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Daniela H. : d. Use the link below to share a full-text version of this article with your friends and colleagues. Learn more. Although sex is a fundamental component of eukaryotic reproduction, the genetic systems that control sex determination are highly variable. In many organisms the presence of sex chromosomes is associated with female or male development. Although certain groups possess stable and conserved sex chromosomes, others exhibit rapid sex chromosome evolution, including transitions between male and female heterogamety, and turnover in the chromosome pair recruited to determine sex.

These turnover events have important consequences for multiple facets of evolution, as sex chromosomes are predicted to play a central role in adaptation, sexual dimorphism, and speciation. However, our understanding of the processes driving the formation and turnover of sex chromosome systems is limited, in part because we lack a complete understanding of interspecific variation in the mechanisms by which sex is determined.

New bioinformatic methods are making it possible to identify and characterize sex chromosomes in a diverse array of non-model species, rapidly filling in the numerous gaps in our knowledge of sex chromosome systems across the tree of life.

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In turn, this growing data set is facilitating and fueling efforts to address many of the unanswered questions in sex chromosome evolution. Here, we synthesize the available bioinformatic approaches to produce a guide for characterizing sex chromosome system and identity simultaneously across clades of organisms.

Furthermore, we survey our current understanding of the processes driving sex chromosome turnover, and highlight important avenues for future research. Sexual reproduction is a fundamental feature of eukaryotes, yet the mechanisms by which sex is determined are highly diverse Bachtrog et al. This variation is apparent even among closely related species, or populations of the same species Tree of Sex Consortium, In many organisms, sex chromosomes are associated with male or female development, and in many groups, including birds Zhou et al.

In addition to turnover in the chromosome pair recruited to determine sex, transitions between different sex chromosome systems e. This diversity is particularly pronounced in certain groups of reptiles Gamble et al. While recent efforts, including those of the Tree of Sex Consortium, have focused on characterizing the tremendous diversity of sex chromosomes across species, it is clear that we currently have an incomplete understanding of the variation in sex determination mechanisms across the tree of life Bachtrog et al.

Despite the growing awareness that sex chromosomes have evolved independently many times throughout eukaryotes, our understanding of the processes driving the formation and turnover of new sex chromosome systems is limited and many unanswered questions remain. Identifying the evolutionary and genomic mechanisms predicted to drive sex chromosome turnover is a major priority, which in turn will shed light on why sex determination is labile in some taxa and not in others. Efforts to rigorously test predictions about the causes and consequences of sex chromosome evolution have been largely hampered by our incomplete knowledge of the diversity of sex chromosomes across a broad taxonomic range and limited power to identify convergent trends across independently evolved sex chromosomes.

However, while there have been recent improvements that facilitate sex chromosome identification using these approaches Ezaz et al. This might disproportionately affect the identification of ZW systems as W chromosomes are predicted to evolve more slowly than Y chromosomes Bachtrog et al. Recently, new bioinformatic methods are making it possible to identify and characterize sex chromosomes in a diverse array of non-model species using next generation sequencing data. In combination with comparative phylogenetic analyses, it is now possible to rigorously test theoretical predictions for sex chromosome formation and turnover.

This is key because the effectiveness of different approaches is influenced by a of factors. In particular, the degree of sequence divergence between the sex chromosomes is an important element to consider. In contrast, homogametic sex chromosomes are almost identical and exhibit few differences from each other in gene content.

It is important to note that homogamety and heterogamety are not discrete states and instead represent two extremes on a continuum of sex chromosome divergence Figure 1. Certain bioinformatic approaches to identify sex chromosomes are more effective for species at different points on this continuum. In addition, while sex chromosomes across species exhibit variation in the degree of heterogamety, different regions of the same sex chromosome can also fall at different points along this continuum Figure 1.

This is because recombination is often suppressed in a stepwise process, resulting in strata of different ages Charlesworth et al. Therefore, a combination of different, complementary methods is often necessary to identify sex chromosomes, and sex-linked regions, among species. Here, we review the range of available approaches to identify sex chromosomes and fill in gaps across the tree of life, highlighting the strengths and weaknesses of each. In turn, we discuss future priorities in sex chromosome research and suggest how to use this growing data set to test, highlighting the strengths and weaknesses of each, how and why sex chromosomes evolve.

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A common approach to identify sex chromosomes is based on genome coverage from next-generation sequencing data. This approach exploits the difference in sex chromosome ploidy between males and females.

Girls looking for sex Cortez pa

In XY systems, X-linked genes show half the of genomic re in males relative to females, and Y-linked re are absent in females Figure 2 a. This can be easily applied to ZW systems, where instead the W is absent in males, and females have only one copy of the Z. Since this approach is based on sex differences in genomic coverage, it is only effective when there is substantial sequence divergence between the sex chromosomes.

Therefore, while it can be used to identify heteromorphic sex chromosomes or old, diverged strata, this method will misclassify pseudoautosomal regions, homomorphic sex chromosomes, or young strata as autosomal. There are three main methods that employ genome coverage to distinguish sex chromosomes from autosomes. In the subtraction-based method, DNA-seq data from the homogametic sex are aligned to a reference genome generated from a heterogametic individual.

As male and female genomes differ only by the Y or W chromosome, scaffolds with low coverage can be inferred as Y-linked or W-linked. Whilst this approach can effectively identify sex-limited scaffolds, and therefore establish whether the sex chromosome system is male or female heterogametic, it has limited potential for identifying the X or Z.

This step is key for establishing the identity of the sex chromosome pair via synteny-based approaches with other species see Box 1as sex-limited chromosomes are often highly degenerated which hinders attempts to infer orthology. Alternatively, the ratio of male to female re aligned to a reference genome can be used to directly distinguish X from autosomal scaffolds Darolti et al.

For example, in an XY system, the male to female coverage ratio for autosomal and X scaffolds should be roughly 1 and 0. A variant of this method is called the chromosome quotient CQ approach Hall et al. Due to noise in mapping re to a genome, the male to female coverage ratio is typically a continuum, where there are two overlapping normal distributions of sex differences in coverage, one for the X or Z chromosome and the other for autosomal scaffolds Figure 2 a.

Male and female genomes are broken up into k -mers, counted computationally, and autosomal, Y- and X-linked k -mers are identified on the basis of read coverage. This method is unaffected by differences in filtering and read length and can be useful for identifying sex chromosomes across species where next-generation sequencing data sets are of varying quality Morris et al.

Finally, in combination with next-generation sequencing data obtained from flow-sorted Y chromosomes, k-mer approaches can filter contaminant autosomal and X-linked sequences, thus improving the quality of the downstream Y chromosome assembly Rangavittal et al. However, there are a of important caveats to consider. Coverage approaches are heavily sensitive to the algorithms used to map re to a reference genome.

This is because heteromorphic sex chromosomes still retain sequence orthology between the X and Y, and incorrectly mapped re can mask coverage differences between the sexes and lead to the misclassification of sex-linked sequences as autosomal. A similar caveat applies to the k -mer approach, where k -mer size can dramatically affect the of inferred sex-linked scaffolds. In principle, a large k ensures that identical k -mers rarely result from sequencing errors and increases the probability that sequences encompass sex-limited sites. However, if k is too large then k-mer depth may be too low to detect statistical sex differences.

In practice, multiple individuals of each sex are required to avoid falsely identifying rare SNP variants as sex-linked contigs, the probability of which will depend on the genetic diversity of the population see Box 1. This approach leverages sex differences in gene expression to identify sex-limited transcripts originating from the Y or W chromosome.

RNA-seq re from the heterogametic sex are mapped to a reference generated from the homogametic sex. Successfully mapped re originate from regions of the genome that are shared between the sexes whereas unmapped re represent sex-limited regions Cortez et al. These unmapped re can be assembled de novo into potential Y- or W-linked contigs.

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Mapping RNA-seq re from the homogametic sex onto these putative contigs can be used to validate sex-limitation Cortez et al. This approach is similar to subtraction-based methods employed using DNA-seq data and is best optimized for systems with sufficiently diverged sex chromosomes or strata where there is sex-specificity among RNA-seq re. Furthermore, this approach may underperform in systems where the sex chromosomes are starting to decay, as the loss of gene expression from genes on the Y or W chromosome has been shown to precede sequence degeneration Bachtrog, Autosomal genes with sex-limited expression may also lead to erroneous.

Therefore, while sufficient data can be obtained from as little as one male and one female, prior knowledge of when sex-limited genes are expressed, and in which tissue, is essential to ensure detection of their associated transcripts. Typically, in heteromorphic systems, W and Y-linked genes tend to be expressed primarily in reproductive tissue Moghadam et al. Several approaches exist to identify sex-linked regions using sex-specific genetic association. While whole-genome sequencing offers the most complete resolution for these analyses, reduced representation methods may also be employed if genotyping is sufficiently dense.

Restriction site-associated DNA sequencing RAD-seq is a powerful tool to identify sex-limited loci and has been used to infer sex chromosome systems across a of species Gamble et al. RAD-seq markers are compared between males and females, and markers present in one sex and absent in the other are kept as candidate loci Y-specific or W-specific; Figure 2 c. For example, a Y-linked allele should have a frequency of 0. The inference of ploidy from RAD-seq data can also be a fruitful avenue to identify sex-linked regions. DetSex is a Bayesian method that infers segregation type based on ploidy information in males and females, which is derived from genotyping data Gautier, The X chromosome is diploid in females yet haploid in males, whereas autosomes are diploid in both sexes.

However, this approach assumes sex chromosomes are old and that Y re do not map onto the X reference, and is therefore optimized for heteromorphic sex chromosomes. Furthermore, this approach requires the sequencing of many individuals 20—50 individuals. The primary advantages of the RAD-seq approach are that it relies on genomic DNA, is relatively cheap, and is highly effective for wild-caught samples, provided they are accurately sexed.

It can be used in combination with certain bioinformatic approaches to identify both homomorphic and heteromorphic sex chromosome systems, and the choice of restriction enzyme can be tailored to cut more or less frequently if the size of the nonrecombining region is known. The main challenge faced when using reduced representation methods is the problem of missing data Lowry et al.

Sex-specific sequences are often detected in both sexes and are likely to represent false positives. A solution might be to increase sample size; however, the of shared loci decreases with sample s in RAD-seq data Mastretta-Yanes et al. Implementing and developing approaches to quantify the false positive rate of identifying sex-linked sequences is a future priority when using this approach see Box 1.

While sex differences in genomic coverage or expression are indicative of diverged sex chromosomes with ificant Y or W degeneration, differences in SNP density between males and females are expected in sex chromosomes at the earlier stages of divergence. In particular, elevated SNP density in the heterogametic sex can be used to infer sex-linked regions when mapped to a reference genome generated from the homogametic sex. For example, in nascent sex chromosomes with limited Y chromosome degeneration, Y-linked genomic re will map to the homologous region of the X in a female reference genome, resulting in elevated SNP density in males relative to females Figure 2 d.

Therefore, elevated SNP density in the heterogametic sex can be used to infer sex-linked regions when mapped to a reference genome generated from the homogametic sex Darolti et al. Therefore, an absence of SNPs in females can indicate X-linked sequences. Finally, scaffolds with limited sex differences in polymorphism are probably autosomal or pseudoautosomal. Together, this rationale can be used not only to identify sex chromosomes at the intermediate stages of divergence, but also strata of different ages along the chromosome Darolti et al.

Contrasting SNP density between males and females is therefore a powerful approach to identify sex chromosomes or strata at the intermediate stages of X and Y or Z and W divergence. The primary drawback of the SNP-based approach is the difficulty in defining a threshold above which SNP density between males and females can be used to infer sex-linkage.

This is because the magnitude of sex differences in SNP density is directly proportional to the degree of divergence between the sex chromosomes. Therefore, implementing these approaches in young sex chromosome systems should ideally be accompanied by information as to the location of the sex determining region. Often this information is not available and therefore a permutation approach to estimate the null distribution of sex differences in SNP density across the genome is essential to identify regions with ificantly elevated SNP density in the heterogametic sex see Box 1.

This method is most successful when combined with the coverage approach Figure 2 d so that multiple, independent lines of evidence can be used to identify sex-linked regions Darolti et al. For example, SNPs in X-linked genes will only be transmitted from the father to daughters but not sons, whereas SNPs in Y-linked genes are only transmitted to sons. Recently, a probabilistic framework SEX-DETector has been developed to infer autosomal and sex-linked genes using patterns of allelic segregation Muyle et al.

Each SNP is ased a likelihood of these three states and the method can also estimate the type of sex chromosome system through a model comparison strategy. An important step is the generation of a de novo reference assembly where X and Y sequences co-assemble into one contig instead of separate X- and Y-linked sequences. Therefore, the approach is best optimized to systems with low or intermediate level of sex chromosome divergence where X and Y sequences are most likely to coassemble in the reference assembly.

This method has been used to identify sex-linked regions in several plant species Martin et al. This approach requires family data and is therefore limited to species for which pedigree information is available. Second, SEX-Detector has primarily been used to analyse RNA-seq derived genotyping data although it can also be used with genomic-based data instead, providing the data set is not too big Muyle et al.

Whilst RNA-seq data clearly has advantages, only genes that are expressed can be identified as sex-linked. However, using multiple tissues or tissues where many genes are expressed can circumvent this problem.

Finally, the pipeline requires polymorphism data to infer certain types of sex-linkage and therefore is not optimized for inbred populations. Ideally, parents should be sampled from different populations in order to maximize the genetic diversity of the progeny and increase statistical power but see Box 1. However, this only applies to X-hemizygous genes, whose identification relies on the presence of polymorphisms on the X copy.

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