Standing genetic variation and chromosome differences drove rapid ecotype formation in a major malaria mosquito

Genomics of urban adaptation and exaptation in mosquitoes and consequences for vectorial capacity

As urbanization accelerates around the world, mosquitoes that are capable of surviving and thriving in urban habitats increasingly spread mosquito-borne diseases. Across the >3,500 known species of mosquitoes, only a few rapidly adapted to the novel (on an evolutionary timescale) urban environments. In this review we highlight several emerging themes and testable hypotheses from recent literature. First, apparent urban adaptations can be roughly divided into newer adaptations arising in an urban context and exaptations - traits that evolved in a different context, prior to modern urbanization. Second, variants involved in urban adaptation are often partitioned among species complexes and cryptic lineages, and the history of gene flow-selection balance may be related to the evolution of compact genomic architectures that could facilitate rapid urban adaptation. Third, urban adaptation often has consequences for vectorial capacity - the ability of mosquitoes to serve as effective vectors of a particular pathogen - though the selective drivers and genetic mechanisms underlying these differences are incompletely understood. To fully understand urban adaptation in mosquitoes, we advocate for a coordinated effort to increase linkages between evolutionary ecology, population genomics, and medical entomology research. We discuss the two traits for which all three perspectives are the most developed - host preference and insecticide resistance - before reviewing several other less studied traits.

Standing genetic variation and introgression shape the cryptic radiation of Aquilegia in the mountains of Southwest China

Cryptic diversity in evolutionary radiation offers an excellent system for investigating the intricacies of evolutionary progress. Understanding the evolution of cryptic diversity is imperative for unraveling the hidden complexities of biodiversity. However, empirical evidence elucidating the mechanisms behind cryptic radiation remains limited, particularly in plants. Here, we focus on a monophyletic group of Aquilegia species mainly distributed in the mountains of Southwest China, one of the world's biodiversity hotspots. Using whole-genome resequencing of 158 individuals from 23 natural populations, we identify three to four paraphyletic lineages within each morphological species. Our findings reveal that 39 out of 43 detected instances of introgression occurred post-lineage formation. Identifying shared genomic regions indicates that the divergence of fixed singletons in lineages from morphological species A. kansuensis and A. rockii predates lineage formation, supporting a scenario where incomplete lineage sorting of standing variation contributes to morphological parallelism. Furthermore, strong positive correlations among genomic differentiation, divergence, and introgression suggest that standing variations and introgression from non-sister lineages contribute to the rapid genetic divergence. Our study illuminates the important roles of standing variations and introgression in plant cryptic radiation, advancing our understanding of the complex mechanisms behind the evolution of biodiversity in recent radiation events.

Evolutionary consequences of long-distance dispersal in mosquitoes

Long-distance dispersal (LDD) provides a means for mosquitoes to invade new regions and spread adaptive alleles, including those conferring insecticide resistance. Most LDD takes place on human transport vessels and will typically be rarer and more directionally constrained than active flight but can connect populations and regions that are otherwise mutually inaccessible. These features make LDD worthy of specific consideration in mosquito research. This paper reviews recent evolutionary research on LDD and its consequences for mosquito populations and mosquito control. LDD is the main source of mosquito range expansions, and genomic methods can now trace the origins of new invasions to specific towns or cities. Genomic methods can also give a rough indication of the number of invaders, which if very small may lead to the stochastic loss of advantageous alleles during invasion bottlenecks. Once invasions are established, LDD spreads adaptive alleles between populations. Emerging insights into insecticide resistance evolution indicate that LDD has repeatedly spread resistance mutations across global species ranges, but these broad patterns are convoluted by two other evolutionary processes: parallel adaptation at the same gene or gene cluster and polygenic adaptation at different genes in different populations. Together, these processes have produced patterns of similarity and dissimilarity at resistance genes that are decoupled from geographical distance. LDD within cities is less well studied but is important for planning and evaluating local control efforts. Urban investigations of LDD may help identify areas experiencing weaker selection pressures from insecticides and isolated areas to target for control.

Evolutionary adaptation under climate change: Aedes sp. demonstrates potential to adapt to warming

Climate warming is expected to shift the distributions of mosquitoes and mosquito-borne diseases, promoting expansions at cool range edges and contractions at warm range edges. However, whether mosquito populations could maintain their warm edges through evolutionary adaptation remains unknown. Here, we investigate the potential for thermal adaptation in Aedes sierrensis, a congener of the major disease vector species that experiences large thermal gradients in its native range, by assaying tolerance to prolonged and acute heat exposure, and its genetic basis in a diverse, field-derived population. We found pervasive evidence of heritable genetic variation in mosquito heat tolerance, and phenotypic trade-offs in tolerance to prolonged versus acute heat exposure. Further, we found genomic variation associated with prolonged heat tolerance was clustered in several regions of the genome, suggesting the presence of larger structural variants such as chromosomal inversions. A simple evolutionary model based on our data estimates that the maximum rate of evolutionary adaptation in mosquito heat tolerance will exceed the projected rate of climate warming, implying the potential for mosquitoes to track warming via genetic adaptation.

Genomic diversity of the African malaria vector Anopheles funestus

Anopheles funestus s.s. is a formidable human malaria vector across sub-Saharan Africa. To understand how the species is evolving, especially in response to malaria vector control, we sequenced 656 modern specimens (collected 2014-2018) and 45 historic specimens (collected 1927-1967) from 16 African countries. We find high levels of genetic variation with clear and stable continental patterns. Six segregating inversions might be involved in adaptation of local ecotypes. Strong recent signals of selection centred on canonical insecticide resistance genes are shared by multiple populations. A promising gene drive target in An. gambiae is highly conserved in An. funestus. This work represents a significant advance in our understanding of the genetic diversity and population structure of An. funestus and will enable smarter targeted malaria control.

Evolutionary adaptation under climate change: Aedes sp. demonstrates potential to adapt to warming

Climate warming is expected to shift the distributions of mosquitoes and mosquito-borne diseases, facilitating expansions at cool range edges and contractions at warm range edges. However, whether mosquito populations could maintain their warm edges through evolutionary adaptation remains unknown. Here, we investigate the potential for thermal adaptation in Aedes sierrensis, a congener of the major disease vector species that experiences large thermal gradients in its native range, by assaying tolerance to prolonged and acute heat exposure, and its genetic basis in a diverse, field-derived population. We found pervasive evidence of heritable genetic variation in acute heat tolerance, which phenotypically trades off with tolerance to prolonged heat exposure. A simple evolutionary model based on our data shows that the estimated maximum rate of evolutionary adaptation in mosquito heat tolerance typically exceeds that of projected climate warming under idealized conditions. Our findings indicate that natural mosquito populations may have the potential to track projected warming via genetic adaptation. Prior climate-based projections may thus underestimate the range of mosquito and mosquito-borne disease distributions under future climate conditions.

Genomic Signatures of Microgeographic Adaptation in Anopheles coluzzii Along an Anthropogenic Gradient in Gabon

Species distributed across heterogeneous environments often evolve locally adapted populations, but understanding how these persist in the presence of homogenizing gene flow remains puzzling. In Gabon, Anopheles coluzzii, a major African malaria mosquito is found along an ecological gradient, including a sylvatic population, away of any human presence. This study identifies into the genomic signatures of local adaptation in populations from distinct environments including the urban area of Libreville, and two proximate sites 10km apart in the La Lopé National Park (LLP), a village and its sylvatic neighborhood. Whole genome re-sequencing of 96 mosquitoes unveiled ∼ 5.7millions high-quality single nucleotide polymorphisms. Coalescent-based demographic analyses suggest an ∼ 8,000-year-old divergence between Libreville and La Lopé populations, followed by a secondary contact ( ∼ 4,000 ybp) resulting in asymmetric effective gene flow. The urban population displayed reduced effective size, evidence of inbreeding, and strong selection pressures for adaptation to urban settings, as suggested by the hard selective sweeps associated with genes involved in detoxification and insecticide resistance. In contrast, the two geographically proximate LLP populations showed larger effective sizes, and distinctive genomic differences in selective signals, notably soft-selective sweeps on the standing genetic variation. Although neutral loci and chromosomal inversions failed to discriminate between LLP populations, our findings support that microgeographic adaptation can swiftly emerge through selection on standing genetic variation despite high gene flow. This study contributes to the growing understanding of evolution of populations in heterogeneous environments amid ongoing gene flow and how major malaria mosquitoes adapt to human.

Significance

Anopheles coluzzii , a major African malaria vector, thrives from humid rainforests to dry savannahs and coastal areas. This ecological success is linked to its close association with domestic settings, with human playing significant roles in driving the recent urban evolution of this mosquito. Our research explores the assumption that these mosquitoes are strictly dependent on human habitats, by conducting whole-genome sequencing on An. coluzzii specimens from urban, rural, and sylvatic sites in Gabon. We found that urban mosquitoes show de novo genetic signatures of human-driven vector control, while rural and sylvatic mosquitoes exhibit distinctive genetic evidence of local adaptations derived from standing genetic variation. Understanding adaptation mechanisms of this mosquito is therefore crucial to predict evolution of vector control strategies.

Signatures of adaptation at key insecticide resistance loci in Anopheles gambiae in Southern Ghana revealed by reduced-coverage WGS

Resistance to insecticides and adaptation to a diverse range of environments present challenges to Anopheles gambiae s.l. mosquito control efforts in sub-Saharan Africa. Whole-genome-sequencing is often employed for identifying the genomic basis underlying adaptation in Anopheles, but remains expensive for large-scale surveys. Reduced coverage whole-genome-sequencing can identify regions of the genome involved in adaptation at a lower cost, but is currently untested in Anopheles mosquitoes. Here, we use reduced coverage WGS to investigate population genetic structure and identify signatures of local adaptation in Anopheles mosquitoes across southern Ghana. In contrast to previous analyses, we find no structuring by ecoregion, with Anopheles coluzzii and Anopheles gambiae populations largely displaying the hallmarks of large, unstructured populations. However, we find signatures of selection at insecticide resistance loci that appear ubiquitous across ecoregions in An. coluzzii, and strongest in forest ecoregions in An. gambiae. Our study highlights resistance candidate genes in this region, and validates reduced coverage WGS, potentially to very low coverage levels, for population genomics and exploratory surveys for adaptation in Anopheles taxa.

Interpreting generative adversarial networks to infer natural selection from genetic data

Understanding natural selection and other forms of non-neutrality is a major focus for the use of machine learning in population genetics. Existing methods rely on computationally intensive simulated training data. Unlike efficient neutral coalescent simulations for demographic inference, realistic simulations of selection typically require slow forward simulations. Because there are many possible modes of selection, a high dimensional parameter space must be explored, with no guarantee that the simulated models are close to the real processes. Finally, it is difficult to interpret trained neural networks, leading to a lack of understanding about what features contribute to classification. Here we develop a new approach to detect selection and other local evolutionary processes that requires relatively few selection simulations during training. We build upon a generative adversarial network trained to simulate realistic neutral data. This consists of a generator (fitted demographic model), and a discriminator (convolutional neural network) that predicts whether a genomic region is real or fake. As the generator can only generate data under neutral demographic processes, regions of real data that the discriminator recognizes as having a high probability of being "real" do not fit the neutral demographic model and are therefore candidates for targets of selection. To incentivize identification of a specific mode of selection, we fine-tune the discriminator with a small number of custom non-neutral simulations. We show that this approach has high power to detect various forms of selection in simulations, and that it finds regions under positive selection identified by state-of-the-art population genetic methods in three human populations. Finally, we show how to interpret the trained networks by clustering hidden units of the discriminator based on their correlation patterns with known summary statistics.