The draft genome of whitefly Bemisia tabaci MEAM1, a global crop pest, provides novel insights into virus transmission, host adaptation, and insecticide resistance.

Background: The whitefly Bemisia tabaci (Hemiptera: Aleyrodidae) is among the 100 worst invasive species in the world. As one of the most important crop pests and virus vectors, B. tabaci causes substantial crop losses and poses a serious threat to global food security. Results: We report the 615-Mb high-quality genome sequence of B. tabaci Middle East-Asia Minor 1 (MEAM1), the first genome sequence in the Aleyrodidae family, which contains 15,664 protein-coding genes. The B. tabaci genome is highly divergent from other sequenced hemipteran genomes, sharing no detectable synteny. A number of known detoxification gene families, including cytochrome P450s and UDP-glucuronosyltransferases, are significantly expanded in B. tabaci. Other expanded gene families, including cathepsins, large clusters of tandemly duplicated B. tabaci-specific genes, and phosphatidylethanolamine-binding proteins (PEBPs), were found to be associated with virus acquisition and transmission and/or insecticide resistance, likely contributing to the global invasiveness and efficient virus transmission capacity of B. tabaci. The presence of 142 horizontally transferred genes from bacteria or fungi in the B. tabaci genome, including genes encoding hopanoid/sterol synthesis and xenobiotic detoxification enzymes that are not present in other insects, offers novel insights into the unique biological adaptations of this insect such as polyphagy and insecticide resistance. Interestingly, two adjacent bacterial pantothenate biosynthesis genes, panB and panC, have been co-transferred into B. tabaci and fused into a single gene that has acquired introns during its evolution. Conclusions: The B. tabaci genome contains numerous genetic novelties, including expansions in gene families associated with insecticide resistance, detoxification and virus transmission, as well as numerous horizontally transferred genes from bacteria and fungi. We believe these novelties likely have shaped B. tabaci as a highly invasive polyphagous crop pest and efficient vector of plant viruses. The genome serves as a reference for resolving the B. tabaci cryptic species complex, understanding fundamental biological novelties, and providing valuable genetic information to assist the development of novel strategies for controlling whiteflies and the viruses they transmit

Detection and quantitation of copy number variation in the voltage-gated sodium channel gene of the mosquito Culex quinquefasciatus

Insecticide resistance is typically associated with alterations to the insecticidal target-site or with gene expression variation at loci involved in insecticide detoxification. In some species copy number variation (CNV) of target site loci (e.g. the Ace-1 target site of carbamate insecticides) or detoxification genes has been implicated in the resistance phenotype. We show that field-collected Ugandan Culex quinquefasciatus display CNV for the voltage-gated sodium channel gene (Vgsc), target-site of pyrethroid and organochlorine insecticides. In order to develop field-applicable diagnostics for Vgsc CN, and as a prelude to investigating the possible association of CN with insecticide resistance, three assays were compared for their accuracy in CN estimation in this species. The gold standard method is droplet digital PCR (ddPCR), however, the hardware is prohibitively expensive for widespread utility. Here, ddPCR was compared to quantitative PCR (qPCR) and pyrosequencing. Across all platforms, CNV was detected in ≈10% of mosquitoes, corresponding to three or four copies (per diploid genome). ddPCR and qPCR-Std-curve yielded similar predictions for Vgsc CN, indicating that the qPCR protocol developed here can be applied as a diagnostic assay, facilitating monitoring of Vgsc CN in wild populations and the elucidation of association between the Vgsc CN and insecticide resistance

A Two-Locus Model of the Evolution of Insecticide Resistance to Inform and Optimise Public Health Insecticide Deployment Strategies

We develop a flexible, two-locus model for the spread of insecticide resistance applicable to mosquito species that transmit human diseases such as malaria. The model allows differential exposure of males and females, allows them to encounter high or low concentrations of insecticide, and allows selection pressures and dominance values to differ depending on the concentration of insecticide encountered. We demonstrate its application by investigating the relative merits of sequential use of insecticides versus their deployment as a mixture to minimise the spread of resistance. We recover previously published results as subsets of this model and conduct a sensitivity analysis over an extensive parameter space to identify what circumstances favour mixtures over sequences. Both strategies lasted more than 500 mosquito generations (or about 40 years) in 24% of runs, while in those runs where resistance had spread to high levels by 500 generations, 56% favoured sequential use and 44% favoured mixtures. Mixtures are favoured when insecticide effectiveness (their ability to kill homozygous susceptible mosquitoes) is high and exposure (the proportion of mosquitoes that encounter the insecticide) is low. If insecticides do not reliably kill homozygous sensitive genotypes, it is likely that sequential deployment will be a more robust strategy. Resistance to an insecticide always spreads slower if that insecticide is used in a mixture although this may be insufficient to outperform sequential use: for example, a mixture may last 5 years while the two insecticides deployed individually may last 3 and 4 years giving an overall ‘lifespan’ of 7 years for sequential use. We emphasise that this paper is primarily about designing and implementing a flexible modelling strategy to investigate the spread of insecticide resistance in vector populations and demonstrate how our model can identify vector control strategies most likely to minimise the spread of insecticide resistance

Automatic target recognition based on cross-plot

Automatic target recognition that relies on rapid feature extraction of real-time target from photo-realistic imaging will enable efficient identification of target patterns. To achieve this objective, Cross-plots of binary patterns are explored as potential signatures for the observed target by high-speed capture of the crucial spatial features using minimal computational resources. Target recognition was implemented based on the proposed pattern recognition concept and tested rigorously for its precision and recall performance. We conclude that Cross-plotting is able to produce a digital fingerprint of a target that correlates efficiently and effectively to signatures of patterns having its identity in a target repository.Kelvin Kian Loong Wong and Derek Abbot