4.5. DEG identification, GO mapping and KEGG pathway analysis

Differential expression analysis was performed using the DESeq2 Bioconductor package [72]. The comparison between the mapped read counts of the virus-infected mosquitoes versus the read counts of uninfected blood-fed mosquitoes identified differentially expressed genes (DEGs). Genes were significantly differentially expressed if the adjusted p-value (false discovery rate) was < 0.05 and showed an absolute fold change of ±1.5. For all DEGs, gene annotation was done using the Biomart tool provided by the VectorBase database. DEG lists were further used for GO, pathway enrichment and immune response analysis. DAVID bioinformatics (V6.8) was used to assign GO terms and KEGG pathways information to differentially expressed genes [73]. WEGO 2.0 was then used to compare and plot GO annotation results at user-specified hierarchical level 2 [74]. The KEGG pathways enriched by DAVID bioinformatics were manually categorized under six main categories and subcategories as defined by the KEGG pathway database [75]. There were some pathways/GO terms with the presence of both up and downregulated genes. This is expected when pathways encode both positive and negative regulators [76]. Thus, if the upregulated gene group contains ‘positive’ regulators and downregulated one includes ‘negative’ regulators, in general, the pathway can be considered as regulated [76]. We used this approach in our descriptions of GO analysis and KEGG pathway analysis. For gene IDs for which functional information could not be assigned via DAVID bioinformatics (v6.8) gene enrichment analysis tool, then such genes were subjected to annotation using VectorBase search and BLAST sequence similarity (https://blast.ncbi.nlm.nih.gov/Blast.cgi).