The interplay of environmental and social factors influences balancing selection: 6Pgdh in bulb mites

The interplay of environmental and social factors influences balancing selection: 6Pgdh in bulb mites | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article The interplay of environmental and social factors influences balancing selection: 6Pgdh in bulb mites Pranav Unnikrishnan, Anna Spaeth, Magdalena Trojańska, Wieslaw Babik, and 1 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-4835969/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Balancing selection, the process by which multiple alleles are maintained in a population, can occur through genotype by environment interactions. The polymorphism of 6Pgdh in bulb mites involves two alleles, S and F, which have opposing effect on male reproductive success. While S-bearing males have a reproductive advantage and the S allele fixes in the laboratory populations, polymorphism is regularly observed in natural populations. We hypothesise that 6Pgdh is under balancing selection in bulb mites, driven by fluctuations of temperature and sexual selection intensity. This study uses experimental evolution to track allele frequency changes over 13 generations under different temperatures (12 °C and 18 °C) and sexual selection intensities (equal and female-biased sex ratios). The results show a significant increase in F allele frequency under higher sexual selection intensity at 12 °C. This suggests that individuals with the F allele gain a reproductive advantage at lower temperatures, and 6Pgdh polymorphism is maintained through a three-way interaction genotype x abiotic (temperature) x social environment. However, in another experiment we did not find significant associations between male genotype and reproductive success across different temperatures. The complex interplay between environmental factors and social dynamics in maintaining genetic polymorphism highlights that multiple factors can interact in driving balancing selection. Biological sciences/Evolution/Experimental evolution Biological sciences/Evolution/Sexual selection Biological sciences/Biological techniques/Experimental organisms/Non-model organisms genetic polymorphism environment-driven balancing selection genotype by environment interaction for fitness sexual selection temperature Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction Genetic variation, which can be considered the fundamental raw material for natural selection, is a crucial factor for evolutionary processes to manifest. An increase in genetic variation within a population increases the potential for evolutionary change, as postulated by Fisher, “the rate of increase in the average fitness of a population is equal to the genetic variance of fitness of that population” (Fisher 1941). Such genetic variation, which results in diverse phenotypes, allows populations to adapt to environmental challenges (Barrett and Schluter 2008). Nevertheless, directional selection tends to diminish genetic variation by selecting for particular variants, thereby increasing their frequency within a population (Bürger and Lynch 1995). This often results in the eventual fixation of the favoured variant (Wright 1932; Endler 1986). Therefore, the persistence of genetic polymorphism, despite the expectation of decreased variation under directional selection, presents a paradox (Lewontin 1974; Radwan et al. 2016; Hallsson and Björklund 2012). Selection processes that result in the maintenance of polymorphisms fall under a common umbrella term, balancing selection. However, a number of different mechanisms of balancing selection have been proposed and their relative importance is still under debate (Stamp and Hadfield 2020; Fijarczyk and Babik 2015). In some populations, heterozygote advantage can be observed, as in the case of the X-linked glucose-6-phosphate dehydrogenase gene in humans, where heterozygous individuals are protected from severe malaria (Manjurano et al. 2015). This increases the survival and reproductive success of heterozygous individuals, ensuring that both alleles remain present in the population (Manjurano et al. 2015). The maintenance of polymorphism can also be attributed to negative frequency-dependent selection, in which fitness of alleles changes depending on their frequency, with rare variants having an advantage over more common ones. Fitzpatrick et al (2007) demonstrated this mechanism for Drosophila melanogaster foraging ( for ) gene, which is responsible for larval foraging behaviour, where the highest fitness always goes to individuals with the rare allele and the polymorphism of the gene is maintained. Antagonistic pleiotropy is another balancing selection mechanism, where the trade-off between different fitness traits leads to the maintenance of polymorphism (Connallon and Clark 2013). For example, in the case of the Mpi and Idh-2 enzyme loci in red deer ( Cervus elaphus ), each with two different alleles associated with juvenile survival, genotypes associated with low survival in the first two years of development were found to have higher female reproductive fitness, resulting in the maintenance of gene polymorphism (Pemberton et al. 1991). An analogous mechanism is sexually antagonistic pleiotropy, where the trade-off is between the fitness of the sexes. Because trait fitness varies between the sexes, polymorphism is maintained within a population. Nuzhdin et al (1997) showed that the genes within five autosomal quantitative trait loci (QTL) associated with lifespan and viability in D. melanogaster showed strong sex-dependent effects, maintaining genetic variation in lifespan. The significance of heterogeneous environments in maintaining genetic variation has been well documented (Hedrick et al. 1976; Slatkin 1987), particularly from early theoretical modelling studies (Via and Lande 1987; Gillespie and Turelli 1989; Levins 1968). The phenomenon termed environment-dependent balancing selection occurs when the fitness of alleles depends on the environment (there is a crossover genotype-by-environment interaction for fitness), and environmental factors vary in space or time (Kokko and Heubel 2008). Given the expected variability of the environment, such environment-dependent selection can potentially be a powerful driver of balancing selection. Early studies on this topic used simple models focusing on simple genetic systems, often considering only a single environmental factor and assuming constant selection pressure over time (Levins 1968; Hedrick et al. 1976). These models suggested that the parameter space in which polymorphism could be maintained was relatively narrow, implying that the maintenance of genetic variation required rather specific conditions that may rarely occur in nature. In contrast, more recent studies have adopted more complex and realistic models that consider polygenic traits, multi-allelic genes, and the simultaneous effects of multiple environmental factors (Carley et al. 2021; Abdul Rahman et al. 2021). These newer models consider the dynamic nature of natural environments, where multiple factors can change in unpredictable ways and interact with genetic systems. As a result, these newer studies have shown that the conditions for maintaining polymorphism are less restrictive than previously thought. The broader and more inclusive parameter space found in these models suggests that genetic variation can be maintained under a wider range of environmental conditions, highlighting the importance of considering complex interactions between genetics and environment to reflect the nature of real-world scenarios. The findings of the newer models have been corroborated by empirical studies, thereby demonstrating their robustness (Brook 2009; van Dongen et al. 2016; Zan and Carlborg 2024). As mentioned above, the role of environmental heterogeneity in driving balancing selection in natural systems can be quite complex. The potential of a given environmental factor to shape genotype-by-environment interactions may depend on another environmental variable. For example, several studies have demonstrated genotype-by-environment interactions for sexual fitness, including male reproductive success (Patlar and Ramm 2020; Greenfield and Rodríguez 2004; Ingleby et al. 2010). The potential of such interactions to drive selection should vary with conditions that influence the strength of sexual selection, such as population density or sex ratio. Consequently, one might observe a three-way interaction between genotype, abiotic and biotic (social) environment. In the case of the 6-phosphogluconate dehydrogenase ( 6Pgdh ) polymorphism in bulb mite Rhizoglyphus robini , a three-way interaction may be expected as the mechanism of polymorphism maintenance, where one of the alleles (the S allele) is associated with increased male reproductive success (Konior 2006; Skwierzyńska and Plesnar-Bielak 2018), which should lead to its rapid fixation and loss of the polymorphism. However, while the alternative F allele is indeed rapidly lost in the laboratory, both alleles are often maintained in natural populations (Unnikrishnnan et al. 2024). A previous experimental evolutionary study showed that the selective advantage of the S allele is reduced (but not lost) in populations evolving at a reduced temperature of 18 °C compared to the standard laboratory temperature of 24 °C (Plesnar-Bielak et al. 2020). Similarly, the study also showed that S allele frequency increased less rapidly in populations where sex ratio manipulation relaxed the intensity of sexual selection (Plesnar-Bielak et al. 2020). It has been speculated that these two factors, if applied simultaneously, could have led to a reversal of fitness rank and a selective advantage for the F allele. In such a case, the interaction of temperature and social environment and their heterogeneity could explain the maintenance of the 6Pgdh polymorphism in the wild. Here we use experimental evolution to test how the interaction of temperature and sexual selection intensity shapes 6Pgdh allele frequencies. We track changes in 6Pgdh frequencies in replicate populations for 13 generations under two levels of temperature (18 °C and 12 °C) interacting with two levels of selection intensity (equal sex ratio and female-biased population with relaxed sexual selection). We predict that there is a cost for the S allele at lower temperature. If this cost is associated with life history fitness (as opposed to reproductive fitness), we predict an increase in F-allele frequency under lower temperature and relaxed sexual selection. This is because under weak sexual selection intensity, the reproductive advantage of the S-allele should be negligible, hence it may be outweighed by the life history cost of the S-allele at lower temperature. Alternatively, if the cost is associated with reproductive fitness, the reproductive advantage of the S allele itself might be temperature dependent. Under such a scenario, the F allele might gain reproductive advantage at low temperature, and we would expect an increase in its frequency under low temperature and intense sexual selection. Materials and Methods Study system 6-Phosphogluconate dehydrogenase ( 6Pgdh ) plays a pivotal role in the pentose phosphate pathway, which, in conjunction with glycolysis, represents a major glucose catabolism pathway. The pentose phosphate pathway generates ribose-5-phosphate sugars and NADPH molecules. The pathway exerts a significant influence on redox homeostasis and the biosynthesis of ribonucleotides and represents a principal source of NADPH (Stincone et al. 2015). A single nonsynonymous nucleotide polymorphism in 6Pgdh is associated with male-fitness differences in bulb mites, representing a case of sexual selection. The two alleles of 6Pgdh , designated S and F, differ in one amino acid substitution (arginine to methionine). Under standard laboratory conditions, males carrying the S allele exhibit increased reproductive fitness, as evidenced by higher mating frequency and sperm production (Skwierzyńska and Plesnar-Bielak 2018) compared to F-bearing males. Heterozygotes appear to exhibit an intermediate phenotype (Łukasik et al. 2010; Skwierzyńska and Plesnar-Bielak 2018). The 6Pgdh genotype does not appear to affect female reproductive fitness. However, females mated with SS males exhibit a decreased fitness compared to those mated with FF males, indicating the presence of sexual conflict. Once more, mating with heterozygous males result in an intermediate level of fitness reduction (Skwierzyńska and Plesnar-Bielak 2018). As predicted, given its advantage in male-male competition, the S-allele rapidly fixes in laboratory populations. However, 6Pgdh -polymorphic populations are common in natural populations, with the level of polymorphism varying across locations and through time (Unnikrishnan et al. 2024). Source population Experimental evolution populations were established from a 6Pgdh polymorphic population (source population), in which the frequency of the F allele had been increased before the start of the experiment. It was done in order to start experimental evolution from approximately equal frequencies of both alleles. To do it, we used a field collected population originating from >100 individuals found on onions collected in Łazany (50.0206 N, 19.8924 E), near Kraków in July 2020. This field collected population was kept at 8 °C, except for the first week after establishment, when they were kept at 24 °C to let juvenile individuals develop so that the population would expand. The source population was created in spring 2021. We randomly paired virgin females and males from the field-collected population, in which the F allele frequency was about 0.23. After the pairs mated (almost 300 pairs) and females laid eggs, both parents were genotyped. We then looked for pairs with at least 2 copies of the F allele (either both parents FS, or one FF and one SS, or one FF and one SF, or both parents FF). The offspring from such pairs were used to establish the source population. The population was allowed to expand freely for ca. 2 months at 24 °C (which corresponds to 3-4 mite generations), before it was moved to 12 °C to extend generation time, to prevent adaptation to 24 °C and the loss of the F allele. This population was used to start the experimental evolution populations within one month after transferring to 12 °C (less than one mite generation at that temperature). The F-allele frequency in the source population was 0.6 when the experimental evolution started. Culturing conditions All populations (source and experimental) were maintained in plastic containers (approximately 2.5 cm in diameter) with a plaster of Paris base soaked with water. They were maintained at >90% humidity, constant darkness, with powdered yeast provided ad libitum as a food source. Individually isolated mites were maintained in glass tubes with diameter of approximately 1 cm. Experimental evolution Experimental evolution was carried out with two levels of temperature (18 °C and 12 °C) crossed with two levels of sexual selection intensity achieved by manipulating the sex ratio (equal sex-ratio and female biased sex-ratio treatments with strong and weak sexual selection intensity respectively). The lowest temperature employed in the preceding study (Plesnar-Bielak et al. 2020) was selected as the high temperature level of 18°C, whereas the lower temperature level of 12 °C is pertinent to the average annual temperature in Poland. In order to achieve a weaker selection intensity, the proportion of males in the weak sexual selection intensity level was reduced to 0.2, in comparison to the previous study where this proportion was 0.3 (Plesnar-Bielak et al. 2020). Five replicate populations were used for each treatment, resulting in a total of 20 populations. For each generation, individuals were isolated at the final nymphal stage (tritonymphs) into separate vials. The individuals were then allowed to develop individually into adults and were sexed (still in individual vials). These virgin mites were then put in common containers (one container per replicate) controlling for the sex ratio (64 females + 16 males in female-biased populations and 40 females + 40 males in equal sex-ratio populations) and allowed to interact for 6 days, during which the mites could mate freely, and females could lay eggs. After this time, adult individuals were removed, and eggs were left for further development. Allele frequencies of 6Pgdh were measured from a random sample of around 40 individuals from every two consecutive generations followed by a five-generation break (Fig 1a). Reproductive success We measured the success of the males with 6Pgdh different genotypes in reproductive competition with SS-homozygous males from the stock laboratory population. The reproductive success was assessed using the sterile male technique, a well-established method in bulb mite research (Parker 1970; Radwan 1991; Radwan and Siva-Jothy 1996). This technique involves using an experimental male and a tester male and allowing them to compete for the female. The tester males are irradiated with 20 kRad (200 Gy) of gamma radiation from Co 60 . Following irradiation with such a dose, males are still able to fertilize eggs, but the eggs do not hatch (Radwan and Siva-Jothy 1996). Therefore, since bulb mite females do not lay unfertilized eggs, an experimental male’s reproductive success can be calculated as a fraction of the eggs that hatched. The fraction of eggs that are fertilized by normal, non-irradiated males and still do not hatch is negligible. The experimental males were taken from three populations that had evolved under 12 °C and equal sex-ratio, since that particular treatment showed F-allele frequency increase. Only three populations from this treatment were included because of logistic constraints, and these were chosen because they had the highest F-frequency within the treatment. The females and tester males originated from the base population maintained under 24 °C, since this population is fixed for S allele. Firstly, 50 females were randomly selected from both the experimental and tester populations and kept in separate containers for one week to lay eggs at 12 °C. After this period, the females were removed and the containers with the eggs were transferred to the respective temperatures. The experiment was conducted at three temperatures: 24 °C (standard laboratory temperature), 12 °C (average yearly ground temperature at 5 cm depth in Poland) and 8 °C (low temperature relevant to colder periods in Poland). When the eggs hatched and the individuals reached the tritonymph stage, approximately 600 tritonymphs from the control population were isolated in individual vials in order to obtain virgin females for the experiment. Following the emergence of the adults in the populations, the experimental and tester (irradiated) males were isolated for a period of three days prior to the commencement of the experiment. The tester males were provided with food containing blue dye, which enabled the distinction between experimental and tester males. The experimental setup comprised one experimental male, one tester male (identifiable due to the blue dye) and the virgin female from the base population. After three days, the tester males were removed, and the experimental males were genotyped. The females were kept for two more days (or four days when there were insufficient number of eggs) and then removed. From each vial, 10 to 20 eggs (depending on the number of eggs available) were then transferred to a different vial as a sample, and the fraction of the eggs hatched was recorded and used for analysis. The experiment was conducted in two separate blocks, each containing experimental males from all three populations, with the populations that were the source for the experimental males differing by two generations between the two blocks (Fig 1b). DNA extraction and 6Pgdh genotyping For DNA extraction, individual mites were placed in 1% chelex solution (40μl) and were crushed. After adding 3μl of proteinase-K (EurX, Poland), such a mixture was incubated in a thermocycler (Thermofisher Scientific, Poland) (10 min 94°C, 15 min 75°C). Such prepared samples were stored in a fridge (ca. 6°C) until the genotyping assay. Real-Time PCR was used for 6Pgdh genotyping. Fluorogenic TaqMan probes (Thermofisher Scientific) specific for the missense single nucleotide polymorphism were used to determine the F and S alleles (see Unnikrishnan et al. 2024). The Bio-Rad CFX96 Real-Time PCR detection system was used for the genotyping. TaqMan Genotyping Master Mix (Thermofisher Scientific) and Custom Genotyping Assay (Thermofisher Scientific) that included allele-specific primers and fluorescent probes were mixed in 10:1 ratio. 5.5μl of such a mix and 4.5μl of chelex with suspended DNA were put in a 96 well plate for genotyping. PCR was performed in 41 cycles (15 sec 95 °C, 1 min 60 °C). Statistical analysis To test how 6Pgdh allele frequencies were changing over generations depending on the selection treatment, we used Generalized Estimating Equations (GEE) approach using the geeglm function (geepack, version 1.3.10). Compared to repeated measures ANOVA, which is usually used to handle generational data, GEE is better suited here because it accommodates various correlation structures and non-Gaussian distributions, providing robust estimates even with complex data. The GEE model here, used a vector containing the S and F alleles counts (per population obtained from each generation tested) as the response variable, with temperature and sexual selection intensity (along with their interaction) as the predictor variables. To incorporate the repeated measure nature of the data in the model, we used population ID as the vector for the clusters (id=Population) and the generation number specifying the order of the repeated measures in each unit (waves=Generation). We used a binomial model with an AR1 (autoregressive) correlation structure. We have also checked for significant increase/decrease in F-allele frequencies within the experimental evolution period. To do it, we calculated differences in F-allele frequencies between generation 13 and generation 0 for each population. For each selection treatment, these differences were compared to 0, using two-tailed one sample t-test (stats package, version 4.3.0). For the reproductive success data, we used Generalized Linear Mixed-Effects Model (GLMM) using glmmTMB function (glmmTMB, version 1.1.9) with a vector containing the number of eggs that hatched (successes) and the number of unhatched eggs (failures) as the response variable, with temperature and genotype of males (with their interaction) and block id as fixed factors and population id of the experimental males as a random factor. The model was fitted assuming a betabinomial distribution to account for the overdispersion. Data visualizations were created using the ggplot2 package in R (ggplot2, version 3.4.4). All statistical analyses were conducted using R version 4.3.0 (2023-04-21 ucrt). Results Experimental evolution We found that sexual selection intensity and temperature affected 6Pgdh allele frequency changes. Notably, the interaction between sexual selection intensity and temperature had a significant effect (GEE, χ² = 4.58, p = 0.03) on the allele frequency of the experimental populations after 13 generations. This indicates that the impact of sexual selection intensity on allele frequency varied with temperature (individual effects: - sexual selection intensity: χ² = 9.56, p = 0.0019; temperature: χ² = 1.51, p = 0.22). To further understand this interaction, we analyzed the effects of sexual selection intensity on allele frequencies at each temperature separately. The results show that sexual selection intensity had a significant effect at 12 °C (χ² = 24.58, p < 0.001) (Fig 2) resulting in an increase in F-allele frequency. This result was confirmed by the t-test, showing an increase in F allele frequency in populations with higher sexual selection intensity at 12 °C (t₄ = 5.06, p = 0.007), but not in populations with lower sexual selection intensity (t₄ = -0.47, p = 0.66). At 18 °C, sexual selection intensity did not significantly affect allele frequencies (χ² = 2.96, p = 0.085), as evidenced by the lack of significant changes in F allele frequency for populations with low sexual selection intensity (t₄ = 1.97, p = 0.12) and those with high sexual selection intensity (t₄ = -0.83, p = 0.45) (Fig 3). Reproductive success We did not find any significant associations between reproductive success of the experimental males and the predictors tested (Fig 4). Specifically, the interaction between temperature and male genotype was not significant (χ 2 = 2.86, p = 0.58), suggesting that the reproductive success of males with different genotypes did not differ in different temperatures. Neither temperature (χ 2 = 2.16, p = 0.34) nor male genotype (χ 2 = 3.60, p = 0.17) were significant individually. The only predictor variable which was significant was block id (χ 2 = 6.4323, p = 0.011). To further investigate the significant effect observed for block id, we tested the model at each of the blocks separately. There were no significant effects for the interaction between temperature and male genotype on the reproductive success at either of the blocks separately (block 1:- temperature X male genotype: χ 2 = 6.03, p = 0.20; block 2:- temperature X male genotype: χ 2 = 4.87, p = 0.30). Discussion The process of balancing selection maintains multiple alleles within a population. Several mechanisms have been proposed to explain this phenomenon, including negative frequency-dependent selection, heterozygote advantage, and environment-dependent selection (Charlesworth 2006; Huang et al. 2023). In systems involving environment-dependent balancing selection, there may be cases where interactions between biotic, abiotic and social environments contribute to the maintenance of polymorphism (Hedrick et al. 1976; Ferrer-Admetlla et al. 2008). Such a situation may occur in the bulb mite metabolic gene 6Pgdh . Although males with the S allele show higher reproductive fitness in laboratory populations, polymorphism persists in natural populations (Unnikrishnan et al. 2024). The aim of this study was to investigate whether environmental factors - temperature and intensity of sexual selection - act alone or in combination to drive this balancing selection. The results of our study provide evidence for the existence of environment-dependent balancing selection on the gene 6Pgdh in bulb mites. In particular, a significant increase in the frequency of the F allele at low temperature and high sexual selection intensity highlights that balancing selection in the bulb mite 6Pgdh gene is driven by a complex interplay between genotype, environmental factors and social dynamics. Furthermore, although there have been several other studies of the factors contributing to balancing selection, many of these have focused on the separate effects of individual factors (Carley et al. 2021; Smith et al. 2021; Lonn et al. 2017). A multifaceted approach to the study of balancing selection has rarely been used. A recent study on seed predation in an African savannah small mammal community system (Schoepf and Pillay 2023) is a notable exception. It shows that multiple factors such as seed size, seed type, predation risk, habitat type, seasonality and their interactions drive seed variation, with the possibility that these factors are likely to be hierarchically ordered. Similarly, a study by Joswig et al (2022) showed how the interaction of climate and soil fertility influences global plant variation. Our study adds to these by highlighting the role of social dynamics in considering such interactions within species. In particular, our results suggest that at lower temperatures, males carrying the F allele gain an advantage in the competition for mates. The observed increase in F allele frequency under low temperature and intense sexual selection supports the notion that the reproductive advantage of the S allele is not absolute but varies with temperature. However, reproductive advantage of the F allele at low temperature was not confirmed by the reproductive success assay using direct male-male competition at different temperatures. It is possible that the conditions of the experiment were not optimal for the reproductive advantage of the F-males to be expressed. It is possible that the reproductive advantage of the F-males could have been observed under conditions with more competitors or if the duration of the competition had been longer. In addition, the design of the experiment introduces some additional variation due to factors such as differences in egg-laying ability of the females (less than 10 eggs from some females to more than 200 eggs from some females) or due to the non-uniform nature of the irradiation effects on the males. This high level of variation indicates that the current experiment lacks sufficient statistical power to detect moderate but still biologically relevant, differences. On the other hand, this method has been used previously in this (Radwan and Siva-Jothy 1996; Plesnar-Bielak et al. 2018; Skwierzyńska and Plesnar-Bielak 2018) and other systems (Sirot et al. 2007; Mazza et al. 2015; Magris et al; 2015) and allowed the detection of significant results. Different factors interacting with each other have been shown to influence adaptation rates, which may be linked to the impact of these factors on genetic variation and polymorphisms in important genes. The importance of considering heterogeneous environments and social structure to study genetic variance in the design and execution of experimental evolution has been recognized and highlighted (Van den Bergh et al. 2018). An experimental evolution study of the bruchid beetle ( Callosobruchus maculatus ) investigated the effect of varying natural (food type) and sexual (mating system) selection intensities on the rate of adaptation (Fricke and Arnqvist 2007). The study showed that mating system treatment (social factor) influenced the rate of adaptation, depending on food type (abiotic factor). In Drosophila serrata , an experimental evolutionary study showed that the effect of natural selection on the rate of adaptation to novel environments was greater in a monogamous mating system (Rundle et al. 2006). A similar result was observed in an experimental evolutionary study of Rhizoglyphus robini , where polygamous populations adapted rapidly to changes in thermal environments, whereas monogamous populations suffered fitness declines and were more likely to go extinct in novel environments (Plesnar-Bielak et al. 2012). These studies, together with our results, emphasize the need to consider methods to incorporate multi-factorial interactions (abiotic, biotic and social factors) in laboratory studies such as experimental evolution in order to obtain meaningful results and ultimately unlock the answers to many evolutionary processes. Furthermore, although such experimental systems and designs could become considerably more complex due to the addition of multiple factors and their interactions, inference could be refined by focusing on individual and key metabolic genes, as demonstrated in our study. By focusing on a key metabolic gene, the insights gained are fundamental to evolutionary biology, and understanding the mechanisms of balancing selection has practical implications for conservation biology (Hoffman et al. 2017; Muirhead 2001). Maintaining genetic diversity is crucial for the adaptability and resilience of populations, particularly in the case of key metabolic genes, as variation in these genes has the potential to significantly affect the fitness and chances of survival of the organism (Koshiba et al. 2020; Whitt et al. 2002). By identifying the mechanisms that maintain specific genetic variation, we can better predict which populations might be especially vulnerable to environmental change and develop targeted strategies to conserve biodiversity. Our results suggest that monitoring multiple factors, such as environmental conditions and social structure, may be a key to predicting the fate of many populations under conservation (Parrett and Knell 2018; Peniston et al. 2020). While our study provides knowledge and insight into the system, it is important to recognize and address its limitations. Although populations were maintained at constant census size (N) and sex ratio was controlled, the effective population size (Ne) may have varied between the populations with female-biased and equal sex-ratio. The potential differences in effective population size (Ne) between treatments might slightly influence allele frequency changes, but these effects are expected to be minor. This discrepancy in Ne has been identified and discussed as a potential limitation in previous experimental evolutionary studies that manipulate sex ratio (LaMunyon et al. 2007; Wigby and Chapman 2004). However, experimental evolution studies in other species have suggested that such differences in Ne between experimental populations should not considerably bias the results (Snook et al. 2009; Edward et al. 2010; Rice and Holland 2005). In addition, recent results on R. robini suggest that Ne does not differ significantly between populations with much higher differences in sex ration that the ones used here (Chmielewski et al. unpublished), making our comparison between our experimental populations valid. Furthermore, although our results suggest that the F allele is further stabilized in the long term in the low temperature/high selection intensity treatments, evolutionary timescales are much longer compared to a 13-generation span. Hence, it would be interesting to experimentally assess the stability of these interactions over longer timescales. Finally, although we have gained insight into the maintenance of polymorphism, we have yet to determine the precise advantage gained by individuals with the F allele at lower temperatures and the associated trade-off in this system. Addressing these limitations in future research will enhance our understanding of the intricate interplay between genetic, environmental, and social factors in shaping population dynamics. Overall, our study provides strong evidence for a three-way environment-by-genotype interaction as a mechanism of balancing selection in 6Pgdh in bulb mites. We found that it is the interplay between the abiotic environmental factor (temperature) and the social environment (intensity of sexual selection) that likely drives the maintenance of polymorphism in such a system, although we were unable to detect differences in reproductive fitness between genotypes at different temperatures. The results of this study highlight the importance of taking a comprehensive approach to the study of balancing selection, where we consider the combined effects of different factors. This broader perspective not only deepens our understanding of evolutionary dynamics, but also paves the way for future research into the complex interplay between genotype, environment, and selective pressures. Declarations Acknowledgements We would like to thank Dr. Mateusz Krzysiek for helping us with the irradiation of the mites along with the Institute of Nuclear Physics Polish Academy of Sciences, Krakow for providing with the equipment and space for the procedure. We thank the students Szymon Grzesik and Gabriela Cygnar for helping us during the initial stages of the experiments. We are grateful to Edyta Fiałkowska for providing onions with mites which were used to create the source population. We are also grateful to the Genomics and Experimental Evolution Group members (Jagiellonian University) for their comments and input, especially during the initial planning stage of the study. The study was funded by a grant from Polish National Science Centre grant no UMO-2019/33/B/NZ8/02442 awarded to Agata Plesnar-Bielak. Author contributions PU, APB and WB were involved in the planning and design of the experiments. PU, APB, AS and MT did the lab work. PU analyzed the data. PU, APB and WB wrote the manuscript. All authors read and approved the final draft. Author declarations The authors declare no competing interests. Data archiving The dataset from this study will be uploaded to Dryad repository (yet to be uploaded). References Abdul-Rahman, Farah, Daniel Tranchina, and David Gresham. “Fluctuating Environments Maintain Genetic Diversity through Neutral Fitness Effects and Balancing Selection.” Molecular Biology and Evolution 38, no. 10 (October 1, 2021): 4362–75. https://doi.org/10.1093/molbev/msab173 . Barrett, Rowan D. H., and Dolph Schluter. “Adaptation from Standing Genetic Variation.” Trends in Ecology & Evolution 23, no. 1 (January 1, 2008): 38–44. https://doi.org/10.1016/j.tree.2007.09.008 . Brook, A. H. “Multilevel Complex Interactions between Genetic, Epigenetic and Environmental Factors in the Aetiology of Anomalies of Dental Development.” Archives of Oral Biology , International Workshop on Oral Growth and Development, 54 (December 1, 2009): S3–17. https://doi.org/10.1016/j.archoralbio.2009.09.005 . Bürger, Reinhard, and Michael Lynch. “Evolution and Extinction in a Changing Environment: A Quantitative-Genetic Analysis.” Evolution 49, no. 1 (1995): 151–63. https://doi.org/10.1111/j.1558-5646.1995.tb05967.x . Carley, Lauren N., Julius P. Mojica, Baosheng Wang, Chia-Yu Chen, Ya-Ping Lin, Kasavajhala V. S. K. Prasad, Emily Chan, et al. “Ecological Factors Influence Balancing Selection on Leaf Chemical Profiles of a Wildflower.” Nature Ecology & Evolution 5, no. 8 (August 2021): 1135–44. https://doi.org/10.1038/s41559-021-01486-0 . Charlesworth, Deborah. “Balancing Selection and Its Effects on Sequences in Nearby Genome Regions.” PLoS Genetics 2, no. 4 (April 28, 2006): e64. https://doi.org/10.1371/journal.pgen.0020064 . Connallon, Tim, and Andrew G. Clark. “ANTAGONISTIC VERSUS NONANTAGONISTIC MODELS OF BALANCING SELECTION: CHARACTERIZING THE RELATIVE TIMESCALES AND HITCHHIKING EFFECTS OF PARTIAL SELECTIVE SWEEPS.” Evolution 67, no. 3 (March 1, 2013): 908–17. https://doi.org/10.1111/j.1558-5646.2012.01800.x . Dongen, Jenny van, Michel G. Nivard, Gonneke Willemsen, Jouke-Jan Hottenga, Quinta Helmer, Conor V. Dolan, Erik A. Ehli, et al. “Genetic and Environmental Influences Interact with Age and Sex in Shaping the Human Methylome.” Nature Communications 7, no. 1 (April 7, 2016): 11115. https://doi.org/10.1038/ncomms11115 . Edward, Dominic A., Claudia Fricke, and Tracey Chapman. “Adaptations to Sexual Selection and Sexual Conflict: Insights from Experimental Evolution and Artificial Selection.” Philosophical Transactions of the Royal Society B: Biological Sciences 365, no. 1552 (August 27, 2010): 2541–48. https://doi.org/10.1098/rstb.2010.0027 . Endler, John A. Natural Selection in the Wild . Princeton University Press, 1986. Ferrer-Admetlla, Anna, Elena Bosch, Martin Sikora, Tomàs Marquès-Bonet, Anna Ramírez-Soriano, Aura Muntasell, Arcadi Navarro, et al. “Balancing Selection Is the Main Force Shaping the Evolution of Innate Immunity Genes1.” The Journal of Immunology 181, no. 2 (July 15, 2008): 1315–22. https://doi.org/10.4049/jimmunol.181.2.1315 . Fijarczyk, Anna, and Wiesław Babik. “Detecting Balancing Selection in Genomes: Limits and Prospects.” Molecular Ecology 24, no. 14 (2015): 3529–45. https://doi.org/10.1111/mec.13226 . Fisher, R. A. “Average Excess and Average Effect of a Gene Substitution.” Annals of Eugenics 11, no. 1 (1941): 53–63. https://doi.org/10.1111/j.1469-1809.1941.tb02272.x . Fitzpatrick, Mark J., Elah Feder, Locke Rowe, and Marla B. Sokolowski. “Maintaining a Behaviour Polymorphism by Frequency-Dependent Selection on a Single Gene.” Nature 447, no. 7141 (May 2007): 210–12. https://doi.org/10.1038/nature05764 . Fricke, Claudia, and Göran Arnqvist. “RAPID ADAPTATION TO A NOVEL HOST IN A SEED BEETLE (CALLOSOBRUCHUS MACULATUS): THE ROLE OF SEXUAL SELECTION.” Evolution 61, no. 2 (February 1, 2007): 440–54. https://doi.org/10.1111/j.1558-5646.2007.00038.x . Gillespie, J H, and M Turelli. “Genotype-Environment Interactions and the Maintenance of Polygenic Variation.” Genetics 121, no. 1 (January 1, 1989): 129–38. https://doi.org/10.1093/genetics/121.1.129 . Greenfield, Michael, and Rafael Rodríguez. “Genotype–Environment Interactions and the Reliability of Mate Signals.” Animal Behaviour 68 (December 1, 2004): 1461–68. https://doi.org/10.1016/j.anbehav.2004.01.014 . Hallsson, L. R., and M. Björklund. “Selection in a Fluctuating Environment Leads to Decreased Genetic Variation and Facilitates the Evolution of Phenotypic Plasticity.” Journal of Evolutionary Biology 25, no. 7 (July 2012): 1275–90. https://doi.org/10.1111/j.1420-9101.2012.02512.x . Hedrick, Philip W., Michael E. Ginevan, and Evelyn P. Ewing. “Genetic Polymorphism in Heterogeneous Environments.” Annual Review of Ecology and Systematics 7, no. 1 (November 1976): 1–32. https://doi.org/10.1146/annurev.es.07.110176.000245 . Hoffmann, Ary A., Carla M. Sgrò, and Torsten N. Kristensen. “Revisiting Adaptive Potential, Population Size, and Conservation.” Trends in Ecology & Evolution 32, no. 7 (July 2017): 506–17. https://doi.org/10.1016/j.tree.2017.03.012 . Huang, Guilian, Wei Wu, Yongmei Chen, Xueke Zhi, Peishan Zou, Zulin Ning, Qiang Fan, et al. “Balancing Selection on an MYB Transcription Factor Maintains the Twig Trichome Color Variation in Melastoma Normale.” BMC Biology 21, no. 1 (May 24, 2023): 122. https://doi.org/10.1186/s12915-023-01611-4 . Ingleby, F. C., J. Hunt, and D. J. Hosken. “The Role of Genotype‐by‐environment Interactions in Sexual Selection.” Journal of Evolutionary Biology 23, no. 10 (October 1, 2010): 2031–45. https://doi.org/10.1111/j.1420-9101.2010.02080.x . Joswig, Julia S., Christian Wirth, Meredith C. Schuman, Jens Kattge, Björn Reu, Ian J. Wright, Sebastian D. Sippel, et al. “Climatic and Soil Factors Explain the Two-Dimensional Spectrum of Global Plant Trait Variation | Nature Ecology & Evolution.” Nature Ecology & Evolution 6, no. 1 (January 2022): 36–50. https://doi.org/10.1038/s41559-021-01616-8 . Kokko, Hanna, and Katja Heubel. “Condition-Dependence, Genotype-by-Environment Interactions and the Lek Paradox.” Genetica 134, no. 1 (September 1, 2008): 55–62. https://doi.org/10.1007/s10709-008-9249-7 . Konior, Magdalena, Jacek Radwan, Maria Kołodziejczyk, and Laurent Keller. “Strong Association between a Single Gene and Fertilization Efficiency of Males and Fecundity of Their Mates in the Bulb Mite.” Proceedings of the Royal Society B: Biological Sciences 273, no. 1584 (February 7, 2006): 309–14. https://doi.org/10.1098/rspb.2005.3302 . Koshiba, Seizo, Ikuko N. Motoike, Daisuke Saigusa, Jin Inoue, Yuichi Aoki, Shu Tadaka, Matsuyuki Shirota, et al. “Identification of Critical Genetic Variants Associated with Metabolic Phenotypes of the Japanese Population.” Communications Biology 3, no. 1 (November 11, 2020): 662. https://doi.org/10.1038/s42003-020-01383-5 . LaMunyon, Craig W., Oussama Bouban, and Asher D. Cutter. “Postcopulatory Sexual Selection Reduces Genetic Diversity in Experimental Populations of Caenorhabditis Elegans.” Journal of Heredity 98, no. 1 (January 1, 2007): 67–72. https://doi.org/10.1093/jhered/esl052 . Levins, Richard. Evolution in Changing Environments: Some Theoretical Explorations . Princeton University Press, 1968. Lewontin, Richard C. The Genetic Basis of Evolutionary Change . Vol. 560. Columbia University Press New York, 1974. https://authors.library.caltech.edu/5456/01/hrst.mit.edu/hrs/evolution/public/papers/lewontin1974/lewontin1974_chap1andfront.pdf . Lonn, Eija, Esa Koskela, Tapio Mappes, Mikael Mokkonen, Angela M. Sims, and Phillip C. Watts. “Balancing Selection Maintains Polymorphisms at Neurogenetic Loci in Field Experiments.” Proceedings of the National Academy of Sciences 114, no. 14 (April 4, 2017): 3690–95. https://doi.org/10.1073/pnas.1621228114 . Łukasik, Piotr, Małgorzata Zygadło, and Jacek Radwan. “The Effect of a Phosphogluconate Dehydrogenase Genotype on Sperm Competitiveness in the Bulb Mite,Rhizoglyphus Robini.” In Trends in Acarology , edited by Maurice W. Sabelis and Jan Bruin, 295–97. Dordrecht: Springer Netherlands, 2010. https://doi.org/10.1007/978-90-481-9837-5_47 . Magris, Martina, Anne E. Wignall, and Marie E. Herberstein. “The Sterile Male Technique: Irradiation Negatively Affects Male Fertility but Not Male Courtship.” Journal of Insect Physiology 75 (April 1, 2015): 85–90. https://doi.org/10.1016/j.jinsphys.2015.02.014 . Manjurano, Alphaxard, Nuno Sepulveda, Behzad Nadjm, George Mtove, Hannah Wangai, Caroline Maxwell, Raimos Olomi, et al. “African Glucose-6-Phosphate Dehydrogenase Alleles Associated with Protection from Severe Malaria in Heterozygous Females in Tanzania.” PLoS Genetics 11, no. 2 (February 2015): e1004960. https://doi.org/10.1371/journal.pgen.1004960 . Mazza, Giuseppe, Alberto Francesco Inghilesi, Gianluca Stasolla, Alessandro Cini, Rita Cervo, Claudia Benvenuti, Valeria Francardi, Massimo Cristofaro, Silvia Arnone, and Pio Federico Roversi. “Sterile Rhynchophorus Ferrugineus Males Efficiently Impair Reproduction While Maintaining Their Sexual Competitiveness in a Social Context.” Journal of Pest Science 89, no. 2 (December 7, 2015): 459–68. https://doi.org/10.1007/s10340-015-0709-4 . Muirhead, Christina A. “CONSEQUENCES OF POPULATION STRUCTURE ON GENES UNDER BALANCING SELECTION.” Evolution 55, no. 8 (August 1, 2001): 1532–41. https://doi.org/10.1111/j.0014-3820.2001.tb00673.x . Nuzhdin, Sergey V., Elena G. Pasyukova, Christy L. Dilda, Zhao-Bang Zeng, and Trudy F. C. Mackay. “Sex-Specific Quantitative Trait Loci Affecting Longevity in Drosophila Melanogaster.” Proceedings of the National Academy of Sciences 94, no. 18 (September 2, 1997): 9734–39. https://doi.org/10.1073/pnas.94.18.9734 . Parker, G. A. “Sperm Competition and Its Evolutionary Effect on Copula Duration in the Fly Scatophaga Stercoraria .” Journal of Insect Physiology 16, no. 7 (July 1, 1970): 1301–28. https://doi.org/10.1016/0022-1910(70)90131-9 . Parrett, Jonathan M., and Robert J. Knell. “The Effect of Sexual Selection on Adaptation and Extinction under Increasing Temperatures.” Proceedings of the Royal Society B: Biological Sciences 285, no. 1877 (April 18, 2018): 20180303. https://doi.org/10.1098/rspb.2018.0303 . Patlar, Bahar, and Steven A. Ramm. “Genotype‐by‐environment Interactions for Seminal Fluid Expression and Sperm Competitive Ability.” Journal of Evolutionary Biology 33, no. 2 (February 1, 2020): 225–36. https://doi.org/10.1111/jeb.13568 . Pemberton, J. M., S. D. Albon, F. E. Guinness, and T. H. Clutton‐Brock. “COUNTERVAILING SELECTION IN DIFFERENT FITNESS COMPONENTS IN FEMALE RED DEER.” Evolution 45, no. 1 (February 1, 1991): 93–103. https://doi.org/10.1111/j.1558-5646.1991.tb05269.x . Peniston, James H., Michael Barfield, Andrew Gonzalez, and Robert D. Holt. “Environmental Fluctuations Can Promote Evolutionary Rescue in High-Extinction-Risk Scenarios.” Proceedings of the Royal Society B: Biological Sciences 287, no. 1932 (August 5, 2020): 20201144. https://doi.org/10.1098/rspb.2020.1144 . Plesnar-Bielak, Agata, Anna M. Skwierzyńska, and Jacek Radwan. “Sexual and Ecological Selection on a Sexual Conflict Gene.” Journal of Evolutionary Biology 33, no. 10 (2020): 1433–39. https://doi.org/10.1111/jeb.13680 . Plesnar-Bielak, Agata, Anna Maria Skwierzyńska, Kasper Hlebowicz, and Jacek Radwan. “Relative Costs and Benefits of Alternative Reproductive Phenotypes at Different Temperatures – Genotype-by-Environment Interactions in a Sexually Selected Trait.” BMC Evolutionary Biology 18, no. 1 (July 11, 2018): 1–10. https://doi.org/10.1186/s12862-018-1226-x . Radwan, Jacek. “Sperm Competition in the Mite Caloglyphus Berlesei.” Behavioral Ecology and Sociobiology 29, no. 4 (November 1991): 291–96. https://doi.org/10.1007/BF00163987 . Radwan, Jacek, Leif Engqvist, and Klaus Reinhold. “A Paradox of Genetic Variance in Epigamic Traits: Beyond ‘Good Genes’ View of Sexual Selection.” Evolutionary Biology 43, no. 2 (June 2016): 267–75. https://doi.org/10.1007/s11692-015-9359-y . Radwan, Jacek, and Michael T. Siva-Jothy. “The Function of Post-Insemination Mate Association in the Bulb Mite,Rhizoglyphus Robini.” Animal Behaviour 52, no. 4 (October 1996): 651–57. https://doi.org/10.1006/anbe.1996.0209 . Rice, William R., and Brett Holland. “Experimentally Enforced Monogamy: Inadvertent Selection, Inbreeding, or Evidence for Sexually Antagonistic Coevolution?” Evolution 59, no. 3 (2005): 682–85. https://doi.org/10.1111/j.0014-3820.2005.tb01026.x . Rundle, Howard D., Stephen F. Chenoweth, and Mark W. Blows. “THE ROLES OF NATURAL AND SEXUAL SELECTION DURING ADAPTATION TO A NOVEL ENVIRONMENT.” Evolution 60, no. 11 (2006): 2218. https://doi.org/10.1554/06-249.1 . Schoepf, Ivana, and Neville Pillay. “Multiple Interacting Factors Affect Seed Predation in an African Savanna Small Mammal Community.” Journal of Mammalogy 104, no. 3 (June 1, 2023): 446–56. https://doi.org/10.1093/jmammal/gyac127 . Sirot, Laura K., H. Jane Brockmann, and Stephen L. Lapointe. “Male Postcopulatory Reproductive Success in the Beetle, Diaprepes Abbreviatus .” Animal Behaviour 74, no. 1 (July 1, 2007): 143–52. https://doi.org/10.1016/j.anbehav.2006.12.004 . Skwierzyńska, Anna M., and Agata Plesnar-Bielak. “Proximate Mechanisms of the Differences in Reproductive Success of Males Bearing Different Alleles of Pgdh – a Gene Involved in a Sexual Conflict in Bulb Mite.” Journal of Evolutionary Biology 31, no. 5 (2018): 657–64. https://doi.org/10.1111/jeb.13250 . Slatkin, Montgomery. “Gene Flow and the Geographic Structure of Natural Populations.” Science 236, no. 4803 (May 15, 1987): 787–92. https://doi.org/10.1126/science.3576198 . Smith, Andrew H., Michael P. O’Connor, Brooke Deal, Coleman Kotzer, Amanda Lee, Barrett Wagner, Jonah Joffe, Stephen Woloszynek, Kerry M. Oliver, and Jacob A. Russell. “Does Getting Defensive Get You Anywhere?—Seasonal Balancing Selection, Temperature, and Parasitoids Shape Real-World, Protective Endosymbiont Dynamics in the Pea Aphid.” Molecular Ecology 30, no. 10 (2021): 2449–72. https://doi.org/10.1111/mec.15906 . Snook, Rhonda R., Lena Brüstle, and Jon Slate. “A TEST AND REVIEW OF THE ROLE OF EFFECTIVE POPULATION SIZE ON EXPERIMENTAL SEXUAL SELECTION PATTERNS.” Evolution 63, no. 7 (July 1, 2009): 1923–33. https://doi.org/10.1111/j.1558-5646.2009.00682.x . Stamp, Megan A., and Jarrod D. Hadfield. “The Relative Importance of Plasticity versus Genetic Differentiation in Explaining between Population Differences; a Meta-Analysis.” Ecology Letters 23, no. 10 (2020): 1432–41. https://doi.org/10.1111/ele.13565 . Stincone, Anna, Alessandro Prigione, Thorsten Cramer, Mirjam M. C. Wamelink, Kate Campbell, Eric Cheung, Viridiana Olin-Sandoval, et al. “The Return of Metabolism: Biochemistry and Physiology of the Pentose Phosphate Pathway.” Biological Reviews 90, no. 3 (2015): 927–63. https://doi.org/10.1111/brv.12140 . Unnikrishnan, Pranav, Szymon Grzesik, Magdalena Trojańska, Beata Klimek, and Agata Plesnar-Bielak. “6Pgdh Polymorphism in Wild Bulb Mite Populations: Prevalence, Environmental Correlates and Life History Trade-Offs.” Experimental and Applied Acarology , April 10, 2024. https://doi.org/10.1007/s10493-024-00909-4 . Van den Bergh, Bram, Toon Swings, Maarten Fauvart, and Jan Michiels. “Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution.” Microbiology and Molecular Biology Reviews 82, no. 3 (July 25, 2018): 10.1128/mmbr.00008-18. https://doi.org/10.1128/mmbr.00008-18 . Via, Sara, and Russell Lande. “Evolution of Genetic Variability in a Spatially Heterogeneous Environment: Effects of Genotype–Environment Interaction.” Genetics Research 49, no. 2 (April 1987): 147–56. https://doi.org/10.1017/S001667230002694X . Whitt, Sherry R., Larissa M. Wilson, Maud I. Tenaillon, Brandon S. Gaut, and Edward S. Buckler. “Genetic Diversity and Selection in the Maize Starch Pathway.” Proceedings of the National Academy of Sciences 99, no. 20 (October 2002): 12959–62. https://doi.org/10.1073/pnas.202476999 . Wigby, Stuart, and Tracey Chapman. “Female Resistance to Male Harm Evolves in Response to Manipulation of Sexual Conflict.” Evolution 58, no. 5 (2004): 1028–37. https://doi.org/10.1111/j.0014-3820.2004.tb00436.x . Wright, Sewall. “The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution,” 1932. http://www.esp.org/books/6th-congress/facsimile/contents/6th-cong-p356-wright.pdf . Zan, Yanjun, and Örjan Carlborg. “Dynamic Genetic Architecture of Yeast Response to Environmental Perturbation Shed Light on Origin of Cryptic Genetic Variation.” Accessed July 18, 2024. https://doi.org/10.1371/journal.pgen.1008801 . 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-4835969","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":345970067,"identity":"30d446f0-68cd-43aa-a813-eeee7613a296","order_by":0,"name":"Pranav Unnikrishnan","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA00lEQVRIiWNgGAWjYBADHnn2BiBlYEG8FhnDngMgLRLEa7FhuJEAoonQYnC79+HngprDPIwzn1/d8KNAgoG/vTsBv5Y7x42lZxw7zMMunVN2swfoMIkzZzfg13IjjUGahy2Nh3F2TtoNHqAWA4lcglqYf/P8S+NhuHkm7eYfIrWwSfO22fAw3GA/dpsoWyTvHGOz5u2z4THsyWG7LWMgwUPQL3y325hv83yTsJdnP/7s5ps/NnL87b34tSBFBI8BmMSvHFUL+wPCqkfBKBgFo2BEAgAT7kK6mir9ZwAAAABJRU5ErkJggg==","orcid":"https://orcid.org/0009-0003-8532-6324","institution":"Jagiellonian University","correspondingAuthor":true,"prefix":"","firstName":"Pranav","middleName":"","lastName":"Unnikrishnan","suffix":""},{"id":345970068,"identity":"ac7fe681-f96c-4070-b1c1-2ecda99ad639","order_by":1,"name":"Anna Spaeth","email":"","orcid":"","institution":"Jagiellonian University","correspondingAuthor":false,"prefix":"","firstName":"Anna","middleName":"","lastName":"Spaeth","suffix":""},{"id":345970069,"identity":"9e4c5ace-392e-4df0-a5a0-f86bed7b1d75","order_by":2,"name":"Magdalena Trojańska","email":"","orcid":"","institution":"University of Veterinary Medicine","correspondingAuthor":false,"prefix":"","firstName":"Magdalena","middleName":"","lastName":"Trojańska","suffix":""},{"id":345970070,"identity":"893d2b84-4a1d-432a-a43a-cfc72e9614e7","order_by":3,"name":"Wieslaw Babik","email":"","orcid":"","institution":"Uniwersytetu Jagiellońskiego","correspondingAuthor":false,"prefix":"","firstName":"Wieslaw","middleName":"","lastName":"Babik","suffix":""},{"id":345970071,"identity":"20a9dc1c-8269-4a70-8ed8-4764001a15f9","order_by":4,"name":"Agata Plesnar-Bielak","email":"","orcid":"https://orcid.org/0000-0002-7806-8908","institution":"Jagiellonian University","correspondingAuthor":false,"prefix":"","firstName":"Agata","middleName":"","lastName":"Plesnar-Bielak","suffix":""}],"badges":[],"createdAt":"2024-07-31 13:35:50","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-4835969/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-4835969/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":64937923,"identity":"fcec997d-bdf2-4248-a3fb-7678827cb90a","added_by":"auto","created_at":"2024-09-20 15:05:28","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":837393,"visible":true,"origin":"","legend":"\u003cp\u003eSteps involved in experimental evolution (a) and reproductive success assay (b).\u003c/p\u003e","description":"","filename":"Fig1.png","url":"https://assets-eu.researchsquare.com/files/rs-4835969/v1/5461da8ed157df0f124e4838.png"},{"id":64937920,"identity":"08725def-a32c-4a67-9710-59a88bcaedc6","added_by":"auto","created_at":"2024-09-20 15:05:28","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":9783,"visible":true,"origin":"","legend":"\u003cp\u003eEvolution of F-allele frequency of the populations over 13 generations. The colours represent the different sex-ratio levels (equal vs female-biased) corresponding to the difference in sexual selection intensity (strong vs weak). The boxplots show the IQL of F-allele frequencies of each treatment group in that generation with the center line representing the median.\u003c/p\u003e","description":"","filename":"Fig2.png","url":"https://assets-eu.researchsquare.com/files/rs-4835969/v1/79f35c5282382b3023995621.png"},{"id":64938678,"identity":"4a54f0c9-5902-4de4-9bb4-0d81215e82f9","added_by":"auto","created_at":"2024-09-20 15:13:28","extension":"png","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":16376,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of generation 0 and generation 13 of each treatment. Only the populations from the treatment with equal sex-ratio (strong sexual selection) and 12 °C (lower temperature) show an increase in F-allele frequency. Each point represents the F-allele frequency of an individual population, and the lines connect the same replicate populations.\u003c/p\u003e","description":"","filename":"Fig3.png","url":"https://assets-eu.researchsquare.com/files/rs-4835969/v1/2a11c377d275a8fb9af0ef87.png"},{"id":64937924,"identity":"7d8f3427-053b-4e13-8782-26845b6f97e8","added_by":"auto","created_at":"2024-09-20 15:05:28","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":13748,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of reproductive success of different genotypes in different temperatures, the y-axis shows the fractions of eggs that hatched which is the representation of the level of reproductive success. The boxplots represent the IQL of the fraction of eggs hatched (reproductive success) with the center line being the median, and the points represent the success of individual males. The two different blocks are represented by the shape and colour of the individual points.\u003c/p\u003e","description":"","filename":"Fig4.png","url":"https://assets-eu.researchsquare.com/files/rs-4835969/v1/831d04503640c62b28b3b5cb.png"},{"id":69475782,"identity":"eef1ad7a-e8b3-48b6-b0d2-a36b053310ca","added_by":"auto","created_at":"2024-11-20 19:23:26","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1198677,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-4835969/v1/36a44cdf-4048-4210-bf06-0d5e30a65bcc.pdf"}],"financialInterests":"There is no duality of interest","formattedTitle":"The interplay of environmental and social factors influences balancing selection: 6Pgdh in bulb mites","fulltext":[{"header":"Introduction","content":"\u003cp\u003eGenetic variation, which can be considered the fundamental raw material for natural selection, is a crucial factor for evolutionary processes to manifest. An increase in genetic variation within a population increases the potential for evolutionary change, as postulated by Fisher, \u0026ldquo;the rate of increase in the average fitness of a population is equal to the genetic variance of fitness of that population\u0026rdquo; (Fisher 1941). Such genetic variation, which results in diverse phenotypes, allows populations to adapt to environmental challenges (Barrett and Schluter 2008). Nevertheless, directional selection tends to diminish genetic variation by selecting for particular variants, thereby increasing their frequency within a population (B\u0026uuml;rger and Lynch 1995). This often results in the eventual fixation of the favoured variant (Wright 1932; Endler 1986). Therefore, the persistence of genetic polymorphism, despite the expectation of decreased variation under directional selection, presents a paradox (Lewontin 1974; Radwan et al. 2016; Hallsson and Bj\u0026ouml;rklund 2012).\u003c/p\u003e\n\u003cp\u003eSelection processes that result in the maintenance of polymorphisms fall under a common umbrella term, balancing selection. However, a number of different mechanisms of balancing selection have been proposed and their relative importance is still under debate (Stamp and Hadfield 2020; Fijarczyk and Babik 2015). In some populations, heterozygote advantage can be observed, as in the case of the X-linked glucose-6-phosphate dehydrogenase gene in humans, where heterozygous individuals are protected from severe malaria (Manjurano et al. 2015). This increases the survival and reproductive success of heterozygous individuals, ensuring that both alleles remain present in the population (Manjurano et al. 2015). The maintenance of polymorphism can also be attributed to negative frequency-dependent selection, in which fitness of alleles changes depending on their frequency, with rare variants having an advantage over more common ones. Fitzpatrick et al (2007) demonstrated this mechanism for \u003cem\u003eDrosophila melanogaster\u0026nbsp;\u003c/em\u003eforaging (\u003cem\u003efor\u003c/em\u003e) gene, which is responsible for larval foraging behaviour, where the highest fitness always goes to individuals with the rare allele and the polymorphism of the gene is maintained. Antagonistic pleiotropy is another balancing selection mechanism, where the trade-off between different fitness traits leads to the maintenance of polymorphism (Connallon and Clark 2013). For example, in the case of the \u003cem\u003eMpi\u003c/em\u003e and \u003cem\u003eIdh-2\u003c/em\u003e enzyme loci in red deer (\u003cem\u003eCervus elaphus\u003c/em\u003e), each with two different alleles associated with juvenile survival, genotypes associated with low survival in the first two years of development were found to have higher female reproductive fitness, resulting in the maintenance of gene polymorphism (Pemberton et al. 1991). An analogous mechanism is sexually antagonistic pleiotropy, where the trade-off is between the fitness of the sexes. Because trait fitness varies between the sexes, polymorphism is maintained within a population. Nuzhdin et al (1997) showed that the genes within five autosomal quantitative trait loci (QTL) associated with lifespan and viability in \u003cem\u003eD. melanogaster\u003c/em\u003e showed strong sex-dependent effects, maintaining genetic variation in lifespan.\u003c/p\u003e\n\u003cp\u003eThe significance of heterogeneous environments in maintaining genetic variation has been well documented (Hedrick et al. 1976; Slatkin 1987), particularly from early theoretical modelling studies (Via and Lande 1987; Gillespie and Turelli 1989; Levins 1968). The phenomenon termed environment-dependent balancing selection occurs when the fitness of alleles depends on the environment (there is a crossover genotype-by-environment interaction for fitness), and environmental factors vary in space or time (Kokko and Heubel 2008). Given the expected variability of the environment, such environment-dependent selection can potentially be a powerful driver of balancing selection. Early studies on this topic used simple models focusing on simple genetic systems, often considering only a single environmental factor and assuming constant selection pressure over time (Levins 1968; Hedrick et al. 1976). These models suggested that the parameter space in which polymorphism could be maintained was relatively narrow, implying that the maintenance of genetic variation required rather specific conditions that may rarely occur in nature. In contrast, more recent studies have adopted more complex and realistic models that consider polygenic traits, multi-allelic genes, and the simultaneous effects of multiple environmental factors (Carley et al. 2021; Abdul Rahman et al. 2021). These newer models consider the dynamic nature of natural environments, where multiple factors can change in unpredictable ways and interact with genetic systems. As a result, these newer studies have shown that the conditions for maintaining polymorphism are less restrictive than previously thought. The broader and more inclusive parameter space found in these models suggests that genetic variation can be maintained under a wider range of environmental conditions, highlighting the importance of considering complex interactions between genetics and environment to reflect the nature of real-world scenarios. The findings of the newer models have been corroborated by empirical studies, thereby demonstrating their robustness (Brook 2009; van Dongen et al. 2016; Zan and Carlborg 2024).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eAs mentioned above, the role of environmental heterogeneity in driving balancing selection in natural systems can be quite complex. The potential of a given environmental factor to shape genotype-by-environment interactions may depend on another environmental variable. For example, several studies have demonstrated genotype-by-environment interactions for sexual fitness, including male reproductive success (Patlar and Ramm 2020; Greenfield and Rodr\u0026iacute;guez 2004; Ingleby et al. 2010). The potential of such interactions to drive selection should vary with conditions that influence the strength of sexual selection, such as population density or sex ratio. Consequently, one might observe a three-way interaction between genotype, abiotic and biotic (social) environment. \u0026nbsp;\u003c/p\u003e\n\u003cp\u003eIn the case of the 6-phosphogluconate dehydrogenase (\u003cem\u003e6Pgdh\u003c/em\u003e) polymorphism in bulb mite \u003cem\u003eRhizoglyphus robini\u003c/em\u003e, a three-way interaction may be expected as the mechanism of polymorphism maintenance, where one of the alleles (the S allele) is associated with increased male reproductive success (Konior 2006; Skwierzyńska and Plesnar-Bielak 2018), which should lead to its rapid fixation and loss of the polymorphism. However, while the alternative F allele is indeed rapidly lost in the laboratory, both alleles are often maintained in natural populations (Unnikrishnnan et al. 2024). A previous experimental evolutionary study showed that the selective advantage of the S allele is reduced (but not lost) in populations evolving at a reduced temperature of 18 \u0026deg;C compared to the standard laboratory temperature of 24 \u0026deg;C (Plesnar-Bielak et al. 2020). Similarly, the study also showed that S allele frequency increased less rapidly in populations where sex ratio manipulation relaxed the intensity of sexual selection (Plesnar-Bielak et al. 2020). It has been speculated that these two factors, if applied simultaneously, could have led to a reversal of fitness rank and a selective advantage for the F allele. In such a case, the interaction of temperature and social environment and their heterogeneity could explain the maintenance of the \u003cem\u003e6Pgdh\u003c/em\u003e polymorphism in the wild.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eHere we use experimental evolution to test how the interaction of temperature and sexual selection intensity shapes \u003cem\u003e6Pgdh\u003c/em\u003e allele frequencies. We track changes in \u003cem\u003e6Pgdh\u003c/em\u003e frequencies in replicate populations for 13 generations under two levels of temperature (18 \u0026deg;C and 12 \u0026deg;C) interacting with two levels of selection intensity (equal sex ratio and female-biased population with relaxed sexual selection). We predict that there is a cost for the S allele at lower temperature. If this cost is associated with life history fitness (as opposed to reproductive fitness), we predict an increase in F-allele frequency under lower temperature and relaxed sexual selection. This is because under weak sexual selection intensity, the reproductive advantage of the S-allele should be negligible, hence it may be outweighed by the life history cost of the S-allele at lower temperature. Alternatively, if the cost is associated with reproductive fitness, the reproductive advantage of the S allele itself might be temperature dependent. Under such a scenario, the F allele might gain reproductive advantage at low temperature, and we would expect an increase in its frequency under low temperature and intense sexual selection.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003e\u003cstrong\u003eStudy system\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e6-Phosphogluconate dehydrogenase (\u003cem\u003e6Pgdh\u003c/em\u003e) plays a pivotal role in the pentose phosphate pathway, which, in conjunction with glycolysis, represents a major glucose catabolism pathway. The pentose phosphate pathway generates ribose-5-phosphate sugars and NADPH molecules. The pathway exerts a significant influence on redox homeostasis and the biosynthesis of ribonucleotides and represents a principal source of NADPH (Stincone et al. 2015).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eA single nonsynonymous nucleotide polymorphism in \u003cem\u003e6Pgdh\u003c/em\u003e is associated with male-fitness differences in bulb mites, representing a case of sexual selection. The two alleles of \u003cem\u003e6Pgdh\u003c/em\u003e, designated S and F, differ in one amino acid substitution (arginine to methionine). Under standard laboratory conditions, males carrying the S allele exhibit increased reproductive fitness, as evidenced by higher mating frequency and sperm production (Skwierzyńska and Plesnar-Bielak 2018) compared to F-bearing males. Heterozygotes appear to exhibit an intermediate phenotype (Łukasik et al. 2010; Skwierzyńska and Plesnar-Bielak 2018). The \u003cem\u003e6Pgdh\u003c/em\u003e genotype does not appear to affect female reproductive fitness. However, females mated with SS males exhibit a decreased fitness compared to those mated with FF males, indicating the presence of sexual conflict. Once more, mating with heterozygous males result in an intermediate level of fitness reduction (Skwierzyńska and Plesnar-Bielak 2018). As predicted, given its advantage in male-male competition, the S-allele rapidly fixes in laboratory populations. However, \u003cem\u003e6Pgdh\u003c/em\u003e-polymorphic populations are common in natural populations, with the level of polymorphism varying across locations and through time (Unnikrishnan et al. 2024).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSource population\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExperimental evolution populations were established from a \u003cem\u003e6Pgdh\u003c/em\u003e polymorphic population (source population), in which the frequency of the F allele had been increased before the start of the experiment. It was done in order to start experimental evolution from approximately equal frequencies of both alleles. To do it, we used a field collected population originating from \u0026gt;100 individuals found on onions collected in Łazany (50.0206 N, 19.8924 E), near Krak\u0026oacute;w in July 2020. This field collected population was kept at 8 \u0026deg;C, except for the first week after establishment, when they were kept at 24 \u0026deg;C to let juvenile individuals develop so that the population would expand.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe source population was created in spring 2021. We randomly paired virgin females and males from the field-collected population, in which the F allele frequency was about 0.23. After the pairs mated (almost 300 pairs) and females laid eggs, both parents were genotyped. We then looked for pairs with at least 2 copies of the F allele (either both parents FS, or one FF and one SS, or one FF and one SF, or both parents FF). The offspring from such pairs were used to establish the source population. The population was allowed to expand freely for ca. 2 months at 24 \u0026deg;C (which corresponds to 3-4 mite generations), before it was moved to 12 \u0026deg;C to extend generation time, to prevent adaptation to 24 \u0026deg;C and the loss of the F allele. This population was used to start the experimental evolution populations within one month after transferring to 12 \u0026deg;C (less than one mite generation at that temperature). The F-allele frequency in the source population was 0.6 when the experimental evolution started.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eCulturing conditions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll populations (source and experimental) were maintained in plastic containers (approximately 2.5 cm in diameter) with a plaster of Paris base soaked with water. They were maintained at \u0026gt;90% humidity, constant darkness, with powdered yeast provided \u003cem\u003ead libitum\u003c/em\u003e as a food source. Individually isolated mites were maintained in glass tubes with diameter of approximately 1 cm.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eExperimental evolution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eExperimental evolution was carried out with two levels of temperature (18 \u0026deg;C and 12 \u0026deg;C) crossed with two levels of sexual selection intensity achieved by manipulating the sex ratio (equal sex-ratio and female biased sex-ratio treatments with strong and weak sexual selection intensity respectively). The lowest temperature employed in the preceding study (Plesnar-Bielak et al. 2020) was selected as the high temperature level of 18\u0026deg;C, whereas the lower temperature level of 12 \u0026deg;C is pertinent to the average annual temperature in Poland. In order to achieve a weaker selection intensity, the proportion of males in the weak sexual selection intensity level was reduced to 0.2, in comparison to the previous study where this proportion was 0.3 (Plesnar-Bielak et al. 2020). Five replicate populations were used for each treatment, resulting in a total of 20 populations.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;For each generation, individuals were isolated at the final nymphal stage (tritonymphs) into separate vials. The individuals were then allowed to develop individually into adults and were sexed (still in individual vials). These virgin mites were then put in common containers (one container per replicate) controlling for the sex ratio (64 females + 16 males in female-biased populations and 40 females + 40 males in equal sex-ratio populations) and allowed to interact for 6 days, during which the mites could mate freely, and females could lay eggs. After this time, adult individuals were removed, and eggs were left for further development. Allele frequencies of \u003cem\u003e6Pgdh\u003c/em\u003e were measured from a random sample of around 40 individuals from every two consecutive generations followed by a five-generation break (Fig 1a).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReproductive success\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe measured the success of the males with \u003cem\u003e6Pgdh\u003c/em\u003e different genotypes in reproductive competition with SS-homozygous males from the stock laboratory population. The reproductive success was assessed using the sterile male technique, a well-established method in bulb mite research (Parker 1970; Radwan 1991; Radwan and Siva-Jothy 1996). This technique involves using an experimental male and a tester male and allowing them to compete for the female. The tester males are irradiated with 20 kRad (200 Gy) of gamma radiation from Co\u003csup\u003e60\u003c/sup\u003e. Following irradiation with such a dose, males are still able to fertilize eggs, but the eggs do not hatch (Radwan and Siva-Jothy 1996). Therefore, since bulb mite females do not lay unfertilized eggs, an experimental male\u0026rsquo;s reproductive success can be calculated as a fraction of the eggs that hatched. The fraction of eggs that are fertilized by normal, non-irradiated males and still do not hatch is negligible. The experimental males were taken from three populations that had evolved under 12 \u0026deg;C and equal sex-ratio, since that particular treatment showed F-allele frequency increase. Only three populations from this treatment were included because of logistic constraints, and these were chosen because they had the highest F-frequency within the treatment. The females and tester males originated from the base population maintained under 24 \u0026deg;C, since this population is fixed for S allele.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eFirstly, 50 females were randomly selected from both the experimental and tester populations and kept in separate containers for one week to lay eggs at 12 \u0026deg;C. After this period, the females were removed and the containers with the eggs were transferred to the respective temperatures. The experiment was conducted at three temperatures: 24 \u0026deg;C (standard laboratory temperature), 12 \u0026deg;C (average yearly ground temperature at 5 cm depth in Poland) and 8 \u0026deg;C (low temperature relevant to colder periods in Poland). When the eggs hatched and the individuals reached the tritonymph stage, approximately 600 tritonymphs from the control population were isolated in individual vials in order to obtain virgin females for the experiment. Following the emergence of the adults in the populations, the experimental and tester (irradiated) males were isolated for a period of three days prior to the commencement of the experiment. The tester males were provided with food containing blue dye, which enabled the distinction between experimental and tester males. The experimental setup comprised one experimental male, one tester male (identifiable due to the blue dye) and the virgin female from the base population. After three days, the tester males were removed, and the experimental males were genotyped. The females were kept for two more days (or four days when there were insufficient number of eggs) and then removed. From each vial, 10 to 20 eggs (depending on the number of eggs available) were then transferred to a different vial as a sample, and the fraction of the eggs hatched was recorded and used for analysis. The experiment was conducted in two separate blocks, each containing experimental males from all three populations, with the populations that were the source for the experimental males differing by two generations between the two blocks (Fig 1b).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eDNA extraction and 6Pgdh genotyping\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eFor DNA extraction, individual mites were placed in 1% chelex solution (40\u0026mu;l) and were crushed. After adding 3\u0026mu;l of proteinase-K (EurX, Poland), such a mixture was incubated in a thermocycler (Thermofisher Scientific, Poland) (10 min 94\u0026deg;C, 15 min 75\u0026deg;C). Such prepared samples were stored in a fridge (ca. 6\u0026deg;C) until the genotyping assay.\u003c/p\u003e\n\u003cp\u003e\u0026nbsp;\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Real-Time PCR was used for \u003cem\u003e6Pgdh\u003c/em\u003e genotyping. Fluorogenic TaqMan probes (Thermofisher Scientific) specific for the missense single nucleotide polymorphism were used to determine the F and S alleles (see Unnikrishnan et al. 2024). The Bio-Rad CFX96 Real-Time PCR detection system was used for the genotyping. TaqMan Genotyping Master Mix (Thermofisher Scientific) and Custom Genotyping Assay (Thermofisher Scientific) that included allele-specific primers and fluorescent probes were mixed in 10:1 ratio. 5.5\u0026mu;l of such a mix and 4.5\u0026mu;l of chelex with suspended DNA were put in a 96 well plate for genotyping. PCR was performed in 41 cycles (15 sec 95 \u0026deg;C, 1 min 60 \u0026deg;C).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStatistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eTo test how \u003cem\u003e6Pgdh\u003c/em\u003e allele frequencies were changing over generations depending on the selection treatment, we used Generalized Estimating Equations (GEE) approach using the geeglm function (geepack, version 1.3.10). Compared to repeated measures ANOVA, which is usually used to handle generational data, GEE is better suited here because it accommodates various correlation structures and non-Gaussian distributions, providing robust estimates even with complex data. The GEE model here, used a vector containing the S and F alleles counts (per population obtained from each generation tested) as the response variable, with temperature and sexual selection intensity (along with their interaction) as the predictor variables. To incorporate the repeated measure nature of the data in the model, we used population ID as the vector for the clusters (id=Population) and the generation number specifying the order of the repeated measures in each unit (waves=Generation). We used a binomial model with an AR1 (autoregressive) correlation structure.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eWe have also checked for significant increase/decrease in F-allele frequencies within the experimental evolution period. To do it, we calculated differences in F-allele frequencies between generation 13 and generation 0 for each population. For each selection treatment, these differences were compared to 0, using two-tailed one sample t-test (stats package, version 4.3.0).\u003c/p\u003e\n\u003cp\u003eFor the reproductive success data, we used Generalized Linear Mixed-Effects Model (GLMM) using glmmTMB function (glmmTMB, version 1.1.9) with a vector containing the number of eggs that hatched (successes) and the number of unhatched eggs (failures) as the response variable, with temperature and genotype of males (with their interaction) and block id as fixed factors and population id of the experimental males as a random factor. The model was fitted assuming a betabinomial distribution to account for the overdispersion.\u003c/p\u003e\n\u003cp\u003eData visualizations were created using the ggplot2 package in R (ggplot2, version 3.4.4). All statistical analyses were conducted using R version 4.3.0 (2023-04-21 ucrt).\u0026nbsp;\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003e\u003cstrong\u003eExperimental evolution\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe found that sexual selection intensity and temperature affected \u003cem\u003e6Pgdh\u003c/em\u003e allele frequency changes. Notably, the interaction between sexual selection intensity and temperature had a significant effect (GEE, \u0026chi;\u0026sup2; = 4.58, p = 0.03) on the allele frequency of the experimental populations after 13 generations. This indicates that the impact of sexual selection intensity on allele frequency varied with temperature (individual effects: - sexual selection intensity: \u0026chi;\u0026sup2; = 9.56, p = 0.0019; temperature: \u0026chi;\u0026sup2; = 1.51, p = 0.22).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further understand this interaction, we analyzed the effects of sexual selection intensity on allele frequencies at each temperature separately. The results show that sexual selection intensity had a significant effect at 12 \u0026deg;C (\u0026chi;\u0026sup2; = 24.58, p \u0026lt; 0.001) (Fig 2) resulting in an increase in F-allele frequency. This result was confirmed by the t-test, showing an increase in F allele frequency in populations with higher sexual selection intensity at 12 \u0026deg;C (t₄ = 5.06, p = 0.007), but not in populations with lower sexual selection intensity (t₄ = -0.47, p = 0.66). At 18 \u0026deg;C, sexual selection intensity did not significantly affect allele frequencies (\u0026chi;\u0026sup2; = 2.96, p = 0.085), as evidenced by the lack of significant changes in F allele frequency for populations with low sexual selection intensity (t₄ = 1.97, p = 0.12) and those with high sexual selection intensity (t₄ = -0.83, p = 0.45) (Fig 3).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eReproductive success\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe did not find any significant associations between reproductive success of the experimental males and the predictors tested (Fig 4). Specifically, the interaction between temperature and male genotype was not significant (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 2.86, p = 0.58), suggesting that the reproductive success of males with different genotypes did not differ in different temperatures. Neither temperature (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 2.16, p = 0.34) nor male genotype (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 3.60, p = 0.17) were significant individually. The only predictor variable which was significant was block id (\u0026chi;\u003csup\u003e2\u003c/sup\u003e = 6.4323, p = 0.011).\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eTo further investigate the significant effect observed for block id, we tested the model at each of the blocks separately. There were no significant effects for the interaction between temperature and male genotype on the reproductive success at either of the blocks separately (block 1:- temperature X male genotype: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 6.03, p = 0.20; block 2:- temperature X male genotype: \u0026chi;\u003csup\u003e2\u003c/sup\u003e = 4.87, p = 0.30).\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThe process of balancing selection maintains multiple alleles within a population. Several mechanisms have been proposed to explain this phenomenon, including negative frequency-dependent selection, heterozygote advantage, and environment-dependent selection (Charlesworth 2006; Huang et al. 2023). In systems involving environment-dependent balancing selection, there may be cases where interactions between biotic, abiotic and social environments contribute to the maintenance of polymorphism (Hedrick et al. 1976; Ferrer-Admetlla et al. 2008). Such a situation may occur in the bulb mite metabolic gene \u003cem\u003e6Pgdh\u003c/em\u003e. Although males with the S allele show higher reproductive fitness in laboratory populations, polymorphism persists in natural populations (Unnikrishnan et al. 2024). The aim of this study was to investigate whether environmental factors - temperature and intensity of sexual selection - act alone or in combination to drive this balancing selection.\u003c/p\u003e\n\u003cp\u003eThe results of our study provide evidence for the existence of environment-dependent balancing selection on the gene \u003cem\u003e6Pgdh\u003c/em\u003e in bulb mites. In particular, a significant increase in the frequency of the F allele at low temperature and high sexual selection intensity highlights that balancing selection in the bulb mite \u003cem\u003e6Pgdh\u003c/em\u003e gene is driven by a complex interplay between genotype, environmental factors and social dynamics. Furthermore, although there have been several other studies of the factors contributing to balancing selection, many of these have focused on the separate effects of individual factors (Carley et al. 2021; Smith et al. 2021; Lonn et al. 2017). A multifaceted approach to the study of balancing selection has rarely been used. A recent study on seed predation in an African savannah small mammal community system (Schoepf and Pillay 2023) is a notable exception. It shows that multiple factors such as seed size, seed type, predation risk, habitat type, seasonality and their interactions drive seed variation, with the possibility that these factors are likely to be hierarchically ordered. Similarly, a study by Joswig et al (2022) showed how the interaction of climate and soil fertility influences global plant variation. \u0026nbsp;Our study adds to these by highlighting the role of social dynamics in considering such interactions within species.\u003c/p\u003e\n\u003cp\u003eIn particular, our results suggest that at lower temperatures, males carrying the F allele gain an advantage in the competition for mates. The observed increase in F allele frequency under low temperature and intense sexual selection supports the notion that the reproductive advantage of the S allele is not absolute but varies with temperature. However, reproductive advantage of the F allele at low temperature was not confirmed by the reproductive success assay using direct male-male competition at different temperatures. It is possible that the conditions of the experiment were not optimal for the reproductive advantage of the F-males to be expressed. It is possible that the reproductive advantage of the F-males could have been observed under conditions with more competitors or if the duration of the competition had been longer. In addition, the design of the experiment introduces some additional variation due to factors such as differences in egg-laying ability of the females (less than 10 eggs from some females to more than 200 eggs from some females) or due to the non-uniform nature of the irradiation effects on the males. This high level of variation indicates that the current experiment lacks sufficient statistical power to detect moderate but still biologically relevant, differences. On the other hand, this method has been used previously in this (Radwan and Siva-Jothy 1996; Plesnar-Bielak et al. 2018; Skwierzyńska and Plesnar-Bielak 2018) and other systems (Sirot et al. 2007; Mazza et al. 2015; Magris et al; 2015) and allowed the detection of significant results.\u003c/p\u003e\n\u003cp\u003eDifferent factors interacting with each other have been shown to influence adaptation rates, which may be linked to the impact of these factors on genetic variation and polymorphisms in important genes. The importance of considering heterogeneous environments and social structure to study genetic variance in the design and execution of experimental evolution has been recognized and highlighted (Van den Bergh et al. 2018). An experimental evolution study of the bruchid beetle (\u003cem\u003eCallosobruchus maculatus\u003c/em\u003e) investigated the effect of varying natural (food type) and sexual (mating system) selection intensities on the rate of adaptation (Fricke and Arnqvist 2007). The study showed that mating system treatment (social factor) influenced the rate of adaptation, depending on food type (abiotic factor). In \u003cem\u003eDrosophila serrata\u003c/em\u003e, an experimental evolutionary study showed that the effect of natural selection on the rate of adaptation to novel environments was greater in a monogamous mating system (Rundle et al. 2006). A similar result was observed in an experimental evolutionary study of \u003cem\u003eRhizoglyphus robini\u003c/em\u003e, where polygamous populations adapted rapidly to changes in thermal environments, whereas monogamous populations suffered fitness declines and were more likely to go extinct in novel environments (Plesnar-Bielak et al. 2012). These studies, together with our results, emphasize the need to consider methods to incorporate multi-factorial interactions (abiotic, biotic and social factors) in laboratory studies such as experimental evolution in order to obtain meaningful results and ultimately unlock the answers to many evolutionary processes. Furthermore, although such experimental systems and designs could become considerably more complex due to the addition of multiple factors and their interactions, inference could be refined by focusing on individual and key metabolic genes, as demonstrated in our study.\u003c/p\u003e\n\u003cp\u003eBy focusing on a key metabolic gene, the insights gained are fundamental to evolutionary biology, and understanding the mechanisms of balancing selection has practical implications for conservation biology (Hoffman et al. 2017; Muirhead 2001). Maintaining genetic diversity is crucial for the adaptability and resilience of populations, particularly in the case of key metabolic genes, as variation in these genes has the potential to significantly affect the fitness and chances of survival of the organism (Koshiba et al. 2020; Whitt et al. 2002). By identifying the mechanisms that maintain specific genetic variation, we can better predict which populations might be especially vulnerable to environmental change and develop targeted strategies to conserve biodiversity. Our results suggest that monitoring multiple factors, such as environmental conditions and social structure, may be a key to predicting the fate of many populations under conservation (Parrett and Knell 2018; Peniston et al. 2020).\u003c/p\u003e\n\u003cp\u003eWhile our study provides knowledge and insight into the system, it is important to recognize and address its limitations. Although populations were maintained at constant census size (N) and sex ratio was controlled, the effective population size (Ne) may have varied between the populations with female-biased and equal sex-ratio. The potential differences in effective population size (Ne) between treatments might slightly influence allele frequency changes, but these effects are expected to be minor. This discrepancy in Ne has been identified and discussed as a potential limitation in previous experimental evolutionary studies that manipulate sex ratio (LaMunyon et al. 2007; Wigby and Chapman 2004). However, experimental evolution studies in other species have suggested that such differences in Ne between experimental populations should not considerably bias the results (Snook et al. 2009; Edward et al. 2010; Rice and Holland 2005). \u0026nbsp;In addition, recent results on \u003cem\u003eR. robini\u003c/em\u003e suggest that Ne does not differ significantly between populations with much higher differences in sex ration that the ones used here (Chmielewski et al. unpublished), making our comparison between our experimental populations valid. Furthermore, although our results suggest that the F allele is further stabilized in the long term in the low temperature/high selection intensity treatments, evolutionary timescales are much longer compared to a 13-generation span. Hence, it would be interesting to experimentally assess the stability of these interactions over longer timescales. Finally, although we have gained insight into the maintenance of polymorphism, we have yet to determine the precise advantage gained by individuals with the F allele at lower temperatures and the associated trade-off in this system. Addressing these limitations in future research will enhance our understanding of the intricate interplay between genetic, environmental, and social factors in shaping population dynamics.\u003c/p\u003e\n\u003cp\u003eOverall, our study provides strong evidence for a three-way environment-by-genotype interaction as a mechanism of balancing selection in \u003cem\u003e6Pgdh\u003c/em\u003e in bulb mites. We found that it is the interplay between the abiotic environmental factor (temperature) and the social environment (intensity of sexual selection) that likely drives the maintenance of polymorphism in such a system, although we were unable to detect differences in reproductive fitness between genotypes at different temperatures. The results of this study highlight the importance of taking a comprehensive approach to the study of balancing selection, where we consider the combined effects of different factors. This broader perspective not only deepens our understanding of evolutionary dynamics, but also paves the way for future research into the complex interplay between genotype, environment, and selective pressures.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgements\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank Dr. Mateusz Krzysiek for helping us with the irradiation of the mites along with the Institute of Nuclear Physics Polish Academy of Sciences, Krakow for providing with the equipment and space for the procedure. We thank the students Szymon Grzesik and Gabriela Cygnar for helping us during the initial stages of the experiments. We are grateful to Edyta Fiałkowska for providing onions with mites which were used to create the source population. We are also grateful to the Genomics and Experimental Evolution Group members (Jagiellonian University) for their comments and input, especially during the initial planning stage of the study. The study was funded by a grant from Polish National Science Centre grant no UMO-2019/33/B/NZ8/02442 awarded to Agata Plesnar-Bielak.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor contributions\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePU, APB and WB were involved in the planning and design of the experiments. PU, APB, AS and MT did the lab work. PU analyzed the data. PU, APB and WB wrote the manuscript. All authors read and approved the final draft.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthor declarations\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare no competing interests.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData archiving\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe dataset from this study will be uploaded to Dryad repository (yet to be uploaded).\u003c/p\u003e"},{"header":"References","content":"\u003cp\u003eAbdul-Rahman, Farah, Daniel Tranchina, and David Gresham. \u0026ldquo;Fluctuating Environments Maintain Genetic Diversity through Neutral Fitness Effects and Balancing Selection.\u0026rdquo; \u003cem\u003eMolecular Biology and Evolution\u003c/em\u003e 38, no. 10 (October 1, 2021): 4362\u0026ndash;75.\u0026nbsp;\u003ca href=\"https://doi.org/10.1093/molbev/msab173\"\u003ehttps://doi.org/10.1093/molbev/msab173\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eBarrett, Rowan D. H., and Dolph Schluter. \u0026ldquo;Adaptation from Standing Genetic Variation.\u0026rdquo; \u003cem\u003eTrends in Ecology \u0026amp; Evolution\u003c/em\u003e 23, no. 1 (January 1, 2008): 38\u0026ndash;44.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.tree.2007.09.008\"\u003ehttps://doi.org/10.1016/j.tree.2007.09.008\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eBrook, A. H. \u0026ldquo;Multilevel Complex Interactions between Genetic, Epigenetic and Environmental Factors in the Aetiology of Anomalies of Dental Development.\u0026rdquo; \u003cem\u003eArchives of Oral Biology\u003c/em\u003e, International Workshop on Oral Growth and Development, 54 (December 1, 2009): S3\u0026ndash;17.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.archoralbio.2009.09.005\"\u003ehttps://doi.org/10.1016/j.archoralbio.2009.09.005\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eB\u0026uuml;rger, Reinhard, and Michael Lynch. \u0026ldquo;Evolution and Extinction in a Changing Environment: A Quantitative-Genetic Analysis.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 49, no. 1 (1995): 151\u0026ndash;63.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1558-5646.1995.tb05967.x\"\u003ehttps://doi.org/10.1111/j.1558-5646.1995.tb05967.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eCarley, Lauren N., Julius P. Mojica, Baosheng Wang, Chia-Yu Chen, Ya-Ping Lin, Kasavajhala V. S. K. Prasad, Emily Chan, et al. \u0026ldquo;Ecological Factors Influence Balancing Selection on Leaf Chemical Profiles of a Wildflower.\u0026rdquo; \u003cem\u003eNature Ecology \u0026amp; Evolution\u003c/em\u003e 5, no. 8 (August 2021): 1135\u0026ndash;44.\u0026nbsp;\u003ca href=\"https://doi.org/10.1038/s41559-021-01486-0\"\u003ehttps://doi.org/10.1038/s41559-021-01486-0\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eCharlesworth, Deborah. \u0026ldquo;Balancing Selection and Its Effects on Sequences in Nearby Genome Regions.\u0026rdquo; \u003cem\u003ePLoS Genetics\u003c/em\u003e 2, no. 4 (April 28, 2006): e64.\u0026nbsp;\u003ca href=\"https://doi.org/10.1371/journal.pgen.0020064\"\u003ehttps://doi.org/10.1371/journal.pgen.0020064\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eConnallon, Tim, and Andrew G. Clark. \u0026ldquo;ANTAGONISTIC VERSUS NONANTAGONISTIC MODELS OF BALANCING SELECTION: CHARACTERIZING THE RELATIVE TIMESCALES AND HITCHHIKING EFFECTS OF PARTIAL SELECTIVE SWEEPS.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 67, no. 3 (March 1, 2013): 908\u0026ndash;17.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1558-5646.2012.01800.x\"\u003ehttps://doi.org/10.1111/j.1558-5646.2012.01800.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eDongen, Jenny van, Michel G. Nivard, Gonneke Willemsen, Jouke-Jan Hottenga, Quinta Helmer, Conor V. Dolan, Erik A. Ehli, et al. \u0026ldquo;Genetic and Environmental Influences Interact with Age and Sex in Shaping the Human Methylome.\u0026rdquo; \u003cem\u003eNature Communications\u003c/em\u003e 7, no. 1 (April 7, 2016): 11115.\u0026nbsp;\u003ca href=\"https://doi.org/10.1038/ncomms11115\"\u003ehttps://doi.org/10.1038/ncomms11115\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eEdward, Dominic A., Claudia Fricke, and Tracey Chapman. \u0026ldquo;Adaptations to Sexual Selection and Sexual Conflict: Insights from Experimental Evolution and Artificial Selection.\u0026rdquo; \u003cem\u003ePhilosophical Transactions of the Royal Society B: Biological Sciences\u003c/em\u003e 365, no. 1552 (August 27, 2010): 2541\u0026ndash;48.\u0026nbsp;\u003ca href=\"https://doi.org/10.1098/rstb.2010.0027\"\u003ehttps://doi.org/10.1098/rstb.2010.0027\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eEndler, John A. \u003cem\u003eNatural Selection in the Wild\u003c/em\u003e. Princeton University Press, 1986.\u003c/p\u003e\n\u003cp\u003eFerrer-Admetlla, Anna, Elena Bosch, Martin Sikora, Tom\u0026agrave;s Marqu\u0026egrave;s-Bonet, Anna Ram\u0026iacute;rez-Soriano, Aura Muntasell, Arcadi Navarro, et al. \u0026ldquo;Balancing Selection Is the Main Force Shaping the Evolution of Innate Immunity Genes1.\u0026rdquo; \u003cem\u003eThe Journal of Immunology\u003c/em\u003e 181, no. 2 (July 15, 2008): 1315\u0026ndash;22.\u0026nbsp;\u003ca href=\"https://doi.org/10.4049/jimmunol.181.2.1315\"\u003ehttps://doi.org/10.4049/jimmunol.181.2.1315\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eFijarczyk, Anna, and Wiesław Babik.\u0026nbsp;\u0026ldquo;Detecting Balancing Selection in Genomes: Limits and Prospects.\u0026rdquo; \u003cem\u003eMolecular Ecology\u003c/em\u003e 24, no. 14 (2015): 3529\u0026ndash;45.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/mec.13226\"\u003ehttps://doi.org/10.1111/mec.13226\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eFisher, R. A. \u0026ldquo;Average Excess and Average Effect of a Gene Substitution.\u0026rdquo; \u003cem\u003eAnnals of Eugenics\u003c/em\u003e 11, no. 1 (1941): 53\u0026ndash;63.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1469-1809.1941.tb02272.x\"\u003ehttps://doi.org/10.1111/j.1469-1809.1941.tb02272.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eFitzpatrick, Mark J., Elah Feder, Locke Rowe, and Marla B. Sokolowski. \u0026ldquo;Maintaining a Behaviour Polymorphism by Frequency-Dependent Selection on a Single Gene.\u0026rdquo; \u003cem\u003eNature\u003c/em\u003e 447, no. 7141 (May 2007): 210\u0026ndash;12.\u0026nbsp;\u003ca href=\"https://doi.org/10.1038/nature05764\"\u003ehttps://doi.org/10.1038/nature05764\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eFricke, Claudia, and G\u0026ouml;ran Arnqvist. \u0026ldquo;RAPID ADAPTATION TO A NOVEL HOST IN A SEED BEETLE (CALLOSOBRUCHUS MACULATUS): THE ROLE OF SEXUAL SELECTION.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 61, no. 2 (February 1, 2007): 440\u0026ndash;54.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1558-5646.2007.00038.x\"\u003ehttps://doi.org/10.1111/j.1558-5646.2007.00038.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eGillespie, J H, and M Turelli. \u0026ldquo;Genotype-Environment Interactions and the Maintenance of Polygenic Variation.\u0026rdquo; \u003cem\u003eGenetics\u003c/em\u003e 121, no. 1 (January 1, 1989): 129\u0026ndash;38.\u0026nbsp;\u003ca href=\"https://doi.org/10.1093/genetics/121.1.129\"\u003ehttps://doi.org/10.1093/genetics/121.1.129\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eGreenfield, Michael, and Rafael Rodr\u0026iacute;guez. \u0026ldquo;Genotype\u0026ndash;Environment Interactions and the Reliability of Mate Signals.\u0026rdquo; \u003cem\u003eAnimal Behaviour\u003c/em\u003e 68 (December 1, 2004): 1461\u0026ndash;68.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.anbehav.2004.01.014\"\u003ehttps://doi.org/10.1016/j.anbehav.2004.01.014\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eHallsson, L. R., and M. Bj\u0026ouml;rklund. \u0026ldquo;Selection in a Fluctuating Environment Leads to Decreased Genetic Variation and Facilitates the Evolution of Phenotypic Plasticity.\u0026rdquo; \u003cem\u003eJournal of Evolutionary Biology\u003c/em\u003e 25, no. 7 (July 2012): 1275\u0026ndash;90.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1420-9101.2012.02512.x\"\u003ehttps://doi.org/10.1111/j.1420-9101.2012.02512.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eHedrick, Philip W., Michael E. Ginevan, and Evelyn P. Ewing. \u0026ldquo;Genetic Polymorphism in Heterogeneous Environments.\u0026rdquo; \u003cem\u003eAnnual Review of Ecology and Systematics\u003c/em\u003e 7, no. 1 (November 1976): 1\u0026ndash;32.\u0026nbsp;\u003ca href=\"https://doi.org/10.1146/annurev.es.07.110176.000245\"\u003ehttps://doi.org/10.1146/annurev.es.07.110176.000245\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eHoffmann, Ary A., Carla M. Sgr\u0026ograve;, and Torsten N. Kristensen. \u0026ldquo;Revisiting Adaptive Potential, Population Size, and Conservation.\u0026rdquo; \u003cem\u003eTrends in Ecology \u0026amp; Evolution\u003c/em\u003e 32, no. 7 (July 2017): 506\u0026ndash;17.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.tree.2017.03.012\"\u003ehttps://doi.org/10.1016/j.tree.2017.03.012\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eHuang, Guilian, Wei Wu, Yongmei Chen, Xueke Zhi, Peishan Zou, Zulin Ning, Qiang Fan, et al. \u0026ldquo;Balancing Selection on an MYB Transcription Factor Maintains the Twig Trichome Color Variation in Melastoma Normale.\u0026rdquo; \u003cem\u003eBMC Biology\u003c/em\u003e 21, no. 1 (May 24, 2023): 122.\u0026nbsp;\u003ca href=\"https://doi.org/10.1186/s12915-023-01611-4\"\u003ehttps://doi.org/10.1186/s12915-023-01611-4\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eIngleby, F. C., J. Hunt, and D. J. Hosken. \u0026ldquo;The Role of Genotype‐by‐environment Interactions in Sexual Selection.\u0026rdquo; \u003cem\u003eJournal of Evolutionary Biology\u003c/em\u003e 23, no. 10 (October 1, 2010): 2031\u0026ndash;45.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1420-9101.2010.02080.x\"\u003ehttps://doi.org/10.1111/j.1420-9101.2010.02080.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eJoswig, Julia S., Christian Wirth, Meredith C. Schuman, Jens Kattge, Bj\u0026ouml;rn Reu, Ian J. Wright, Sebastian D. Sippel, et al. \u0026ldquo;Climatic and Soil Factors Explain the Two-Dimensional Spectrum of Global Plant Trait Variation | Nature Ecology \u0026amp; Evolution.\u0026rdquo; \u003cem\u003eNature Ecology \u0026amp; Evolution\u003c/em\u003e 6, no. 1 (January 2022): 36\u0026ndash;50.\u0026nbsp;\u003ca href=\"https://doi.org/10.1038/s41559-021-01616-8\"\u003ehttps://doi.org/10.1038/s41559-021-01616-8\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eKokko, Hanna, and Katja Heubel. \u0026ldquo;Condition-Dependence, Genotype-by-Environment Interactions and the Lek Paradox.\u0026rdquo; \u003cem\u003eGenetica\u003c/em\u003e 134, no. 1 (September 1, 2008): 55\u0026ndash;62.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/s10709-008-9249-7\"\u003ehttps://doi.org/10.1007/s10709-008-9249-7\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eKonior, Magdalena, Jacek Radwan, Maria Kołodziejczyk, and Laurent Keller. \u0026ldquo;Strong Association between a Single Gene and Fertilization Efficiency of Males and Fecundity of Their Mates in the Bulb Mite.\u0026rdquo; \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e 273, no. 1584 (February 7, 2006): 309\u0026ndash;14.\u0026nbsp;\u003ca href=\"https://doi.org/10.1098/rspb.2005.3302\"\u003ehttps://doi.org/10.1098/rspb.2005.3302\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eKoshiba, Seizo, Ikuko N. Motoike, Daisuke Saigusa, Jin Inoue, Yuichi Aoki, Shu Tadaka, Matsuyuki Shirota, et al. \u0026ldquo;Identification of Critical Genetic Variants Associated with Metabolic Phenotypes of the Japanese Population.\u0026rdquo; \u003cem\u003eCommunications Biology\u003c/em\u003e 3, no. 1 (November 11, 2020): 662.\u0026nbsp;\u003ca href=\"https://doi.org/10.1038/s42003-020-01383-5\"\u003ehttps://doi.org/10.1038/s42003-020-01383-5\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eLaMunyon, Craig W., Oussama Bouban, and Asher D. Cutter. \u0026ldquo;Postcopulatory Sexual Selection Reduces Genetic Diversity in Experimental Populations of Caenorhabditis Elegans.\u0026rdquo; \u003cem\u003eJournal of Heredity\u003c/em\u003e 98, no. 1 (January 1, 2007): 67\u0026ndash;72.\u0026nbsp;\u003ca href=\"https://doi.org/10.1093/jhered/esl052\"\u003ehttps://doi.org/10.1093/jhered/esl052\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eLevins, Richard. \u003cem\u003eEvolution in Changing Environments: Some Theoretical Explorations\u003c/em\u003e. Princeton University Press, 1968.\u003c/p\u003e\n\u003cp\u003eLewontin, Richard C. \u003cem\u003eThe Genetic Basis of Evolutionary Change\u003c/em\u003e. Vol. 560. Columbia University Press New York, 1974.\u0026nbsp;\u003ca href=\"https://authors.library.caltech.edu/5456/01/hrst.mit.edu/hrs/evolution/public/papers/lewontin1974/lewontin1974_chap1andfront.pdf\"\u003ehttps://authors.library.caltech.edu/5456/01/hrst.mit.edu/hrs/evolution/public/papers/lewontin1974/lewontin1974_chap1andfront.pdf\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eLonn, Eija, Esa Koskela, Tapio Mappes, Mikael Mokkonen, Angela M. Sims, and Phillip C. Watts. \u0026ldquo;Balancing Selection Maintains Polymorphisms at Neurogenetic Loci in Field Experiments.\u0026rdquo; \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 114, no. 14 (April 4, 2017): 3690\u0026ndash;95.\u0026nbsp;\u003ca href=\"https://doi.org/10.1073/pnas.1621228114\"\u003ehttps://doi.org/10.1073/pnas.1621228114\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eŁukasik, Piotr, Małgorzata Zygadło, and Jacek Radwan.\u0026nbsp;\u0026ldquo;The Effect of a Phosphogluconate Dehydrogenase Genotype on Sperm Competitiveness in the Bulb Mite,Rhizoglyphus Robini.\u0026rdquo; In \u003cem\u003eTrends in Acarology\u003c/em\u003e, edited by Maurice W. Sabelis and Jan Bruin, 295\u0026ndash;97. Dordrecht: Springer Netherlands, 2010.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/978-90-481-9837-5_47\"\u003ehttps://doi.org/10.1007/978-90-481-9837-5_47\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eMagris, Martina, Anne E. Wignall, and Marie E. Herberstein. \u0026ldquo;The Sterile Male Technique: Irradiation Negatively Affects Male Fertility but Not Male Courtship.\u0026rdquo; \u003cem\u003eJournal of Insect Physiology\u003c/em\u003e 75 (April 1, 2015): 85\u0026ndash;90.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.jinsphys.2015.02.014\"\u003ehttps://doi.org/10.1016/j.jinsphys.2015.02.014\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eManjurano, Alphaxard, Nuno Sepulveda, Behzad Nadjm, George Mtove, Hannah Wangai, Caroline Maxwell, Raimos Olomi, et al. \u0026ldquo;African Glucose-6-Phosphate Dehydrogenase Alleles Associated with Protection from Severe Malaria in Heterozygous Females in Tanzania.\u0026rdquo; \u003cem\u003ePLoS Genetics\u003c/em\u003e 11, no. 2 (February 2015): e1004960.\u0026nbsp;\u003ca href=\"https://doi.org/10.1371/journal.pgen.1004960\"\u003ehttps://doi.org/10.1371/journal.pgen.1004960\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eMazza, Giuseppe, Alberto Francesco Inghilesi, Gianluca Stasolla, Alessandro Cini, Rita Cervo, Claudia Benvenuti, Valeria Francardi, Massimo Cristofaro, Silvia Arnone, and Pio Federico Roversi. \u0026ldquo;Sterile Rhynchophorus Ferrugineus Males Efficiently Impair Reproduction While Maintaining Their Sexual Competitiveness in a Social Context.\u0026rdquo; \u003cem\u003eJournal of Pest Science\u003c/em\u003e 89, no. 2 (December 7, 2015): 459\u0026ndash;68.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/s10340-015-0709-4\"\u003ehttps://doi.org/10.1007/s10340-015-0709-4\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eMuirhead, Christina A. \u0026ldquo;CONSEQUENCES OF POPULATION STRUCTURE ON GENES UNDER BALANCING SELECTION.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 55, no. 8 (August 1, 2001): 1532\u0026ndash;41.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.0014-3820.2001.tb00673.x\"\u003ehttps://doi.org/10.1111/j.0014-3820.2001.tb00673.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eNuzhdin, Sergey V., Elena G. Pasyukova, Christy L. Dilda, Zhao-Bang Zeng, and Trudy F. C. Mackay. \u0026ldquo;Sex-Specific Quantitative Trait Loci Affecting Longevity in Drosophila\u0026thinsp;Melanogaster.\u0026rdquo; \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 94, no. 18 (September 2, 1997): 9734\u0026ndash;39.\u0026nbsp;\u003ca href=\"https://doi.org/10.1073/pnas.94.18.9734\"\u003ehttps://doi.org/10.1073/pnas.94.18.9734\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eParker, G. A. \u0026ldquo;Sperm Competition and Its Evolutionary Effect on Copula Duration in the Fly \u003cem\u003eScatophaga Stercoraria\u003c/em\u003e.\u0026rdquo; \u003cem\u003eJournal of Insect Physiology\u003c/em\u003e 16, no. 7 (July 1, 1970): 1301\u0026ndash;28.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/0022-1910(70)90131-9\"\u003ehttps://doi.org/10.1016/0022-1910(70)90131-9\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eParrett, Jonathan M., and Robert J. Knell. \u0026ldquo;The Effect of Sexual Selection on Adaptation and Extinction under Increasing Temperatures.\u0026rdquo; \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e 285, no. 1877 (April 18, 2018): 20180303.\u0026nbsp;\u003ca href=\"https://doi.org/10.1098/rspb.2018.0303\"\u003ehttps://doi.org/10.1098/rspb.2018.0303\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003ePatlar, Bahar, and Steven A. Ramm. \u0026ldquo;Genotype‐by‐environment Interactions for Seminal Fluid Expression and Sperm Competitive Ability.\u0026rdquo; \u003cem\u003eJournal of Evolutionary Biology\u003c/em\u003e 33, no. 2 (February 1, 2020): 225\u0026ndash;36.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/jeb.13568\"\u003ehttps://doi.org/10.1111/jeb.13568\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003ePemberton, J. M., S. D. Albon, F. E. Guinness, and T. H. Clutton‐Brock. \u0026ldquo;COUNTERVAILING SELECTION IN DIFFERENT FITNESS COMPONENTS IN FEMALE RED DEER.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 45, no. 1 (February 1, 1991): 93\u0026ndash;103.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1558-5646.1991.tb05269.x\"\u003ehttps://doi.org/10.1111/j.1558-5646.1991.tb05269.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003ePeniston, James H., Michael Barfield, Andrew Gonzalez, and Robert D. Holt. \u0026ldquo;Environmental Fluctuations Can Promote Evolutionary Rescue in High-Extinction-Risk Scenarios.\u0026rdquo; \u003cem\u003eProceedings of the Royal Society B: Biological Sciences\u003c/em\u003e 287, no. 1932 (August 5, 2020): 20201144.\u0026nbsp;\u003ca href=\"https://doi.org/10.1098/rspb.2020.1144\"\u003ehttps://doi.org/10.1098/rspb.2020.1144\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003ePlesnar-Bielak, Agata, Anna M. Skwierzyńska, and Jacek Radwan.\u0026nbsp;\u0026ldquo;Sexual and Ecological Selection on a Sexual Conflict Gene.\u0026rdquo; \u003cem\u003eJournal of Evolutionary Biology\u003c/em\u003e 33, no. 10 (2020): 1433\u0026ndash;39.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/jeb.13680\"\u003ehttps://doi.org/10.1111/jeb.13680\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003ePlesnar-Bielak, Agata, Anna Maria Skwierzyńska, Kasper Hlebowicz, and Jacek Radwan. \u0026ldquo;Relative Costs and Benefits of Alternative Reproductive Phenotypes at Different Temperatures \u0026ndash; Genotype-by-Environment Interactions in a Sexually Selected Trait.\u0026rdquo; \u003cem\u003eBMC Evolutionary Biology\u003c/em\u003e 18, no. 1 (July 11, 2018): 1\u0026ndash;10.\u0026nbsp;\u003ca href=\"https://doi.org/10.1186/s12862-018-1226-x\"\u003ehttps://doi.org/10.1186/s12862-018-1226-x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eRadwan, Jacek. \u0026ldquo;Sperm Competition in the Mite Caloglyphus Berlesei.\u0026rdquo; \u003cem\u003eBehavioral Ecology and Sociobiology\u003c/em\u003e 29, no. 4 (November 1991): 291\u0026ndash;96.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/BF00163987\"\u003ehttps://doi.org/10.1007/BF00163987\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eRadwan, Jacek, Leif Engqvist, and Klaus Reinhold. \u0026ldquo;A Paradox of Genetic Variance in Epigamic Traits: Beyond \u0026lsquo;Good Genes\u0026rsquo; View of Sexual Selection.\u0026rdquo; \u003cem\u003eEvolutionary Biology\u003c/em\u003e 43, no. 2 (June 2016): 267\u0026ndash;75.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/s11692-015-9359-y\"\u003ehttps://doi.org/10.1007/s11692-015-9359-y\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eRadwan, Jacek, and Michael T. Siva-Jothy. \u0026ldquo;The Function of Post-Insemination Mate Association in the Bulb Mite,Rhizoglyphus Robini.\u0026rdquo; \u003cem\u003eAnimal Behaviour\u003c/em\u003e 52, no. 4 (October 1996): 651\u0026ndash;57.\u0026nbsp;\u003ca href=\"https://doi.org/10.1006/anbe.1996.0209\"\u003ehttps://doi.org/10.1006/anbe.1996.0209\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eRice, William R., and Brett Holland. \u0026ldquo;Experimentally Enforced Monogamy: Inadvertent Selection, Inbreeding, or Evidence for Sexually Antagonistic Coevolution?\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 59, no. 3 (2005): 682\u0026ndash;85.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.0014-3820.2005.tb01026.x\"\u003ehttps://doi.org/10.1111/j.0014-3820.2005.tb01026.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eRundle, Howard D., Stephen F. Chenoweth, and Mark W. Blows. \u0026ldquo;THE ROLES OF NATURAL AND SEXUAL SELECTION DURING ADAPTATION TO A NOVEL ENVIRONMENT.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 60, no. 11 (2006): 2218.\u0026nbsp;\u003ca href=\"https://doi.org/10.1554/06-249.1\"\u003ehttps://doi.org/10.1554/06-249.1\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSchoepf, Ivana, and Neville Pillay. \u0026ldquo;Multiple Interacting Factors Affect Seed Predation in an African Savanna Small Mammal Community.\u0026rdquo; \u003cem\u003eJournal of Mammalogy\u003c/em\u003e 104, no. 3 (June 1, 2023): 446\u0026ndash;56.\u0026nbsp;\u003ca href=\"https://doi.org/10.1093/jmammal/gyac127\"\u003ehttps://doi.org/10.1093/jmammal/gyac127\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSirot, Laura K., H. Jane Brockmann, and Stephen L. Lapointe. \u0026ldquo;Male Postcopulatory Reproductive Success in the Beetle, \u003cem\u003eDiaprepes Abbreviatus\u003c/em\u003e.\u0026rdquo; \u003cem\u003eAnimal Behaviour\u003c/em\u003e 74, no. 1 (July 1, 2007): 143\u0026ndash;52.\u0026nbsp;\u003ca href=\"https://doi.org/10.1016/j.anbehav.2006.12.004\"\u003ehttps://doi.org/10.1016/j.anbehav.2006.12.004\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSkwierzyńska, Anna M., and Agata Plesnar-Bielak. \u0026ldquo;Proximate Mechanisms of the Differences in Reproductive Success of Males Bearing Different Alleles of Pgdh \u0026ndash; a Gene Involved in a Sexual Conflict in Bulb Mite.\u0026rdquo; \u003cem\u003eJournal of Evolutionary Biology\u003c/em\u003e 31, no. 5 (2018): 657\u0026ndash;64.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/jeb.13250\"\u003ehttps://doi.org/10.1111/jeb.13250\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSlatkin, Montgomery. \u0026ldquo;Gene Flow and the Geographic Structure of Natural Populations.\u0026rdquo; \u003cem\u003eScience\u003c/em\u003e 236, no. 4803 (May 15, 1987): 787\u0026ndash;92.\u0026nbsp;\u003ca href=\"https://doi.org/10.1126/science.3576198\"\u003ehttps://doi.org/10.1126/science.3576198\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSmith, Andrew H., Michael P. O\u0026rsquo;Connor, Brooke Deal, Coleman Kotzer, Amanda Lee, Barrett Wagner, Jonah Joffe, Stephen Woloszynek, Kerry M. Oliver, and Jacob A. Russell. \u0026ldquo;Does Getting Defensive Get You Anywhere?\u0026mdash;Seasonal Balancing Selection, Temperature, and Parasitoids Shape Real-World, Protective Endosymbiont Dynamics in the Pea Aphid.\u0026rdquo; \u003cem\u003eMolecular Ecology\u003c/em\u003e 30, no. 10 (2021): 2449\u0026ndash;72.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/mec.15906\"\u003ehttps://doi.org/10.1111/mec.15906\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eSnook, Rhonda R., Lena Br\u0026uuml;stle, and Jon Slate. \u0026ldquo;A TEST AND REVIEW OF THE ROLE OF EFFECTIVE POPULATION SIZE ON EXPERIMENTAL SEXUAL SELECTION PATTERNS.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 63, no. 7 (July 1, 2009): 1923\u0026ndash;33.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.1558-5646.2009.00682.x\"\u003ehttps://doi.org/10.1111/j.1558-5646.2009.00682.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eStamp, Megan A., and Jarrod D. Hadfield. \u0026ldquo;The Relative Importance of Plasticity versus Genetic Differentiation in Explaining between Population Differences; a Meta-Analysis.\u0026rdquo; \u003cem\u003eEcology Letters\u003c/em\u003e 23, no. 10 (2020): 1432\u0026ndash;41.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/ele.13565\"\u003ehttps://doi.org/10.1111/ele.13565\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eStincone, Anna, Alessandro Prigione, Thorsten Cramer, Mirjam M. C. Wamelink, Kate Campbell, Eric Cheung, Viridiana Olin-Sandoval, et al. \u0026ldquo;The Return of Metabolism: Biochemistry and Physiology of the Pentose Phosphate Pathway.\u0026rdquo; \u003cem\u003eBiological Reviews\u003c/em\u003e 90, no. 3 (2015): 927\u0026ndash;63.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/brv.12140\"\u003ehttps://doi.org/10.1111/brv.12140\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eUnnikrishnan, Pranav, Szymon Grzesik, Magdalena Trojańska, Beata Klimek, and Agata Plesnar-Bielak. \u0026ldquo;6Pgdh Polymorphism in Wild Bulb Mite Populations: Prevalence, Environmental Correlates and Life History Trade-Offs.\u0026rdquo; \u003cem\u003eExperimental and Applied Acarology\u003c/em\u003e, April 10, 2024.\u0026nbsp;\u003ca href=\"https://doi.org/10.1007/s10493-024-00909-4\"\u003ehttps://doi.org/10.1007/s10493-024-00909-4\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eVan den Bergh, Bram, Toon Swings, Maarten Fauvart, and Jan Michiels. \u0026ldquo;Experimental Design, Population Dynamics, and Diversity in Microbial Experimental Evolution.\u0026rdquo; \u003cem\u003eMicrobiology and Molecular Biology Reviews\u003c/em\u003e 82, no. 3 (July 25, 2018): 10.1128/mmbr.00008-18.\u0026nbsp;\u003ca href=\"https://doi.org/10.1128/mmbr.00008-18\"\u003ehttps://doi.org/10.1128/mmbr.00008-18\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eVia, Sara, and Russell Lande. \u0026ldquo;Evolution of Genetic Variability in a Spatially Heterogeneous Environment: Effects of Genotype\u0026ndash;Environment Interaction.\u0026rdquo; \u003cem\u003eGenetics Research\u003c/em\u003e 49, no. 2 (April 1987): 147\u0026ndash;56.\u0026nbsp;\u003ca href=\"https://doi.org/10.1017/S001667230002694X\"\u003ehttps://doi.org/10.1017/S001667230002694X\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWhitt, Sherry R., Larissa M. Wilson, Maud I. Tenaillon, Brandon S. Gaut, and Edward S. Buckler. \u0026ldquo;Genetic Diversity and Selection in the Maize Starch Pathway.\u0026rdquo; \u003cem\u003eProceedings of the National Academy of Sciences\u003c/em\u003e 99, no. 20 (October 2002): 12959\u0026ndash;62.\u0026nbsp;\u003ca href=\"https://doi.org/10.1073/pnas.202476999\"\u003ehttps://doi.org/10.1073/pnas.202476999\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWigby, Stuart, and Tracey Chapman. \u0026ldquo;Female Resistance to Male Harm Evolves in Response to Manipulation of Sexual Conflict.\u0026rdquo; \u003cem\u003eEvolution\u003c/em\u003e 58, no. 5 (2004): 1028\u0026ndash;37.\u0026nbsp;\u003ca href=\"https://doi.org/10.1111/j.0014-3820.2004.tb00436.x\"\u003ehttps://doi.org/10.1111/j.0014-3820.2004.tb00436.x\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eWright, Sewall. \u0026ldquo;The Roles of Mutation, Inbreeding, Crossbreeding, and Selection in Evolution,\u0026rdquo; 1932.\u0026nbsp;\u003ca href=\"http://www.esp.org/books/6th-congress/facsimile/contents/6th-cong-p356-wright.pdf\"\u003ehttp://www.esp.org/books/6th-congress/facsimile/contents/6th-cong-p356-wright.pdf\u003c/a\u003e.\u003c/p\u003e\n\u003cp\u003eZan, Yanjun, and \u0026Ouml;rjan Carlborg. \u0026ldquo;Dynamic Genetic Architecture of Yeast Response to Environmental Perturbation Shed Light on Origin of Cryptic Genetic Variation.\u0026rdquo; Accessed July 18, 2024.\u0026nbsp;\u003ca href=\"https://doi.org/10.1371/journal.pgen.1008801\"\u003ehttps://doi.org/10.1371/journal.pgen.1008801\u003c/a\u003e.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"genetic polymorphism, environment-driven balancing selection, genotype by environment interaction for fitness, sexual selection, temperature","lastPublishedDoi":"10.21203/rs.3.rs-4835969/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-4835969/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"Balancing selection, the process by which multiple alleles are maintained in a population, can occur through genotype by environment interactions. The polymorphism of 6Pgdh in bulb mites involves two alleles, S and F, which have opposing effect on male reproductive success. While S-bearing males have a reproductive advantage and the S allele fixes in the laboratory populations, polymorphism is regularly observed in natural populations. We hypothesise that 6Pgdh is under balancing selection in bulb mites, driven by fluctuations of temperature and sexual selection intensity. This study uses experimental evolution to track allele frequency changes over 13 generations under different temperatures (12 °C and 18 °C) and sexual selection intensities (equal and female-biased sex ratios). The results show a significant increase in F allele frequency under higher sexual selection intensity at 12 °C. This suggests that individuals with the F allele gain a reproductive advantage at lower temperatures, and 6Pgdh polymorphism is maintained through a three-way interaction genotype x abiotic (temperature) x social environment. However, in another experiment we did not find significant associations between male genotype and reproductive success across different temperatures. The complex interplay between environmental factors and social dynamics in maintaining genetic polymorphism highlights that multiple factors can interact in driving balancing selection.","manuscriptTitle":"The interplay of environmental and social factors influences balancing selection: 6Pgdh in bulb mites","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2024-09-20 15:05:23","doi":"10.21203/rs.3.rs-4835969/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"b058faf8-c5a6-48de-9b27-50327779314c","owner":[],"postedDate":"September 20th, 2024","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":36681526,"name":"Biological sciences/Evolution/Experimental evolution"},{"id":36681527,"name":"Biological sciences/Evolution/Sexual selection"},{"id":36681528,"name":"Biological sciences/Biological techniques/Experimental organisms/Non-model organisms"}],"tags":[],"updatedAt":"2024-11-20T19:15:19+00:00","versionOfRecord":[],"versionCreatedAt":"2024-09-20 15:05:23","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-4835969","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-4835969","identity":"rs-4835969","version":["v1"]},"buildId":"qtupq5eGEP_6zYnWcrvyt","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}