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The Yin and Yang of Linkage Disequilibrium: Mapping of Genes and Nucleotides Conferring Insecticide Resistance in Insect Disease Vectors

  • William C. BlackIV
  • Norma Gorrochetegui-Escalante
  • Nadine P. Randle
  • Martin J. Donnelly
Part of the Advances in Experimental Medicine and Biology book series (AEMB, volume 627)

Abstract

Genetic technologies developed in the last 20 years have lead to novel and exciting methods to identify genes and specific nudeotides within genes that control phenotypes in field collected organisms. In this review we define and explain two of these methods: linkage disequilibrium (LD) mapping and quantitative trait nucleotide (QTN) mapping. The power to detect valid genotype-phenotype associations with LD or QTN mapping depends critically on the extent to which segregating sites in a genome assort independendy. LD mapping depends on markers being in disequilibrium with the genes that condition expression of the phenotype. In contrast, QTN mapping depends critically upon most proximal loci being at equilibrium. We show that both patterns actually exist in the genome of Anopheles gambiae, the most important malaria vector in sub-Saharan Africa while segregating sites appear to be largely in equilibrium throughout the genome of Aedes aegypti, the vector of Dengue and Yellow fever flaviviruses. We discuss additional approaches that will be needed to identify genes and nudeotides that control phenotypes in field collected organisms, focusing specifically on ongoing studies of genes conferring resistance to insecticides.

Keywords

Quantitative Trait Locus Linkage Disequilibrium Quantitative Trait Locus Mapping Malaria Vector Insecticide Resistance 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.

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References

  1. 1.
    Black WC, Baer CF, Antolin MF et al. Population genomics: Genome-wide sampling of insect populations. Annu Rev Entomol 2001; 46:441–469.PubMedCrossRefGoogle Scholar
  2. 2.
    Erickson DL, Fenster CB, Stenoien HK et al. Quantitative trait locus analyses and the study of evolutionary process. Mol Ecol 2004; 13:2505–2522.PubMedCrossRefGoogle Scholar
  3. 3.
    Stephens JC, Briscoe D, O’Brien SJ. Mapping by admixture linkage disequilibrium in human populations: Limits and guidelines. Am J Hum Genet 1994; 55:809–824.PubMedGoogle Scholar
  4. 4.
    Keim P, Diers BW, Olson TC et al. RFLP mapping in soybean: Association between marker loci and variation in quantitative traits. Genetics 1990; 126:735–742.PubMedGoogle Scholar
  5. 5.
    Osterberg MK, Shavorskaya O, Lascoux M et al. Naturally occurring indel variation in the Brassica nigra COL 1 gene is associated with variation in flowering time. Genetics 2002; 161:299–306.PubMedGoogle Scholar
  6. 6.
    Maksymowych WP, Rahman P, Reeve JP et al. Association of the IL1 gene cluster with susceptibility to ankylosing spondylitis: An analysis of three Canadian populations. Arthritis Rheum 2006; 54:974–985.PubMedCrossRefGoogle Scholar
  7. 7.
    Morton NE. Fifty years of genetic epidemiology, with special reference to Japan. J Hum Genet 2006; 51:269–277.PubMedCrossRefGoogle Scholar
  8. 8.
    Zeng Z, Zhou Y, Zhang W et al. Family-based association analysis validates chromosome 3p21 as a putative nasopharyngeal carcinoma susceptibility locus. Genet Med 2006; 8:156–160.PubMedCrossRefGoogle Scholar
  9. 9.
    Palsson A, Dodgson J, Dworkin I et al. Tests for the replication of an association between Egfr and natural variation in Drosophila melanogaster wing morphology. BMC Genet 2005; 6:44.PubMedCrossRefGoogle Scholar
  10. 10.
    Genissel A, Pastinen T, Dowell A et al. No evidence for an association between common nonsynonymous polymorphisms in delta and bristle number variation in natural and laboratory populations of Drosophila melanogaster. Genetics 2004; 166:291–306.PubMedCrossRefGoogle Scholar
  11. 11.
    Grisart B, Farnir F, Karim L et al. Genetic and functional confirmation of the causality of the DGAT1 K232A quantitative trait nucleotide in affecting milk yield and composition. Proc Natl Acad Sci USA 2004; 101:2398–2403.PubMedCrossRefGoogle Scholar
  12. 12.
    Gorrochotegui-Escalante N, Lozano-Fuentes S, Bennett KE et al. Association mapping of segregating sites in the early trypsin gene and susceptibility to dengue-2 virus in the mosquito Aedes aegypti. Insect Biochem Mol Biol 2005; 35:771–788.PubMedCrossRefGoogle Scholar
  13. 13.
    Curtis CF. Should DDT continue to be recommended for malaria vector control? Med Vet Entomol 1994; 8:107–112.PubMedCrossRefGoogle Scholar
  14. 14.
    Curtis CF, Miller JE, Hodjati MH et al. Can anything be done to maintain the effectiveness of pyrethroid-impregnated bednets against malaria vectors? Philos Trans R Soc Lond B Biol Sci 1998; 353:1769–1775.PubMedCrossRefGoogle Scholar
  15. 15.
    Donnelly MJ, Simard F, Lehmann T. Evolutionary studies of malaria vectors. Trends Parasitol 2002; 18:75–80.PubMedCrossRefGoogle Scholar
  16. 16.
    Hemingway J, Hawkes NJ, McCarroll L et al. The molecular basis of insecticide resistance in mosquitoes. Insect Biochem Mol Biol 2004; 34:653–665.PubMedCrossRefGoogle Scholar
  17. 17.
    Roberts DR, Andre RG. Insecticide resistance issues in vector-borne disease control. Am J Trop Med Hyg 1994; 50:21–34.PubMedGoogle Scholar
  18. 18.
    Kolaczinski JH, Curtis CF. Investigation of negative cross-resistance as a resistance-management tool for insecticide-treated nets. J Med Entomol 2004; 41:930–934.PubMedGoogle Scholar
  19. 19.
    Kurtak D, Meyer R, Ocran M et al. Management of insecticide resistance in control of the Simulium damnosum complex by the Onchocerciasis Control Programme, West Africa: Potential use of negative correlation between organophosphate resistance and pyrethroid susceptibility. Med Vet Entomol 1987; 1:137–146.PubMedCrossRefGoogle Scholar
  20. 20.
    Tabashnik BE. Implications of gene amplification for evolution and management of insecticide resistance. J Econ Entomol 1990; 83:1170–1176.PubMedGoogle Scholar
  21. 21.
    Kublin JG, Cortese JF, Njunju EM et al. Reemergence of chloroquine-sensitive Plasmodium falciparum malaria after cessation of chloroquine use in Malawi. J Infect Dis 2003; 187:1870–1875.PubMedCrossRefGoogle Scholar
  22. 22.
    Brogdon WG, McAllister JC. Insecticide resistance and vector control. Emerg Infect Dis 1998; 4:605–613.PubMedCrossRefGoogle Scholar
  23. 23.
    Brogdon WG, Beach RF, Barber AM et al. A generalized approach to detection of organophosphate resistance in mosquitoes. Med Vet Entomol 1992; 6:110–114.PubMedCrossRefGoogle Scholar
  24. 24.
    Brogdon WG, McAllister JC. Simplification of adult mosquito bioassays through use of time-mortality determinations in glass bottles. J Am Mosq Control Assoc 1998; 14:159–164.PubMedGoogle Scholar
  25. 25.
    Saelim V, Brogdon WG, Rojanapremsuk J et al. Bottle and biochemical assays on temephos resistance in Aedes aegypti in Thailand. Southeast Asian J Trop Med Public Health 2005; 36:417–425.PubMedGoogle Scholar
  26. 26.
    Vulule JM, Beach RF, Atieli FK et al. Elevated oxidase and esterase levels associated with permethrin tolerance in Anopheles gambiae from Kenyan villages using permethrin-impregnated nets. Med Vet Entomol 1999; 13:239–244.PubMedCrossRefGoogle Scholar
  27. 27.
    Brown SE, Severson DW, Smith LA et al. Integration of the Aedes aegypti mosquito genetic linkage and physical maps. Genetics 2001; 157:1299–1305.PubMedGoogle Scholar
  28. 28.
    Wall JD. A comparison of estimators of the population recombination rate. Mol Biol Evol 2000; 17:156–163.PubMedGoogle Scholar
  29. 29.
    Carvajal-Rodriguez A, Crandall KA, Posada D. Recombination estimation under complex evolutionary models with the coalescent composite-likelihood method. Mol Biol Evol 2006; 23:817–827.PubMedCrossRefGoogle Scholar
  30. 30.
    Hudson RR, Kreitman M, Aguade M. A test of neutral molecular evolution based on nucleotide data. Genetics 1987; 116:153–159.PubMedGoogle Scholar
  31. 31.
    Beerli P, Felsenstein J. Maximum-likelihood estimation of migration rates and effective population numbers in two populations using a coalescent approach. Genetics 1999; 152:763–773.PubMedGoogle Scholar
  32. 32.
    Beerli P, Felsenstein J. Maximum likelihood estimation of a migration matrix and effective population sizes in n subpopulations by using a coalescent approach. Proc Natl Acad Sci USA 2001; 98:4563–4568.PubMedCrossRefGoogle Scholar
  33. 33.
    Gorrochotegui-Escalante N, Gomez-Machorro C, Lozano-Fuentes S et al. Breeding structure of Aedes aegypti populations in Mexico varies by region. Am J Trop Med Hyg 2002; 66:213–222.PubMedGoogle Scholar
  34. 34.
    Lehmann T, Hawley WA, Grebert H et al. The effective population size of Anopheles gambiae in Kenya: Implications for population structure. Mol Biol Evol 1998; 15:264–276.PubMedGoogle Scholar
  35. 35.
    Ranson H, Paton MG, Jensen B et al. Genetic mapping of genes conferring permethrin resistance in the malaria vector, Anopheles gambiae. Insect Mol Biol 2004; 13:379–386.PubMedCrossRefGoogle Scholar
  36. 36.
    Ohta T. Linkage disequilibrium due to random genetic drift in finite subdivided populations. Proc Natl Acad Sci USA 1982; 79:1940–1944.PubMedCrossRefGoogle Scholar
  37. 37.
    Turner TL, Hahn MW, Nuzhdin SV. Genomic islands of speciation in Anopheles gambiae. PLoS Biol 2005; 3:e285.PubMedCrossRefGoogle Scholar
  38. 38.
    Tripet F, Toure YT, Taylor CE et al. DNA analysis of transferred sperm reveals significant levels of gene flow between molecular forms of Anopheles gambiae. Mol Ecol 2001; 10:1725–1732.PubMedCrossRefGoogle Scholar
  39. 39.
    Stump AD, Fitzpatrick MC, Lobo NF et al. Centromere-proximal differentiation and speciation in Anopheles gambiae. Proc Natl Acad Sci USA 2005; 102:15930–15935.PubMedCrossRefGoogle Scholar
  40. 40.
    Stump AD, Shoener JA, Costantini C et al. Sex-linked differentiation between incipient species of Anopheles gambiae. Genetics 2005; 169:1509–1519.PubMedCrossRefGoogle Scholar
  41. 41.
    Nair S, Williams JT, Brockman A et al. A selective sweep driven by pyrimethamine treatment in southeast asian malaria parasites. Mol Biol Evol 2003; 20:1526–1536.PubMedCrossRefGoogle Scholar
  42. 42.
    Roper C, Pearce R, Nair S et al. Intercontinental spread of pyrimethamine-resistant malaria. Science 2004; 305:1124.PubMedCrossRefGoogle Scholar
  43. 43.
    Wootton JC, Feng X, Ferdig MT et al. Genetic diversity and chloroquine selective sweeps in Plasmodium falciparum. Nature 2002; 418:320–323.PubMedCrossRefGoogle Scholar
  44. 44.
    Harr B, Kauer M, Schlotterer C. Hitchhiking mapping: A population-based fine-mapping strategy for adaptive mutations in Drosophila melanogaster. Proc Natl Acad Sci USA 2002; 99:12949–12954.PubMedCrossRefGoogle Scholar
  45. 45.
    Black W, Severson D. Genetics of vector competence. In: Marquardt W, ed. Biology of Disease Vectors. 2nd ed. Harcourt Academic Press, 2002.Google Scholar
  46. 46.
    Menge DM, Zhong D, Guda T et al. Quantitative trait loci controlling refractoriness to plasmodium falciparum in natural anopheles gambiae from a malaria endemic region in western kenya. Genetics 2006.Google Scholar
  47. 47.
    Zheng L, Wang S, Romans P et al. Quantitative trait loci in Anopheles gambiae controlling the encapsulation response against Plasmodium cynomolgi Ceylon. BMC Genet 2003; 4:16.PubMedCrossRefGoogle Scholar
  48. 48.
    Gorman MJ, Severson DW, Cornel AJ et al. Mapping a quantitative trait locus involved in melanotic encapsulation of foreign bodies in the malaria vector, Anopheles gambiae. Genetics 1997; 146:965–971.PubMedGoogle Scholar
  49. 49.
    Niare O, Markianos K, Volz J et al. Genetic loci affecting resistance to human malaria parasites in a West African mosquito vector population. Science 2002; 298:213–216.PubMedCrossRefGoogle Scholar
  50. 50.
    Ranson H, Jensen B, Wang X et al. Genetic mapping of two loci affecting DDT resistance in the malaria vector Anopheles gambiae. Insect Mol Biol 2000; 9:499–507.PubMedCrossRefGoogle Scholar
  51. 51.
    Slotman M, Delia Torre A, Powell JR. Female sterility in hybrids between Anopheles gambiae and A. arabiensis, and the causes of Haldane’s rule. Evolution Int J Org Evolution 2005; 59:1016–1026.Google Scholar
  52. 52.
    Slotman M, Delia Torre A, Powell JR. The genetics of inviability and male sterility in hybrids between Anopheles gambiae and An. arabiensis. Genetics 2004; 167:275–287.PubMedCrossRefGoogle Scholar
  53. 53.
    Severson DW, Mori A, Zhang Y et al. Chromosomal mapping of two loci affecting filarial worm susceptibility in Aedes aegypti. Insect Mol Biol 1994; 3:67–72.PubMedCrossRefGoogle Scholar
  54. 54.
    Beerntsen BT, Severson DW, Klinkhammer JA et al. Aedes aegypti: A quantitative trait locus (QTL) influencing filarial worm intensity is linked to QTL for susceptibility to other mosquito-borne pathogens. Exp Parasitol 1995; 81:355–362.PubMedCrossRefGoogle Scholar
  55. 55.
    Severson DW, Thathy V, Mori A et al. Restriction fragment length polymorphism mapping of quantitative trait loci for malaria parasite susceptibility in the mosquito Aedes aegypti. Genetics 1995; 139:1711–1717.PubMedGoogle Scholar
  56. 56.
    Severson DW, Zaitlin D, Kassner VA. Targeted identification of markers linked to malaria and filarioid nematode parasite resistance genes in the mosquito Aedes aegypti. Genet Res 1999; 73:217–224.PubMedCrossRefGoogle Scholar
  57. 57.
    Zhong D, Menge DM, Temu EA et al. AFLP mapping of quantitative trait loci for malaria parasite susceptibility in the yellow fever mosquito, Aedes aegypti. Genetics 2006.Google Scholar
  58. 58.
    Bennett KE, Flick D, Fleming KH et al. Quantitative trait loci that control dengue-2 virus dissemination in the mosquito Aedes aegypti. Genetics 2005; 170:185–194.PubMedCrossRefGoogle Scholar
  59. 59.
    Gomez-Machorro C, Bennett KE, del Lourdes Munoz M et al. Quantitative trait loci affecting dengue midgut infection barriers in an advanced intercross line of Aedes aegypti. Insect Mol Biol 2004; 13:637–648.PubMedCrossRefGoogle Scholar
  60. 60.
    Bosio CF, Fulton RE, Salasek ML et al. Quantitative trait loci that control vector competence for dengue-2 virus in the mosquito Aedes aegypti. Genetics 2000; 156:687–698.PubMedGoogle Scholar
  61. 61.
    Dana AN, Hong YS, Kern MK et al. Gene expression patterns associated with blood-feeding in the malaria mosquito Anopheles gambiae. BMC Genomics 2005; 6:5.PubMedCrossRefGoogle Scholar
  62. 62.
    David JP, Strode C, Vontas J et al. The Anopheles gambiae detoxification chip: A highly specific microarray to study metabolic-based insecticide resistance in malaria vectors. Proc Natl Acad Sci USA 2005; 102:4080–4084.PubMedCrossRefGoogle Scholar
  63. 63.
    Chen H, Wang J, Liang P et al. Microarray analysis for identification of Plasmodium-refractoriness candidate genes in mosquitoes. Genome 2004; 47:1061–1070.PubMedCrossRefGoogle Scholar
  64. 64.
    Hall N, Karras M, Raine JD et al. A comprehensive survey of the Plasmodium life cycle by genomic, transcriptomic, and proteomic analyses. Science 2005; 307:82–86.PubMedCrossRefGoogle Scholar
  65. 65.
    Sanders HR, Evans AM, Ross LS et al. Blood meal induces global changes in midgut gene expression in the disease vector, Aedes aegypti. Insect Biochem Mol Biol 2003; 331105–1122.PubMedCrossRefGoogle Scholar
  66. 66.
    Ranson H, Claudianos C, Ortelli F et al. Evolution of supergene families associated with insecticide resistance. Science 2002; 298:179–181.PubMedCrossRefGoogle Scholar
  67. 67.
    Christophides GK, Zdobnov E, Barillas-Mury C et al. Immunity-related genes and gene families in Anopheles gambiae. Science 2002; 298:159–165.PubMedCrossRefGoogle Scholar
  68. 68.
    Morel CM, Toure YT, Dobrokhotov B et al. The mosquito genome—a breakthrough for public health. Science 2002; 298:79.PubMedCrossRefGoogle Scholar
  69. 69.
    Zdobnov EM, von Mering C, Letunic I et al. Comparative genome and proteome analysis of Anopheles gambiae and Drosophila melanogaster. Science 2002; 298:149–159.PubMedCrossRefGoogle Scholar
  70. 70.
    Dimopoulos G, Christophides GK, Meister S et al. Genome expression analysis of Anopheles gambiae: Responses to injury, bacterial challenge, and malaria infection. Proc Natl Acad Sci USA 2002; 99:8814–8819.PubMedCrossRefGoogle Scholar
  71. 71.
    Kemp CA, Flanagan JU, van Eldik AJ et al. Validation of model cytochrome P450 2D6: An in silico tool for predicting metabolism and inhibition. J Med Chem 2004; 47:5340–5346.PubMedCrossRefGoogle Scholar
  72. 72.
    Lycett GJ, McLaughlin A, Ranson H et al. Anopheles gambiae P450 reductase is highly expressed in oenocytes and in vivo knock down increases permethrin susceptibility. Insect Mol Biol 2006; 15:321–327.PubMedCrossRefGoogle Scholar
  73. 73.
    Ding Y, Ortelli F, Rossiter LC et al. The Anopheles gambiae glutathione transferase supergene family: Annotation, phylogeny and expression profiles. BMC Genomics 2003; 4:35.PubMedCrossRefGoogle Scholar
  74. 74.
    Lumjuan N, McCarroll L, Prapanthadara LA et al. Elevated activity of an Epsilon class glutathione transferase confers DDT resistance in the dengue vector, Aedes aegypti. Insect Biochem Mol Biol 2005; 35:861–871.PubMedCrossRefGoogle Scholar
  75. 75.
    ffrench-Constant RH, Daborn PJ, Le Goff G. The genetics and genomics of insecticide resistance. Trends Genet 2004; 20:163–170.PubMedCrossRefGoogle Scholar
  76. 76.
    Nene V, Wortman JR, Lawson D et al. Genome sequence of Aedes aegypti, a major arborvirus vector. Science 2007; 316:1718–1723.PubMedCrossRefGoogle Scholar
  77. 77.
    Strode C, Wondji CS, David J-P et al. Genomic analysis of detoxification genes in the mosquito Aedes aegypti. Insect Biochem Mol Biol 2007; 2008, 38(1):1130123.Google Scholar

Copyright information

© Landes Bioscience and Springer Science+Business Media 2008

Authors and Affiliations

  • William C. BlackIV
    • 1
  • Norma Gorrochetegui-Escalante
    • 1
  • Nadine P. Randle
    • 2
  • Martin J. Donnelly
    • 2
  1. 1.Department of Microbiology, Immunology and PathologyColorado State UniversityFort CollinsUSA
  2. 2.Vector GroupLiverpool School of Tropical MedicinePembroke PlaceUK

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