However, embryonic tissue specific mean d

/d

profiles did change from having highest female divergence to highest male divergence. However, there was a severe deficit of sex-biased genes in both ED19 and ED15, thus permutation tests were not carried out due to lack of statistical support.

A

Tissue specific adult gonad fc>2

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16 0.18

ub mb fb

dN/dS

B

Tissue specific ED19 gonad fc>2

0 0.02 0.04 0.06 0.08 0.1 0.12 0.14 0.16

ub mb fb

dN/dS

C

Tissue specific ED15 gonad fc2 and 2.5

0.095 0.1 0.105 0.11 0.115 0.12 0.125

ub mb f b

dN/dS

Figure 3. Mean divergence estimates for genes maximally expressed in the gonad (A=Adult, B=ED 19 and

C=ED 15). Sex-biased categories marked with * differ significantly from the unbiased mean divergence

value based on permutation tests with 1000 replicates (P<0.05).

Gene ontology

For genes expressed in the gonad, there were significant differences in overrepresented GO terms between sex-biased and unbiased gene classes. For all time points there were fewer overrepresented unbiased GO terms than sex-biased GO terms, and

overrepresented GO terms were highest amongst male-biased genes (Table 1). Most terms are not overrepresented across developmental time points except between ED19 and ED15, whereby males showed higher overlap (40%) compared to females (18.8%).

Table 1. Numbers of overrepresented GO terms for gonad genes at each developmental time point.

Numbers based on significance level P< 0.001. Bracketed numbers are after Bonferroni correction for multiple tests (P<0.05).

Time point Unbiased Female biased Male biased

Adult 2 (1) 28 (13) 31 (22)

ED 19 0 (0) 12 (8) 21 (16)

ED 15 2 (0) 4 (1) 14 (14)

During the embryonic stages overrepresented gonad terms belong mostly to classes of genes involved in basic metabolism and cellular processes (See appendix for tables of overrepresented terms). Interestingly, in adult males, the classes of overrepresented GO terms belong to processes affecting sperm production such as microtubule formation, motor activity and organelle production presumably of the mitochondria.

The results are fairly similar in the brain complement of genes. There are fewer

overrepresented unbiased GO terms, and male biased classes contain the most significant

GO terms (Table 2). In this analysis there was no overlap in GO terms between the

developmental time points for both male and female biased genes.

Table 2. Numbers of overrepresented GO terms for brain genes at each developmental time point. Numbers based on significance level P< 0.001. Bracketed numbers are after Bonferroni correction for multiple tests (P<0.05).

Time point Unbiased Female biased Male biased

Adult 0 (0) 5 (4) 0 (0)

ED 19 0 (0) 2 (0) 8 (4)

ED 15 0 (0) 2 (2) 3 (0)

ED 10 2 (2) 5 (3) 19 (9)

The types of overrepresented terms vary between biological, cellular and molecular processes. Furthermore, the types of GO terms differ between males and females. There is no clear process affecting brain development visible in the GO terms; however there may be some indication of bias towards cell development and signal transduction pathways (See appendix for complete list of GO terms).

Polymorphism analysis

One problem that became apparent during the polymorphism analysis was the lack of a comprehensive polymorphism data set for chicken. In the ChickVD database used here, there are only ~7400 genes, compared to ~12 000 for the divergence analysis, thereby reducing statistical power. Nevertheless, the analysis was carried out to see if I could detect a general pattern of selection on chicken sex-biased genes.

When it comes to the gonad genes, unbiased genes appeared to be evolving neutrally or

deleteriously, d

/d

<p

/p

(See appendix for actual values). The same is true for all

female biased gene categories. Interestingly for the male biased genes, genes which are

differentially expressed during embryonic development had d

/d

>p

/p

and may be

therefore evolving adaptively. In this analysis there were only few genes for which

polymorphism data were available resulting in low statistical power and interpretability

of these results.

As in the divergence test, there were very few genes which where sex biased in the brain.

In the majority of the tests there were <50 sex biased genes per fold change, too few for proper statistical analysis, sometimes there were no sex biased genes at all (See appendix for actual values). All unbiased brain gene categories had d

/d

<p

/p

indicating that mutations in unbiased genes are either neutral or deleterious. For both male and female biased genes d

/d

<p

/p

again indicating that sex biased brain genes are evidently not evolving adaptively. There are a few incidences where d

/d

>p

/p

but these are for cases where p

/p

=0

thus I can not conclude that adaptive selection occurred in these cases.

Discussion

There is evidence for selection of sex biased genes in the chicken genome. Higher mean d

/d

values for sex-biased genes than unbiased genes support this conclusion, and may hint at developmental difference between males and females in gonad expressed genes.

Evidence for selection of sex biased genes remains when only a subset of tissue specific genes are analysed, at least for gonad. The lack of a comprehensive polymorphism database for chicken made it difficult to determine what type of selection is acting on sex biased genes in both the gonad and brain. An analysis of overrepresented gene ontology terms reveals that there may be a bias towards sperm production in male biased genes.

Higher mean d

/d

values for sex biased genes in the chicken gonad are suggestive of a faster rate of evolution than unbiased genes. My results are consistent with those of Panhuis & Swanson (2006) who attributed a high rate of adaptive evolution to a

coevolutionary arms race of genes coding reproductive proteins in Drosophila resulting from sperm competition. In another Drosophila study genes with high d

/d

were located to the reproductive tract and may have important function in sexually selected

reproductive traits (Swanson et al. 2004). Thus high rates of functional change observed in this study may be indicative of sexual selection acting on genes involved in the reproductive tract in chicken.

Differences in divergence estimates of sex biased categories at different developmental

chicken gonad. During embryogenesis there appears to be higher mean d

/d

for female biased genes, and this difference was significant at ED 19 prior to hatching. Female birds develop their full complement of gametes prior to birth and that female meiosis is

arrested until reproductive maturity. The drop in mean divergence after reproductive adulthood in female biased genes could be indicative of this process. Specifically, genes which are involved in female meiosis and development of female gametes would undergo higher rates of functional change during development when gametes production occurs, which can ultimately be due to stronger sexual selection pressures on sex biased genes.

However, I cannot rule out the possibility of selection acting on female fecundity over sexually selected traits, therefore further studies are needed to determine what traits are under selection.

The same developmental process of gamete production in males can explain the male biased pattern of divergence estimates for chicken. In my analysis male biased genes have highest mean d

/d

in adulthood only. Adulthood coincides with the time whereby reproductively mature males produce sperm. Thus these results are consistent with those of Panhuis and Swanson (2007) and Swanson et al. (2004), and could imply that male biased genes expressed during adulthood experience higher rates of divergence due to sexual selection pressures from sperm competition and other related processes. However, these hypotheses would have to be verified to determine if indeed adaptive evolution of genes involved in gamete production occurs resulting in the mean divergence estimates seen in this study.

The McDonald-Krietman test used in this study failed to find any evidence of positive selection in both chicken gonad and brain expressed genes. As mentioned above there is no comprehensive database of chicken polymorphisms available at the time of this study.

Other studies have also struggled with the lack of power due to incomplete chicken polymorphism datasets thus being unable to detect positive selection (Axelsson &

Ellegren 2009). As a consequence estimates of p

/p

are not reliable and the mean values

calculated here are probably not accurate estimates and thus should be interpreted with

evolving via positive selection. This is contrary to the conclusions drawn from the divergence analysis, as I would have expected to see signatures of positive selection on male biased genes during adulthood and gamete production, not during embryonic development. However, this result is probably an artifact of the small number of samples used to calculate p

/p

and does not reflect the underlying biological process.

Overrepresented gene ontology terms for adult male biased genes support the hypothesis that sex biased genes may be important for sperm production. In my analysis several significantly overrepresented GO terms can be implicated in spermatogenesis. These include terms which are implicit in the formation of the microtubules as well as

microtubule movement and motor activity. The absence of such terms during embryonic development could be indicative of the importance of specific genes during

spermatogenesis. Therefore genes which affect the production of sperm microtubules and motor complex could experience higher adaptive rates of evolution during adulthood, resulting in higher d

/d

and bias GO terms.

The same sex specific argument for female biased gonad terms as well as all sex biased brain genes can not be made. There was no distinguishable GO terms involved in oogenesis during embryonic development in female chicken. However, this may be a reflection of my lack of knowledge as to what types of biological processes should be occurring during ova production.

Analysis of sex-biased genes expressed in the brain produced weak results. This was due mainly to the lack of sex-biased brain genes detectable in this study. Although

insignificant, there was a trend for female-biased genes to have higher d

/d

than male-

biased genes. Another study found that female-biased genes in chicken embryos at ED 18

evolved more rapidly over male-biased genes (Mank et al. 2007). The increased rate of

evolution in female-biased genes could not be explained by genomic properties such as

GC content, and was therefore attributed to differential selective pressures between the

sexes. Thus, there may be some indication of accelerated selection rates in female-biased

The same is true for sex biased brain genes; no discernable sex specific GO terms emerged in the analysis. I would argue that this is due to the essentiality of the brain.

Perhaps brain development is conserved between males and females so one would not expect to find developmental difference between the sexes. I would have however assumed that male brain chemistry would reflect differences associated with courtship and mating, differences which would be lacking in the female brain. The combination of an incomplete polymorphism dataset as well as the lower detectability of brain genes resulted in few available polymorphisms with which to calculate p

/p

, therefore I was unable to discern whether or not evolution in brain biased genes deviated from neutrality.

In summary this analysis did show some interesting differences in developmental

divergences of sex biased gonad genes possibly due to increased sexual selection on traits involved with gametogenesis. The polymorphism analysis unfortunately was

inconclusive as to whether higher divergence estimates were due to positive selection of genes implicit for gonadal development. Overrepresented GO terms for male biased genes expressed during adulthood are implicated with sperm production providing further support for increased sexual selection forces driving the evolution of sex biased genes. To ascertain whether or not sexual selection is accelerating the evolution of sex biased genes via positive selection requires the development of more extensive polymorphism

databases for chicken. Extensive SNP databases would be invaluable for this type of

study as well as other types of molecular studies in chicken.

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Appendix

Table A1. Mean divergence estimates for autosomal sex-biased genes expressed in the gonad in adult chicken.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

200% 0.106

(3138)

0.099 (1223)

0.121*

(813)

250% 0.106

(3626)

0.097*

(917)

0.125*

(631)

300% 0.105

(3957)

0.098 (692)

0.128*

(525) d

200% 0.024 0.022 0.027*

250% 0.022 0.022* 0.028*

300% 0.023 0.022* 0.029*

d

200% 0.224 0.225 0.223

250% 0.223 0.226 0.227

300% 0.224 0.224 0.227

Significant difference between sex-biased categories and unbiased categories based on permutation tests

Table A2. Mean divergence estimates for autosomal sex-biased genes expressed in the gonad in ED 19 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

200% 0.105

(4929)

0.146*

(136)

0.126 (69)

250% 0.106

(5014)

0.152*

(85)

0.118 (35)

300% 0.105

(5053)

0.155*

(59)

0.114 (22) d

200% 0.023 0.036* 0.026

250% 0.024 0.035* 0.026

300% 0.024 0.038* 0.024

d

200% 0.224 0.249 0.206

250% 0.224 0.232 0.220

300% 0.224 0.248 0.205

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A3. Mean divergence estimates for autosomal sex-biased genes expressed in the gonad at ED 15 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

200% 0.104

(3189)

0.116 (114)

0.105 (70)

250% 0.104

(3189)

0.116 (114)

0.105 (70)

300% 0.104

(3300)

0.122 (50)

0.095 (23) d

200% 0.024 0.035* 0.022

250% 0.024 0.035* 0.022

300% 0.024 0.035* 0.020

d

200% 0.233 0.304* 0.211

250% 0.233 0.304* 0.211

300% 0.234 0.289* 0.215

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A4. Mean divergence estimates for autosomal sex-biased genes expressed in the brain in adult chicken.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

125% 0.106

(5002)

0.116 (42)

0.106 (113)

133% 0.106

(5100)

0.127 (19)

0.125 (38)

150% 0.106

(5147)

0.188 (6)

0.167 (4) d

125% 0.024 0.024 0.020*

133% 0.024 0.024 0.024

150% 0.024 0.028 0.030

d

125% 0.224 0.206 0.189*

133% 0.224 0.192 0.194

150% 0.224 0.146 0.180

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A5. Mean divergence estimates for autosomal sex-biased genes expressed in the brain in ED 19 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

125% 0.106

(5112)

0.119 (18)

0.074 (17)

133% 0.106

(5135)

0.181 (6)

0.054 (6)

150% 0.106

(5143)

0.086 (1)

0.019 (3) d

125% 0.024 0.021 0.014

133% 0.024 0.030 0.009

150% 0.024 0.008 0.004

d

125% 0.224 0.179 0.190

133% 0.224 0.166 0.175

150% 0.224 0.096 0.230

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A6. Mean divergence estimates for autosomal sex-biased genes expressed in the brain in ED 15 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

125% 0.106

(5117)

0.120 (19)

0.062 (8)

133% 0.106

(5139)

0.112 (5)

0.000 (0)

150% 0.106

(5144)

0.000 (0)

0.000 (0) d

125% 0.024 0.025 0.012

133% 0.024 0.023 0.000

150% 0.024 0.000 0.000

d

125% 0.224 0.210 0.192

133% 0.224 0.206 0.000

150% 0.224 0.000 0.000

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A7. Mean divergence estimates for autosomal sex-biased genes expressed in the brain in ED 10 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

d

/d

125% 0.106

(5063)

0.131 (50)

0.110 (53)

133% 0.106

(5114)

0.137 (27)

0.101 (25)

150% 0.106

(5155)

0.177 (5)

0.046 (6) d

125% 0.024 0.027 0.027

133% 0.024 0.028 0.028

150% 0.024 0.041 0.009

d

125% 0.224 0.209 0.205

133% 0.224 0.207 0.183

150% 0.224 0.231 0.193

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A8. Mean polymorphism estimates for autosomal sex-biased genes expressed in the gonad in adult chicken.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.160

(3667)

0.160 (994)

0.161 (1051)

250% 0.159

(4121)

0.170 (741)

0.158 (850)

300% 0.159

(4455)

0.177 (544)

0.158 (713) p

200% 0.0005 0.0005 0.0005

250% 0.0005 0.0005 0.0005

300% 0.0005 0.0005 0.0005

p

200% 0.003 0.003 0.003

250% 0.003 0.003 0.003

300% 0.003 0.003 0.003

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A9. Mean polymorphism estimates for autosomal sex-biased genes expressed in the gonad in ED 19 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.160

(5476)

0.173 (122)

0.126 (75)

250% 0.160

(5560)

0.204 (77)

0.087*

(36)

300% 0.160

(5592)

0.204 (57)

0.075*

(24) p

200% 0.0005 0.0007* 0.0005

250% 0.0005 0.0008* 0.0004

300% 0.0005 0.0008* 0.0004

p

200% 0.003 0.004* 0.004

250% 0.003 0.004 0.004

300% 0.003 0.004 0.005*

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A10. Mean polymorphism estimates for autosomal sex-biased genes expressed in the gonad in ED 15 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.169

(2946)

0.120 (89)

0.103*

(68)

250% 0.169

(2946)

0.120 (89)

0.103*

(68)

300% 0.167

(3046)

0.147 (34)

0.083 (23) p

200% 0.0006 0.0004* 0.0004

250% 0.0006 0.0004* 0.0004

300% 0.0006 0.0004 0.0004

p

200% 0.004 0.003 0.004

250% 0.004 0.003 0.004

300% 0.004 0.003 0.005

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A11. Mean polymorphism estimates for autosomal sex-biased genes expressed in the brain in adult chicken.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.160

(5541)

0.132 (50)

0.168 (95)

250% 0.160

(5632)

0.100 (18)

0.150 (36)

300% 0.160

(5676)

0.200 (6)

0.000 (4) p

200% 0.0005 0.0005 0.0006

250% 0.0005 0.0003 0.0005

300% 0.0005 0.0004 0.000

p

200% 0.003 0.004 0.003

250% 0.003 0.003 0.003

300% 0.003 0.002 0.003

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A12. Mean polymorphism estimates for autosomal sex-biased genes expressed in the brain in ED 19 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.160

(5571)

0.349 (18)

0.128 (64)

250% 0.160

(5632)

0.000 (2)

0.094 (19)

300% 0.160

(5650)

0.000 (0)

0.081 (3) p

200% 0.0005 0.0008 0.0003

250% 0.0005 0.000 0.0002

300% 0.0005 0.000 0.0001

p

200% 0.003 0.002 0.002

250% 0.003 0.001 0.002

300% 0.003 0.000 0.002

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A13. Mean polymorphism estimates for autosomal sex-biased genes expressed in the brain in ED 15 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.161

(5633)

0.148 (18)

0.044 (13)

250% 0.160

(5659)

0.542 (2)

0.000 (3)

300% 0.160

(5663)

0.000 (0)

0.000 (1) p

200% 0.0005 0.0005 0.0002

250% 0.0005 0.001 0.000

300% 0.0005 0.000 0.000

p

200% 0.003 0.003 0.005

250% 0.003 0.002 0.003

300% 0.003 0.000 0.002

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A14. Mean polymorphism estimates for autosomal sex-biased genes expressed in the brain in ED 10 chicken embryos.

fold-change cut-off unbiased (n)

female-biased (n)

male-biased (n)

p

/p

200% 0.160

(5475)

0.190 (89)

0.127 (122)

250% 0.160

(5613)

0.247 (29)

0.113 (42)

300% 0.160

(5673)

0.219 (3)

0.132 (8) p

200% 0.0005 0.0008* 0.0004

250% 0.0005 0.001 0.0004

300% 0.0005 0.0009 0.0007

p

200% 0.003 0.004 0.003

250% 0.003 0.005 0.004

300% 0.003 0.004 0.006

Significant difference between sex-biased categories and unbiased categories based on permutation tests

with 1000 replicates are marked by * (P<0.05). n= number of genes in each category.

Table A15. Overrepresented GO terms for genes expressed in the gonad. Only terms with P<0.001 are included. P(adj) refers to Bonferroni correction for multiple testing.

Time point

Sex-bias GO Name Process* P (P

)

ED 15 Female

0003918

DNA topoisomerase (ATP-hydrolyzing) activity

M 0.000

(0.036) 0003916 DNA topoisomerase activity

M 0.000

(0.05) 0006265 DNA topological change

B 0.000

(0.114) 0040007 growth

B 0.000

(0.178) Male

0009211

pyrimidine deoxyribonucleoside triphosphate metabolic process

B 0.000

(0.000) 0009200

deoxyribonucleoside triphosphate metabolic process

B 0.000

(0.002) 0009120 deoxyribonucleoside metabolic process

B 0.000

(0.002) 0006213 pyrimidine nucleoside metabolic process

B 0.000

(0.002) 0009219

pyrimidine deoxyribonucleotide metabolic process

B 0.000

(0.002) 0046125

pyrimidine deoxyribonucleoside metabolic process

B 0.000

(0.002) 0046080 dUTP metabolic process

B 0.000

(0.002) 0009262 deoxyribonucleotide metabolic process

B 0.000

(0.002) 0009147

pyrimidine nucleoside triphosphate metabolic process

B 0.000

(0.002) 0006220 pyrimidine nucleotide metabolic process

B 0.000

(0.002) 0009141 nucleoside triphosphate metabolic process

B 0.000

(0.01) 0009116 nucleoside metabolic process

B 0.000

(0.01) 0004190 aspartic-type endopeptidase activity

M 0.000

(0.01) 0070001 aspartic-type peptidase activity

M 0.000

(0.01) Unbiased

0006650 glycerophospholipid metabolic process

B 0.000

(0.094) 0030384 phosphoinositide metabolic process

B 0.000

(0.094) ED 19 Female

0004089 carbonate dehydratase activity

M 0.000

(0.00) 0000228 nuclear chromosome

C 0.000

(0.004) 0005833 hemoglobin complex

C 0.000

(0.004) 0005576 extracellular region

C 0.000

(0.01)

0015669 gas transport

B 0.000

(0.016) 0019825 oxygen binding

M 0.000

(0.026) 0016836 hydro-lyase activity

M 0.000

(0.046) 0003918

DNA topoisomerase (ATP-hydrolyzing) activity

M 0.000

(0.078) 0003916 DNA topoisomerase activity

M 0.000

(0.094) 0006265 DNA topological change

B 0.000

(0.12) 0016835 carbon-oxygen lyase activity

M 0.000

(0.12) Male

0009262 deoxyribonucleotide metabolic process

B 0.000

(0.00) 0046080 dUTP metabolic process

B 0.000

(0.002) 0009211

pyrimidine deoxyribonucleoside triphosphate metabolic process

B 0.000

(0.002) 0009200

deoxyribonucleoside triphosphate metabolic process

B 0.000

(0.002) 0009120 deoxyribonucleoside metabolic process

B 0.000

(0.002) 0009219

pyrimidine deoxyribonucleotide metabolic process

B 0.000

(0.002) 0046125

pyrimidine deoxyribonucleoside metabolic process

B 0.000

(0.002) 0006213 pyrimidine nucleoside metabolic process

B 0.000

(0.002) 0009147

pyrimidine nucleoside triphosphate metabolic process

B 0.000

(0.01) 0005694 chromosome

C 0.000

(0.01) 0019967 interleukin-1, Type I, activating binding

M 0.000

(0.01) 0004909

interleukin-1, Type I, activating receptor activity

M 0.000

(0.01) 0004910

interleukin-1, Type II, blocking receptor activity

M 0.000

(0.01) 0019968 interleukin-1, Type II, blocking binding

M 0.000

(0.01) 0006220 pyrimidine nucleotide metabolic process

B 0.000

(0.01) 0009116 nucleoside metabolic process

B 0.000

(0.054) 0004190 aspartic-type endopeptidase activity

M 0.000

(0.054) 0070001 aspartic-type peptidase activity

M 0.000

(0.054) 0006435 threonyl-tRNA aminoacylation

B 0.000

(0.25)

M 0.000

Adult Female

0005201 extracellular matrix structural constituent

M 0.000

(0.00) 0006817 phosphate transport

B 0.000

0.002) 0050819 negative regulation of coagulation

B 0.000

(0.008) 0050818 regulation of coagulation

B 0.000

(0.008) 0051241

negative regulation of multicellular organismal process

B 0.000

(0.008) 0051239

regulation of multicellular organismal process

B 0.000

(0.008) 0005578 proteinaceous extracellular matrix

C 0.000

(0.012) 0055102 lipase inhibitor activity

M 0.000

(0.016) 0004859 phospholipase inhibitor activity

M 0.000

(0.016) 0031012 extracellular matrix

C 0.000

(0.022) 0016491 oxidoreductase activity

M 0.000

(0.022) 0005506 iron ion binding

M 0.000

(0.03) 0030118 clathrin coat

C 0.000

(0.038) 0005544 calcium-dependent phospholipid binding

M 0.000

(0.052) 0005581 collagen

C 0.000

(0.052) 0044421 extracellular region part

C 0.000

(0.058) 0005622 intracellular

C 0.000

(0.108) 0044420 extracellular matrix part

C 0.000

(0.128) 0042612 MHC class I protein complex

C 0.000

(0.14) 0030131 clathrin adaptor complex

C 0.000

(0.164) 0030119 AP-type membrane coat adaptor complex

C 0.000

(0.164) 0006826 iron ion transport

B 0.000

(0.19) 0030117 membrane coat

C 0.000

(0.23) 0048475 coated membrane

C 0.000

(0.23) 0008083 growth factor activity

M 0.000

(0.238)

0016616

oxidoreductase activity acting on the CH- OH group of donors, NAD or NADP as acceptor

M

0.000

(0.246)

(0.248) Male

0006996 organelle organization and biogenesis

B 0.000

(0.00) 0016043

cellular component organization and biogenesis

B 0.000

(0.002) 0007017 microtubule-based process

B 0.000

(0.002) 0007010 cytoskeleton organization and biogenesis

B 0.000

(0.002) 0015630 microtubule cytoskeleton

C 0.000

(0.002) 0043228 non-membrane-bounded organelle

C 0.000

(0.002) 0043232

intracellular non-membrane-bounded organelle

C 0.000

(0.002) 0030705

cytoskeleton-dependent intracellular transport

B 0.000

(0.002) 0007018 microtubule-based movement

B 0.000

(0.002) 0003777 microtubule motor activity

M 0.000

(0.002) 0044430 cytoskeletal part

C 0.000

(0.002) 0005875 microtubule associated complex

C 0.000

(0.002) 0005856 cytoskeleton

C 0.000

(0.002) 0005694 chromosome

C 0.000

(0.002) 0003774 motor activity

M 0.000

(0.004) 0044422 organelle part

C 0.000

(0.004) 0044446 intracellular organelle part

C 0.000

(0.004) 0051276 chromosome organization and biogenesis

B 0.000

(0.006 0006869 lipid transport

B 0.000

(0.006) 0005319 lipid transporter activity

M 0.000

(0.01) 0030286 dynein complex

C 0.000

(0.014) 0005874 microtubule

C 0.000

(0.02) 0005200 structural constituent of cytoskeleton

M 0.000

(0.08) 0016817

hydrolase activity, acting on acid anhydrides

M 0.000

(0.098)

0016818

hydrolase activity acting on acid anhydrides, in phosphorus-containing anhydrides

M

0.000 (0.098)

M 0.000

0006333 chromatin assembly or disassembly

B 0.000

(0.152) 0032555 purine ribonucleotide binding

M 0.000

(0.152) 0032553 ribonucleotide binding

M 0.000

(0.152) 0017076 purine nucleotide binding

M 0.000

(0.152) Unbiased

0046983 protein dimerization activity

M 0.000

(0.012) 0034645

cellular macromolecule biosynthetic process

B 0.000

(0.092)

* B= Biological process, C= Cellular component, and M= Molecular function