Copy number variation of a fatty acid desaturase gene Fads2 associated with ecological divergence in freshwater stickleback populations

Abstract

Fitness of aquatic animals can be limited by the scarcity of nutrients such as long-chain polyunsaturated fatty acids, especially docosahexaenoic acid (DHA). DHA availability from diet varies among aquatic habitats, imposing different selective pressures on resident animals to optimize DHA acquisition and synthesis. For example, DHA is generally poor in freshwater ecosystems compared to marine ecosystems. Our previous work revealed that, relative to marine fishes, several freshwater fishes evolved higher copy numbers of the fatty acid desaturase2 (Fads2) gene, which encodes essential enzymes for DHA biosynthesis, likely compensating for the limited availability of DHA in freshwater. Here, we demonstrate that Fads2 copy number also varies between freshwater sticklebacks inhabiting lakes and streams with stream fish having higher Fads2 copy number. Additionally, populations with benthic-like morphology possessed higher Fads2 copy number than those with planktivore-like morphology. This may be because benthic-like fish mainly feed on DHA-deficient prey such as macroinvertebrates whereas planktivore-like fish forage more regularly on DHA-rich prey, like copepods. Our results suggest that Fads2 copy number variation arises from ecological divergence not only between organisms exploiting marine and freshwater habitats but also between freshwater organisms exploiting divergent resources.

1. Introduction

Nutrient scarcity limits the growth, survival and reproduction of organisms [1,2]. Since habitats vary in nutritional availability, populations in different habitats should experience divergent selection for distinct strategies to optimize acquisition and synthesis of essential nutrients. Limiting nutrients include the omega-3 and omega-6 long-chain polyunsaturated fatty acids (LC-PUFAs), especially docosahexaenoic acid (DHA) (22 : 6n-3) [3]. DHA is essential for animals at all taxonomic levels since it plays crucial roles in growth, development, energy allocation, reproduction and survival [3]. Animals either obtain DHA from their diets or synthesize DHA from diet-derived shorter-chained PUFA precursors, such as alpha-linolenic acid (ALA) and eicosapentaenoic acid (EPA). Because primary producers in different habitats vary in fatty acid composition, there is spatial variation in the availability of DHA and its precursors for consumers [4]. For instance, primary producers from marine ecosystems often contain more DHA and EPA than those from freshwater ecosystems, which instead generally contain more ALA [5]. Such spatial variation should generate divergent selection on the consumers, for instance to increase conversion efficiencies of precursors, such as ALA, to DHA in freshwater environments [1,2].

Our previous study revealed that multiple fish lineages that colonized DHA-deficient freshwater habitats evolved increased copy number of fatty acid desaturase2 (Fads2), a gene that encodes enzymes for the biosynthesis of DHA [6]. For instance, freshwater three-spined stickleback (Gasterosteus aculeatus), which is ancestrally marine but colonized freshwater habitats after glacial retreat, showed multiple independent increases of Fads2 copy number in replicate watersheds, compared to marine populations. Marine populations generally possess one Fads2 copy on chromosome 12 and another copy on the X chromosome (chromosome 19), whereas duplication of Fads2 occurred on the X chromosome in several freshwater populations [6]. Accordingly, fish with higher Fads2 copy number better synthesized DHA when fed with DHA-deficient diets, suggesting higher Fads2 copy number is adaptive in DHA-deficient freshwater habitats. Convergent increases of Fads2 copies were also observed in multiple freshwater ray-finned fish species [6].

Compared to the marine–freshwater transitions, we know little about the evolutionary mechanisms of adaptation of PUFA metabolism within freshwater ecosystems. Fatty acid availability varies among different types of freshwater habitats due to different primary producer and prey species compositions and environmental conditions [4,7]. For instance, our previous meta-analysis showed that limnetic prey items generally contain more DHA than benthic prey items [6]. More specifically, the biomass of DHA-rich copepods [6,8] is higher in deeper lake habitats [9,10], whereas shallower lakes and streams have a higher frequency of DHA-poor benthic macroinvertebrates. Therefore, we hypothesized that adaptive copy number variation of Fads2 might also exist even between freshwater fishes exploiting different habitats and/or prey items.

Here, we tested this hypothesis using freshwater three-spined sticklebacks living in lakes and streams. The three-spined sticklebacks have repeatedly radiated into different freshwater habitats after Pleistocene glacial retreat 12 000 years ago, resulting in the formation of pairs of different ecotypes, such as parapatric lake-stream pairs [11–16]. Lake sticklebacks tend to consume more pelagic prey and less benthic prey than stream sticklebacks [17]. Therefore, we tested whether stream sticklebacks should have higher Fads2 copies to compensate for the lower availability of DHA in their benthic invertebrate diets.

However, a recent study revealed that the simple dichotomic categorization of lake-versus-stream ecotypes was insufficient to appropriately investigate evolutionary responses to quantitative environmental variation [12]. Morphological differences between lake and stream sticklebacks were often inconsistent from one watershed to the next, due to unique features of each lake and stream environment. Sticklebacks with more numerous and longer gill rakers, longer jaws and more slender bodies are better at foraging zooplankton, including DHA-rich copepods [11,13,15,16,18,19]. Although morphological divergence between lake and stream stickleback generally reflects the difference in diet items [14,16,20–23], a previous study showed that lake populations have more gill rakers than their stream neighbours in 14 out of 16 pairs with two exceptions [12]. As such, we tested whether the foraging traits and the prey items in each habitat are correlated with the Fads2 copy number.

2. Material and methods

(a) . Measurement of relative copy number of Fads2

We used 547 individuals from 16 lake-stream pairs of the three-spined stickleback on Vancouver Island collected in May to July 2013, which were reported previously [12]. Each pair is from a separate watershed created after Pleistocene glacial retreat, and at least 11 pairs represent independent evolutionary replicates. Fish were euthanized in 500 mg l⁻¹ MS-222 for more than 2 min, confirming that all opercular movement ceases, equilibrium is lost, and there is no reflex movement in response to handling or tail pinch. A fin clip was cut for DNA and preserved in 95% ethanol, whereas the rest of the fish was immediately fixed in formalin. We extracted genomic DNA using the Promega Wizard SV Genomic DNA Purification Kit (Promega) [12], treated the extracts with RNase A (Qiagen) to remove RNA and then purified the DNA using the Agencourt AMPure XP (Beckman Coulter Life Science). Relative Fads2 copy numbers were determined for each individual by genomic quantitative PCR (qPCR) as described previously [6]. Briefly, we designed forward and reverse primers and a TaqMan probe on a region conserved among Fads2 haplotypes (electronic supplementary material, table S1). Thyroid stimulating hormone ß2 was used as a reference to normalize the relative copy number of Fads2 because this gene shows no sign of copy number variation in sticklebacks [6]. Genomic qPCR reactions were run on a StepOnePlus (Applied Biosystems) with TaqMan Real-Time PCR Master Mix (Applied Biosystems). Relative copy numbers of Fads2 were calculated from standard curves drawn from the serially diluted DNA pools of all analysed fish.

(b) . Morphological and environmental variables

Morphological variables were obtained from the previous study (electronic supplementary material, table S2) [12]. Because morphological data were taken from different individuals than those we sequenced, we could not make associations at the individual level. Thus, we took the mean of each variable for each sex of each population and used these means, natural log-transformed, for analyses at the population level. Environmental variables analysed included habitat (lake or stream), stomach contents (see below), mean temperature at 0.5 m depth, and the migration rate between the parapatric lake and stream populations, which were also taken from the previous study [12]. For stomach content analysis, traps were in place no longer than 3 h to ensure representation of recently consumed prey. Stomachs were dissected out of preserved specimens, and prey was identified to the lowest feasible taxonomic level and counted. Of the 57 stomach content prey items, we excluded 24 minor prey items that were found only in five or fewer individuals among all 525 individuals (electronic supplementary material, table S2). Analysis of the effects of stomach contents on Fads2 copy number was also conducted at the population level, because stomach content is just a snapshot of trophic ecology and the average at the population level may reflect the trophic ecology of the population more than the snapshot in the individual stomach. In addition to the presence/absence in each population, we calculated the fraction of individuals (for each sex, by population) that had a given prey in their stomachs.

(c) . Statistical analysis

All statistical analyses were conducted with R v. 3.6.2 [24]. To test whether lake and stream populations possess different Fads2 copy number, we used Poisson generalized linear models (GLM) that account for the relative Fads2 copy number of individuals as a dependent variable and watershed, habitat and sex as independent variables. Because at least one Fads2 copy is located on the X chromosome but not on the Y chromosome, resulting in females having more copies than males [6], we included the sex in the model. Because a full model with all interactions among independent variables detected no significant interactions, we excluded all interactions from the final model.

To investigate whether foraging traits were correlated with Fads2 copy number, we first conducted principal component (PC) analysis on the population means of the 14 morphological variables. We used GLM that account for the relative Fads2 copy number of populations as a dependent variable and PC1–5 and sex as independent variables with interactions between PC1–5 and sex. To find environmental variables significantly associated with Fads2 copy, we conducted the elastic net regression analysis [25] using glmnet package [26]. This method integrates Ridge regression and LASSO regression and is recommended when explanatory variables are correlated [27]. The best model parameters that minimize the elastic net function were searched using 10-fold cross validation of the parameters in the elastic net function. The Fads2 copy number was the dependent variable. The input variables for the elastic net were the binary category of habitat and sex, the continuous variables of the mean temperature at 0.5 m depth and the migration rate, and either the presence/absence of each prey item in the population or fraction of individuals that had each 33 prey item in the stomach. As the analysed samples included no females in Joe Lake, only one male in Pye Lake and only two females in Kennedy Lake, we excluded females of the lake-stream pairs of Joe and Kennedy and males of the Pye pair.

3. Results

We found effects of habitat, sex and watershed on Fads2 copy number variation (figure 1). Stream fish had a higher copy number of Fads2 than lake fish (p = 0.013) (electronic supplementary material, table S3 and S4). Across both habitats, females had higher copy number than males (p = 2.14 × 10⁻⁵). Joe, Pye and Village Bay watersheds had higher copy numbers than other watersheds (p = 0.040, 6.39 × 10⁻⁴ and 0.026, respectively).

Figure 1.

Relative copy number of Fads2 in males (a) and females (b) of 16 lake-stream pairs. Each dot indicates a single individual with the square and bar indicating mean ± s.e.

PC2 and PC5 of foraging traits were significantly correlated with the relative copy number of Fads2 (figure 2; electronic supplementary material, tables S2, S5 and S6, figure S1). Populations with higher PC2 (i.e. benthic morphology with fewer and shorter gill rakers and lower gill raker density) had higher Fads2 copy numbers (p = 0.041), while those with higher PC5 (i.e. limnetic morphology with lower jaw opening in lever length, larger buccal cavity and wider gape) had lower Fads2 copy numbers (p = 0.044) (figure 2; electronic supplementary material, tables S5 and S6). Notably, PC2 significantly differed between the lake and stream populations (GLM, p = 1.7 × 10⁻⁴) (electronic supplementary material, table S7) with the stream fish having higher PC2. The interaction between the sex and morphology was not significant for PC2 or PC5 (electronic supplementary material, table S6).

Figure 2.

Correlations between the Fads2 copy number and morphology PC2 (a,b) or PC5 (c,d). Each dot indicates a single population. Females are circles. Males are triangles.

Some diet items were also associated with the Fads2 copy number. The presence of cycloid, ostracods and Baetis in the stomach content of the population was negatively correlated whereas that of diatoms, insect eggs, Collembola (springtails) and Trichoptera (caddisfly) was positively associated with the copy number (table 1). The fractions of individuals that had Collembola, Empididae (dagger flies), diatoms and insect eggs in the stomach was positively associated with the Fads2 copy number, while the fractions of individuals that had snail shells and Leptodoridae (water fleas) were negatively associated with the Fads2 copy number (table 1).

Table 1.

Coefficient estimates of the effects of the presence/absence and fraction of individuals with stomach contents on Fads2 copy number variations in the best models.

variables	presence/absence	fraction of individuals
Baetis spp.	−0.091
Collembola	0.009	0.968
cyclopoid	−0.189
diatoms	0.671	0.055
Empididae		0.884
insect eggs	0.476	0.044
Leptodoridae		−0.275
ostracods	−0.057
sex	−0.597	−0.172
snail shells		−0.193
Trichoptera	0.332

4. Discussion

Here, we have shown that the Fads2 copy number varies among freshwater sticklebacks that reside in different habitats. Stream fish had higher Fads2 copy numbers than lake fish, suggesting that spatial variation in prey items between lake and stream environments can generate a divergent selection to change Fads2 copy number.

Additionally, populations with benthic-like morphology had higher Fads2 copy numbers than planktivore-like populations. These results suggest that morphological adaptation for benthivory might cause selective pressure for increasing DHA synthesis efficiency, relative to planktivorous populations.

We also found that populations feeding Collembola, Trichoptera, insect eggs and Empididae had higher copy numbers of Fads2. Most terrestrial insects have low LC-PUFA concentrations [3], suggesting that stickleback populations feeding on DHA-deficient prey have evolved increased Fads2 copy number to enhance DHA synthesis. By contrast, stickleback populations feeding cyclopoid copepods, Leptodoridae water fleas and snail shells had lower copy numbers. Copepods are generally rich in DHA [6,8,28]. Although cladoceran zooplankton including Leptodoridae contain larger amounts of EPA than DHA [3,29], it is possible that they are also important DHA sources for the freshwater sticklebacks. Finally, snails may be possible sources of DHA, since some Mollusca species accumulate DHA [29]. Therefore, fish populations consuming DHA-rich prey may be able to take enough DHA from the diets and tolerate lower Fads2 copy numbers.

There are several caveats in this study. First, fish were collected between May and July, so stomach items represent prey only from a single season of a year. Though this snapshot found a significant association between prey items and Fads2 copy number, it is possible that prey variation in other seasons could also contribute to the copy number variation. However, a previous study revealed a strong correlation between gut contents and stable isotopes, suggesting that snapshot samples are fairly indicative of broader dietary trends [30]. Second, we did not analyse the fatty acid content of prey items at these sites. However, many previous studies have shown strong patterns that terrestrial insects have low LC-PUFA, while copepods and cladoceran have high DHA and/or EPA in freshwater ecosystems. Since the majority of stomach contents with significant positive and negative effects on the Fads2 copy number were the terrestrial insects and copepods/cladoceran, respectively, we think that our overall conclusions are reasonable. Third, we do not know which loci contain the copy number variants. Finally, in addition to copy number variation, other types of mutations, such as amino acid changes of Fads2 genes, may also contribute to metabolic adaptation within freshwater fishes [6,31]. Further investigation of the genetics and ecology of these populations will help to understand the roles of freshwater ecology in the evolution of copy numbers of metabolic genes.

In conclusion, we have shown that the copy number variations of Fads2 genes could underlie adaptive ecological divergence among habitats in the freshwater ecosystem. Spatial variation in LC-PUFA within freshwater ecosystem may be an under-appreciated selective pressure that can shape adaptive diversification in aquatic animals.

Ethics

Collections were permitted by the British Columbia Ministry of Forests, Lands, and Natural Resource Operations (NA13-85103) and the animal experiments were approved by the institutional animal care and use committee of the University of Texas at Austin (protocol no. UP-2012-00065).

Data accessibility

Raw data are available from the Dryad Digital Repository: https://doi.org/10.5061/dryad.fxpnvx0s9 [32].

The data are provided in the electronic supplementary material [33].

Authors' contributions

A.I. and J.K. designed the study. Y.E.S. and D.I.B. collected the data. A.I. performed experiments and data analysis. A.I. and J.K. wrote the first draft of the manuscript with Y.E.S. and D.I.B. making significant contributions to editing. All authors agree to be held accountable for the content therein and approve the final version of the manuscript.

Competing interests

We declare we have no competing interests.

Funding

This research was supported by a Grant-in-Aid for Scientific Research (A) from the Japan Society for the Promotion of Science (grant no. 19H01003) to J.K., a Grant-in-Aid for Scientific Research (B) (grant no. 19H03277), a Fund for the Promotion of Joint International Research (Fostering Joint International Research (B)) (grant no. 19KK0187) and a Grant-in-Aid for Scientific Research on Innovative Areas (grant no. 20H04873) from the Japan Society for the Promotion of Science to A.I. It was also supported by U.S. National Science Foundation grant nos. DEB-1144773 and DEB-1466462 to D.I.B. and Y.E.S.