foraging and Plasticity Figure 4. Transcriptional interactions between foraging alleles and food. Individual genes involved in energy metabolism have significant for6food interactions (Int) with GEI I,0 for catabolism and I.0 for anabolism (top row), while two functional groups of genes involved in catabolism and anabolism have group-level interactions in the same pattern (bottom row). (A) Glycogen phosphorylase (GlyP), a key enzyme in glycogen breakdown; q(Int) = 5.6861025, I,0. (B) eukaryotic translation initiation factor 4A (eIF-4A), part of the translation initiation complex; q(Int) = 0.0041, I.0. (C) Group-level ANOVA (see Methods) for Gene Ontology (GO) group 5975, carbohydrate metabolism; q(Int) = 0.032, I,0. (D) GO group 6412, protein biosynthesis; q(Int) = 0.0023, I.0 (Table S3 has GO group ANOVA tables). Error bars are 61 s.e.m. There is a significant background (BG)6food interaction in (d) (q = 8.7561027); for (A–C) there is no BG6food interaction; there is a BG main effect in (A,C,D). doi:10.1371/journal.pgen.1000609.g004 p0 both for the top-1000 highest expressing genes and for increasingly large groups of genes based on minimum expression levels. If signal to noise is the only factor affecting p0 then the intercept of the curve of p0 values based on expression is an estimator of 1-DEG. In practice we found good agreement between the latter method and p0 for the top 1000 genes, so we report the top-1000 figure. This analysis was done for each ANOVA p-value (for all main and interaction effects). The palt = 12p0 for a given set of p-values (e.g. for main effect p values) estimates the true DEG rate for that effect. Our top-1000 palt values were BG = 0.84, food = 0.73, BG6food = 0.63, for = 0.59, and for6food = 0.57. That is, among the top-1000 genes by mean expression level, 84% had a main effect of BG, 73% of food, 63% showed BG6food, 59% had a main effect of for and 57% had for6food GEI. Thus, although for6food GEI affects the smallest proportion of top-expressing genes, it still has an effect on 57% of these genes. A quantitative measure of plasticity is higher in rovers The interaction between for and feeding state could be due either to the genotypes responding in equal amounts but opposite directions to feeding (same plasticity of each genotype), or to one genotype responding more than the other (differences in magnitude of plasticity). To quantify differences in plasticity between rovers and sitters, we calculated an index of plasticity called Relative Nutrient Sensitivity (RNS) for any given trait as the difference between the size of the trait’s rover response to food and the size of the sitter response: RNS = (|rover change|2|sitter change|)/C (where C = 1 for log2 transformed data, otherwise C = mean level of trait). In other words, for each trait compared (e.g., behaviour, metabolite, gene expression), RNS compares the absolute magnitude of for-dependent changes in response to food rather than their direction (see Methods). When RNS.0, rovers show a larger response; when RNS,0, sitters respond more. When we tabulated RNS for behaviour, metabolites, gene expression, and functional gene categories, we found RNS.0 (rovers change more) in 8 of 9 behaviour cases (89%, Figure 5A, p = 0.03). For metabolites, gene expression, and functional gene categories, a significant majority of traits had RNS.0 (Figure 5B–5D, p,10215 and Table S4). Thus, for a large majority of behavioural, metabolic, and gene expression traits, rovers exhibit greater food-related plasticity than sitters. This is true PLoS Genetics | www.plosgenetics.org 4 August 2009 | Volume 5 | Issue 8 | e1000609