Statistical analysis of non-molecular phenotypes For each phenotype, normality of the data was visually inspected using normal quantile plots and precisely determined with the Shapiro-Wilk test. Homogeneity of variances was estimated using the Levene’s test. Parametric tests were used if the departure from the assumptions of normality and homosce- dasticity was absent or negligible. The Welch ANOVA was used if only heterodasticity was detected. Different transformations (log2 or arcsine square root, depending on the test) of the measurements were calculated for some phenotypes to improve fit to normality although this had a very little effect. Alternatively, non-parametric tests (e.g. Kruskal-Wallis) were used. When multiple post-hoc contrasts were necessary, appropriate tests that account for multiple comparisons were used (e.g. Steel-Dwass). In the case of the departure from expected Mendelian ratios in frequency- dependent competition experiments, the G-test for goodness of fit, upon applying the William’s correction, was used. Statistical contrasts were performed with JMP 4.1 (SAS Institute); the evaluation of the sensitivity to detect statistically significant differences was done with GPower 3.1.3 when needed [69]. Expression data and analysis Three low-density crosses were set up for the strains REC, INV1, INV2, SIM1, REV1, and REV2. The resulting virgin progeny was collected, separated by sex, and allowed to age for 5–7 days. Fifty individuals for each sex were snap frozen in liquid nitrogen at the same time of the day within a 2 hours window and subsequently stored at 280uC. Total RNA from biological samples was extracted using TRIzol Reagent (Invitrogen) and purified using the RNeasy Mini Kit (Qiagen). Concentration, quality and integrity of the RNA samples were estimated using a NanoDrop 8000 Spectrophotometer and the RNA 6000 Nano Chip Kit (Agilent Technologies) with an Agilent 2100 Bioana- lyzer. Ten mg of total RNA were reverse transcribed into cDNA using the SuperScript Double-Stranded cDNA Labeling Kit (Invitrogen). Probe labeling, hybridization, array scanning, and data extraction were performed by Roche NimbleGen Service Group in Iceland. We used the oligonucleotide NimbleGen 126135k D. melanogaster arrays, which contain 135,000 probes including different types of controls and 16,637 transcripts of protein-coding genes as annotated in release 5.7. The experiment consisted of 36 one-color hybridizations (6 samples62 sexes63 biological replicates). Raw fluorescence intensity values of probe pairs were summarized for each transcript using the median value after log transformation. Subsequent data analysis was performed using the tools implemented in the online pipeline WebArrayDB [70]. Data were normalized between arrays using the scale method [71] implemented in the LIMMA package [72]. Data for males and females were analyzed separately. Statistically significant differences across strains were assessed using a fixed- effect model ANOVA and multiple testing was performed with the Benjamini-Hochberg correction [73]. Similarity in expression profiles across genes and strains was assessed by hierarchical clustering using Ward’s minimum variances as a distance metric. The first principal component was used to assist in the sorting. Six biologically meaningful planned contrasts defined a priori, all of them orthogonal, were done likewise by pooling the appropriately expression data of different strains as necessary (Table S17). Scrutiny of the differences in post-hoc comparisons among strains was done using the ‘‘multcomp’’ R package [74]. Functional information for relevant genes was obtained from FlyBase [30] and enrichment for particular Gene Ontology term categories (biological processes, molecular functions, and cellular components), KEGG pathways, and InterPro protein domains Collinearity Conservation in Eukaryotes was evaluated using DAVID [75]. Benjamini-Hochberg correc- tion [73] was applied to account for multiple tests. We proceeded likewise, but for each strain separately, to evaluate statistically significant differences between the sexes. Raw microarray data were deposited at the Gene Expression Omnibus database (GSE31120). In relation to the characterization of the expression profiles of the genes in the region under study during the life cycle of D. melanogaster, RPKM expression values across 30 timepoints and conditions [2] were extracted from FlyBase [30], log transformed, and compared using hierarchical clustering as above. Promoter analysis Core promoter predictions for all the transcripts of protein- coding genes examined were done with McPromoter using the most stringent parameter values [76]. We inspected 500 nt upstream of the 59 UTR start of each transcripts as annotated in FlyBase [30]. In the absence of an annotated 59UTR, a stretch of DNA of equal length upstream of the first nucleotide annotated was examined. Categorization of genes as responsive to HCNEs was based on the prediction of having an Inr core promoter type. Comparative organization of the ultraconserved region CG15121–CG16894 We retrieved mapping coordinates of protein-coding genes included in the ultraconserved region under study in A. gambiae (AgamP3 assembly) using Biomart [77]. Any orthologous mapping information that did not conform to a one-to-one relationship between species was discarded. The global gene organization nearby the ortholog of Toll-7 in A. gambiae and A. aegypti was examined through VectorBase [78]. Phylogenetic relationships among Obp-related amino acid sequences encoded by genes in the same region that harbors the gene Toll-7 from the two mosquito species were conducted in MEGA 5.0 [79]. Amino acid sequences were downloaded from VectorBase [78] and aligned with CLUSTALW [80]. The best evolutionary model of amino acid evolution was found to be WAG and the consensus tree was built using the Maximum Likelihood method [81]. A discrete Gamma distribution was used to model evolutionary rate differences among sites (+G; 4 categories). Bootstrapping was performed to determine the confidence of the branches (1,000 replicates). Supporting Information Dataset S1 Estimates of the average level of expression for all protein-coding genes in the D. melanogaster genome across six strains plus the statistical significance of differences in expression. (7Z) Dataset S2 Statistical significance of differences in gene expression in relevant planned contrasts. (7Z) Dataset S3 Statistical significance of differences in gene expression between males and females for six strains. (7Z) Figure S1 Hierarchical clustering of the expression levels of the protein-coding genes included in the ultraconserved region CG15121–CG16894 during the life cycle of D. melanogaster. Differences in expression levels are color coded (high expression, red ; low expression, green). Asterisks denote genes for which lethal phenotypes have been reported [30,31]. Predictions for the type of core promoter were obtained using McPromoter [76]. The relative order of the protein-coding genes within the region under study is PLoS Genetics | www.plosgenetics.org 9 February 2012 | Volume 8 | Issue 2 | e1002475