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Miles, A.

Publications and source records attributed to Miles, A..

At least 19 recordsLinked to original sources

Validation of a quantitative PCR assay for the detection and quantification of the nematode Litylenchus crenatae in American beech leaf tissue

Beech leaf disease (BLD), caused by the migratory plant pathogenic nematode, Litylenchus crenatae (LC, Anguinidae) is presently one of the most concerning forest diseases in the United States. BLD has spread rapidly across the landscape and is currently found in 15 U.S. states and Ontario, Canadian, making monitoring a top priority. Here, we report on the development and testing of a probe-based qPCR detection assay that integrates previously reported LC-specific primers with a newly designed probe, enabling sensitive and reproducible quantification of nematodes in plant and non-plant matrices. This assay exhibited strong in silico and in planta specificity and high quantitative performance (R2 = 0.988-0.996), with amplification efficiencies of 90.0-96.8%. The assay also performed consistently on LC-spiked spore trap membranes used to monitor the fungal aerobiome, despite matrix-associated shifts in amplification efficiency. These results support the utility of the assay for monitoring and surveillance. The reliability was further evaluated by two independent diagnostic laboratories, demonstrating high inter-laboratory concordance in detection and strong agreement in relative quantification. The analytical sensitivity and reproducible performance of the assay align with key validation principles outlined by the APS Diagnostic Assay Validation Network (DAVN) and support its application as a molecular tool in experimental, diagnostic, and surveillance contexts, with important implications for national and international LC monitoring and disease management.

molecular biology↗

Genomic connectivity and the spread of adaptive insecticide resistance alleles in Anopheles arabiensis from East Africa

Population connectivity and adaptive gene flow in disease vectors can shape the emergence and spread of insecticide resistance, with direct implications for control strategies such as insecticide spraying or the use of bed nets for malaria control. Using whole-genome sequencing, we first resolved the geographic population structure of the major but understudied malaria vector, Anopheles arabiensis, across the East African region, including the geographically diverse country of Ethiopia. We then assessed evidence for adaptive gene flow of insecticide resistance alleles across the region. Within Ethiopia, Central Rift Valley populations flanked by mountainous terrain were subject to restricted gene flow, although higher connectivity with the southwestern populations suggests an intermediate point of genetic exchange with the rest of Ethiopia. Anopheles arabiensis from western and northernmost Ethiopia were connected to populations from a similarly arid environment in Turkana - Kenya. Furthermore, broad-scale analysis revealed that populations from the rest of Kenya were connected with those from Uganda and Tanzania, but finer-scale analysis revealed more subtle structuring along the Rift Valley flanks, underscoring the role of landscape features in shaping patterns of gene flow. Adaptive gene flow analyses of diplotype clustering revealed that resistance alleles such as Cyp6aa/p and Gste2 copy number variants (CNV) were widely spread across East Africa despite the geographical population structuring we observed. At the Gste2 locus, An. arabiensis from Ethiopia and Kenya carried a newly annotated CNV spanning chromosome position 3R:28,596,832-28,606,222 linked to the non-synonymous SNP V47L, which was only at a low frequency in Kenya. Collectively, our findings demonstrate that An. arabiensis is subject to transboundary movement of resistance alleles, highlighting the need for coordinated cross-country vector management. Although areas of high connectivity may challenge genetic control technologies such as gene drives, more isolated populations may provide opportunities for targeted deployment. SignificanceMosquitoes movement across landscapes determines how insecticide resistance spreads, yet the genomic connectivity of Anopheles arabiensis populations in East Africa is understudied. Using whole genome data, we show that geographic features such as the Rift Valley restrict gene flow in Ethiopia, with western and northernmost Ethiopia connecting to Turkana, while Kenyan populations outside Turkana connect further south with Tanzania and Uganda. Despite these geographic barriers, resistance variants at genes such as Cyp6aa/p and Gste2 spread widely through adaptive gene flow, including a newly annotated CNV allele at Gste2 in Ethiopia and Kenya. These findings demonstrate that resistance alleles move across national borders, underscoring the need for coordinated regional vector management. They also highlight that while broader connectivity may limit genetic control tools such as gene drive, more isolated populations offer opportunities for targeted deployment.

genomics↗

Genomic signatures of selection in Anopheles funestus reveal shared and population-specific adaptive variation across African populations

Insecticide resistance in Anopheles funestus threatens malaria vector control across sub-Saharan Africa, yet genomic signatures of selection across geographically structured populations remain poorly understood. We analysed whole-genome sequence data from 635 An. funestus mosquitoes from West (Senegal, Guinea, Nigeria), Central (Cameroon), and East Africa (Kenya) to characterise population structure and identify targets of recent positive selection. Population genomic analyses revealed strong differentiation between East African and West/Central African populations, with finer-scale structuring within West Africa. Genome-wide selection scans using H12 identified sweep regions on chromosome arms 2RL and 3RL, overlapping a cytochrome P450 cluster and the gamma-aminobutyric acid (GABA) receptor locus respectively. iSAFE prioritised candidate variants within these sweeps: non-synonymous substitutions in CYP6A14 were identified at high frequencies in Guinea, Nigeria, and Cameroon, while population-restricted variants implicated octopamine receptor genes on 2RL and the GABA receptor on 3RL. Diplotype clustering and copy number variation analyses confirmed the causal role of candidate variants, embedded within extended haplotypes of reduced heterozygosity consistent with recent positive selection. These findings demonstrate that adaptive evolution in An. funestus reflects both shared and population-specific selective processes shaped by geography and ecological context. Whereas selection on detoxification pathways appears widespread, localised signals in neuromodulatory loci, including the GABA receptor and octopamine-related genes, reveal that biological systems beyond metabolic resistance contribute to mosquito adaptation. The convergence of selective signals across these gene classes highlights neuromodulatory pathways as potential complementary targets for next-generation vector control strategies.

genomics↗

Direct Reconstruction of DC Cortical Conductivity from Large-Scale Electron Microscopy Data

Electrical conductivity of cortical gray matter governs the magnitude and spatial distribution of electric fields generated by brain stimulation and intrinsic neuronal activity measured with M/EEG and intracortical recordings. However, reported macroscopic conductivity values vary by more than threefold, limiting the fidelity of bioelectromagnetic models and leaving unresolved whether this variability reflects measurement uncertainty or genuine structural heterogeneity of cortical tissue. Here, we present a multiscale computational framework that, for the first time, attempts to derive mesoscale conductivity maps of mouse visual cortex at 50-{micro}m resolution directly from large-volume, segmented nanometer-scale electron microscopy data. The Minnie 65 subvolume of the MICrONS dataset is accurately subdivided into 1,224 50-{micro}m cubic blocks. Each block contains, on average, 40-50 million membrane facets of a highly convoluted and dense cellular structure. Three orthogonal electrode pairs are applied to each isolated block to estimate the three principal components of the conductivity tensor. Quasistatic electric modeling is enabled by an iterative boundary-element fast multipole method (BEM-FMM) under the approximation of non-conducting membranes (DC conductivity). Spatially averaged conductivity values predicted by our framework agree well with prior low-resolution measurements in rats, validating the approach. At the same time, the resulting mesoscale maps reveal pronounced conductivity granularity at 50-100 {micro}m scales as well as significant variations in both radial and tangential directions. These results indicate that mesoscale conductivity heterogeneity could be an intrinsic structural property of the cortex. Limitations and extensions of this study are discussed in detail.

neuroscience↗

An atlas of positive selection in the genomes of major malaria vectors

Insecticide resistance poses a major threat to malaria control efforts in Africa, yet our understanding of the genomic basis of adaptation in malaria vectors remains incomplete. Here we present a comprehensive atlas of recent positive selection in natural populations of the major African malaria vectors; the An. gambiae species complex and An. funestus. By analyzing whole-genome sequence data from 4,306 mosquitoes collected across twenty-one countries, we identify and characterize both known and novel genomic regions under strong positive selection. We develop an innovative approach for identifying and localising selection signals, and find extensive evidence for parallel evolution between species, with all important loci in An. funestus also under selection in An. gambiae s.l. We confirm intense selection at established resistance loci including known target site proteins (Vgsc, Rdl, Ace1) and metabolic enzymes (Cyp6p, Cyp9k1, Gste, Coeaexf) and describe novel signals at a diacylglycerol kinase on the X chromosome, and in An. gambiae s.l, at the metabolic regulator Keap1. To support real-time monitoring of emerging variants threatening vector control, we present an open-source web resource containing detailed selection scan results for all cohorts. The resource is driven by an automated computational workflow, which enables continuous updates as new whole-genome data are generated. The selection atlas provides a foundation for understanding vector adaptation to insecticide-based interventions and we hope will inform evidence-based resistance management strategies that are critical for sustaining malaria control.

genomics↗

Signatures of selection and mechanisms of insecticide resistance in Ugandan Anopheles funestus: Insights from embedding translational genomics into the LLINEUP cluster randomised trial.

In response to the emerging threat of insecticide resistance in malaria vectors, insecticides are being repurposed for vector control or developed de novo. Good stewardship of these finite new resources is essential if disease control programmes are to remain effective. This is dependent on timely data to help guide evidence-based decision-making for National Malaria Control programmes (NMCPs). By embedding genomics into cluster randomized control trials (cRCTs), we can perform surveillance and early detection of insecticide resistance variants to new and repurposed chemicals in natural field conditions, supporting effective stewardship. The LLIN Evaluation Uganda Project (LLINEUP) trial evaluated the efficacy of pyrethroid-piperonyl butoxide (PBO) and pyrethroids-only long-lasting insecticidal nets (LLINs). It was conducted in Uganda between 2017-2020 and was the largest cRCT to date, covering 40% of the country in 104 health sub-districts. We embedded genomic surveillance within LLINEUP to detect and track insecticide resistance variants. At baseline and throughout the trial, we sampled Anopheles mosquitoes with Prokopack aspirators and performed Illumina whole-genome sequencing. We show that An. funestus populations were relatively unaffected by the interventions, compared to An. gambiae s.l., which were markedly reduced six months following LLIN deployment. Standard approaches for describing genetic diversity and population structure e.g. fixation index (FST), Principal Component Analysis (PCA) and Neighbour-Joining (NJ) trees, were consistent with the density observations and suggestive of a single large An. funestus population in Uganda with little genetic differentiation. Genome-wide selection scans revealed strong signals of selection at the Resistance to pyrethroid-1 (RP1) locus and Cyp9k1, both loci previously implicated in pyrethroid resistance. We report two additional loci, eye diacylglycerol kinase (Dgk) ({cong}13.5Mb on the X chromosome) and O-mannosyl-transferase (TMC-like) ({cong}67.9Mb on 3RL) that showed signals of selection. Known DDT and permethrin resistance-associated variants at the Gste2 locus, L119F and L119V, were also identified. Over the trial period, changes in haplotype frequencies were observed in regions under selection, with more pronounced shifts in the PBO arm. Notably, there were significant reductions in the frequencies of swept haplotypes (measured by delta ({Delta}) H12) in the Dgk and Cyp6p9a regions, while significant increases in haplotype frequency were observed at Gste2 and Cyp9k1 loci. Our findings reveal the differential impact of the trial on An. gambiae s.l. and An. funestus densities and the differing responses of An. funestus populations to pyrethroid and pyrethroid-PBO selection pressure. These insights underscore the potential value of tailored, species- and region-specific vector control strategies, supported by regional genetic surveillance, to better control insecticide resistance evolution and spread. By embedding genomic surveillance in cRCTs we can facilitate the discovery of putative resistance variants and can provide evidence of their impact on vector control tool efficacy; both of crucial importance to evidence-based deployment of vector control tools by NMCPs.

genomics↗

Spatially-explicit genomics of An. gambiae s.l uncovers fine-scale population structure and mechanisms of insecticide resistance

Progress in malaria control in sub-Saharan Africa is stalling, partly due to the spread of insecticide resistance in Anopheles vectors. Monitoring the evolution of insecticide resistance alleles and their spatial heterogeneity is important for malaria control programmes, and genomic surveillance has emerged as a pivotal tool for this purpose. Earlier genomics research has typically employed convenience-based sampling, and research has yet to be performed to optimise sampling regimens for malaria vector genomics. In an earlier study, we developed a spatially explicit sampling framework that considers the underlying ecology to enable sampling mosquitoes with reduced bias. We applied this framework to sample and perform whole-genome sequencing on 485 individual specimens of An. gambiae s.l mosquitoes from Obuasi, central Ghana, an area with extensive gold mining activities. In this region, An. gambiae s.l have been documented as highly resistant to multiple insecticides, including pyrethroids used for the treatment of bed-nets. High resolution of fine-scale population structure enabled the detection of isolation-by-distance in An. coluzzii in Obuasi, whilst finding that at this scale, geographic distance, rather than the underlying habitat, drives population structure. We examine methods to estimate mosquito kinship, demonstrating that polymorphic chromosomal inversions significantly confound established analytical tools, while revealing how the mosquitos chromosome architecture generates high variance in genetic relatedness among kin. Using genome-wide selection scans and clustering, we discover the novel mutations Gste2-F120L and Cyp9K1-N224I in detoxification enzymes that are driving selective sweeps, likely in response to insecticidal pressure. We find that the frequencies of some resistance variants are associated with artisanal-gold mines, and elucidate the continued evolution of the Voltage-gated sodium channel, the target of pyrethroid insecticides. Overall, we show that sampling vectors strategically may enhance our ability to perform effective genomic surveillance.

genomics↗

Genetic Surveillance Reveals Differential Evolutionary Dynamic of Anopheles gambiae Under Contrasting Insecticidal Tools used in Malaria control

Malaria, a febrile disease caused by the Plasmodium parasites and transmitted by mosquitoes, is a leading cause of mortality in children under 5 in endemic countries. The widespread deployment of insecticide-treated bed nets (ITNs) has significantly reduced malaria transmission, but rising levels of insecticide resistance threatens to halt the progress. Monitoring insecticide resistance is vital for effective vector control, particularly when deploying new tools. Understanding mosquito population responses to these interventions is crucial for guiding control programmes in making informed decisions about the selection, timing, and geographic deployment of tools. This genomic study investigates the demographic and evolutionary consequences on the malaria vector Anopheles gambiae of deploying standard ITNs (containing only pyrethroids) and pyrethroid-PBO nets (containing pyrethroids plus the synergist piperonyl butoxide) during a clinical trial in Uganda. Despite substantial reductions in indoor mosquito densities in the clinical trial, estimates of nucleotide diversity ({pi}) and linkage disequilibrium revealed no significant decline in effective population size, reflecting continued large population size even after effective control. Marked allele frequency shifts at resistance-associated loci indicated strong selection pressures driven by the interventions, with distinct selective dynamics between the two net types, highlighting alternative pyrethroid detoxification pathways in the presence of PBO. A duplication in the Cyp9k1 gene significantly increased in frequency in populations exposed to pyrethroid-only nets but decreased in populations exposed to PBO-treated nets, suggesting that selection for over-expression of this gene is removed when this resistance mechanism is impacted by PBO. An alternative potential detoxification mechanism was selected within a region of the 2La chromosomal inversion on chromosome 2L, which encompasses the UDP-glucose 6-dehydrogenase gene. This variant consistently increased in frequency when exposed to PBO-treated nets. Additionally, pyrethroid-only nets selected for a novel locus on the X chromosome containing the diacylglycerol kinase gene, which is potentially linked to behavioural adaptations through its role in neurotransmission modulation. Our findings underscore the importance of genomic surveillance in vector control, revealing distinct evolutionary dynamics of insecticide resistance mechanisms in the presence of PBO. While ITNs remain effective, the persistence and evolution of resistance-associated alleles highlight the need for adaptive and dynamic resistance management strategies. By integrating high-resolution genomic data with epidemiological and entomological monitoring, this study offers actionable insights to sustain malaria control efforts amid the ongoing challenge of insecticide resistance.

genomics↗

Targeted genomic surveillance of insecticide resistance in African malaria vectors

The emergence of insecticide resistance is threatening the efforts of malaria control programmes, which rely heavily on a limited arsenal of insecticidal tools, such as insecticide-treated bed nets. Importantly, genomic surveillance of malaria vectors can provide critical, policy-relevant insights into the presence and evolution of insecticide resistance, allowing us to maintain and extend the shelf life of these interventions. Yet the complex genetic architecture of resistance, combined with resource constraints in malaria-endemic settings, have thus far precluded the widespread use of genomics in routine surveillance. Meanwhile, stakeholders in sub-Saharan Africa are moving towards locally driven, decentralised generation of genomic data, underscoring the need for standardised and robust genomics workflows. To address this need, we demonstrate an approach to targeted genomic surveillance in Anopheles gambiae s.l with Illumina sequencing. We target 90 genomic loci in the Anopheles gambiae s.l genome, including 55 resistance-associated mutations and 35 ancestry informative markers. This protocol is coupled with advanced, automated software for accurate and reproducible variant analysis. We are able to elucidate population structure and ancestry in our cohorts and accurately identify most species in the An. gambiae species complex. We report frequencies of variants at insecticide-resistance loci and explore the continued evolution of the pyrethroid target site, the Voltage-gated sodium channel. Applying the platform to a recently established colony of field-caught resistant mosquitoes (Siaya, Kenya), we identified seven independent resistance-associated variants contributing to reduced efficacy of insecticide-treated nets in East Africa. Additionally, we leverage a machine learning algorithm (XGBoost) to demonstrate the possibility of predicting bioassay mortality using genotypes alone. This achieved high accuracy (75%), demonstrating the potential of targeted genomics to predictively monitor insecticide resistance. Together these tools provide a practical, scalable solution for resistance monitoring while advancing the goal of building local genomic surveillance capacity in sub-Saharan Africa.

genomics↗

Distinct Genetic Populations and Resistance Backgrounds of the Malaria Vector Anopheles funestus in Tanzania

Population genetic analysis of mosquitoes is becoming increasingly important for understanding the distribution of insecticide resistance alleles, devising sustainable insecticide-based vector control approaches, and how malaria vector populations are structured in space. Anopheles funestus is the dominant malaria vector in Tanzania and most parts of East and Southern Africa. To better understand its population genomic structure in Tanzania, we sequenced the genomes of 334 individual An. funestus mosquitoes from 11 administrative regions. We found two genetically differentiated populations; one inland and at high altitude (found in Katavi, Kagera, Kigoma, and Mwanza) and a second coastal, at low altitude (found in Pwani, Morogoro, Tanga, Ruvuma, Mtwara, Dodoma, and Lindi), with differences in genetic diversity and inbreeding. We found asynchronous selective sweeps, associated with insecticide resistance phenotypes, at the Cyp9k1 gene, and Cyp6p gene cluster, with distinct copy number-variant profiles between the coastal and inland populations. These results suggest that inland and coastal An. funestus populations have divergent histories, with the arid, central region of Tanzania, which also contains the Rift Valley being a possible barrier to gene flow. Such population disconnectedness should be considered for insecticide deployment, resistance management, and the rollout of novel genetic- based vector control approaches. These findings provide the most detailed study of Tanzanian An. funestus population structure and resistance genetics to date. Future research should examine the epidemiological relevance of this discontinuity in gene flow and whether these populations have different malaria transmission abilities.

genetics↗

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.

genomics↗

Analysis-ready VCF at Biobank scale using Zarr

BackgroundVariant Call Format (VCF) is the standard file format for interchanging genetic variation data and associated quality control metrics. The usual row-wise encoding of the VCF data model (either as text or packed binary) emphasises efficient retrieval of all data for a given variant, but accessing data on a field or sample basis is inefficient. Biobank scale datasets currently available consist of hundreds of thousands of whole genomes and hundreds of terabytes of compressed VCF. Row-wise data storage is fundamentally unsuitable and a more scalable approach is needed. ResultsZarr is a format for storing multi-dimensional data that is widely used across the sciences, and is ideally suited to massively parallel processing. We present the VCF Zarr specification, an encoding of the VCF data model using Zarr, along with fundamental software infrastructure for efficient and reliable conversion at scale. We show how this format is far more efficient than standard VCF based approaches, and competitive with specialised methods for storing genotype data in terms of compression ratios and single-threaded calculation performance. We present case studies on subsets of three large human datasets (Genomics England: n=78,195; Our Future Health: n=651,050; All of Us: n=245,394) along with whole genome datasets for Norway Spruce (n=1,063) and SARS-CoV-2 (n=4,484,157). We demonstrate the potential for VCF Zarr to enable a new generation of high-performance and cost-effective applications via illustrative examples using cloud computing and GPUs. ConclusionsLarge row-encoded VCF files are a major bottleneck for current research, and storing and processing these files incurs a substantial cost. The VCF Zarr specification, building on widely-used, open-source technologies has the potential to greatly reduce these costs, and may enable a diverse ecosystem of next-generation tools for analysing genetic variation data directly from cloud-based object stores, while maintaining compatibility with existing file-oriented workflows. Key PointsO_LIVCF is widely supported, and the underlying data model entrenched in bioinformatics pipelines. C_LIO_LIThe standard row-wise encoding as text (or binary) is inherently inefficient for large-scale data processing. C_LIO_LIThe Zarr format provides an efficient solution, by encoding fields in the VCF separately in chunk-compressed binary format. C_LI

bioinformatics↗

Variation in spatial population structure in the Anopheles gambiae species complex

Anopheles gambiae, Anopheles coluzzii, and Anopheles arabiensis are three of the most widespread vectors of malaria parasites, with geographical ranges stretching across wide swaths of Africa. Understanding the population structure of these closely related species, including the extent to which populations are connected by gene flow, is essential for understanding how vector control implemented in one location might indirectly affect vector populations in other locations. Here, we assessed the population structure of each species based on a combined data set of publicly available and newly processed whole-genome sequences. The data set included single nucleotide polymorphisms from whole genomes of 2,410 individual mosquitoes sampled from 128 locations across 19 African countries. We found that A. gambiae sampled from several countries in West and Central Africa showed low genetic differentiation from each other according to principal components analysis (PCA) and ADMIXTURE modeling. Using Estimated Effective Migration Surfaces (EEMS), we showed that this low genetic differentiation indicates high effective migration rates for A. gambiae across this region. Outside of this region, we found eight groups of sampling locations from Central, East, and Southern Africa for which A. gambiae showed higher genetic differentiation, and lower effective migration rates, between each other and the West/Central Africa group. These results indicate that the barriers to and corridors for migration between populations of A. gambiae differ across the geographical range of this malaria vector species. Using the same methods, we found higher genetic differentiation and lower migration rates between populations of A. coluzzii in West and Central Africa than for A. gambiae in the same region. In contrast, we found lower genetic differentiation and higher migration rates between populations of A. arabiensis in Tanzania, compared to A. gambiae in the same region. These differences between A. gambiae, A. coluzzii, and A. arabiensis indicate that migration barriers and corridors may vary, even between very closely related species. Overall, our results demonstrate that migration rates vary both within and between species of Anopheles mosquitoes, presumably based on species-specific responses to the ecological or environmental conditions that may impede or facilitate migration, and the geographical patterns of these conditions across the landscape. Together with previous findings, this study provides robust evidence that migration rates between populations of malaria vectors depend on the ecological context, which should be considered when planning surveillance of vector populations, monitoring for insecticide resistance, and evaluating interventions.

ecology↗

Electromagnetic Modeling within a Microscopically Realistic Brain - Implications for Brain Stimulation

Modeling brain stimulation at the microscopic scale may reveal new paradigms for various stimulation modalities. We present the largest map to date of extracellular electric field distributions within a layer L2/L3 mouse primary visual cortex brain sample. This was enabled by the automated analysis of serial section electron microscopy images with improved handling of image defects, covering a volume of 250 x 140 x 90 m3. The map was obtained by applying a uniform brain stimulation electric field at three different polarizations and accurately computing microscopic field perturbations using the boundary element fast multipole method. We used the map to identify the effect of microscopic field perturbations on the activation thresholds of individual neurons. Previous relevant studies modeled a macroscopically homogeneous cortical volume. Our result shows that the microscopic field perturbations - an electric field spatial noise with a mean value of zero - only modestly influence the macroscopically predicted stimulation field strengths necessary for neuronal activation. The thresholds do not change by more than 10% on average. Under the stated limitations and assumptions of our method, this result justifies the conventional theory of "invisible" neurons embedded in a macroscopic brain model for transcranial magnetic and transcranial electrical stimulation. However, our result is solely sample-specific and largely neglects the effect of the microcapillary network. Furthermore, we only considered the uniform impressed field and a single- pulse stimulation time course. Significance statementThis study is arguably the first attempt to model brain stimulation at the microscopic scale, enabled by automated analysis of modern scanning electron microscopy images of the brain. It concentrates on modeling microscopic perturbations of the extracellular electric field caused by the physical cell structure and is applicable to any type of brain stimulation. Data availability statementPost-processed cell CAD models (383, stl format), microcapillary CAD models (34, stl format), post-processed neuron morphologies (267, swc format), extracellular electric field and potential distributions at different polarizations (267x3, MATLAB format), *.ses projects files for biophysical modeling with Neuron software (267x2, Neuron format), and computed neuron activating thresholds at different conditions (267x8, Excel tables, without the sample polarization correction from Section 2.8) are made available online through BossDB, a volumetric open-source database for 3D and 4D neuroscience data.

neuroscience↗

Cryptic population structure and insecticide resistance in Anopheles gambiae from the southern Democratic Republic of Congo

The Democratic Republic of Congo (DRC) suffers from one of the highest malaria burdens worldwide, but information on its Anopheles vector populations is relatively limited. Preventative malaria control in DRC is reliant on pyrethroid-treated nets, raising concerns over the potential impacts of insecticide resistance. We sampled Anopheles gambiae from three geographically distinct populations (Kimpese, Kapolowe and Mikalayi) in southern DRC, collecting from three sub-sites per population and characterising mosquito collections from each for resistance to pyrethroids using WHO tube bioassays. Resistance to each of three different pyrethroids was generally high in An. gambiae with <92% mortality in all tests, but varied between collections, with mosquitoes from Kimpese being the most resistant. Whole genome sequencing of 165 An. gambiae revealed evidence for genetic differentiation between Kimpese and Kapolowe / Mikalayi, but not between the latter two sample sites despite separation of approximately 800km. Surprisingly, there was evidence of population structure at a small spatial scale between collection subsites in Kimpese, despite separation of just tens of kilometres. Intra-population (H12) and inter-population (FST) genome scans identified multiple peaks corresponding to genes associated with insecticide resistance such as the voltage gated sodium channel (Vgsc) target site on chromosome 2L, a Cyp6 cytochrome P450 cluster on chromosome arm 2R, and the Cyp9k1 P450 gene on chromosome X. In addition, in the Kimpese subsites, the P450 redox partner gene Cpr showed evidence for contemporary selection (H12) and population differentiation (FST) meriting further exploration as a potential resistance associated marker.

evolutionary biology↗

Copy number variants underlie the major selective sweeps in insecticide resistance genes in Anopheles arabiensis from Tanzania.

To keep ahead of the evolution of resistance to insecticides in mosquitoes, national malaria control programmes must make use of a range of insecticides, both old and new, while monitoring resistance mechanisms. Knowledge of the mechanisms of resistance remains limited in Anopheles arabiensis, which in many parts of Africa is of increasing importance because it is apparently less susceptible to many indoor control interventions. Furthermore, comparatively little is known in general about resistance to non-pyrethroid insecticides such as pirimiphos-methyl (PM), which are crucial for effective control in the context of resistance to pyrethroids. We performed a genome-wide association study to determine the molecular mechanisms of resistance to deltamethrin (commonly used in bednets) and PM, in An. arabiensis from two regions in Tanzania. Genomic regions of positive selection in these populations were largely driven by copy number variants (CNVs) in gene families involved in resistance to these two insecticides. We found evidence of a new gene cluster involved in resistance to PM, identifying a strong selective sweep tied to a CNV in the Coeae2g-Coeae6g cluster of carboxylesterase genes. Using complementary data from An. coluzzii in Ghana, we show that copy number at this locus is significantly associated with PM resistance. Similarly, for deltamethrin, resistance was strongly associated with a novel CNV allele in the Cyp6aa / Cyp6p cluster. Against this background of metabolic resistance, target site resistance was very rare or absent for both insecticides. Mutations in the pyrethroid target site Vgsc were at very low frequency in Tanzania, yet combining these samples with three An. arabiensis individuals from West Africa revealed a startling diversity of evolutionary origins of target site resistance, with up to 5 independent origins of Vgsc-995 mutations found within just 8 haplotypes. Thus, despite having been first recorded over 10 years ago, Vgsc resistance mutations in Tanzanian An. arabiensis have remained at stable low frequencies. Overall, our results provide a new copy number marker for monitoring resistance to PM in malaria mosquitoes, and reveal the complex picture of resistance patterns in An. arabiensis.

genomics↗

Parallel evolution in mosquito vectors - a duplicated esterase locus is associated with resistance to pirimiphos-methyl in An. gambiae

The primary control methods for the African malaria mosquito, Anopheles gambiae, are based on insecticidal interventions. Emerging resistance to these compounds is therefore of major concern to malaria control programmes. The organophosphate, pirimiphos-methyl, is a relatively new chemical in the vector control armoury but is now widely used in indoor residual spray campaigns. Whilst generally effective, phenotypic resistance has developed in some areas in malaria vectors. Here, we used a population genomic approach to identify novel mechanisms of resistance to pirimiphos-methyl in Anopheles gambiae s.l mosquitoes. In multiple populations, we found large and repeated signals of selection at a locus containing a cluster of detoxification enzymes, some of whose orthologs are known to confer resistance to organophosphates in Culex pipiens. Close examination revealed a pair of alpha-esterases, Coeae1f and Coeae2f, and a complex and diverse pattern of haplotypes under selection in An. gambiae, An. coluzzii and An. arabiensis. As in Cx. pipiens, copy number variation seems to play a role in the evolution of insecticide resistance at this locus. We used diplotype clustering to examine whether these signals arise from parallel evolution or adaptive introgression. Using whole-genome sequenced phenotyped samples, we found that in West Africa, a copy number variant in Anopheles gambiae is associated with resistance to pirimiphos-methyl. Overall, we demonstrate a striking example of contemporary parallel evolution which has important implications for malaria control programmes.

evolutionary biology↗

Mechanisms of transcriptional regulation in Anopheles gambiae revealed by allele specific expression

Malaria control relies on insecticides targeting the mosquito vector, but this is increasingly compromised by insecticide resistance, which can be achieved by elevated expression of detoxifying enzymes that metabolize the insecticide. In diploid organisms, gene expression is regulated both in cis, by regulatory sequences on the same chromosome, and by trans acting factors, affecting both alleles equally. Differing levels of transcription can be caused by mutations in cis-regulatory modules (CRM), but few of these have been identified in mosquitoes. We crossed bendiocarb resistant and susceptible Anopheles gambiae strains to identify cis-regulated genes that might be responsible for the resistant phenotype using RNAseq, and cis-regulatory module sequences controlling gene expression in insecticide resistance relevant tissues were predicted using machine learning. We found 115 genes showing allele specific expression in hybrids of insecticide susceptible and resistant strains, suggesting cis regulation is an important mechanism of gene expression regulation in Anopheles gambiae. The genes showing allele specific expression included a higher proportion of Anopheles specific genes on average younger than genes those with balanced allelic expression. Author SummaryThe evolution of insecticide resistance, including resistance that is due to changes in the expression levels of certain resistance associated genes is threatening progress in malaria control. We investigated how the expression of genes in the malaria vector Anopheles gambiae is controlled, by implementing a method for the first time in this species. Each mosquito inherits a set of chromosomes from both parents, so has a maternal and paternal copy of most genes. When a gene is expressed, the DNA encoding that gene is transcribed into messenger RNA. This process is controlled by the cellular environment and by other DNA sequences on the same chromosome as each gene. We crossed mosquitoes from insecticide resistant and susceptible strains to equalize the cellular environment and then measured the levels of messenger RNA from both gene copies. 115 genes showed consistently different messenger RNA levels between gene copies in most crosses, suggesting these genes are regulated by factors on the same chromosome. There were relatively more Anopheles specific genes with imbalanced expression. Using machine learning we identified DNA sequences that may be responsible for controlling gene expression in mosquito tissues; several of these sequences were close to genes with imbalanced expression.

genetics↗