A multi-omic meta-analysis reveals novel mechanisms of insecticide resistance in malaria vectors - Sanjay C. Nagi; Victoria A. Ingham (Communications Biology)
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. Here we show an inverse relationship between genetic diversity and gene expression, with highly expressed genes experiencing stronger purifying selection. Gene expression clusters physically in the genome, revealing potential coordinated regulation, and we find that highly over-expressed genes are associated with selective sweep loci. We identify known and novel candidate insecticide resistance genes, enriched for metabolic, cuticular, and behavioural functioning. 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.