https://orcid.org/0009-0004-3838-0085
Figures
Abstract
Aedes aegypti and Aedes albopictus are the most competent vectors of multiple human arboviral diseases, posing a global public health concern, particularly in Bangladesh. While there are numerous genomic resources available worldwide, the genomic resources from Southeast Asian countries are scarce. Current study reported the first characterization of the complete mitochondrial (mt) genomes of Ae. aegypti and Ae. albopictus from Bangladesh. The circular mitogenomes are 16,662 bp and 16,585 bp in size, with AT contents of 79.02% and 78.81%, respectively. Both mitogenomes contain all 37 functional subunits, including 13 protein-coding genes (PCGs), two ribosomal RNA genes, 22 transfer RNA genes (tRNAs), and a control region. We also reported the unique codon usage and Relative synonymous codon usage patterns, which are congruent with other members of the Culicine family. Our intraspecific analysis of 15 mitochondrial genes revealed higher genetic distance, but lower SNP density in Ae. aegypti, compared to Ae. albopictus, indicating Ae. aegypti might have a longer evolutionary history, while Ae. albopictus might have experienced recent population expansion with steady divergence. Similarity metrics and phylogeny of 13 PCGs from 37 taxa indicated both species of Aedes formed specific clusters, where Bangladeshi Aedes spp. showed close relationships with North American, Oceania and European populations. Our comprehensive tree incorporating Aedes, Ochleroratus and Culex spp. revealed distinct clades, aligning with previous studies. Current study provides a foundation for future research on Aedes spp. of Bangladesh, leveraging it to other Southeast Asian countries, aiding vector identification, control, and disease mitigation.
Citation: Islam MA, Begum S, Solaiman M, Zohora F-T-, Datta SK, Ahmed KA, et al. (2025) Complete mitogenomes of two major dengue vectors Aedes aegypti and Aedes albopictus from Bangladesh: Insights from comparative genomics with global mitogenome diversity and phylogenetics. PLoS One 20(9): e0333693. https://doi.org/10.1371/journal.pone.0333693
Editor: Muzafar Riyaz, Saint Xavier's College, INDIA
Received: March 20, 2025; Accepted: September 17, 2025; Published: September 30, 2025
Copyright: © 2025 Islam et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The mitogenome assemblies are deposited and publicly available under NCBI GenBank (https://www.ncbi.nlm.nih.gov/). GenBank Accession Nos. PQ197330 and PQ197331 are for Aedes aegypti and Aedes albopictus, respectively.
Funding: The research was partially supported by the CSIRO Postdoctoral Research Fund. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors declare no competing interests.
Introduction
The genus Aedes is medically significant, with species like Aedes aegypti (Linnaeus, 1762) and Aedes albopictus (Skuse, 1894) serving as vectors for several arboviruses that cause diseases like Dengue, Yellow Fever, Chikungunya, and Zika in humans. The native range of Ae. aegypti is West Africa, while Ae. albopictus originates from Southeast Asia, but both species are now found worldwide, including in the Indo-Pacific regions [1–3]. Ae. ageypti and Ae. albopictus are most prevalent in low-income countries, such as Bangladesh [4–6]. Geographically, Bangladesh is located at the center of South-East Asia, with a well-suited environment for mosquito breeding. Besides, wide distribution and strong adaptability, their diurnal biting habits and human blood preferences have contributed to the serial outbreaks of several mosquito-borne diseases in recent years [7–10]. Recently, Dengue fever has become a significant concern for public health, causing socioeconomic losses all over the country. Bangladesh has experienced sporadic outbreaks of Dengue since 1964, followed by the first large outbreak in 2000 [11]. The infection and deaths upsurged in outbreaks in the following 2019 and 2023 years, with >100,000 and >250,000 infected individuals and >160 and >1,700 deaths respectively [7,12].
To control the spread of Dengue and other mosquito-transmitting diseases, it is important to control mosquito populations, especially these two Aedes spp. [9,13]. Bangladesh has taken numerous unorganized strategies, e.g., insecticide spray, using mosquito nets in houses, campaigns for maintaining hygiene and destroying mosquito habitats, but as one of the most densely populated countries around the world, these measures are surely not enough [14]. Unorganized practices of insecticide usage often resulted in insecticide resistance. For example, one study reported widespread pyrethroid resistance in Ae. aegypti population from Bangladesh, with population-specific variabilities in deltamethrin and malathion susceptibilities [15]. A subsequent study on Ae. albopictus further demonstrated resistance to pyrethroid (permethrin), while showing susceptibility to pyrethroid (deltamethrin), organophosphate (malathion), and Carbamate (bendiocarb) insecticides [16]. For a comprehensive management program, it is important to understand the endemic populations, habitat characterization, and most importantly the unique genetic elements of local populations.
A review study reported 123 mosquito species from Bangladesh [17]. Although our literature search can find gene sequences (e.g., cox1, 16S or microsatellites) of these species from various parts of the world [18–20], there is a scarcity of genomic resources of Dengue vectors from Southeast Asian countries, including Bangladesh. A morphological and partial cox1-based study by Siddiki et al., (2019) [21] reported three mosquito species, namely Ae. albopictus, Ae. aegypti and C. pipiens from various locations of South-eastern part (Chattogram Metropolitan area) of Bangladesh. A recent study [22] has identified eleven species mosquitoes, including two species of Aedes, from six different locations from Bangladesh, using partial cox1 gene sequences. Further, using two mitochondrial gene sequences [23] recorded few C. pipiens complexes from Gulshan, Dhaka, Bangladesh, reporting the first record of C. pipiens pallens in the Indian region, which is commonly found in East Asian countries and vectors of filariasis.
A partial mitochondrial sequence cannot confer the overall genetic markup of a species. To understand these two species comprehensively, it is important to look at the bigger picture, at the whole genome scale, or at least at the maternally inherited whole mitogenome level. Population level and high-resolution genetic studies are essential to control the spread of mosquito-borne diseases. Further, it can set up baseline resources to evaluate the efficacy of existing pesticide-based control strategies. It is intriguing that, even though there are several mosquito mitogenomes sequenced worldwide, none of them are from Southeast Asian countries, which are considered a hotspot of these mosquitoes. Also, existing mitogenomes show a high skew for the Anopheles genus; considerably less data is known for Aedes, Ochlerotatus, Culex, and other genera [24]. This gap in knowledge hinders our ability to apply genomic insights to local vector control efforts.
The present study aims to fill this gap by utilizing high thought put, Illumina short-read based sequencing technology and subsequently assembly and curation of the complete mitogenomes of these two Aedes spp. To our knowledge, this is the first record and detailed characterization of the complete mitochondrial genomes from Bangladesh, broadly Southeast Asia. We also conducted a comparative phylogenetic analysis with 37 other complete mitogenomes, reported in NCBI to date. Our detailed characterization and comparison with other Aedes spp. from different countries set up a baseline for future research of whole genome level comparison, and species uniqueness and will also play a vital role in the development of more effective strategies for dengue control in the region.
Materials and methods
Sample collection and identification
The specimen of adult Ae. aegypti individual was collected from Kamrangirchar, Dhaka, Bangladesh (geographic location: 23.71756194 N 90.37314583 E) on August 11, 2023, using a sweep net. On the other hand, Ae. albopictus was collected from Curzon Hall, Dhaka, Bangladesh (geographic location: 23.727000 N 90.401462 E) on August 14, 2023, using the same process. The collected specimens were identified using standard dichotomous taxonomic keys [25].
Genomic DNA extraction and sequencing
Genomic DNA was extracted from both collected specimens using the DNeasy Blood & Tissue Kit (Qiagen, Germany) following the manufacturer’s protocol. The quality of DNA was assessed using a NanoDrop spectrophotometer (Thermo Fisher Scientific, USA). Only high-quality DNA samples were sent for sequencing. The library preparation and Illumina-based sequencing were commercially sourced at GENEWIZ Genomic Center, Suzhou, China. From the prepared library, 150 bp paired-end reads were generated and sequenced in a NovaSeq 6000 system (Illumina, San Diego, CA). A total of 10Gb of raw data per species was generated.
Preprocessing and Bioinformatics Workflow
The sequences were processed as per previously described methods [26]. Briefly, the read quality was checked by FastQC (0.12.1) [27] and quality was trimmed using TrimGalore v6.6 [28]. Trimmed reads were used to assemble mitogenomes of Ae. aegypti and Ae. albopictus. Reference-based assemblies were conducted using CLC Genomics Workbench 23.0.4 (CLC Bio, Aarhus, Denmark), where respective complete mitogenomes (NC_035159.1 for Ae. aegypti and KR068634.1 for Ae. albopictus) were used as references. Assemblies were confirmed visually by mapping raw reads back to each assembly. For annotation, multiple sequence alignment was performed retrieving other mosquito mitogenomes from GenBank using MAFFT v7.2.1.5 [29]. The circular map of the mitogenomes of both species was drawn using the Geneious Programme. Base composition and skewness were calculated in Seqkit [30] and Microsoft Excel programs and plotted using ggplot2 R Package [31]. Relative Synonymous Codon Usage was calculated using the Codon Adaptation Index calculator (CAI) [32].
Phylogenetic analysis
For phylogenetic tree construction, a total of 37 mitogenome sequences (two from this study, and 35 derived from GenBank) were considered. The species names and associated accession numbers are shown in the generated tree. For each species, all 13 protein-coding genes were concatenated, making a single sequence for each. The coding sequences were aligned using MAFFT v7.2.1.5 [29], followed by optimal model selection, a maximum likelihood (ML) based phylogeny, and bootstrap analysis using IQ-Tree [33]. The iTol web server was used to visualize the consensus cladogram [34]. Bootstrap values ≥70% were considered to represent moderate confidence [35]. Additionally, for Bayesian inferences, BEAST software suite (v.10.5.0) was utilized. Briefly, the aligned sequences were used to create an XML file with HKY substitution model, using BEAUTi module and phylogenetic analysis conducted using BEAST. The tree was constructed using TreeAnnotator module, with 1000000 Burnin and the target tree type as Maximum clade credibility tree. The resulting nexus file was visualized using iTol web server.
Results
Features of Ae. aegypti and Ae. albopictus mitogenomes from Bangladesh
The complete mitogenomes of Ae. aegypti and Ae. albopictus were determined to be 16,662 bp and 16,585 bp in length, respectively, with high sequence similarities (99.75% and 99.85%) to NCBI reference mitogenomes (Fig 1). The complete mitogenomes sequences were submitted to GenBank with accession number PQ197330, and PQ197331, respectively. Both mitogenomes were circular, containing all 37 expected genes including 13 protein-coding genes (PCGs; cytb, atp6, atp8, nad1–6, cox1–3 and nad4L), 2 ribosomal RNAs (rRNAs) (12S and 16S) and 22 tRNAs with a AT-rich control region (CR). Both species’ mitochondrial sequences exhibited AT-biasness. Overall, in both mitogenomes, GC content was 20.98 and 20.10% in Ae. aegypti and Ae. albopictus, respectively – but AT content was elevated to 78.02% and 79.02%, which are > 4 times higher than GC content. The AT skew values are 0.02 and 0.01, and the GC skew values are −0.22 and −0.19, respectively (S1 Fig).
Both mitogenomes contain 13 PCGs with variable gene lengths. The extent of the protein-coding gene (PCG) regions was 11,191 base pairs in Ae. aegypti and 11,223 base pairs in Ae. Albopictus (Table 1). The relative lengths of the PCGs (range:162–1731 bp) showed the subsequent organization: nad5 > cox1 > nad4 > cytb> nad2 > nad1 > cox3 > cox2 > atp6 > nad6 > nad3 > nad4L > atp8. In both sequences, nine PCGs, specifically cox1, cox2, cox3, nad2, nad3, nad6 atp8, atp6, and cytb, showed a sense of transcription on the forward strand (+), and the remaining PCGs, namely nad5, nad4, nad4L, and nad1, displayed the sense of transcription on the reverse strand (-). Most PCGs used ATN as the start codon, with cox1 employing a noncanonical TCG start codon. Among the start codons, ATG was the most prevalent (in cox2, atp6, cox3, nad4, nad4L, and cytb), followed by ATT (in nad2, atp8, nad3, and nad6). On the other hand, the stop codons were predominantly TAA, although some incomplete stop codons (T or TA) were observed (Table 1).
Throughout the 13 protein-coding genes Serine (Ser) and Leucine were most recurrent exhibiting codon usages (11.67% each) and (10%) respectively. Serine with 7 distinct codons and Leucine with 6 codons. In both Ae. aegypti and Ae. albopictus, Proline (Pro), Alanine (Ala), Valine (Val), Glycine (Gly), and Arginine (Arg) utilized 4 different codons (6.67%) (Fig 2). Threonine (Thr) and Arginine (Arg) used 3 different codons (5%) in Ae. aegypti and Ae. albopictus (Fig 2), respectively. In both species, the remaining amino acids had codon usages of 3.34% utilizing only two codons each (Fig 2). Some codons were used preferentially across all PCGs, with TTA (Leu) showing the highest abundance (RSCU > 4). Codon usage bias was similar between the two species. Codon usage bias highlights evolutionary pressures shaping mitochondrial genomes. Among the 60 codons, 10 codons (GAA for glutamic acid, TTA for leucine, AAT for asparagine, ATA for methionine, CAA for glutamine, AGT and TCT for serine, ATT for isoleucine, TTT for phenylalanine, and ACT for threonine) in Ae. aegypti, while 12 codons (TTA for leucine, AAT for asparagine, ATA for methionine, AGT, TCA, and TCT for serine, ATT for isoleucine, TTT for phenylalanine, ACA and ACT for threonine, TAT for tyrosine, and GTA for valine) in Ae. albopictus emerged throughout the 13 PCGs (RSCU > 0). The TTA codon of leucine had an RSCU value greater than 4 across all 13 PCGs, indicating its highest abundance in both species. Additionally, summing up the RSCU values across the PCGs, the TTA codon of leucine had higher cumulative RSCU values of 64.20 in Ae. aegypti and 64.80 in Ae. albopictus. Conversely, low RSCU values, less than 2, were observed in six codons in Ae. aegypti and eight codons in Ae. albopictus across the 13 PCGs (Fig 2). The codon ACG for threonine was used in Ae. albopictus but absent in Ae. aegypti (Fig 2B), whereas CGC for arginine was used in Ae. aegypti but unused in Ae. albopictus (Fig 2A).
The placement of the 12S and 16S (ribosomal RNA genes) was consistent across both mt genomes, whereas 16S (large subunit) was surrounded by tRNA-Leu and tRNA-Val, which were 1,333 bp (Ae. aegypti) and 1,332 bp (Ae. albopictus) in lengths and 12S (small subunit) was flanked by tRNA-Val and the AT-rich region, which were 778 bp (Ae. aegypti) and 795 bp (Ae. albopictus) long. Individually, the length of the large ribosomal subunit 16S had narrow variation whereas the small ribosomal subunit 12S was a little bit spacious. The AT-rich CR region is one of the highlights of both assemblies. We found the CR of Ae. aegypti is larger (1,721 bp), compared to that of Ae. albopictus (1,694).
Evolutionary relationship of Aedes species from different countries
We compared gene sequences from various countries, including six Aedes aegypti and thirteen Aedes albopictus specimens. We considered 13 PCGs and 2 rRNA sequences. As the CR region is not well annotated in several NCBI records, we did not consider it for this analysis. In terms of K2P distance, we found an average distance of 0.008 and 0.004 (dotted lines in Fig 3A) in Ae. aegypti and Ae. albopictus respectively, showing higher genetic diversity of mitochondrial genes of Ae. aegypti than that of Ae. albopictus. In Ae. aegypti, atp8, and 16S genes showed the highest and lowest distances, while in Ae. albopictus, nad5, and nad3 showed the highest and lowest values. Interestingly, K2P distances of two rRNAs (12S and 16S) and two nad-genes (nad5 and nad6) were less in Ae. aegypti, compared to other species. All other PCGs showed high distance across Ae. aegypti. The large error bars across Ae. aegypti genes indicate higher within-species genetic variations, including a possibility of greater evolutionary divergence within populations around the world.
The base pair per single nucleotide polymorphism (SNP) is shown in Fig 3B. A mean base pair per SNP of 137 and 80 bp is found in Ae. aegypti and Ae. albopictus genes, which means one SNP variation was detected in every 137 and 80 bp of these species respectively. Overall, Ae. aegypti showed high estimates, especially in rRNA genes, demonstrating high conservation of these gene sequences across all specimens considered. On the contrary, relatively stable estimates were found across all the PCGs and rRNA genes in Ae. albopictus, which conveys uniform mutational distribution. At the gene level, the highest and lowest estimates were observed in 12S (549) atp8 (32), and nad3 (342) and nad5 (11) genes, in Ae. aegypti and Ae. albopictus, respectively. Interestingly, both species showed the same values for cox2, cytb, nad2, and nad3 genes. By combining insights from K2P and base pair per SNP estimates, our analysis showed some interesting insights. We have found higher K2P distance and base pair per SNP (fewer SNPs) in Ae. aegypti. It can be due to mutation clustering in specific genes, rather than evenly spread out across the genes. This may convey toward longer evolutionary history with isolated populations, where mutations could accumulate over time, increasing genetic distance, but conserving few SNPs per gene.
Phylogeny across various mosquito mitogenomes
A similarity matrix and phylogenetic tree based on all 13 protein-coding regions, were generated to find the position of Ae. aegypti and Ae. albopictus among other mitogenomes available at NCBI (S1 Table). The identity matrix revealed that, Ae. aegypti from Bangladesh exhibited high similarities with 99.7% and 99.8% identities to populations from Australia and Trinidad-Tobago (S2 Fig). The similarity with the United Kingdom and Brazil was slightly lower at 98.6%. In contrast, Ae. albopictus showed remarkable similarity, with a 99.9% identity with several countries, including Thailand, the USA, Cameroon, Albania, Greece, Italy, Mexico, Japan, France, the Philippines, Brazil, and Taiwan.
Using the concatenated PCG, we have constructed a ML tree (Fig 4) and a Bayesian inference tree (S3 Fig), which showed mostly similar topology with higher Bootstrap (>75%) and Bayesian posterior probability ≥ 0.95. In the phylogenetic tree, Ae. aegypti and Ae. albopictus are positioned within distinct clades. Ae. aegypti from Bangladesh clustered with specimen from Australia and Trinidad-Tobago with a bootstrap value of 96–100%, while Ae. albopictus formed clades with Thailand, USA, and Cameroon populations (90–100%). The evolutionary divergence of Ae. aegypti and Ae. albopictus from their common ancestor was confirmed, with outgroup C. quinquefasciatus forming a distinct outgroup. Phylogenetic analysis showed that the Ae. aegypti mitogenome from Bangladesh clusters with its counterparts from Australia and Trinidad and Tobago, forming a clade. Meanwhile, Ae. aegypti from the United Kingdom and Brazil form a separate clade with 100% bootstrap support. Similarly, Ae. albopictus formed a clade with populations from Thailand, the USA, and Cameroon with 100% bootstrap value, while Ae. albopictus populations from China, Brazil, Albania, Italy, France, Taiwan, Mexico, and Japan formed separate clusters. Interestingly, the Philippine Ae. albopictus isolate diverged from other populations, suggesting genetic heterogeneity that warrants further investigation. Additionally, our phylogenetic tree identified some additional findings. Ochlerotatus vigilax from Brazil and Australia formed a separate sister clade (100%) due to their mitogenome sequence peculiarities, while Ae. bucki and Ae. notoscriptus from Saba and Australia were their close relatives. Ae. japonicus from the USA and Japan were also close related as they formed a separate lineage with strong support (100%). The Ae. vexans populations from China and the USA clustered together with a bootstrap value of 100%, indicating a close evolutionary relationship. The outgroup species C. quinquefasciatus formed a distinct clade, reinforcing its distant evolutionary relationship within the Culicidae family.
The maximum likelihood tree was constructed by concatenation of 13 PCGs listed in Supplementary S1 Table. 1000 bootstrap values were considered. The species sequenced in this study are shown in red.
Discussion
The findings of this study provide insights into the mitogenomic characteristics of Ae. aegypti and Ae. albopictus from Bangladesh, reinforcing their genomic similarities and differences. By sequencing and characterizing these mitogenomes, we have significantly expanded the genomic resources available for these major dengue vectors in this region, especially Southeast Asia. Our findings reveal distinct genetic features and variations in the mitochondrial DNA of both species, providing valuable insights into their evolutionary trajectories and population genetics. This study represents the first comprehensive analysis of the complete mitochondrial genomes of Aedes aegypti and Aedes albopictus collected from Bangladesh, revealing a high degree of similarity with previously studied Aedes species. The high sequence similarity (>99%) between the newly sequenced mitogenomes and reference sequences confirms the consistency of mitochondrial genome structures across different populations.
The genomes of both species contain all 37 genes, including 13 protein-coding genes (PCGs), and exhibit AT biasness. The observed AT-rich composition aligns with known insect mitogenomic trends, supporting the influence of replication-associated biases. The bias resembles the presumed distinct features of previously recorded mosquito mitochondrial genomes, such as Ae. aegypti (AT: 78.2%), Ae. vexans (AT: 78.54%), and Ae. fluviatilis (AT: 77.5%) [36–38]. Insect mitogenomes display a unique strand-specific nucleotide composition bias, resulting from mutations associated with replication or transcription [39]. A high proportion of AT pairs suggests that most of the mitogenome backbone is composed of adenine and thymine, compared to the proportions of guanine and cytosine. Our findings output similar results of the other insect family Culicidae where the overall AT skew was 77.08% [40].
Our in-depth analysis of mitogenomes showed some unique features between two Aedes species. Among the 38 genes (13 PCG, 2rRNA, 22 tRNA and 1 CR) of both species, the strand-ness and sizes are mostly similar, except strandness of trnS1 and trnL1 and minor base pair differences of 18 genes (trnI, trnQ, trnM, trnY, trnL2, trnK, nad3, trnR, trnA, trnN, trnE, trnT, nad6, cytb, nad1, 12S, 16S and CR). As we used identical processing, assembly and annotation steps, such discrepancy might be attributed to the species-specific changes, which is evident in similar studies [26,41]. In congruent with other mitogenomes from Culicidae, CR of both species is located between the 12S and tRNA-Ile genes which have varying sizes, with a length of 1,721 bp and 1,694 bp, respectively. The CR of the current two species were distinct from others such as Ae. vexans (948 bp), Ae. alboannulatus (1,072 bp), and Ae. notoscriptus (939 bp) [36]. The AT-rich control region typically contains numerous homopolymer sequences and exhibits high variability in both sequence length and mutation rates, which pose challenges for next-generation sequencing technologies [42,43]. It is often difficult to assemble, due to their highly repetitive homology, and often long read sequencing is recommended to resolve the ambiguities. Overall, the control regions exhibit unique sequence and structural features that may be Genus-specific, making them valuable genetic markers for evolutionary and population genetic studies of mosquito species [44]. In the mitochondrial genomes of invertebrates, the most frequent standard initiation codons are found to be ATA, ATG, ATT, and GTG, and the majority of mosquito protein-coding genes use ATG. However, across some species, GTG was observed as the start codon for nad5 and is likely to be a standard feature [45]. In contrast, both cox1 genes utilize a TCG codon, an unconventional start codon for mitochondrial genes. Comparative analyses with other mosquito mitogenomes indicate that this atypical start codon is also present in beetle (Thalassa montezumae) and Anopheles (A. gambiae, A. funestus) species [45–47], suggesting that it is evolutionarily conserved rather than species-specific. The preference for ATG start codons and incomplete stop codons (T or TA) further reflects the adaptation of mitochondrial translation mechanisms.
A comparative analysis between RSCU values of two species indicates identical features. Codon usage bias highlights evolutionary pressures shaping mitochondrial genomes. Serine and Leucine are the highest used codons in both species, notably the TTA codon of Leucine – which achieved an RSCU value greater than 4. One study [48] showed different arthropods differentially bias their usage of Serine, Arginine and Leucine codons and among which Serine bias is correlated with nucleotide topologies. Overall, similar codon usage and RSCU values are observed in both Aedes species, which is identical not only across Aedes genera, but also across diverse arthropod taxa [49]. Some minor species specific RSCU values and codon utilization are also observed, highlighting minor evolutionary divergences between the two species, aligning with previous studies on relative synonymous codon usage (RSCU) in Aedes species [36,37].
Our comparative assessment of 15 mitochondrial genes, based on K2P and base pair per SNP, showed higher genetic distance, but low SNPs per base pair in Ae. aegypti than Ae. albopictus. This pattern can be explained by the broader geographic spread and greater genomic diversity among the Ae. aegypti specimens analyzed (Australia, Trinidad-Tobago, the United Kingdom, Brazil, and Bangladesh). The higher genetic distance reflects accumulated divergences across these geographically distant populations, while the lower SNP density per base pair may point to past demographic events such as selective sweeps or historical bottlenecks that reduced standing variation. In contrast, Ae. albopictus exhibited higher SNP density but comparatively lower genetic distance, consistent with a rapid and more recent global expansion, where high levels of polymorphism are maintained within relatively less divergent lineages. A coxI-based study also showed similar trends of higher haplotype diversities of Ae. aegypti and better capability to adapt to rapidly changing environmental variabilities [50]. A whole genome wide study among 27 populations of Ae. aegypti and Ae. albopictus found high genetic distance in Ae. aegypti populations, especially in Pacific populations [51]. While we were limited by the accessions available at NCBI, we still found some indication of higher genetic distance of Oceania population (Australia) with that of the specimen from other countries (United Kingdom, Brazil, and Bangladesh). Interestingly, even mitogenomes from twelve different countries were considered for Ae. albopictus analysis, a lesser genetic distance was observed with uniform mutational diversities across the genes. This confers to recent population expansion of Ae. albopictus in various parts of the world [52]. Together, these findings highlight distinct evolutionary trajectories between Ae. aegypti and Ae. albopictus, suggesting that demographic history and dispersal patterns have shaped their mitochondrial diversity differently.
The phylogenetic analysis confirmed that Ae. aegypti and Ae. albopictus form distinct clades, reflecting their evolutionary divergence. Bangladeshi Ae. aegypti clustered with populations from Australia and Trinidad-Tobago (bootstrap 96–100%), suggesting either human-mediated dispersal facilitated by global trade and travel or retention of ancestral lineages, while other populations, such as those from the UK and Brazil, formed separate clades. Ae. albopictus from Bangladesh grouped with Thailand, USA, and Cameroon populations (bootstrap 100%), whereas isolates from China, Brazil, Europe, Taiwan, Mexico, and Japan formed distinct clusters. The divergence of the Philippine isolate (bootstrap 81–95%) highlights potential local adaptation or unique demographic history. Notably, we could not find mitogenomes of Ae. albopictus from Australia (which invaded in 2004) and Trinidad-Tobago (first reported in 2002). Investigating these populations further may provide insights into genetic variations and incursions from neighboring countries. Combined with the published mitogenome sequence of Culicidae, the phylogenetic tree confirmed the monophyly and position of Culicidae with high support value. Our phylogeny placed members of Aedini tribe together, which consists of four closely related taxa, namely Aedes, Ochlerotatus, Haemagogus, and Psorophora genera. The topology placed Aedes aegypti closer to Ae. vexans, which is well supported by previous studies [36]. Members of Ae. albopictus appeared separately as a cluster and closely appeared with its sister species, Ae. flavopictus. Ae. flavopictus is often a rare species, which often co-occurs with Ae. albopictus [53]. The members of the Culicini tribe (Culex spp.) are used as an outgroup and well separated from the Aedini tribe. A molecular study showed these tribes diversified approx. 130 million years ago [38,54].
Overall, these findings contribute valuable genetic data for mosquito evolutionary studies and provide a foundation for understanding mitochondrial genome variability within Aedes species. Although current study has got some limitations, e.g., single individual sequencing, lack of long read-based sequencing data, these short-read based mitogenome assemblies still play valuable role to trace invasion routes of these notorious vectors and also can be instrumental to track presence of insecticide resistance. The data may also facilitate vector control strategies by elucidating genetic markers for population differentiation and transmission dynamics. The detailed mitogenomic sequences obtained offer a robust framework for further studies on the genetic diversity and adaptation of these mosquitoes. The identification of specific mitochondrial gene variants and potential markers of interest enhances our understanding of the molecular basis underlying vector biology and disease transmission dynamics in Bangladesh. This baseline genomic data marks a significant advancement in our ability to combat several human arboviral diseases especially Dengue, Chikungunya, Yellow fever, Zika through genomics-informed vector management approaches.
Supporting information
S1 Fig. AT/GC contents and AT/GC-skews of the investigated mitogenomes.
https://doi.org/10.1371/journal.pone.0333693.s001
(TIF)
S2 Fig. Identity similarity matrix of mitogenomes of different mosquito species.
Sample information and accessions can be found in supplementary S1 Table.
https://doi.org/10.1371/journal.pone.0333693.s002
(TIF)
S3 Fig. Bayesian inference of phylogenetic tree based on concatenated PCGs of different mosquito species.
Bayesian posterior probability values are shown in nodes.
https://doi.org/10.1371/journal.pone.0333693.s003
(TIF)
S1 Table. A table showing list of mosquito sequence accessions utilized for comparative study.
https://doi.org/10.1371/journal.pone.0333693.s004
(PDF)
Acknowledgments
Authors are grateful to the all members of Advanced Fisheries and DNA barcoding Laboratory, Department of Zoology, University of Dhaka, Bangladesh, for their support. We extend heartfelt appreciation to our family and friends who helped directly and indirectly during the entire study.
References
- 1. Crawford JE, Alves JM, Palmer WJ, Day JP, Sylla M, Ramasamy R, et al. Population genomics reveals that an anthropophilic population of Aedes aegypti mosquitoes in West Africa recently gave rise to American and Asian populations of this major disease vector. BMC Biol. 2017;15(1):16. pmid:28241828
- 2. Powell JR, Gloria-Soria A, Kotsakiozi P. Recent History of Aedes aegypti: Vector Genomics and Epidemiology Records. Bioscience. 2018;68(11):854–60. pmid:30464351
- 3. Wu J-Y, Lun Z-R, James AA, Chen X-G. Dengue Fever in mainland China. Am J Trop Med Hyg. 2010;83(3):664–71. pmid:20810836
- 4. Abuelmaali SA, Jamaluddin JAF, Noaman K, Allam M, Abushama HM, Elnaiem DE. Distribution and genetic diversity of Aedes aegypti subspecies across the sahelian belt in sudan. Pathogens. 2021;10(1):1–15.
- 5. Dalpadado R, Amarasinghe D, Gunathilaka N. Water quality characteristics of breeding habitats in relation to the density of Aedes aegypti and Aedes albopictus in domestic settings in Gampaha district of Sri Lanka. Acta Trop. 2022;229:106339. pmid:35114170
- 6. Deng Y, Ren S, Liu Q, Zhou D, Zhong C, Jin Y, et al. A high heterozygosity genome assembly of Aedes albopictus enables the discovery of the association of PGANT3 with blood-feeding behavior. BMC Genomics. 2024;25(1):336. pmid:38570743
- 7. Rafi A, Mousumi AN, Ahmed R, Chowdhury RH, Wadood A, Hossain G. Dengue epidemic in a non-endemic zone of Bangladesh: Clinical and laboratory profiles of patients. PLoS Negl Trop Dis. 2020;14(10):e0008567. pmid:33048921
- 8. Mutsuddy P, Tahmina Jhora S, Shamsuzzaman AKM, Kaisar SMG, Khan MNA. Dengue Situation in Bangladesh: An Epidemiological Shift in terms of Morbidity and Mortality. Can J Infect Dis Med Microbiol. 2019;2019:3516284. pmid:30962860
- 9. Khan HR, Islam MM, Akter T, Karim MR, Farid MS. Diversity of mosquitoes and their seasonal fluctuation in two wards of Dhaka city. Dhaka Univ J Biol Sci. 2014;23(1):17–26.
- 10. Benelli G, Pavela R, Rakotosaona R, Nzekoue FK, Canale A, Nicoletti M, et al. Insecticidal and mosquito repellent efficacy of the essential oils from stem bark and wood of Hazomalania voyronii. J Ethnopharmacol. 2020;248:112333. pmid:31654797
- 11. Mahmood R, Benzadid MS, Weston S, Hossain A, Ahmed T, Mitra DK, et al. Dengue outbreak 2019: clinical and laboratory profiles of dengue virus infection in Dhaka city. Heliyon. 2021;7(6):e07183. pmid:34141938
- 12. Amin MR. Recent trend in dengue in Bangladesh. Bangladesh J Med. 2023;34(3):176–8.
- 13.
Islam J, Asif MH, Rahman S. Exploring mosquito hazards in Bangladesh: challenges and sustainable solutions. 2024;7(2):1–29.
- 14. Hossain MS, Noman AA, Mamun SMAA, Mosabbir AA. Twenty-two years of dengue outbreaks in Bangladesh: epidemiology, clinical spectrum, serotypes, and future disease risks. Trop Med Health. 2023;51(1):37. pmid:37434247
- 15. Al-Amin HM, Johora FT, Irish SR, Hossainey MRH, Vizcaino L, Paul KK, et al. Insecticide resistance status of Aedes aegypti in Bangladesh. Parasit Vectors. 2020;13(1):622. pmid:33317603
- 16. Al-Amin HM, Irish S, Lenhart A, Alam MS. Preliminary report of the insecticide susceptibility status of Aedes albopictus in Bangladesh. Am J Trop Med Hyg. 2021;106(1):332–3.
- 17. Irish SR, Al-Amin HM, Alam MS, Harbach RE. A review of the mosquito species (Diptera: Culicidae) of Bangladesh. Parasit Vectors. 2016;9(1):559. pmid:27770829
- 18. Shin J, Rahman MM, Kim J, Marcombe S, Jung J. Genetic diversity of dengue vector Aedes albopictus collected from South Korea, Japan, and Laos. Insects. 2023;14(3).
- 19. Gandhi R, Yadav KK, Patil PB, Bihani P, Char B, Dasgupta SK, et al. Molecular analysis of mitochondrial cytochrome oxidase I gene of Aedes aegypti L. mosquitoes. Journal of Asia-Pacific Entomology. 2020;23(1):51–9.
- 20. Kawada H, Futami K, Higa Y, Rai G, Suzuki T, Rai SK. Distribution and pyrethroid resistance status of Aedes aegypti and Aedes albopictus populations and possible phylogenetic reasons for the recent invasion of Aedes aegypti in Nepal. Parasit Vectors. 2020;13(1):213. pmid:32321546
- 21. Siddiki AM, Sarker MS, Mazumder S, Bhuiya BA, Basher K, Kamal T, Hossain MA. Morphotaxonomic and DNA barcoding analyses of mosquitoes collected from Chattogram Metropolitan area. Bangladesh Journal of Veterinary and Animal Sciences. 2019 Jan;7(1):1-08.
- 22. Rain FF, Aslam AF, Al-amin HM, Alam MS. Molecular characterization of major vector mosquitoes of Bangladesh. Acta Entomol Serbica. 2023;2023(2):91–102.
- 23. Jannat KNE, Datta SK, Ahmed MS, Begum M. Culex pipiens complex with three new records in Bangladesh: a new challenge to the elimination of lymphatic filariasis. Bangladesh J Zool. 2024;52(1):95–110.
- 24. Foster PG, de Oliveira TMP, Bergo ES, Conn JE, Sant’Ana DC, Nagaki SS, et al. Phylogeny of Anophelinae using mitochondrial protein coding genes. R Soc Open Sci. 2017;4(11):170758. pmid:29291068
- 25. Rueda LM. Pictorial keys for the identification of mosquitoes (Diptera: Culicidae) associated with dengue virus transmission. Zootaxa. 2004;589(1):1–60.
- 26. Siddika MA, Ahmed KA, Alam MS, Bushra J, Begum RA. Complete mitogenome and intra-family comparative mitogenomics showed distinct position of Pama Croaker Otolithoides pama. Sci Rep. 2024;14(1):13820. pmid:38879694
- 27.
Andrews S. FastQC: a quality control tool for high throughput sequence data. 2010.
- 28.
Krueger F. Trim Galore!: A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data. Babraham Inst. 2015.
- 29. Katoh K, Standley DM. MAFFT multiple sequence alignment software version 7: improvements in performance and usability. Mol Biol Evol. 2013;30(4):772–80. pmid:23329690
- 30. Shen W, Le S, Li Y, Hu F. SeqKit: A Cross-Platform and Ultrafast Toolkit for FASTA/Q File Manipulation. PLoS One. 2016;11(10):e0163962. pmid:27706213
- 31. Wickham H. Ggplot2. Wiley Interdiscip Rev Comput Stat. 2011;3(2):180–5.
- 32. Puigbò P, Bravo IG, Garcia-Vallve S. CAIcal: a combined set of tools to assess codon usage adaptation. Biol Direct. 2008;3:38. pmid:18796141
- 33. Nguyen L-T, Schmidt HA, von Haeseler A, Minh BQ. IQ-TREE: a fast and effective stochastic algorithm for estimating maximum-likelihood phylogenies. Mol Biol Evol. 2015;32(1):268–74. pmid:25371430
- 34. Letunic I, Bork P. Interactive Tree of Life (iTOL) v6: recent updates to the phylogenetic tree display and annotation tool. Nucleic Acids Res. 2024;52(W1):W78–82. pmid:38613393
- 35. Tang C, Du X. Complete mitochondrial genomes of two moths in the tribe Trichaeini (Lepidoptera: Crambidae) and their phylogenetic implications. Ecol Evol. 2023;13(6):e10188. pmid:37304368
- 36. Ma X, Wang F, Wu T, Li Y, Sun X, Wang C, et al. First description of the mitogenome and phylogeny: Aedes vexans and Ochlerotatus caspius of the Tribe Aedini (Diptera: Culicidae). Infect Genet Evol. 2022;102(April).
- 37. Sousa AA, Cruz ACR, da Silva FS, da Silva SP, Neto JPN, Barros MC. Sequencing and analysis of the mitochondrial genome of Aedes aegypti (Diptera: Culicidae) from the Brazilian Amazon region. Insects. 2023;14(12).
- 38. do Nascimento BLS, da Silva FS, Nunes-Neto JP, de Almeida Medeiros DB, Cruz ACR, da Silva SP, et al. First Description of the Mitogenome and Phylogeny of Culicinae Species from the Amazon Region. Genes (Basel). 2021;12(12):1983. pmid:34946932
- 39. Cameron SL. Insect mitochondrial genomics: implications for evolution and phylogeny. Annu Rev Entomol. 2014;59:95–117. pmid:24160435
- 40. Zhang S-K, Shu J-P, Wang Y-D, Liu Y-N, Peng H, Zhang W, et al. The complete mitochondrial genomes of two sibling species of camellia weevils (Coleoptera: Curculionidae) and patterns of Curculionini speciation. Sci Rep. 2019;9(1):3412. pmid:30833607
- 41. Ahmed KA, Karawita A, Klein MJ, Mincarelli LF, Secondini B, Satta G, et al. Complete mitochondrial genomes of Culicoides brevitarsis and Culicoides imicola biting midge vectors of Bluetongue Virus. Mitochondrial DNA B Resour. 2025;10(1):67–71. pmid:39776561
- 42. Matthews BJ, Dudchenko O, Kingan SB, Koren S, Antoshechkin I, Crawford JE, et al. Improved reference genome of Aedes aegypti informs arbovirus vector control. Nature. 2018;563(7732):501–7. pmid:30429615
- 43. Hardy CM, Court LN, Morgan MJ, Webb CE. The complete mitochondrial DNA genomes for two lineages of Aedes notoscriptus (Diptera: Culicidae). Mitochondrial DNA A DNA Mapp Seq Anal. 2016;27(3):2024–5. pmid:25350735
- 44. Hao Y-J, Zou Y-L, Ding Y-R, Xu W-Y, Yan Z-T, Li X-D, et al. Complete mitochondrial genomes of Anopheles stephensi and An. dirus and comparative evolutionary mitochondriomics of 50 mosquitoes. Sci Rep. 2017;7(1):7666. pmid:28794438
- 45. Iovinella I, Giovannini L, Mazza G, Naqqi Manco B, Strangi A. The complete mitogenome and phylogenetic analysis of Thalassa montezumae Mulsant, 1850 (Coleoptera: coccinellidae). Mitochondrial DNA B Resour. 2024;9(10):1355–9. pmid:39381364
- 46. Beard CB, Hamm DM, Collins FH. The mitochondrial genome of the mosquito Anopheles gambiae: DNA sequence, genome organization, and comparisons with mitochondrial sequences of other insects. Insect Mol Biol. 1993;2(2):103–24. pmid:9087549
- 47. Krzywinski J, Grushko OG, Besansky NJ. Analysis of the complete mitochondrial DNA from Anopheles funestus: an improved dipteran mitochondrial genome annotation and a temporal dimension of mosquito evolution. Mol Phylogenet Evol. 2006;39(2):417–23. pmid:16473530
- 48. Stabelli OR, Lartillot N, Philippe H, Pisani D. Serine codon usage bias in deep phylogenomics: pancrustacean relationships as a case study. Syst Biol. 2012.
- 49. da Silva E Silva LH, da Silva FS, Medeiros DB de A, Cruz ACR, da Silva SP, Aragão A de O, et al. Description of the mitogenome and phylogeny of Aedes spp. (Diptera: Culicidae) from the Amazon region. Acta Trop. 2022;232:106500. pmid:35584780
- 50. Guo Y, Song Z, Luo L, Wang Q, Zhou G, Yang D, et al. Molecular evidence for new sympatric cryptic species of Aedes albopictus (Diptera: Culicidae) in China: A new threat from Aedes albopictus subgroup?. Parasites & Vectors. 2018;11:1–4.
- 51. Schmidt TL, Chung J, Honnen A-C, Weeks AR, Hoffmann AA. Population genomics of two invasive mosquitoes (Aedes aegypti and Aedes albopictus) from the Indo-Pacific. PLoS Negl Trop Dis. 2020;14(7):e0008463. pmid:32678817
- 52. Vulu F, Futami K, Sunahara T, Mampuya P, Bobanga TL, Mumba Ngoyi D, et al. Geographic expansion of the introduced Aedes albopictus and other native Aedes species in the Democratic Republic of the Congo. Parasit Vectors. 2024;17(1):35. pmid:38279140
- 53. Chaves LF, Friberg MD. Aedes albopictus and Aedes flavopictus (Diptera: Culicidae) pre-imaginal abundance patterns are associated with different environmental factors along an altitudinal gradient. Curr Res Insect Sci. 2021;1:100001. pmid:36003600
- 54. Reidenbach KR, Cook S, Bertone MA, Harbach RE, Wiegmann BM, Besansky NJ. Phylogenetic analysis and temporal diversification of mosquitoes (Diptera: Culicidae) based on nuclear genes and morphology. BMC Evol Biol. 2009;9:298. pmid:20028549