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Annual Review of Phytopathology

Volume 55, 2017

Exploiting Genetic Information to Trace Plant Virus Dispersal in Landscapes

Abstract

During the past decade, knowledge of pathogen life history has greatly benefited from the advent and development of molecular epidemiology. This branch of epidemiology uses information on pathogen variation at the molecular level to gain insights into a pathogen's niche and evolution and to characterize pathogen dispersal within and between host populations. Here, we review molecular epidemiology approaches that have been developed to trace plant virus dispersal in landscapes. In particular, we highlight how virus molecular epidemiology, nourished with powerful sequencing technologies, can provide novel insights at the crossroads between the blooming fields of landscape genetics, phylogeography, and evolutionary epidemiology. We present existing approaches and their limitations and contributions to the understanding of plant virus epidemiology.

Keyword(s): high-throughput sequencing, host range, invasion pathway, outbreak, transmission tree, vector
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2017-08-04
2024-04-20
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Literature Cited

  1. Almeida RP, Bennett GM, Anhalt MD, Tsai CW, O'Grady P. 1.  2009. Spread of an introduced vector-borne banana virus in Hawaii. Mol. Ecol. 18:1136–46 [Google Scholar]
  2. Anderson RM, May RM. 2.  1992. Infectious Diseases of Humans: Dynamics and Control Oxford: Oxford Univ. Press
  3. Avise JC. 3.  2000. Phylogeography: The History and Formation of Species Cambridge, MA: Harvard Univ. Press
  4. Baele G, Suchard MA, Rambaut A, Lemey P. 4.  2017. Emerging concepts of data integration in pathogen phylodynamics. Syst. Biol. 66:1e47–65 [Google Scholar]
  5. Balkenhol N, Waits LP, Dezzani RJ. 5.  2009. Statistical approaches in landscape genetics: an evaluation of methods for linking landscape and genetic data. Ecography 32:5818–30 [Google Scholar]
  6. Bebber DP, Holmes T, Gurr SJ. 6.  2014. The global spread of crop pests and pathogens. Glob. Ecol. Biogeogr. 23:121398–407 [Google Scholar]
  7. Biek R, Pybus OG, Lloyd-Smith JO, Didelot X. 7.  2015. Measurably evolving pathogens in the genomic era. Trends Ecol. Evol. 30:6306–13This review highlights landscape genetic principles relevant to infection dynamics. [Google Scholar]
  8. Biek R, Real LA. 8.  2010. The landscape genetics of infectious disease emergence and spread. Mol. Ecol. 19:173515–31 [Google Scholar]
  9. Bloomquist EW, Lemey P, Suchard MA. 9.  2010. Three roads diverged? Routes to phylogeographic inference. Trends Ecol. Evol. 25:11626–32 [Google Scholar]
  10. Bouckaert R, Heled J, Kühnert D, Vaughan T, Wu CH. 10.  et al. 2014. BEAST 2: a software platform for Bayesian evolutionary analysis. PLOS Comput. Biol. 10:4e1003537 [Google Scholar]
  11. Bousalem M, Dallot S, Fuji S, Natsuaki KT. 11.  2003. Origin, world-wide dispersion, bio-geographical diversification, radiation and recombination: an evolutionary history of Yam mild mosaic virus (YMMV). Infect. Genet. Evol. 3:3189–206 [Google Scholar]
  12. Bousalem M, Dallot S, Guyader S. 12.  2000. The use of phylogenetic data to develop molecular tools for the detection and genotyping of Yam mosaic virus. Potential application in molecular epidemiology. J. Virol. Methods 90:125–36 [Google Scholar]
  13. Britton T, Giardina F. 13.  2016. Introduction to statistical inference for infectious diseases. J. Société Fr. Stat. 157:153–70 [Google Scholar]
  14. Brunker K. 14.  2016. The landscape epidemiology of canine rabies virus in Tanzania PhD Thesis Univ. Glasgow
  15. Brunker K, Marston DA, Horton DL, Cleaveland S, Fooks AR. 15.  et al. 2015. Elucidating the phylodynamics of endemic rabies virus in eastern Africa using whole-genome sequencing. Virus Evol 1:1vev011 [Google Scholar]
  16. Bull RA, Eltahla AA, Rodrigo C, Koekkoek SM, Walker M. 16.  et al. 2016. A method for near full-length amplification and sequencing for six hepatitis C virus genotypes. BMC Genom 17:247 [Google Scholar]
  17. Candresse T, Filloux D, Muhire B, Julian C, Galzi S. 17.  et al. 2014. Appearances can be deceptive: revealing a hidden viral infection with deep sequencing in a plant quarantine context. PLOS ONE 9:7e102945 [Google Scholar]
  18. Clark MF, Adams AN. 18.  1977. Characteristics of the microplate method of enzyme-linked immunosorbent assay for the detection of plant viruses. J. Gen. Virol. 34:3475–83 [Google Scholar]
  19. Cottam EM, Thébaud G, Wadsworth J, Gloster J, Mansley L. 19.  et al. 2008. Integrating genetic and epidemiological data to determine transmission pathways of foot-and-mouth disease virus. Proc. R. Soc. B 275:1637887–95This early approach infers transmission trees using epidemiological data and virus genomes. [Google Scholar]
  20. Cuevas JM, Willemsen A, Hillung J, Zwart MP, Elena SF. 20.  2015. Temporal dynamics of intrahost molecular evolution for a plant RNA virus. Mol. Biol. Evol. 32:51132–47 [Google Scholar]
  21. Davino S, Willemsen A, Panno S, Davino M, Catara A. 21.  et al. 2013. Emergence and phylodynamics of Citrus tristeza virus in Sicily, Italy. PLOS ONE 8:6e66700 [Google Scholar]
  22. De Bruyn A, Harimalala M, Zinga I, Mabvakure BM, Hoareau M. 22.  et al. 2016. Divergent evolutionary and epidemiological dynamics of cassava mosaic geminiviruses in Madagascar. BMC Evol. Biol. 16:182 [Google Scholar]
  23. De Bruyn A, Villemot J, Lefeuvre P, Villar E, Hoareau M. 23.  et al. 2012. East African cassava mosaic-like viruses from Africa to Indian Ocean islands: molecular diversity, evolutionary history and geographical dissemination of a bipartite begomovirus. BMC Evol. Biol. 12:228 [Google Scholar]
  24. Dellicour S, Rose R, Pybus OG. 24.  2016. Explaining the geographic spread of emerging epidemics: a framework for comparing viral phylogenies and environmental landscape data. BMC Bioinform 17:82 [Google Scholar]
  25. Didelot X, Gardy J, Colijn C. 25.  2014. Bayesian inference of infectious disease transmission from whole-genome sequence data. Mol. Biol. Evol. 31:71869–79 [Google Scholar]
  26. Diekmann O, Heesterbeek H, Britton T. 26.  2012. Mathematical Tools for Understanding Infectious Disease Dynamics Princeton, NJ: Princeton Univ. Press
  27. Drummond AJ, Ho SYW, Phillips MJ, Rambaut A. 27.  2006. Relaxed phylogenetics and dating with confidence. PLOS Biol 4:5e88 [Google Scholar]
  28. Drummond AJ, Nicholls GK, Rodrigo AG, Solomon W. 28.  2002. Estimating mutation parameters, population history and genealogy simultaneously from temporally spaced sequence data. Genetics 161:31307–20 [Google Scholar]
  29. Drummond AJ, Pybus OG, Rambaut A, Forsberg R, Rodrigo AG. 29.  2003. Measurably evolving populations. Trends Ecol. Evol. 18:9481–88 [Google Scholar]
  30. Drummond AJ, Suchard MA, Xie D, Rambaut A. 30.  2012. Bayesian phylogenetics with BEAUti and the BEAST 1.7. Mol. Biol. Evol. 29:81969–73 [Google Scholar]
  31. Duchêne S, Duchêne D, Holmes EC, Ho SYW. 31.  2015. The performance of the date-randomisation test in phylogenetic analyses of time-structured virus data. Mol. Biol. Evol. 32:71895–906 [Google Scholar]
  32. Duffy S, Shackelton LA, Holmes EC. 32.  2008. Rates of evolutionary change in viruses: patterns and determinants. Nat. Rev. Genet. 9:4267–76This review clearly explains the factors affecting virus mutation and substitution rates. [Google Scholar]
  33. Dupanloup I, Schneider S, Excoffier L. 33.  2002. A simulated annealing approach to define the genetic structure of populations. Mol. Ecol. 11:122571–81 [Google Scholar]
  34. D'Urso F, Sambade A, Moya A, Guerri J, Moreno P. 34.  2003. Variation of haplotype distributions of two genomic regions of Citrus tristeza virus populations from eastern Spain. Mol. Ecol. 12:2517–26 [Google Scholar]
  35. Eldholm V, Rieux A, Monteserin J, Lopez JM, Palmero D. 35.  et al. 2016. Impact of HIV co-infection on the evolution and transmission of multidrug-resistant tuberculosis. eLife 5:e16644 [Google Scholar]
  36. Elena SF, Bedhomme S, Carrasco P, Cuevas JM, de la Iglesia F. 36.  et al. 2011. The evolutionary genetics of emerging plant RNA viruses. Mol. Plant-Microbe Interact. 24:3287–93 [Google Scholar]
  37. Excoffier L, Laval G, Schneider S. 37.  2007. An integrated software package for population genetics data analysis. Evol. Bioinform. 1:47–50 [Google Scholar]
  38. Fabre F, Moury B, Johansen EI, Simon V, Jacquemond M, Senoussi R. 38.  2014. Narrow bottlenecks affect Pea seedborne mosaic virus populations during vertical seed transmission but not during leaf colonization. PLOS Pathog 10:1e1003833 [Google Scholar]
  39. Famulare M, Hu H. 39.  2015. Extracting transmission networks from phylogeographic data for epidemic and endemic diseases: Ebola virus in Sierra Leone, 2009 H1N1 pandemic influenza and polio in Nigeria. Int. Health 7:2130–38 [Google Scholar]
  40. Fargette D, Konaté G, Fauquet C, Muller E, Peterschmitt M, Thresh JM. 40.  2006. Molecular ecology and emergence of tropical plant viruses. Annu. Rev. Phytopathol. 44:235–60 [Google Scholar]
  41. Faria NR, Suchard MA, Rambaut A, Streicker DG, Lemey P. 41.  2013. Simultaneously reconstructing viral cross-species transmission history and identifying the underlying constraints. Philos. Trans. R. Soc. B 368:161420120196 [Google Scholar]
  42. Fraile A, Malpica JM, Aranda MA, Rodríguez-Cerezo E, García-Arenal F. 42.  1996. Genetic diversity in tobacco mild green mosaic tobamovirus infecting the wild plant Nicotiana glauca. . Virology 223:1148–55 [Google Scholar]
  43. Frost SDW, Pybus OG, Gog JR, Viboud C, Bonhoeffer S, Bedford T. 43.  2015. Eight challenges in phylodynamic inference. Epidemics 10:88–92 [Google Scholar]
  44. García-Arenal F, Fraile A, Malpica JM. 44.  2001. Variability and genetic structure of plant virus populations. Annu. Rev. Phytopathol. 39:157–86 [Google Scholar]
  45. Gavryushkina A, Welch D, Stadler T, Drummond AJ. 45.  2014. Bayesian inference of sampled ancestor trees for epidemiology and fossil calibration. PLOS Comput. Biol. 10:12e1003919 [Google Scholar]
  46. Gibbs AJ, Fargette D, García-Arenal F, Gibbs MJ. 46.  2010. Time—the emerging dimension of plant virus studies. J. Gen. Virol. 91:113–22 [Google Scholar]
  47. Gilligan CA. 47.  2008. Sustainable agriculture and plant diseases: an epidemiological perspective. Philos. Trans. R. Soc. B 363:1492741–59 [Google Scholar]
  48. Glais L, Kerlan C, Tribodet M, Marie-Jeanne Tordo V, Robaglia C, Astier-Manifacier S. 48.  1996. Molecular characterization of potato virus YN isolates by PCR-RFLP. Eur. J. Plant Pathol. 102:7655–62 [Google Scholar]
  49. Goss EM. 49.  2015. Genome-enabled analysis of plant-pathogen migration. Annu. Rev. Phytopathol. 53:121–35 [Google Scholar]
  50. Grenfell BT, Pybus OG, Gog JR, Wood JLN, Daly JM. 50.  et al. 2004. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303:5656327–32This review presents the principles of the phylodynamics framework, which relates phylogenies and epidemiology. [Google Scholar]
  51. Grünwald NJ, Goss EM. 51.  2011. Evolution and population genetics of exotic and re-emerging pathogens: novel tools and approaches. Annu. Rev. Phytopathol. 49:249–67 [Google Scholar]
  52. Guillot G, Leblois R, Coulon A, Frantz AC. 52.  2009. Statistical methods in spatial genetics. Mol. Ecol. 18:234734–56 [Google Scholar]
  53. Haegeman B, Hamelin J, Moriarty J, Neal P, Dushoff J, Weitz JS. 53.  2013. Robust estimation of microbial diversity in theory and in practice. ISME J 7:61092–101 [Google Scholar]
  54. Hall M, Woolhouse M, Rambaut A. 54.  2015. Epidemic reconstruction in a phylogenetics framework: transmission trees as partitions of the node set. PLOS Comput. Biol. 11:12e1004613 [Google Scholar]
  55. Hampson K, Dushoff J, Cleaveland S, Haydon DT, Kaare M. 55.  et al. 2009. Transmission dynamics and prospects for the elimination of canine rabies. PLOS Biol 7:3e1000053 [Google Scholar]
  56. Haydon DT, Chase-Topping M, Shaw DJ, Matthews L, Friar JK. 56.  et al. 2003. The construction and analysis of epidemic trees with reference to the 2001 UK foot-and-mouth outbreak. Proc. R. Soc. B 270:1511121–27 [Google Scholar]
  57. Heller R, Chikhi L, Siegismund HR. 57.  2013. The confounding effect of population structure on Bayesian skyline plot inferences of demographic history. PLOS ONE 8:5e62992 [Google Scholar]
  58. Ho SYW, Duchêne S. 58.  2014. Molecular-clock methods for estimating evolutionary rates and timescales. Mol. Ecol. 23:245947–65This review presents the different molecular clock models. [Google Scholar]
  59. Ho SYW, Shapiro B. 59.  2011. Skyline-plot methods for estimating demographic history from nucleotide sequences. Mol. Ecol. Resour. 11:3423–34 [Google Scholar]
  60. Holmes EC. 60.  2009. The evolutionary genetics of emerging viruses. Annu. Rev. Ecol. Evol. Syst. 40:353–72 [Google Scholar]
  61. Hughes JB, Hellmann JJ, Ricketts TH, Bohannan BJM. 61.  2001. Counting the uncountable: statistical approaches to estimating microbial diversity. Appl. Environ. Microbiol. 67:104399–406 [Google Scholar]
  62. Jeger MJ, Seal SE, Van den Bosch F. 62.  2006. Evolutionary epidemiology of plant virus disease. Adv. Virus Res. 67:163–203 [Google Scholar]
  63. Joannon B, Lavigne C, Lecoq H, Desbiez C. 63.  2010. Barriers to gene flow between emerging populations of Watermelon mosaic virus in southeastern France. Phytopathology 100:121373–79 [Google Scholar]
  64. Jombart T, Cori A, Didelot X, Cauchemez S, Fraser C, Ferguson N. 64.  2014. Bayesian reconstruction of disease outbreaks by combining epidemiologic and genomic data. PLOS Comput. Biol. 10:1e1003457 [Google Scholar]
  65. Jombart T, Devillard S, Balloux F. 65.  2010. Discriminant analysis of principal components: a new method for the analysis of genetically structured populations. BMC Genet 11:94 [Google Scholar]
  66. Jombart T, Devillard S, Dufour A-B, Pontier D. 66.  2008. Revealing cryptic spatial patterns in genetic variability by a new multivariate method. Heredity 101:192–103 [Google Scholar]
  67. Jombart T, Eggo RM, Dodd PJ, Balloux F. 67.  2011. Reconstructing disease outbreaks from genetic data: a graph approach. Heredity 106:2383–90This study presents the first R package enabling to reconstruct transmission graphs from genetic data. [Google Scholar]
  68. Jridi C, Martin J-F, Marie-Jeanne V, Labonne G, Blanc S. 68.  2006. Distinct viral populations differentiate and evolve independently in a single perennial host plant. J. Virol. 80:52349–57 [Google Scholar]
  69. Kamvar ZN, Brooks JC, Grünwald NJ. 69.  2015. Novel R tools for analysis of genome-wide population genetic data with emphasis on clonality. Front. Genet. 6:208 [Google Scholar]
  70. Kenah E, Britton T, Halloran ME, Longini IM Jr.. 70.  2016. Molecular infectious disease epidemiology: survival analysis and algorithms linking phylogenies to transmission trees. PLOS Comput. Biol. 12:4e1004869 [Google Scholar]
  71. Klinkowski M. 71.  1970. Catastrophic plant diseases. Annu. Rev. Phytopathol. 8:37–60 [Google Scholar]
  72. Kraberger S, Harkins GW, Kumari SG, Thomas JE, Schwinghamer MW. 72.  et al. 2013. Evidence that dicot-infecting mastreviruses are particularly prone to inter-species recombination and have likely been circulating in Australia for longer than in Africa and the Middle East. Virology 444:1–2282–91 [Google Scholar]
  73. Lacroix C, Renner K, Cole E, Seabloom EW, Borer ET, Malmstrom CM. 73.  2016. Methodological guidelines for accurate detection of viruses in wild plant species. Appl. Environ. Microbiol. 82:61966–75 [Google Scholar]
  74. Lau MSY, Marion G, Streftaris G, Gibson G. 74.  2015. A systematic Bayesian integration of epidemiological and genetic data. PLOS Comput. Biol. 11:11e1004633 [Google Scholar]
  75. Lefeuvre P, Martin DP, Harkins G, Lemey P, Gray AJA. 75.  et al. 2010. The spread of Tomato yellow leaf curl virus from the Middle East to the world. PLOS Pathog 6:10e1001164 [Google Scholar]
  76. Lemey P, Rambaut A, Bedford T, Faria N, Bielejec F. 76.  et al. 2014. Unifying viral genetics and human transportation data to predict the global transmission dynamics of human influenza H3N2. PLOS Pathog 10:2e1003932 [Google Scholar]
  77. Lemey P, Rambaut A, Drummond AJ, Suchard MA. 77.  2009. Bayesian phylogeography finds its roots. PLOS Comput. Biol. 5:9e1000520This article presents a Bayesian framework for inference, visualization, and hypothesis testing of phylogeographic history. [Google Scholar]
  78. Lemey P, Rambaut A, Welch JJ, Suchard MA. 78.  2010. Phylogeography takes a relaxed random walk in continuous space and time. Mol. Biol. Evol. 27:81877–85 [Google Scholar]
  79. Logan G, Freimanis GL, King DJ, Valdazo-González B, Bachanek-Bankowska K. 79.  et al. 2014. A universal protocol to generate consensus level genome sequences for foot-and-mouth disease virus and other positive-sense polyadenylated RNA viruses using the Illumina MiSeq. BMC Genom 15:828 [Google Scholar]
  80. Mabvakure B, Martin DP, Kraberger S, Cloete L, van Brunschot S. 80.  et al. 2016. Ongoing geographical spread of Tomato yellow leaf curl virus. . Virology 498:257–64 [Google Scholar]
  81. Maio ND, Wu CH, O'Reilly KM, Wilson D. 81.  2015. New routes to phylogeography: a Bayesian structured coalescent approximation. PLOS Genet 11:8e1005421This paper introduces BASTA, a phylogeographic model combining accurate coalescence methods and computational efficiency. [Google Scholar]
  82. Malmstrom CM, Shu R, Linton EW, Newton LA, Cook MA. 82.  2007. Barley yellow dwarf viruses (BYDVS) preserved in herbarium specimens illuminate historical disease ecology of invasive and native grasses. J. Ecol. 95:61153–66 [Google Scholar]
  83. Marais A, Faure C, Couture C, Bergey B, Gentit P, Candresse T. 83.  2014. Characterization by deep sequencing of divergent Plum bark necrosis stem pitting–associated virus (PBNSPaV) isolates and development of a broad-spectrum PBNSPaV detection assay. Phytopathology 104:6660–66 [Google Scholar]
  84. Martin DP, Biagini P, Lefeuvre P, Golden M, Roumagnac P, Varsani A. 84.  2011. Recombination in eukaryotic single stranded DNA viruses. Viruses 3:91699–738 [Google Scholar]
  85. Martin DP, Lemey P, Posada D. 85.  2011. Analysing recombination in nucleotide sequences. Mol. Ecol. Resour. 11:6943–55 [Google Scholar]
  86. McRae BH. 86.  2006. Isolation by resistance. Evolution 60:81551–61 [Google Scholar]
  87. Meentemeyer RK, Haas SE, Václavík T. 87.  2012. Landscape epidemiology of emerging infectious diseases in natural and human-altered ecosystems. Annu. Rev. Phytopathol. 50:379–402 [Google Scholar]
  88. Mollentze N, Nel LH, Townsend S, Roux K, Hampson K. 88.  et al. 2014. A Bayesian approach for inferring the dynamics of partially observed endemic infectious diseases from space-time-genetic data. Proc. R. Soc. B 281:178220133251This article describes a framework for reconstructing transmission trees using genetic, temporal, and spatial information. [Google Scholar]
  89. Monjane AL, Harkins GW, Martin DP, Lemey P, Lefeuvre P. 89.  et al. 2011. Reconstructing the history of Maize streak virus strain A dispersal to reveal diversification hot spots and its origin in southern Africa. J. Virol. 85:189623–36 [Google Scholar]
  90. Monmonier MS. 90.  1973. Maximum-difference barriers: an alternative numerical regionalization method. Geogr. Anal. 5:3245–61 [Google Scholar]
  91. Morelli MJ, Thébaud G, Chadœuf J, King DP, Haydon DT, Soubeyrand S. 91.  2012. A Bayesian inference framework to reconstruct transmission trees using epidemiological and genetic data. PLOS Comput. Biol. 8:11e1002768 [Google Scholar]
  92. Moury B, Desbiez C, Jacquemond M, Lecoq H. 92.  2006. Genetic diversity of plant virus populations: towards hypothesis testing in molecular epidemiology. Adv. Virus Res. 67:49–87 [Google Scholar]
  93. Moury B, Fabre F, Senoussi R. 93.  2007. Estimation of the number of virus particles transmitted by an insect vector. PNAS 104:4517891–96 [Google Scholar]
  94. Mullan B, Sheehy P, Shanahan F, Fanning L. 94.  2004. Do Taq-generated RT-PCR products from RNA viruses accurately reflect viral genetic heterogeneity?. J. Viral Hepat. 11:2108–14 [Google Scholar]
  95. Murray GGR, Wang F, Harrison EM, Paterson GK, Mather AE. 95.  et al. 2016. The effect of genetic structure on molecular dating and tests for temporal signal. Methods Ecol. Evol. 7:180–89 [Google Scholar]
  96. Nelson MI, Viboud C, Vincent AL, Culhane MR, Detmer SE. 96.  et al. 2015. Global migration of influenza A viruses in swine. Nat. Commun. 6:6696 [Google Scholar]
  97. Ng TFF, Duffy S, Polston JE, Bixby E, Vallad GE, Breitbart M. 97.  2011. Exploring the diversity of plant DNA viruses and their satellites using vector-enabled metagenomics on whiteflies. PLOS ONE 6:4e19050 [Google Scholar]
  98. O'Fallon BD. 98.  2013. ACG: rapid inference of population history from recombining nucleotide sequences. BMC Bioinform 14:40 [Google Scholar]
  99. Ohshima K, Akaishi S, Kajiyama H, Koga R, Gibbs AJ. 99.  2010. Evolutionary trajectory of turnip mosaic virus populations adapting to a new host. J. Gen. Virol. 91:3788–801 [Google Scholar]
  100. Ohshima K, Matsumoto K, Yasaka R, Nishiyama M, Soejima K. 100.  et al. 2016. Temporal analysis of reassortment and molecular evolution of Cucumber mosaic virus: extra clues from its segmented genome. Virology 487:188–97 [Google Scholar]
  101. Olarte Castillo XA, Fermin G, Tabima J, Rojas Y, Tennant PF. 101.  et al. 2011. Phylogeography and molecular epidemiology of Papaya ringspot virus. . Virus Res. 159:2132–40 [Google Scholar]
  102. Orita M, Iwahana H, Kanazawa H, Hayashi K, Sekiya T. 102.  1989. Detection of polymorphisms of human DNA by gel electrophoresis as single-strand conformation polymorphisms. PNAS 86:82766–70 [Google Scholar]
  103. Ostfeld RS, Glass GE, Keesing F. 103.  2005. Spatial epidemiology: an emerging (or re-emerging) discipline. Trends Ecol. Evol. 20:6328–36 [Google Scholar]
  104. Palanga E, Filloux D, Martin DP, Fernandez E, Gargani D. 104.  et al. 2016. Metagenomic-based screening and molecular characterization of cowpea-infecting viruses in Burkina Faso. PLOS ONE 11:10e0165188 [Google Scholar]
  105. Parker IM, Gilbert GS. 105.  2004. The evolutionary ecology of novel plant-pathogen interactions. Annu. Rev. Ecol. Evol. Syst. 35:675–700 [Google Scholar]
  106. Piry S, Chapuis M-P, Gauffre B, Papaïx J, Cruaud A, Berthier K. 106.  2016. Mapping averaged pairwise information (MAPI): a new exploratory tool to uncover spatial structure. Methods Ecol. Evol. 7:1463–75 [Google Scholar]
  107. Posada D, Crandall KA. 107.  2001. Evaluation of methods for detecting recombination from DNA sequences: computer simulations. PNAS 98:2413757–62 [Google Scholar]
  108. Prasanna H, Sinha DP, Verma A, Singh M, Singh B. 108.  et al. 2010. The population genomics of begomoviruses: global scale population structure and gene flow. Virol. J. 7:220 [Google Scholar]
  109. Pybus OG, Rambaut A. 109.  2009. Evolutionary analysis of the dynamics of viral infectious disease. Nat. Rev. Genet. 10:8540–50 [Google Scholar]
  110. Pybus OG, Suchard MA, Lemey P, Bernardin FJ, Rambaut A. 110.  et al. 2012. Unifying the spatial epidemiology and molecular evolution of emerging epidemics. PNAS 109:3715066–71 [Google Scholar]
  111. Pybus OG, Tatem AJ, Lemey P. 111.  2015. Virus evolution and transmission in an ever more connected world. Proc. R. Soc. B 282:182120142878 [Google Scholar]
  112. Quick J, Loman NJ, Duraffour S, Simpson JT, Severi E. 112.  et al. 2016. Real-time, portable genome sequencing for Ebola surveillance. Nature 530:7589228–32 [Google Scholar]
  113. 113. R Dev. Team. 2015. R: A Language and Environment for Statistical Computing Vienna, Austria: R Found. Stat. Comput.
  114. Rakotomalala M, Pinel-Galzi A, Mpunami A, Randrianasolo A, Ramavovololona P. 114.  et al. 2013. Rice yellow mottle virus in Madagascar and in the Zanzibar Archipelago; island systems and evolutionary time scale to study virus emergence. Virus Res 171:171–79 [Google Scholar]
  115. Rasmussen DA, Ratmann O, Koelle K. 115.  2011. Inference for nonlinear epidemiological models using genealogies and time series. PLOS Comput. Biol. 7:8e1002136 [Google Scholar]
  116. Rees EE, Pond BA, Cullingham CI, Tinline R, Ball D. 116.  et al. 2008. Assessing a landscape barrier using genetic simulation modelling: implications for raccoon rabies management. Prev. Vet. Med. 86:1–2107–23 [Google Scholar]
  117. Rieux A, Balloux F. 117.  2016. Inferences from tip-calibrated phylogenies: a review and a practical guide. Mol. Ecol. 25:91911–24This review summarizes tip dating approaches and provides a guide to performing such analyses. [Google Scholar]
  118. Rissler LJ. 118.  2016. Union of phylogeography and landscape genetics. PNAS 113:298079–86 [Google Scholar]
  119. Rodríguez-Cerezo E, Moya A, García-Arenal F. 119.  1989. Variability and evolution of the plant RNA virus pepper mild mottle virus. J. Virol. 63:52198–203 [Google Scholar]
  120. Rolland M, Glais L, Kerlan C, Jacquot E. 120.  2008. A multiple single nucleotide polymorphisms interrogation assay for reliable Potato virus Y group and variant characterization. J. Virol. Methods 147:1108–17 [Google Scholar]
  121. Romero-Severson E, Skar H, Bulla I, Albert J, Leitner T. 121.  2014. Timing and order of transmission events is not directly reflected in a pathogen phylogeny. Mol. Biol. Evol. 31:92472–82 [Google Scholar]
  122. Roossinck MJ. 122.  2014. Metagenomics of plant and fungal viruses reveals an abundance of persistent lifestyles. Virology 5:767 [Google Scholar]
  123. Roossinck MJ, Martin DP, Roumagnac P. 123.  2015. Plant virus metagenomics: advances in virus discovery. Phytopathology 105:6716–27 [Google Scholar]
  124. Sanger F, Air GM, Barrell BG, Brown NL, Coulson AR. 124.  et al. 1977. Nucleotide sequence of bacteriophage ϕX174 DNA. Nature 265:687–95 [Google Scholar]
  125. Sanjuán R. 125.  2012. From molecular genetics to phylodynamics: evolutionary relevance of mutation rates across viruses. PLOS Pathog 8:5e1002685 [Google Scholar]
  126. Sanjuán R, Nebot MR, Chirico N, Mansky LM, Belshaw R. 126.  2010. Viral mutation rates. J. Virol. 84:199733–48 [Google Scholar]
  127. Schierup MH, Hein J. 127.  2000. Consequences of recombination on traditional phylogenetic analysis. Genetics 156:2879–91 [Google Scholar]
  128. Schubert J, Habekuß A, Kazmaier K, Jeske H. 128.  2007. Surveying cereal-infecting geminiviruses in Germany—diagnostics and direct sequencing using rolling circle amplification. Virus Res 127:161–70 [Google Scholar]
  129. Schulte PA, Perera FP. 129.  1993. Molecular Epidemiology: Principles and Practices San Diego: Academic
  130. Seo TK, Thorne JL, Hasegawa M, Kishino H. 130.  2002. A viral sampling design for testing the molecular clock and for estimating evolutionary rates and divergence times. Bioinformatics 18:1115–23 [Google Scholar]
  131. Shah VB, McRae BH. 131.  2008. Circuitscape: a tool for landscape ecology. Proc. Python Sci. Conf., 7th, Pasadena Aug. 19–24 62–65 https://hal.archives-ouvertes.fr/hal-00502586 [Google Scholar]
  132. Shapiro B, Ho SYW, Drummond AJ, Suchard MA, Pybus OG, Rambaut A. 132.  2011. A Bayesian phylogenetic method to estimate unknown sequence ages. Mol. Biol. Evol. 28:2879–87 [Google Scholar]
  133. Simmons HE, Dunham JP, Stack JC, Dickins BJA, Pagán I. 133.  et al. 2012. Deep sequencing reveals persistence of intra- and inter-host genetic diversity in natural and greenhouse populations of zucchini yellow mosaic virus. J. Gen. Virol. 93:81831–40 [Google Scholar]
  134. Smith O, Clapham A, Rose P, Liu Y, Wang J, Allaby RG. 134.  2014. A complete ancient RNA genome: identification, reconstruction and evolutionary history of archaeological Barley Stripe Mosaic Virus. Sci. Rep. 4:4003 [Google Scholar]
  135. Soubeyrand S. 135.  2016. Construction of semi-Markov genetic-space-time SEIR models and inference. J. Soc. Fr. Stat. 157:1129–52 [Google Scholar]
  136. Stadler T, Bonhoeffer S. 136.  2013. Uncovering epidemiological dynamics in heterogeneous host populations using phylogenetic methods. Philos. Trans. R. Soc. B 368:161420120198 [Google Scholar]
  137. Stainton D, Martin DP, Muhire BM, Lolohea S, Halafihi M. 137.  et al. 2015. The global distribution of Banana bunchy top virus reveals little evidence for frequent recent, human-mediated long distance dispersal events. Virus Evol 1:1vev009 [Google Scholar]
  138. Sztuba-Solińska J, Urbanowicz A, Figlerowicz M, Bujarski JJ. 138.  2011. RNA-RNA recombination in plant virus replication and evolution. Annu. Rev. Phytopathol. 49:415–43 [Google Scholar]
  139. Tomimura K, Špak J, Katis N, Jenner CE, Walsh JA. 139.  et al. 2004. Comparisons of the genetic structure of populations of Turnip mosaic virus in West and East Eurasia. Virology 330:2408–23 [Google Scholar]
  140. Trovão NS, Baele G, Vrancken B, Bielejec F, Suchard MA. 140.  et al. 2015. Host ecology determines the dispersal patterns of a plant virus. Virus Evol 1:1vev016 [Google Scholar]
  141. van Etten J. 141.  2015. R Package Gdistance: Distances and Routes on Geographical Grids https://cran.r-project.org/package=gdistance
  142. Viboud C, Nelson MI, Tan Y, Holmes EC. 142.  2013. Contrasting the epidemiological and evolutionary dynamics of influenza spatial transmission. Philos. Trans. R. Soc. B 368:161420120199 [Google Scholar]
  143. Vurro M, Bonciani B, Vannacci G. 143.  2010. Emerging infectious diseases of crop plants in developing countries: impact on agriculture and socio-economic consequences. Food Secur 2:2113–32 [Google Scholar]
  144. Wang IJ. 144.  2010. Recognizing the temporal distinctions between landscape genetics and phylogeography. Mol. Ecol. 19:132605–8 [Google Scholar]
  145. Wheeler DC, Waller LA, Biek R. 145.  2010. Spatial analysis of feline immunodeficiency virus infection in cougars. Spat. Spatiotemporal Epidemiol. 1:2–3151–61 [Google Scholar]
  146. Worby CJ, Lipsitch M, Hanage WP. 146.  2014. Within-host bacterial diversity hinders accurate reconstruction of transmission networks from genomic distance data. PLOS Comput. Biol. 10:3e1003549 [Google Scholar]
  147. Yasaka R, Nguyen HD, Ho SYW, Duchêne S, Korkmaz S. 147.  et al. 2014. The temporal evolution and global spread of Cauliflower mosaic virus, a plant pararetrovirus. PLOS ONE 9:1e85641 [Google Scholar]
  148. Yasaka R, Ohba K, Schwinghamer MW, Fletcher J, Ochoa-Corona FM. 148.  et al. 2015. Phylodynamic evidence of the migration of turnip mosaic potyvirus from Europe to Australia and New Zealand. J. Gen. Virol. 96:3701–13 [Google Scholar]
  149. Ypma RJF, van Ballegooijen WM, Wallinga J. 149.  2013. Relating phylogenetic trees to transmission trees of infectious disease outbreaks. Genetics 195:31055–62 [Google Scholar]
  150. Ypma RJF, Bataille AMA, Stegeman A, Koch G, Wallinga J, van Ballegooijen WM. 150.  2012. Unravelling transmission trees of infectious diseases by combining genetic and epidemiological data. Proc. R. Soc. B 279:1728444–50 [Google Scholar]
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Exploiting Genetic Information to Trace Plant Virus Dispersal in Landscapes
Annual Review of Phytopathology 55, 139 (2017); https://doi.org/10.1146/annurev-phyto-080516-035616
/content/journals/10.1146/annurev-phyto-080516-035616
/content/journals/10.1146/annurev-phyto-080516-035616
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