Genomic Profiling of Insecticide Resistance in Malaria Vectors: Insights into Molecular Mechanisms.

Abstract

Abstract Malaria control faces challenges from widespread insecticide resistance in major Anopheles species. This study, employing a cross-species approach, integrates RNA-Sequencing, whole-genome sequencing, and microarray data to elucidate drivers of insecticide resistance in Anopheles gambiae complex and An. funestus. Findings show an inverse relationship between genetic diversity and gene expression, with highly expressed genes experiencing stronger purifying selection. These genes cluster physically in the genome, revealing potential coordinated regulation. We identified known and novel candidate insecticide resistance genes, enriched in metabolic, cuticular, and behavioural functions. We also present AnoExpress, a Python package, and an online interface for user-friendly exploration of resistance candidate expression. Despite millions of years of speciation, convergent gene expression responses to insecticidal selection pressures are observed across Anopheles species, providing crucial insights for malaria vector control. This study culminates in a rich dataset that allows us to understand molecular mechanisms, better enabling us to combat insecticide resistance effectively.