doi:10.1111/j.1420-9101.2005.01016.x
Altitudinal patterns for latitudinally varying traits and polymorphic markers in Drosophila melanogaster from eastern Australia J. E. COLLINGE,* A. A. HOFFMANN & S. W. MCKECHNIE* *Centre for Environmental Stress and Adaptation Research (CESAR), School of Biological Sciences, Monash University, Victoria, Australia Centre for Environmental Stress and Adaptation Research (CESAR), Department of Genetics, The University of Melbourne, Victoria, Australia
Keywords:
Abstract
altitude variation; Drosophila; fitness-related traits; heat-shock gene polymorphism; microsatellites; thermal tolerance.
Altitudinal changes in traits and genetic markers can complement the studies on latitudinal patterns and provide evidence of natural selection because of climatic factors. In Drosophila melanogaster, latitudinal variation is well known but altitudinal patterns have rarely been investigated. Here, we examine five traits and five genetic markers on chromosome 3R in D. melanogaster collected at high and low altitudes from five latitudes along the eastern coast of Australia. Significant altitudinal differentiation was observed for cold tolerance, development time, ovariole number in unmated females, and the microsatellite marker DMU25686. Differences tended to match latitudinal patterns, in that trait values at high altitudes were also found at high latitudes, suggesting that factors linked to temperature are likely selective agents. Cold tolerance was closely associated with average temperature and other climatic factors, but no significant associations were detected for the other traits. Genes around DMU25686 represent good candidates for climatic adaptation.
Introduction Because altitudinal changes occur over relatively small distances, there is generally a more rapid change in environmental conditions, especially temperature, compared with equivalent distances over latitudinal gradients (Heath & Williams, 1979; Baur & Raboud, 1988). As a consequence, for a given temperature change, higher gene flow is more likely along altitudinal gradients compared with latitudinal gradients (Blanckenhorn, 1997). Altitudinal genetic differentiation is therefore less likely to be an effect of nonadaptive processes like founder effects and can be more easily attributed to natural selection, with temperature being a strong candidate selective agent. In Drosophila, altitudinal gradients have been studied less frequently than latitudinal gradients. Exceptions include altitudinal clines in inversion polymorphisms in D. robusta (Etges & Levitan, 2004), a cline in wing shape in D. mediopunctata (Bitner-Mathe et al., 1995), and altitude differences for wing length, oviposition activity, heat/ Correspondence: Stephen W. McKechnie, Centre for Environmental Stress and Adaptation Research (CESAR), School of Biological Sciences, Monash University, Victoria 3800, Australia. Tel.: 61 3 9905 3863; fax: 61 3 9905 5613; e-mail:
[email protected]
desiccation responses and hsp70 expression in D. buzzatii (Dahlgaard et al., 2001; Sørensen et al., 2001, 2005). No differentiation was detected in D. buzzatii for eight traits over a short altitudinal transect in the Canary Islands (Bubliy & Loeschcke, 2005). In D. melanogaster from eastern Australia, latitudinal clines have been reported in cold tolerance, heat resistance, ovariole number, development time and body size (James et al., 1995; James & Partridge, 1995; Azevedo et al., 1996; Hoffmann et al., 2002). Some of these traits also show parallel clines on other continents and in other Drosophila species (Watada et al., 1986; Capy et al., 1993; Starmer & Wolf, 1997; Van’t Land et al., 1999; Hallas et al., 2002), which suggests that the traits are under climatic selection. Additionally, thermal laboratory selection experiments have implicated temperature as the agent of selection for variation in clinal body size, development time and wing shape (Partridge et al., 1994a; Santos et al., 2004). At the genetic level, there are several molecular markers on chromosomes 2 and 3 in D. melanogaster that shows latitudinal variation. These mark blocks of genes that are potentially involved with climatic adaptation (Weeks et al., 2002). Markers on chromosome 3, especially on the right arm, are of particular interest as this region contains genes that are involved with variation in thermotolerance and body size (Cavicchi et al., 1989; Partridge
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et al., 1994b; Bettencourt et al., 2002; Weeks et al., 2002; Anderson et al., 2003). Along the eastern coast of Australia, polymorphic genetic markers on chromosome 3R that show a latitudinal cline include hsr-omegaL/S, hsp70, DMU25686, DMTRXIII and AC008193 (Gockel et al., 2001; Bettencourt et al., 2002; Anderson et al., 2003). Here we considered altitudinal variation in these third chromosome markers and traits by examining flies from high and low elevation sites at five locations along the eastern Australian latitudinal gradient. In this way, we could directly compare the degree of altitudinal variation relative to latitudinal variation. Population variation in traits and markers were compared with variation in climatic parameters to test if latitudinal and altitudinal patterns were associated with climate variables, irrespective of the physical distance between sites.
Methods Collection sites Isofemale lines were set up from field-inseminated females collected from paired locations in February and March 2002. The females were collected from high and low altitude from five different latitudes along the eastern coast of Australia (Fig. 1) using banana bait traps (Tidon & Sene, 1988). Table 1 gives site locations and the
Fig. 1 Collection sites showing the five paired latitudinal locations. Bold font indicates low altitude sites.
number of isofemale lines established from each site, along with climatic variables (mean temperature, rainfall and humidity). Continent-wide surfaces for these variables were interpolated from weather station data (>30 years) with the program A N U C L I M (Houlder et al., 2000) using a 0.05 resolution digital elevation model (DEM) (Hutchinson & Dowling, 1991) and data for exact collection locations were then determined with A R C V I E W (http://www.esri.com/software). High altitude sites were cooler and tended to have a lower humidity than low altitude sites from the same latitude. Flies were reared on potato medium under the same constant temperature (18 C), light (12D : 12L) and humidity conditions for a number of generations in the laboratory so that environmentally induced phenotypic plasticity was diminished and genetic differences could be observed (Berven, 1982b). Mass-bred populations were founded by pooling 15 F7progeny from 17 different isofemale lines for each collection location. These populations were left for two generations as massbreds and then tested for the quantitative traits (except ovariole number) and for the molecular markers. Ovariole number was scored directly with flies from some of the isofemale lines (five lines per population) just prior to establishment of the mass-bred lines. Traits For all traits, the influence of altitude and latitude was tested by comparing the populations. Additional factors were tested for several of the traits, because of the presence of a hardening treatment (heat resistance), mating status effect (ovariole number) and sex effect (size). Cold tolerance was measured on the mass-bred populations using a chill coma recovery assay similar to that described in Gibert & Huey (2001). Populations were reared at 18 C under low-density conditions, by limiting oviposition by 25 adults to 4 days in 275 mL bottles containing 65 mL Drosophila potato medium [potato mash (2% w/v), sugar (3%), agar (0.6%), yeast (3.1%), nipagin (0.11%) and propionic acid (0.5%)]. Females were collected for chill coma 4 – 6 days posteclosion. Ten females were placed in empty 42 mL capped glass vials for each population and randomized. The vials were placed in a 0 C water bath (containing ethylene glycol) for 4 h. Vials were removed from the water bath and allowed to recover at 25 C because this temperature provides a range of recovery times but still allowed several replicate experiments to be completed within a day. Recovery was scored every minute for each fly. A fly was considered recovered when it was able to stand. This process was repeated four times (four replicate ‘runs’ of 10 flies per population). Heat resistance was measured on individual females from mass-bred populations using a heat knockdown assay (Hoffmann et al., 1997). Populations were reared
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Table 1 Collection and climate details for five paired latitudinal collection sites. Location
Altitude (m)
Latitude
Longitude
N*(I)
Rainfall (mm)
Mean temperature (C)
Humidity
Malanda Innisfail Springbrook Kingscliff Armidale Coffs Harbour Blackheath Wollongong Adaminaby Bega
800 10 1031 10 1296 14 1046 10 1025 60
1719¢S 1730¢S 2814¢S 2817¢S 3031¢S 3022¢S 3338¢S 3425¢S 3559¢S 3641¢S
14531¢E 14560¢E 15316¢E 15307¢E 15141¢E 15306¢E 15017¢E 15052¢E 14846¢E 14950¢E
138 138 68 172 134 106 96 96 102 72
1610 3494 2160 1893 739 1671 1187 1325 741 880
19.6 23.4 15.9 19.5 12.7 18.1 10.9 16.8 9.3 14.5
70.48 80.85 74.23 75.11 61.85 70.75 68.83 69.62 63.91 67.83
(69) (69) (17) (46) (67) (53) (48) (48) (53) (36)
*number alleles scored from isofemale lines in marker analysis; number of isofemale lines established.
under low-density at 25 C in bottles containing Drosophila potato medium, prior to heat knockdown. This rearing temperature is higher than the temperature used for routine maintenance of the lines (18 C) but population variation in heat resistance is not influenced by rearing temperature (Hoffmann et al., 2005). Individual mated females from these cultures (4 days post-eclosion) were placed in 5 mL capped vials and submerged in a 39 C water bath. Heat knockdown was scored every minute and flies were considered knocked down, if unable to stand. Flies were either tested, after being hardened by a prior no-lethal heat exposure (37 C for 1 h, 6 h prior to testing) or without hardening. Two hardened and two nonhardened flies from each of the 10 populations were tested at the same time and these were arranged in a randomized order. This resulted in 40 females being tested in an assay. The assay process was repeated 18 times (i.e. 18 ‘runs’ of four individual females per population). To measure the ovariole number of each population, five isofemale lines from each population were chosen at random and scored for this trait. Lines were reared at 18 C under low density (20 eggs per 45 mL vial). Two vials, each with 7.5 mL of Drosophila potato medium were set up from each isofemale line. The first vial contained four nonmated females and the second vial contained four females and four males. After 5 days, the females were collected and frozen at )20 C until dissection. Both ovaries were extracted in Becker Ringer’s solution (6.5 g NaCl, 0.14 g KCl, 0.2 g NaHCO3, 0.12 g CaCl2, 0.01 g NaH2PO4 made up to 1 L with water) and stained in saturated potassium dichromate for 4 min (Carlson et al., 1998; Wayne & Mackay, 1998). Excess stain was removed using Ringer solution and the ovarioles from both ovaries were extracted and counted. The number of ovarioles per ovary was averaged over females from a particular isofemale line (i.e. one mated and one nonmated data point per line, five data points per population). Egg to adult development time was determined for the mass-bred populations. One hundred eggs (15%) using PCR and described primers (Gockel et al., 2001). In addition, one primer of each pair was supplemented with an infrared labelled primer (IRDyes). Amplification was carried out with the following cycling conditions: 95 C (2 min); 95 C (1 min), 54 C (1 min), 72 C (1 min) 35 cycles; 72 C (2 min). The reaction reagents include 2 mM MgCl2, 0.2 mM dNTPs, 0.2 pmoles lL)1 each unlabelled primer, 8 nmoles lL)1 labelled primer and 0.5 units Taq polymerase. The PCR products were run on Seqagel at 1500v for 1 h 45 min using the Li-Cor Global IR2 (Li-Cor, Lincoln, NE, USA). Statistical analysis A N O V A s were undertaken to examine the effects of the latitude location along the coast and altitude on the phenotypic traits as well as the interaction between these effects. These factors were treated as fixed effects because we deliberately selected latitude points along the eastern coast and high/low altitude sites. In addition, other factors were included for different traits because these were part of the experimental design. For chill coma resistance, we included an effect of run because a number of replicate runs were undertaken with the flies. For heat resistance, we also included an effect of run as well as hardening as a fixed factor in the analysis. For ovariole number, we tested the fixed effect of mating in the A N O V A , whereas for size we included a fixed effect of sex. The mean development time of vials may have been influenced by the proportion of adults that developed from the 10 eggs. We therefore undertook an analysis of covariance (A N C O V A ) for this trait, using the proportion of females in the flies emerging as a covariate. As well as testing for significance of all factors, we also computed effect sizes (g2) defined as SSeffect/SStotal, the proportion of the total variance that is attributed to an effect. Multiple regression analyses were carried out in exploratory analyses to examine associations between population trait means and the three climatic variables. Under strong climatic selection, we might expect associations between trait means and climatic variables regardless of the distance between populations. Both forward selection and backward elimination were used to determine the regression model that fitted the phenotypic data and thereby suggested climatic variables associated with
the traits. Only the forward selection analyses are presented as the two approaches always led to selection of the same regression model. The association between the frequency of genotypic markers in each population and latitude as well as elevation was tested by A N C O V A . Latitude was treated as a covariate and the effect of elevation on marker frequencies was then tested after angular transformation). Multiple regressions were also used in exploratory analyses to examine if any of the climatic variables were associated with population allele frequencies.
Results Traits For chill coma recovery, the A N O V A indicated significant effects of altitude, latitude, run and an altitude by latitude interaction (Table 3). Populations from higher latitudes were more tolerant of this stress (Fig. 2) and populations from the different latitudes varied in the extent to which chill coma recovery was affected by altitude. Populations from the higher altitude sites had greater cold tolerance at temperate latitudes but not at tropical latitudes. There was a significant effect of runs as typically found for this trait (Hoffmann et al., 2002). A regression of the climatic variables onto chill coma recovery time led to the same final model regardless of whether forward selection or backward elimination was followed. Under forward (and backward) selection, fitting temperature alone led to the strongest association and a highly significant regression (F(1,8) ¼ 13.50, P < 0.01, R2 ¼ 0.63), but the addition of rainfall and humidity further significantly improved the fit of the regression equation (F(1,6) ¼ 25.01, P < 0.001, R2 ¼ 0.88). Chill coma resistance was therefore closely tied to the climatic variables. For heat knockdown resistance, there was a significant effect of run, hardening and latitude on resistance (Table 3). Flies from the northernmost tropical population had the longest knockdown time and heat resistance was increased by hardening as reflected by an increase in knockdown time (Fig. 2). Altitude was marginally nonsignificant and there was a suggestion of increased resistance in the high altitude flies particularly in nonhardened flies (Fig. 2). Interaction effects were not significant in the A N O V A . Population means for heat resistance were not associated with any of the climatic variables in regression analyses regardless of hardening. There was a significant effect of mating as well as altitude for ovariole number, as well as a significant interaction between mating and altitude (Table 4). Mating decreased ovariole number, whereas the effect of altitude on ovariole number depended on mating status (Fig. 3). Nonmated females from low altitude sites showed relatively higher ovariole numbers, whereas there was no altitude effect on ovariole number in mated
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Table 3 Analyses of variance and covariance of trait data.
Trait
Source
d.f.
Mean square
Chill coma
Run Altitude Latitude Alt by Lat Error Hardening Altitude Latitude Run Heat by Alt Heat by Lat Alt by Lat Heat by Alt by Lat Error Mating status Altitude Latitude Mating by Alt Mating by Lat Alt by Lat Mating by Lat by Alt Error Covariate Altitude Latitude Alt by Lat Error Sex Altitude Latitude Sex by Lat Sex by Alt Alt by Lat Sex by Lat by Alt Error
3 1 4 4 746 1 1 4 17 1 4 4 4 675 1 1 4 1 4 4 4 80 1 1 4 4 89 1 1 4 4 1 4 4 180
18 605.15 2023.58 1009.48 1200.21 388.91 1303.83 67.00 165.49 117.86 4.67 39.34 36.77 2.97 18.97 74.43 39.40 3.50 27.64 14.46 9.32 4.23 6.94 2.11 1.97 0.77 0.29 0.11 189.06 1.49 5.16 1.46 0.02 4.10 0.56 1.14
Heat knockdown
Ovariole number
Development time
24
Cold tolerance
50
40
30
20
24
Heat resistance – non-hardened Heat knockdown (min)
60
Heat knockdown (min)
100 - chill coma recovery time (min)
Size
22 20 18 16 14 12
17
28
30
34
36
P
Effect size (g2)
47.84 5.2 2.6 3.09
