The physical constraints and darwinian forces that shape genomes of species are similar, and indeed the genes themselves are shared through the common ancestor. Based on this, comparative biology in general, and genomics in particular has been very successful in studying and deconstructing the genetic complexity of organisms such as ourselves, by extrapolating from discoveries made in simpler ones. However in some cases, focusing exclusively on highly conserved genes misses what corresponds important species-specific biology. This can be especially relevant when dealing with insects, which have colonized nearly every planetary habitat. Contrary to highly conserved sequences, genes that are evolving rapidly between, and/or within species may do so to respond to species-specific pressures. Unfortunately, genes that are rapidly evolving are challenging to study in non-model organisms, in part because cataloguing genes in a new genome typically embeds scaffolding using orthology, and meaningfully interpreting rates of evolution requires significant genomic data from individuals, or populations, or closely related species.
    We have recently shown in four malaria vectors that investing in the generation of such data can shed new light on our understanding of mosquito evolution: here that positive selection affects disproportionally genes orchestrating aspects of female-specific biology [1]. This finding contrasts data from most similarly examined species, in which rapid evolution is usually a characteristic associated with male reproduction.

Based on these results, we will now explore using functional genomics the roles of the most rapidly evolving genes, which included several that are likely important in female immune system and some expressed exclusively in the female salivary gland, which is both the first and last tissue to be visited by the parasites in transit. Extension of this work to include additional datasets from within species, for example using data from the 1000 Anopheles genome project, or similar data from other species, will allow our bioinformatic work to refine further our understanding of the evolution of pathways regulating traits relevant to disease transmission, or insecticide resistance or of adaptation of invasive species to new environments. This work will address whether and which rapidly evolving genetic circuits correspond to pathways that define vectorial capacity, and may aid in the design of transmission-blocking vaccines or alleles to be included in genetic control strategies aiming to target vectorial capacity within natural populations.