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Article

Cryptic Diversity and Demographic Expansion of Plasmodium knowlesi Malaria Vectors in Malaysia

by
Sandthya Pramasivan
1,
Van Lun Low
2,*,
Nantha Kumar Jeyaprakasam
3,
Jonathan Wee Kent Liew
4,
Romano Ngui
1,5 and
Indra Vythilingam
1,*
1
Department of Parasitology, Faculty of Medicine, Universiti Malaya, Kuala Lumpur 50603, Malaysia
2
Tropical Infectious Diseases Research & Education Centre (TIDREC), Universiti Malaya, Kuala Lumpur 50603, Malaysia
3
Biomedical Science Program, Center for Toxicology and Health Risk Studies, Faculty of Health Sciences, Universiti Kebangsaan Malaysia, Kuala Lumpur 50300, Malaysia
4
Environmental Health Institute, National Environment Agency, Singapore 569874, Singapore
5
Malaria Research Centre, Faculty of Medicine and Health Sciences, Universiti Malaysia Sarawak (UNIMAS), Kota Samarahan 94300, Sarawak, Malaysia
*
Authors to whom correspondence should be addressed.
Genes 2023, 14(7), 1369; https://doi.org/10.3390/genes14071369
Submission received: 30 May 2023 / Revised: 26 June 2023 / Accepted: 27 June 2023 / Published: 28 June 2023
(This article belongs to the Special Issue Advances in Evolutionary Genetics and Phylogenetics of Mosquito Species)
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Abstract

:
Although Malaysia is considered free of human malaria, there has been a growing number of Plasmodium knowlesi cases. This alarming trend highlighted the need for our understanding of this parasite and its associated vectors, especially considering the role of genetic diversity in the adaptation and evolution among vectors in endemic areas, which is currently a significant knowledge gap in their fundamental biology. Thus, this study aimed to investigate the genetic diversity of Anopheles balabacensis, Anopheles cracens, Anopheles introlatus, and Anopheles latens—the vectors for P. knowlesi malaria in Malaysia. Based on cytochrome c oxidase 1 (CO1) and internal transcribed spacer 2 (ITS2) markers, the genealogic networks of An. latens showed a separation of the haplotypes between Peninsular Malaysia and Malaysia Borneo, forming two distinct clusters. Additionally, the genetic distances between these clusters were high (2.3–5.2% for CO1) and (2.3–4.7% for ITS2), indicating the likely presence of two distinct species or cryptic species within An. latens. In contrast, no distinct clusters were observed in An. cracens, An. balabacensis, or An. introlatus, implying a lack of pronounced genetic differentiation among their populations. It is worth noting that there were varying levels of polymorphism observed across the different subpopulations, highlighting some levels of genetic variation within these mosquito species. Nevertheless, further analyses revealed that all four species have undergone demographic expansion, suggesting population growth and potential range expansion for these vectors in this region.

1. Introduction

Malaria remains a persistent global public health challenge, and countries in Southeast Asia have been assigned the goal of malaria elimination by 2030. This ambitious target highlights the urgency and importance of concerted efforts to combat malaria and reduce its burden in the region. Malaysia has been free of human malaria since 2018 [1], but P. knowlesi, a simian malaria parasite, is the predominant species currently occurring in the country [2]. All countries in SEA have reported the occurrence of P. knowlesi, with the exception of Timor-Leste [3]. It is crucial to consider the WHO [4] recommendation to postpone the certification of a malaria-free status for countries reporting significant P. knowlesi cases in the region. This highlights the importance of ongoing surveillance, monitoring, and control efforts to effectively address the persistence of malaria and prevent the potential reintroduction of human malaria in Malaysia and neighboring countries.
In addition to P. knowlesi, other simian malarias, such as Plasmodium cynomolgi, Plasmodium inui, and Plasmodium fieldi, have been reported in Southeast Asia [5,6,7,8,9,10,11,12,13,14]. The long-tailed (Macaca fascicularis) and pig-tailed macaques (Macaca nemestrina) are the primary hosts of these simian malaria parasites. Recent studies have shown that P. cynomolgi and P. inui are the predominant species occurring in macaques [15]. Similar findings have been observed in the simian malaria vectors [3].
Anopheles hackeri (belonging to the Leucosphyrus Group) was the first species to be incriminated as the vector of P. knowlesi in Peninsular Malaysia [16]. This was followed by the incrimination of An. latens [17,18], An. cracens [19,20], An. balabacensis [21], and An. introlatus [22], which all belong to the Leucosphyrus Group of mosquitoes, as vectors for P. knowlesi in Malaysia. With changes in landscape and deforestation, humans, macaques, and mosquitoes are now found in the same environment, thus enabling the transmission of simian malaria to humans [23].
To obtain certification as a malaria-free country, it is crucial to address the spread of simian malaria within Malaysia. However, there are currently limited data on the vectors responsible for transmitting simian malaria in the country. The Leucosphyrus Group of Anopheles, which comprises a complex of species, presents challenges in morphological identification of each species. Additionally, there is a lack of comprehensive information on the genetic studies of natural vectors of simian malaria in Malaysia. In a previous study, the genetic variation within the subpopulations of An. balabacensis in Kudat, Sabah, was examined using mitochondrial genes, revealing an expanding and growing population of An. balabacensis in Sabah. Notably, while the overall population showed low genetic diversity, the subpopulations exhibited high genetic diversity, likely due to interpopulation migration and breeding, facilitating gene flow among the subpopulations [24].
Hence, the information on genetic diversity of vectors in endemic areas is crucial for determining species taxonomy and the spatial limitations of natural populations [25]. Based on this knowledge, researchers may understand and predict the epidemiology, distribution, and transmission dynamics of vector-borne diseases [25]. As a result, studies on the genetic diversity and population structure of malaria vectors are critical for successfully executing vector control programs against malaria in the country.
Thus, this study aimed to analyze the population genetic structure and genetic diversity of the four important malaria vectors, An. balabacensis, An. cracens, An. introlatus, and An. latens, using the mitochondrial and ribosomal sequences for the first time in Malaysia.

2. Materials and Methods

2.1. Study Location

Anopheles mosquitoes were collected from multiple states across Malaysia, including Negeri Sembilan, Johor, Kelantan, Pahang, Perak, and Sarawak. This sampling strategy ensured that the study covered the north, south, east, and west regions of the country. The selection of survey locations was based on the Ministry of Health (MoH), Malaysia’s data on P. knowlesi malaria cases, allowing for a comprehensive assessment of vector populations in areas with known incidences of the disease (Figure 1).

2.2. Sample Collection

Mosquitoes were collected using bare-leg catch (BLC), human-baited trap, Mosquito Magnet, and CDC light trap [26] during the sampling period from June 2019 until January 2021 between 1800 and 0000 h. The sample collection process was mainly through the BLC method, whereas other sampling methods depended on the specific location and the workforce available for the study. Detailed information on the samples from the different sampling locations is illustrated in Table 1.

2.3. DNA Extraction and Polymerase Chain Reaction

DNA was extracted from the mosquitoes’ legs using InstaGene Matrix (Bio-Rad, Hercules, CA, USA) according to the manufacturers’ protocol. The extracted DNA was kept at −20 °C until required. All Anopheles mosquitoes from the Leucosphyrus Group obtained in this study, including some archived samples, were further molecularly characterised using the internal transcribed spacer 2 (ITS2) region and mitochondrial cytochrome c oxidase subunit 1(CO1) gene. The ITS2 was amplified by ITS2A and ITS2B primers [27], with the PCR conditions as follows: denaturation at 95 °C for 2 min; 35 cycles of amplification at 95 °C for 30 s; annealing step at 51 °C for 30 s, with elongation step at 72 °C for 1 min; followed by final elongation step of 10 min at 72 °C. LCO1490 and HCO2198 primers [28] were used to amplify the CO1 gene. The PCR conditions were as follows: denaturation at 95 °C for 3 min; 35 cycles of amplification at 95 °C for 1 min; annealing step at 50 °C for 1 min, with elongation step at 72 °C for 1 min; followed by final elongation step of 10 min at 72 °C and held at a temperature of 4 °C. Each reaction mixture of 25 μL contained 5 μL DNA template, 0.5 μM primers, respectively, 0.2 mM dNTP, 3 mM MgCl2, 1 × GoTaq® Flexi Buffer, and 1.0 U of GoTaq® DNA polymerase (Promega Corporation, Madison, WI, USA). This master mix was used for both primer sets. Amplicons were subjected to electrophoresis on 1.5% agarose gels. The amplified product was purified from the gel and outsourced for Sanger sequencing (Apical Scientific Sdn. Bhd., Malaysia). Sequences of each species were performed using the Basic Local Alignment Search Tool (BLAST) (http://blast.ncbi.nlm.nih.gov/Blast.cgi, accessed on 12 February 2021) for similarity searches. A species was confirmed by ≥98% identity and query coverage to the deposited sequence.

2.4. Data Analyses for Genetic Studies

The study included sequences of mosquitoes collected from Peninsular Malaysia and Sarawak, while additional sequences from Sabah and Selangor were retrieved from the NCBI GenBank, providing a comprehensive representation of mosquito populations across different regions of Malaysia. CO1, ITS2, and combined sequences of each species were aligned using BioEdit (Version 7.2) [29]. Haplotype networks for An. balabacensis, An. cracens, An. introlatus, and An. latens, based on their polymorphic sites, were constructed by using the median-joining method in NETWORK version 5.0.0.1 software (Fluxus Technology LTD, Suffolk, UK). The number of haplotypes in the subpopulations, haplotype diversity [30], and nucleotide diversity [31] were also estimated using DnaSP 5.0 software. Genetic distances among species/populations were calculated using MEGA 11 software [32].
Pairwise genetic differentiation (FST) and gene flow (Nm) values between the subpopulations of each species were tested for significance. DnaSP 5.0 software was also used in estimating gene flow using 1000 permutations [33]. The levels of genetic differentiation can be categorized as FST > 0.25 (great differentiation), 0.05 to 0.25 (moderate differentiation), and FST < 0.05 (negligible differentiation) [34]. The levels of gene flow can be categorized as Nm > 1 (high gene flow), 0.25 to 0.99 (intermediate gene flow), and Nm < 0.25 (low gene flow) [35]. To analyse the randomness of DNA sequence evolution, a neutrality test was performed by using Tajima’s D [36] and Fu’s Fs [37] with 1000 simulations. Mismatch analysis, Harpending’s raggedness index (Rag) [38], and the R2 statistic of Ramos-Onsins and Rozas [39] were used to investigate demographic expansion.

3. Results

3.1. Genetic Diversity Indices

An. introlatus had a greater number of haplotypes in the combined sequences (n = 25), followed by An. latens (n = 15) and An. cracens (n = 7), and the least was An. balabacensis (n = 5) (Table 1). The An. introlatus subpopulations from Kongsi Balak, Johor (Hd = 0.899 ± 0.031, π = 0.00273 ± 0.00045), An. latens from Rumah Sewa Panto, Sarawak (Hd = 1.000 ± 0.177, π = 0.01410 ± 0.00642), An. cracens from Kem Sri Gading, Pahang (Hd = 0.791 ± 0.044, p = 0.00093 ± 0.00009), and An. balabacensis from Simpang Utong, Sabah (Hd = 1.000 ± 0.27, p = 0.00168 ± 0.00059) had the highest haplotype and nucleotide diversities.
An. cracens had the least number of haplotypes in ITS2 (n = 15) and CO1 (n = 4) compared with the others. The overall subpopulation of ITS2 (Hd = 0.611 ± 0.067) showed lower haplotype diversity than CO1 (Hd = 0.702 ± 0.031). The summaries of the CO1 and ITS2 diversities are shown in Supplementary Tables S1 and S2, respectively. However, ITS2 (p = 0.00165 ± 0.00035) showed higher nucleotide diversity than did CO1 (p = 0.00146 ± 0.00013) for the overall population.
A greater number of haplotypes were found in the ITS2 (n = 21) and CO1 (n = 16) sequences of An. introlatus. The highest haplotype diversity was noticed in Sg. Sendat, Selangor (Hd = 0.833 ± 0.222), while the highest nucleotide diversity was in Kem Microwave, Johor (p = 0.00563 ± 0.00085) for the CO1 analysis. Among the subpopulations in Hulu Kalong and Sg. Sendat from Selangor, the ITS2 sequences depicted the highest haplotype diversity (Hd = 1.000 ± 0.126). Similarly, Hulu Kalong had the highest nucleotide diversity (p = 0.00513 ± 0.00124).
Compared with ITS2 (n = 16), CO1 showed a smaller number of haplotypes, n = 14 for An. latens. Based on CO1, the Rumah Sewa Panto, Sarawak, subpopulation had the highest haplotype and nucleotide diversities (Hd = 1.000 ± 0.177, p = 0.01997 ± 0.00871). In addition, the ITS2 subpopulation of Rumah Sewa Panto, Sarawak, indicated high nucleotide diversity, p = 0.00674 ± 0.00358, but high haplotype diversity was observed in Danum Valley Field Centre, Sabah (Hd = 0.956 ± 0.033).
A total of 16 and 10 haplotypes were observed in the CO1 and ITS2 sequences, respectively, for An. balabacensis. Based on CO1, the highest haplotype diversity was observed in Simpang Utong, Sarawak (Hd = 1.000 ± 0.272), and the highest nucleotide diversity was observed in Lipasu Lama, Sabah (p = 0.00200 ± 0.00094). The highest haplotype and nucleotide diversities in ITS2 were recorded in Limbuak Laut, Sabah (Hd = 0.939 ± 0.058, p = 0.00395 ± 0.00080).

3.2. Demographic Analyses

The low values of the raggedness index and R2 statistic from the mismatch distribution tests and the results of the neutrality test indicated that all the vector species studied were expanding. This expansion trend was further supported by the unimodal shape of the graph observed in at least one gene dataset of the mismatch distribution analysis. These findings collectively suggest that the vector populations are undergoing growth and expansion (Figure 2). Despite a multimodal shape being observed in An. latens due to the presence of two distinct lineages, a separate analysis was conducted for each lineage, and a unimodal shape was also observed (unpublished data The mismatch distribution graphs for CO1 and ITS2 of An. introlatus, An. latens, An. cracens, and An. balabacensis are shown in Supplementary Figure S1.

3.3. Haplotype Network

An. introlatus from Johor had the highest number of haplotypes for CO1, ITS2, and the combined dataset (red colour). A higher number of haplotypes (n = 25) was observed in the combined network, with the majority originating from Johor. An. latens from Peninsular Malaysia were clustered distantly from Malaysia Borneo in all three CO1, ITS2, and combined network analyses. H4 in An. cracens held all the populations from Perlis, and the other three haplotypes included the Pahang population for CO1. Only H1 (the predominant haplotype) shared populations from Perlis and Pahang for ITS2. The haplotypes from the combined network were connected to each other, as they were from the same population (Pahang) of An. cracens. The “star-like” shape was observed across all four species. Overall, the combined network for An. balabacensis indicated fewer haplotypes (n = 5) compared with CO1 and ITS2 (Figure 3).

3.4. Genetic Differentiation (FST) and Gene Flow (Nm)

Overall, in the 10 subpopulations, the highest genetic differentiation was observed between Kg. Sg Dara, Perak, and Hutan Lenggor, Johor, for the concatenated sequences of CO1 and ITS2 in An. introlatus (Table 2). Two out of the three subpopulations exhibited high levels of genetic differentiation, and moderate gene flow was detected between most of the subpopulation pairs in An. latens (Table 3). Intermediate genetic differentiation and correspondingly high gene flow were observed between the two subpopulations of An. cracens (Table 4). In contrast, low levels of genetic differentiation and gene flow were found between the Kem Kayu Merarap, Sarawak, and Simpang Utong, Sarawak, subpopulations in An. balabacensis (Table 5).

4. Discussion

This study represents the first attempt to investigate four simian malaria vectors (An. balabacensis, An. cracens, An. introlatus, and An. latens) collected from various sites in Malaysia. Based on the combined sequences of An. introlatus, the samples from Hulu Kalong and Kongsi Balak had the highest genetic diversities among the other subpopulations, suggesting greater genetic variation and potential population differentiation in these specific locations. The population from Perak had zero diversity for all the sequences analysed. This is likely linked to the lack of variation within the population in Perak [40], sampling errors [24], or the low number of samples (n = 5) within the same area. The presence of the same haplotypes in the different subpopulations, such as in CO1-H2, ITS2-H1, and the combined sequences-H2, creates the possibility of inter-breeding and migration among the An. introlatus subpopulations [24]. Hence, a different number of haplotypes and unique haplotype network structures for each gene can be observed.
The Anopheles latens sequences from West and East Malaysia were examined in this study. High haplotype and nucleotide diversities were observed in the subpopulations of East Malaysia (Sabah and Sarawak) for CO1, ITS2, and the combined sequences. This hypothesis needs further attention because low genetic diversity is the typical characteristic of insects in island populations [41,42,43]. The haplotypes of An. latens were separated into two clusters for all three haplotype networks. The haplotype clusters contained sequences from Peninsular Malaysia separated from sequences from Malaysia Borneo. Consequently, it is unknown whether the behaviour and the capability of spreading the simian malaria parasites of these two clusters of An. latens mosquitoes are similar or different.
Additionally, this study revealed the presence of the two genetically distinct An. latens clusters based on the CO1 and ITS2 sequences. Nonetheless, defining a species in Anopheles is challenging, even if it is well studied. Thus, multiple genes and concatenated markers were used to improve the accuracy of the assessments of the genetic population structure [44,45]. It is known that CO1 is commonly used for genetic studies of malaria vectors [46,47,48,49], and ITS2 is the well-known molecular marker for species identifications [50]. Thus, based on the results obtained from these gene markers, it is plausible to consider the existence of two different types of An. latens in Malaysia.
The genetic distances between the two clades of An. latens from Peninsular Malaysia and Malaysia Borneo were relatively high, ranging from 2.3% to 5.2% for CO1 and from 2.3% to 4.7% for ITS2. Notably, a cutoff point of 3% is often used as a threshold for species boundaries in insects. Given that the genetic distances observed between the An. latens populations from these different geographical regions surpassed this threshold, it strongly suggests that they may represent two distinct species. A detailed morphological examination is also warranted to confirm its species status.
The findings demonstrated that geographic distance might have a major effect on the genetic structure of An. latens from the two different geographical regions. The South China Sea significantly divides East and West Malaysia, and this may be a factor leading to the intra-specific genetic discontinuities [51,52]. Therefore, the South China Sea is likely a barrier to gene flow between An. latens from Peninsular Malaysia and Borneo. This is further supported by the high levels of genetic differentiation and moderate gene flow in this study.
Overall, the high haplotype diversity observed in An. cracens in Pahang indicates its population growth, likely resulting from the accumulation of new mutations over time, with the emergence of new haplotypes within the population. Differences were observed between the CO1 and ITS2 markers, which can be attributed to the selection of different molecular markers. Each marker may have distinct mutation or evolutionary rates, varying selection pressures, and different gene constraints [53,54]. Nevertheless, this diversity provided valuable insights into the genetic variation, population structure, and evolutionary processes of the mosquito populations. High gene flow was observed between the Kem Sri Gading and Sg. Ular subpopulation pairs from Pahang, despite being collected from different sites. This can be attributed to the absence of significant geographical barriers between these locations. Furthermore, moderate and low levels of genetic differentiation were observed between the subpopulation pairs. The Sg. Ular subpopulation, located within a durian plantation, and the Kem Sri Gading subpopulation, designated as a reserved forest for camping, tracking, and cycling activities, exhibited distinct ecological characteristics. The association between the geographic distance and the anopheline population genetic structure likely differed by species, most likely due to variations in breeding sites, breeding patterns, and behaviour [55]. The gene flow or genetic differentiation of An. cracens in the study were not dependent on the geographical distances. Gene flow among the vectors of malaria due to the lack of geographical distance and barriers was observed in several studies [55,56,57,58,59].
The samples from different study sites could belong to the same, single continuous population because of the low genetic differentiation detected among the subpopulation pairs in both genes for An. balabacensis. Nevertheless, low levels of gene flow were also observed from the overall subpopulations in the combined sequences, yet high gene flow was seen in the COI and ITS2 analyses. Although the sampling distributions varied, the ecological habit is relatively similar in Sabah and Sarawak [60]. Thus, the gene flow occurred easily without significant physical barriers.
The “star-like” network observed in all four vectors suggests population expansion [61,62]. Furthermore, the unimodal shape and low values of the raggedness index and R2 statistic from the mismatch distribution tests, along with the negative values from the neutrality tests, further support the population expansion of An. balabacensis, An. introlatus, An. latens, and An. cracens in Malaysia. Likewise, evidence of demographic expansion has also been reported in other insects, such as dragon flies, black flies, and buffalo flies, in Southeast Asia [63,64,65].

5. Conclusions

A deeper understanding of the genetic diversity of local vectors could provide valuable information for epidemiological surveillance and malaria vector control strategies. The presence of the different lineages in the An. latens populations could be a topic of interest for future studies, as it would allow for the identification of which genotypes are more likely to be exposed to simian malaria infection in the wild. Furthermore, in this study, the collection sites covered most of the P. knowlesi malaria endemic regions in Malaysia, yet future research should conduct extensive sample collection in a wider distribution area to obtain a complete overview of the genetic structure of the vectors. Thus, in light of the elimination of malaria, it is timely for Southeast Asian nations to commit a concerted effort to study the vectors and to develop vector control strategies to prevent future outbreaks.

Supplementary Materials

The following supporting information can be downloaded at https://www.mdpi.com/article/10.3390/genes14071369/s1, Table S1: Summary of CO1 diversity and neutrality test in An. introlatus, An. latens, An. cracens, and An. balabacensis; Table S2: Summary of ITS2 diversity and neutrality test in An. introlatus, An. latens, An. cracens, and An. balabacensis; Figure S1: Graphs of the mismatch distribution analysis for (a) An. introlatus, (b) An. latens, (c) An. cracens, and (d) An. balabacensis based on combined sequences of CO1 and ITS2.

Author Contributions

Conceptualization, I.V. and V.L.L.; methodology, S.P., V.L.L. and I.V.; software, V.L.L.; validation, I.V. and V.L.L.; formal analysis, S.P.; investigation, S.P.; resources, S.P., J.W.K.L. and N.K.J.; data curation, S.P. and J.W.K.L.; visualization, I.V.; supervision, V.L.L.; project administration, S.P.; funding acquisition, I.V.; writing—original draft preparation, S.P.; writing—review and editing, S.P., I.V., J.W.K.L., R.N., V.L.L. and N.K.J. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Ministry of Higher Education of Malaysia Long-Term Research Grant Scheme (LRGS), grant no. LRGS 1/2018/UM/01/1/3.

Institutional Review Board Statement

This study was approved by Medical Research and Ethics Committee, Ministry of Health Malaysia (NMRR-19-962-47606).

Informed Consent Statement

Informed consent was obtained from all volunteers collecting mosquitoes.

Data Availability Statement

All data are available within the manuscript.

Acknowledgments

We thank the staff and field teams of the various district health offices for their assistance in identifying the sampling sites and in sample collection. We thank Phang Wei Kit, Naqib Rafieqin, Tan Jia Hui, Ng Yee Ling, Shahhaziq, and Lee Phone Youth from the Department of Parasitology, University of Malaya, for their assistance in the field work.

Conflicts of Interest

The authors declare no conflict of interest.

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Genes 14 01369 g001 550
Figure 1. Anopheles mosquito collections in Malaysia encompassed various states, spanning both Peninsular Malaysia and Malaysia Borneo.
Figure 1. Anopheles mosquito collections in Malaysia encompassed various states, spanning both Peninsular Malaysia and Malaysia Borneo.
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Genes 14 01369 g002 550
Figure 2. Graphs of the mismatch distribution analysis for (a) An. introlatus, (b) An. latens, (c) An. cracens, and (d) An. balabacensis based on combined sequences of CO1Th and ITS2. A multimodal shape was observed in An. latens due to the presence of two distinct lineages.
Figure 2. Graphs of the mismatch distribution analysis for (a) An. introlatus, (b) An. latens, (c) An. cracens, and (d) An. balabacensis based on combined sequences of CO1Th and ITS2. A multimodal shape was observed in An. latens due to the presence of two distinct lineages.
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Genes 14 01369 g003 550
Figure 3. Median-joining networks of (a) An. introlatus, (b) An. latens, (c) An. cracens, and (d) An. balabacensis.
Figure 3. Median-joining networks of (a) An. introlatus, (b) An. latens, (c) An. cracens, and (d) An. balabacensis.
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Table
Table 1. Summary of concatenated sequences of CO1 and ITS2 diversity and neutrality tests in An. introlatus, An. latens, An. cracens, and An. balabacensis. Values marked with an asterisk indicate significance: * p < 0.05.
Table 1. Summary of concatenated sequences of CO1 and ITS2 diversity and neutrality tests in An. introlatus, An. latens, An. cracens, and An. balabacensis. Values marked with an asterisk indicate significance: * p < 0.05.
SpeciesSubpopulationNo. of Haplotypes, H/SamplesNucleotide Diversity, πHaplotype Diversity, HdNeutrality Test
Tajima’s DFu’s Fs
An. introlatusJOHOR
Gunung Panti3/70.00205 ± 0.002060.524 ± 0.209−1.610 *2.091 *
Kg. Seri Delima1/1----
Kem Microwave12/440.00266 ± 0.000380.810 ± 0.046−0.645−1.084
Hutan Lenggor9/440.00129 ± 0.000360.673 ± 0.070−1.910 *−2.702
Kongsi Balak14/350.00273 ± 0.000450.899 ± 0.031−0.429−3.199
Kg. OA Punjut1/1----
Kg. OA Berasau1/1----
Total230.00213 ± 0.000240.787 ± 0.033−1.170−7.773
KELANTAN
Kg. Lalang2/60.00072 ± 0.000320.600 ± 0.215−1.233−0.189 *
Kg. Dusun Durian1/1----
Kg. Lebur Jaya1/1----
Total20.00092 ± 0.000240.714 ± 0.1230.4580.671
PAHANG
Kem Sri Gading4/100.00127 ± 0.000180.711 ± 0.1170.9880.334
Total40.00127 ± 0.000180.711 ± 0.1170.9880.334
PERAK
Kg. Sg. Dara1/50.00000 ± 0.000000.000 ± 0.0000.0000.000
Kg. Draco1/30.00000 ± 0.000000.000 ± 0.000--
Total10.00000 ± 0.000000.000 ± 0.0000.0000.000
NEGERI SEMBILAN
Kebun Durian Tekir1/20.00000 ± 0.000000.000 ± 0.000--
Hutan Lenggeng2/50.00029 ± 0.000170.400 ± 0.237−0.7720.090
Total20.00020 ± 0.000140.286 ± 0.196−1.006−0.095
Overall Total250.00199 ± 0.000210.823 ± 0.022−1.320−9.677
An. latensJOHOR
Gunung Panti5/170.00267 ± 0.000520.824 ± 0.0640.676−0.223
Total50.00267 ± 0.000520.824 ± 0.0640.676−0.223
KELANTAN
Kg. Lalang7/100.00255 ± 0.000410.933 ± 0.0621.758−2.029
Total70.00255 ± 0.000410.933 ± 0.0621.758−2.029
SARAWAK
Taman Ixora1/1----
Kg. Sawang1/1----
Rumah Sewa Panto4/40.01410 ± 0.006421.000 ± 0.177−0.5660.903
Total50.01037 ± 0.005100.933 ± 0.122−1.1771.138
Overall Total150.01419 ± 0.003440.902 ± 0.0360.1952.674
An. cracensPAHANG
Kem Sri Gading7/370.00093 ± 0.000090.791 ± 0.0440.800−1.573
Sg. Ular2/80.00039 ± 0.000090.536 ± 0.1231.1670.866
Overall Total70.00085 ± 0.000080.764 ± 0.0400.632−1.600
An. balabacensisSARAWAK
Kem Kayu Merarap4/210.00065 ± 0.000180.557 ± 0.092−0.848−0.521
Simpang Utong3/30.00168 ± 0.000591.000 ± 0.27--
Kebun Ldg Sawit Jelapang1/20.00000 ± 0.000000.000 ± 0.000--
Overall Total50.00074 ± 0.000170.609 ± 0.068−0.917−1.106
Table
Table 2. Genetic differentiation (FST) and gene flow (Nm) between subpopulations of An. introlatus based on concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST. Values marked with an asterisk indicate that the genetic distances between two subpopulations are significant: * p < 0.05, ** p < 0.01, *** p < 0.001.
Table 2. Genetic differentiation (FST) and gene flow (Nm) between subpopulations of An. introlatus based on concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST. Values marked with an asterisk indicate that the genetic distances between two subpopulations are significant: * p < 0.05, ** p < 0.01, *** p < 0.001.
Subpopulation 12345678910
Gunung Panti1-−6.680−9.350−10.3500.7101.9500.3600.2900.3700.410
Kem Microwave2−0.039-3.67012.7500.7102.2800.3601.6201.4900.400
Hutan Lenggor3−0.0270.064 *-5.4700.6101.1300.2401.3801.3500.300
Kongsi Balak4−0.0250.019 *0.044 *-1.2101.5500.6101.7801.5900.670
Kg. Lalang50.260 *0.260 *0.289 **0.171-0.6802.7503.7503.6002.450
Kem Sri Gading60.114 *0.099 *0.181 ***0.139 *0.269-0.2400.9801.1000.300
Kg. Sg Dara70.412 *0.412 ***0.508 ***0.2910.0490.506-≠≠2.000
Kg. Draco80.464 *0.134 **0.153 **0.1230.0490.203≠-≠2.670
Kebun Durian Tekir90.403 *0.144 *0.157 ***0.1360.0640.186≠≠-3.500
Hutan Lenggeng100.380 *0.387 ***0.458 *0.2710.0330.4560.1110.0080.031-
≠ This sign indicates polymorphic sites were not observed in the selected subpopulation pairs.
Table
Table 3. Genetic differentiation (FST) and gene flow (Nm) among the subpopulations of An. latens based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST. Values marked with an asterisk indicate that the genetic distances between the two subpopulations are significant: * p < 0.05.
Table 3. Genetic differentiation (FST) and gene flow (Nm) among the subpopulations of An. latens based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST. Values marked with an asterisk indicate that the genetic distances between the two subpopulations are significant: * p < 0.05.
Subpopulation 123
Gunung Panti1-4.9800.070
Kg. Lalang20.048-0.070
Rumah Sewa Panto30.785 *0.780-
Table
Table 4. Genetic differentiation (FST) and gene flow (Nm) between the subpopulations of An. cracens based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST.
Table 4. Genetic differentiation (FST) and gene flow (Nm) between the subpopulations of An. cracens based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST.
Subpopulation 12
Sg. Ular1-3.150
Kem Sri Gading20.074-
Table
Table 5. Genetic differentiation (FST) and gene flow (Nm) between the subpopulations of An. balabacensis based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST.
Table 5. Genetic differentiation (FST) and gene flow (Nm) between the subpopulations of An. balabacensis based on the concatenated sequences of CO1 and ITS2. Values above the diagonal are for Nm, while values below the diagonal are for FST.
Subpopulation 123
Kem Kayu Merarap1-−2.2800.260
Simpang Utong2−0.123-0.750
Kebun Ldg Sawit Jelapang30.4880.250-
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Pramasivan, S.; Low, V.L.; Jeyaprakasam, N.K.; Liew, J.W.K.; Ngui, R.; Vythilingam, I. Cryptic Diversity and Demographic Expansion of Plasmodium knowlesi Malaria Vectors in Malaysia. Genes 2023, 14, 1369. https://doi.org/10.3390/genes14071369

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Pramasivan S, Low VL, Jeyaprakasam NK, Liew JWK, Ngui R, Vythilingam I. Cryptic Diversity and Demographic Expansion of Plasmodium knowlesi Malaria Vectors in Malaysia. Genes. 2023; 14(7):1369. https://doi.org/10.3390/genes14071369

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Pramasivan, Sandthya, Van Lun Low, Nantha Kumar Jeyaprakasam, Jonathan Wee Kent Liew, Romano Ngui, and Indra Vythilingam. 2023. "Cryptic Diversity and Demographic Expansion of Plasmodium knowlesi Malaria Vectors in Malaysia" Genes 14, no. 7: 1369. https://doi.org/10.3390/genes14071369

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