The study focused on the Anopheles gambiae species complex, a group of morphologically identical mosquitoes that includes the most efficient malaria vectors in Africa. Within Burkina Faso, the dominant vectors are Anopheles coluzzii and Anopheles gambiae sensu stricto, alongside Anopheles arabiensis. Understanding whether these populations are genetically divided by geography is far from an academic question. If mosquito populations in different regions are genetically isolated, a control tool introduced in one place may fail to spread or may need to be tailored separately for each region. Conversely, if mosquitoes mix freely across the country, a single intervention could, in principle, ripple outward through the entire population.

To answer this question, the researchers collected mosquito specimens across three ecological settings in Burkina Faso using pyrethroid spray catches, the standard method for sampling indoor-resting mosquitoes. The whole genomes of the captured Anopheles gambiae sensu lato specimens were then sequenced under the Ag1000G framework, a major international effort to catalogue genomic variation in African malaria vectors. The team analysed the resulting data using MalariaGEN resources, applying tools such as principal component analysis, ancestry-informative markers, pairwise genetic differentiation measures and neighbour joining trees to dissect the structure of the populations at single nucleotide polymorphism resolution.

The headline result is striking: neither Anopheles coluzzii nor Anopheles gambiae sensu stricto showed any detectable geographical population structure across the three climatic zones sampled. Mosquitoes from the Soudanian south and the Sahelian north of the country were, genomically speaking, members of the same interbreeding populations. This pattern points to high levels of gene flow within Burkina Faso, meaning mosquitoes are moving, or their genes are moving, across ecological boundaries at a rate sufficient to erase any regional genetic fingerprints. For two species that thrive in such different environments, the absence of differentiation is a powerful testament to their mobility and adaptability.

Anopheles arabiensis told a different story. This species displayed a weak but real structure that separated samples from the Hauts-Bassins region in the Soudanian zone from all other An. arabiensis samples in the study. In other words, while most of the country’s An. arabiensis mosquitoes appear well mixed, a distinct genetic signature sets the Hauts-Bassins population apart. The authors suggest this could reflect a distinct demographic history for that population. Indeed, their diversity analyses revealed evidence that An. arabiensis populations have undergone either a reduction in effective population size or a bottleneck, in contrast to the signals of population expansion observed across An. gambiae sensu lato more broadly.

The genomic toolkit behind these conclusions deserves attention. Nucleotide diversity and Watterson’s theta, two complementary estimators of genetic variation, were computed for each population, alongside Tajima’s D, a statistic sensitive to changes in population size. Heterozygosity was mapped across chromosome 3R in windows of ten thousand base pairs, allowing the team to examine variation at fine scale. Principal component analyses were performed both across the full dataset and per year, and pairwise differentiation was calculated within each species per region. The consistency of these independent lines of evidence strengthens the central claim that the two major vectors are panmictic, or freely interbreeding, across the country while An. arabiensis follows its own demographic trajectory.

One notable absence from the genomic data also caught the researchers’ attention. Two cryptic species, Anopheles goundry and Anopheles tengrela, previously identified within Burkina Faso, were not detected in this study. Cryptic species are lineages that look identical to their relatives but are genetically distinct, and their presence can complicate vector control because they may differ in behaviour, habitat preference or susceptibility to insecticides. Their non-detection in this nationwide sampling suggests these lineages are either rare, locally restricted or no longer circulating at detectable levels, though the authors are careful to frame this as an observation from the sampled specimens rather than proof of absence.

The implications for existing vector control are immediate. Long-lasting insecticidal nets and indoor residual spraying remain the backbone of malaria prevention in Burkina Faso, yet both are threatened by the expansion and persistence of insecticide resistance in vector populations. If resistance-conferring variants can move freely across the country through the same high gene flow documented here, then resistance management strategies, such as rotating insecticide classes or deploying new generation nets, may need to be coordinated nationally rather than regionally. A patchwork of local approaches could be undermined by mosquitoes or their genes arriving from neighbouring districts where a different insecticide is in use.

The implications for gene drive technology are even more profound. Gene drives are engineered genetic systems that bias inheritance so that a chosen trait, such as sterility or susceptibility to parasites, spreads rapidly through a wild population, even if the trait reduces the carrier’s reproductive fitness. The feasibility and safety of such systems depend critically on population structure. A drive released into a fragmented population might stall at genetic boundaries, limiting its effectiveness but also containing any unintended spread. The absence of geographical structure in An. coluzzii and An. gambiae sensu stricto within Burkina Faso suggests, by contrast, that a gene drive construct released in one part of the country could spread rapidly throughout the entire national population of these vectors. That is precisely the efficiency designers hope for, but it also underscores why containment modelling, staged testing and community engagement are central to the gene drive programmes now under development for malaria vector control in Africa.

The study was made possible by an unusually broad coalition. Sampling was carried out by the Institut de Recherche en Sciences de la Santé with the Ministry of Health of Burkina Faso and community health workers, and the work was funded by the Gates Foundation and Wellcome, which also support the safe and sustainable implementation of gene drive technology for malaria vector control in Africa. Genomic sequencing and analysis drew on the MalariaGEN Vector Observatory, an international collaboration building capacity for malaria vector genomic surveillance, with contributions from the Liverpool School of Tropical Medicine, the Broad Institute and the Wellcome Sanger Institute. For a country at the frontline of both malaria and mosquito innovation, the message of this research is clear: its two deadliest vectors behave, genetically, as a single connected population, and any strategy that hopes to outmanoeuvre them must think at national scale, while the more demographically fragile An. arabiensis may require a separate plan of its own.

Subject of Research: Population genomics of Anopheles gambiae complex malaria vectors in Burkina Faso and implications for gene drive implementation

Article Title: No geographical population structure of malaria vectors Anopheles gambiae and Anopheles coluzzii but weak structure in Anopheles arabiensis within Burkina Faso: implications for vector control and gene drive implementation

Article References: Kaboré, H., Brenas, J., Kientega, M., Traoré, N., Pescod, P., Sawadogo, G., Koutoucheva, A. H., Lanfrancotti, A., Namountougou, M., Maiga, H., Nolan, T., Miles, A., Clarkson, C. S., & Diabaté, A. (2026). No geographical population structure of malaria vectors Anopheles gambiae and Anopheles coluzzii but weak structure in Anopheles arabiensis within Burkina Faso: implications for vector control and gene drive implementation. BMC Genomics. https://doi.org/10.1186/s12864-026-13321-6

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13321-6

Keywords: Anopheles gambiae, Anopheles coluzzii, Anopheles arabiensis, malaria vectors, population structure, gene flow, gene drive, vector control, whole-genome sequencing, Burkina Faso, genetic diversity, insecticide resistance

An international team of researchers, led by scientists at the University of Buea in Cameroon and including collaborators from the Liverpool School of Tropical Medicine, the MRC Unit The Gambia at the London School of Hygiene and Tropical Medicine, and the Ellison Institute of Technology in Oxford, analysed whole genome sequence data from 276 mosquitoes belonging to the Anopheles gambiae complex. These insects were collected between 2020 and 2021 in six communities distributed along the altitudinal gradient of Mount Cameroon, a volcanic mountain whose slopes create a patchwork of ecological conditions that can shape the biology of the insects living there.

The Anopheles gambiae complex is a group of morphologically indistinguishable mosquito species, several of which are among the most efficient malaria vectors in the world. Because the members of the complex look identical, researchers rely on genetic tools to tell them apart. In this study, the team used ancestral informative markers, which are genetic variants known to distinguish particular species, to assign each of the 276 mosquitoes to a taxon. The results showed that 93 of the mosquitoes were Anopheles coluzzii, 178 were Anopheles gambiae sensu stricto, and four were Anopheles melas, a saltwater-tolerant member of the complex, while a single mosquito could not be assigned to any of these groups.

To investigate population structure, the researchers randomly selected a set of 100,000 neutral biallelic single nucleotide polymorphisms, or SNPs, meaning variants scattered across the genome that are not under obvious selective pressure and therefore mainly reflect ancestry and gene flow. Using principal component analysis and the fixation index, a standard measure of genetic differentiation between populations, along with admixture, identity by descent and population dynamics analyses, the team reconstructed the evolutionary relationships among the mosquito populations on the mountain and compared them with reference populations from Burkina Faso.

The most striking result emerged from the Anopheles coluzzii samples. Rather than forming a single genetically uniform population, the mosquitoes from Missellele, a locality at the foot of the mountain, split cleanly into two distinct subpopulations, which the authors designated Anopheles coluzzii A and Anopheles coluzzii B. The first of these groups contained 83 of the 93 Anopheles coluzzii individuals, while the second comprised just 10. What makes this finding remarkable is that the two subpopulations were collected from the same locality, meaning they are likely to be sympatric, sharing the same breeding grounds and habitats, yet their genomes tell stories of separate ancestry and limited interbreeding.

The smaller group, Anopheles coluzzii B, was found to be ancestrally closer to Anopheles coluzzii populations from Burkina Faso than to its geographical neighbours in the larger subpopulation. This pattern suggests a connection to more distant West African populations that has somehow been maintained despite the considerable distance separating the Sahelian country from the Cameroonian coast, or alternatively points to a complex demographic history in which lineages with different origins came to coexist in the same place. Meanwhile, the dominant subpopulation, Anopheles coluzzii A, proved to be the most genetically differentiated of all the Anopheles coluzzii populations examined in the study, standing apart not only from Anopheles coluzzii B but also from the Burkina Faso reference populations.

Digging deeper into the location of the genetic differences, the researchers found that the strong differentiation of Anopheles coluzzii A was driven principally by variants located on the X chromosome and chromosome arm 2L. The X chromosome is of particular interest in studies of speciation and reproductive isolation because genes located on it often play an outsized role in hybrid incompatibilities, a pattern observed across many organisms. The concentration of highly differentiated variants on the X and 2L therefore hints at possible local reproductive isolation, meaning the mosquitoes may be beginning to diverge into reproductively separated groups, potentially accompanied by ecological adaptation to local conditions on the mountain slopes. Windowed principal component analysis further revealed signals of chromosomal inversions on chromosome arms 2L and 2R, structural rearrangements of the genome that are known to suppress recombination and can help maintain locally adapted gene combinations in the face of gene flow.

The study also detected evidence of recent population expansion in all species and populations examined, indicating that the mosquito populations on Mount Cameroon have grown substantially in the recent past. Expanding populations can spread rapidly and can dilute the effects of vector control measures if survivors of interventions repopulate breeding sites quickly. Combined with the genetic fragmentation observed among the Anopheles coluzzii, this demographic signal paints a picture of vector populations that are both dynamic and structured, a combination that complicates the assumption, common in control programmes, that mosquitoes in a given area behave and evolve as a single homogeneous population.

The practical implications are considerable. Vector control interventions such as insecticide-treated bed nets and indoor residual spraying exert strong selection on mosquitoes, and the effectiveness of these tools depends on how resistance genes move through populations. If Anopheles coluzzii populations on the slopes of Mount Cameroon are genetically isolated from one another, then insecticide resistance, behavioural changes and other adaptations that arise in one subpopulation may not spread readily to the others. Each genetically distinct population may require its own surveillance and tailored control strategy. The authors argue that the genetic divergence and recent expansion they documented call for further genomic surveillance to support locally tailored vector control and malaria elimination efforts, effectively making the case that a one-size-fits-all approach will be insufficient in this landscape.

Mount Cameroon itself provides a compelling natural laboratory for this kind of work. Rising steeply from the Atlantic coast to more than 4,000 metres, the mountain compresses a wide range of climates and habitats into a small geographic area, from humid lowland plantations and coastal flats to montane forest and alpine scrub. Communities at different altitudes experience different intensities and seasonality of malaria transmission, and the mosquitoes that transmit the parasite face different ecological pressures along the gradient. The study, which received funding from the Pan African Malaria Genetic Epidemiology Network under the Human Heredity and Health in Africa programme and from DELTAS Africa, demonstrates how high-resolution genomic data can expose hidden population structure even within a seemingly continuous landscape, information that was simply inaccessible in the era before whole genome sequencing became routine.

More broadly, the findings contribute to a growing appreciation of the fine-scale genetic heterogeneity of Africa’s major malaria vectors. Anopheles coluzzii and Anopheles gambiae sensu stricto diverged from a common ancestor relatively recently and are still in the process of reproductive separation, making them a textbook example of ongoing speciation. Documenting an additional layer of divergence within Anopheles coluzzii itself, in a population at the edge of the species’ range and on the slopes of an isolated volcano, adds an important data point to this evolutionary picture. It also underscores the value of sustained, locally grounded genomic monitoring: as malaria elimination campaigns intensify across Africa, understanding the genetic architecture of the vectors in each transmission setting will be essential for anticipating how the mosquitoes respond to interventions and for designing strategies that stay ahead of their capacity to adapt. For the communities on the slopes of Mount Cameroon, the invisible genetic walls now revealed among their mosquito populations may ultimately help determine whether and how malaria can finally be pushed out of the region.

Subject of Research: Genomic analysis of genetically isolated Anopheles coluzzii malaria vector populations on Mount Cameroon

Article Title: Genome-wide sequence analysis of malaria vectors reveals genetically isolated Anopheles coluzzii populations along the slopes of Mount Cameroon

Article References: Kwi, P. N., Dze, J. E., Brenas, J., Sadio, A., Tangi, L. N., Chi, H. F., Assogba, B. S., Milugo, T. K., Miles, A., Clarkson, C., Amambua-Ngwa, A., & Apinjoh, T. O. (2026). Genome-wide sequence analysis of malaria vectors reveals genetically isolated Anopheles coluzzii populations along the slopes of Mount Cameroon. BMC Genomics. https://doi.org/10.1186/s12864-026-13341-2

Image Credits: AI Generated

DOI: 10.1186/s12864-026-13341-2

Keywords: Anopheles coluzzii, Anopheles gambiae complex, whole genome sequencing, population structure, malaria vectors, Mount Cameroon, SNPs, reproductive isolation, chromosomal inversions, genomic surveillance, vector control, Cameroon