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Keywords:

  • altitude;
  • knock-down;
  • longevity;
  • QST;
  • starvation;
  • thermal adaptation

Abstract

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Patterns of clinal genetic variation in Drosophila are often characterized after rearing at constant temperatures. However, clinal patterns might change after acclimation if populations differ in their plastic response to fluctuating environments. We studied longevity, starvation and heat knock-down resistance after development at either constant or fluctuating temperatures in nine Drosophila buzzatii populations collected along an altitudinal gradient in Tenerife, Spain. Flies that developed at fluctuating temperatures had higher stress resistance despite experiencing a slightly lower average temperature than those at constant temperatures. Genetic variation along the gradient was found in both stress-resistance traits. Because QST values greatly exceeded FST values, genetic drift could not explain this diversification. In general, differences among populations were larger after rearing at fluctuating temperatures, especially in heat knock-down, for which clinal patterns disappeared when flies were reared at constant temperatures. This result emphasizes the importance of determining whether populations originating from different environments differ in their plastic responses to stress.


Introduction

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Clinal variation in traits related to stress resistance is common in ectotherms as populations adapt to local environmental conditions along an altitudinal or latitudinal gradient (Hoffmann et al., 2003; Angilletta et al., 2005; Hoffmann & Weeks, 2007). These patterns are often measured in individuals that are reared under uniform, constant and benign conditions in the laboratory. Such uniformity is important to ensure that any differences among populations are the result of genetic differences. However, when all environmental factors, e.g. temperature, are kept constant during development, flies collected from nature are placed in a novel and highly artificial environment that very few organisms will experience in the wild. In most cases, the thermal environment at least will fluctuate (Gibbs et al., 2003) and often induce an acclimation response. This response is a gradual habituation to the current climatic conditions, which can be quite substantial and can explain, for example, more than 80% of the total variation in cold resistance (Ayrinhac et al., 2004). Reports have described differences in plastic responses to an acclimation treatment among populations of different geographic origin (Kipyatkov & Lopatina, 2002) and after laboratory selection in Drosophila buzzatii (Patterson and Wheeler) (Krebs & Loeschcke, 1996). The inference from these observations is that the clinal pattern found in stress-related traits after constant rearing conditions might change when tested after development in a fluctuating temperature environment. The geographic pattern that emerges after acclimation thus might be ecologically more relevant.

To test whether the clinal pattern changes when rearing conditions change, we investigated two stress resistance–related traits, knock-down time and starvation resistance, and longevity in isofemale lines from nine populations of D. buzzatii collected along an altitudinal gradient. The resistance traits were measured in flies reared at either a constant 25 °C or at a fluctuating temperature of 21 °C for 20 h and 35 °C for 4 h. The fluctuating temperature regime was designed so that the low temperature matched the average temperature during summer nights at the lowest locality, and the high temperature matched the temperature in the shade on a sunny day. The 35 °C temperature is a mildly stressful temperature for D. buzzatii and will result in Hsp70 induction within an hour in adult flies, as shown for a laboratory population originating from Tenerife (Kristensen et al., 2002).

The populations were collected along an altitudinal gradient on the Canary Island of Tenerife. The climatic conditions on Tenerife are much more diverse than on most islands of a comparable size. It is situated 100 km off the North African coast in a cool ocean current. The island is volcanic in origin and rose from the Atlantic about 8 to 12 million years ago and now reaches 3718 m above sea level. At low altitudes, the climate is dry and warm with palms, but further inland at higher elevations, the climate becomes more cool and humid as the moist air in the trade winds cools on the way up the mountain. This setting establishes the potential for adaptive differentiation of closely spaced populations if natural selection is strong enough to override gene flow. Genetic differentiation in various stress-resistance traits has been shown in five closely spaced populations of D. buzzatii and Drosophila simulans on the neighbouring island of La Gomera, even though gene flow among the populations was high enough to prevent genetic differentiation in neutral markers (Bubliy & Loeschcke, 2005a; Sarup et al., 2009). Most work on clinal genetic variation has been carried out on populations originating from a latitudinal gradient. Whereas average temperature undoubtedly changes with latitude, so does day length, which might confound results. Also, along latitudinal clines, the sampled populations need to be separated by a considerable distance to be considered as originating from climatic conditions that can be said to differ meaningfully. This requirement inevitably results in comparably low gene flow among the studied populations, which in turn allows the populations to accumulate genetic differences in quantitative traits by genetic drift.

Although the investigated populations were closely spaced with presumably high gene flow, the possibility of diversification in quantitative characters because of genetic drift should not be neglected. QST is a measure that quantifies the genetic differences in quantitative traits among populations comparable to the way FST sums up the genetic differences among populations. QST can be used to distinguish divergence in quantitative traits among populations that is attributable to genetic drift from signs of natural selection. It also can be compared to FST estimated from divergence in presumably neutral markers (microsatellites). Merila & Crnokrak (2001) suggested that a QST larger than FST could signal diversification driven by natural selection. However, this conclusion is valid only if the confidence interval of the QST value, and not only the QST value itself, lies outside the confidence interval of the FST value (Whitlock, 2008).

Populations adapted to high-temperature environments generally remain active longer at high temperatures, resulting in a clear clinal pattern in the knock-down resistance; thus, we expected to identify a negative relationship between altitude and knock-down resistance (Dahlgaard et al., 2001; Hoffmann et al., 2002; Sørensen et al., 2005; Sarup et al., 2006). Increased starvation resistance can result from direct selection for starvation resistance (Harshman et al., 1999) but can also arise as a correlated response to selection for many kinds of stress resistance (Bubliy & Loeschcke, 2005b). For D. buzzatii, food resources (rotting cladodes of Opuntia cacti) could be scarcer at the highest collection sites because of a lower frequency of rots, which might select for higher starvation resistance in highland populations. Indeed, a regression with a positive slope of starvation resistance on altitude in D. buzzatii has been reported previously (Sørensen et al., 2005; Sarup et al., 2009), and a higher starvation resistance has been identified in northern (compared to southern) populations of Drosophila ananassae, Drosophila melanogaster and Zaprionus indianus (Karan et al., 1998). However, a negative relationship between altitude and starvation resistance has been reported in other species of Drosophila (Parkash et al., 2005).

Many stress-resistance traits have been positively linked to longevity (Chippindale et al., 1998; Hoffmann & Harshman, 1999; Norry & Loeschcke, 2002), including starvation resistance, but strains selected for stress resistance are not necessarily long-lived (Archer et al., 2003; Bubliy & Loeschcke, 2005b; Baldal et al., 2006). Altitudinal variation in longevity has been found to differ between rearing regimes and sexes in D. buzzatii (Norry et al., 2006) where female longevity has a negative relationship with altitude after development at 25 °C, but high-altitude males reared at 29 °C live longer than males from low altitudes. A shorter life span in high-altitude females is also found in Sepsis cynipsea (Blanckenhorn, 1997) and in high-altitude Melanoplus grasshoppers (Tatar et al., 1997). The short lifespan in high-altitude populations might be a reaction to a short breeding season, at least in grasshoppers that do not overwinter as adults.

In the current work, we expected and found that any differentiation in quantitative traits would primarily be driven by natural selection, resulting in QST values that significantly exceeded FST values. Clinal variation did change when the rearing regime changed. This result stresses the importance of determining whether populations originating from different environments differ in their plastic responses to stress.

Materials and methods

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Origin and maintenance of flies

Flies were collected in October 2004 at nine sites at increasing altitude on the southern part of the island of Tenerife. Geographic coordinates were determined with a global positioning system (Table 1). The temperatures during the collection were recorded on data loggers (ACR systems Inc., Surrey, B.C, Canada) and were representative of the Canarian summer climate. Table 1 gives maximum (day) and minimum (night) temperatures during collection at each site. At collection sites 1–3, the climate was hot and dry when compared with the relatively cool and humid climate at localities 6–9. Localities 4 and 5 had intermediate temperature and humidity values.

Table 1.   Position, altitude, and maximum and minimum temperatures during collection at collection sites for the populations.
PopulationPositionAltitude (m a.s.l.*)Min. temp (°C)Max. temp (°C)
  1. *Metres above sea level.

128°03.48′N, 16°32.68′W10919.333
228°04.07′N, 16°42.78′W13318.235.5
328°05.22′N, 16°33.96′W3181628
428°06.48′N, 16°34.69′W55514.531
528°07.47′N, 16°35.42′W82513.531
628°07.99′N, 16°36.06′W93511.331
728°07.25′N, 16°40.00′W106810.628
828°08.27′N, 16°37.03′W1142928
928°08.64′N, 16°37.38′W12719.527

From each of the nine localities, 10 isofemale lines were established. The lines were maintained at 25 °C with 15 mating pairs for 24 h in each of six bottles with 21 mL of instant Drosophila medium with live yeast added (Carolina Biological Supply, Burlington, NC, USA). Throughout the experiments, instant Drosophila medium was used unless stated otherwise. All experiments were conducted within 4–7 generations after collection and with two sets of flies. One set was kept at 25 °C throughout development, and the other set was subjected to a fluctuating thermal regime of 21 °C (20 h)/35 °C (4 h) 2 days after egg laying.

Knock-down resistance

Flies less than 24 h post eclosion were collected from five random lines from each rearing environment and collection site and transferred to agar-sugar-oatmeal-yeast medium vials at a density of approximately 50 (equal number of both sexes) with three replicates per line. They were placed at 25 °C and transferred to fresh vials every second day. When flies were between 4 and 5 days old (post-eclosion), the knock-down test (Huey et al., 1992) was conducted as described in Sørensen et al. (2001) at a constant temperature of 40.7 ± 0.1 °C for flies raised at 25 °C and 41.7 ± 0.1 °C for flies raised at 21 °C (20 h)/35 °C (4 h). Flies from locality 6 had a slower development at the fluctuating temperature compared to those from other localities, which resulted in problems with synchronizing the flies’ emergence. Therefore, flies reared at fluctuating temperatures from locality 6 were not tested for knock-down resistance. The flies from the different rearing regimes differed greatly in knock-down resistance, to the extent that we could not identify a test temperature that did not result in either almost-immediate or very slow knock-down in a given regime. Either situation would disguise any difference in thermal tolerance among the populations in one of the rearing regimes but not the other, giving rise to a significant but biologically meaningless interaction between rearing regime and population. For this reason, we set the knock-down temperature for each rearing regime so that on average, it took 20 min to knock down all the flies in a replicate across populations. This approach standardized the stress exposure of the flies from the two rearing regimes, making it possible to do a meaningful test of the interaction among rearing regime, population and sex using a three-way anova with lines nested within populations (excluding the locality 6 population).

Starvation resistance

From nine lines of flies reared at 25 °C and for five randomly selected lines of flies reared at 21 °C (20 h)/35 °C (4 h) from each collection site, freshly emerged flies (< 12 h post eclosion) were sexed under light CO2 anaesthesia and transferred to agar vials (to prevent desiccation) with 20 flies per vial and three vials per sex and line. The flies from the different rearing regimes differed so greatly in starvation resistance that when a significant proportion of the flies reared at 25 °C had died, almost all flies reared at 21 °C (20 h)/35 °C (4 h) were still alive. When only a small proportion (≤ 10%) of the more resistant flies had died, all flies reared at the constant temperature were dead. Thus, if the flies from the two rearing regimes were starved for the same number of hours, the results could not reveal difference in thermal tolerance among the populations in one of the rearing regimes but might do so in the other rearing regime, giving rise to a significant but biologically meaningless interaction between rearing regime and population. Instead, the flies were starved until, on average across populations, 50% of the flies were dead. This approach led to designation of the following time points for scoring populations for survival: males for 116 h and females for 140 h if reared at 25 °C; and males for 143 h and females for 167 h if reared at 21 °C (20 h)/35 °C (4 h). The standardized stress exposure of the flies from the two rearing regimes made it biologically meaningful to test the interaction among rearing regime, population and sex using a three-way anova with lines nested within populations (only including the lines and populations that were tested in both rearing regimes). Because of the synchronization problems, flies from locality 6 were not tested under the fluctuating rearing regime. Also, because survival was calculated as proportions, the arcsine-square-root transformation was applied to improve normality and homogeneity of variances.

Longevity

Flies reared at 25 °C or 21 °C (20 h)/35 °C (4 h) were collected < 24 h after eclosion from five random lines from each population and transferred to agar-sugar-oatmeal-yeast medium vials at a density of 20 (equal number of both sexes) with three replicates/line. Flies were returned to the temperature regime at which they were reared. Every second day, the flies were transferred to fresh food vials, and dead flies were sexed and scored. The number of vials was gradually reduced as deaths occurred, with surviving flies being keep at a density as close to 20 per vial as possible.

Genetic differentiation in neutral markers

DNA was extracted from between 28 and 30 wild-caught flies from each population with equal numbers of males and females using the Hexadecyltrimethylammonium bromide (CTAB) method modified from Doyle & Doyle (1987). The flies were genotyped using 15 microsatellite loci (Db003, Db013, Db034, Db052, Db087, Db090, Db109, Db122, Db142, Db223, Db225, Db290, Db411, Db493 and Db681) (see Frydenberg et al., 2002; loci given with M instead of Db; and Barker et al., 2009, for primer sequences, chromosomal location and genetic variation). The number of alleles per locus ranged from 2 to 5 (Table 2). The analysis of Db087, Db122, Db142, Db223, Db225, Db290, Db411, Db493 and Db681 was performed on a Beckman CEQ8000 sequencer (Beckman Coulter, Brea, California, USA) with 5′-labelled (ResGen) forward primers, while the remaining loci were run on an ALF-express sequencer.

Table 2.   Properties and references for the microsatellite loci used.
Locus nameChromosomal locationSize rangeNumber of allelesReferences
M003?252–2603Barker et al., 2009
M013274–884Barker et al., 2009
M0342252–2583Barker et al., 2009
M522141–1554Frydenberg et al., 2002
M874163–2033Frydenberg et al., 2002
M0905185–1954Barker et al., 2009
M1092151–1675Barker et al., 2009
M1224217–2212Frydenberg et al., 2002
M1424194–2064Frydenberg et al., 2002
M2235227–2292Frydenberg et al., 2002
M2255166–1723Frydenberg et al., 2002
M2902167–1793Frydenberg et al., 2002
M4112234–2484Frydenberg et al., 2002
M4932165–1692Frydenberg et al., 2002
M6814255–2753Frydenberg et al., 2002

Statistics

The effects of rearing regime, population and sex were tested by a three-way anova with isofemale lines nested within populations using JMP v.7 (SAS, 2007), including only the lines and populations that were tested in both rearing regimes (i.e. five lines from each of eight populations, excluding the population originating from locality 6, for all traits except longevity, for which nine populations were tested). As there were significant interactions among rearing regime and population or sex in all traits, main effects were tested using the joint factor test in JMP. For traits for which the effect of population was significant, trait measures were regressed on the altitude of the populations. To test for nonlinear relationships, quadratic and cubic terms were included, and the explanatory variable with the highest R2 was chosen as the best descriptor. Because longevity was not normally distributed and transforming the data did not change this, differences in lifespan among populations were tested using a proportional hazards model, and median lifespan of the lines was used in the regressions.

Also, for knock-down and starvation resistance, individual nested anovas were performed for each combination of sex and rearing regime (as we found significant interactions between sex and population and between rearing regime and population in both traits) to estimate divergence in quantitative traits (QST), which was calculated as follows:

  • image

(Merila & Crnokrak, 2001), where sGb is the among-populations genetic variance, and sGw is the among-lines, within-populations genetic variance, both estimated as variance components in the hierarchical anova. The 95% confidence limits of the QST values were estimated using resampling without replacement.

The microsatellite loci were checked for null alleles using FreeNA (Chapuis & Estoup, 2007). We analysed genetic differentiation among populations (FST; Wright, 1951) using Fstat 2.9.3.2 (Goudet, 1995) and tested the significance of FST using 1000 permutations in hierfstat for R (Goudet, 2005).

Results

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Knock-down resistance

The populations differed in their response to developmental acclimation, as can be seen from the significant effects for rearing regime × population (Table 3). Also, the sexes differed in their variance in starvation resistance among populations. All main effects were significant, indicating genetic variation in knock-down resistance both within (line) and among populations (Table 3).

Table 3.   Results of anovas and joint factor tests.
SourceKnock-downStarvation
MS*d.f.†PMS*d.f.†P
  1. *Mean squares.

  2. †Degrees of freedom.

Line (pop)808136< 0.0010.38928< 0.001
Pop186197< 0.0010.6717< 0.001
Sex268781< 0.012.2771< 0.001
Rearing218431< 0.016.2591< 0.001
Sex*rearing596451< 0.0010.0341NS
Sex*pop67937< 0.050.0897< 0.05
Rearing*pop81627< 0.010.4187< 0.001
Sex*rearing*pop33837NS0.0137NS
Error286494 0.036366 
Joint factor test
Term
 Line808136< 0.0010.38928< 0.001
 Pop860064< 0.0010.35356< 0.001
 Sex989916< 0.0010.20316< 0.001
 Rearing1012116< 0.0010.66116< 0.001

At 25 °C, the regression of knock-down resistance on altitude was not significant. At 21 °C (20 h)/35 °C (4 h), we found that significant clinal variation and altitude explained 17.1% of the variation in knock-down time in males (Fig. 1). We found significant quantitative genetic divergence (QST) in male knock-down resistance (Table 4).

image

Figure 1.  Knock-down resistance in seconds ± SE at 41.7 °C for males reared at fluctuating temperatures [21 °C (20 h) and 35 °C (4 h)] (open symbols) and at 40.7 °C for males reared at a constant 25 °C (closed symbols) plotted against altitude. After fly development at fluctuating temperatures, the regression on altitude was significant (β = −0.0785 s m−1; < 0.01). Metres above sea level is abbreviated as m a.s.l.

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Table 4.   Variance components for nested anovas with significant population effects knock-down resistance in males reared at fluctuating temperatures (KD♂ 35), starvation resistance in males reared at constant temperatures (ST♂ 25) and in females at fluctuating temperatures (ST♀ 35).
 KD♂ 35ST♂ 25ST♀ 35
  1. P values: *< 0.05; **< 0.01; ***< 0.0001.

Pop3005*0.013***0.020***
Line1773**0.049*0.031**
Residual69670.0190.027
QST0.459 ± 0.110.120 ± 0.010.244 ± 0.05

Starvation resistance

The populations differed in their response to developmental acclimation, as can be seen from the significant effects for rearing regime × population (Table 3). All main effects were significant, indicating genetic variation in starvation resistance both within (line) and among populations (Table 3).

At 25 °C, we found significant clinal variation in both sexes, with altitude explaining 10.9% of the variation (Fig. 2) in males and 7.9% of the variation (Fig. 3) in females. For males, QST for starvation resistance is given in Table 4; in females, the population effect was not significant (Fig. 3).

image

Figure 2.  Starvation resistance ± SE in males reared at fluctuating temperatures [21 °C for 20 h and 35 °C for 4 h (143 h)] (open symbols) and reared at a constant 25 °C (116 h) (closed symbols) plotted against altitude. After rearing at 25 °C, there was a significant regression on altitude (β = −0.00021 m−1, < 0.01), as was also the case after rearing at fluctuating temperatures cubed (β = −1.25 × 10−10 m−1; < 0.05). Metres above sea level is abbreviated m a.s.l.

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image

Figure 3.  Starvation resistance ± SE in females reared at fluctuating temperatures [21 °C for 20 h and 35 °C for 4 h (167 h)] (open symbols) and reared at a constant 25 °C (140 h) (closed symbols) plotted against altitude. In females reared at 25 °C, there was a regression on altitude (β = −0.00016 m−1; < 0.05), and after rearing at fluctuating temperatures, there was a significant regression on altitude cubed (β = −1.32 × 10−10 m−1, P < 0.001). Metres above sea level is abbreviated m a.s.l.

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Also at 21 °C (20 h)/35 °C (4 h), we found significant clinal variation in starvation resistance in both sexes, with altitude cubed (Fig. 2) explaining 13.9% of the variation in starvation resistance in males. In females, altitude cubed (Fig. 3) explained 12.6% of the variation, and QST for starvation resistance is given in Table 4, while in males the population effect was not significant.

Longevity

In both rearing regimes, we found a significant effect on lifespan of population × sex (Table 5), indicating that the sexes differed in their variance in lifespan among populations. However, individual analysis for each combination of sex and rearing regime confirmed the genetic variation in lifespan among populations (results not shown).

Table 5.   Results of proportional hazards analysis of lifespan in flies reared and kept at either constant 25 °C or fluctuating temperatures (21 °C for 20 h and 35 °C for 4 h).
Rearing temp. Sourced.f.25 °C21/35 °C
χ2Pχ2P
Line (pop)36732< 0.001405< 0.001
Pop8284< 0.001196< 0.001
Sex11590< 0.0011130< 0.001
Pop*sex870< 0.00137< 0.001

Genetic differentiation in neutral markers

No null alleles were detected in any of the loci. Significant global genetic differentiation among populations was found with FST = 0.009, with a 95% confidence interval of 0.003–0.017 obtained by bootstrapping. There were significant deviations from Hardy–Weinberg expectations among populations (e.g. Wahlund effect, Wahlund, 1928; test based on 1700 randomizations, < 0.001), resulting in an FST value significantly different from zero (< 0.001; test based on 1000 permutations), but not within populations (HO, HE and FIS values can be found in the Supporting Information Appendix S1).

Discussion

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Even though the average temperature of the fluctuating rearing regime was slightly lower than the temperature in the constant rearing regime (23.3 °C versus 25 °C), flies from the fluctuating temperature regime were more resistant to starvation and heat knock-down, as can be seen from the increased stress level needed to elicit a response in these flies compared with flies reared at 25 °C. This result implies that variation in temperature is of greater importance to the acclimation response of thermal-resistance traits than average temperatures.

The populations were genetically differentiated in both stress-resistance traits and presumed neutral characters. With QST values between 0.12 and 0.45, our estimates fell in the low to middle range reported in reviews of QST studies (Merila & Crnokrak, 2001; Leinonen et al., 2008), but as the FST values for presumably neutral markers among the D. buzzatii populations on Tenerife are much lower than what is reported in most of these studies, the difference between QST and FST fell between 0.11 and 0.44 and was equal to or above the average reported by Leinonen et al. (0.12 ± 0.27). When we found significant genetic differentiation in quantitative traits, the calculated QST always exceeded the FST value by an order of magnitude. A difference of this size is not likely to stem from dominance effects, which can inflate the difference between QST and FST but normally not by more than 10% (Santure & Wang, 2009). As the sampling scale (a few kilometres) was low compared to the dispersal capacity of Drosophila, the high QST value was not likely to be caused by an unaccounted population substructure, which can also give rise to elevated QST values (Martin et al., 2008). Instead, the results imply that the observed differences are not mainly caused by random drift but rather by directional selection presumably driven by climatic differences.

The significant rearing regime × population interaction indicated that the populations differed in the magnitude of the acclimation response in both starvation and knock-down resistance, which resulted in significant population effects in only some combinations of rearing regime and sex. This finding could dramatically change the conclusions formed based on comparison of QST with FST. If only uniform rearing conditions had been applied in this study, the conclusion would have been that only starvation resistance in males showed signs of genetic differentiation in quantitative traits.

Generally, in the cases in which we found a significant population effect, the high-altitude populations displayed less stress resistance than populations originating from warmer sites. However, the pattern was a little more complicated in starvation resistance after development in the fluctuating temperature regime; here, there was a significant nonlinear relation with altitude. Such nonlinear effects have been seen in D. buzzatii before (Sarup et al., 2006, 2009) and may be the result of the larger effect of gene flow in marginal populations at species borders (Eckert et al., 2008).

Knock-down resistance showed the expected negative relationship with altitude although only in males reared at 21 °C (20 h)/35 °C (4 h), again confirming the ecological relevance of this trait (Hoffmann et al., 2002; Sørensen et al., 2005) and the presence of sex-specific responses to selection. In a related study, the authors did not find any significant correlation between the sexes in knock-down resistance in five populations collected along an altitudinal gradient in either D. buzzatii or D. simulans (Sarup et al., 2009). When Hoffmann et al. (2005) examined the relationship between rearing regime and clinal variation of knock-down resistance in D. melanogaster from Australia, in contrast to our results, they found no differences in the plastic response of flies reared under either summer or winter temperature and light conditions. These contrasting results could arise from differences in the way the two species react to selection for knock-down resistance, perhaps because of differences in their genetic makeup, or because both species potentially can respond to selection by changing the basal resistance or the magnitude of the acclimation response (or both). Either possibility remains to be investigated.

Starvation resistance showed clinal variation. In both sexes and rearing regimes, the lowland populations survived better than the highland populations. This finding is contrary to our expectations and to prior results with D. buzzatii (Sørensen et al., 2005; Sarup et al., 2009). Increased starvation resistance can be a correlated response to selection for many types of stress resistance (Bubliy & Loeschcke, 2005b). Thus, as we collected the flies from La Gomera in autumn, it could be that the higher starvation resistance in lowland populations may be a correlated response to selection for increased resistance towards other stresses in the lowland populations, which presumably are heat stressed during summer.

Although we did find genetic variation in lifespan among populations, there was no cline in longevity under either rearing regime. This outcome might be the result of a lack of power in the analysis or of a lack of relationship between longevity and knock-down or starvation resistance in this study. The conflicting findings regarding the connection between stress resistance and longevity (Hoffmann & Harshman, 1999; Norry & Loeschcke, 2002; Norry et al., 2006) might be the result of differences in the genetic background or the selection regimes.

For both starvation and knock-down resistance, the proportion of the variation that could be explained by altitude was low (7.9–17.1%). One possible reason for this observation could be differences in microclimate and biotic environment at the collection sites that are not explained by altitude. Nonetheless, the R2 values were comparable to many of the values found in a study of populations along a latitudinal gradient where climatic conditions differed more than in our study (Sarup et al., 2006).

Finally, clinal variation did change when the rearing regime changed. Even though this is not always the case (Hoffmann et al., 2005), this result stresses the importance of examining whether populations originating from different environments differ in their plastic responses to stress, which could either increase or decrease difference in stress resistance among populations in a natural environment.

Acknowledgments

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

The authors are grateful to Doth Andersen and Mia F. Nielsen for technical assistance, to Stuart Barker, Torsten Kristensen and Cino Pertoldi for helpful comments on the manuscript, to the Sr. Consejero de Medio Ambiente, Excmo. Cabildo Insular de Tenerife, for permitting us to collect flies, and to the Danish Natural Sciences Research Council (frame and centre grant to V.L.) and Lundbeck Foundation, Carlsbergfondet and the Faculty of Sciences, University of Aarhus (stipend to P.S.), for financial support.

References

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Supporting Information

  1. Top of page
  2. Abstract
  3. Introduction
  4. Materials and methods
  5. Results
  6. Discussion
  7. Acknowledgments
  8. References
  9. Supporting Information

Appendix S1 Expected and observed heterozygosities, FIS, number of alleles genotyped and P value.

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