Whether speciation through ecological specialization occurs has been a thriving research area ever since Mayr (1942) stated this to play a central role. In herbivorous insects, ecological specialization is most likely to happen through host plant differentiation (Funk et al. 2002). Therefore, after Dorothy Pashley had identified two host strains in the Fall armyworm (FAW), Spodoptera frugiperda, in 1988 (Pashley 1988), researchers have been trying to decipher the evolutionary history of these strains, as this seems to be a model species in which speciation is currently occurring through host plant specialization. Even though FAW is a generalist, feeding on many different host plant species (Pogue 2002) and a devastating pest in many crops, Pashley identified a so-called corn strain and a so-called rice strain in Puerto Rico. Genetically, these strains were found to differ mostly in an esterase, although later studies showed additional genetic differences and markers, mostly in the mitochondrial COI and the nuclear TPI. Recent genomic studies showed that the two strains are overall so genetically different (2% of their genome being different) that these two strains could better be called different species (Kergoat et al. 2012). So far, the most consistent differences between the strains have been their timing of mating activities at night (Schoefl et al. 2009, 2011; Haenniger et al. 2019) and hybrid incompatibilities (Dumas et al. 2015; Kost et al. 2016). Whether and to what extent host plant preference or performance contributed to the differentiation of these sympatrically occurring strains has remained unclear.
In the current study, Orsucci et al. (2020) performed oviposition assays and reciprocal transplant experiments with both strains to measure fitness effects, in combination with a comprehensive RNAseq experiment, in which not only lab reared larvae were analysed, but also field-collected larvae. When testing preference and performance on the two host plants corn and rice, the authors did not find consistent fitness differences between the two strains, with both strains performing less on rice plants, although larvae from the corn strain survived more on corn plants than those from the rice strain. These results mostly confirm findings of a number of investigations over the past 30 years, where no consistent differences on the two host plants were observed (reviewed in Groot et al. 2016). However, the RNAseq experiments did show some striking differences between the two strains, especially in the reciprocally transplanted larvae, where both strains had been reared on rice or on corn plants for one generation: both strains showed transcriptional responses that correspond to their respective putative host plants, i.e. overexpression of genes involved in digestion and metabolic activity, and underexpression of genes involved in detoxification, in the corn strain on corn and in the rice strain on rice. Interestingly, similar sets of genes were found to be overexpressed in the field-collected larvae with which a RNAseq experiment was conducted as well.
The most interesting result of the study performed by Orsucci et al. (2020) is the underexpression in the corn strain of so-called numts, small genomic sequences that corresponded to fragments of the mitochondrial COI and COIII. These two numts were differentially expressed in the two strains in all RNAseq experiments analysed. This result coincides with the fact that the COI is one of the main diagnostic markers to distinguish these two strains. The authors suggestion that a difference in energy production between these two strains may be linked to a shift in host plant preference matches their finding that rice plants seem to be less suitable host plants than corn plants. However, as the lower suitability of rice plants was true for both strains, it remains unclear whether and how this difference could be linked to possible host plant differentiation between the strains. The authors also suggest that COI and potentially other mitochondrial genes may be the original target of selection between these two strains. This is especially interesting in light of the fact that field-collected larvae have frequently been found to have a rice strain mitochondrial genotype and a corn strain nuclear genotype, also in this study, while in the lab (female rice strain x male corn strain) hybrid females (i.e. females with a rice strain mitochondrial genotype and a corn strain nuclear genotype) are behaviorally sterile (Kost et al. 2016). Whether and how selection on mitochondrial genes or on mitonuclear interactions has indeed affected the evolution of these strains in the New world, and will affect the evolution of FAW in newly invaded habitats in the Old world, including Asia and Australia – where, so far, only corn strain and (female rice strain x male corn strain) hybrids have been found (Nagoshi 2019), will be a challenging research question for the coming years.

References

[1] Dumas, P. et al. (2015). Spodoptera frugiperda (Lepidoptera: Noctuidae) host-plant variants: two host strains or two distinct species?. Genetica, 143(3), 305-316. doi: 10.1007/s10709-015-9829-2
[2] Funk, D. J., Filchak, K. E. and Feder J. L. (2002) Herbivorous insects: model systems for the comparative study of speciation ecology. In: Etges W.J., Noor M.A.F. (eds) Genetics of Mate Choice: From Sexual Selection to Sexual Isolation. Contemporary Issues in Genetics and Evolution, vol 9. Springer, Dordrecht. doi: 10.1007/978-94-010-0265-3_10
[3] Groot, A. T., Unbehend, M., Hänniger, S., Juárez, M. L., Kost, S. and Heckel D. G.(2016) Evolution of reproductive isolation of Spodoptera frugiperda. In Allison, J. and Cardé, R. (eds) Sexual communication in moths. Chapter 20: 291-300.
[4] Hänniger, S. et al. (2017). Genetic basis of allochronic differentiation in the fall armyworm. BMC evolutionary biology, 17(1), 68. doi: 10.1186/s12862-017-0911-5
[5] Kost, S., Heckel, D. G., Yoshido, A., Marec, F., and Groot, A. T. (2016). AZ‐linked sterility locus causes sexual abstinence in hybrid females and facilitates speciation in Spodoptera frugiperda. Evolution, 70(6), 1418-1427. doi: 10.1111/evo.12940
[6] Mayr, E. (1942) Systematics and the origin of species. Columbia University Press, New York.
[7] Nagoshi, R. N. (2019). Evidence that a major subpopulation of fall armyworm found in the Western Hemisphere is rare or absent in Africa, which may limit the range of crops at risk of infestation. PloS one, 14(4). doi: 10.1371/journal.pone.0208966
[8] Orsucci, M., Moné, Y., Audiot, P., Gimenez, S., Nhim, S., Naït-Saïdi, R., Frayssinet, M., Dumont, G., Boudon, J.-P., Vabre, M., Rialle, S., Koual, R., Kergoat, G. J., Nagoshi, R. N., Meagher, R. L., d’Alençon, E. and Nègre N. (2020) Transcriptional differences between the two host strains of Spodoptera frugiperda (Lepidoptera: Noctuidae). bioRxiv, 263186, ver. 2 peer-reviewed and recommended by PCI Evol Biol. doi: 10.1101/263186
[9] Pashley, D. P. (1988) Current Status of Fall Armyworm Host Strains. Florida Entomologist 71 (3): 227–34. doi: 10.2307/3495425
[10] Pogue, M. (2002). A World Revision of the Genus Spodoptera Guenée (Lepidoptera: Noctuidae). American Entomological Society.
[11] Schöfl, G., Heckel, D. G., and Groot, A. T. (2009). Time‐shifted reproductive behaviours among fall armyworm (Noctuidae: Spodoptera frugiperda) host strains: evidence for differing modes of inheritance. Journal of Evolutionary Biology, 22(7), 1447-1459. doi: 10.1111/j.1420-9101.2009.01759.x
[12] Schöfl, G., Dill, A., Heckel, D. G., and Groot, A. T. (2011). Allochronic separation versus mate choice: nonrandom patterns of mating between fall armyworm host strains. The American Naturalist, 177(4), 470-485. doi: 10.1086/658904

Understanding how species respond to environmental changes is becoming increasingly important in order to predict the future of biodiversity and species distributions under current global warming conditions (Rezende 2020; Bennett et al 2021). Two key factors to take into account in these predictions are the tolerance of organisms to heat stress and subsequently how they adapt to increasingly warmer temperatures. Coupled with this, one important factor that is often overlooked when addressing the evolution of thermal tolerance, is the correlated responses in traits that are important to fitness, such as life histories, behavior and the underlying metabolic processes.

The rate and intensity of the thermal stress are expected to be major factors in shaping the evolution of heat tolerance and correlated responses in other traits. For instance, lower rates of thermal stress are predicted to select for individuals with a slower metabolism (Santos et al 2012), whereas low metabolism is expected to lead to a lower reproductive rate (Dammhahn et al 2018). To quantify the importance of the rate and intensity of thermal stress on the evolutionary response of heat tolerance and correlated response in behavior, Mesas et al (2021) performed experimental evolution in Drosophila subobscura using selective regimes with slow or fast ramping protocols. Whereas both regimes showed increased heat tolerance with similar evolutionary rates, the correlated responses in thermal performance curves for locomotor behavior differed between selection regimes. These findings suggest that thermal rate and intensity may shape the evolution of correlated responses in other traits, urging the need to understand possible correlated responses at relevant levels such as life history and metabolism. 

In the present contribution, Mesas and Castañeda (2022) investigate whether the disparity in thermal performance curves observed in the previous experiment (Mesas et al 2021) could be explained by differences in metabolic energy production and consumption, and how this correlated with the reproductive output (fecundity and viability). Overall, the authors show some evidence for lowered enzyme activity and increased performance in life-history traits, particularly for the slow-ramping selected flies. Specifically, the authors observe a reduction in glucose metabolism and increased viability when evolving under slow ramping stress. Interestingly, both regimes show a general increase in fecundity, suggesting that adaptation to these higher temperatures is not costly (for reproduction) in the ancestral environment. The evidence for a somewhat lower metabolism in the slow-ramping lines suggests the evolution of a slow “pace of life”. The “pace of life” concept tries to bridge variation across several levels namely metabolism, physiology, behavior and life history, with low “pace of life” organisms presenting lower metabolic rates, later reproduction and higher longevity than fast “pace of life” organisms (Dammhahn et al 2018, Tuzun & Stocks 2022).  As the authors state there is not a clear-cut association with the expectations of the pace of life hypothesis since there was evidence for increased reproductive output under both selection intensity regimes. This suggests that, given sufficient trait genetic variance, positively correlated responses may emerge during some stages of thermal evolution. As fecundity estimates in this study were focussed on early life, the possibility of a decrease in the cumulative reproductive output of the selected flies, even under benign conditions, cannot be excluded. This would help explain the apparent paradox of increased fecundity in selected lines. In this context, it would also be interesting to explore the variation in reproductive output at different temperatures, i.e to obtain thermal performance curves for life histories. 

Mesas and Castañeda (2022) raise important questions to pursue in the future and contribute to the growing evidence that, in order to predict the distribution of ectothermic species under current global warming conditions, we need to expand beyond determining the physiological thermal limits of each organism (Parratt et al 2021). Ultimately, integrating metabolic, life-history and behavioral changes during evolution under different thermal stresses within a coherent framework is key to developing better predictions of temperature effects on natural populations.  

References

Bennett, J.M., Sunday, J., Calosi, P. et al. The evolution of critical thermal limits of life on Earth. Nat Commun 12, 1198 (2021). https://doi.org/10.1038/s41467-021-21263-8

Dammhahn, M., Dingemanse, N.J., Niemelä, P.T. et al. Pace-of-life syndromes: a framework for the adaptive integration of behaviour, physiology and life history. Behav Ecol Sociobiol 72, 62 (2018). https://doi.org/10.1007/s00265-018-2473-y

Mesas, A,  Jaramillo, A,  Castañeda, LE.  Experimental evolution on heat tolerance and thermal performance curves under contrasting thermal selection in Drosophila subobscura. J Evol Biol  34, 767– 778 (2021). https://doi.org/10.1111/jeb.13777

Mesas, A, Castañeda, LE Evolutionary responses of energy metabolism, development, and reproduction to artificial selection for increasing heat tolerance in Drosophila subobscura. bioRxiv, 2022.02.03.479001, ver. 4 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://doi.org/10.1101/2022.02.03.479001

Parratt, S.R., Walsh, B.S., Metelmann, S. et al. Temperatures that sterilize males better match global species distributions than lethal temperatures. Nat. Clim. Chang. 11, 481–484 (2021). https://doi.org/10.1038/s41558-021-01047-0

Santos, M, Castañeda, LE, Rezende, EL Keeping pace with climate change: what is wrong with the evolutionary potential of upper thermal limits? Ecology and evolution, 2(11), 2866-2880 (2012). https://doi.org/10.1002/ece3.385

Tüzün, N, Stoks, R. A fast pace-of-life is traded off against a high thermal performance. Proceedings of the Royal Society B, 289(1972), 20212414 (2022). https://doi.org/10.1098/rspb.2021.2414

Rezende, EL, Bozinovic, F, Szilágyi, A, Santos, M. Predicting temperature mortality and selection in natural Drosophila populations. Science, 369(6508), 1242-1245  (2020). https://doi.org/10.1126/science.aba9287

Genetic diversity is a key aspect of biodiversity and has important implications for evolutionary potential and thereby the persistence of species. Improving our understanding of the factors that drive genetic structure within and between populations is, therefore, a long-standing goal in evolutionary biology. However, this is a major challenge, because of the complex interplay between genetic drift, migration, and extinction/colonization dynamics on the one hand, and the biology and ecology of species on the other hand (Romiguier et al. 2014, Ellegren and Galtier 2016, Charlesworth 2003). 

Jarne et al. (2021) studied whether environmental and demographic factors affect the population genetic structure of four species of hermaphroditic freshwater snails in a similar way, using comparative analyses of neutral genetic microsatellite markers. 

Specifically, they investigated microsatellite variability of Hygrophila in almost 280 sites in Guadeloupe, Lesser Antilles, as part of a long-term survey experiment (Lamy et al. 2013). They then modelled the influence of the mating system, local environmental characteristics and demographic factors on population genetic diversity.

Consistent with theoretical predictions (Charlesworth 2003), they detected higher genetic variation in two outcrossing species than in two selfing species, emphasizing the importance of the mating system in maintaining genetic diversity. The study further identified an important role of site connectivity, through its influences on effective population size and extinction/colonisation events. Finally, the study detects an influence of interspecific interactions caused by an ongoing invasion by one of the studied species on genetic structure, highlighting the indirect effect of changes in community composition and demography on population genetics.

Jarne et al. (2021) could address the extent to which genetic structure is determined by demographic and environmental factors in multiple species given the remarkable sampling available. Additionally, the study system is extremely suitable to address this hypothesis as species’ habitats are defined and delineated. Whilst the authors did attempt to test for across-species correlations, further investigations on this matter are required. Moreover, the effect of interactions between factors should be appropriately considered in any modelling between genetic structure and local environmental or demographic features.

The findings in this study contribute to improving our understanding of factors influencing population genetic diversity, and highlights the complexity of interacting factors, therefore also emphasizing the challenges of drawing general implications, additionally hampered by the relatively limited number of species studied. Jarne et al. (2021) provide an excellent showcase of an empirical framework to test determinants of genetic structure in natural populations. As such, this study can be an example for further attempts of comparative analysis of genetic diversity.

References

Charlesworth, D. (2003) Effects of inbreeding on the genetic diversity of populations. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 358, 1051-1070. doi: https://doi.org/10.1098/rstb.2003.1296

Ellegren, H. and Galtier, N. (2016) Determinants of genetic diversity. Nature Reviews Genetics, 17, 422-433. doi: https://doi.org/10.1038/nrg.2016.58

Jarne, P., Lozano del Campo, A., Lamy, T., Chapuis, E., Dubart, M., Segard, A., Canard, E., Pointier, J.-P. and David, P. (2021) Connectivity and selfing drives population genetic structure in a patchy landscape: a comparative approach of four co-occurring freshwater snail species. HAL, hal-03295242, ver. 2 peer-reviewed and recommended by Peer Community in Evolutionary Biology. https://hal.archives-ouvertes.fr/hal-03295242

Lamy, T., Gimenez, O., Pointier, J. P., Jarne, P. and David, P. (2013). Metapopulation dynamics of species with cryptic life stages. The American Naturalist, 181, 479-491. doi: https://doi.org/10.1086/669676

Romiguier, J., Gayral, P., Ballenghien, M. et al. (2014) Comparative population genomics in animals uncovers the determinants of genetic diversity. Nature, 515, 261-263. doi: https://doi.org/10.1038/nature13685

Spatial genetic structure, i.e. the non-random spatial distribution of genotypes, arises in populations because of different processes including spatially limited dispersal and selection. Knowledge on the spatial genetic structure of plant populations is important to assess biological parameters such as gene dispersal distances and the potential for local adaptations, as well as for applications in conservation management and breeding. In their work, Niskanen and colleagues demonstrate a multifaceted approach to characterise the spatial genetic structure in two replicate sites of a continuously distributed Scots pine population in South-Eastern Finland. They mapped and assessed the ages of 469 naturally regenerated adults and genotyped them using a SNP array which resulted in 157 325 filtered polymorphic SNPs. Their dataset is remarkably powerful because of the large numbers of both individuals and SNPs genotyped. This made it possible to characterise precisely the decay of genetic relatedness between individuals with spatial distance despite the extensive dispersal capacity of Scots pine through pollen, and ensuing expectations of an almost panmictic population.

The authors’ data analysis was particularly thorough. They demonstrated that two metrics of pairwise relatedness, the genomic relationship matrix (GRM, Yang et al. 2011) and the kinship coefficient (Loiselle et al. 1995) were strongly correlated and produced very similar inference of family relationships: >99% of pairs of individuals were unrelated, and the remainder exhibited 2nd (e.g., half-siblings) to 4th degree relatedness. Pairwise relatedness decayed with spatial distance which resulted in extremely weak but statistically significant spatial genetic structure in both sites, quantified as Sp=0.0005 and Sp=0.0008. These estimates are at least an order of magnitude lower than estimates in the literature obtained in more fragmented populations of the same species or in other conifers. Estimates of the neighbourhood size, the effective number of potentially mating individuals belonging to a within-population neighbourhood (Wright 1946), were relatively large with Nb=1680-3210 despite relatively short gene dispersal distances, σg = 36.5–71.3m, which illustrates the high effective density of the population. 

The authors showed the implications of their findings for selection. The capacity for local adaptation depends on dispersal distances and the strength of the selection coefficient. In the study population, the authors inferred that local adaptation can only occur if environmental heterogeneity occurs over a distance larger than approximately one kilometre (or larger, if considering long-distance dispersal). Interestingly, in Scots pine, no local adaptation has been described on similar geographic scales, in contrast to some other European or Mediterranean conifers (Scotti et al. 2023).

The authors’ results are relevant for the management of conservation and breeding. They showed that related individuals occurred within sites only and that they shared a higher number of rare alleles than unrelated ones. Since rare alleles are enriched in new and recessive deleterious variants, selecting related individuals could have negative consequences in breeding programmes. The authors also showed, in their response to reviewers, that their powerful dataset was not suitable to obtain a robust estimate of effective population size, Ne, based on the linkage disequilibrium method (Do et al. 2014). This illustrated that the estimation of Ne used for genetic indicators supported in international conservation policy (Hoban et al. 2020, CBD 2022) remains challenging in large and continuous populations (see also Santo-del-Blanco et al. 2023, Gargiulo et al. 2024).

References

CBD (2022) Kunming-Montreal Global Biodiversity Framework. https://www.cbd.int/doc/decisions/cop-15/cop-15-dec-04-en.pdf

Do C, Waples RS, Peel D, Macbeth GM, Tillett BJ, Ovenden JR (2014). NeEstimator v2: re-implementation of software for the estimation of contemporary effective population size (Ne ) from genetic data. Molecular Ecology Resources 14: 209–214. https://doi.org/10.1111/1755-0998.12157

Gargiulo R, Decroocq V, González-Martínez SC, Paz-Vinas I, Aury JM, Kupin IL, Plomion C, Schmitt S, Scotti I, Heuertz M (2024) Estimation of contemporary effective population size in plant populations: limitations of genomic datasets. Evolutionary Applications, in press, https://doi.org/10.1101/2023.07.18.549323

Hoban S, Bruford M, D’Urban Jackson J, Lopes-Fernandes M, Heuertz M, Hohenlohe PA, Paz-Vinas I, et al. (2020) Genetic diversity targets and indicators in the CBD post-2020 Global Biodiversity Framework must be improved. Biological Conservation 248: 108654. https://doi.org/10.1016/j.biocon.2020.108654

Loiselle BA, Sork VL, Nason J & Graham C (1995) Spatial genetic structure of a tropical understorey shrub, Psychotria officinalis (Rubiaceae). American Journal of Botany 82: 1420–1425. https://doi.org/10.1002/j.1537-2197.1995.tb12679.x

Santos-del-Blanco L, Olsson S, Budde KB, Grivet D, González-Martínez SC, Alía R, Robledo-Arnuncio JJ (2022). On the feasibility of estimating contemporary effective population size (Ne) for genetic conservation and monitoring of forest trees. Biological Conservation 273: 109704. https://doi.org/10.1016/j.biocon.2022.109704

Scotti I, Lalagüe H, Oddou-Muratorio S, Scotti-Saintagne C, Ruiz Daniels R, Grivet D, et al. (2023) Common microgeographical selection patterns revealed in four European conifers. Molecular Ecology 32: 393-411. https://doi.org/10.1111/mec.16750

Wright S (1946) Isolation by distance under diverse systems of mating. Genetics 31: 39–59. https://doi.org/10.1093/genetics/31.1.39

Yang J, Lee SH, Goddard ME & Visscher PM (2011) GCTA: a tool for genome-wide complex trait analysis. The American Journal of Human Genetics 88: 76–82. https://www.cell.com/ajhg/pdf/S0002-9297(10)00598-7.pdf

The emergence and spread of insecticide resistance compromises the efficiency of insecticides as prevention tool against the transmission of insect-transmitted diseases (Moyes et al. 2017). In this context, the understanding of the genetic mechanisms of resistance and the way resistant alleles spread in insect populations is necessary and important to envision resistance management policies. A common and important mechanism of insecticide resistance is gene amplification and in particular amplification of insecticide detoxification genes, which leads to the overexpression of these genes (Bass & Field, 2011). Cattel and coauthors (2020) adopt a combination of experimental approaches to study the role of gene amplification in resistance to organophosphate insecticides in the mosquito Aedes aegypti and its occurrence in populations of South East Asia and to develop a molecular test to track resistance alleles.
Their first approach consists in performing an artificial selection on laboratory Ae. Aegypti populations started with individuals collected in Laos. In the selected population, an initial 90% mortality by adult exposure to the organophosphate insecticide malathion is imposed. This population shows a steep increase in resistance to malathion and other organophosphate insecticides, which is absent in the paired control population. The transcriptomic patterns of the control and the evolved populations as well as of a reference sensitive population reveals, among other differences, the over-expression of five carboxy/choline esterase (CCE) genes in the insecticide selected population. These five genes happen to be clustered in the Ae. aegypti genome and whole genome sequencing of a highly resistant population combined to qPCR test on genomic DNA showed that the overexpression of these genes is due to gene amplification. Although it would have been more elegant to have replicate selected and control populations and to perform the transcriptomic and the genomic analyses directly on the experimental populations, the authors gather a set of experimental evidence which combined to previous knowledge on the function of the amplified and over-expressed genes and on their implication in organophosphate insecticide resistance in other species allow to discard the possibility that this gene amplification spread by drift in the selected population.
In a second part of the paper, copy number variation for CCE genes is checked in field sample populations. This test reveals the presence of resistance alleles in half of the fourteen South East Asia populations sampled. Very interestingly, it also reveals a high level of complexity and diversity among the resistance alleles: it shows first the existence, both in the experimental and the field populations, of at least two amplified alleles (differing by the number of genes amplified) and second a high variation in the copy number of amplified genes. This indicates that gene amplification as a molecular resistance mechanism has actually lead to a high diversity of resistance alleles. These alleles are likely to differ both by the level of resistance conferred and the fitness cost imposed in the absence of the insecticide and these two values are affecting the evolution of their frequency in the field and ultimately the spread of resistance.
The last part of the paper is devoted to the development of a high-throughput Taqman assay which allows to determine rapidly the copy number of one of the esterase genes amplified in the resistance alleles described earlier. This assay is nicely validated and will definitely be a useful tool to determine the occurrence of these resistance alleles in field population. The fact that it gives access to the copy number will also allow to follow its copy number across time and get insight into the complexity of resistance evolution by gene amplification.
To sum up, this paper studies the implication of carboxy/choline esterase genes amplification in organophosphate resistance evolution in Ae. aegypti, reveals the diversity among individuals and populations of this resistance mechanism, because of variation both in the identity of the genes amplified and in their copy number and sets up a fast and efficient tool to detect and follow the spread of these resistant alleles in the field. Additionally, the different experimental approaches adopted have generated genomic and transcriptomic data, of which only the part related to CCE gene amplification has been exploited. These data are very likely to reveal other genomic and expression determinants of resistance that will give access to an extra degree of complexity in organophosphate insecticide resistance determinism and evolution.

References

Bass C, Field LM (2011) Gene amplification and insecticide resistance. Pest Management Science, 67, 886–890. https://doi.org/10.1002/ps.2189
Cattel J, Haberkorn C, Laporte F, Gaude T, Cumer T, Renaud J, Sutherland IW, Hertz JC, Bonneville J-M, Arnaud V, Nous C, Fustec B, Boyer S, Marcombe S, David J-P (2020) A genomic amplification affecting a carboxylesterase gene cluster confers organophosphate resistance in the mosquito Aedes aegypti: from genomic characterization to high-throughput field detection. bioRxiv, 2020.06.08.139741, ver. 4 peer-reviewed and recommended by PCI Evolutionary Biology. https://doi.org/10.1101/2020.06.08.139741
Moyes CL, Vontas J, Martins AJ, Ng LC, Koou SY, Dusfour I, Raghavendra K, Pinto J, Corbel V, David J-P, Weetman D (2017) Contemporary status of insecticide resistance in the major Aedes vectors of arboviruses infecting humans. PLOS Neglected Tropical Diseases, 11, e0005625. https://doi.org/10.1371/journal.pntd.0005625