ABSTRACT
Objective
Culiseta longiareolata (Cs. longiareolata), a mosquito species found in Europe, Asia, and North Africa, is an important vector for various diseases like West Nile encephalitis, and malaria. This study aimed to assess the genetic diversity of the Cs. longiareolata mosquito population in Fars province, southern Iran due to the critical role of genetic diversity in shaping the adaptability and survival of mosquito populations and also adaptation of mosquitoes to environmental changes, insecticides, and pathogens.
Methods
In this study, samples of Cs. longiareolata mosquitoes were collected from 12 locations in Fars province, Iran. Larval stages were collected using the dipping method, while adults were captured with aspirators and mosquito nets, then stored at -20 °C for later DNA extraction. The COI gene was amplified via polymerase chain reaction (PCR) for genetic analysis. The sequencing was done by Bioneer Company in South Korea, and the results were analyzed using bioinformatics tools like Chromas, ClustalW2, and MEGA7. The final sequences were registered in GenBank for further analysis.
Results
The phylogenetic analysis using the maximum likelihood method revealed that Cs. longiareolata samples from Iran clustered with populations from various countries. The analysis involved 17 nucleotide sequences with 504 positions, using the Tamura-Nei model. The genetic diversity index was 0.0165, with 6 haplotypes and a haplotype diversity of 0.721. Demographic expansion indices suggested a potential expansion event in the population. A total of 274 mosquitoes were collected, with 18 examined by PCR and 6 sequenced for the study.
Conclusion
This study provides the first comprehensive genetic assessment of Cs. longiareolata populations in southern Iran using the COI gene which contributes valuable baseline data for future molecular and ecological studies. The findings reveal a moderate level of genetic diversity and clear genetic connections with Mediterranean and Middle Eastern populations, highlighting possible regional gene flow. The research highlights the significance of genetic diversity in comprehending mosquito dynamics and enhancing disease control efforts. Ongoing genetic monitoring is essential for managing vector-borne diseases.
INTRODUCTION
Mosquitoes are among the most important insects in the field of medicine and public health, known as vectors of numerous human and animal diseasefs (1-6). To date, more than 3,500 species of mosquitoes have been reported worldwide. Species belonging to the four genera Culiseta, Anopheles, Aedes, and Culex play a key role in the transmission of significant diseases such as malaria, filariasis, encephalitis, and arboviral diseases (7-16). Among these, Culiseta longiareolata (Cs. longiareolata) has attracted special attention as one of the important mosquito species. This species was first reported in Algeria (North Africa) (17) and is now found in diverse natural habitats such as ponds, valleys, streams, and even stagnant water in plastic containers, tires, and fountains (18-20). The geographic distribution of this mosquito includes the southern Palearctic, Mediterranean, European, and Asian regions (18-20).
Cs. longiareolata is easily distinguished from other species of the genus Culiseta by its distinctive white stripes on various parts of its body (21). This species is not only known as a nuisance pest, but also plays an important role in the transmission of various diseases to humans and animals. Cs. longiareolata is one of the mosquito species that directly and indirectly affects human and animal health and acts as an intermediate host for the transmission of several pathogens and is involved in the spread of diseases such as West Nile encephalitis, and malaria (22, 23). Some aspects of the medical importance of this species are mentioned. First, West Nile Encephalitis: This viral disease caused by the West Nile virus is usually transmitted to humans and animals by mosquitoes. Cs. longiareolata is one of the mosquito species that can play a role in the transmission of this virus (24). This disease can cause severe neurological symptoms such as inflammation of the brain (encephalitis) and, in severe cases, death. Second, role in the transmission of parasitic diseases; avian malaria: Cs. longiareolata is known as a potential vector for the Plasmodium parasite in birds. This parasite causes avian malaria, which can have a significant impact on wild and domestic bird populations (24). While this disease does not directly affect humans, it can lead to a decrease in biodiversity and disruption of ecosystems. Third, role in the transmission of Malta fever; although Malta fever is mainly transmitted through the consumption of water or food contaminated with the bacterium Brucella, Cs. longiareolata can also play a role in the transmission of this disease (24). By transmitting the bacteria between different hosts, this mosquito can contribute to the spread of the disease in different areas. Fourth, human harassment; in addition to its role in the transmission of diseases, Cs. longiareolata also act as a nuisance pest for humans. The bite of this mosquito can cause itching, inflammation, and allergic reactions in people. This can lead to a decrease in quality of life and disruption of daily activities, especially in areas with high densities of this mosquito.
Considering the medical importance and wide geographic distribution of this species, studying the genetic diversity of Cs. longiareolata can provide valuable information about the population structure, genetic patterns, and phylogenetic relationships of this species. The cytochrome c oxidase subunit I (COI) gene is a common molecular marker in genetic and phylogenetic studies, widely used for species identification and evolutionary relationship analysis. Due to its relatively constant evolutionary rate and ability to distinguish species, this gene is a suitable tool for studying genetic diversity in different populations.
This study aims to investigate the genetic diversity of Cs. longiareolata in Fars province based on the COI gene due to the critical role and importance of genetic diversity in shaping the adaptability and survival of mosquito populations. This research seeks to analyze the population structure, identify haplotypes, and determine the phylogenetic relationships of this species in the region. The findings of this study can enhance our understanding of the distribution patterns, ecology, and role of this mosquito in disease transmission. Additionally, they provide essential information for control and management programs targeting this species.
METHODS
Study Area
The collection of Culiseta samples was carried out using the stratified sampling method. For this purpose, Fars province was initially divided into four regions: north, south, west, and east, and three sampling locations were selected from each region. In total, 12 locations were selected for sampling from Fars province for this project (Figure 1 and Table 1). This study was conducted with the approval of the Ethics Committee of Shiraz University of Medical Sciences (number: IR.SUMS.SCHEANUT.REC.1403.078, date: 10.11.2024).
Mosquito Collection
Collecting adult samples at dusk to determine abundance, conduct genetic diversity studies, and analyze phylogenetic relationships in each of the study sites where no spraying was done, such as human, animal, and outdoor spaces, was carried out using an mouth aspirator and mosquito net.
DNA Extraction
DNA extraction from adult mosquitoes to determine genetic diversity was performed using the method described by Collins et al. (28). After DNA extraction, to determine the genetic diversity of the Culiseta DNA genome, we used a 721-bp region of the mitochondrial DNA-encoded COI gene amplified in a thermal cycler using forward primers (GGTCAACAAATCATAAAGATATTGG) and reverse primers (TAAACTTCAGGGTGACCAAAAAATCA) (29).
The polymerase chain reaction (PCR) reaction was carried out in a total reaction volume of 20 µL (4 mM of magnesium chloride, 1.5 µM of forward primer, 1.5 of reverse primer, 2 mM buffer, 150 mM of each deoxynucleoside triphosphate, 1 U Taq DNA polymerase, 40 ng of DNA and deionized water to correct volume). The thermal conditions for the PCR reaction consisted of an initial denaturation at 95 °C for 10 min; followed by 30 cycles of amplification (denaturation at 95 °C for 1 min, annealing at 54 °C for 1 min and expansion at 70 °C for 1 min; with a final extension at 70 °C for 10 min (30).
Then, this amplified DNA was loaded onto a 1% agarose gel along with a 100 bp ladder marker. Staining with green viewer solution was performed to visualize the bands formed on the ultraviolet trans-illuminator. The PCR product was purified and sequenced (30).
Phylogenetic Analysis
For sequencing and analysis of the COI gene, we sent 30 microliters of the gene amplification product from those of suitable quality through the Takapouzist Institute to Bioneer Company in South Korea, and sequencing was performed using the primers used in the PCR reactions (29). The results obtained from the sequenced samples were reviewed and edited using the bioinformatics software Chromas (31). To examine the similarity of the obtained sequences with each other, ClustalW2 software was used, and to compare with the sequences registered in GenBank, the NCBI BLAST server available in the GenBank databasewas used. The MEGA7 software was used to examine phylogenetic relationships and draw the phylogenetic tree, and subsequently, the obtained sequences were submittedto GenBank (32).
Statistical Analysis
Genetic diversity indices, including nucleotide diversity (π), the number of segregating sites, haplotype diversity (Hd), and the average number of pairwise nucleotide differences (Ka, Kb), were calculated using DnaSP version 6.12.03. Population expansion was assessed through Fu and Li’s D and F tests, Tajima’s D, Fu’s Fs, Strobeck’s S, and Harpending’s raggedness index (r) to infer potential demographic events. These tests were used to evaluate deviations from neutrality and detect signs of population expansion or selection. All analyses were based on COI gene sequences and performed using default parameters. Phylogenetic relationships were examined using the maximum likelihood (ML) method in MEGA X, applying the Tamura-Nei model with a gamma distribution (+G) to account for evolutionary rate heterogeneity across sites. A total of 504 aligned positions were used in the final dataset, excluding gaps and missing data from the analysis.
RESULTS
The evolutionary history was inferred using the ML method based on the Tamura-Nei model. The tree with the highest log-likelihood value (-943.91) is shown, with branch percentages indicating related taxa clustering. The initial tree was obtained using the Neighbor-Join and BioNJ algorithms on pairwise distances. The analysis included 17 nucleotide sequences, with 504 positions after removing gaps. The substitution model included a discrete gamma distribution for rate variation across sites, with estimated nucleotide frequencies of A=30.33%, T/U=39.29%, C=15.59%, and G=14.79%.
ML values were estimated based on an automatically calculated tree topology. Molecular phylogenetic analysis using the ML method showed that the Cs. longiareolata samples from Iran (codes OR250657 to OR250662) are clustered with other populations of this species from Türkiye, Malta, Portugal, Croatia, Spain, Greece, the Netherlands, Germany, and the United Arab Emirates. The genetic distance between these samples indicates a moderate genetic diversity among the different populations of this species. Based on the provided tables, 274 adult mosquitoes were collected from 6 regions in southern Iran, of which 18 samples were examined by PCR and 6 samples were sequenced. π was 0.0165, and 6 haplotypes with a Hd of 0.721 were observed. Demographic expansion indices (such as Fu and Li’s D and F, Tajima’s D, and R2) indicated that the population of this species may have experienced a demographic expansion event (Tables 2 and 3, Figure 1).
All genetic variability indices were computed using DnaSP v6.12 for a 504bp mitochondrial COI fragment from 17 Cs. longiareolata specimens.
π : Average number of pairwise nucleotide differences per site (unit: substitutions/site).
Ka and Kb: Average number of pairwise nucleotide differences per sequence (unit: substitutions/sequence); their identical values indicate they represent the same metric (likely duplicated in labeling).
Өs (theta, per site): Population mutation rate estimate based on the number of segregating sites, scaled per site (unit: substitutions/site).
Өg (theta, per sequence): Same as Өs, but scaled to the full sequence length (unit: substitutions/sequence).
Hap (number of haplotypes): Count of distinct mitochondrial haplotypes observed.
Hd: Probability that two randomly chosen haplotypes differ (dimensionless, range 0-1).
Variance of Hd: Sampling variance of haplotype diversity.
Population expansion indices were calculated using DnaSP v6.12 based on 17 mitochondrial COI haplotypes (504 bp).
D+ and F+: Fu and Li’s tests comparing singleton vs. internal mutations (negative values suggest recent expansion or positive selection).
Fs: Fu’s statistic; strongly negative values indicate excess of haplotypes, consistent with population expansion.
S: Strobeck’s statistic (ratio of segregating sites to pairwise differences); lower values support expansion.
D: Tajima’s D; negative values reflect an excess of low-frequency variants, typical after demographic expansion.
R₂: Harpending’s raggedness index; low values (e.g., <0.3) indicate a smooth mismatch distribution, supporting recent expansion.
DISCUSSION
Previous studies have shown that Cs. longiareolata has a wide geographical distribution in Asia, Europe and Africa (18-20). The findings of this research are also consistent with these data and indicate that the populations in Iran have a genetic connection with global populations. The medium to high level of genetic diversity indicates that the populations of this species are not completely isolated in different regions. Phylogenetic data indicate that the populations in Iran are likely interacting genetically with other regions, which could be due to natural migration or environmental influences. Population expansion indices (such as Fu and Li’s D, Tajima’s D) indicate a probable increase in population size in the past, and this growth could be due to climatic changes, the expansion of suitable habitats, and an increase in water resources in the environment. Cs. longiareolata is a vector of important viral and bacterial diseases such as West Nile encephalitis, brucellosis, and avian influenza (7-11,24). Considering these factors, studying the genetic diversity of this species can help predict population changes and provide more effective control measures to reduce diseases transmitted by this mosquito. This research is one of practical comprehensive studies on the genetic diversity of Cs. longiareolata in Iran and provides valuable information for environmental management and vector control programs.
Genetic studies on mosquito populations have shown that environmental factors, including temperature, humidity, and available breeding sites, significantly impact genetic variation (33). The phylogenetic relationships of Cs. longiareolata populations in Iran suggest possible genetic exchange with populations from neighboring countries, further supporting the role of migration in maintaining genetic diversity (34). Studies on mosquito-borne disease transmission emphasize that genetic diversity in vector populations can influence pathogen susceptibility and transmission efficiency (35). Genetic studies on mosquito populations in Iran have demonstrated that environmental heterogeneity—including regional variation in temperature, precipitation, and larval habitat availability—shapes population structure and genetic diversity. For instance, analyses of mosquito species across Iranian ecozones revealed significant genetic differentiation correlated with altitude and aridity gradients (34). Notably, phylogeographic work on Cs. longiareolata in southern and western Iran identified shared haplotypes with populations from Iraq and Türkiye (35), providing direct molecular evidence of cross-border gene flow. Such migration likely counteracts genetic drift and sustains diversity in peripheral populations. Furthermore, studies on Aedes caspius and Culex pipiens in Iran have linked higher mitochondrial Hd with increased vector competence for West Nile virus and Dirofilaria immitis (1-3,11-12.36-38) underscoring the epidemiological relevance of genetic variation in local vector populations.
Additionally, research indicates that climatic shifts have historically played a role in mosquito population dynamics, leading to fluctuations in genetic diversity due to changes in habitat suitability (39). The presence of genetically distinct yet interconnected populations suggests that movement between regions may be more frequent than previously assumed, potentially facilitated by human activities and natural dispersal mechanisms (40). Such findings highlight the need for continuous surveillance and genetic monitoring of mosquito populations to mitigate the risks associated with emerging infectious diseases (41).
Incorporating molecular tools for vector surveillance can aid in identifying cryptic species and understanding their role in disease ecology, improving vector control strategies (42-44). Future research should focus on the impact of anthropogenic factors on genetic variation and how these changes may influence disease transmission dynamics. Strengthening collaborative research efforts across different geographical regions will enhance our ability to predict and manage vector-borne disease risks effectively. New studies suggest that genetic changes in mosquito populations are influenced by environmental factors, especially in areas with unstable climates (33). This adaptability may explain the persistence of Cs. longiareolata across diverse habitats, supporting their role as efficient disease vectors (37). The application of genomic sequencing in mosquito surveillance programs has provided novel insights into the evolutionary trajectories of different populations (38). Such approaches are essential for identifying emerging threats and assessing the impact of control measures (39). Furthermore, ecological studies have revealed that competition with other mosquito species, as well as interspecies hybridization, may also contribute to genetic differentiation in Cs. longiareolata (40). This underscores the need for integrated vector management programs that incorporate ecological, genetic, and epidemiological data (41).
Study Limitations
This study was limited by the small number of sequenced samples (n=6) due to budget and logistical constraints. Additionally, only one genetic marker (COI) was analyzed, which may not capture the full extent of genetic variation. Future research using multilocus approaches and larger datasets is recommended.
CONCLUSION
This study confirms that Cs. longiareolata populations in Iran share genetic connections with global populations, showing medium to high genetic diversity and this represents the first COI-based phylogenetic assessment of Cs. longiareolata in southern Iran that can show critical role of genetic diversity in shaping the adaptability of mosquito populations. The genetic exchange likely occurs through migration or environmental factors, with population expansion possibly driven by climatic changes and habitat availability. The research highlights the importance of genetic diversity in predicting mosquito population dynamics and improving disease control measures. Environmental factors and migration are key in maintaining genetic variation, which can affect disease transmission. Continued genetic monitoring is crucial for managing vector-borne diseases and improving surveillance strategies.
