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Am. J. Trop. Med. Hyg., 71(6), 2004, pp. 795-802
Copyright © 2004 by The American Society of Tropical Medicine and Hygiene

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INTRASPECIFIC NUCLEOTIDE VARIATION IN ANOPHELES GAMBIAE: NEW INSIGHTS INTO THE BIOLOGY OF MALARIA VECTORS

ISABELLE MORLAIS, NICOLAS PONÇON, FRÉDÉRIC SIMARD, ANNA COHUET, AND DIDIER FONTENILLE
Laboratoire de Lutte Contre les Insectes Nuisibles, Institut de Recherche pour le Développement, Montpellier, France; Organisation de Coodination pour la lutte Contre les Endémise en Afrique Centrale, Yaounde, Cameroon; European Molecular Biology Laboratory, Heidelberg, Germany


ABSTRACT
TOP
 ABSTRACT
INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
The Anopheles gambiae genome sequence, together with the recent development of molecular tools for genome-wide analysis, promises new insights into the biology of the malaria vector. These insights should help define the best possible breakdown point for interrupting transmission in the mosquito vector. A survey of the intraspecific nucleotide diversity in coding regions of three different mosquito strains showed an average of one single nucleotide polymorphism (SNP) every 125 coding base pairs. High levels of nucleotide polymorphism were observed in mosquito immune-related genes and pathogen recognition receptors harbored higher replacement substitutions. Genotyping at SNP loci in natural populations of An. gambiae from three malaria foci showed contrasting patterns. The distribution of mutation Y443H in the thioester-containing protein 3 (TEP3) gene suggested this mutational event has occurred under selective constraints. Our results show that SNP-based studies will be valuable in identifying the sequence variation associated with phenotypic traits shaping vector competence.


INTRODUCTION
TOP
 ABSTRACT
 INTRODUCTION
MATERIALS AND METHODS
 RESULTS
 DISCUSSION
 REFERENCES
 
Anopheles gambiae is the major mosquito vector of malaria in Africa, one of the most devastating diseases that affects 300–500 million people and causes 2–3 million deaths per year. Infection of the mosquito vector takes place while blood-feeding on an infected human host. During development within the mosquito, malaria parasites undergo large numerical losses, and it was shown that vector immune mechanisms attenuate the efficiency of parasite development.1–3 Several approaches to identify key mosquito genes interacting with Plasmodium parasites during their development have been developed and the number of putative anti-malarial immune defense molecules has increased rapidly.4–7 Germline transformation of mosquitoes has now been achieved in the laboratory and the principal remaining goal for producing transgenic mosquitoes, with altered vector competence, is to identify suitable targets to be driven into the genome.8,9 Thus, discovering mutations underlying specific traits that could be used for developing new malaria control strategies has become a great challenge. Different ways are currently envisioned, including reduction of the population density and/or longevity of the mosquito, alteration of their anthropophily level, and disruption of the malaria parasite cycle in the insect vector. Thus, investigations of sequence variation between An. gambiae populations of divergent phenotype are needed.

The effort to identify single nucleotide polymorphisms (SNPs) has recently been accelerated by the availability of whole genome sequences and the emergence of high-throughput genotyping tools.10 The SNPs are the most frequent sequence variations found in vertebrate and invertebrate genomes. They are extremely abundant, co-dominant and easy to score. Thus, SNPs have become genetic markers of choice for high-resolution mapping, population genomics, and allelic association studies.11–13 The SNPs located in non-coding regions of the genome and SNPs at synonymous sites in coding regions (sSNPs), with no direct impact on the phenotype, provide useful markers in population genetics and evolutionary studies; whereas SNPs at nonsynonymous sites (nsSNPs), which alter the structure and potentially the function of the encoded proteins, represent target markers to identify genetic variations associated with complex phenotypic traits. In the An. gambiae genome assembly released in public databases at the end of 2002, an overall SNP frequency of 1.6 x 10–3 was found throughout the 278 Mb of the mosquito genome14; this large amount of polymorphisms raises the possibility of undertaking SNP-based studies.

We examined nucleotide variation at coding regions of mosquito nuclear genes by sequence comparison of individual mosquitoes that originated from three different laboratory strains: Yaounde, L35, and 4arr. These three mosquito strains belong to the M molecular form,15 which allows measurement of intraspecific genetic variation. Genes to be compared were chosen for two purposes: 1) they were spread out over the whole genome so that it will be possible to draw a SNP map for An. gambiae, and 2) most of them were genes involved in the immune system, in parasite-vector interactions, or in sexual selection, which will facilitate association studies. To assess the usefulness of SNP markers in population genetics, genotyping was investigated at three SNP loci in natural populations of An. gambiae from three different locations.


MATERIALS AND METHODS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
RESULTS
 DISCUSSION
 REFERENCES
 
Mosquitoes. All mosquitoes used in this study were adult female An. gambiae s.s. Mosquitoes used to assess the nucleotide diversity were from three laboratory strains: Yaounde, L35, and 4arr. The three mosquito strains belong to the M molecular form. The Yaounde strain, which is permissive to Plasmodium falciparum, was colonized in Cameroon in 1988 and was selected for membrane feeding.16 The L35 and 4arr strains were genetically selected for Plasmodium refractoriness and permissiveness, respectively; both strains were derived from the G3 strain, colonized in The Gambia in 1975, following several selection processes.17,18 Mosquitoes used for SNP genotyping were collected in three different field areas where both M and S molecular forms are sympatric: Dielmo in Senegal, Vallée du Kou in Burkina Faso, and Simbock in Cameroon.

Extraction of DNA, primer design, polymerase chain reaction amplification, and sequencing. Genomic DNA was extracted from whole mosquitoes by grinding tissues with a micropestle in an extraction buffer (0.1 M Tris HCl, pH 8.0, 0.01 M EDTA, 1.4 M NaCl, 2% cetylltrimethyl ammonium bromide). The mixture was incubated at 65°C for ten min. Total DNA was extracted with chloroform, precipitated in isopropanol, washed in 70% ethanol, and resuspended in sterile water.

Target genes for this study were selected based on putative role in pathogen-vector interactions or in mosquito behavior. They were also chosen to be dispersed throughout the genome (Table 1Go and Figure 1Go). Three genes of redox processes that were up-regulated upon malaria challenge or associated with oocyst development were screened.4,19 Two housekeeping genes were used as controls, BolA, which plays a role in regulating transcription, and ß-tubulin, which is involved in the cytoskeleton formation. Target genes sequences were extracted from the PEST strain genome database, non-coding regions were identified, and primer sets were designed to allow amplification of 600–1,000-basepair DNA fragments using Primer3 software.20 Regions containing repetitive sequences, introns and untranslated regions were avoided. Primer sequences are available from the corresponding author (IM). For each primer set, the optimum annealing temperature was determined using an Eppendorf MasterCycler Gradient (Eppendorf, Hamburg, Germany).


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TABLE 1
Nucleotide diversity in coding regions of 35 genes of Anopheles gambiae*
 


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  		    FIGURE 1. Relative location of target genes on the Anopheles gambiae genome. For definitions of genes, see Table 1Go.

 
Polymerase chain reactions (PCRs) were carried out with 5 ng of template DNA in a final volume of 50 µL containing 50 mM Tris-HCl, pH 8.3, 2.5 mM MgCl2, 50 mM KCl, 200 µM of each dNTP (Eurogentec, Herstal, Belgium), 0.25 units of Taq polymerase (Qiagen, Courtaboeuf, France), and 10 pmoles of each primer. The PCRs included an initial denaturation step at 95°C for three minutes, followed by 30 cycles at 95°C for 30 seconds, at the specific annealing temperature for 30 seconds, and at 72°C for one minute, and a final extension step at 72°C for six minutes. Five microliters of PCR products were resolved by electrophoresis on a 1% agarose gel, stained with ethidium bromide, and visualized under ultraviolet light (UV). The remaining PCR products were used for sequencing, using reverse- and forward-specific primers.

Electrophoregrams were inspected visually and heterozygous sites were scored according to Black and others.11 Sequences and position of polymorphisms were deposited in GeneBank. Non-coding regions (3,538 basepairs) were removed for sequence analysis. Sequences from 2–3 individuals from each strain were aligned using ClustalX.21 Nucleotide variation was analyzed using MEGA version 2.1.22 The average number of nucleotide substitutions per site {pi} was calculated for the 35 genes for all sequenced individual mosquitoes and for each strain (Table 1Go). Estimates of synonymous and nonsynonymous substitution rates Ks and Ka were computed between sequences using the approximate methods of Kumar, which corrects for transition/transversion bias and handles degenerated sites.23

Single nucleotide polymorphism genotyping. The SNP genotyping assay was conducted on field-caught females (see mosquitoes section). Species and molecular form identification was conducted according to Fanello and others24; only An. gambiae s.s. mosquitoes were used. Polymorphism in the three natural populations was screened at three SNP loci. The SNPs were chosen in coding regions FBN9_Y185H and TEP3_Y443H, corresponding to nonsynonymous substitutions, and PGRP-LP, which was a 27-basepair insertion/deletion (indel) polymorphism (Table 2Go).


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TABLE 2
Characteristics of the three SNP loci screened*
 
Specific primers flanking the SNP or the indel were defined using Primer3 software,20 and the optimum annealing temperature was determined using an Eppendorf MasterCycler Gradient. The PCRs were carried out in a 25-µL reaction mixture as described earlier, but the PCR elongation time was reduced to 30 seconds. Ten microliters of PCR products were used for digestion in a final volume of 25 µL containing 1x reaction buffer, 1x bovine serum albumin, and two units of the appropriate enzyme (Qbiogene, Carlsbad, CA). Digestions were performed overnight at 37°C. Fifteen microliters of the reaction products were resolved by electrophoresis on a 2% agarose gel, photographed under UV light, and individual genotypes were scored. Genotypes for each SNP marker are shown in Table 2Go.


RESULTS
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
DISCUSSION
 REFERENCES
 
Intraspecific nucleotide diversity. The intraspecific diversity of An. gambiae was assessed at coding regions of 35 nuclear genes. Table 1Go details the characteristic features of these genes and Figure 1Go shows their genome location. Sequence comparison identified 460 SNPs and 9 indels over 22,680 basepairs examined. All genes contained at least one SNP. All indels were base triplets and did not cause frame shifting; 30% (140 of 460) of the SNPs were nonsynonymous substitutions and thus induced an amino acid change, only one (in the agCP14332 sequence) was a nonsense SNP.

The average nucleotide diversity per gene was 7.9 x 10–3, ranging from 0.8 x 10–3 to 26.6 x 10–3. Nucleotide diversity was not statistically different between chromosomes 2 and 3 (8.9 x 10–3 and 6.8 x 10–3; P = 0.16, by Student’s t-test). The Yaounde strain exhibited higher intra-strain variability (P < 0.001, by Student’s t-test). This could be due to lower selection procedures that have maintained a certain extent of genetic polymorphism, whereas multiple selections of the L3-5 and 4aRR strains might have drastically reduced their genetic heterogeneity. Interestingly, pairwise comparison of nucleotide diversity between the three strains did not yield significant difference ({pi}Yd/4arr = 9.8 x 10–3, {pi}Yd/L35 = 11.9 x 10–3, {pi}L35/4arr = 8.9 x 10–3, P > 0.1); L35 and 4arr strains were as divergent to each other as with the Yaounde strain. We also observed, depending on genes, haplotypes conserved between both Yaounde and 4arr (CP14332), Yaounde and L35 (Gambif), or 4arr and L35 (SRPN10, LRR-Toll). These findings may reflect bottlenecks induced by selection procedures and that have preserved different ancestral alleles.

Nucleotide diversity was significantly reduced in behavior genes (Arrestin, Period, and Orr1) (P < 0.05), and no non-synonymous substitutions were found in this group (Table 1Go). These genes are associated with sexual selection or host-feeding recognition and, as for the housekeeping genes, they are likely under selective constraints for sequence conservation.

The average Ka was significantly higher for genes putatively involved in the recognition of parasites (i.e., the pattern recognition receptors and membrane-bound receptors) than for others immune-related genes (P < 0.04). This finding could indicate a diversity-enhancing selection on receptor genes, which supports the hypothesis that high levels of polymorphism are maintained in genes involved in parasite recognition because heterozygotes can recognize a greater diversity of antigens.25,26

Genotyping natural populations with SNP markers. Allele frequencies for the three SNP markers are shown in Figure 2Go. Allelic distributions differed from one sampling site to another and between molecular forms. For example, the deleted fragment (allele C) of PGRP-LP marker had a higher frequency in the S molecular form from Dielmo, whereas allele H of FBN9_Y185H marker was more frequent in the Simbock mosquito population of molecular form M.



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  		    FIGURE 2. Allele frequencies of three single nucleotide polymorphisms in Anopheles gambiae natural populations from three different sampling sites (Dielmo in Senegal, Vallée du Kou in Burkina Faso, and Simbock in Cameroon) where molecular forms M and S are sympatric. The numbers of mosquitoes screened are shown in parentheses. For definitions of genes, see Table 1Go.

 
Mutation Y443H in TEP3 gene showed marked differences in its distribution pattern between sampling sites (Figures 2Go and 3Go). Allele H was fixed in all mosquitoes of molecular form S, but allele frequencies differed from one location to another for individuals of molecular form M. In Simbock, only allele H was found, whereas in Vallée du Kou all mosquitoes but one had allele Y, and the mosquito harboring allele H was heterozygote. In contrast, in Dielmo both alleles Y and H were found at almost equal frequency.



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  		    FIGURE 3. Genotypic distribution of the TEP3_Y443H single nucleotide polymorphism in Anopheles gambiae natural populations from three different sampling sites. Sn = Senegal; BF = Burkina Faso; Cam = Cameroon. Numbers in parentheses indicate the sampling size. TEP3 = thioester-containing protein 3.

 

DISCUSSION
TOP
 ABSTRACT
 INTRODUCTION
 MATERIALS AND METHODS
 RESULTS
 DISCUSSION
REFERENCES
 
Genome sequencing projects offer the possibility to undertake studies at a whole-genome scale, and the availability of a growing number of genome sequences facilitates the discovery of massive numbers of genetic markers. In this study, we investigated the genetic variation in coding regions of 35 nuclear genes of An. gambiae and our data, showing an overall average of one SNP every 125 coding basepairs in the mosquito nuclear genes, confirmed the high nucleotide diversity observed in insect genomes.14,27,28

Anopheles gambiae s.s. is characterized by two distinct molecular forms, M and S.15 The molecular forms have maintained their ability to cross-mate, yielding fertile progeny in the laboratory, but the M and S forms exist as isolated populations in sympatric areas, which is indicative of incipient speciation.29–31 The An. gambiae genome sequence was obtained from the PEST strain, which was produced by cross-mating a laboratory strain originating in Nigeria and harboring the Mopti cytotype (molecular form M) with the progeny of field-caught mosquitoes from western Kenya that carried the Savanna cytotype (molecular form S). The genetic composition of the outbred colony was predominantly derived from the Savanna form, but the assembly of the mosquito genome was nonetheless hampered by the presence of dual haplotypes and the PEST strain appeared to have a mosaic genome structure.14 The SNP distribution on a genome-wide scale was heterogeneous across the genome, with SNP densities varying approximately 500-fold according to genomic regions.14 This heterogeneity in the PEST strain is probably due in part to genetic introgression between molecular forms. However, nucleotide diversity is usually positively correlated with recombination rates and a higher level of polymorphism is generally observed at the telomere regions.27,32 The SNP distribution on genes in P. falciparum chromosome 2 was shown to be regional, with most polymorphisms occurring in genes encoding antigens and membrane-associated proteins.33 Most of these proteins interact with the host immune system and, as for the acquired immune system of mammals, genes involved in parasite recognition are likely subject to selective pressures. In Drosophila simulans, DNA variation indicated that adaptive selection has an important role in driving immunity gene evolution.34 The higher rate of replacement substitutions we observed in An. gambiae genes that have a putative receptor function would then suggest that mosquito genes associated in host-pathogen interactions may be well specialized.

Genes exhibiting large number of nonsynonymous substitutions are generally fast-evolving.35 These genes can evolve rapidly because of a lack of strong functional or structural constraints: they evolve in a neutral fashion or because of a positive diversifying selection, with sequence polymorphism giving a selective advantage under a variety of conditions. Thus, to verify adaptive molecular evolution putatively acting on the mosquito receptor genes, it would be interesting to investigate nucleotide divergence in closely related species such as An. arabiensis and An. melas, other efficient malaria vectors, and An. quadriannulatus, which does not naturally transmit P. falciparum parasites because of its zoophilic feeding preferences.36 Similarly, the high sequence diversity we observed in agCP14332 and agCP5039, the function of which is still unknown, is indicative they represent fast-evolving genes. In Drosophila, it has been estimated that 20% of genes represent fast-evolving genes and this proportion is approximately 11% in the mosquito genome.37,38 A large number of these genes do not have homologs in other species, which is the case here for agCP14332 and agCP5039, and it will be of critical importance to determine the function of the encoded proteins since they could be involved in specific adaptations.

The distribution of mutation Y443H in the TEP3 gene is likely due to selective constraints, but this particular allelic distribution could also be linked to chromosomal forms. Indeed, in Simbock, only chromosomal form Forest occurs31 and in Vallée du Kou, mosquitoes of molecular form M carry chromosomal form Mopti, whereas molecular form S has the Savana cytotype.29 In Dielmo, we do not know the relationship between molecular and chromosomal forms, but mosquitoes of molecular form S are harboring the Savana karyotype throughout Senegal whereas molecular form M can carry Savana, Mopti, or Bissau karyotypes.29 However, three of the 12 individuals of the M form screened in Dielmo were heterozygotes and heterocaryotypes are rare in nature.39 Nonetheless mutation Y443H in the TEP3 gene can be associated with some ecologic adaptations and chromosomal forms reflect adaptations to environmental constraints.30 In Vallée du Kou, An. gambiae M form occurs in irrigated zones of rice cultivation, whereas the S form develops in rain-dependent breeding sites.40 At Simbock, both forms are found in the same breeding sites that are characterized by temporary puddles. No information, to our knowledge, is available concerning breeding sites of the different molecular forms in Dielmo.

TEP3 is an immune gene, a member of a family of thioester-containing proteins (TEPs) that are parasite recognition molecules sharing similarities with vertebrates complement factors and {alpha}2-macroglobulins.41 TEP3 is up-regulated upon bacterial challenge and parasite infection.7,41 Mutation Y443H in the TEP3 gene is unlikely related to Plasmodium infection because both molecular forms transmit malaria parasites in these areas. Conversely, the presence of bacteria in permanent breeding sites such as irrigated zones could have exerted a selection pressure on the larval stage and selected this mutation. Characterization of breeding habitats for the M and S molecular forms of An. gambiae in Vallée du Kou would allow confirmation of this assumption, and genotyping mutation Y443H in mosquitoes of known chromosomal form in Dielmo would help decipher the correlation between the mutation and mosquito cytotypes. Functional mutations have already been characterized in genes associated to insecticide resistance, and it was shown that such mutations with strong adaptive value were passed through introgression between incipient species.42,43 Introgressive hybridization is thought to represent a mechanism for generating new adaptations, and monitoring such adaptive genetic changes in natural populations could improve vector control operations implementation and management.30

Population genetics approaches are based on the distribution of genetic variability within and among populations of mosquitoes and SNP markers will provide powerful tools to analyze variation throughout the entire genome. The three SNPs we screened here gave promising results for such population genetics analysis. Genotyping large numbers of SNP markers should facilitate the study of genetic structure of natural populations, which is necessary to predict the spread of genes of interest, such as insecticide resistance genes or malaria-associated genes.

Development of new malaria control measures necessitates the identification of candidate gene(s) that affects phenotypes such as anthropophily, fertility, or parasite permissiveness. Functional genomics tools will help to identify these genes, for example, by comparing genome-wide expression profiles between mosquito populations exhibiting contrasting phenotypes and comparative genomics of functional regions of genes between closely related species (e.g., An. arabiensis and An. quadriannulatus) would help identifying phenotypic markers linked to vectorial capacity and competence. Whole-genome analysis promises new insights into the biology of malaria vectors, and the mosquito genetic variation offers the possibility of designing genotype-phenotype association studies that will aid improving or developing strategies to reduce malaria transmission. The numerous polymorphisms we found in the mosquito genes will be useful for drawing a preliminary SNP map for An. gambiae and to undertake association studies. Genome-wide analysis using SNPs will allow discovering genetic factors associated with complex traits such as permissiveness to Plasmodium.

Received April 7, 2004. Accepted for publication June 29, 2004.

Acknowledgments: We thank Mark Benedict (Malaria Research Activities, National Institute of Allergy and Infections Diseases, National Institutes of Health, Bethesda, MD) for providing L35 and 4arr mosquito strains and Myriam Collin for help in mosquito maintenance in the insectary. We are grateful to Abdoulaye Diabaté (Institut de Recherche en Sciences de la Santé, Bobo-Dioulasso, Burkina Faso) and Ibrahima Dia (Institut Pasteur, Dakar, Senegal) for kindly providing DNA samples from Burkina Faso and Senegal, respectively.

Financial support: This work was supported by the Centre National de la Recherche Scientifique. Isabelle Morlais was supported by the Fondation pour la Recherche Médicale.

Authors’ addresses: Isabelle Morlais, Nicolas Ponçon, and Didier Fontenille, Laboratoire de Lutte Contre les Insectes Nuisibles, Institut De Recherche Pour Le Développement, 911 Avenue Agropolis, BP 64501, 34 394 Montpellier Cedex 5, France, Telephone: 33-467-043-222, Fax: 33-467-542-044, E-mails: isabelle.morlais{at}ird.fr, poncon{at}mpl.ird.fr, and fontenil{at}mpl.ird.fr. Frédéric Simard, Organisation de Coordination pour la Lutte Contre les Endémies en Afrique Centrale, BP 288, Yaounde, Cameroon, Telephone: 237-223-2232, Fax: 237-223-0061, out_of_cameroun{at}yahoo.fr. Anna Cohuet, European Molecular Biology Laboratory, Meyerhofstrasse 1, 69117 Heidelberg, Germany, Telephone: 49-6221-387-288, Fax: 49-6221-387-211, cohuet{at}embl.de.

Reprint requests: Isabelle Morlais, Laboratoire de Lutte Contre Les Insectes Nuisibles, Institut de Recherche pour le Développement, 911 Avenue Agropolis, BP 64501, 34 394 Montpellier Cedex 5, France.


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 DISCUSSION
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