Analysis of population genetic structure of Indian Anopheles culicifacies species A using microsatellite markers
© Sunil et al.; licensee BioMed Central Ltd. 2013
Received: 29 April 2013
Accepted: 4 June 2013
Published: 6 June 2013
Anopheles culicifacies sensu lato is an important vector of malaria in Southeast Asia contributing to almost 70% of malaria cases in India. It exists as morphologically similar sibling species A, B, C, D and E with varied geographical distribution patterns. Vector control measures have been difficult for this important vector as the sibling species have developed varying levels of resistance to the currently used insecticides. In view of the importance of this vector, we developed and validated a set of microsatellite markers and the same were used to analyze the population genetic structure of five different geographical populations of An. culicifacies A.
Anopheles culicifacies A samples were collected from different localities across India, and genotyping was performed using eight microsatellite markers on ABI Prism 310 Genetic Analyzer. Several statistical analyses were performed to ascertain the genetic diversity that exists within and between the populations.
The markers were found to be moderately polymorphic in the populations. Genetic analysis indicated significant genetic differentiation between the majority of the population pairs analyzed and was not found to be related to the geographical distances between populations.
This is the first and successful attempt to test the microsatellite markers developed for population genetic analysis of An. culicifacies A. Host feeding and breeding habits of species A suggest that factors other than ecological and geographical barriers were responsible for the genetic differentiation that has been observed between the populations.
Anopheles culicifacies sensu lato has a wide distribution in India and extends into the west to Ethiopia, Yemen, Iran, Afghanistan and Pakistan, and in the east to Bangladesh, Myanmar, Thailand, Cambodia and Vietnam and is also found in Nepal and southern China in the north and extends to Sri Lanka in the south [1, 2]. It is an important malaria vector in India, Sri Lanka and in the countries west of India. It is responsible for 60-70% of new malaria cases in India . This taxon has now been recognized as a species complex with five members provisionally designated as species A and B , C , D  and E . Species, A, B, C and D, were recognized following the observation of a total absence or significant deficiency of heterozygotes in natural populations for the alternate arrangements observed in polytene chromosomes due to paracentric inversions. The fifth species, species E, was identified by correlating Y-chromosome polymorphisms of sons and the sporozoite positivity of mothers.
There is little information available about the population structure and gene flow that occurs between and/or within An. culicifacies sibling species populations in India. Several studies were carried out to examine the population structure of vectors in Africa and other countries, namely An. gambiae s. s. , An. arabiensis, An. funestus, An. darlingii and many other vectors, using microsatellite markers and mitochondrial genes. Recently, two major vectors found in India, An. stephensi an urban malaria vector  and An. baimaii, a vector in north eastern states  were analysed for population genetic structure and gene flow using microsatellite markers and mitochondrial DNA genes respectively. Microsatellites are highly polymorphic genetic markers used extensively for studying genetic structure of populations. Realizing the importance of knowledge on the population structure and gene flow for implementing insecticide resistance management strategies for the control of An. culicifacies sibling species, microsatellite markers developed in our laboratory  were used in this study to understand the population structure of An. culicifacies species A populations, and the results are reported in this paper.
Sample collection and species identification
Genomic DNA extraction and Microsatellite genotyping of field collected samples
List of microsatellite markers used in the study with details of the primer sequences
Primer sequence 5′-3′
Random mating i.e., agreement to Hardy-Weinberg Equilibrium (HWE) within each of the populations was tested by using the Arlequin v.2.0 software . An unbiased estimate of the exact P-value for each locus was computed using the Markov chain method of Geo and Thompson  with the forecasted chain length of 100,000 steps and dememorization steps of 1000. The observed proportion of heterozygote deficiencies (D) and the frequencies of null alleles (r) that caused the heterozygote deficiencies were estimated following the method described in Chakraborty et al., . For calculation of D and r, the following equations were used: D = (HE-Ho)/HE and r = (HE-Ho)/(HE + Ho); where HE is expected heterozygote frequency and HO is observed frequency of heterozygotes.
Genetic variability among the populations was measured by Wright’s F-statistics . Further, F-statistics values were also calculated according to the method of Weir and Cockerham using the GenAlex v.5.4 (MS Excel-based genetic analysis tool) . The significance of FST values was tested using the formula described by Workman and Niswander where Chi square = 2NFST (where N is the population size with n-1 degrees of freedom for ‘n’ subpopulations) .
The effective migration rate (Nm) was estimated according to Slatkin’s (1987) formula; Nm = 1/4 [(1/ FST)-1] . To investigate, if levels of differentiation were related to geographical distances, the regression of FST (1-FST) on the natural log (ln) of geographical distance was used .
Morphologically identified An. culicifacies specimens were collected from five different localities in India that were selected to best represent the diversity of Indian geography and its ecology (Figure 1). Of the specimens identified, both cytotaxonomically and by PCR methods, a total of 104 species A samples were analyzed for the population structure of An. culicifacies in India. Details of the number of samples from each of the five localities are given in Table 1 and the location of the study sites are shown in Figure 1.
Distribution and the level of genetic diversity
Details of genetic diversity at microsatellite loci among five populations of species A
Microsatellite markers (total no. of alleles observed)
An. culicifacies species A
Hardy-Weinberg equilibrium (HWE)
Number of alleles observed for each locus, and the allele with the maximum frequency observed in the population of An. culicifacies species A
Total number of alleles observed
7 + 1*
Alleles with maximum frequency (allelic frequency)
Allahabad (Uttar Pradesh) N = 23
Bijapur (Karnataka) N = 24
Sonepat (Haryana) N = 28
Kheda (Gujarat) N = 17
Jodhpur (Rajasthan) N = 11
112(0.26) 114 (0.26)
Correlation between the population divergence and isolation of populations by distance
The five populations exhibited remarkably similar allelic distributions on averaging all loci but differential patterns were observed among the loci in four out of eight loci (Table 3). A single allele of 206 bp of the marker ACA59 was predominant in all the five populations of species A, and with reference to the ACAVIB213 locus, each of the populations had a different predominant allele (Table 3). There were also alleles unique to one or the other populations, but the frequencies of these alleles were very low (data not shown). The maximum frequency of alleles at each of the loci ranged from 0.2 to 0.9 in the populations (Table 3).
F ST and Nm values for the population comparisons of An. culicifacies populations
U. P.- A
All the eight microsatellite markers examined in An. culicifacies species A populations were polymorphic. Maximum number of alleles at each locus ranged from 4 to 10 with the exception for one marker (ACAVVIB213), which exhibited 17 alleles, suggesting that these markers are moderately polymorphic in the populations. Except for AcAVIIB46 and AcAVB93A with the least number of alleles, the other markers did not exhibit all the alleles in any of the five populations. Significant deviations from the Hardy-Weinberg expectations for these markers were observed in the populations studied. The deficiency of heterozygotes observed in these populations could be due to population sub-structuring or due to the presence of null alleles, i.e. mutation/s in the primer sites that may prevent annealing of primers to the DNA samples. This results in either total failure of amplification (homozygous for null allele), or most commonly one strand will be amplified and the sample will be scored as a homozygote, which in fact is a heterozygote . During genotyping, a few DNA samples did not amplify for one or the other marker. In order to rule out the problems of multiplexing, these samples were also genotyped separately by setting up an individual PCR. As these samples were normally amplified in some other combinations, non-amplification is necessarily not due to the poor quality of DNA or other general PCR procedural problems. Grouping together of different gene pools (Wahlund effect) and non-random mating within the populations i.e. presence of sub-populations as a reason for the deficiencies is not being favored because (i) collections were of only indoor-resting mosquitoes, collected from both human dwellings and cattle sheds, and mosquitoes were collected from structures within a single village or one or two more which are within 5–10 km range, (ii) the extensive cytotaxonomic studies carried out in different parts of the country did not indicate any sub-populations and (iii) that D values up to 10% do not indicate the presence of sub-populations . The D-values observed in this study are significantly low. Therefore, presence of null alleles is being considered to be mainly responsible for the deficiencies of heterozygotes observed at these loci. However, it is not known whether the markers not being in Hardy-Weinberg equilibrium has had any influence on the population genetic parameters estimated in this study. Keeping this in view and that the markers were randomly selected not knowing whether they represent the entire genome, a few conservative conclusions are being drawn from the F-statistics data. FST values have shown a great genetic differentiation between the pairs of populations analyzed. Low Nm values (<1) between Haryana and Uttar Pradesh, and Rajasthan and Haryana suggest a limited gene flow. The geographical distances of these two population pairs were less than those observed for Gujarat and Haryana, and Gujarat and Karnataka which had maximum Nm values (>5 and 7 respectively).
Vindhyachal Mountain ranges which pass through central India (Maharashtra and Madhya Pradesh States) separate northern and southern parts of India. Karnataka is located in the southern part of India. There are no known geographical barriers that exist between the other four populations studied. Furthermore, anopheline species in general are known to have limited flight range. For species A, which is predominantly zoophagic (maximum anthropophilic index observed was 3-4%), An. culicifacies being a rural mosquito and agriculture being practiced extensively in these areas indicate free availability of cattle for blood feeding. Irrigation channels are preferred breeding habitat for species A. This suggests that other than geographical or ecological, some other barriers are playing a role for differential genetic differentiation levels observed between these populations. Residual sprays with effective insecticides alter and interfere with population sizes. At the time of collection of mosquitoes, no spray operations were going on in sites in Uttar Pradesh, Haryana and Rajasthan states. In Gujarat and Karnataka, malathion was being sprayed in the study sites, which even at present is effective on An. culicifacies populations in these areas. Therefore, the effect of insecticide sprays on the mosquito population sampling cannot be ruled out.
This is the first and successful attempt made to study the population genetic structure of An. culicifacies using microsatellite markers. Genetic analysis of five different populations of species A was carried out with eight microsatellite markers. FST values indicated significant genetic differentiation between the majorities of the population pairs analyzed. We hope that these results may add a further step in understanding the dynamics of the vector species for planning effective vector control activities based on population genetic structure.
Financial support for this study (Project ID no: 990484) was received from WHO/TDR under Molecular Entomology Committee. The authors would like to thank all technical staff of NIMR for their assistance in conducting the study.
This manuscript was approved by NIMR publication committee (Approval no: 009/2013).
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