AJTMH Transactions of the Royal Society of Tropical Medicine and Hygiene
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Am. J. Trop. Med. Hyg., 77(2), 2007, pp. 310-315
Copyright © 2007 by The American Society of Tropical Medicine and Hygiene

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Analysis of the Population Genetic Structure of the Malaria Vector Anopheles sinensis in South Korea Based on Mitochondrial Sequences

Jongwoo Jung, Yunjung Jung, Gi-Sik Min, AND Won Kim*
School of Biological Sciences, Seoul National University, Seoul, Republic of Korea; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea; Department of Biological Sciences, Inha University, Incheon, Republic of Korea; School of Biological Sciences, Seoul National University, Seoul, Republic of Korea


ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The population genetics of Anopheles sinensis, a major malaria vector in South Korea, was studied based on the nucleotide sequences of a 238-bp variable region of the mitochondrial control region. Three features of genetic variance were observed. First, the Taebaek and Sobaek mountain ranges may function as genetic barriers between the Northern Group (NG) and the Southern Group (SG). These mountain ranges are associated with the subdivision of the population, and significant and unique population differentiation was observed in the examined area. Second, the genetic cohesiveness observed within each group may have been caused by a recent expansion in the population rather than recurrent gene flow. Third, a marked dissimilarity in the genetic diversity between the two groups may also have resulted from several factors that caused a difference in the effective population sizes.


INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Various levels of population subdivision of the anopheline mosquito species have been observed from nearly panmictic across a wide geographic range to highly divergent within a short distance. A high rate of recurrent gene flow and/or recency of population expansion leave populations of some anopheline species hardly differentiated.1–3 However, other species are composed of highly structured populations that are mainly caused by genetic barriers such as mountain chains or arid valleys.4–6 Because this suggests valuable information about, for instance, the degree of dispersal of insecticide-resistant individuals or genetically modified mosquitoes, population genetic data of vector species could enable us to map out effective strategies for controlling malaria.7

Despite its malaria vectorial capacity, Anopheles sinensis has not been a focus of concern for population geneticists because this species does not show an active anthrophilic preference.8 However, population genetic information of this species, at least in South Korea where this species has become a major malaria vector,9 is needed in controlling malaria for the several hundred cases of this disease occurring every year in this country despite various efforts such as quarantine and treatment with insecticides.10 Located on a peninsula, South Korean populations of An. sinensis may be hardly affected by the gene flow from the continent or nearby islands. Thus, populations in South Korea would be suitable for studying genetic diversity influenced mostly by population substructure within this region with the help of mitochondrial DNA sequences that would be useful to detect subtle genetic divergence because of a quarter of its effective population size compared with that of nuclear DNA. In this study, based on the sequences of the mitochondrial control region, we attempted to elucidate the genetic properties and subdivisions of the South Korean population of An. sinensis.


MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Sampling and DNA extraction. We collected 290 An. sinensis individuals from 19 locations in South Korea (Figure 1Go; Table 1Go) by using a CDC Miniature Light Trap (John W. Hock Company, Gainesville, FL). The collected samples were preserved on site using dry ice, and their morphologic characters were studied under a stereomicroscope in the laboratory. DNA was extracted from entire individuals or parts of their bodies by following a standard phenol extraction protocol.11


Figure 1
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  		    FIGURE 1. Locations where the individuals were collected are identified on a map of Korea. Populations belonging to the NG and SG are represented as {blacksquare} and{square}, respectively. The solid line indicates the Taebaek and Sobaek mountain ranges.

 

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TABLE 1
Geographic information, indices of genetic diversity, and theta estimates of each population
 
Sequence analysis of the mitochondrial control region. To amplify the 238-bp variable region of the mitochondrial control region, primers (U415, 5'-CCTCCTAATAATTTTC-CCC-3'; L672, 5'-GGGTGATATTAATTATAGACC-3') were designed based on the complete sequences (GenBank accession numbers, DQ466091–DQ466107) that were amplified and sequenced using the primers DMP5 and DM57.12 Polymerase chain reaction (PCR) mixtures were made up of 1x Taq polymerase buffer, a 1-mmol/L dNTP mix that was AT rich (80% AT content), 2.5 mmol/L MgCl2, 0.5 µmol/L of each primer, 2.5–250 pg total DNA, and 0.04 U/µL of Taq polymerase (Promega, Madison, WI). PCR was performed using the GeneAmp PCR system 9700 (Applied Biosystems, Foster City, CA) under the following cycle conditions: initial denaturation at 94°C for 3 minutes, followed by 30 cycles at 94°C for 30 seconds, 45°C for 50 seconds, and 72°C for 50 seconds, and a final elongation at 72°C for 7 minutes. The amplified products were purified from the PCR mixtures using a QIAquick PCR purification kit (Qiagen, Valencia, CA). Subsequently, the PCR products were sequenced using both the amplifying primers and the Big Dye terminator sequencing kit (Applied Biosystems), according to the manufacturer’s instructions. After purification, the reaction products were analyzed on an ABI PRISM Genetic Analyzer 3100 (Applied Biosystems). Bidirectional sequences were aligned and visually examined using Sequence Navigator v1.0.1 (Applied Biosystems). The sequences were aligned with ClustalX13 and were exported to the NEXUS and PHYLIP formats for data analyses.

Data analyses. DnaSP 4.1014 was used to calculate the frequency of each haplotype, haplotype diversity,15 nucleotide diversity,16 and theta ({theta}) values based on the number of polymorphic sites (S) and the mean number of pairwise differences ({pi}), respectively. Using TCS 1.18,17 a 95% set of plausible haplotype networks and the outgroup probability of the haplotypes were computed based on statistical parsimony. To measure the genetic distance between populations, pairwise {gamma}ST and {gamma}ST18 were calculated using DnaSP 4.10.14 Subsequently, the distance matrices of pairwise {gamma}ST and {delta}ST were used to determine a relationship among populations by using the neighbor-joining (NJ) method as implemented by the MEGA 3.119 software. To evaluate the significance of differentiation between the two populations based on pairwise FST, the exact test20 was performed using Arlequin 3.0121 with a Markov chain length of 10,000 and 1,000 burn-in steps. Using the same software, analysis of molecular variance (AMOVA)22 was conducted to measure the extent to which genetic variance is assigned to the hierarchical level of population organization. The statistical significance for AMOVA was evaluated using > 10,000 permutations. DnaSP 4.1014 was used to evaluate the significance of differentiation among the populations within a group, between the groups, or among all the populations using the {chi}2 test, and gene flow estimates among the populations were calculated by the method described by Hudson and others.23 Using Arlequin 3.01,21 the Mantel test24 was performed to test any significant relationship between geographical distance and population genetic distance (linearized FST).25 Using DnaSP 4.10,14 population demographic parameters such as tau ({tau}) and theta initial ({theta}0) were estimated assuming theta final ({theta}1) as infinite,26 and the raggedness index27 was used to show the unimodality of mismatch distribution. The results of the neutrality tests of Tajima28 and Fu29 were calculated using Arlequin 3.01.21 The significance of the D and Fs values of Tajima and Fu, respectively, was evaluated by comparison with randomly generated values based on the observed {theta}(S) with 10,000 repeats.


RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Haplotypes and genetic diversity. From the sequence analysis, 60 haplotypes were identified among the 290 An. sinensis individuals of Korea (GenBank accession numbers: DQ445543–DQ445602), and their average guanine and cytosine (GC) content was observed to be 4.45%. The haplotype diversity, i.e., the probability that two randomly selected haplotypes are present in the sample, was 0.8871 ± 0.0122. There were 41 polymorphic sites, and no gaps were present. The nucleotide diversity per site ({pi}) was 0.010317 ± 0.006194 (no gamma correction) based on the mean number of pairwise differences (2.455507 ± 1.332656). The number of individuals containing the seven haplotypes that exhibited the highest frequency was 206, and this accounted for 71% of the total (Figure 2Go). Although the most frequently occurring haplotype was BY02, CC05 represented the highest outgroup weight probability (0.15). Forty haplotypes (67% of the total number) occurred as private alleles and were present in a single individual. The genetic diversity indices for each population are presented in Table 1Go. Of the 19 locations, the Nakan and Guryongpo populations displayed the highest gene and nucleotide diversity, respectively. Furthermore, the highest {theta}(S) and {theta}({pi}) values were recorded in the Jain and Guryongpo populations, respectively. The Taean population displayed the lowest values for all the indices of genetic diversity and the lowest theta estimates (Table 1Go).


Figure 2
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  		    FIGURE 2. The 95% set of plausible haplotype networks as calculated by TCS 1.18.17 Each circle represents a haplotype, and the numbers indicate haplotype identification. The size of the circles denotes the number of individuals that contain that haplotype, and the shaded portions of the pies indicate the group containing the particular haplotype. Black and white colors of pies represent the NG and SG, respectively. •, missing haplotypes. {dagger}CC05, haplotypes with the highest outgroup probability; {ddagger}BY02, haplotype with the highest frequency in South Korea.

 
Genetic structure of An. sinensis in South Korea. Based on results of the pairwise FST analysis (Table 2Go) and NJ analysis of pairwise {gamma}ST and {delta}ST, the Korean populations of An. sinensis were found to be separated into two groups (Figure 3Go). The Northern Group (NG) was made up of 13 populations that were present in the northern region of South Korea, and the other 6 populations belonged to the Southern Group (SG) (Figure 1Go). AMOVA revealed that most of the genetic variance lay within the populations, which may have been because of the existence of several private alleles; the 8.78% significant variance observed between the two groups further substantiated the division of the South Korean populations into two groups and also suggested that genetic variance was not structured within the groups (Table 3Go). The Mantel test supported the AMOVA results and showed that there was a nonrandom association (P < 0.01) between the genetic differences (linearized FSTs) and geographic distances among all the 19 populations, but no correlation was observed in each group (PNG = 0.334 and PSG = 0.329). Significant genetic differentiation among populations was not observed within either group; however, according to the results of the {chi}2 test to detect differentiation, it was observed between the two groups (Table 4Go).


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TABLE 2
Pairwise FST values among populations of An. sinensis in South Korea
 

Figure 3
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  		    FIGURE 3. Population tree constructed using NJ analysis of pairwise {gamma}ST A, and {delta}ST B.

 

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TABLE 3
AMOVA of geographic variation among the An. sinensis individuals collected from Korea
 

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TABLE 4
Comparison of gene flow estimates, genetic diversity, and theta estimates in the SG and NG of the South Korean populations of An. sinensis
 
Comparison of the two South Korean groups. All estimates of genetic diversity and theta calculated for the SG were higher than those calculated for the NG; this was observed not only when comparing the populations (Table 1Go) but also when comparing the average values of the two groups (Table 4Go). The haplotype composition differed between the two groups. The SG contained a considerable number of private alleles, i.e., 22 of the 40 private alleles found in South Korea, considering that the number of individuals in the SG was nearly one half that in the NG. No remarkable relationship was observed between geographic distribution and haplotype lineage in the haplotype network (Figure 2Go). Most of the high-frequency haplotypes were observed in both the groups. The NG contained all the individuals carrying BY02, the most frequent haplotype, except one individual belonging to the Andong population present in the SG (Figure 2Go). Gene flow estimates were high among populations within each group. However, populations belonging to the SG were slightly more differentiated than those belonging to the NG (Table 4Go). According to the results of the mismatch analysis and neutrality tests, both groups have recently experienced expansion in population size (Figure 4Go; Table 4Go). Judging from the smaller {theta}0 value and larger {tau} value of the SG, it may have undergone expansion earlier, with an initial population size that was smaller than that of the NG (Table 4Go).


Figure 4
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  		    FIGURE 4. Distribution of the pairwise differences (dotted line) in all the individuals of the NG A, and SG B, in South Korea based on the 238-bp variable sequences in the mitochondrial control region. The expected values (solid line) were estimated according to the population expansion model.

 

DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Anopheline mosquitoes of Africa usually form relatively large geographic demes either because of the extensive gene flow (populations are genetically differentiated in an isolation-by-distance manner) or because of recent range expansion from relatively large, stable populations.1,2,30 The An. sinensis population in South Korea also showed an almost panmictic structure, except for the distinct subdivision into the NG and SG. Geographic features such as mountains and arid valleys have been considered potent genetic barriers for several anopheline species.4,5 Considering the geographic distribution of the locations of the NG and SG, the Taebaek and Sobaek mountain ranges may play a key role in establishing a genetic barrier that traverses South Korea from the northeast to the southwest (Figure 1Go). This is supported by the result that all but one individual containing BY02, the most frequent haplotype, were only found in the NG.

Genetic cohesiveness among the populations belonging to each group may be the result of a recent expansion in population size rather than extensive gene flow. According to the mark-release-recapture experiment conducted for this species, migration range is not considerably large; 87.6% of the individuals were recaptured within < 6 km from the release point, although some individuals were able to fly ≥ 12 km in one night.31 These results are in agreement with the fact that almost all malaria cases in South Korea were reported within 10 km of the demilitarized zone (DMZ) during the early days after re-emergence,32 which was caused by sporozoite-infected mosquitoes that originated from North Korea where malaria has recently been prevalent because of its primitive medical system and long-term poverty.10 From the mismatch distribution (Figure 4Go) and neutrality tests (Table 4Go), it can be inferred that the Korean An. sinensis may have expanded. The slight genetic differentiation observed in the SG may be attributed to an earlier expansion in the SG than in the NG, which provided time for the SG to differentiate.

The two groups of the Korean An. sinensis population possessed several differences in terms of genetic properties. First, the SG was more genetically diverse than the NG and comparison of the individual values of each population and the average values of each group revealed higher genetic diversity indices for the SG (Tables 1Go and 4Go). Second, the SG contained a larger number of private alleles than the NG (Figure 3Go). Finally, the theta estimates were higher in the SG than in the NG; assuming an equal mutation rate, the above-mentioned differences indicate that the SG was made up of a relatively large effective population size. This larger effective population size may have resulted from various factors such as less fluctuation in the population size over time and/or less variance in reproductive success, which could be elucidated by further detailed studies.

In summary, the South Korean populations of An. sinensis are divided into two groups, i.e., the NG and SG, and the Taebaek and Sobaek mountain ranges may have played a major role in the genetic divergence observed. Compared with the low gene flow rate between the two groups, an extremely high gene flow rate was detected among the populations within each group. This may be attributed to a recent population expansion rather than the recurrence of gene flow. Furthermore, the SG was superior to the NG with regard to genetic diversity and theta estimates, and the various causative factors for this need to be elucidated.

Received April 10, 2006. Accepted for publication April 18, 2007.

Acknowledgments: The authors thank Dr. Yong-Jin Won (Ewha Womans University) and anonymous reviewers for valuable comments on this manuscript.

Financial support: This work was supported by Korea Research Foundation Grant KRF-2002-070-C00080 and the Korea Science and Engineering Foundation (R21-2005-000-10013-0).

* Address correspondence to Won Kim, School of Biological Sciences, Seoul National University, San 56-1 Shillim-dong, Gwanak-gu, Seoul 151-747, Republic of Korea. E-mail: wonkim{at}plaza.snu.ac.kr Back

Authors’ addresses: Jongwoo Jung, Yunjung Jung, and Won Kim, School of Biological Sciences, Seoul National University, San 56-1 Shillim-dong, Gwanak-gu, Seoul 151-747, Republic of Korea. Gi-Sik Min, Department of Biological Sciences, Inha University, 253 Yonghyun-dong, Nam-gu, Incheon 402-751, Republic of Korea.

Reprint requests: Won Kim, School of Biological Sciences, Seoul National University, San 56-1 Shillim-dong, Gwanak-gu, Seoul 151-747, Republic of Korea. E-mail: wonkim{at}plaza.snu.ac.kr.


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 RESULTS
 DISCUSSION
 REFERENCES
 

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