Gray shading indicates nonsignificant gene expression effects. Candidate
genes discussed in text are highlighted with bold underlining.1 GeneID and description taken from the NCBI RefSeq
annotation release 100.2 Log2-Fold change (log2FC) values are
included with the corresponding statistical significance (* FDR p
< 0.05, ** FDR p < 0.01). Positive values indicate
elevated expression in SB/SB samples relative to samples withSb-bearing genotypes, negative values indicate elevated
expression for Sb-bearing genotypes.3 Presence in the supergene is based on the previously
published linkage mapping data (Pracana, Priyam, et al., 2017; Wang et
al., 2013).4 Additional support indicates whether each gene has
been reported as differentially expressed in previous studies.a indicates (Wang et al., 2008), b indicates (Wang et
al., 2013), c indicates (Nipitwattanaphon et al., 2013),d indicates (Pracana, Levantis, et al., 2017), and eindicates haplotype-specific gene duplications identified in (Fontana et
al., 2019). Criteria for inclusion of genes in each category were
specific, conservative P-value thresholds conceived in our study (see
Methods for details).5 Details on uncharacterized candidate loci expression
are reported in Supplementary Data 2
SUPPLEMENTARY DATA
Supplementary Data 1: RNA quality, microsatellite-based
relatedness assay, sequence quality control and alignment statistics for
each of our samples.
Supplementary Data 2: Compendium of differential expression and
allele-specific expression for all genes.
Supplementary Data 3: GO term enrichment for differential
expression analyses (P < 0.05).
Supplementary Data 4: Overlap and correlations for differentially
expressed genes when using the Wurm et al. 2011 and Yan et al. 2020
genome assemblies.
SUPPLEMENTARY METHODS
Polar Dominance Analysis. To quantify the dominance patterns of
the various differentially expressed genes, we needed to leverage
information from both the SB/SB vs. SB/Sb comparison as
well as the SB/SB vs. Sb/Sb comparison at the same time.
Additionally, we needed to check all genes effected by the presence of
the supergene, not simply the genes that were differentially expressed
in either comparison. To this end we used the full glm approach querying
for any genes whose expression was significantly affected by the
presence of the supergene (FDR < 0.01). We then computed the
angle between the log2-fold change in the SB/SB vs. SB/Sbcomparison and the log2-fold change in the SB/SB vs. Sb/Sbcomparison (Figure S3). This angle is descriptive of the dominance
pattern of that particular gene.
Odorant Binding Protein Differential Expression . Leveraging the
gene models from previously published work (Pracana, Levantis, et al.,
2017), we tested for differential expression amongst the most complete
set of odorant binding proteins (OBPs) available in the system. We
re-mapped our aligned reads to the OBP gene models using RSubread’s
FeatureCounts function (Liao et al., 2013) and then computed
differential expression using edgeR as described in the Methods
(McCarthy et al., 2012). We then plotted the log2-fold change and
FDR-corrected p-value using the pheatmap package in R. GP-9 is described
here as SiOBP3.
GO term enrichment analysis. GO terms were determined
for each gene using BLAST2GO to search for homologous sequences in theDrosophila melanogaster genome (version r6.20). We then
used topGO with default parameters to compute enriched GO terms amongst
significantly differentially expressed genes (FDR < 0.01)
compared against a background of genes that passed our coverage
filtration. Terms with a P < 0.05 were deemed significant.