Comparative genomics and gene regulatory network reconstruction between Rhynchophorus ferrugineus and Elaeidobius kamerunicus to identify potential targets for insecticide development

Abstract

In sustaining the productivity of agricultural yields, precise population control between pests and beneficial species is often key to long-term success. In palm tree plantations, Rhynchophorus ferrugineus has long been the most threatening pest species to the industry and is commonly treated with broad-spectrum insecticides. However, the off-target movement of insecticides can cause undesirable damage to other beneficial species in the same area. With the Malaysian oil palm plantation as the study setting and utilization of genomic and transcriptomic data from public domain, this research aimed to pinpoint unique genes in R. ferrugineus with potential as insecticide targets while minimizing off-target damage towards the beneficial species Elaeidobius kamerunicus. Through the bi-directional similarity searches between the genomic profiles of both species, nonorthologous genes were identified and retained after the ortholog clustering process. Additionally, differential gene expression analysis between larval and adult phases of R. ferrugineus further narrowed the list of selection. 8 genes were selected based on the outcomes of differential gene expression analysis and functional annotation, with preference given to genes annotated with gene ontology (GO) terms related to digestive, detoxification, and signal transduction activities. Essentially, the selected genes included metallocarboxypeptidase, cathepsin, chitinase, ecdysteroid 2-hydroxylase, cytochrome P450 and G-protein coupled receptor (GPCR) with potential for further experimental validation as insecticide targets. In elucidating the species-specific gene-gene interacting mechanisms, inference of gene regulatory network (GRN) is chosen as the systematic approach to identify the key player genes with potential as insecticide target. Given a skeleton network first reconstructed, gene-to-gene regulatory relationships was further inferred under regressive quantitative model as to elucidate the activating/repressing roles within the reconstructed network. As the result of second unique genes selection, 4 R. ferrugineus genes annotated as Influenza virus ns1a-binding protein (Ivns1abp), glucosyl glucuronosyl transferases (ugt), aminopeptidase (carP), phosphoglucomutase (pgm) were selected given their pivotal roles in the reconstructed gene regulatory networks. With comparative genomics studies between R. ferrugineus and E. kamerunicus as the foundation of unique gene selection, the final selection outcomes serve rightly for further R. ferrugineus insecticide development with high specificity and minimal off-target influence towards beneficial species E. kamerunicus.