Research Paper

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Postcopulatory inbreeding avoidance in guppies

Corresponding Author

J. L. Fitzpatrick

Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK

Centre for Evolutionary Biology, School of Animal Biology, University of Western Australia, Crawley, WA, Australia

Correspondence: John L. Fitzpatrick, Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.

Tel.: +44 0161 275 5021; fax: +44 0161 275 1491; e-mail: [email protected]

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J. P. Evans,

J. P. Evans

Centre for Evolutionary Biology, School of Animal Biology, University of Western Australia, Crawley, WA, Australia

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J. L. Fitzpatrick,

Corresponding Author

J. L. Fitzpatrick

Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester, UK

Centre for Evolutionary Biology, School of Animal Biology, University of Western Australia, Crawley, WA, Australia

Correspondence: John L. Fitzpatrick, Computational and Evolutionary Biology, Faculty of Life Sciences, University of Manchester, Manchester M13 9PT, UK.

Tel.: +44 0161 275 5021; fax: +44 0161 275 1491; e-mail: [email protected]

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J. P. Evans,

J. P. Evans

Centre for Evolutionary Biology, School of Animal Biology, University of Western Australia, Crawley, WA, Australia

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First published: 11 November 2014

https://doi.org/10.1111/jeb.12545

Citations: 39

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Abstract

In many species, the negative fitness effects of inbreeding have facilitated the evolution of a wide range of inbreeding avoidance mechanisms. Although avoidance mechanisms operating prior to mating are well documented, evidence for postcopulatory mechanisms of inbreeding avoidance remain scarce. Here, we examine the potential for paternity biases to favour unrelated males when their sperm compete for fertilizations though postcopulatory inbreeding avoidance mechanisms in the guppy, Poecilia reticulata. To test this possibility, we used a series of artificial inseminations to deliver an equal number of sperm from a related (either full sibling or half sibling) and unrelated male to a female while statistically controlling for differences in sperm quality between rival ejaculates. In this way, we were able to focus exclusively on postcopulatory mechanisms of inbreeding avoidance and account for differences in sperm competitiveness between rival males. Under these carefully controlled conditions, we report a significant bias in paternity towards unrelated males, although this effect was only apparent when the related male was a full sibling. We also show that sperm competition generally favours males with highly viable sperm and thus that some variance in sperm competitiveness can be attributed to difference in sperm quality. Our findings for postcopulatory inbreeding avoidance are consistent with prior work on guppies, revealing that sperm competition success declines linearly with the level of relatedness, but also that such effects are only apparent at relatedness levels of full siblings or higher. These findings reveal that postcopulatory processes alone can facilitate inbreeding avoidance.

Introduction

Reproduction among close relatives can dramatically reduce offspring viability and fitness, a phenomenon known as inbreeding depression (Charlesworth & Charlesworth, 1999; Keller & Waller, 2002). To reduce the costs associated with inbreeding, many species exhibit a wide range of inbreeding avoidance mechanisms. For example, precopulatory mechanisms of inbreeding avoidance, such as dispersing away from natal territories and/or recognizing kin, can represent effective methods for reducing the likelihood of inbreeding (Pusey & Wolf, 1996). However, postcopulatory inbreeding avoidance mechanisms can also evolve, particularly when the risks and costs of inbreeding are high, when precopulatory inbreeding avoidance mechanisms are absent (e.g. Pitcher et al., 2008; Tan et al., 2012), or when precopulatory processes can be undermined through forced matings (Kokko & Ots, 2006). Thus, polyandrous females may avoid inbreeding depression by engaging in postcopulatory cryptic female choice to bias fertilizations towards unrelated males (Stockley et al., 1993; Zeh & Zeh, 1996, 1997).

Postcopulatory inbreeding avoidance mechanisms may bias paternity in favour of genetically dissimilar males during competitive fertilizations. Accordingly, when inseminated with sperm from both related and unrelated males, cryptic female choice is thought to bias fertilization success towards unrelated males (Bishop, 1996; Bishop et al., 1996; Olsson et al., 1996; Wilson et al., 1997; Stockley, 1999; Kraaijeveld-Smit et al., 2002; Mack et al., 2002; Thuman & Griffith, 2005; Jehle et al., 2007; Firman & Simmons, 2008; Brekke et al., 2012; but for counter examples, see Kleven et al., 2005; Sherman et al., 2008; Evans et al., 2008; Ala-Honkola et al., 2010, 2011). Mechanistically, females can bias paternity by influencing the number of sperm accepted during mating (or stored following insemination) in favour of unrelated males (Bretman et al., 2004; Pizzari et al., 2004; Welke & Schneider, 2009; Ala-Honkola et al., 2010; Tuni et al., 2013), or though interactive effects, for example between ovarian fluid and sperm performance, that differentially influence sperm quality in favour of unrelated sperm (Gasparini & Pilastro, 2011; Butts et al., 2012). Despite promising support for the idea that cryptic female choice moderates inbreeding avoidance, very few studies have been able to exclude the influence of precopulatory inbreeding avoidance mechanisms (Pusey & Wolf, 1996), or alternative postcopulatory processes, such as differential sperm allocation or investment by males based on genetic relatedness (Pizzari et al., 2004; Fitzpatrick et al., 2014). Moreover, most studies of postcopulatory inbreeding avoidance do not account for differences in sperm quality (i.e. sperm traits such as swimming speed, viability and morphology that predict fertilization success, Simmons & Fitzpatrick, 2012) between competing males. Indeed, only a single study (Denk et al., 2005), which failed to detect an effect of genetic relatedness on competitive fertilization success, controlled for differences in sperm quality between competing males when assessing postcopulatory inbreeding avoidance mechanisms. Consequently, examining the potential for postcopulatory inbreeding avoidance requires both the influence of cryptic female choice and sperm competition to be assessed simultaneously within an experimental framework that separates pre- from postcopulatory inbreeding avoidance mechanisms.

The guppy, Poecilia reticulata, is ideally suited to studies of postcopulatory inbreeding avoidance. Guppies are internally fertilizing, live-bearing freshwater fish characterized by high levels of polyandry (Neff et al., 2008; Evans & Pilastro, 2011). In their native tropical freshwater streams, guppies are likely to suffer periodic or sustained periods of elevated inbreeding risk, as small populations can often become isolated as water levels recede during the dry season (Griffiths & Magurran, 1997). Indeed, molecular data indicate that as many as 16% of randomly chosen pairs of guppies in a Trinidadian stream reached levels of relatedness higher than those of half siblings (Hain & Neff, 2007). Moreover, inbreeding depression can be severe in guppies, and studies have shown that inbred offspring have reduced survival (Nakadate et al., 2003), vertebral deformities (Shikano et al., 2005), reduced reproductive rates (Zajitschek & Brooks, 2008), and for males, reduced courtship, sexual colouration, sperm counts and semen quality (van Oosterhout et al., 2003; Mariette et al., 2006; Zajitschek et al., 2009). However, despite the high potential for inbreeding in wild populations, and associated costs, adult female guppies do not appear to practice precopulatory inbreeding avoidance through active mate choice (Viken et al., 2006; Pitcher et al., 2008; Zajitschek & Brooks, 2008). Instead, polyandry, coupled with forced copulations by males (Magurran & Seghers, 1994; Pilastro & Bisazza, 1999), suggests that females may have to rely on postcopulatory inbreeding avoidance mechanisms (Gasparini & Pilastro, 2011).

Here, we examine whether genetic relatedness influences a males' competitive fertilization success using an established artificial insemination protocol (Evans et al., 2003) to assess the potential for postcopulatory processes to influence relative paternity of related and unrelated males. Artificial insemination effectively uncouples pre- from postcopulatory inbreeding avoidance mechanisms and allows for rigorous control over sperm numbers between competing males, mating order effects and differential sperm retention by females, all of which have the potential to influence competitive fertilization success in guppies (Evans & Magurran, 2001; Pilastro et al., 2004). In addition, our protocol accounts for differences in components of sperm quality (e.g. velocity and viability) between rival males when assessing postcopulatory inbreeding avoidance mechanisms.

Materials and methods

Experimental animals and breeding protocols

Experiments were performed on captive-bred guppies that were descendants (9–12 generations) of wild-caught fish collected from Alligator Creek in Queensland, Australia. Stock populations were maintained in eight independent mixed-sex holding tanks, each containing ~300–400 guppies. To minimize inbreeding in the stock populations, random subsets of fish are transferred among holding tanks on a yearly basis. Full and half siblings were generated by randomly pairing a sexually mature male from one holding tank sequentially with two unrelated virgin females who originated from different holding tanks. Males and females were housed together for a 5-day mating period in a 3-L tank, after which males were removed from the tank and transferred to another 3-L tank for a subsequent 5-day mating period. Following the mating period, females were left undisturbed until broods were produced. This breeding protocol was repeated for 40 independent replicates (called ‘family’ hereafter). Offspring from each family were separated by sex at the earliest sign of sexual differentiation (when the male intromittent organ begins to develop) and reared in sex-specific family groups until reaching sexual maturity. The intention of this breeding design was to generate full and half male siblings for each family. However, due to a range of factors, including small brood sizes, the production of mono-sex broods, the apparent absence of breeding and/or fertilizations during the mating period in some pairs, unsuccessful artificial inseminations or a combination of these factors, we lacked sufficient replicates to evaluate both levels of relatedness for every family. Instead, we divided the families into two groups: a focal virgin female was artificially inseminated either with sperm from an unrelated male (R₀) and a full sibling (R_0.5) (R_0.5 + R₀; n = 16) or with sperm from an unrelated male (R₀) and a half sibling (R_0.25) (R_0.25 + R₀; n = 14). For all artificial inseminations, the unrelated male was chosen randomly from a different family generated through the breeding protocol described above, thus ensuring all males were housed in similar conditions. However, this design meant that some families (but not individuals from these families) were represented in both the full- and half-sibling treatments, which we account for in the statistical analyses (described below).

Sperm collection

Male guppies produce sperm bundles (spermatozeugmata) that are easily collected manually (Matthews et al., 1997; Evans et al., 2003). Briefly, sexually mature males were anaesthetized and placed on a glass slide under low-power magnification (Evans, 2009). The ventral side of each male was dried before 60 μL of an extender medium (207 mm NaCl, 5.4 mm KCl, 1.3 mm CaCl₂, 0.49 mm MgCl₂, 0.41 mm MgSO₄ and 10 mm Tris with pH 7.5) was pipetted to the base of the male's gonopodium. The use of the extender medium ensured that sperm remained quiescent prior to analyses (Gardiner, 1978). Gentle pressure was applied to the male's abdomen to release sperm bundles into the extender solution. For each male (R_0.5, R_0.25 and R₀), sperm bundles were subdivided into four separate aliquots: 10 sperm bundles were collected for artificial inseminations, 2–4 sperm bundles were collected for sperm velocity analyses, 10 bundles were collected to assay sperm viability, and the remaining sperm bundles were used to assess sperm morphology. The order of sperm collection was randomized based on relatedness for each competitive dyad to avoid stripping order effects.

Artificial inseminations

Ten sperm bundles from each of the two rival males in each trial (i.e. R_0.5 + R₀ and R_0.25 + R₀) were added to an Eppendorf tube in 20 μL of extender solution and gently mixed to ensure a homogenous distribution of sperm bundles. Because each sperm bundle contains ~2.7 × 10⁵ sperm cells, performing competitive fertilization experiments with an equal number of sperm bundles from each male effectively controls for differences in sperm number between males (Evans et al., 2003). The mixed sperm bundles were taken up by a Drummond^® microdispenser (Drummond Scientific Company, Broomall, PA, USA) and artificially inseminated into an anaesthetized virgin focal female viewed under low-power magnification. Fin clip samples from females and males were collected and stored in absolute ethanol for subsequent paternity analyses. Females were left undisturbed in 3-L tanks for ~10 weeks, during which up to two broods per female were obtained for paternity analyses. Offspring were euthanized within 48 h of birth and placed in absolute ethanol for subsequent molecular analyses (sample sizes are reported below).

Sperm quality analyses

Sperm quality was assessed for each male by quantifying sperm swimming speed, viability and morphology. These are biologically important measures of sperm quality that are associated with fertilization success in noncompetitive and competitive fertilizations in guppies and other taxa (reviewed by Simmons & Fitzpatrick, 2012; Fitzpatrick & Lüpold, 2014). A 3-μL aliquot of the extender medium containing two sperm bundles was placed on an individual well of a 12-cell multitest slide (MP Biomedicals, Aurora, OH, USA), previously coated with 1% polyvinyl alcohol to reduce sperm sticking to the glass (Wilson-Leedy & Ingermann, 2007). These quiescent sperm samples were then activated with 3 μL of a 150 mm KCl solution (Billard et al., 1990) containing 2 mg L⁻¹ BSA to further prevent sperm from sticking to the slide (Pitcher et al., 2007). Computer-assisted sperm analysis (CASA) was used to assess sperm swimming speed for each sample using a CEROS Sperm Tracker (Hamilton Thorne Research, Beverly, MA, USA) under 100× magnification using the threshold values described in Evans (2009). Two sperm velocity measures were determined for each male from different sperm subpopulations within a sample, and the mean of these values was used for analyses. Sperm velocity measures were based on 68 ± 7.6 (mean ± SE) motile sperm tracks per sample. CASA produces several highly co-linear measures of sperm velocity (Simpson et al., 2014), including the average path velocity (VAP), which estimates the smoothed path velocity, the curvilinear velocity (VCL), which is the actual velocity of the sperm over the path, and the straight-line velocity (VSL), which measures the distance between the start and endpoint of the path. To incorporate as much information as possible in our analyses, these co-linear sperm velocity measures were collapsed using principal component analyses into a single principal component (PC1) with an eigenvalue of 2.59, which explained 86.4% of the variance in sperm swimming speed. PC1 was used as a measure of sperm swimming speed in all analyses (note, however, that we obtained qualitatively similar results when using any of the individual measures of sperm velocity). We were unable to quantify sperm swimming speed for one male in the full sibling/unrelated male cross due to an experimental handling error and consequently removed this replicate from analyses of sperm quality.

Sperm viability (i.e. the proportion of live sperm in the male's ejaculate) was determined using a live/dead sperm viability assay (Life Technologies Australia Pty Ltd., Mulgrave, Vic., Australia). This assay uses fluorescent dyes that stain live sperm green with the membrane-permeant nucleic acid stain SYBR-14 and dead sperm red with propidium iodide. Sperm bundles (10 bundles in 20 μL of the extender medium) were broken up by thoroughly vortexing the sample. A 1 : 50 dilution of the SYBR-14 (1 mm) stain was added to a 10 μL sample of the sperm/extender solution. Samples were left in the dark for 10 min, followed by the addition of 2 μL of 2.4 mm propidium iodide and an additional incubation in the dark for 10 min. Samples were viewed under a Leica DM 1000 fluorescence microscope (Leica Microsystems Pty Ltd., North Ryde, NSW, Australia) under 400× magnification, and the number of live and dead sperm was counted from 200 sperm per sample as an estimate of sperm viability.

To assess sperm morphology, sperm head, midpiece and flagellum length were measured from 20 sperm per male. Sperm were digitally photographed using a Leica DFC320 camera fitted to Leica DM 1000 phase contrast microscope under 400× magnification. Sperm lengths were measured using imagej (v1.37; http://imagej.nih.gov/ij/), and mean values were used in statistical analyses.

We did not expect any systematic differences in sperm quality measures between related and unrelated males given the breeding protocols outlined above. Nevertheless, we were concerned that any such systematic differences in sperm quality generated by chance could bias our results. Therefore, we compared each of the sperm traits measured between related and unrelated males to account for any unintentional source of bias in our analyses and found no difference between competing related and unrelated males in any of the sperm traits assessed in this study (Table S1).

Parentage analysis

Genomic DNA was extracted from adult and offspring tissue samples using a standard salting-out protocol (Patwary et al., 1994). Paternity was determined by scoring up to five polymorphic microsatellite loci that have been optimized previously for guppies: TTA, KonD15, KonD21, Pret46 and Pr39 (GenBank accession numbers AF164205, AF368429, AF368430, AB100334 and AF467903, respectively). PCR amplifications were performed on a GeneAmp PCR System 2700 Thermocycler (Applied Biosystems, Foster City, CA, USA) following methods described in Gasparini et al. (2010a). Amplified fragments were separated using an ABI 3100 sequencer (ABI PRISM; Applied Biosystems), and PCR products were visualized using GeneMarker v1.91 (http://www.softgenetics.com). Paternity was assigned to putative fathers, incorporating the known genotype of the mother, using cervus v3.0.6 (Kalinowski et al., 2007). A total of 235 offspring were scored (mean ± SE: 7.8 ± 0.9 per female, n = 30, range 3–21). Families were only considered in the analyses if more than two offspring were assigned to either of the competing males; this criterion removed one family (consisting of three offspring from the R_0.5 + R₀ male treatment) from the analyses. Our final sample size therefore comprised 232 offspring. cervus assigned paternity to 93% (n = 216) of the offspring at the strict (95%) level of confidence and assigned an additional two offspring (from one brood) at the relaxed (80%) level of confidence. Our results remained qualitatively similar when we restricted our analysis to include only offspring assigned using the strict confidence level and when we included males assigned at both levels of confidence. Consequently, we only present data from the strict level of confidence. Seventeen offspring, from eight crosses, could not be assigned to either of the putative fathers (i.e. confidence < 80%) and were therefore excluded from our analyses.

Statistical analyses

To determine whether paternity differed between related and unrelated males, we used a randomization test to compare the observed paternity share of the unrelated males against a null expectation that assumes relatedness does not bias sperm use (i.e. paternity probability = 0.5). Specifically, the observed difference in paternity success between related and unrelated males was compared to the expected difference in paternity success between related and unrelated males for the given brood size under the assumption that competing males had an equal probability of fertilizing eggs. Random binomial probabilities were calculated and resampled 100 000 times to obtain an expected distribution against which the observed binomial distributions from each replicate were tested. Randomization tests were performed for the R_0.5 + R₀ and R_0.25 + R₀ crosses separately using an r script written by W. Black.

To determine the relationship between sperm quality, relatedness and paternity success, we used a generalized linear mixed model (GLMM) with a binomial error distribution and a logit link function. Paternity was coded from the related male's perspective, with offspring sired by the related male coded as successes and offspring sired by the unrelated male coded as failures. All crosses were assessed in a single model with difference in sperm trait values (i.e. sperm head length, midpiece length, flagellum length, swimming speed PC1 and viability) between the related and unrelated male (i.e. related male sperm – unrelated male sperm traits) in each cross added as covariates, the relatedness level of the related male (i.e. full sibling or half sibling) included as a fixed effect and all interactions between each of the sperm traits and the relatedness level as fixed effects. To account for the use of individuals from the same families in the artificial inseminations at different levels of relatedness, we included family identity as a random effect in the model. Attempts to reduce the model by removing nonsignificant interaction terms degraded the model fit, evidenced by elevated Akaike information criterion (AIC) values in the reduced model compared to the full model (full model: AIC = 104.50; reduced model: AIC = 559.32). Consequently, we only consider the full model in the analyses. All analyses were performed in r v3.0.1 (R Development Core Team, 2013). GLMM analyses were performed using the glmer function in the lme4 package (Bates et al., 2014). Significant values from the glmer model were calculated from type II Wald chi-square tests using the ‘anova’ function in the car package. Overdispersion was assessed using the function overdisp_fun in r, and this analysis revealed that overdispersion was not an issue in the model.

Results

Paternity analyses revealed that fertilization success was skewed towards unrelated males, but only when females were inseminated with sperm from full siblings and an unrelated male competitor (i.e. R_0.5 + R₀). When females were artificially inseminated with an equal number of sperm from a full sibling and unrelated male, mean (± SE) paternity percentage was 40.6 ± 8.7% for R_0.5 males. The mean difference in paternity between R_0.5 and R₀ males was −18.9% (n = 15, Fig. 1), which differs significantly from the null expectation of equal paternity between competing males (random binomial probability, P = 0.038). In contrast, when females were artificially inseminated with sperm from a half sibling and unrelated male, mean (± SE) paternity percentage was 52.2 ± 6.3% for R_0.25 males. The mean difference in paternity between R_0.25 and R₀ males was 4.3% (n = 13, Fig. 1), which did not differ from the null expectation (P = 0.35).

Details are in the caption following the image — **Figure 1**
Open in figure viewer PowerPoint

Proportion of offspring sired (mean ± SE) by related males when females were artificially inseminated with equal numbers of sperm from a related and unrelated male. Males were related at the level of half sibling (R_0.25) or full (R_0.5) sibling, resulting in artificial inseminations of half sibling and unrelated male (R_0.25 + R₀) or a full sibling and unrelated male (R_0.5 + R₀). The dotted line represents the null expectation of equal paternity between competing males. The * indicates a significant difference in paternity success between males based on randomization tests.

The paternity skew against related males observed in the R_0.5 + R₀ treatment could have been generated by postcopulatory mechanisms of inbreeding avoidance (e.g. cryptic female choice in favour of unrelated sperm) and/or sperm competition (i.e. differences in sperm quality between competing males where sperm quality was consistently higher in unrelated males). To distinguish between these possibilities, we determined whether the proportion of offspring sired by the related male (R_0.5 and R_0.25) was influenced by sperm quality while also controlling for the relatedness level of the competing males. Relatedness level and difference in sperm viability between males significantly influenced paternity success of related males in the full and reduced model (Table 1, Fig. 2). However, the significant relatedness level × sperm viability interaction terms in the model revealed that although males with greater sperm viability sired more offspring in both relatedness treatments, the effect of sperm viability on competitive fertilization success was influenced by the level of relatedness of male competitors (Fig. 2). Specifically, the effect of sperm viability on competitive fertilization success is more pronounced in the full-sibling treatment than the half-sibling treatment. Compared with the half-sibling treatment, full-sibling males sired more offspring when they had high sperm viability (relative to unrelated males) and fewer offspring when they had lower sperm viability (relative to unrelated males) in competitive fertilizations (Fig. 2). No other sperm quality traits measured predicted paternity success (Table 1). Thus, this analysis supports the paternity results from our randomization tests while demonstrating the importance of considering complex interactions between sperm traits, in this case sperm viability, and levels of relatedness when examining paternity success.

Table 1. The proportion of offspring sired by related males in relation to differences in sperm traits between the competing males and level of male relatedness. Relatedness refers to the level of relatedness of the related sperm competitor (R_0.5 or R_0.25). Test parameters (χ²) and significance levels (P) are generated from generalized linear mixed-effects models. Significant parameter values are presented in bold text

Parameter	χ²	P
Sperm head length	2.37	0.12
Sperm midpiece length	1.16	0.28
Sperm flagellum length	1.94	0.16
Sperm viability	14.88	< 0.001
Sperm swimming speed (PC1)	0.00	0.99
Relatedness	14.52	< 0.001
Relatedness × Sperm head length	1.16	0.28
Relatedness × Sperm midpiece length	0.00	0.99
Relatedness × Sperm flagellum length	0.01	0.91
Relatedness × Sperm viability	10.20	< 0.01
Relatedness × Sperm swimming speed (PC1)	1.58	0.21

Discussion

Our results demonstrate that competitive fertilization success was biased towards unrelated male guppies, but only when females were inseminated with sperm from a full sibling (R_0.5) and an unrelated male (R₀). In contrast, competitive fertilization success was not influenced by genetic relatedness when females were artificially inseminated with sperm from a half sibling (R_0.25) and an unrelated male (R₀). As our experimental design prevented precopulatory mechanisms from biasing paternity, our results provide strong support for the idea of postcopulatory inbreeding avoidance in guppies. These findings support recent work showing that female guppies use postcopulatory processes to bias paternity towards unrelated males following artificial insemination by full-sibling and nonsibling males (Gasparini & Pilastro, 2011) or highly inbred (four generations of full-sibling matings) and outbred males (Zajitschek et al., 2009). However, our data also demonstrate that paternity biasing in guppies is sensitive to the genetic relatedness of the competing males and is only evident in matings involving full siblings (also see Zajitschek et al., 2009). Similar inbreeding avoidance mechanisms appear to be in place in wild populations. For example, Johnson et al. (2010) reported that unrelated males sired more offspring in clutches from multiply mated female Trinidadian guppies, although this field result could have resulted potentially from both pre- and postcopulatory processes. Inbreeding avoidance mechanisms specifically targeting brothers are likely beneficial for female guppies as a single generation of full-sibling inbreeding can reduce juvenile survival (Nakadate et al., 2003) and delay the onset of sexual maturity (Pitcher et al., 2008) and reduce male courtship behaviours (Mariette et al., 2006). Consequently, multiple mating by females coupled with postcopulatory inbreeding avoidance mechanisms likely mitigates inbreeding depression in guppies.

The extensive use of guppies as a model system for studying postcopulatory sexual selection and inbreeding offers a rare opportunity to evaluate how variance in male relatedness influences inbreeding avoidance exclusively at the postcopulatory level. Together with the present study, seven other studies have used artificial inseminations to assess sperm competitiveness in males of varying levels of relatedness (Evans et al., 2003, 2008; Evans & Rutstein, 2008; Zajitschek et al., 2009; Gasparini et al., 2010a; Boschetto et al., 2011; Gasparini & Pilastro, 2011). Examining these studies together revealed two important patterns. First, significant biasing of paternity in favour of unrelated males is only observed in artificial inseminations involving relatedness levels of full sibling and above in guppies (e.g. this study, Zajitschek et al., 2009; Gasparini & Pilastro, 2011). Second, when we combined these studies to examine the relationship between related male paternity and level of relatedness (see Supporting Information for details), we observed a significant decrease in paternity success of related males as male relatedness to females increased (linear regression: n = 5, r = 0.91, P = 0.03, Fig. 3). Thus, in guppies, postcopulatory inbreeding avoidance appears to be increased when inbreeding risk is elevated. A similar pattern of reduced paternity of related males with increasing relatedness was observed in Drosophila melanogaster, where full-sibling males exhibited lower competitive paternity success than half siblings, cousins and unrelated males (Mack et al., 2002; but see Ala-Honkola et al., 2011). Moreover, negative relationships between genetic similarity (i.e. band sharing) between males and females and a males' paternity success in the sand lizard Lacerta agilis (Olsson et al., 1996), ascidian Diplosoma listerianum (Bishop et al., 1996) and the marsupial Antechinus agilis (Kraaijeveld-Smit et al., 2002) also suggest that cryptic female choice for unrelated sperm intensifies as relatedness between males and females increases. However, the accumulated evidence from guppies (Fig. 3) represents the first evidence for a graded inbreeding avoidance response that can be attributed solely to postcopulatory processes. This graded response may stem from the relative costs and benefits of inbreeding, as females should only avoid inbreeding when the costs are high (i.e. in full-sibling matings), while potentially reaping inclusive fitness benefits when the costs are low (i.e. in matings involving relatedness levels of half siblings or lower) (Kokko & Ots, 2006).

Our analysis also sheds light on how variation in sperm quality among males influences competitive fertilization success. Our results revealed that sperm viability is an important predictor of competitive fertilization success in guppies, although levels of relatedness of the competing males modulated this effect. Although sperm viability is commonly expected to influence male fertility and to be shaped by sperm competition, there is relatively little evidence that sperm viability influences competitive fertilization success (Simmons & Fitzpatrick, 2012). For example, sperm viability predicts competitive fertilization success in the cricket Teleogryllus oceanicus (García-González & Simmons, 2005) and the swordtail Xiphophorus nigrensis (Smith, 2012), but in two species of frogs (Crinia georgiana and Litoria peronii), sperm viability does not influence male fertility under competitive conditions (Sherman et al., 2008, 2009; Dziminski et al., 2009). Therefore, our findings contribute towards a relatively scarce body of the literature revealing the importance of sperm viability during sperm competition. Interestingly, however, the remaining sperm traits assessed in this study (sperm morphology and velocity) did not predict sperm competitiveness. This is surprising as sperm viability is negatively genetically correlated with sperm morphology (head, flagellum and total length) in the study population (Evans, 2011). Yet, our finding is partially in keeping with recent work on guppies and other poeciliid fishes that did not find an effect of sperm morphology and only weak effects of sperm swimming speed on competitive fertilization success (Gasparini et al., 2010b; Boschetto et al., 2011; Smith, 2012). Nevertheless, it remains unclear why sperm morphology and swimming speed appear to be unrelated to male fertility in this and other studies of poeciliid fishes, as there is growing evidence that these sperm traits, particularly sperm swimming speed, predict male fertilization success during sperm competition (Simmons & Fitzpatrick, 2012).

Our results, and those summarized from recent studies of guppies (Fig. 3), highlight the importance of postcopulatory inbreeding avoidance mechanisms as a means of mitigating inbreeding. Although we cannot entirely rule out the possibility that differences in ejaculate traits (not measured here) may have contributed towards our findings, we suggest that our results are more consistent with the notion that females exert some form of postcopulatory selection that favours unrelated males. One potential mechanism to account for the paternity biases detected in our study is that offspring arising from consanguineous matings (i.e. > R = 0.5) exhibit impaired survival compared to those sired by unrelated parents. However, in the case of guppies, this explanation seems unlikely as Gasparini & Pilastro (2011) demonstrated that under noncompetitive fertilization conditions, females produced equivalent sized broods when artificially inseminated with sperm from full siblings or unrelated males. Instead, we suggest that our findings are more likely to be explained by fertilization biases that favour sperm from unrelated males when they compete to fertilize eggs. This conclusion is supported by the previous observation that female guppies exert cryptic female choice via the differential action of their ovarian fluid on the sperm swimming velocity of ejaculates from related and unrelated males (Gasparini & Pilastro, 2011). Moreover, Gasparini & Pilastro (2011) showed that under conditions of sperm competition, this differential effect of ovarian fluid on sperm velocity generated a significant bias in paternity in favour of unrelated males, leading them to hypothesize that such effects may be attributable to interactions between peptides in the ovarian fluid and sperm membrane [e.g. major histocompatibility (MHC) peptides]. Indeed, the MHC complex mediates fertilization success in mice (e.g. Wedekind et al., 1996; Rülicke et al., 1998) and may play a similar role in guppies. Thus, avenues for future examination would be to experimentally validate the role of MHC in postcopulatory inbreeding avoidance mechanisms in guppies and to assess whether the graded response in paternity biasing observed across various levels of relatedness is mirrored by increasing effects of ovarian fluid on sperm performance as relatedness increased. Elucidating the mechanisms driving paternity biasing based on relatedness promises to be both a challenging and stimulating future research endeavour.

Acknowledgments

We thank C. Duggin for his assistance with data collection, Y. Hitchen for performing paternity analyses, W. Black for his assistance with analyses and the FLS R Group for helpful discussion. We also thank L. Cookson, R. Cresswell-Davies, M. Darkes, D. Darlington, I. Darolti, K. Elsom, E. Varga and two anonymous referees for useful comments on an earlier draft of this manuscript. This research was funded by the Australian Research Council in the form of an Australian Postdoctoral Fellowship to JLF, a Discovery Project Grant to JPE and a University of Western Australia Research Development Award to JLF. This research was performed in accordance with the guidelines governing the use of animals in research and was approved by the University of Western Australia's Animal Ethics Committee (Licence # 3/100/513).

Supporting Information

References

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Volume27, Issue12

December 2014

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jeb12545-sup-0001-TableS1.docxWord document, 26.6 KB	Table S1. Comparison between sperm traits of related and unrelated males competing to fertilize eggs in artificial inseminations.
jeb12545-sup-0002-AppendixS1.docxWord document, 13.4 KB	Appendix S1. Additional methodological details.
jeb12545-sup-0003-SuppInfo.docxWord document, 15 KB

Postcopulatory inbreeding avoidance in guppies

Abstract

Introduction

Materials and methods

Experimental animals and breeding protocols

Sperm collection

Artificial inseminations

Sperm quality analyses

Parentage analysis

Statistical analyses

Results

Discussion

Acknowledgments

Supporting Information

References

Citing Literature

Figures

References

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