Two-way transcriptome approach for the identification of common gene targets across four insect orders and its validation in Oxycarenus laetus.

Cotton production is negatively impacted by many insect pests from multiple orders, resulting in significant agronomic and economic losses. This study utilized a comparative transcriptomic methodology to discover conserved gene targets with potential applications in pest management across four insect orders that infest cotton: Hemiptera, Lepidoptera, Orthoptera, and Thysanoptera. A total of 104 publicly available RNA-Seq datasets, representing 17 pest species were de novo assembled in two ways, first was classified by read length (PE100 and PE150) and secondly as species-specific transcriptomes, and their qualities were assessed (alignment ≥ 90%, BUSCO ≥ 80%). Functional annotation utilizing insect-specific databases and orthology-based filtering identified three highly conserved genes, namely Arginine kinase (ArgK), Ryanodine receptor (RyR), and Serine/Threonine Protein phosphatase (STPP). These genes are involved in critical physiological functions, including ATP regeneration, calcium ion homeostasis, and phosphorylation-dependent signaling, and were enriched in pathways associated with insect development and stress response, including as JAK/STAT signaling and chitin metabolism. The study aimed to find broad-spectrum targets across several taxa; however, Oxycarenus laetus, a prominent sap-sucking pest of cotton, was chosen for downstream validation because of its increasing importance and ease of access for experimental research. The expression of ArgK, RyR, and STPP in O. laetus was validated by qPCR, affirming the biological significance of these targets and their functional conservation. This integrated methodology, which includes cross-order comparative transcriptome analysis and species-specific validation, illustrates a scalable approach for discovering essential molecular targets with translational potential in pest control. The results establish a basis for the development of RNAi-based or chemical strategies designed for cotton pest control.