The mosquito Aedes aegypti is thought to have originated as an ecological opportunist in forested areas of sub-Saharan Africa, and extant African populations of the subspecies Ae. aegypti formosus is relative generalists (Figure 1A). They breed in a wide variety of habitats and opportunistically bite a wide variety of human and non-human animals (McBride et al., 2014; Rose et al., 2020; Xia et al., 2021; Diouf et al., 2021). However, at some point in the past, a few populations in West Africa evolved to specialize in living with and biting humans, giving rise to a human-adapted subspecies Ae. aegypti aegypti that has since spread around the global tropics (Figure 1A) and become the world’s most effective vector of the viruses responsible for yellow fever, dengue, Zika, and chikungunya (McBride et al., 2014; Brady and Hay, 2020; Powell et al., 2018; but see Chadee et al., 1998 ).

Figure 1

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Understanding the ecological factors that drive mosquitoes like Ae. aegypti to adapt to human hosts and habitats is important because it can help us predict and respond to future burdens of mosquito-borne disease on a planet whose climate and landscape are being transformed by human activity. Recent work suggests that human specialization in Ae. aegypti originally evolved as an adaptation to the extremely long, hot dry seasons of the Sahel region of West Africa (Figure 1B). Aedes mosquitoes lay their eggs just above the water line in small, contained bodies of water, and immature stages require water for development. The scarcity of natural tree-hole and rock-pool aquatic habitat for up to 9 months of the year in the Sahel likely forced Ae. aegypti to rely on human-stored water for survival, with adaptations to breeding in artificial containers (Powell et al., 2018; Gillett, 1955; Petersen, 1977; Leahy et al., 1978; Metz et al., 2023) and biting humans (McBride et al., 2014; Rose et al., 2020; Gouck, 1972) soon following. For example, adaptation to artificial containers involved changes in egg hatching behavior and larval starvation resistance (Saul et al., 1980) that allow immature stages to thrive in water that is relatively low in nutrients (e.g. bacteria and detritus) and high in oxygen. However, neither highly seasonal precipitation patterns nor human-derived pots of water were present in the Sahel until relatively recently in evolutionary time. Settled human societies practicing water storage in clay vessels likely developed within the last 10,000 years in sub-Saharan Africa (Huysecom et al., 2004; Ehret, 2002). Meanwhile, the Sahara Desert and associated Sahelian biome have only existed in their present form for the past 5000 years; the region was a vast savannah during the African Humid Period from 15,000–5000 years ago. If Ae. aegypti evolved to specialize in biting humans as a by-product of breeding among humans during the intense dry seasons of the West African Sahel (hereafter ‘Sahel’), then the shift should have occurred no more than 5000 years ago.

The idea that Ae. aegypti aegypti first emerged when all elements of its current niche were finally present approximately 5000 years ago and has been suggested multiple times in the vector biology literature (e.g. Powell et al., 2018; Petersen, 1977; Peter, 2016), but has never been comprehensively tested with modern genomic data. A site-frequency-spectrum- (SFS-) based analysis of exome sequence data estimated that neighboring generalist and human-specialist populations in West Africa diverged about 15,000 years ago (Crawford et al., 2017), but this estimate was sensitive to model specification and parameterization. Conversely, a molecular clock-based phylogenetic analysis found that all African populations of Ae. aegypti have a common ancestor approximately 17,000–25,000 years ago, but did not precisely date the subsequent split between human-specialist and generalist subspecies (Soghigian et al., 2020).

In contrast to the uncertainty surrounding exactly when (and why) specialization occurred (Figure 1C), the historical forces that led to the spread of Ae. aegypti aegypti out of Africa are better understood. Human-specialist Ae. aegypti is thought to have first migrated to the Americas on ships during the Atlantic Slave Trade approximately 500 years ago (Figure 1C). Its arrival there coincided with the first recorded outbreaks of yellow fever in the New World in the 1600s (Powell et al., 2018). Subsequent outbreaks of yellow fever exacted an enormous toll in the following centuries, especially among immunologically naive European and Indigenous populations, shaping not just health outcomes, but also the political and economic history of the Americas (McNeill, 2010). Similarly, Ae. aegypti’s invasion of Asia and Oceania was followed by outbreaks of dengue, chikungunya, and later Zika, although yellow fever remains absent in these areas (Brady and Hay, 2020; Powell et al., 2018). Today, invasive populations of Ae. aegypti in the Americas and Asia are almost all closely related to each other and distinct from their ancestors in Africa (Powell et al., 2018; Gloria-Soria et al., 2016).

A third and putatively much more recent event in the evolutionary history of human-specialist Ae. aegypti involves a shift towards human biting in growing African cities that would otherwise be expected to harbor generalist populations. Regardless of local climate, urban Ae. aegypti mosquitoes in places like Kumasi, Ghana and Ouagadougou, Burkina Faso are consistently more responsive to humans than those from nearby rural areas (Figure 1B, compare KUM to KIN and OGD to OHI) (Rose et al., 2020). This shift is associated with the same underlying ancestry component that defines human specialists in the Sahel and outside Africa, suggesting that it results from an influx of human-specialist alleles into urban areas rather than independent evolution of human biting (Figure 1C; Rose et al., 2020). Although the exact timing of the observed influx in places like Kumasi and Ouagadougou remains to be tested, it likely occurred recently; the cities involved have only reached the high levels of human population density associated with greater mosquito preference for humans within the past few decades (United Nations, 2019). Urban populations that lack substantial admixture from this human-specialist ancestry component have also been described and posited to represent a genetically independent adaptation to human environments (Brown et al., 2011). However, when their behavior has been tested, these populations do not show an increased preference for human hosts (Rose et al., 2020). This does not preclude other forms of adaptation to human habitats.

Here, we take advantage of existing population genomic data from diverse African and non-African populations (Rose et al., 2020) to infer the timing of two key events in the evolutionary history of the human-specialist form of Ae. aegypti (Figure 1C) and thereby more rigorously test key hypotheses concerning their underlying ecological drivers. First, we address the timing of the initial emergence of specialist populations in the Sahel via cross-coalescent analysis—a methodological framework developed for studying human evolution that has rarely been applied in other species. Importantly, we take advantage of the known migration of specialist Ae. aegypti out of Africa 150–500 years ago to calibrate the coalescent clock and thus obtain a much more precise estimate than would otherwise be possible. Second, we use ancestry tract length analysis to infer the timing of the recent shift towards human biting in large West African cities. We find that human specialists originated with the emergence of the modern Sahelian climate approximately 5000 years ago, while the influx of human-specialist ancestry into urban areas coincides with rapid urbanization over the past 20–40 years.

Taken together, our results suggest that the ecology of Ae. aegypti has been in flux across human history (Figure 4). We previously found that Ae. aegypti populations in their native range in sub-Saharan Africa were most specialized on human hosts in the West African Sahel, where they depend on human water storage for breeding across the long dry season (Rose et al., 2020). However, urban populations were also more attracted to human hosts than nearby rural populations regardless of climate (Rose et al., 2020). Here, we used cross-coalescent and ancestry tract analyses of genomic data to determine when these ecological shifts occurred and thus gain additional insight into their underlying drivers. According to our cross-coalescent estimates, human-specialist and generalist populations of Ae. aegypti diverged rapidly at the end of the African Humid Period, about 5000 years ago. In contrast, our ancestry tract analyses suggest that the urbanization effects are much more recent, playing out over the last 20–40 years.

Figure 4

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The finding that human specialists emerged at the end of the African Humid Period is consistent with the hypothesis that climate provided the initial selective push toward specialization. It was at this time, approximately 5000 years ago, that the Sahara dried and the highly seasonal Sahel biome to its south came to be. Ae. aegypti mosquitoes inhabiting the area would have found themselves in a novel situation, devoid of rain-filled breeding sites for nine months of the year. This could have driven adaptation to human-derived breeding sites, such as the clay pots used for water storage by early pearl millet farmers (Huysecom et al., 2004; Burgarella et al., 2018). Interestingly, pearl millet domestication is also estimated to have occurred ~5000 years ago in the western Sahel (Burgarella et al., 2018), bringing multiple aspects of this mosquito’s human-specialist niche together simultaneously in the region. In addition to the signal of rapid divergence 5000 years ago, we saw some evidence for steady population growth and accumulation of modest genetic structure starting 15,000–30,000 years ago. This observation is compatible with a model where some populations expanded into newly habitable parts of the present-day Sahara/Sahel at the start of the African Humid Period, giving rise to weak geographical structure, before rapidly diverging in response to a drying climate and the emergence of the human-specialist niche at its end. Although they seem to have occasionally interbred, specialist and generalist populations then became largely isolated and ecologically distinct.

It is widely accepted that human-specialist Ae. aegypti spread to the Americas (and eventually throughout the global tropics) during the Atlantic Slave Trade, ushering in a new era of vector-borne disease (Powell et al., 2018). We relied on this historical understanding to calibrate our coalescent scaling factor. However, our results also help establish its credibility. The cross-coalescent signal between Ngoye, Senegal, and Santarem, Brazil closely fit a priori expectations, even without calibration. Using literature values for average insect mutation rates and our best estimate of Ae. aegypti generation time would have also yielded good correspondence between the inferred timing of migration and the historical record of the Atlantic Slave Trade (Figure 2A). The duration and sudden drop-off in migration observed in the coalescent signal also closely match expectations from the historical record (Figure 2A).

Luanda, Angola was a major port during the Atlantic Slave Trade and likely served as the proximate source of many Ae. aegypti mosquitoes introduced to the Americas. Ae. aegypti populations there show substantial human-specialist ancestry, similar to those from Senegal (Powell et al., 2018; Kotsakiozi et al., 2018). This raises the question of whether human-specialist populations of Ae. aegypti could have arisen in or around Angola rather than in the western Sahel. However, the closest generalist relatives of human-specialist populations are found in West Africa (Kotsakiozi et al., 2018). Present distributions of populations may not perfectly match their historical distributions, but the most parsimonious explanation is that human specialists (the ‘proto-Ae. aegypti’ described in Powell et al., 2018) first arose in the western Sahel and later spread to both Luanda and the Americas during the slave trade.

While our cross-coalescent analyses are remarkably consistent with prior expectations, several caveats and open questions remain. First, the temporal resolution of our inferences is relatively low, and both previously published simulations (Wang et al., 2020) and our own bootstrap replicates (Figure 2B–D, gray lines) suggest relatively wide bounds for the precise timing of events. Second, it is difficult for us to validate the long-range statistical phasing upon which the analyses are based. Overall linkage disequilibrium is relatively low in Ae. aegypti, dropping off quickly over a few kilobases and reaching half its maximum value within about 50 kb Matthews et al., 2018; this is likely sufficient for assembling shorter, high-confidence prephase blocks into longer haplotypes in many cases. However, phase-switch errors may be common across longer distances – potentially affecting inferences in the most recent time windows. Nevertheless, the similar results we obtain using different proxy populations (and thus different input haplotype structures) for human-specialist and generalist lineages (see Figure 2—figure supplement 1) suggests that our results are robust to potential mistakes in long-range haplotype phasing.

Another important source of uncertainty comes from our assumption that the coalescent scaling factor should maximize the overlap between the peak of estimated Ae. aegypti migration and the peak of the Atlantic Slave Trade (Figure 2B). If we instead consider alternative scenarios where peak migration occurred at the beginning of the slave trade era, around 1500, then our inferred mutation rate would be lower (about 2.4e-9, assuming 15 generations per year), pushing back the split of human-specialist lineages to ~10,000 years before present. This scenario seems less plausible, in part because our isolation-with-migration analyses suggest a gradual onset of migration between continents rather than a single, early-pulse model. It would also make it harder to explain the timing of the bottleneck observed in invasive populations; the first signs of this bottleneck occur at the beginning of the slave trade (~500 years ago) with our current calibration (Figure 2—figure supplement 1A), but would be pushed to a pre-trade date in this alternative scenario. We can also consider a scenario in which peak Ae. aegypti migration occurred more recently, perhaps around 1850, corresponding to increased global shipping traffic outside the slave trade alone. In this case, our inferred mutation rate would be higher (or generation time lower), and the split of human-specialist lineages would be placed at about 3000 years ago. Overall, the best match between the existing literature and our data corresponds to our main estimates, but alternative scenarios could gain support if future research finds evidence for a different time course of invasion than is suggested by the epidemiological record.

This study represents one of the first applications of cross-coalescent analysis to a non-model system. Cross-coalescent analyses are a powerful tool for understanding historical relationships between populations, but they are difficult to implement in practice, largely due to the logistical/computational burden of developing a large genome phasing panel and the difficulty of estimating an accurate coalescent scaling factor. Accurate calibration of coalescent analysis is notoriously difficult even in well-understood systems like humans (Scally and Durbin, 2012). Here, we take advantage of a continent-wide set of genomes, combined with read-based prephasing and population-wide statistical phasing, to develop a phasing panel that will enable future studies in Ae. aegypti with a lower barrier to entry. The same approach may work for other study organisms with similar population genomic properties; high levels of diversity are helpful for prephasing and at least moderate levels of linkage disequilibrium are important for the assembly of prephase blocks. Likewise, our use of the historical record to calibrate a coalescent scaling factor may be effective in other taxa whose history is characterized by known historical events as well as events with unknown timing. Similar calibrations have been used to understand the relationship between coalescent analyses and human history (O’Fallon and Fehren-Schmitz, 2011; Schiffels and Durbin, 2014), but the approach should be especially valuable in non-model organisms where mutation rates and generation times are less well characterized.

Human specialization first emerged within Ae. aegypti thousands of years ago, but now, in the face of the rapid urbanization in sub-Saharan Africa, generalist populations of this species seem to be undergoing a new shift. We estimate an influx of human-specialist alleles into the rapidly growing cities of Kumasi and Ouagadougou within the past 20–40 years. Positive selection during adaptive introgression can increase tract lengths and make admixture appear more recent than it actually is. For this reason, we masked regions of the genome thought to underlie adaptation to human habitats before running our analysis. If selection has acted outside these regions, however, admixture may be somewhat older than we estimate. The exact geographic origin of the human-specialist ancestry tracts found in both cities also remains uncertain. They are likely derived from nearby specialist populations, with whom both KUM and OGD showed affinity in previous ADMIXTURE analyses (Rose et al., 2020). They could alternatively (or additionally) be derived from distant specialist populations or even invasive populations outside Africa; dormant Ae. aegypti eggs are often transported inadvertently, e.g., in the used-tire trade. More comprehensive sampling and analysis of human-specialist populations inside and outside Africa will be necessary to identify the precise origins of the genetic material currently transforming urban populations in Africa.

Regardless of the source, the influx of human-specialist ancestry into Ae. aegypti mosquitoes inhabiting African cities will likely have important implications for human health. Human-specialist Ae. aegypti are both more likely to bite humans and more likely to serve as competent vectors of dengue, Zika, and yellow fever (Rose et al., 2020; Sylla et al., 2009; Aubry et al., 2020; Miller et al., 1989). Ouagadougou has seen repeated outbreaks of dengue fever in recent years (Im et al., 2020; Badolo et al., 2022), and mosquitoes there are still genetically and phenotypically intermediate between generalists and specialists (Rose et al., 2020; Kotsakiozi et al., 2018; Badolo et al., 2022). It is possible that such populations will eventually become more specialized as urbanization continues. The emergence of urban yellow fever in Africa since 2016 may have also been hastened by the expansion of human-specialist populations of Ae. aegypti (Kraemer et al., 2017; Klitting et al., 2018). For these reasons, monitoring and control of Ae. aegypti, taking into account possible changes in the vector capacity of local populations over time, should remain a high priority in the native range of this key vector species.

Scripts and processed data are available at https://github.com/noahrose/aaeg-evol-hist (copy archived at swh:1:rev:3d3b779b241244f8f17d873f316e7baedb930e18). Raw genomic data are available in the NCBI SRA at accession PRJNA602495. Phasing reference panel is available at https://doi.org/10.5061/dryad.2bvq83btk.

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Author details

1. Noah H Rose

   1. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, United States
   2. Princeton Neuroscience Institute, Princeton University, Princeton, United States

   Contribution

   Conceptualization, Data curation, Formal analysis, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

   For correspondence

   noahr@princeton.edu

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0001-7129-4753

2. Athanase Badolo

   Laboratory of Fundamental and Applied Entomology, Université Joseph Ki-Zerbo, Ouagadougou, Burkina Faso

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-6652-4240

3. Massamba Sylla

   Department of Livestock Sciences and Techniques, Sine Saloum University El Hadji Ibrahima NIASS, Kaffrine, Senegal

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

4. Jewelna Akorli

   Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-3972-0860

5. Sampson Otoo

   Department of Parasitology, Noguchi Memorial Institute for Medical Research, University of Ghana, Accra, Ghana

   Contribution

   Conceptualization, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

6. Andrea Gloria-Soria

   Department of Entomology. Center for Vector Biology & Zoonotic Diseases. The Connecticut Agricultural Experiment Station, New Haven, United States

   Contribution

   Conceptualization, Data curation, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

   "This ORCID iD identifies the author of this article:" 0000-0002-5401-3988

7. Jeffrey R Powell

   Yale University, New Haven, United States

   Contribution

   Conceptualization, Data curation, Investigation, Writing – review and editing

   Competing interests

   No competing interests declared

8. Bradley J White

   Verily Life Sciences, South San Francisco, United States

   Contribution

   Conceptualization, Data curation, Investigation, Writing – review and editing

   Competing interests

   is affiliated with Verily Life Sciences. The author has no financial interests to declare

9. Jacob E Crawford

   Verily Life Sciences, South San Francisco, United States

   Contribution

   Conceptualization, Data curation, Investigation, Writing – review and editing

   Competing interests

   is affiliated with Verily Life Sciences. The author has no financial interests to declare

10. Carolyn S McBride

    1. Department of Ecology and Evolutionary Biology, Princeton University, Princeton, United States
    2. Princeton Neuroscience Institute, Princeton University, Princeton, United States

    Contribution

    Conceptualization, Supervision, Investigation, Visualization, Methodology, Writing – original draft, Writing – review and editing

    For correspondence

    csm7@princeton.edu

    Competing interests

    No competing interests declared

    "This ORCID iD identifies the author of this article:" 0000-0002-8898-1768

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