A sweeping population‑genomics effort has generated the first large collection of complete genomes for Anopheles darlingi, the dominant malaria vector across South America. The dataset—more than 1,000 high‑coverage genomes from six countries—offers the clearest picture to date of how this mosquito species is structured, how it adapts, and which genetic pathways may be shifting under insecticide pressure.
Malaria transmission in South America remains persistent, with hundreds of thousands of cases reported annually, largely in Brazil, Colombia, and Venezuela. An. darlingi is responsible for most of that burden, yet its evolutionary dynamics have been comparatively understudied. Previous work relied on limited genetic markers, leaving major questions about population structure, local adaptation, and the origins of insecticide resistance unresolved.
The new study, titled “Population genomics of Anopheles darlingi, the principal South American malaria vector mosquito,” led by researchers at the Harvard T.H. Chan School of Public Health and published in Science, fills that gap by sequencing whole genomes from mosquitoes collected across forests, wetlands, agricultural zones, mining regions, and urban areas. “Our study plays a major role in revealing the evolutionary dynamics of a primary malaria vector,” said corresponding author Jacob Tennessen, PhD, in a press release. “These insights into Anopheles darlingi biology could help improve methods for blocking disease transmission.”
One of the most striking findings is the presence of strong selection signals in metabolic genes, particularly members of the cytochrome P450 family. The patterns observed suggest that An. darlingi populations may be adapting to insecticide exposure. “Insecticide resistance has only been sporadically documented in Anopheles darlingi, which have not been subject to intensive insecticide-heavy campaigns like those elsewhere in the world,” Tennessen said. “Resistance may be driven by agricultural insecticides rather than those used for vector control specifically.”
Beyond resistance‑associated genes, the researchers uncovered deep geographic population structure and high overall genetic diversity. Mosquitoes from regions such as Guyana and Venezuela showed substantial interpopulation divergence. “We observe deep geographic population structure, high genetic diversity including 13 putative segregating inversions, and no evidence for sympatric cryptic taxa despite high interpopulation divergence,” the authors wrote.
These findings have practical implications for malaria control. Understanding how An. darlingi populations are partitioned across the continent—and how they respond to environmental pressures—can inform surveillance strategies, insecticide deployment, and future genetic‑control approaches. “Vector‑targeted disease control efforts require a thorough understanding of mosquito demographic and evolutionary patterns,” the authors wrote. The genomic framework established here provides a foundation for that work, while also highlighting the challenges posed by a vector with substantial adaptive capacity.
Although the study expands the knowledge base for malaria‑vector biology in the Americas, the authors emphasize that it represents fundamental research rather than an immediate guide for policy changes. Still, the scale and resolution of the dataset set the stage for future investigations into Anopheles species across the region.
