An Africa-wide genomic evolution of insecticide resistance in the malaria vector Anopheles funestus involves selective sweeps, copy number variations, gene conversion and transposons


Autoři: Gareth D. Weedall aff001;  Jacob M. Riveron aff001;  Jack Hearn aff001;  Helen Irving aff001;  Colince Kamdem aff004;  Caroline Fouet aff004;  Bradley J. White aff005;  Charles S. Wondji aff001
Působiště autorů: Vector Biology Department, Liverpool School of Tropical Medicine (LSTM), Pembroke Place, Liverpool, United Kingdom aff001;  School of Biological and Environmental Sciences, Liverpool John Moores University, Liverpool, United Kingdom aff002;  School of Natural Sciences and Psychology, Liverpool John Moores University, Liverpool, United Kingdom aff002;  Centre for Research in Infectious Diseases (CRID), Yaoundé, Cameroon aff003;  LSTM Research Unit at CRID, Yaoundé, Cameroon aff004;  Department of Entomology, University of California, Riverside, California, United States of America aff005;  Verily Life Sciences, South San Francisco, California, United States of America aff006
Vyšlo v časopise: An Africa-wide genomic evolution of insecticide resistance in the malaria vector Anopheles funestus involves selective sweeps, copy number variations, gene conversion and transposons. PLoS Genet 16(6): e32767. doi:10.1371/journal.pgen.1008822
Kategorie: Research Article
doi: 10.1371/journal.pgen.1008822

Souhrn

Insecticide resistance in malaria vectors threatens to reverse recent gains in malaria control. Deciphering patterns of gene flow and resistance evolution in malaria vectors is crucial to improving control strategies and preventing malaria resurgence. A genome-wide survey of Anopheles funestus genetic diversity Africa-wide revealed evidences of a major division between southern Africa and elsewhere, associated with different population histories. Three genomic regions exhibited strong signatures of selective sweeps, each spanning major resistance loci (CYP6P9a/b, GSTe2 and CYP9K1). However, a sharp regional contrast was observed between populations correlating with gene flow barriers. Signatures of complex molecular evolution of resistance were detected with evidence of copy number variation, transposon insertion and a gene conversion between CYP6P9a/b paralog genes. Temporal analyses of samples before and after bed net scale up suggest that these genomic changes are driven by this control intervention. Multiple independent selective sweeps at the same locus in different parts of Africa suggests that local evolution of resistance in malaria vectors may be a greater threat than trans-regional spread of resistance haplotypes.

Klíčová slova:

Africa – Benin – Genetic loci – Ghana – Haplotypes – Population genetics – Sequence alignment – Uganda


Zdroje

1. Bhatt S, Weiss DJ, Cameron E, Bisanzio D, Mappin B, Dalrymple U, et al. The effect of malaria control on Plasmodium falciparum in Africa between 2000 and 2015. Nature. 2015;526(7572):207–11. doi: 10.1038/nature15535 26375008.

2. Ranson H, Lissenden N. Insecticide Resistance in African Anopheles Mosquitoes: A Worsening Situation that Needs Urgent Action to Maintain Malaria Control. Trends Parasitol. 2016;32(3):187–96. doi: 10.1016/j.pt.2015.11.010 26826784.

3. WHO. World Malaria Report 20182018.

4. Anopheles gambiae Genomes C, Data analysis g, Partner working g, Sample c-A, Burkina F, Cameroon, et al. Genetic diversity of the African malaria vector Anopheles gambiae. Nature. 2017;552(7683):96–100. doi: 10.1038/nature24995 29186111.

5. Barnes KG, Weedall GD, Ndula M, Irving H, Mzihalowa T, Hemingway J, et al. Genomic Footprints of Selective Sweeps from Metabolic Resistance to Pyrethroids in African Malaria Vectors Are Driven by Scale up of Insecticide-Based Vector Control. PLoS Genet. 2017;13(2):e1006539. doi: 10.1371/journal.pgen.1006539 28151952.

6. Weedall GD, Mugenzi LMJ, Menze BD, Tchouakui M, Ibrahim SS, Amvongo-Adjia N, et al. A cytochrome P450 allele confers pyrethroid resistance on a major African malaria vector, reducing insecticide-treated bednet efficacy. Sci Transl Med. 2019;11(484). doi: 10.1126/scitranslmed.aat7386 30894503.

7. Sinka ME, Bangs MJ, Manguin S, Coetzee M, Mbogo CM, Hemingway J, et al. The dominant Anopheles vectors of human malaria in Africa, Europe and the Middle East: occurrence data, distribution maps and bionomic precis. Parasit Vectors. 2010;3:117. doi: 10.1186/1756-3305-3-117 21129198; PubMed Central PMCID: PMC3016360.

8. Coetzee M, Koekemoer LL. Molecular systematics and insecticide resistance in the major African malaria vector Anopheles funestus. Annu Rev Entomol. 2013;58:393–412. doi: 10.1146/annurev-ento-120811-153628 23317045.

9. Djouaka R, Riveron JM, Yessoufou A, Tchigossou G, Akoton R, Irving H, et al. Multiple insecticide resistance in an infected population of the malaria vector Anopheles funestus in Benin. Parasit Vectors. 2016;9:453. doi: 10.1186/s13071-016-1723-y 27531125; PubMed Central PMCID: PMC4987972.

10. Menze BD, Riveron JM, Ibrahim SS, Irving H, Antonio-Nkondjio C, Awono-Ambene PH, et al. Multiple Insecticide Resistance in the Malaria Vector Anopheles funestus from Northern Cameroon Is Mediated by Metabolic Resistance Alongside Potential Target Site Insensitivity Mutations. PLoS One. 2016;11(10):e0163261. doi: 10.1371/journal.pone.0163261 27723825; PubMed Central PMCID: PMC5056689.

11. Riveron JM, Tchouakui M, Mugenzi LMJ, Menze BD, Chiang M, Wondji CS. Insecticide Resistance in Malaria Vectors: An Update at a Global Scale. In: Manguin S, dev V, editors. Towards Malaria Elimination—A Leap Forward: IntechOpen; 2018.

12. Riveron JM, Watsenga F, Irving H, Irish SR, Wondji CS. High Plasmodium Infection Rate and Reduced Bed Net Efficacy in Multiple Insecticide-Resistant Malaria Vectors in Kinshasa, Democratic Republic of Congo. The Journal of infectious diseases. 2018;217(2):320–8. doi: 10.1093/infdis/jix570 29087484; PubMed Central PMCID: PMC5853898.

13. Riveron JM, Ibrahim SS, Mulamba C, Djouaka R, Irving H, Wondji MJ, et al. Genome-Wide Transcription and Functional Analyses Reveal Heterogeneous Molecular Mechanisms Driving Pyrethroids Resistance in the Major Malaria Vector Anopheles funestus Across Africa. G3 (Bethesda). 2017;7(6):1819–32. doi: 10.1534/g3.117.040147 28428243; PubMed Central PMCID: PMC5473761.

14. Barnes KG, Irving H, Chiumia M, Mzilahowa T, Coleman M, Hemingway J, et al. Restriction to gene flow is associated with changes in the molecular basis of pyrethroid resistance in the malaria vector Anopheles funestus. Proc Natl Acad Sci U S A. 2017;114(2):286–91. doi: 10.1073/pnas.1615458114 28003461; PubMed Central PMCID: PMC5240677.

15. Michel AP, Ingrasci MJ, Schemerhorn BJ, Kern M, Le Goff G, Coetzee M, et al. Rangewide population genetic structure of the African malaria vector Anopheles funestus. Mol Ecol. 2005;14(14):4235–48. doi: 10.1111/j.1365-294X.2005.02754.x 16313589.

16. Temu EA, Hunt RH, Coetzee M. Microsatellite DNA polymorphism and heterozygosity in the malaria vector mosquito Anopheles funestus (Diptera: Culicidae) in east and southern Africa. Acta Trop. 2004;90(1):39–49. doi: 10.1016/j.actatropica.2003.10.011 14739021.

17. Garros C, Koekemoer LL, Kamau L, Awolola TS, Van Bortel W, Coetzee M, et al. Restriction fragment length polymorphism method for the identification of major African and Asian malaria vectors within the Anopheles funestus and An. minimus groups. Am J Trop Med Hyg. 2004;70(3):260–5. Epub 2004/03/20. 70/3/260 [pii]. 15031514.

18. Cohuet A, Dia I, Simard F, Raymond M, Fontenille D. Population structure of the malaria vector Anopheles funestus in Senegal based on microsatellite and cytogenetic data. Insect Mol Biol. 2004;13(3):251–8. doi: 10.1111/j.0962-1075.2004.00482.x 15157226.

19. Koekemoer LL, Kamau L, Garros C, Manguin S, Hunt RH, Coetzee M. Impact of the Rift Valley on restriction fragment length polymorphism typing of the major African malaria vector Anopheles funestus (Diptera: Culicidae). J Med Entomol. 2006;43(6):1178–84. Epub 2006/12/14. doi: 10.1603/0022-2585(2006)43[1178:iotrvo]2.0.co;2 17162950.

20. Wondji CS, Dabire RK, Tukur Z, Irving H, Djouaka R, Morgan JC. Identification and distribution of a GABA receptor mutation conferring dieldrin resistance in the malaria vector Anopheles funestus in Africa. Insect Biochem Mol Biol. 2011;41(7):484–91. Epub 2011/04/20. S0965-1748(11)00080-4 [pii] doi: 10.1016/j.ibmb.2011.03.012 21501685.

21. Riveron JM, Yunta C, Ibrahim SS, Djouaka R, Irving H, Menze BD, et al. A single mutation in the GSTe2 gene allows tracking of metabolically-based insecticide resistance in a major malaria vector. Genome Biol. 2014;15(2):R27. doi: 10.1186/gb-2014-15-2-r27 24565444.

22. Mugenzi LMJ, Menze BD, Tchouakui M, Wondji MJ, Irving H, Tchoupo M, et al. Cis-regulatory CYP6P9b P450 variants associated with loss of insecticide-treated bed net efficacy against Anopheles funestus. Nat Commun. 2019;10(1):4652. doi: 10.1038/s41467-019-12686-5 31604938.

23. Ibrahim SS, Ndula M, Riveron JM, Irving H, Wondji CS. The P450 CYP6Z1 confers carbamate/pyrethroid cross-resistance in a major African malaria vector beside a novel carbamate-insensitive N485I acetylcholinesterase-1 mutation. Mol Ecol. 2016;25(14):3436–52. doi: 10.1111/mec.13673 27135886; PubMed Central PMCID: PMC4950264.

24. Lehmann T, Licht M, Elissa N, Maega BT, Chimumbwa JM, Watsenga FT, et al. Population Structure of Anopheles gambiae in Africa. J Hered. 2003;94(2):133–47. doi: 10.1093/jhered/esg024 12721225.

25. Wondji CS, Irving H, Morgan J, Lobo NF, Collins FH, Hunt RH, et al. Two duplicated P450 genes are associated with pyrethroid resistance in Anopheles funestus, a major malaria vector. Genome Res. 2009;19(3):452–9. Epub 2009/02/07. gr.087916.108 [pii] doi: 10.1101/gr.087916.108 19196725.

26. Sharakhov IV, Serazin AC, Grushko OG, Dana A, Lobo N, Hillenmeyer ME, et al. Inversions and gene order shuffling in Anopheles gambiae and A. funestus. Science. 2002;298(5591):182–5. doi: 10.1126/science.1076803 12364797.

27. Ibrahim SS, Riveron JM, Bibby J, Irving H, Yunta C, Paine MJ, et al. Allelic Variation of Cytochrome P450s Drives Resistance to Bednet Insecticides in a Major Malaria Vector. PLoS Genet. 2015;11(10):e1005618. doi: 10.1371/journal.pgen.1005618 26517127; PubMed Central PMCID: PMC4627800.

28. Vontas J, Grigoraki L, Morgan J, Tsakireli D, Fuseini G, Segura L, et al. Rapid selection of a pyrethroid metabolic enzyme CYP9K1 by operational malaria control activities. Proc Natl Acad Sci U S A. 2018;115(18):4619–24. doi: 10.1073/pnas.1719663115 29674455; PubMed Central PMCID: PMC5939083.

29. Riveron JM, Irving H, Ndula M, Barnes KG, Ibrahim SS, Paine MJ, et al. Directionally selected cytochrome P450 alleles are driving the spread of pyrethroid resistance in the major malaria vector Anopheles funestus. Proc Natl Acad Sci U S A. 2013;110(1):252–7. doi: 10.1073/pnas.1216705110 23248325; PubMed Central PMCID: PMC3538203.

30. Lehmann T, Blackston CR, Besansky NJ, Escalante AA, Collins FH, Hawley WA. The Rift Valley complex as a barrier to gene flow for Anopheles gambiae in Kenya: the mtDNA perspective. J Hered. 2000;91(2):165–8. doi: 10.1093/jhered/91.2.165 10768135.

31. Kamdem C, Fouet C, White BJ. Chromosome arm-specific patterns of polymorphism associated with chromosomal inversions in the major African malaria vector, Anopheles funestus. Mol Ecol. 2017;26(20):5552–66. doi: 10.1111/mec.14335 28833796; PubMed Central PMCID: PMC5927613.

32. Hunt R, Edwardes M, Coetzee M. Pyrethroid resistance in southern African Anopheles funestus extends to Likoma Island in Lake Malawi. Parasit Vectors. 2010;3:122. Epub 2011/01/05. 1756-3305-3-122 [pii] doi: 10.1186/1756-3305-3-122 21192834; PubMed Central PMCID: PMC3020165.

33. Riveron JM, Chiumia M, Menze BD, Barnes KG, Irving H, Ibrahim SS, et al. Rise of multiple insecticide resistance in Anopheles funestus in Malawi: a major concern for malaria vector control. Malar J. 2015;14(1):344. doi: 10.1186/s12936-015-0877-y 26370361; PubMed Central PMCID: PMC4570681.

34. Mulamba C, Riveron JM, Ibrahim SS, Irving H, Barnes KG, Mukwaya LG, et al. Widespread pyrethroid and DDT resistance in the major malaria vector Anopheles funestus in East Africa is driven by metabolic resistance mechanisms. PLoS One. 2014;9(10):e110058. doi: 10.1371/journal.pone.0110058 25333491; PubMed Central PMCID: PMC4198208.

35. Schlenke TA, Begun DJ. Strong selective sweep associated with a transposon insertion in Drosophila simulans. Proc Natl Acad Sci U S A. 2004;101(6):1626–31. Epub 2004/01/28. doi: 10.1073/pnas.0303793101 [pii]. 14745026; PubMed Central PMCID: PMC341797.

36. Ibrahim SS, Amvongo-Adjia N, Wondji MJ, Irving H, Riveron JM, Wondji CS. Pyrethroid Resistance in the Major Malaria Vector Anopheles funestus is Exacerbated by Overexpression and Overactivity of the P450 CYP6AA1 Across Africa. Genes (Basel). 2018;9(3). doi: 10.3390/genes9030140 29498712; PubMed Central PMCID: PMC5867861.

37. Hunt RH, Brooke BD, Pillay C, Koekemoer LL, Coetzee M. Laboratory selection for and characteristics of pyrethroid resistance in the malaria vector Anopheles funestus. Med Vet Entomol. 2005;19(3):271–5. doi: 10.1111/j.1365-2915.2005.00574.x 16134975.

38. Riveron JM, Osae M, Egyir-Yawson A, Irving H, Ibrahim SS, Wondji CS. Multiple insecticide resistance in the major malaria vector Anopheles funestus in southern Ghana: implications for malaria control. Parasit Vectors. 2016;9(1):504. doi: 10.1186/s13071-016-1787-8 27628765; PubMed Central PMCID: PMC5024453.

39. Menze BD, Wondji MJ, Tchapga W, Tchoupo M, Riveron JM, Wondji CS. Bionomics and insecticides resistance profiling of malaria vectors at a selected site for experimental hut trials in central Cameroon. Malar J. 2018;17(1):317. doi: 10.1186/s12936-018-2467-2 30165863; PubMed Central PMCID: PMC6117958.

40. Riveron JM, Huijben S, Tchapga W, Tchouakui M, Wondji MM, Tchoupo M, et al. Escalation of pyrethroid resistance in the malaria vector Anopheles funestus induces a loss of efficacy of PBO-based insecticide-treated nets in Mozambique. The Journal of infectious diseases. 2019. doi: 10.1093/infdis/jiz139 30923819.

41. Livak KJ. Organization and mapping of a sequence on the Drosophila melanogaster X and Y chromosomes that is transcribed during spermatogenesis. Genetics. 1984;107(4):611–34. Epub 1984/08/01. 6430749; PubMed Central PMCID: PMC1202380.

42. Peterson BK, Weber JN, Kay EH, Fisher HS, Hoekstra HE. Double digest RADseq: an inexpensive method for de novo SNP discovery and genotyping in model and non-model species. PLoS One. 2012;7(5):e37135. Epub 2012/06/08. doi: 10.1371/journal.pone.0037135 22675423; PubMed Central PMCID: PMC3365034.

43. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetjournal. 2011;17:10–2.

44. Joshi NA, Fass JN. Joshi NA, Fass JN. (2011). Sickle: A sliding-window, adaptive, quality-based trimming tool for FastQ files Available at https://githubcom/najoshi/sickle. 2011; (Version 1.33) [Software].

45. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9(4):357–9. doi: 10.1038/nmeth.1923 22388286; PubMed Central PMCID: PMC3322381.

46. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The Sequence Alignment/Map format and SAMtools. Bioinformatics. 2009;25(16):2078–9. doi: 10.1093/bioinformatics/btp352 19505943; PubMed Central PMCID: PMC2723002.

47. Kofler R, Pandey RV, Schlotterer C. PoPoolation2: identifying differentiation between populations using sequencing of pooled DNA samples (Pool-Seq). Bioinformatics. 2011;27(24):3435–6. doi: 10.1093/bioinformatics/btr589 22025480; PubMed Central PMCID: PMC3232374.

48. Wei Z, Wang W, Hu P, Lyon GJ, Hakonarson H. SNVer: a statistical tool for variant calling in analysis of pooled or individual next-generation sequencing data. Nucleic Acids Res. 2011;39(19):e132. doi: 10.1093/nar/gkr599 21813454; PubMed Central PMCID: PMC3201884.

49. Li H, Durbin R. Fast and accurate short read alignment with Burrows-Wheeler transform. Bioinformatics. 2009;25(14):1754–60. Epub 2009/05/20. doi: 10.1093/bioinformatics/btp324 19451168; PubMed Central PMCID: PMC2705234.

50. Koboldt DC, Chen K, Wylie T, Larson DE, McLellan MD, Mardis ER, et al. VarScan: variant detection in massively parallel sequencing of individual and pooled samples. Bioinformatics. 2009;25(17):2283–5. Epub 2009/06/23. doi: 10.1093/bioinformatics/btp373 19542151; PubMed Central PMCID: PMC2734323.

51. Li H. A statistical framework for SNP calling, mutation discovery, association mapping and population genetical parameter estimation from sequencing data. Bioinformatics. 2011;27(21):2987–93. Epub 2011/09/10. doi: 10.1093/bioinformatics/btr509 21903627; PubMed Central PMCID: PMC3198575.

52. Hivert V, Leblois R, Petit EJ, Gautier M, Vitalis R. Measuring Genetic Differentiation from Pool-seq Data. Genetics. 2018;210(1):315–30. Epub 2018/08/01. doi: 10.1534/genetics.118.300900 30061425; PubMed Central PMCID: PMC6116966.

53. Pickrell JK, Pritchard JK. Inference of population splits and mixtures from genome-wide allele frequency data. PLoS Genet. 2012;8(11):e1002967. Epub 2012/11/21. doi: 10.1371/journal.pgen.1002967 23166502; PubMed Central PMCID: PMC3499260.

54. Catchen J, Hohenlohe PA, Bassham S, Amores A, Cresko WA. Stacks: an analysis tool set for population genomics. Mol Ecol. 2013;22(11):3124–40. doi: 10.1111/mec.12354 23701397; PubMed Central PMCID: PMC3936987.

55. Pritchard JK, Stephens M, Donnelly P. Inference of population structure using multilocus genotype data. Genetics. 2000;155(2):945–59. 10835412.

56. Earl DA, vonHoldt BM. STRUCTURE HARVESTER: a website and program for visualizing STRUCTURE output and implementing the Evanno method. Conservation Genetics Resources. 2012;4:359–61.

57. Evanno G, Regnaut S, Goudet J. Detecting the number of clusters of individuals using the software STRUCTURE: a simulation study. Mol Ecol. 2005;14(8):2611–20. doi: 10.1111/j.1365-294X.2005.02553.x 15969739.

58. Jakobsson M, Rosenberg NA. CLUMPP: a cluster matching and permutation program for dealing with label switching and multimodality in analysis of population structure. Bioinformatics. 2007;23(14):1801–6. doi: 10.1093/bioinformatics/btm233 17485429.

59. Rousset F. genepop'007: a complete re-implementation of the genepop software for Windows and Linux. Mol Ecol Resour. 2008;8(1):103–6. doi: 10.1111/j.1471-8286.2007.01931.x 21585727.

60. Jombart T. adegenet: a R package for the multivariate analysis of genetic markers. Bioinformatics. 2008;24(11):1403–5. doi: 10.1093/bioinformatics/btn129 18397895.

61. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, et al. Versatile and open software for comparing large genomes. Genome Biol. 2004;5(2):R12. doi: 10.1186/gb-2004-5-2-r12 14759262; PubMed Central PMCID: PMC395750.

62. Edgar RC. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 2004;32(5):1792–7. doi: 10.1093/nar/gkh340 15034147; PubMed Central PMCID: PMC390337.

63. Gouy M, Guindon S, Gascuel O. SeaView version 4: A multiplatform graphical user interface for sequence alignment and phylogenetic tree building. Mol Biol Evol. 2010;27(2):221–4. doi: 10.1093/molbev/msp259 19854763.

64. Felsenstein J. PHYLIP (Phylogeny Inference Package) version 3.6. Distributed by the author. Department of Genome Sciences, University of Washington, Seattle.


Článek vyšel v časopise

PLOS Genetics


2020 Číslo 6

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Přihlášení
Zapomenuté heslo

Nemáte účet?  Registrujte se

Zapomenuté heslo

Zadejte e-mailovou adresu se kterou jste vytvářel(a) účet, budou Vám na ni zaslány informace k nastavení nového hesla.

Přihlášení

Nemáte účet?  Registrujte se