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Supporting Information 1
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Methods and results
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Specific growth rates
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Lengths were measured at the beginning of the experiment (March 23), on May 3 (day
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42), and again for the 22°C fish on June 11 (day 81) and for the 7°C fish on November 17 (day
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242). Specific growth rate (SGR) for length was measured according to the formula:
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SGR = % length (mm)/day = [(ln Lt2 – ln Lt1) / (t2 – t1)] x 100,
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where Lt1 and Lt2 are the fork lengths (mm) at the beginning and end of the experiment,
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respectively. SGR was calculated for each population per tank (fish were not individually
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marked), and the tank averages used in an ANOVA to assess whether experimental populations
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differed in growth rates.
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Significant differences in growth rate reaction norms were observed between populations
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during the first forty-two days of the experiment (population F3,14 = 15.6, p < 0.001, temperature
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F1,14 = 115, p < 0.001, population x temperature F3,14 = 6.6, p = 0.005), with marine populations
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growing slower than freshwater populations at 22°C. The trend for slower growth in the marine
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populations held for the duration of the experimental trial but was statistically significant only
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for the first 42 days (comparing populations between day 1 and the end of the experiment, ~1700
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GDD, population F3,14 = 0.9, p = 0.49, temperature F1,14 = 130, p < 0.001, population x
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temperature F3,14 = 1.0, p = 0.42, tank F1,17 = 0.02, p = 0.9).
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Population-level comparisons of gene expression
Methods before model fitting are identical to those found in text, with the exception that
the microarray data was not filtered, so as not to violate variance assumptions implicit in
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LIMMA. Data were then fit with an empirical Bayes linear regression model developed by
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Smyth (2004, 2005). LIMMA employs a two-step procedure. The first step fits the data to the
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linear model; the second step returns t-statistics and p-values for the contrasts of interest. To
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reduce the False Discovery Rate resulting from multiple hypothesis testing, α was adjusted using
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the Benjamini-Hochberg (BH) method (Benjamini and Hochberg 1995). This method cannot be
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used to make inferences beyond the four populations studied. A 4 x 2 factorial design was tested
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in LIMMA, with the four populations (HLF, CLF, OLM, and LCM) and the two temperatures
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(7ºC and 22ºC) as factors. Differences in transcript abundance were assessed between
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temperatures for each population.
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Both freshwater populations had more genes respond to temperature than either marine
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population (Supp. Figure 3) (CLF = 5468 genes, HLF = 4971 genes, OLM = 3954 genes, LCM =
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2526 genes). The least-plastic freshwater population (HLF) was significantly more plastic than
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the most-plastic marine population (OLM) (χ2 = 49.9, d.f. = 1, p < 0.001).
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Gene enrichment analysis for genes that exhibited gene expression plasticity in both freshwater
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or both marine populations only
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LIMMA isolated genes differentially expressed in both marine or both freshwater
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populations only. Using the 943 genes that were differentially expressed in both freshwater
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populations, and the 153 genes that were differentially expressed in both marine populations, we
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used GOEAST as described in the main text to identify enriched gene classes for those genes up-
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regulated at 7ºC or 22ºC. 69% of these genes had GOIDs that were used in these analyses.
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At 22ºC, the freshwater stickleback shared four enriched gene classes (three cellular, one
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molecular): proteinaceous extracellular matrix (6 of 48 genes), prefoldin complex (2 of 9 genes),
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Z disc (2 of 8 genes), and structural molecule activity (12 of 237 genes). The marine stickleback
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shared five enriched gene classes (one biological, one cellular, three molecular): metabolic
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process (18 of 4073 genes), mitochondrial respiratory chain (2 of 7 genes), cytochrome-c oxidase
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activity (2 of 20 genes), heme binding (4 of 98 genes), and electron carrier activity (3 of 97
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genes). The three enriched classes pertaining to mitochondrial activity contained four unique
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genes: CYP3C1, CYP2Y3, COX7A3, and COX6A2.
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At 7ºC, there were many enriched gene classes unique to the freshwater stickleback. The
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marine stickleback shared three enriched gene classes (two biological and one molecular):
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translation (5 of 228 genes), protein folding (3 of 84 genes), and growth factor activity (3 of 91
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genes). The freshwater stickleback, on the other hand, shared 16 enriched gene classes (6
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biological, 5 cellular, 6 molecular): ATP synthesis coupled proton transport (8 of 14 genes),
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aerobic respiration (6 of 19 genes), ATP hydrolysis coupled proton transport (5 of 25 genes),
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embryonic epithelial tube formation (3 of 7 genes), nucleocytoplasmic transport (11 of 144
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genes), GTP catabolic process (15 of 222 genes), mitochondrial proton-transporting ATP
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synthase complex, coupling factor F(o) (4 of 6 genes), proton-transporting ATP synthase
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complex, catalytic core F(1) (3 of 5 genes), proton-transporting two-sector ATPase complex,
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proton-transporting domain (7 of 19 genes), proton-transporting V-type ATPase complex (3 of
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17 genes), hydrogen ion transmembrane transporter activity (17 of 74 genes), acyl-CoA
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dehydrogenase activity (4 of 14 genes), purine ribonucleoside triphosphate binding (65 of 1582
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genes), GTPase activity (17 of 293 genes), carbohydrate kinase activity (4 of 19 genes), and
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coenzyme binding (9 of 123 genes). The large number of enrichment classes pertaining to
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mitochondrial biogenesis and activity, that were significantly enriched in both freshwater but
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neither marine population, supports the findings of the main paper: that adaptation to freshwater
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has evolved in part through the parallel evolution of physiological plasticity pertaining to
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mitochondria.
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Although the LIMMA analysis is not suitable for making generalized inferences, the
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freshwater core suggests that differences between freshwater populations are not due solely to
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drift – parallel evolution may have occurred in response to similar novel temperature conditions
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in freshwater lakes.