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Kinship networks of seed exchange shape spatial patterns of plant virus diversity

  • 1.

    Chakraborty, S. & Newton, A. C. Climate change, plant diseases and food security: an overview. Plant Pathol. 60, 2–14 (2011).

    Article 

    Google Scholar 

  • 2.

    Savary, S. et al. The global burden of pathogens and pests on major food crops. Nat. Ecol. Evol. 3, 430–439 (2019).

    PubMed 
    Article 
    PubMed Central 

    Google Scholar 

  • 3.

    McGuire, S. & Sperling, L. Seed systems smallholder farmers use. Food Secur. 8, 179–195 (2016).

    Article 

    Google Scholar 

  • 4.

    Almekinders, C. J., Louwaars, N. P. & De Bruijn, G. H. Local seed systems and their importance for an improved seed supply in developing countries. Euphytica 78, 207–216 (1994).

    Article 

    Google Scholar 

  • 5.

    McGuire, S. & Sperling, L. Making seed systems more resilient to stress. Global Environ. Chang. 23, 644–653 (2013).

    Article 

    Google Scholar 

  • 6.

    Legg, J. et al. Community phytosanitation to manage Cassava Brown Streak Disease. Virus Res. 241, 236–253 (2017).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 7.

    McQuaid, C. F. et al. Spatial dynamics and control of a crop pathogen with mixed-mode transmission. PLoS Comput. Biol. 13, e1005654 (2017a).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 8.

    Chernela, J. M. Os cultivares de mandioca na área do Uaupés (Tukâno). In Suma Etnológica Brasileira (ed Ribeiro, D.) 151–158 (Finep, Petrópolis, 1986).

  • 9.

    Emperaire, L., Pinton, F. & Second, G. Gestion dynamique de la diversité variétale du manioc en Amazonie du Nord-Ouest. Nat. Sci. Soc. 6, 27–42 (1998).

    Article 

    Google Scholar 

  • 10.

    Sirbanchongkran, A., Yimyam, N., Boonma, W. & Rerkasem, K. Varietal turnover and seed exchange: implications for conservation of rice genetic diversity on farm. Int. Rice Res. Notes 29, 12–14 (2004).

    Google Scholar 

  • 11.

    Delêtre, M., McKey, D. B. & Hodkinson, T. R. Marriage exchanges, seed exchanges, and the dynamics of manioc diversity. Proc. Natl Acad. Sci. USA 108, 18249–18254 (2011).

    ADS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 12.

    Labeyrie, V., Thomas, M., Muthamia, Z. K. & Leclerc, C. Seed exchange networks, ethnicity, and sorghum diversity. Proc. Natl Acad. Sci. USA 113, 98–103 (2016).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 13.

    Brown, J. K. et al. Revision of Begomovirus taxonomy based on pairwise sequence comparisons. Arch. Virol. 160, 1593–1619 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 14.

    Legg, J. P. et al. Comparing the regional epidemiology of the cassava mosaic and cassava brown streak pandemics in Africa. Virus Res. 159, 161–170 (2011).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 15.

    Patil, B. L. & Fauquet, C. M. Cassava mosaic geminiviruses: actual knowledge and perspectives. Mol. Plant Pathol. 10, 685–701 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 16.

    Harrison, B. D., Zhou, X., Otim‐Nape, G. W., Liu, Y. & Robinson, D. J. Role of a novel type of double infection in the geminivirus‐induced epidemic of severe cassava mosaic in Uganda. Ann. Appl. Biol. 131, 437–448 (1997).

    Article 

    Google Scholar 

  • 17.

    Consultative Group for International Agricultural Research. CGIAR Research Program 3.4: Roots, tubers, and bananas for food security and income. Final revised proposal. September 2011. https://hdl.handle.net/10947/5314.

  • 18.

    Duffy, S. & Holmes, E. C. Validation of high rates of nucleotide substitution in geminiviruses: phylogenetic evidence from East African cassava mosaic viruses. J. Gen. Virol. 90, 1539–1547 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 19.

    Grenfell, B. T. et al. Unifying the epidemiological and evolutionary dynamics of pathogens. Science 303, 327–332 (2004).

    ADS 
    CAS 
    Article 

    Google Scholar 

  • 20.

    Pybus, O. G. & Rambaut, A. Evolutionary analysis of the dynamics of viral infectious disease. Nat. Rev. Genet. 10, 540–550 (2009).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 21.

    Fauquet, C. & Fargette, D. African cassava mosaic virus: etiology, epidemiology and control. Plant Dis. 74, 404–411 (1990).

    Article 

    Google Scholar 

  • 22.

    Zhou, X. et al. Evidence that DNA A of a geminivirus associated with severe cassava mosaic disease in Uganda has arisen by interspecific recombination. J. Gen. Virol. 78, 2101–2111 (1997).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 23.

    Pita, J. S. et al. Recombination, pseudorecombination and synergism of geminiviruses are determinant keys to the epidemic of severe cassava mosaic disease in Uganda. J. Gen. Virol. 82, 655–665 (2001).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 24.

    Lefeuvre, P. & Moriones, E. Recombination as a motor of host switches and virus emergences: geminiviruses as case studies. Curr. Opin. Virol. 10, 14–19 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 25.

    Tiendrébéogo, F. et al. Evolution of African cassava mosaic virus by recombination between bipartite and monopartite begomoviruses. Virol. J. 9, 67 (2012).

    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 26.

    Syrjala, S. E. A statistical test for a difference between the spatial distributions of two populations. Ecology 77, 75–80 (1996).

    Article 

    Google Scholar 

  • 27.

    Chevenet, F., Jung, M., Peeters, M., de Oliveira, T. & Gascuel, O. Searching for virus phylotypes. Bioinformatics 29, 561–570 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 28.

    Jost, L. Entropy and diversity. Oikos 113, 363–375 (2006).

    Article 

    Google Scholar 

  • 29.

    Pallmann, P. et al. Assessing group differences in biodiversity by simultaneously testing a user‐defined selection of diversity indices. Mol. Ecol. Resour. 12, 1068–1078 (2012).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 30.

    Volz, E. M., Koelle, K. & Bedford, T. Viral phylodynamics. PLoS Comput. Biol. 9, e1002947 (2013).

    ADS 
    MathSciNet 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 31.

    Legg, J. P. & Fauquet, C. M. Cassava mosaic geminiviruses in Africa. Plant Mol. Biol. 56, 585–599 (2004).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 32.

    Legg, J. P., Ndjelassili, F. & Okao-Okuja, G. First report of cassava mosaic disease and cassava mosaic geminiviruses in Gabon. Plant Pathol. 53, 232 (2004).

    Article 

    Google Scholar 

  • 33.

    Legg, J. P. Bemisia tabaci: the whitefly vector of cassava mosaic geminiviruses in Africa: an ecological perspective. Afr. Crop Sci. J. 2, 437–448 (1994).

    Google Scholar 

  • 34.

    Fargette, D. & Thresh, J. M. The ecology of African cassava mosaic geminivirus. In Ecology of Plant Pathogens (eds Blakeman, J. P. & Williamson, B.) 269–282 (CAB International, Oxford, 1994).

  • 35.

    Anderson, P. K. & Morales, F. Whitefly and whitefly borne viruses in the tropics: building a knowledge base for global action (International Center for Tropical Agriculture, Cali, 2005).

  • 36.

    Zinga, I. et al. Epidemiological assessment of cassava mosaic disease in Central African Republic reveals the importance of mixed viral infection and poor health of plant cuttings. Crop Prot. 44, 6–12 (2013).

    Article 

    Google Scholar 

  • 37.

    Delêtre, M. The ins and outs of manioc diversity in Gabon, Central Africa: a pluridisciplinary approach to the dynamics of genetic diversity of Manihot esculenta Crantz (Euphorbiaceae) (Trinity College Dublin, 2010).

  • 38.

    Messe Mbega, C. Y. Les régions transfrontalières: un exemple d’intégration sociospatiale de la population en Afrique centrale? Éthique publique 17, http://ethiquepublique.revues.org/1724 (2015).

  • 39.

    Akinbade, S. A. et al. First report of the East African cassava mosaic virus-Uganda (EACMV-UG) infecting cassava (Manihot esculenta) in Cameroon. N. Dis. Rep. 22, 2044–0588 (2010).

    Google Scholar 

  • 40.

    Valam-Zango, A. et al. First report of cassava mosaic geminiviruses and the Uganda strain of East African cassava mosaic virus (EACMV-UG) associated with cassava mosaic disease in Equatorial Guinea. N. Dis. Rep. 32, 29 (2015).

    Article 

    Google Scholar 

  • 41.

    Trovão, N. S. et al. Host ecology determines the dispersal patterns of a plant virus. Virus Evol. 1, vev016 (2015).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 42.

    Sallinen, S. et al. Intraspecific host variation plays a key role in virus community assembly. Nat. Commun. 11, 5610 (2020).

    ADS 
    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 43.

    Patil, B. L., Legg, J. P., Kanju, E. & Fauquet, C. M. Cassava brown streak disease: a threat to food security in Africa. J. Gen. Virol. 96, 956–968 (2015).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 44.

    Maruthi, M. N., Jeremiah, S. C., Mohammed, I. U. & Legg, J. P. The role of the whitefly, Bemisia tabaci (Gennadius), and farmer practices in the spread of cassava brown streak ipomoviruses. J. Phytopathol. 165, 707–717 (2017).

    CAS 
    Article 

    Google Scholar 

  • 45.

    McQuaid, C. F., Gilligan, C. A. & van den Bosch, F. Considering behaviour to ensure the success of a disease control strategy. R. Soc. Open Sci. 4, 170721 (2017b).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 46.

    Almekinders, C. J. et al. Understanding the relations between farmers’ seed demand and research methods: the challenge to do better. Outlook Agric. 48, 16–21 (2019a).

    Article 

    Google Scholar 

  • 47.

    Almekinders, C. J. et al. Why interventions in the seed systems of roots, tubers and bananas crops do not reach their full potential. Food Secur. 11, 23–42 (2019b).

    Article 

    Google Scholar 

  • 48.

    R Foundation for Statistical Computing. R: a language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, 2018).

  • 49.

    Zeileis, A. ineq: Measuring inequality, concentration, and poverty. R package version 0.2-13. https://CRAN.R-project.org/package=ineq (2014).

  • 50.

    Alabi, O. J., Kumar, P. L. & Naidu, R. A. Multiplex PCR method for the detection of African cassava mosaic virus and East African cassava mosaic Cameroon virus in cassava. J. Virol. Methods 154, 111–120 (2008).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 51.

    Edgar, R. C. MUSCLE: multiple sequence alignment with high accuracy and high throughput. Nucleic Acids Res. 32, 1792–1797 (2004).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 52.

    Martin, D. P., Murrell, B., Golden, M., Khoosal, A. & Muhire, B. RDP4: detection and analysis of recombination patterns in virus genomes. Virus Evol. 1, vev003 (2015).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 53.

    Price, M. N., Dehal, P. S. & Arkin, A. P. FastTree 2–approximately maximum-likelihood trees for large alignments. PLoS ONE 5, e9490 (2010).

    ADS 
    PubMed 
    PubMed Central 
    Article 
    CAS 

    Google Scholar 

  • 54.

    Anisimova, M. & Gascuel, O. Approximate likelihood-ratio test for branches: a fast, accurate, and powerful alternative. Syst. Biol. 55, 539–552 (2006).

    PubMed 
    Article 

    Google Scholar 

  • 55.

    Rambaut, A., Lam, T. T., de Carvalho, L. M. & Pybus, O. G. Exploring the temporal structure of heterochronous sequences using TempEst. Virus Evol. 2, vew007 (2016).

    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 56.

    Ragonnet-Cronin, M. et al. Automated analysis of phylogenetic clusters. BMC Bioinforma. 14, 317 (2013).

    Article 

    Google Scholar 

  • 57.

    Chao, A. et al. Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecol. Monogr. 84, 45–67 (2014).

    Article 

    Google Scholar 

  • 58.

    Hsieh, T. C., Ma, K. H. & Chao, A. iNEXT: an R package for interpolation and extrapolation of species diversity (Hill numbers). Methods Ecol. Evol. 7, 1451–1456 (2016).

    Article 

    Google Scholar 

  • 59.

    Scherer, R. & Pallmann, P. Simboot: simultaneous inference for diversity indices. R package version 0.2-6. https://CRAN.R-project.org/package=simboot (2017).

  • 60.

    Oksanen J. et al. vegan: Community Ecology Package. R package version 2.4-1. https://CRAN.R-project.org/package=vegan (2016).

  • 61.

    Prost, S. & Anderson, C. N. K. TempNet: a method to display statistical parsimony networks for heterochronous DNA sequence data. Methods Ecol. Evol. 2, 663–667 (2011).

    Article 

    Google Scholar 

  • 62.

    Posada, D. & Crandall, K. A. Intraspecific gene genealogies: trees grafting into networks. TRENDS Ecol. Evol. 16, 37–45 (2001).

    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 63.

    Corander, J., Marttinen, P., Sirén, J. & Tang, J. Enhanced Bayesian modelling in BAPS software for learning genetic structures of populations. BMC Bioinforma. 9, 539 (2008).

    Article 
    CAS 

    Google Scholar 

  • 64.

    Cheng, L., Connor, T. R., Sirén, J., Aanensen, D. M. & Corander, J. Hierarchical and spatially explicit clustering of DNA sequences with BAPS software. Mol. Biol. Evol. 30, 1224–1228 (2013).

    CAS 
    PubMed 
    PubMed Central 
    Article 

    Google Scholar 

  • 65.

    De la Cruz, M. Métodos para analizar datos puntuales. In Introducción al Análisis Espacial de Datos en Ecología y Ciencias Ambientales: Métodos y Aplicaciones (eds Maestre, F. T., Escudero, A. & Bonet, A.) 76–127. (Asociación Española de Ecología Terrestre, Universidad Rey Juan Carlos y Caja de Ahorros del Mediterráneo, Madrid, 2008).

  • 66.

    Fick, S. E. & Hijmans, R. J. WorldClim 2: new 1km spatial resolution climate surfaces for global land areas. Int. J. Climatol. 37, 4302–4315 (2017).

    Article 

    Google Scholar 

  • 67.

    Mayaux, P., Bartholomé, E., Fritz, S. & Belward, A. A new land‐cover map of Africa for the year 2000. J. Biogeogr. 31, 861–877 (2004).

    Article 

    Google Scholar 

  • 68.

    Guthrie, M. The Classification of the Bantu Languages (Oxford Univ. Press for the International African Institute, London, 1948).

  • 69.

    Nei, M., Tajima, F. & Tateno, Y. Accuracy of estimated phylogenetic trees from molecular data. II. Gene frequency data. J. Mol. Evol. 19, 153–170 (1983).

    ADS 
    CAS 
    PubMed 
    Article 

    Google Scholar 

  • 70.

    Rogers, J. S. Deriving phylogenetic trees from allele frequencies: a comparison of nine genetic distances. Syst. Biol. 35, 297–310 (1986).

    Article 

    Google Scholar 


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