• View in gallery

    Left, Collection sites in Mali of samples used in this study. Top right, Polytene chromosome map indicating the breakpoints and size of inversions on the 2R chromosome arm in Anopheles gambiae. Bottom right, Chromosomal polymorphisms found in the BAMAKO, SAVANNA, and MOPTI chromosomal forms.

  • 1

    Coluzzi M, Petrarca V, Di Deco MA, 1985. Chromosomal inversion intergradation and incipient speciation in Anopheles gambiae. Boll Zool 52 :45–63.

    • Search Google Scholar
    • Export Citation
  • 2

    Coluzzi M, Sabatini A, della Torre A, Di Deco MA, Petrarca V, 2002. A polytene chromosome analysis of the Anopheles gambiae species complex. Science 298 :1415–1418.

    • Search Google Scholar
    • Export Citation
  • 3

    Favia G, della Torre A, Bagayoko M, Lanfrancotti A, Sagnon N’F, Touré YT, Coluzzi M, 1997. Molecular identifications of sympatric chromosomal forms of Anopheles gambiae and further evidence of their reproductive isolation. Insect Mol Biol 6 :377–383.

    • Search Google Scholar
    • Export Citation
  • 4

    della Torre A, Fanello C, Akogbeto M, Dossou-yovo J, Favia G, Petrarca V, Coluzzi M, 2001. Molecular evidence of incipient speciation within Anopheles gambiae s.s. in West Africa. Insect Mol Biol 10 :9–18.

    • Search Google Scholar
    • Export Citation
  • 5

    Gentile G, Slotman M, Ketmaier V, Powell JR, Caccone A, 2001. Attempts to molecularly distinguish cryptic taxa in Anopheles gambiae s.s., and the problem of taxonomic status. Insect Mol Biol 10 :25–32.

    • Search Google Scholar
    • Export Citation
  • 6

    Taylor C, Touré YT, Carnahan J, Norris DE, Dolo G, Traoré SF, Edillo FE, Lanzaro GC, 2001. Gene flow among populations of the malaria vector, Anopheles gambiae, in Mali, West Africa. Genetics 157 :743–750.

    • Search Google Scholar
    • Export Citation
  • 7

    Tripet F, Toure YT, Taylor CE, Norris DE, Dolo G, Lanzaro GC, 2001. DNA analysis of transferred sperm reveals significant levels of gene flow between molecular forms of Anopheles gambiae. Mol Ecol 10 :1725–1732.

    • Search Google Scholar
    • Export Citation
  • 8

    della Torre A, Tu Z, Petrarca V, 2005. On the distribution and genetic differentiation of Anopheles gambiae s.s. molecular forms. Insect Biochem Mol Biol 35 :755–769.

    • Search Google Scholar
    • Export Citation
  • 9

    Wang RL, Zheng L, Touré Y, Dandekar T, Kafatos F, 2001. When genetic distance matters: measuring genetic differentiation at microsatellite loci in whole-genome scans of recent and incipient species. Proc Natl Acad Sci USA 98 :10769–10774.

    • Search Google Scholar
    • Export Citation
  • 10

    Lehmann T, Licht M, Elissa N, Maega BTA, 2003. Population structure of Anopheles gambiae in Africa. J Hered 94 :133–147.

  • 11

    Stump AD, Shoener JA, Constantini C, Sagnon NF, Besansky NJ, 2005. Sex-linked differentiation between incipient species of Anopheles gambiae. Genetics 169 :1509–1519.

    • Search Google Scholar
    • Export Citation
  • 12

    Lanzaro GC, Touré YT, Carnahan J, Zheng L, Dolo G, Traoré SF, Petrarca V, Vernick KD, Taylor CE, 1998. Complexities in the genetic structure of Anopheles gambiae populations in West Africa as revealed by microsatellite DNA analysis. Proc Natl Acad Sci USA 95 :14260–14265.

    • Search Google Scholar
    • Export Citation
  • 13

    Tripet F, Dolo G, Lanzaro GC, 2005. Multilevel analyses of genetic differentiation in Anopheles gambiae s.s. reveal patterns of gene flow important for malaria-fighting mosquito projects. Genetics 169 :315–324.

    • Search Google Scholar
    • Export Citation
  • 14

    Mukabayire O, Caridi J, Wang X, Touré YT, Coluzzi M, Besansky NJ, 2001. Patterns of DNA sequence variation in chromosomally recognized taxa of Anopheles gambiae: evidence from rDNA and single-copy loci. Insect Mol Biol 10 :33–46.

    • Search Google Scholar
    • Export Citation
  • 15

    Touré YT, Petrarca V, Traoré S, Coulibaly A, Maiga HM, Sankare O, Sow M, Di Deco MA, Coluzzi M, 1998. The distribution and inversion polymorphism of chromosomally recognized taxa of the Anopheles gambiae complex in Mali, West Africa. Parassitologia 40 :477–511.

    • Search Google Scholar
    • Export Citation
  • 16

    Fanello C, Petrarca V, della Torre A, Santolamazza F, Dolo G, Coulibaly M, Alloueche A, Curtis CF, Touré YT, Coluzzi M, 2003. The pyrethroid knock-down resistance gene in the Anopheles gambiae complex in Mali and further indication of incipient speciation within An. gambiae s.s. Insect Mol Biol 12 :241–245.

    • Search Google Scholar
    • Export Citation
  • 17

    Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Homes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M, 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23 :4407–4414.

    • Search Google Scholar
    • Export Citation
  • 18

    Mendelson TC, Shaw KL 2005. Use of AFLP markers in surveys of arthropod biodiversity. Methods Enzymol 395 :161–177.

  • 19

    Luikart G, England PR, Tallmon D, Jordan S, Taberlet P, 2003. The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet 4 :981–994.

    • Search Google Scholar
    • Export Citation
  • 20

    Albertson RC, Markert JA, Danley PD, Kocher TD, 1999. Phylogeny of a rapidly evolving clade: the cichlid fishes of Lake Malawi, east Africa. Proc Natl Acad Sci USA 96 :5107–5110.

    • Search Google Scholar
    • Export Citation
  • 21

    della Torre A, 1997. Polytene chromosome preparation from Anopheline mosquitoes. Crampton JM, Beard CB, Louis C, eds. Molecular Biology of Insect Disease Vectors. London: Chapman and Hall, 329–336.

  • 22

    Coluzzi M, Sabatini A, Petrarca V, Di Deco MA, 1979. Chromosomal differentiation and adaptation to human environments in the Anopheles gambiae complex. Trans R Soc Trop Med Hyg 73 :483–497.

    • Search Google Scholar
    • Export Citation
  • 23

    Post R, Flook PK, Millest AL, 1993. Methods for the preservation of insects for DNA studies. Biochem Systematics Ecol 21 :85–92.

  • 24

    Peakall R, Smouse PE, 2001. GenAlEx version 5: Genetic Analysis in Excel. Population Genetic Software for Teaching and Research. Canberra, Australia; Australian National University. Available from http://www.anu.edu.au/BoZo/GenAlEx/

  • 25

    Excoffier L, Smouse P, Quatro J, 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: applications to human mitochondrial DNA restriction data. Genetics 131 :479–491.

    • Search Google Scholar
    • Export Citation
  • 26

    Rolf FJ, 1994. NTSYS-pc. Numerical Taxonomy and Multivariate Analysis System. Version 1.80. Setauket, NY: Exeter Software.

  • 27

    Duchesne P, Bernatchez L, 2002. AFLPOP: a computer program for simulated and real population allocation, based on AFLP data. Mol Ecol Notes 2 :380–383.

    • Search Google Scholar
    • Export Citation
  • 28

    Vekemans X, Beauwens T, Lemaire M, Roldan-Ruiz I, 2002. Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size. Mol Ecol 11 :139–151.

    • Search Google Scholar
    • Export Citation
  • 29

    Munstermann LE, 1994. Unexpected genetic consequences of colonization and inbreeding-allozyme tracking in Culicidae (Diptera). Ann Entomol Soc Am 87 :157–164.

    • Search Google Scholar
    • Export Citation
  • 30

    Norris DE, Shurtleff AC, Touré YT, Lanzaro GC, 2001. Microsatellite DNA polymorphism and heterozygosity among field and laboratory populations of Anopheles gambiae s.s. (Diptera: Culicidae). J Med Entomol 38 :336–340.

    • Search Google Scholar
    • Export Citation
  • 31

    Garcia BA, Caccone A, Mathiopoulos KD, Powell JR, 1996. Inversion monophyly in African Anopheline malaria vectors. Genetics 143 :1313–1320.

    • Search Google Scholar
    • Export Citation
  • 32

    Krimbass CB, Powell JR, 1992. Drosophila Inversion Polymorphism. Boca Raton, FL: CRC Press.

  • 33

    Diabate A, Baldet T, Chandre C, Dabire KR, Kenge P, Guiguemde TR, Simard F, Guillet P, Hemingway J, Hougard JM, 2003. KDR mutation, a genetic marker to assess events of introgression between molecular M and S forms of Anopheles gambiae (Diptera: Culicidae) in the tropical savannah area of West Africa. J Med Entomol 40 :195–198.

    • Search Google Scholar
    • Export Citation
  • 34

    Favia G, Lanfrancotti A, Spanos L, Sidén-Kiamos I, Louis C, 2001. Molecular characterization of ribosomal DNA polymorphisms discriminating among chromosomal forms of Anopheles gambiae s.s. Insect Mol Biol 10 :19–23.

    • Search Google Scholar
    • Export Citation
  • 35

    Gentile G, della Torre A, Maegga B, Powell JR, Caccone A, 2002. Genetic differentiation in the African malaria vector, Anopheles gambiae s.s., and the problem of taxonomic status. Genetics 161 :1561–1578.

    • Search Google Scholar
    • Export Citation
  • 36

    Turner TL, Hahn MW, Nuzhdin SV, 2005. Genomic islands of speciation. PLoS Biol 3 :1572–1578.

  • 37

    Gentile G, Santolamazza F, Fanello C, Petrarca V, Caccone A, della Torre A, 2004. Variation in an intron sequence of the voltage-gated sodium channel gene correlates with genetic differentiation between Anopheles gambiae s.s. molecular forms. Insect Mol Biol 13 :371–377.

    • Search Google Scholar
    • Export Citation
  • 38

    Kai Y, Nakayama K, Nakabo T, 2002. Genetic differences among three colour morphotypes of the black rockfish, Sebastes inermis, inferred from mtDNA and AFLP analyses. Mol Ecol 11 :2591–2598.

    • Search Google Scholar
    • Export Citation
  • 39

    Bleeker W, 2003. Hybridization and Rorippa austriaca (Brassi-caceae) invasion in Germany. Mol Ecol 12 :1831–1841.

  • 40

    Haig SM, Mullins TD, Forsman ED, Trail PW, 2003. Genetic identification of spotted owls, barred owls and their hybrids: legal implications of hybrid identity. Conservation Biol 18 :1347–1357.

    • Search Google Scholar
    • Export Citation
  • 41

    Garzón CD, Geiser DM, Woorman GW, 2005. Diagnosis and population analysis of Pythium species using AFLP fingerprinting. Plant Dis 89 :81–89.

    • Search Google Scholar
    • Export Citation
  • 42

    Wu CA, Campbell DR, 2005. Cytoplasmic and nuclear markers reveal contrasting patterns of spatial and genetic structure in a natural Ipomopsis hybrid zone. Mol Ecol 14 :781–792.

    • Search Google Scholar
    • Export Citation
  • 43

    Jones CJ, Edwards KJ, Castaglione S, Winfield MO, Sala F, van de Weil C, Bredemeijer G, Vosman B, Matthes M, Daly A, Brettschneider R, Bettni P, Buitti M, Maestri E, Malcevschi A, Marmiroli N, Aert R, Volckaert G, Rueda J, Linacero R, Vazquez A, Karp A, 1997. Reproducibility testing of RAPD, AFLP and SSR markers in plants by a network of European laboratories. Mol Breeding 3 :381–390.

    • Search Google Scholar
    • Export Citation
  • 44

    della Torre A, Merzagora L, Powell JR, Coluzzi M, 1997. Selective introgression of paracentric inversions between two sibling species of the Anopheles gambiae complex. Genetics 246 :239–244.

    • Search Google Scholar
    • Export Citation
  • 45

    Besansky NJ, Krzywinski J, Lehmann T, Simard F, Kern M, Mukabayire O, Fontenille D, Touré YT, Sagnon N’F, 2003. Semipermeable species boundaries between Anopheles gambiae and An. arabiensis: evidence from multilocus DNA sequence variation. Proc Natl Acad Sci USA 100 :10818–10823.

    • Search Google Scholar
    • Export Citation
  • 46

    Slotman MA, della Torre A, Calzetta M, Powell JR, 2005. Differential introgression of chromosomal regions between Anopheles gambiae and An. arabiensis. Am J Trop Med Hyg 73 :326–335.

    • Search Google Scholar
    • Export Citation
  • 47

    Lehmann T, Hawley WA, Grebert H, Collins FH, 1998. The effective population size of Anopheles gambiae in Kenya: implications for population structure. Mol Biol Evol 15 :264–276.

    • Search Google Scholar
    • Export Citation
 
 
 
 

 

 
 
 

 

 

 

 

 

 

GENETIC DIFFERENTIATION BETWEEN THE BAMAKO AND SAVANNA CHROMOSOMAL FORMS OF ANOPHELES GAMBIAE AS INDICATED BY AMPLIFIED FRAGMENT LENGTH POLYMORPHISM ANALYSIS

View More View Less
  • 1 Department of Ecology and Evolutionary Biology, and Yale Institute for Biospheric Studies, Yale University, New Haven, Connecticut; Sezione di Parassitologia, Dipartimento di Scienze di Sanità Pubblica, Università di Roma La Sapienza, Rome, Italy; Malaria Research Training Center, Départment d’Entomologie, Ecole Nationale de Médecine et de Pharmacie, Bamako, Mali; World Health Organization, Geneva, Switzerland

The main vector of malaria in sub-Saharan Africa, Anopheles gambiae, is subdivided into five chromosomal forms. Three of them (i.e., BAMAKO, SAVANNA, and MOPTI) are found in sympatry in Mali, where MOPTI can be distinguished from the other two forms based on differences in the ribosomal DNA locus. However, no molecular markers are available to distinguish BAMAKO from SAVANNA. We examined the banding patterns of 139 amplified fragment length polymorphism primer combinations in an attempt to identify diagnostic differences between SAVANNA and BAMAKO. Despite screening > 10,000 bands, no diagnostic differences were found. However, additional AFLP analyses indicated that BAMAKO is genetically differentiated from SAVANNA, with a significant Φst value of 0.072. This could indicate that gene flow between these forms is restricted in at least some portion of the genome and the lack of identifiable fixed differences between the two forms is probably due to their recent origin.

INTRODUCTION

Anopheles gambiae sensu stricto is the principal vector of human malaria in sub-Saharan Africa. It has developed the highest degree of synanthropy, i.e., the ability to exploit anthropogenic breeding sites, feeds almost exclusively on human blood, and bites and rests indoors. Genetic discontinuities within West African populations of An. gambiae have been described by Coluzzi and others based on analysis of polymorphic inversions on the right (2R) and left (2L) arms of chromosome 2.1,2 These studies led to the description of five chromosomal forms (named with a non-Linnean nomenclature FOREST, SAVANNA, MOPTI, BAMAKO, and BISSAU). These forms are characterized by adaptation to different ecologic settings.

Molecular discontinuities were discovered in the ribosomal DNA (rDNA) region of An. gambiae, 3 and two molecular forms (provisionally named with a non-Linnean nomenclature M form and S form) were defined on the basis of single nucleotide differences in the intergenic spacer and internal transcribed spacer regions.4,5 The relationship between chromosomal and molecular forms has been shown to vary along their range of distribution, but in Mali and Burkina Faso, the molecular form M corresponds to the chromosomal form MOPTI, whereas the SAVANNA and BAMAKO chromosomal form are of the S molecular type.

Hybrids between the M and S forms are rarely encountered in nature,68 which indicates strong barriers to gene flow. Additional studies have shown that microsatellites located close to the rDNA on the X chromosome are significantly differentiated between the M and S forms.913 Loci on the 2R, which are located close to or inside the inversions that characterize the chromosomal forms, are also significantly differentiated between BAMAKO and MOPTI, whereas other loci are not.12,13 However, two other studies did not find diagnostic differences in 13 genes located throughout the genome.5,14 Therefore, it appears that fixed differences between SAVANNA/BAMAKO and MOPTI are limited to very few areas of the genome, although genetic differentiation, i.e., differentiation in allele frequencies due to restricted gene flow or selection between the BAMAKO and MOPTI forms extend to a larger area of the second chromosome.

The level of reproductive isolation between the Bamako and Savanna chromosomal forms is unclear. Inversion karyotypes indicative of putative hybrids between the forms are underrepresented,15 but this could be caused by selection acting on inversions. However, other studies suggest that some isolation between these forms exists. Taylor and others investigated genetic differentiation of microsatellite loci between a BAMAKO and SAVANNA population and reported significant overall differentiation, with higher differentiation of second chromosome loci.6 Unfortunately, these investigators did not report whether significant differentiation was detected outside the second chromosome. Additionally, the study compared populations 380 km apart, which could have contributed to the observed differentiation. Perhaps the strongest evidence for reproductive isolation between the BAMAKO and SAVANNA chromosomal forms comes from observations that the kdr allele, which confers resistance against pyrethroid insecticides, was present in SAVANNA in two villages in Mali at frequencies of up to 62%, whereas it was not found in sympatric BAMAKO populations.16 Notably, the kdr allele is located on the 2L chromosome and is therefore not linked to the chromosomal arrangements on the 2R that define the chromosomal forms.

The three forms present in Mali vary in their geographic and temporal distributions, as well as in ecologic preferences: SAVANNA is fully dependent on rainfall for its breeding and disappears during the dry season; BAMAKO is primarily associated with the riverine zones of the upper Niger River and breeds mostly during the mid-late rainy season; and MOPTI breeds in flooded plains and irrigated fields, and is the only form found during the dry season, extending the malaria season.15 From a biomedical perspective, although the three forms do not show significant differences with regards to sporozoite rate and anthropophily, the process of ecotypic differentiation and niche partitioning increases the diversity of the vector system and its flexibility in exploiting the environmental resources, likely resulting in an increased stability of the overall vectorial capacity.15 Moreover, the presence of the kdr allele in SAVANNA populations and not in the two sympatric chromosomal forms highlights the relevance of the differentiation process ongoing within An. gambiae also from the malaria vector control perspective.

It is thus clear that investigations aimed at increasing our knowledge of the biology, ecology, and vectorial capacity of these malaria vectors depends crucially on our ability to identify the three chromosomal forms. However, the sole technique so far available to differentiate between them is polytene chromosome analysis. This approach has severe limitations because it can only be performed on blood fed females in a half-gravid stage of ovarial development and requires trained cytogenetists to interpret the banding patterns.

Amplified fragment length polymorphiasm (AFLP) analysis17 has become a popular tool for population genetic studies and is also frequently used to study genetic differentiation,18 identify loci under selection,19 and investigate phylogenetic relationships between closely related taxa.20 One of the strengths of AFLP analysis is the ability to sample large numbers of loci that are randomly distributed across the genome, without prior knowledge of the genome of the investigated species. The large number of markers typically scored in an AFLP analysis increases the possibility of detecting differentiation between closely related taxa, whose genomes may have only a few differentiated regions. AFLP markers have also been used to identify diagnostic differences between putative species.

We present results of AFLP analyses performed on several mosquito populations of BAMAKO and SAVANNA from Mali with the aim of finding diagnostic differences between these two chromosomal forms. Additionally, we measured overall levels of genome wide genetic differentiation between all three chromosomal forms in Mali to examine if significant differences in gene frequencies are present between the BAMAKO and SAVANNA chromosomal forms.

MATERIALS AND METHODS

Study sites.

Laboratory specimens were obtained from a SAVANNA colony established in the insectaries of the Parasitology Unit in Rome, Italy from single ovipositions of An. gambiae s.s. collected in Pimperena, Mali in October 1996 and classified by their chromosomal arrangement as follows: Xag, 2Rb, 2La, 3R, and 3L. BAMAKO colony specimens were obtained from a BAMAKO colony established in the insectary of the Malaria Research Training Center in Bamako, Mali from approximately 20 females collected in November 2000 in Moribabougou, Mali.

All field specimens used in this study were collected in the following localities in Mali, where at least two chromosomal forms are known to be sympatric: Moribabougou (1996 and 2000), N’Gabakoro Droit (1999), Banambani (1996 and 2000), and Fanzana (2001). Additional DNA samples were kindly provided by Gregory Lanzaro (University of California, Davis, CA). These were collected in the following localities: N’Gabakoro Droit (1999), Selenkenyi (1993), Soulouba (1996), and Pimperena (1997). To improve our sample size, more than 500 females were collected in 2001 from six other villages in Mali. Unfortunately, only a few samples from one of the six locations (Balama) yielded material suitable for karyotyping, and these were included in the study. Collection sites are shown in Figure 1.

Polytene chromosome analyses.

Abdomens of half-gravid females were preserved in Carnoy’s solution. Ovaries of these specimens were prepared for chromosomal analysis using the procedure of della Torre.21 The remainder of the specimens was preserved in alcohol for DNA extraction. Inversion karyotypes were scored using a phase-contrast microscope according to the procedure of Coluzzi and others.22

Molecular methods.

DNA was extracted from the head and thorax by the procedure of Post and others.23 AFLP analysis was performed by the procedure of Vos and others.17 Briefly, genomic DNA was digested with Eco RI and Mse I restriction enzymes. DNA fragments were ligated with Eco RI and Mse I adaptors, and a pre-selective polymerase chain reaction (PCR) was performed using two primer combinations that annealed to the Mse I and Eco RI adaptors plus an additional nucleotide; M-C + E-A and M-G + E-A. Selective PCRs were performed on the diluted product of the pre-selective PCR using a fluorescently labeled Eco RI and unlabeled Mse I primer. The Eco RI primers contained three selective nucleotides, whereas the Mse I primer contained either three or four selective nucleotides.

Three sets of samples (Table 1) were screened for diagnostic differences using various AFLP primer combinations. A list of these is available from the authors upon request. Although in most cases the samples from each village used in the larger sample sets include those samples that were used for the smaller sets, this was not always the case. In a few instances not enough DNA was available and the samples were substituted. Sample set 4 (Table 1) was run on the following five primer-combinations: M-GAA + E-AGT, M-GAC + E-TGG, M-GAT + E-TAG, M-GTC + E-TGC, and M-GTT + E-AGA. Selective PCR products were subjected to electrophoresis on an acrylamide gel using an ABI 373 automated sequencer (Applied Biosystems, Foster City, CA).

Data analyses.

The AFLP data were collected using Genescan software (Applied Biosystems). Banding patterns were examined visually for the presence of diagnostic bands. Bands from the analysis on sample set 4 were assigned a size within a one-basepair range using Genotyper (Applied Biosystems). Analysis of molecular variance (AMOVA) was performed on this data set using the GENALEX software version 524 by the procedure by Excoffier and others.25 This software package was also used to calculate Φst values. These statistics are estimated using AMOVA based on genetic distance, and are analogous to Fsts, with the advantage that there is no assumption of Hardy-Weinberg equilibrium. This is important because this assumption cannot be tested for dominant markers. The number of permutations used to estimate p values was 999.

Principle component analysis (PCA) was performed using NTSYS version 2.10j.26 Population assignment tests were performed using AFLPOP version 1.1,27 which is specifically designed to handle AFLP data. We used the re-allocation procedure, which estimates the expected allocation success rate for each of the source populations. Using this procedure, each specimen was withdrawn from its population of origin (i.e., its chromosomal form), and subsequently assigned to one of the three chromosomal forms. Zero frequencies were replaced with 0.001 to allow for a small amount of error in the data and the minimum log likelihood difference used was 0.27

RESULTS

Screen for diagnostic differences between BAMAKO and SAVANNA.

Initially, 21 mosquitoes from a SAVANNA and a BAMAKO colony were screened using 48 AFLP primer combinations. Primer sets that produced bands that differentiated between the two forms were later tested on field-collected mosquitoes. However, none of these bands proved diagnostic for the field-collected SAVANNA and BAMAKO specimens. That is, no bands were found that were always present in one chromosomal form and always absent in the other. Based on a random sample of 10 primer combinations, each set of primers produced 39.5 distinct bands on average (range = 30–77) in these samples. Assuming that each band represented an independent locus, approximately 1,900 loci were screened for diagnostic differences using these laboratory colonies. The assumption that each band represents a distinct locus is not necessarily correct. For example, Vekemans and others28 suggested that size homoplasy of AFLP bands is quite common, although their study concerned single bands representing multiple loci, rather than multiple loci producing more than one band. Our estimate of the number of loci may be a slight overestimate.

It is well known that samples obtained from mosquito laboratory colonies contain significantly less variation than natural populations.29,30 Therefore, we continued our screen directly on field-collected samples when sufficient field-collected specimens from both chromosomal forms were obtained. This set included 30 BAMAKO and 33 SAVANNA specimens from various locations in Mali (set 1, Table 1). Samples from several locations were included to increase the probability that any identified fixed differences are present throughout the distribution of these chromosomal forms. However, no diagnostic differences were found between these BAMAKO and SAVANNA samples using 34 different primer combinations.

Given our lack of success in finding diagnostic differences, and to expedite subsequent screening of AFLP markers, we continued with a smaller subset of samples. This set included 10 BAMAKO and 10 SAVANNA specimens (set 2, Table 1), and was used to screen 39 additional primer combinations. None of these yielded any diagnostic differences between the BAMAKO and SAVANNA samples. Subsequently, we included 13 field-collected MOPTI specimens (set 3, Table 1), to investigate if AFLP markers could be identified that distinguish between SAVANNA and MOPTI. This set was used to screen an additional 18 primer combinations. No diagnostic differences between BAMAKO and SAVANNA could be identified using these primers, nor were any diagnostic differences found to distinguish the MOPTI from SAVANNA and/ or BAMAKO.

Based on an analysis of 10 randomly chosen primer sets, each primer set that was run on the field-collected samples produced an average of 121 distinct bands (range = 56–154). A total of 91 primer combinations were screened on field-collected samples. If it is assumed that each band represents a distinct locus, we screened approximately 11,000 loci on field-collected samples. If we include the approximately 1,900 loci that were screened on the colony samples, approximately 12,900 loci were examined in this analysis. Since we used a four-basepair and a six-basepair cutter restriction enzyme, and since the primers contained either three or four selective nucleotides, each band screened 16 or 17 basepairs for nucleotide substitutions. If the assumption that each band represents a distinct locus is correct, we have screened approximately 213,700 basepairs for diagnostic nucleotide substitutions between the BAMAKO and SAVANNA.

Genetic differentiation among the three chromosomal forms.

To examine levels of genetic differentiation between the BAMAKO, SAVANNA and MOPTI chromosomal forms, we ran AFLPs on a larger sample of 50 to 62 specimens from each form (set 4, Table 1) using five primers sets. These primer sets were selected based on the quality of their amplification and the number of bands present in the profiles. These five primers produced 587 bands. The GENALIX software that was used to estimate levels of genetic differentiation between forms cannot handle more than 256 loci. Therefore, we removed bands that were observed less than fives times in all the samples. Our reasoning behind this was that these bands are the most likely to represent artifacts (i.e., noise). Additionally, removal of these bands will have little effect on our estimates of genetic differentiation because of their very low frequency. After removal of these bands our data set contained 166 loci.

An AMOVA of the complete data sets indicated that 10% of the observed variation is between chromosomal forms, whereas 90% was shared. Based on Φst values, all three forms are significantly differentiated from each other (Table 2). Differentiation is lowest between BAMAKO and SAVANNA, while BAMAKO and MOPTI are the most differentiated forms, and the Φst value for SAVANNA and MOPTI is intermediate. Unfortunately, we were not able to obtain large numbers of samples from all forms from the same locality. Therefore, these results include samples from various locations. However, significant differentiation was also observed between BAMAKO and SAVANNA in Banambani and N’Gabakoro Droit (comparison 4 and 5, Table 2), even though samples sizes were small for at least one of the forms in each comparison (n = 5 and 20 in Banambani and n = 17 and 4 in N’Gabakoro Droit for BAMAKO and SAVANNA, respectively). Three of the collection sites are located in close proximity to each other. N’Gabakoro Droit and Moribabougou are within 8 km of each other, whereas Banambani is within 90 km of both. To avoid confounding effects caused by differences in collection sites for some of the specimens, values were also calculated using specimens collected Φst from these sites only (Table 2). The results of this analysis are similar and portray the same picture. Differentiation is largest between BAMAKO and MOPTI, followed by MOPTI and SAVANNA, and finally BAMAKO and SAVANNA.

Genetic differentiation was also examined within forms between those populations for which at least 14 specimens were available. No significant differentiation was detected between the two BAMAKO populations (N’Gabakoro Droit and Moribabougou), nor between the three MOPTI populations (N’Gabakoro Droit, Moribabougou, and Fanzana). As noted above, N’Gabakoro Droit and Moribabougou are within a few kilometers of each other and the lack of genetic differentiation between these localities is not surprising. Fanzana is located approximately 180 km from N’Gabakoro Droit and Moribabougou, but no genetic differentiation was detected between this locality and either of the other two localities with the MOPTI form (comparison 11 and 12, Table 2). Sufficient SAVANNA samples were available from three locations (Pimperena, Soulouba, and Banambani), which are located within 150–340 km of each other. In contrast to the lack of differentiation within the MOPTI form, significant differentiation was detected between all three localities within the SAVANNA form (Table 2).

To examine how many loci are responsible for the observed differentiation between the chromosomal forms, Φst values were also calculated for all 166 loci individually. This analysis was performed using all 167 specimens. Of the 166 loci, 36 were significantly differentiated between BAMAKO and SAVANNA, 38 between MOPTI and SAVANNA, and 62 between BAMAKO and MOPTI. The lowest Φst values observed for individual loci for all comparisons was 0, and the highest were 0.718, 0.656, and 0.791 for BAMAKO-MOPTI, BAMAKO-SAVANNA, and SAVANNA-MOPTI, respectively.

It should be noted that the number of differentiated loci is an overestimation. Based on α = 0.05, 8.3 loci are expected to be significantly differentiated by chance alone. We did not apply a Bonferroni correction because setting the probability of a type I error for any locus at 0.05, i.e., α = 0.0003 for individual loci, would dramatically increase the probability of a type II error. In any case, the maximum number of permutations the GENALEX software allows for estimating p values is 999, and therefore an estimation of p values beyond three decimal points is not possible.

A principle component analysis (PCA) was performed using the same data set. The first three principle components represented 26.2%, 5.5%, and 3.5% of the variation, respectively. The cluster of BAMAKO and SAVANNA specimens largely overlapped and could not be distinguished from each other. However, the second principle component separates most of the MOPTI specimens from the BAMAKO and SAVANNA specimens, with the exception of five MOPTI specimens that cluster with BAMAKO/SAVANNA.

Finally, a population assignment test was performed to examine if the specimens could be assigned to the correct chromosomal form based on these five AFLP primer sets. Of 50 BAMAKO specimens, 44 were correctly assigned to the BAMAKO form (88%), with the remainder being assigned as SAVANNA. Of 62 SAVANNA specimens, 52 were assigned to correct form (83.9%), and the remaining 10 specimens were assigned to the BAMAKO form. Of 55 MOPTI specimens, 51 were correctly assigned (92.7%), and 2 specimens were assigned to both BAMAKO and SAVANNA.

DISCUSSION

A large number of AFLP primer combinations were screened for diagnostic differences between the BAMAKO and SAVANNA chromosomal forms. If we assume that each observed band represents an independent locus, approximately 13,000 loci were screened. This translates to approximately 1 marker/20 kb. However, this number is likely an overestimation because some bands could have been artifacts, i.e., noise, or some loci may produce multiple bands due to the presence of indels. However, the number of loci screened in this study was substantial. We did not observe any diagnostic differences between BAMAKO and SAVANNA.

Previous attempts to find diagnostic differences in coding and intron sequences of several genes between BAMAKO and SAVANNA also failed,5,14 although these studies examined a much smaller number of loci. To date, the only way to distinguish BAMAKO is by the presence of the fixed 2Rj, 2Rc, 2Ru, and the polymorphic 2Rb inversions.15 Considering that inversions suppress recombination, and are likely to be monophyletic,31 fixed nucleotide substitutions might be expected to be more prevalent inside inversions than elsewhere in the genome. Although the 2Rj inversion can be found in SAVANNA, none of the SAVANNA specimens we used carried it; therefore fixed nucleotide substitutions in this inversion might have been expected. The 2Rj inversion incorporates approximately 4.5% of the genome, and therefore approximately 4.5% of the number of screened loci is expected to be located within its breakpoints. Although inversions are expected to suppress recombination, double recombination events can reduce linkage between the inversion and loci located within it.32 However, such events should be relatively rare, especially if one considers the low frequency of the 2Rj inversion in the SAVANNA chromosomal form.

A smaller number of AFLP markers (~ 2,000) was also screened for diagnostic differences between the MOPTI and BAMAKO/SAVANNA. Our AFLP analysis did not detect fixed differences between these chromosomal forms. To the extent that they overlap with the M and S molecular forms, their reproductive isolation is better established based on fixed differences in the rDNA, and the low number of adult hybrids observed between the molecular forms (0.05–0.30%).4,7,33 However, fixed genetic differences appear to be limited to a small region on the X chromosome,3436 and possibly two small regions on the second chromosome.36,37 It is therefore possible that not enough markers were tested to identify the presumably very few fixed nucleotide differences between the MOPTI and the BAMAKO/SAVANNA chromosomal forms.

The AFLP markers have been used successfully to identify diagnostic differences between numerous species of plants, fungi, and animals, including many that hybridize.3842 For example, Kai and others38 using six AFLP primer sets identified five loci that together are diagnostic for three sympatric morphotypes of Sebastes inermis, the black rockfish. Garzón and others41 were able to distinguish between several Phythium species using only a single primerset, yielding 399 fragments. These investigators were also able to show distinct differences in patterns of intraspecific variation between species.

Several possible explanations can be offered for our lack of success in identifying fixed differences between the BAMAKO and SAVANNA chromosomal form. The AFLP method may not be robust enough to reliably produce all the bands present in certain individuals. However, it has been shown that AFLP generally produce very repeatable and reliable results.43 Another potential problem with using AFLP to identify diagnostic differences is the potential for size homoplasy. In studies of population structuring, this normally leads to an underestimation of genetic differentiation, but it can also reduce the probability of identifying fixed differences between forms. Although this may have played a role, it cannot explain why no fixed differences were observed if many were present.

It is also possible that no reproductive isolation exists between SAVANNA and BAMAKO. Considering the evidence for the adaptation of several 2R inversions in An. gambiae to environmental conditions such as aridity level,22 it is conceivable that differences in inversion frequencies could be maintained by selection against heterokaryotypes, and that BAMAKO is in fact a form of SAVANNA. However, if reproductive isolation exists between BAMAKO and SAVANNA, our data suggest that the forms separated very recently, with little time to accumulate fixed differences. Our data indicate that SAVANNA and MOPTI are more differentiated than BAMAKO and SAVANNA. Since only few areas of the genome are known to contain fixed differences between the M and the S forms,5,3437 it should not surprise us that no fixed differences could be found between the BAMAKO and SAVANNA chromosomal forms. The DNA micro-array technology that has recently become available for An. gambiae might be able to shed more light on this issue. Although the high cost of this technology could make it impractical for testing large numbers of samples, it could be used to identify potential markers, which subsequently could be tested on a larger sample using different methodologies.

Although our attempt to identify diagnostic differences between BAMAKO and SAVANNA using AFLP markers failed, we did observe significant genetic differentiation between the two chromosomal forms. Admittedly, due to limits on the availability of samples, the sampling scheme for this study was less than optimal. However, when comparing genetic differentiation between BAMAKO and SAVANNA in Banambani and N’Gabakoro Droit, significant differentiation was found between the forms, even though sample sizes were small for one of the forms in both localities. Also, when combining the samples from N’Gabakoro Droit and Moribabougou with those from Banambani, located approximately 90 km away, genetic differentiation was highly significant between forms. It is true that we also observed genetic differentiation within the SAVANNA form, but it was less and the geographic distances were 1.7–3.8 times larger.

The inversions found in BAMAKO are also present in the SAVANNA form, although at different frequencies and in different combinations. Whereas BAMAKO is polymorphic only for the 2Rb inversion, SAVANNA is polymorphic for all the 2R inversions. That is, SAVANNA populations are more heterogeneous with respect to the 2R inversions. If, as is generally assumed, most inversions are monophyletic and if recombination between inverted and non-inverted chromosome regions is suppressed, loci inside the inversion breakpoints will differentiate between inverted and non-inverted individuals, even in the absence of reproductive isolation between groups. The four inversions on the 2R span approximately 10% of the genome, whereas approximately 22% of the loci we studied are significantly differentiated between BAMAKO and SAVANNA. It therefore seems unlikely that the presence of the inversions at different frequencies in the two forms is responsible for the observed number of differentiated loci. However, since we do not know where in the genome the loci are located, we cannot rule this out.

Our results indicate that BAMAKO is more similar to SAVANNA than to MOPTI: the Φst values between BAMAKO and SAVANNA were lowest, and PCA was not able to differentiate samples of both forms, while most MOPTI specimens were clustered separately. Furthermore, the population assignment test assigned all misclassified BAMAKO specimens to the SAVANNA form, and all but one of the misclassified SAVANNA specimens to the BAMAKO form. Finally, the number of differentiated loci between BAMAKO and MOPTI is much lower than between BAMAKO and MOPTI.

This does not correspond to the observation by Taylor and others6 that levels of microsatellite differentiation were higher between BAMAKO versus SAVANNA than between SAVANNA and MOPTI. However, in that case the BAMAKO and SAVANNA populations used were 380 km apart and this may have affected the estimate. Our observations correspond largely with what other studies have shown. The chromosomal forms were described based on the frequency of 2R inversions, with only individuals carrying certain inversion combinations in H-W equilibrium,15 and with a marked deficiency of hybrids between forms. Karyotypes that could represent hybrids between BAMAKO and SAVANNA, as well as between SAVANNA and MOPTI, were observed regularly, whereas karyotypes that could represent hybrids between BAMAKO and MOPTI were almost absent.15 Additionally, the BAMAKO and SAVANNA forms share the rDNA S pattern.34 This clearly points to a closer relationship between BAMAKO and SAVANNA.

Two previous studies have investigated levels of gene flow between BAMAKO and MOPTI. Lanzaro and others12 compared levels of differentiation in microsatellites located on the 2R and elsewhere in the genome. Loci on the 2R had highly significant Fst values ranging from 0.042 to 0.089 between various populations of MOPTI and BAMAKO, whereas few other loci showed any significant differentiation between forms. Similarly, Tripet and others13 compared microsatellite loci located inside the j inversion with loci located on the third chromosome. Differentiation of loci inside the j inversion was highly significant between all BAMAKO and MOPTI populations, with Fst values ranging from 0.046 to 0.134. Only few comparisons showed a significant differentiation of 3rd chromosome loci, the highest Fst value being 0.028. Finally, Taylor and others6 based on 21 microsatellite markers, reported an Fst value of 0.073 between SAVANNA and BAMAKO.

Our estimates of Φst, an Fst analog, are somewhat higher than the Fst values estimated for microsatellite differentiation between MOPTI and BAMAKO. Our estimates of the level of differentiation between BAMAKO and SAVANNA, correspond closely to those reported by Taylor and others.6 Our results therefore indicate that AFLP analysis is a useful tool for detecting differentiation between these closely related populations.

It has been proposed that some species of the An. gambiae complex, as well as the various forms of An. gambiae s.s., have genomes that are mosaics. That is, various parts of the genomes show different levels of differentiation due to differences in the levels of gene flow and introgression.35,36,4446 Our observation that only a subset of loci are differentiated is consistent with this idea.

The samples included in our analysis were not all collected in the same year. It has been shown however that effective population sizes of An. gambiae in Mali, as well as in Kenya, probably range in the several thousands.6,47 Therefore, allele frequencies of neutral markers in An. gambiae are unlikely to vary substantially over the course of a few years.

Our lack of success in identifying fixed differences between natural populations of BAMAKO and SAVANNA is consistent with the recent origin of these chromosomal forms, as already hypothesized by Touré and others.15 The observed differences in gene frequencies for a subset of the studied loci, could indicate that gene flow is prevented in some areas of the genome between BAMAKO and SAVANNA, although we cannot rule out that the observed differences are due to differences in inversion frequencies.

Table 1

Sample sizes for various villages in the different sample sets used in the amplified fragment length polymorphism analysis

SavannaBamakoMopti
VillageSet 1Set 2Set 3Set 4Set 1Set 2Set 3Set 4Set 1Set 2Set 3Set 4
Banambani10552077553
Moribabougou318815
N’Gabakoro Droit4141718
Fanzana314
Selenkenyi3314366
Balama73
Soulouba20551421
Pimperena141
Total33101362301013501355
Table 2

Levels of genetic differentiation between chromosomal forms of Anopheles gambiae s.s.*

Chromosomal formsLocationΦstP
* Bam = Bamako; Sav = Savanna; Mop = Mopti; Ban = Banambani; N’G = N’Gabakoro Droit; Mor = Moribabougou; Fan = Fanzana; Pim = Pimperena; Sou = Soulouba. For sample sizes, see set 4 in Table 1.
Between forms
    1 Bam-SavAll0.0460.001
    2 Sav-MopAll0.1090.001
    3 Bam-MopAll0.1400.001
    4 Bam-SavBan0.1070.001
    5 Bam-SavN’G0.0540.022
    6 Bam-SavN’G, Mor, Ban0.0720.001
    7 Sav-MopN’G, Mor, Ban0.1300.001
    8 Bam-MopN’G, Mor, Ban0.1490.001
Within form
    9 Bam-BamN’G vs Mor0.003NS
    10 Mop-MopN’G vs Mor0.009NS
    11 Mop-MopN’G vs Fan0.002NS
    12 Mop-MopMor vs Fan0.000NS
    13 Sav-SavPim vs Sou0.0360.008
    14 Sav-SavPim vs Ban0.0440.001
    15 Sav-SavSou vs Ban0.0570.001
Figure 1.
Figure 1.

Left, Collection sites in Mali of samples used in this study. Top right, Polytene chromosome map indicating the breakpoints and size of inversions on the 2R chromosome arm in Anopheles gambiae. Bottom right, Chromosomal polymorphisms found in the BAMAKO, SAVANNA, and MOPTI chromosomal forms.

Citation: The American Journal of Tropical Medicine and Hygiene Am J Trop Med Hyg 74, 4; 10.4269/ajtmh.2006.74.641

*

Address correspondence to Michel A. Slotman, Department of Ecology and Evolutionary Biology, Yale University, 21 Sachem Street, New Haven, CT 06511-7444. E-mail: michel.slotman@yale.edu

Authors’ addresses; Michel A. Slotman, Monique M. Mendez, and Adalgisa Caccone, Department of Ecology and Evolutionary Biology, Yale University, 21 Sachem Street, New Haven CT 06511-7444, Telephone: 203-432-5259, E-mail: michel.slotman@yale.edu. Alessandra della Torre, Instituto di Parassitologia, Fondazione Pasteur-Conci Bolognetti, Università di Roma La Sapienza, P.le A. Moro 5, 00185 Rome, Italy. Guimogo Dolo, Départment d’ Epidémiologie des Affections Parasitaires, Ecole Nationale de Médicine et de Pharmacie, Bamako, BP 1805 Mali. Yeya T. Touré, World Health Organization, Geneva, CH 1211 27, Switzerland.

Acknowledgments: We are very grateful to Gregory Lanzaro for providing part of the mosquito samples used in this study. We also thank Jeffrey Powell for general support of the work and Frederic Tripet, Jonathan Marshall, and two anonymous reviewers for providing helpful comments to improve the manuscript.

Financial support: This work was supported by World Health Organization Special Program for Research and Training in Tropical Diseases (Tropical Disease Research) grant 941584980800101 to Adalgisa Caccone. Michel Slotman was supported by National Institutes of Health Grant R01 46018 to Jeffrey Powell and by the Centers for Disease Control and Prevention Fellowship Training Program in Vector-Borne Infectious Diseases (T01/CCT122306). Alesssandra Della Torre was supported by the United Nations Development Program/World Bank/World Health Organization Special Program for Research and Training in Tropical Diseases and by MUIR/COFIN funds.

REFERENCES

  • 1

    Coluzzi M, Petrarca V, Di Deco MA, 1985. Chromosomal inversion intergradation and incipient speciation in Anopheles gambiae. Boll Zool 52 :45–63.

    • Search Google Scholar
    • Export Citation
  • 2

    Coluzzi M, Sabatini A, della Torre A, Di Deco MA, Petrarca V, 2002. A polytene chromosome analysis of the Anopheles gambiae species complex. Science 298 :1415–1418.

    • Search Google Scholar
    • Export Citation
  • 3

    Favia G, della Torre A, Bagayoko M, Lanfrancotti A, Sagnon N’F, Touré YT, Coluzzi M, 1997. Molecular identifications of sympatric chromosomal forms of Anopheles gambiae and further evidence of their reproductive isolation. Insect Mol Biol 6 :377–383.

    • Search Google Scholar
    • Export Citation
  • 4

    della Torre A, Fanello C, Akogbeto M, Dossou-yovo J, Favia G, Petrarca V, Coluzzi M, 2001. Molecular evidence of incipient speciation within Anopheles gambiae s.s. in West Africa. Insect Mol Biol 10 :9–18.

    • Search Google Scholar
    • Export Citation
  • 5

    Gentile G, Slotman M, Ketmaier V, Powell JR, Caccone A, 2001. Attempts to molecularly distinguish cryptic taxa in Anopheles gambiae s.s., and the problem of taxonomic status. Insect Mol Biol 10 :25–32.

    • Search Google Scholar
    • Export Citation
  • 6

    Taylor C, Touré YT, Carnahan J, Norris DE, Dolo G, Traoré SF, Edillo FE, Lanzaro GC, 2001. Gene flow among populations of the malaria vector, Anopheles gambiae, in Mali, West Africa. Genetics 157 :743–750.

    • Search Google Scholar
    • Export Citation
  • 7

    Tripet F, Toure YT, Taylor CE, Norris DE, Dolo G, Lanzaro GC, 2001. DNA analysis of transferred sperm reveals significant levels of gene flow between molecular forms of Anopheles gambiae. Mol Ecol 10 :1725–1732.

    • Search Google Scholar
    • Export Citation
  • 8

    della Torre A, Tu Z, Petrarca V, 2005. On the distribution and genetic differentiation of Anopheles gambiae s.s. molecular forms. Insect Biochem Mol Biol 35 :755–769.

    • Search Google Scholar
    • Export Citation
  • 9

    Wang RL, Zheng L, Touré Y, Dandekar T, Kafatos F, 2001. When genetic distance matters: measuring genetic differentiation at microsatellite loci in whole-genome scans of recent and incipient species. Proc Natl Acad Sci USA 98 :10769–10774.

    • Search Google Scholar
    • Export Citation
  • 10

    Lehmann T, Licht M, Elissa N, Maega BTA, 2003. Population structure of Anopheles gambiae in Africa. J Hered 94 :133–147.

  • 11

    Stump AD, Shoener JA, Constantini C, Sagnon NF, Besansky NJ, 2005. Sex-linked differentiation between incipient species of Anopheles gambiae. Genetics 169 :1509–1519.

    • Search Google Scholar
    • Export Citation
  • 12

    Lanzaro GC, Touré YT, Carnahan J, Zheng L, Dolo G, Traoré SF, Petrarca V, Vernick KD, Taylor CE, 1998. Complexities in the genetic structure of Anopheles gambiae populations in West Africa as revealed by microsatellite DNA analysis. Proc Natl Acad Sci USA 95 :14260–14265.

    • Search Google Scholar
    • Export Citation
  • 13

    Tripet F, Dolo G, Lanzaro GC, 2005. Multilevel analyses of genetic differentiation in Anopheles gambiae s.s. reveal patterns of gene flow important for malaria-fighting mosquito projects. Genetics 169 :315–324.

    • Search Google Scholar
    • Export Citation
  • 14

    Mukabayire O, Caridi J, Wang X, Touré YT, Coluzzi M, Besansky NJ, 2001. Patterns of DNA sequence variation in chromosomally recognized taxa of Anopheles gambiae: evidence from rDNA and single-copy loci. Insect Mol Biol 10 :33–46.

    • Search Google Scholar
    • Export Citation
  • 15

    Touré YT, Petrarca V, Traoré S, Coulibaly A, Maiga HM, Sankare O, Sow M, Di Deco MA, Coluzzi M, 1998. The distribution and inversion polymorphism of chromosomally recognized taxa of the Anopheles gambiae complex in Mali, West Africa. Parassitologia 40 :477–511.

    • Search Google Scholar
    • Export Citation
  • 16

    Fanello C, Petrarca V, della Torre A, Santolamazza F, Dolo G, Coulibaly M, Alloueche A, Curtis CF, Touré YT, Coluzzi M, 2003. The pyrethroid knock-down resistance gene in the Anopheles gambiae complex in Mali and further indication of incipient speciation within An. gambiae s.s. Insect Mol Biol 12 :241–245.

    • Search Google Scholar
    • Export Citation
  • 17

    Vos P, Hogers R, Bleeker M, Reijans M, van de Lee T, Homes M, Frijters A, Pot J, Peleman J, Kuiper M, Zabeau M, 1995. AFLP: a new technique for DNA fingerprinting. Nucleic Acids Res 23 :4407–4414.

    • Search Google Scholar
    • Export Citation
  • 18

    Mendelson TC, Shaw KL 2005. Use of AFLP markers in surveys of arthropod biodiversity. Methods Enzymol 395 :161–177.

  • 19

    Luikart G, England PR, Tallmon D, Jordan S, Taberlet P, 2003. The power and promise of population genomics: from genotyping to genome typing. Nat Rev Genet 4 :981–994.

    • Search Google Scholar
    • Export Citation
  • 20

    Albertson RC, Markert JA, Danley PD, Kocher TD, 1999. Phylogeny of a rapidly evolving clade: the cichlid fishes of Lake Malawi, east Africa. Proc Natl Acad Sci USA 96 :5107–5110.

    • Search Google Scholar
    • Export Citation
  • 21

    della Torre A, 1997. Polytene chromosome preparation from Anopheline mosquitoes. Crampton JM, Beard CB, Louis C, eds. Molecular Biology of Insect Disease Vectors. London: Chapman and Hall, 329–336.

  • 22

    Coluzzi M, Sabatini A, Petrarca V, Di Deco MA, 1979. Chromosomal differentiation and adaptation to human environments in the Anopheles gambiae complex. Trans R Soc Trop Med Hyg 73 :483–497.

    • Search Google Scholar
    • Export Citation
  • 23

    Post R, Flook PK, Millest AL, 1993. Methods for the preservation of insects for DNA studies. Biochem Systematics Ecol 21 :85–92.

  • 24

    Peakall R, Smouse PE, 2001. GenAlEx version 5: Genetic Analysis in Excel. Population Genetic Software for Teaching and Research. Canberra, Australia; Australian National University. Available from http://www.anu.edu.au/BoZo/GenAlEx/

  • 25

    Excoffier L, Smouse P, Quatro J, 1992. Analysis of molecular variance inferred from metric distances among DNA haplotypes: applications to human mitochondrial DNA restriction data. Genetics 131 :479–491.

    • Search Google Scholar
    • Export Citation
  • 26

    Rolf FJ, 1994. NTSYS-pc. Numerical Taxonomy and Multivariate Analysis System. Version 1.80. Setauket, NY: Exeter Software.

  • 27

    Duchesne P, Bernatchez L, 2002. AFLPOP: a computer program for simulated and real population allocation, based on AFLP data. Mol Ecol Notes 2 :380–383.

    • Search Google Scholar
    • Export Citation
  • 28

    Vekemans X, Beauwens T, Lemaire M, Roldan-Ruiz I, 2002. Data from amplified fragment length polymorphism (AFLP) markers show indication of size homoplasy and of a relationship between degree of homoplasy and fragment size. Mol Ecol 11 :139–151.

    • Search Google Scholar
    • Export Citation
  • 29

    Munstermann LE, 1994. Unexpected genetic consequences of colonization and inbreeding-allozyme tracking in Culicidae (Diptera). Ann Entomol Soc Am 87 :157–164.

    • Search Google Scholar
    • Export Citation
  • 30

    Norris DE, Shurtleff AC, Touré YT, Lanzaro GC, 2001. Microsatellite DNA polymorphism and heterozygosity among field and laboratory populations of Anopheles gambiae s.s. (Diptera: Culicidae). J Med Entomol 38 :336–340.

    • Search Google Scholar
    • Export Citation
  • 31

    Garcia BA, Caccone A, Mathiopoulos KD, Powell JR, 1996. Inversion monophyly in African Anopheline malaria vectors. Genetics 143 :1313–1320.

    • Search Google Scholar
    • Export Citation
  • 32

    Krimbass CB, Powell JR, 1992. Drosophila Inversion Polymorphism. Boca Raton, FL: CRC Press.

  • 33

    Diabate A, Baldet T, Chandre C, Dabire KR, Kenge P, Guiguemde TR, Simard F, Guillet P, Hemingway J, Hougard JM, 2003. KDR mutation, a genetic marker to assess events of introgression between molecular M and S forms of Anopheles gambiae (Diptera: Culicidae) in the tropical savannah area of West Africa. J Med Entomol 40 :195–198.

    • Search Google Scholar
    • Export Citation
  • 34

    Favia G, Lanfrancotti A, Spanos L, Sidén-Kiamos I, Louis C, 2001. Molecular characterization of ribosomal DNA polymorphisms discriminating among chromosomal forms of Anopheles gambiae s.s. Insect Mol Biol 10 :19–23.

    • Search Google Scholar
    • Export Citation
  • 35

    Gentile G, della Torre A, Maegga B, Powell JR, Caccone A, 2002. Genetic differentiation in the African malaria vector, Anopheles gambiae s.s., and the problem of taxonomic status. Genetics 161 :1561–1578.

    • Search Google Scholar
    • Export Citation
  • 36

    Turner TL, Hahn MW, Nuzhdin SV, 2005. Genomic islands of speciation. PLoS Biol 3 :1572–1578.

  • 37

    Gentile G, Santolamazza F, Fanello C, Petrarca V, Caccone A, della Torre A, 2004. Variation in an intron sequence of the voltage-gated sodium channel gene correlates with genetic differentiation between Anopheles gambiae s.s. molecular forms. Insect Mol Biol 13 :371–377.

    • Search Google Scholar
    • Export Citation
  • 38

    Kai Y, Nakayama K, Nakabo T, 2002. Genetic differences among three colour morphotypes of the black rockfish, Sebastes inermis, inferred from mtDNA and AFLP analyses. Mol Ecol 11 :2591–2598.

    • Search Google Scholar
    • Export Citation
  • 39

    Bleeker W, 2003. Hybridization and Rorippa austriaca (Brassi-caceae) invasion in Germany. Mol Ecol 12 :1831–1841.

  • 40

    Haig SM, Mullins TD, Forsman ED, Trail PW, 2003. Genetic identification of spotted owls, barred owls and their hybrids: legal implications of hybrid identity. Conservation Biol 18 :1347–1357.

    • Search Google Scholar
    • Export Citation
  • 41

    Garzón CD, Geiser DM, Woorman GW, 2005. Diagnosis and population analysis of Pythium species using AFLP fingerprinting. Plant Dis 89 :81–89.

    • Search Google Scholar
    • Export Citation
  • 42

    Wu CA, Campbell DR, 2005. Cytoplasmic and nuclear markers reveal contrasting patterns of spatial and genetic structure in a natural Ipomopsis hybrid zone. Mol Ecol 14 :781–792.

    • Search Google Scholar
    • Export Citation
  • 43

    Jones CJ, Edwards KJ, Castaglione S, Winfield MO, Sala F, van de Weil C, Bredemeijer G, Vosman B, Matthes M, Daly A, Brettschneider R, Bettni P, Buitti M, Maestri E, Malcevschi A, Marmiroli N, Aert R, Volckaert G, Rueda J, Linacero R, Vazquez A, Karp A, 1997. Reproducibility testing of RAPD, AFLP and SSR markers in plants by a network of European laboratories. Mol Breeding 3 :381–390.

    • Search Google Scholar
    • Export Citation
  • 44

    della Torre A, Merzagora L, Powell JR, Coluzzi M, 1997. Selective introgression of paracentric inversions between two sibling species of the Anopheles gambiae complex. Genetics 246 :239–244.

    • Search Google Scholar
    • Export Citation
  • 45

    Besansky NJ, Krzywinski J, Lehmann T, Simard F, Kern M, Mukabayire O, Fontenille D, Touré YT, Sagnon N’F, 2003. Semipermeable species boundaries between Anopheles gambiae and An. arabiensis: evidence from multilocus DNA sequence variation. Proc Natl Acad Sci USA 100 :10818–10823.

    • Search Google Scholar
    • Export Citation
  • 46

    Slotman MA, della Torre A, Calzetta M, Powell JR, 2005. Differential introgression of chromosomal regions between Anopheles gambiae and An. arabiensis. Am J Trop Med Hyg 73 :326–335.

    • Search Google Scholar
    • Export Citation
  • 47

    Lehmann T, Hawley WA, Grebert H, Collins FH, 1998. The effective population size of Anopheles gambiae in Kenya: implications for population structure. Mol Biol Evol 15 :264–276.

    • Search Google Scholar
    • Export Citation
Save