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Background Whole genome re-sequencing provides powerful data for population genomic studies, allowing robust inferences of population structure, gene flow and evolutionary history. For the major malaria vector in Africa, Anopheles gambiae, other genetic aspects such as selection and adaptation are also important. In the present study, we explore population genetic variation from genome-wide sequencing of 765 An. gambiae and An. coluzzii specimens collected from across Africa. We used t-SNE, a recently popularized dimensionality reduction method, to create a 2D-map of An. gambiae and An. coluzzii genes that reflect their population structure similarities. Results The map allows intuitive navigation among genes distributed throughout the so-called “mainland” and numerous surrounding “island-like” gene clusters. These gene clusters of various sizes correspond predominantly to low recombination genomic regions such as inversions and centromeres, and also to recent selective sweeps. Because this mosquito species complex has been studied extensively, we were able to support our interpretations with previously published findings. Several novel observations and hypotheses are also made, including selective sweeps and a multi-locus selection event in Guinea-Bissau, a known intense hybridization zone between An. gambiae and An. coluzzii. Conclusions Our results present a rich dataset that could be utilized in functional investigations aiming to shed light onto An. gambiae s.l genome evolution and eventual speciation. In addition, the methodology presented here can be used to further characterize other species not so well studied as An. gambiae, shortening the time required to progress from field sampling to the identification of genes and genomic regions under unique evolutionary processes.

Using high-depth whole genome sequencing of F0 mating pairs and multiple individual F1 offspring, we estimated the nuclear mutation rate per generation in the malaria vectors Anopheles coluzzii and Anopheles stephensi by detecting de novo genetic mutations. A purpose-built computer program was employed to filter actual mutations from a deep background of superficially similar artifacts resulting from read misalignment. Performance of filtering parameters was determined using software-simulated mutations, and the resulting estimate of false negative rate was used to correct final mutation rate estimates. Spontaneous mutation rates by base substitution were estimated at 1.00 × 10−9 (95% confidence interval, 2.06 × 10−10—2.91 × 10−9) and 1.36 × 10−9 (95% confidence interval, 4.42 × 10−10—3.18 × 10−9) per site per generation in A. coluzzii and A. stephensi respectively. Although similar studies have been performed on other insect species including dipterans, this is the first study to empirically measure mutation rates in the important genus Anopheles, and thus provides an estimate of µ that will be of utility for comparative evolutionary genomics, as well as for population genetic analysis of malaria vector mosquito species.

Anopheles pretoriensis is widely distributed across Africa, including on oceanic islands such as Grande Comore in the Comoros. This species is known to be mostly zoophylic and therefore considered to have low impact on the transmission of human malaria. However, A. pretoriensis has been found infected with Plasmodium, suggesting that it may be epidemiologically important. In the present study, we sequenced and assembled the complete mitogenome of A. pretoriensis and inferred its phylogenetic relationship among other species in the subgenus Cellia. We also investigated the genetic structure of A. pretoriensis populations on Grande Comore Island, and between this island population and sites in continental Africa, using partial sequence of the mitochondrial cytochrome c oxidase subunit I (COI) gene. Seven haplotypes were found on the island, one of which was ubiquitous. There was no clear divergence between island haplotypes and those found on the continent. The present work contributes knowledge on this understudied, yet abundant, Anopheles species.

Novel malaria control strategies using genetically engineered mosquitoes (GEMs) are on the horizon. Population modification is one approach wherein mosquitoes are engineered with genes rendering them refractory to the malaria parasite, Plasmodium falciparum, coupled with a low‐threshold, Cas9‐based gene drive. When released into a wild vector population, GEMs preferentially transmit these parasite‐blocking genes to their offspring, ultimately modifying a vector population into a nonvector one. Deploying this technology awaits ecologically contained field trial evaluations. Here, we consider a process for site selection, the first critical step in designing a trial. Our goal is to identify a site that maximizes prospects for success, minimizes risk, and serves as a fair, valid, and convincing test of efficacy and impacts of a GEM product intended for large‐scale deployment in Africa. We base site selection on geographic, geological, and biological, rather than social or legal, criteria. We recognize the latter as critically important but not as a first step in selecting a site. We propose physical islands as being the best candidates for a GEM field trial and present an evaluation of 22 African islands. We consider geographic and genetic isolation, biological complexity, island size, and topography and identify two island groups that satisfy key criteria for ideal GEM field trial sites.

Anopheles coluzzii is a major malaria vector throughout its distribution in west-central Africa. Here we present a whole-genome study of 142 specimens from nine countries in continental Africa and three islands in the Gulf of Guinea. This sample set covers a large part of this species’ geographic range. Our population genomic analyses included a description of the structure of mainland populations, island populations, and connectivity between them. Three genetic clusters are identified among mainland populations and genetic distances (FST) fits an isolation-by-distance model. Genomic analyses are applied to estimate the demographic history and ancestry for each island. Taken together with the unique biogeography and history of human occupation for each island, they present a coherent explanation underlying levels of genetic isolation between mainland and island populations. We discuss the relationship of our findings to the suitability of São Tomé and Príncipe islands as candidate sites for potential field trials of genetic-based malaria control strategies., Campos, Lanzaro and colleagues use whole-genome sequencing and population genomic analyses to infer connectivity between mainland and island mosquito populations in West Africa. The unique biogeographic history for each island population is reported, and the findings highlight potential candidate sites for genetic-based malaria control strategies.

We report the first complete mitogenome (Mt) sequence of Anopheles coustani, an understudied malaria vector in Africa. The sequence was extracted from one individual mosquito from São Tomé island. The length of the A. coustani Mt genome was 15,408 bp with 79.3% AT content. Phylogenetic analysis revealed that A. coustani is most closely related to A. sinensis (93.5% of identity); and 90.1% identical to A. gambiae complex members. publishersversion published

Made available in DSpace on 2019-10-06T17:09:58Z (GMT). No. of bitstreams: 0 Previous issue date: 2019-05-17 Background: In the Amazon Basin, Nyssorhynchus (Anopheles) darlingi is the most aggressive and effective malaria vector. In endemic areas, behavioral aspects of anopheline vectors such as host preference, biting time and resting location post blood meal have a key impact on malaria transmission dynamics and vector control interventions. Nyssorhynchus darlingi presents a range of feeding and resting behaviors throughout its broad distribution. Methods: To investigate the genetic diversity related to biting behavior, we collected host-seeking Ny. darlingi in two settlement types in Acre, Brazil: Granada (~ 20-year-old, more established, better access by road, few malaria cases) and Remansinho (~ 8-year-old, active logging, poor road access, high numbers malaria cases). Mosquitoes were classified by the location of collection (indoors or outdoors) and time (dusk or dawn). Results: Genome-wide SNPs, used to assess the degree of genetic divergence and population structure, identified non-random distributions of individuals in the PCA for both location and time analyses. Although genetic diversity related to behavior was confirmed by non-model-based analyses and F ST values, model-based STRUCTURE detected considerable admixture of these populations. Conclusions: To our knowledge, this is the first study to detect genetic markers associated with biting behavior in Ny. darlingi. Additional ecological and genomic studies may help to understand the genetic basis of mosquito behavior and address appropriate surveillance and vector control. Biotechnology Institute (IBTEC) Biosciences Institute at Botucatu (IBB) Sao Paulo State University (UNESP) Department of Biomedical Sciences School of Public Health University at Albany (State University of New York) Wadsworth Center New York State Department of Health Division of Infectious Diseases Department of Medicine University of California San Diego Laboratorio de Investigación y Desarrollo Departamento de Ciencias Celulares y Moleculares Instituto de Medicina Tropical Alexander von Humboldt Universidad Peruana Cayetano Heredia Biology Department St. Mary's College of Maryland Biotechnology Institute (IBTEC) Biosciences Institute at Botucatu (IBB) Sao Paulo State University (UNESP)

Made available in DSpace on 2014-09-30T18:18:20Z (GMT). No. of bitstreams: 0 Previous issue date: 2013Bitstream added on 2014-10-01T14:04:14Z : No. of bitstreams: 1 S0074-02762013000900003.pdf: 529161 bytes, checksum: 81385c72bbd25c5d11a271d286f7317a (MD5) The increasing population of Aedes aegypti mosquitoes on Madeira Island (Portugal) resulted in the first autochthonous dengue outbreak, which occurred in October 2012. Our study establishes the first genetic evaluation based on the mitochondrial DNA (mtDNA) genes [cytochrome oxidase subunit I (COI) and NADH dehydrogenase subunit 4 (ND4)] and knockdown resistance ( kdr ) mutations exploring the colonisation history and the genetic diversity of this insular vector population. We included mosquito populations from Brazil and Venezuela in the analysis as putative geographic sources. The Ae. aegyptipopulation from Madeira showed extremely low mtDNA genetic variability, with a single haplotype for COI and ND4. We also detected the presence of two important kdr mutations and the quasi-fixation of one of these mutations (F1534C). These results are consistent with a unique recent founder event that occurred on the island of Ae. aegyptimosquitoes that carry kdr mutations associated with insecticide resistance. Finally, we also report the presence of the F1534C kdr mutation in the Brazil and Venezuela populations. To our knowledge, this is the first time this mutation has been found in South American Ae. aegypti mosquitoes. Given the present risk of Ae. aegypti re-invading continental Europe from Madeira and the recent dengue outbreaks on the island, this information is important to plan surveillance and control measures. Unidade de Ensino e Investigacao-Parasitologia Medica Centro de Malaria e outras Doencas Tropicais Universidade Nova de Lisboa Instituto de Higiene e Medicina Tropical Unidade de Parasitologia e Microbiologia Medicas Instituto de Administracao da Saude e Assuntos Sociais Unidade de Engenharia Sanitaria Departamento de Promocao e Protecao da Saude Universidade Estadual Paulista Instituto de Biociencias Departamento de Parasitologia Universidad Central de Venezuela Instituto de Medicina Tropical Seccion Entomologia Medica Universidade Estadual Paulista Instituto de Biociencias Departamento de Parasitologia