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Supporting information for online publication
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Insect collection, rearing and sampling
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For Experiment 1, a plaster nest containing the colony (brood, workers and the queen) was
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put into a plastic box. The box was separated from a second plastic box (the foraging area)
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containing a frozen cricket, sugar water and water tubes. Food and water were supplied twice a
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week at regular days in the foraging area only. Ants needed to cross from the nest area to the
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foraging area through a plastic tube 100 cm long to get access to the food. The top of the rearing
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boxes and the external face of the tubes were covered with Teflon to prevent ants from escaping.
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We assigned workers to two treatment groups according to the observed behavior at the moment of
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collection and independently of the age or size. We labeled as “foraging workers” (out) all the
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individuals that were collected in the foraging area in the process of handling food, water or sugar
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water, while we labeled as “non-foraging workers” (in) all the ants that were sampled within the
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nesting chamber in close proximity to the brood pile. Based on previous observations, foraging
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behavior in fire ants is consistent across time: Mirenda and Vinson (1981) reported that once a
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worker appeared in the foraging area for the first time then it was seen there regularly until death
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and Sorensen et al. (1984) observed in a series of experiments that foragers never went back to
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nursing tasks. These observations are supported by more recent findings in another ant species
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where different behavioral phenotypes of workers showed strong differences in the spatial location
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and spatial fidelity (Mersch et al. 2013).
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For Experiment 2, we prepared two colony fragments from each of 10 colonies. We placed
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the mother queen in one colony fragment (queenright or QR); the other fragment was queenless
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(QL). Each fragment was housed in a plastic pencil box containing a small nesting chamber on one
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side, and a small foraging area on the other side with a frozen cricket, water and sugar water (Figure
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S1). In all colony fragments we transferred equal amounts of brood (a full 0.5ml plastic tube),
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workers (5ml) and winged females (virgin queens, ca. 10) from the original colony. After 5 days, we
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collected foraging and non-foraging workers as above from each fragment. We opted for this time
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window since 5 days seemed a suitable amount of time for behavioral changes to occur: in previous
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studies it has been observed that 48 hours are required to observe a reduction in the rate of sexual
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larvae execution by queenless workers (Klobuchar and Deslippe 2002) and it has been shown that
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the level of workers’ aggression towards conspecifics significantly decreases during the first 5 days
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post-orphaning (Vander Meer and Alonso 2002).
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Samples were collected between 1:30pm and 5:00pm for Experiment 1 and between 9:00am
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and 1:00pm for Experiment 2. Specimens were flash frozen in dry ice and stored at -80 °C until
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processed for molecular work.
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Sample preparation for molecular analyses
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Concentration and purity of RNA samples were assessed using NanoDrop (Thermo Scientific,
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Wilmington, DE) and Qubit 2.0 Fluorometer (Life Technologies, Grand Island, NY) and RNA quality
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was assessed using RNA Nano Chips on the Agilent 2100 Bioanalyzer (Agilent Technologies, Palo
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Alto, CA). One µg of each sample was amplified using the Amino Allyl MessageAmp II aRNA
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Amplification Kit (AM1753, Ambion, Austin, TX). Fifteen µg of aRNA was labeled with Cy3 or Cy5 (GE
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Health Care, Pittsburgh, PA) and subsequently purified according to the Ambion Kit instructions. 1.5
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µg of a Cy3 labeled sample were combined with 1.5 µg of a Cy5 labeled sample and fragmented
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using RNA Fragmentation Reagents (Ambion AM8740, Austin, TX) according to the manufacturer’s
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instructions. Samples were hybridized with mixing in a MAUI hybridization instrument overnight at
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42 °C. Arrays were scanned using Axon GenePix 4000B.
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Protocols for microarray analysis
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Array data were analyzed using two statistical software packages for both experiments. We
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first analyzed array data using SAS (Cary, NC). Any spots with an intensity of less than 300 (equal to
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the mean background level on the arrays) were removed from the analyses, as were spots present
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on less than 20 out of 24 arrays: this reduced the number of probes included into the analyses to
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37,252 for Experiment 1 and 38,511 for Experiment 2. Expression data were log-transformed and
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normalized using a mixed-model normalization (proc MIXED, SAS, Cary, NC) with the following
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model:
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Y = μ + dye + block + array + array*dye + array*block + є
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where Y is expression, dye and block are fixed effects, and array, array*dye and array*block are
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random effects. Transcripts with significant expression differences between groups were detected
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by using a mixed-model ANOVA with the model:
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Y = μ + treatment + spot + dye + array + є
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where Y represents the residual from the previous model. Treatment, spot and dye are fixed effects
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and array is a random effect. In Experiment 1, “treatment” corresponded to the behavioral state of
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the worker ants (i.e. foraging vs. non-foraging workers) while in Experiment 2 “treatment” included
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worker behavioral state (foraging vs. non-foraging), queen effect (presence vs. absence) and their
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interaction. P-values were corrected for multiple testing using a false discovery rate or FDR
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(Benjamini & Hochberg 1995) of < 0.05 (proc MULTTEST, SAS).
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The same array data also were analyzed using R 2.11.1 (Team 2009). Background correction
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(with parameter “normexp+offset=50”) and normalization (“NormalizedWithinArrays” with
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parameter “loess” followed by “NormalizedBetweenArrays” method = “Aquantile”) were done in the
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“limma” package for R (Smyth 2004). For both experiments, we used a direct two-colors design to
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compare gene expression in the different treatment groups. We fit a linear model using the limma
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function “lmFit” and we created a contrast matrix to test all the pairwise comparisons of interest.
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For Experiment 1 we set only one pairwise comparison (foraging vs. non-foraging) since there were
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only two treatment groups. For Experiment 2, the tested pairwise comparisons were the following:
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QRin vs. QLin, QRout vs. QLout, QRin vs. QRout, QLin vs. QLout. We used the limma function
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“eBayes” to estimate a “Bayesian moderate t-statistic” (Smyth 2004), setting the FDR at 0.05. To
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correct for multiple testing across contrasts, we used the limma function “decideTests” with
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method=“separate” and setting the p-value at 0.05.
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For both experiments, analyses with R detected a higher number of significantly
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differentially expressed transcripts compared with SAS: 1387 vs. 771 in Experiment 1 (a significant
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proportion of the differentially expressed transcripts were common to both analyses; see Figure S4)
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and 395 vs. 4 in Experiment 2. Therefore, we relied on the analyses with R to characterize genes that
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were differentially expressed and to perform gene ontology analyses. We used analyses with SAS
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instead to visualize global patterns of gene expression (hierarchical clustering and principal
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component analyses) and to perform studies of directional overlap in queenless workers, since SAS
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outputs were more suitable for these specific analyses. The array data were deposited on the
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ArrayExpress website according to MIAME standards (ArrayExpress ID number will be provided prior
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to publication).
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Validation of differential expression of candidate genes using quantitative real-time PCR
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We used total RNA extracted with RNeasy Plus kit (Qiagen, Valencia CA) from pools of 10
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workers from the same colonies that were used for Experiment 2 and compared gene expression
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between QRin, QRout and QLin using an ABI Prism 7900 instrument (Foster City, CA). cDNA was
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synthesized using SuperScript III First-Strand Synthesis System for RT-PCR (Invitrogen-Life
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Technologies, Carlsbad, CA, USA) and Random Hexamers according to the manufacturer's protocol.
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The cDNA was then diluted 7 times with ultra-pure water. Amplifications were performed in a 10 μl
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reaction mixture containing 5 μl of 2X SYBR Green Master Mix (Applied Biosystems-Life
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Technologies, Carlsbad, CA, USA), 1 μl of each primer (10 μM) and 2 μl of cDNA at the following
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conditions: 50 °C for 2 min, 95 °C for 10 min, 40 cycles of 95 °C for 15 sec and 60 °C for 1 min, a
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dissociation step of 95 °C for 15 sec and 60 °C for 15 sec. We used 9 pools of workers for QLin, 8 for
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QRin and 5 for QRout. Triplicate reactions were performed for each sample and averaged for use in
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statistical analysis. Expression levels of candidate genes were normalized to the geometric mean of
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two housekeeping genes, Rp-9 and Rp-37 (Wurm et al. 2011). Negative control (cDNA reaction
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without RT enzyme) was also used to control for potential contamination by genomic DNA. Primer
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sequences (Table S10) were developed in Primer3Plus (Untergasser et al. 2012) and primer
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efficiency was first validated using standard curves. Statistical analysis was performed with
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nonparametric Wilcoxon comparisons for each pair of treatments in JMP 10 (SAS, Cary, NC). The
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data are shown normalized to the group QRin.
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Expression patterns of all seven candidate genes were consistent with results from arrays,
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although expression differences were significant for two genes only (Figure S6). We examined
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expression of for, which is a major regulator of worker DOL in other social insects: for was slightly
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upregulated in QRin but expression levels were not significantly different across groups. For immune
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response, we examined Hym and spirit: both of these genes were downregulated in QRin and
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expression levels of Hym were significantly different between QRin and QRout (P<0.05) while no
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significant differences were detected for spirit. Finally, mf (chaeta development), mhc (locomotion),
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oat (neurogenesis) and syt1 (neurotransmitter secretion) were all upregulated in QRin: of these
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genes, only oat was significantly differentially expressed between QRin and QRout (P<0.01) and QLin
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and QRout (P<0.05).
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Comparative studies across species
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Alaux et al. (2009) found 937 genes differentially expressed between young nurse and old
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forager worker honey bees from brain tissue. Only 81 genes were in common with our study
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(Representation factor = 0.7, p < 4.81e-06, significantly less than expected by chance) and 1 GO term:
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generation of precursor metabolites and energy.
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Ament et al. (2011) found 1719 genes differentially expressed between nurse and forager
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worker honey bees from fat body tissue. 185 genes were in common with our study (Representation
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factor = 0.8, p < 8.73e-06, significantly less than expected by chance) together with 14 GO terms:
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generation of precursor metabolites and energy, oxidative phosphorylation, mitochondrial electron
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transport, NADH to ubiquinone, energy derivation by oxidation of organic compounds, electron
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transport chain, respiratory electron transport chain, monocarboxylic acid metabolic process,
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response to chemical stimulus, ATP synthesis coupled electron transport, mitochondrial ATP
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synthesis coupled, electron transport, cellular respiration, multi-organism process, response to other
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organism, oxidation-reduction process.
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Toth et al. (2010) found 219 genes associated with foraging and provisioning in the
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primitively eusocial paper wasp Polistes metricus from brain tissue. In this case no GO terms were
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shared with our study and only 26 genes were in common (Representation factor = 0.4, p < 2.02e -14,
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significantly less than expected by chance).
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Discussion of genes of interest
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Genes associated with carbohydrate metabolism included: forkhead box, sub-group O (foxo),
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a major player in the insulin-signaling pathway which is associated with caste determination in
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honey bees and to the workers’ transition from nursing to foraging behavior (Wheeler et al. 2006);
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phosphoglycerate kinase (Pgk) and Triose phosphate isomerase (Tpi), both players in the glycolytic
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pathway (Celotto et al. 2006; Wang et al. 2004); Hexosaminidase 2 (Hexo2), which plays a role in
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glycoprotein maturation within the insect secretory pathway (Léonard et al. 2006); and aconitase
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(Acon), which catalyzes the conversion of citrate to isocitrate in the tricarboxylic acid (TCA) cycle
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(Cheng et al. 2013). With the exception of Tpi, all these genes were upregulated in foraging workers.
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Genes associated with lipid storage and metabolism were upregulated in both groups of
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workers. The following genes were upregulated in non-foraging workers: Indy, which is involved in
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the transport and storage of Krebs cycle intermediates in tissues and an important player in the
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regulation of life span via an effect on metabolism (Wang et al. 2009); Lsp2, a storage protein
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expressed in the fat body tissue of Drosophila (Beneš et al. 1990); Lipid storage droplet-1 and 2 (Lsd-
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1 and Lsd-2), which respectively regulate lipolysis and a promote lipid storage (Beller et al. 2010);
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and beta-coatomer protein (betaCop), an essential component of the trafficking machinery cycling
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between the endoplasmic reticulum and Golgi (Beller et al. 2008). Interestingly, expression of Indy
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was associated with aging and metabolic processes in another study comparing how different social
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environments affect global gene expression of fire ant queens during colony founding (Manfredini et
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al. 2013). In both studies, Indy was downregulated in the group where we expected a longer lifespan
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(non-foraging workers and haplometrotic queens), which is in agreement with the pattern observed
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in Drosophila. This result suggests that Indy might be an important regulator of aging in S. invicta as
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well. By contrast, several other noteworthy genes associated with lipid metabolism were
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upregulated in foraging workers. These included: juvenile hormone epoxide hydrolase 2 (Jheh2),
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which is involved in juvenile hormone catabolic process; helix loop helix protein 106 (HLH106), a
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major player in the metabolism of fatty acids (Kunte et al. 2006); and CTP:phosphocholine
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cytidylyltransferase 1 (CctI), a member of the phospholipid signaling pathways that might affect life
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span when overexpressed (Landis et al. 2003).
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We found that S. invicta workers with foraging/non-foraging tasks significantly differed in
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expression of genes associated with larval central nervous system remodeling and signal
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transduction. Some of these genes were upregulated in non-foraging workers, including: for, which
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encodes a cyclic guanosine monophosphate-dependent protein kinase and was previously
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characterized as a fundamental regulator of foraging behavior across multiple insect species (Ingram
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et al. 2011; Lucas et al. 2010; Lucas & Sokolowski 2009); syt1, a regulator of neurotransmitter
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release (Lee et al. 2013); AkhR, a member of the G-protein coupled receptor 1 family (Hewes &
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Taghert 2001); and finally oat, which is involved in the urea cycle and arginine biosynthesis
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(Neumüller et al. 2011).
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Only a handful of genes were differentially expressed between queenright and queenless
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workers at FDR<0.1. Toy, which is expressed in both eyes and the brain of Drosophila and
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responsible for axonal outgrowth and differentiation of mushroom bodies (Furukubo-Tokunaga et al.
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2009) and cuticular proteins 49Aa, which may play a role in chemical recognition among nestmates,
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were upregulated in queenless workers. Npc2a, which is involved in sterol homeostasis and steroid
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biosynthesis and recently characterized as a player in the antibacterial immune response (Huang et
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al. 2007; Shi et al. 2012), syt1 and oat (see above) were downregulated in queenless workers.
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