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Fine-scale landscape genomics reveals asymmetric gene flow in invasive tiger mosquito populations

A bioRxiv preprint applies landscape genomics to Aedes albopictus, the tiger mosquito, finding that urban structure creates directional asymmetries in gene flow with implications for understanding the spread of dengue, Zika, and chikungunya vectors.

Published · AI-drafted summary based on 1 public source
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Aedes albopictus, the Asian tiger mosquito, is an invasive species now established across much of North America, Europe, and beyond, and acts as a vector for dengue, Zika, and chikungunya viruses. While the global dispersal history of the species is well characterised, how fine-scale urban landscape features influence local gene flow and population connectivity has remained unclear.

A preprint posted to bioRxiv reports findings from a landscape genomics study that used genome-wide data to examine dispersal patterns of Ae. albopictus populations at fine spatial scales. The researchers found that gene flow between populations is asymmetric — that is, movement and genetic exchange is directional rather than uniform — and that heterogeneous urban land-use features appear to shape these patterns. Populations in artificial container-rich urban and suburban environments can reach high densities, and understanding local dispersal dynamics has potential relevance for vector control programme design.

The preprint has not yet been peer-reviewed. The study contributes to a body of work on how genomic methods can inform understanding of invasive species spread, and may be of interest to researchers working at the intersection of population genetics, vector biology, and public health entomology.

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  1. Primary sourcePreprint bioRxiv (Cold Spring Harbor Laboratory) · 2026-06-02
    Fine-scale landscape genomics show asymmetric patterns of gene flow for the invasive mosquito Aedes albopictus

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aedes-albopictus landscape-genomics gene-flow invasive-species vector-biology population-genetics mosquito
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Genetic Current is the news section of Evagene, an academic, research, and educational pedigree-modelling platform. Stories are AI-drafted summaries of items from trusted public sources, written for researchers, clinicians, educators, students, genealogists, and patients with an interest in genetics. Summaries are for educational and research purposes only and are not medical advice.

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