Role of host genetic diversity for susceptibility-to-infection in the evolution of virulence of a plant virus

This article has been accepted for publication in Virus Evolution published by Oxford University Press.[EN] Predicting viral emergence is difficult due to the stochastic nature of the underlying processes and the many factors that govern pathogen evolution. Environmental factors affecting the host, the pathogen and the interaction between both are key in emergence. In particular, infectious disease dynamics are affected by spatiotemporal heterogeneity in their environments. A broad knowledge of these factors will allow better estimating where and when viral emergence is more likely to occur. Here, we investigate how the population structure for susceptibility-to-infection genes of the plant Arabidopsis thaliana shapes the evolution of Turnip mosaic virus (TuMV). For doing so we have evolved TuMV lineages in two radically different host population structures: (1) a metapopulation subdivided into six demes (subpopulations); each one being composed of individuals from only one of six possible A. thaliana ecotypes and (2) a well-mixed population constituted by equal number of plants from the same six A. thaliana ecotypes. These two populations were evolved for twelve serial passages. At the end of the experimental evolution, we found faster adaptation of TuMV to each ecotype in the metapopulation than in the well-mixed heterogeneous host populations. However, viruses evolved in well-mixed populations were more pathogenic and infectious than viruses evolved in the metapopulation. Furthermore, the viruses evolved in the demes showed stronger signatures of local specialization than viruses evolved in the well-mixed populations. These results illustrate how the genetic diversity of hosts in an experimental ecosystem favors the evolution of virulence of a pathogen.We thank Francisca de la Iglesia for continuous excellent technical support. Work was supported by Spain's Agencia Estatal de Investigacion-FEDER grant BFU2015-65037-P and Generalitat Valenciana grant GRISOLIA/2018/005 to S.F.E. R.G. was supported by Spain's Agencia Estatal de Investigacion pre-doctoral contract BES-2016-077078.González, R.; Butkovic, A.; Elena Fito, SF. (2019). Role of host genetic diversity for susceptibility-to-infection in the evolution of virulence of a plant virus. Virus Evolution. 5(2):1-12. https://doi.org/10.1093/ve/vez024S11252Altizer, S., Dobson, A., Hosseini, P., Hudson, P., Pascual, M., & Rohani, P. (2006). Seasonality and the dynamics of infectious diseases. Ecology Letters, 9(4), 467-484. doi:10.1111/j.1461-0248.2005.00879.xAnttila, J., Kaitala, V., Laakso, J., & Ruokolainen, L. (2015). Environmental Variation Generates Environmental Opportunist Pathogen Outbreaks. PLOS ONE, 10(12), e0145511. doi:10.1371/journal.pone.0145511Bascompte, J., Jordano, P., Melian, C. J., & Olesen, J. M. (2003). The nested assembly of plant-animal mutualistic networks. Proceedings of the National Academy of Sciences, 100(16), 9383-9387. doi:10.1073/pnas.1633576100Baylis, M. (2017). Potential impact of climate change on emerging vector-borne and other infections in the UK. Environmental Health, 16(S1). doi:10.1186/s12940-017-0326-1Belshaw, R., Gardner, A., Rambaut, A., & Pybus, O. G. (2008). Pacing a small cage: mutation and RNA viruses. Trends in Ecology & Evolution, 23(4), 188-193. doi:10.1016/j.tree.2007.11.010Bennett, A. F., Lenski, R. E., & Mittler, J. E. (1992). EVOLUTIONARY ADAPTATION TO TEMPERATURE. I. FITNESS RESPONSES OF ESCHERICHIA COLI TO CHANGES IN ITS THERMAL ENVIRONMENT. Evolution, 46(1), 16-30. doi:10.1111/j.1558-5646.1992.tb01981.xBerngruber, T. W., Lion, S., & Gandon, S. (2015). Spatial Structure, Transmission Modes and the Evolution of Viral Exploitation Strategies. PLOS Pathogens, 11(4), e1004810. doi:10.1371/journal.ppat.1004810Blüthgen, N., Menzel, F., & Blüthgen, N. (2006). BMC Ecology, 6(1), 9. doi:10.1186/1472-6785-6-9Boots, M., & Mealor, M. (2007). Local Interactions Select for Lower Pathogen Infectivity. Science, 315(5816), 1284-1286. doi:10.1126/science.1137126Boots, M., & Sasaki, A. (1999). ‘Small worlds’ and the evolution of virulence: infection occurs locally and at a distance. Proceedings of the Royal Society of London. Series B: Biological Sciences, 266(1432), 1933-1938. doi:10.1098/rspb.1999.0869Boots, M., & Sasaki, A. (2002). Parasite‐Driven Extinction in Spatially Explicit Host‐Parasite Systems. The American Naturalist, 159(6), 706-713. doi:10.1086/339996BROCKHURST, M. A., BUCKLING, A., & RAINEY, P. B. (2006). Spatial heterogeneity and the stability of host-parasite coexistence. Journal of Evolutionary Biology, 19(2), 374-379. doi:10.1111/j.1420-9101.2005.01026.xBrown, J. K. M., & Tellier, A. (2011). Plant-Parasite Coevolution: Bridging the Gap between Genetics and Ecology. Annual Review of Phytopathology, 49(1), 345-367. doi:10.1146/annurev-phyto-072910-095301Chabas, H., Lion, S., Nicot, A., Meaden, S., van Houte, S., Moineau, S., … Gandon, S. (2018). Evolutionary emergence of infectious diseases in heterogeneous host populations. PLOS Biology, 16(9), e2006738. doi:10.1371/journal.pbio.2006738Chen, C. C., Chao, C. H., Chen, C. C., Yeh, S. D., Tsai, H. T., & Chang, C. A. (2003). Identification of Turnip mosaic virus Isolates Causing Yellow Stripe and Spot on Calla Lily. Plant Disease, 87(8), 901-905. doi:10.1094/pdis.2003.87.8.901Comins, H. N., Hassell, M. P., & May, R. M. (1992). The Spatial Dynamics of Host--Parasitoid Systems. The Journal of Animal Ecology, 61(3), 735. doi:10.2307/5627Cornwall, D. H., Kubinak, J. L., Zachary, E., Stark, D. L., Seipel, D., & Potts, W. K. (2018). Experimental manipulation of population-level MHC diversity controls pathogen virulence evolution inMus musculus. Journal of Evolutionary Biology, 31(2), 314-322. doi:10.1111/jeb.13225Cuevas, J. M., Moya, A., & Elena, S. F. (2003). Evolution of RNA virus in spatially structured heterogeneous environments. Journal of Evolutionary Biology, 16(3), 456-466. doi:10.1046/j.1420-9101.2003.00547.xDi Giallonardo, F., & Holmes, E. C. (2015). Viral biocontrol: grand experiments in disease emergence and evolution. Trends in Microbiology, 23(2), 83-90. doi:10.1016/j.tim.2014.10.004Engering, A., Hogerwerf, L., & Slingenbergh, J. (2013). Pathogen–host–environment interplay and disease emergence. Emerging Microbes & Infections, 2(1), 1-7. doi:10.1038/emi.2013.5Fry, J. D. (1996). The Evolution of Host Specialization: Are Trade-Offs Overrated? The American Naturalist, 148, S84-S107. doi:10.1086/285904Furio, V., Garijo, R., Duran, M., Moya, A., Bell, J. C., & Sanjuan, R. (2012). Relationship between within-Host Fitness and Virulence in the Vesicular Stomatitis Virus: Correlation with Partial Decoupling. Journal of Virology, 86(22), 12228-12236. doi:10.1128/jvi.00755-12Gandon, S. (2004). EVOLUTION OF MULTIHOST PARASITES. Evolution, 58(3), 455-469. doi:10.1111/j.0014-3820.2004.tb01669.xLocal adaptation and gene-for-gene coevolution in a metapopulation model. (1996). Proceedings of the Royal Society of London. Series B: Biological Sciences, 263(1373), 1003-1009. doi:10.1098/rspb.1996.0148Gandon, S., & Michalakis, Y. (2002). Local adaptation, evolutionary potential and host-parasite coevolution: interactions between migration, mutation, population size and generation time. Journal of Evolutionary Biology, 15(3), 451-462. doi:10.1046/j.1420-9101.2002.00402.xGanusov, V. V., Bergstrom, C. T., & Antia, R. (2002). WITHIN-HOST POPULATION DYNAMICS AND THE EVOLUTION OF MICROPARASITES IN A HETEROGENEOUS HOST POPULATION. Evolution, 56(2), 213-223. doi:10.1111/j.0014-3820.2002.tb01332.xGarrett, K. A., Dendy, S. P., Frank, E. E., Rouse, M. N., & Travers, S. E. (2006). Climate Change Effects on Plant Disease: Genomes to Ecosystems. Annual Review of Phytopathology, 44(1), 489-509. doi:10.1146/annurev.phyto.44.070505.143420Gavrilets, S., & Gibson, N. (2002). Fixation probabilities in a spatially heterogeneous environment. Population Ecology, 44(2), 51-58. doi:10.1007/s101440200007HARAGUCHI, Y., & SASAKI, A. (2000). The Evolution of Parasite Virulence and Transmission Rate in a Spatially Structured Population. Journal of Theoretical Biology, 203(2), 85-96. doi:10.1006/jtbi.1999.1065Hillung, J., Cuevas, J. M., Valverde, S., & Elena, S. F. (2014). EXPERIMENTAL EVOLUTION OF AN EMERGING PLANT VIRUS IN HOST GENOTYPES THAT DIFFER IN THEIR SUSCEPTIBILITY TO INFECTION. Evolution, 68(9), 2467-2480. doi:10.1111/evo.12458HUGHES, W. O. H., & BOOMSMA, J. J. (2006). Does genetic diversity hinder parasite evolution in social insect colonies? Journal of Evolutionary Biology, 19(1), 132-143. doi:10.1111/j.1420-9101.2005.00979.xKassen, R. (2002). The experimental evolution of specialists, generalists, and the maintenance of diversity. Journal of Evolutionary Biology, 15(2), 173-190. doi:10.1046/j.1420-9101.2002.00377.xKassen, R., & Bell, G. (1998). Experimental evolution in Chlamydomonas. IV. Selection in environments that vary through time at different scales. Heredity, 80(6), 732-741. doi:10.1046/j.1365-2540.1998.00329.xKoonin, E. V., Wolf, Y. I., Nagasaki, K., & Dolja, V. V. (2008). The Big Bang of picorna-like virus evolution antedates the radiation of eukaryotic supergroups. Nature Reviews Microbiology, 6(12), 925-939. doi:10.1038/nrmicro2030Kubinak, J. L., Cornwall, D. H., Hasenkrug, K. J., Adler, F. R., & Potts, W. K. (2015). Serial infection of diverse host ( Mus ) genotypes rapidly impedes pathogen fitness and virulence. Proceedings of the Royal Society B: Biological Sciences, 282(1798), 20141568. doi:10.1098/rspb.2014.1568Leggett, H. C., Buckling, A., Long, G. H., & Boots, M. (2013). Generalism and the evolution of parasite virulence. Trends in Ecology & Evolution, 28(10), 592-596. doi:10.1016/j.tree.2013.07.002Lively, C. M. (2010). The Effect of Host Genetic Diversity on Disease Spread. The American Naturalist, 175(6), E149-E152. doi:10.1086/652430Malpica, J. M., Sacristán, S., Fraile, A., & García-Arenal, F. (2006). Association and Host Selectivity in Multi-Host Pathogens. PLoS ONE, 1(1), e41. doi:10.1371/journal.pone.0000041McLeish, M., Sacristán, S., Fraile, A., & García-Arenal, F. (2017). Scale dependencies and generalism in host use shape virus prevalence. Proceedings of the Royal Society B: Biological Sciences, 284(1869), 20172066. doi:10.1098/rspb.2017.2066Moreno-Gámez, S., Stephan, W., & Tellier, A. (2013). Effect of disease prevalence and spatial heterogeneity on polymorphism maintenance in host-parasite interactions. Plant Pathology, 62, 133-141. doi:10.1111/ppa.12131Morens, D. M., & Fauci, A. S. (2013). Emerging Infectious Diseases: Threats to Human Health and Global Stability. PLoS Pathogens, 9(7), e1003467. doi:10.1371/journal.ppat.1003467Newman, M. E. J. (2006). Modularity and community structure in networks. Proceedings of the National Academy of Sciences, 103(23), 8577-8582. doi:10.1073/pnas.0601602103Papaïx, J., David, O., Lannou, C., & Monod, H. (2013). Dynamics of Adaptation in Spatially Heterogeneous Metapopulations. PLoS ONE, 8(2), e54697. doi:10.1371/journal.pone.0054697Parratt, S. R., Numminen, E., & Laine, A.-L. (2016). Infectious Disease Dynamics in Heterogeneous Landscapes. Annual Review of Ecology, Evolution, and Systematics, 47(1), 283-306. doi:10.1146/annurev-ecolsys-121415-032321Pfennig, K. S. (2001). Evolution of pathogen virulence: the role of variation in host phenotype. Proceedings of the Royal Society of London. Series B: Biological Sciences, 268(1468), 755-760. doi:10.1098/rspb.2000.1582Regoes, R. R., Nowak, M. A., & Bonhoeffer, S. (2000). EVOLUTION OF VIRULENCE IN A HETEROGENEOUS HOST POPULATION. Evolution, 54(1), 64-71. doi:10.1111/j.0014-3820.2000.tb00008.xRodelo-Urrego, M., Pagán, I., González-Jara, P., Betancourt, M., Moreno-Letelier, A., Ayllón, M. A., … García-Arenal, F. (2013). Landscape heterogeneity shapes host-parasite interactions and results in apparent plant-virus codivergence. Molecular Ecology, 22(8), 2325-2340. doi:10.1111/mec.12232Rodelo-Urrego, M., García-Arenal, F., & Pagán, I. (2015). The effect of ecosystem biodiversity on virus genetic diversity depends on virus species: A study of chiltepin-infecting begomoviruses in Mexico. Virus Evolution, 1(1). doi:10.1093/ve/vev004RodrÍguez, D. (2001). Models of Infectious Diseases in Spatially Heterogeneous Environments. Bulletin of Mathematical Biology, 63(3), 547-571. doi:10.1006/bulm.2001.0231Rosenthal, S. R., Ostfeld, R. S., McGarvey, S. T., Lurie, M. N., & Smith, K. F. (2015). Redefining disease emergence to improve prioritization and macro-ecological analyses. One Health, 1, 17-23. doi:10.1016/j.onehlt.2015.08.001Rubio, B., Cosson, P., Caballero, M., Revers, F., Bergelson, J., Roux, F., & Schurdi‐Levraud, V. (2018). Genome‐wide association study reveals new loci involved in Arabidopsis thaliana and Turnip mosaic virus (Tu MV ) interactions in the field. New Phytologist, 221(4), 2026-2038. doi:10.1111/nph.15507Schmid-Hempel, P., & Koella, J. C. (1994). Variability and its implications for host-parasite interactions. Parasitology Today, 10(3), 98-102. doi:10.1016/0169-4758(94)90007-8Simko, I., & Piepho, H.-P. (2012). The Area Under the Disease Progress Stairs: Calculation, Advantage, and Application. Phytopathology®, 102(4), 381-389. doi:10.1094/phyto-07-11-0216Thrall, P. H., & Burdon, J. J. (2003). Evolution of Virulence in a Plant Host-Pathogen Metapopulation. Science, 299(5613), 1735-1737. doi:10.1126/science.1080070Thrall, P. H., Laine, A.-L., Ravensdale, M., Nemri, A., Dodds, P. N., Barrett, L. G., & Burdon, J. J. (2012). Rapid genetic change underpins antagonistic coevolution in a natural host-pathogen metapopulation. Ecology Letters, 15(5), 425-435. doi:10.1111/j.1461-0248.2012.01749.xVurro, M., Bonciani, B., & Vannacci, G. (2010). Emerging infectious diseases of crop plants in developing countries: impact on agriculture and socio-economic consequences. Food Security, 2(2), 113-132. doi:10.1007/s12571-010-0062-7Weitz, J. S., Poisot, T., Meyer, J. R., Flores, C. O., Valverde, S., Sullivan, M. B., & Hochberg, M. E. (2013). Phage–bacteria infection networks. Trends in Microbiology, 21(2), 82-91. doi:10.1016/j.tim.2012.11.003Whitlock, M. C. (1996). The Red Queen Beats the Jack-Of-All-Trades: The Limitations on the Evolution of Phenotypic Plasticity and Niche Breadth. The American Naturalist, 148, S65-S77. doi:10.1086/285902Whitlock, M. C., & Gomulkiewicz, R. (2005). Probability of Fixation in a Heterogeneous Environment. Genetics, 171(3), 1407-1417. doi:10.1534/genetics.104.040089Woolhouse, M. E. J., & Dye, C. (2001). Preface. Philosophical Transactions of the Royal Society of London. Series B: Biological Sciences, 356(1411), 981-982. doi:10.1098/rstb.2001.0899Yates, A., Antia, R., & Regoes, R. R. (2006). How do pathogen evolution and host heterogeneity interact in disease emergence? Proceedings of the Royal Society B: Biological Sciences, 273(1605), 3075-3083. doi:10.1098/rspb.2006.368

Effect of Biodiversity Changes in Disease Risk: Exploring Disease Emergence in a Plant-Virus System

The effect of biodiversity on the ability of parasites to infect their host and cause disease (i.e. disease risk) is a major question in pathology, which is central to understand the emergence of infectious diseases, and to develop strategies for their management. Two hypotheses, which can be considered as extremes of a continuum, relate biodiversity to disease risk: One states that biodiversity is positively correlated with disease risk (Amplification Effect), and the second predicts a negative correlation between biodiversity and disease risk (Dilution Effect). Which of them applies better to different host-parasite systems is still a source of debate, due to limited experimental or empirical data. This is especially the case for viral diseases of plants. To address this subject, we have monitored for three years the prevalence of several viruses, and virus-associated symptoms, in populations of wild pepper (chiltepin) under different levels of human management. For each population, we also measured the habitat species diversity, host plant genetic diversity and host plant density. Results indicate that disease and infection risk increased with the level of human management, which was associated with decreased species diversity and host genetic diversity, and with increased host plant density. Importantly, species diversity of the habitat was the primary predictor of disease risk for wild chiltepin populations. This changed in managed populations where host genetic diversity was the primary predictor. Host density was generally a poorer predictor of disease and infection risk. These results support the dilution effect hypothesis, and underline the relevance of different ecological factors in determining disease/infection risk in host plant populations under different levels of anthropic influence. These results are relevant for managing plant diseases and for establishing conservation policies for endangered plant species

Coevolución virus-planta: impacto de las infecciones virales en poblaciones silvestres de Chiltepín (capsicum annuum var. Aviculare (dierbach) d’arcy & eshbaugh) en México.

El impacto negativo que tienen los virus en las plantas hace que estos puedan ejercer un papel ecológico como moduladores de la dinámica espacio-temporal de las poblaciones de sus huéspedes. Entender cuáles son los mecanismos genéticos y los factores ambientales que determinan tanto la epidemiología como la estructura genética de las poblaciones de virus puede resultar de gran ayuda para la comprensión del papel ecológico de las infecciones virales. Sin embargo, existen pocos trabajos experimentales que hayan abordado esta cuestión. En esta tesis, se analiza el efecto de la heterogeneidad del paisaje sobre la incidencia de los virus y la estructura genética de sus poblaciones. Asimismo, se explora como dichos factores ambientales influyen en la importancia relativa que los principales mecanismos de generación de variabilidad genética (mutación, recombinación y migración) tienen en la evolución de los virus. Para ello se ha usado como sistema los begomovirus que infectan poblaciones de chiltepín (Capsicum annuum var. aviculare (Dierbach) D´Arcy & Eshbaugh) en México. Se analizó la incidencia de diferentes virus en poblaciones de chiltepín distribuidas a lo largo de seis provincias biogeográficas, representando el área de distribución de la especie en México, y localizadas en hábitats con diferente grado de intervención humana: poblaciones sin intervención humana (silvestres); poblaciones toleradas (lindes y pastizales), y poblaciones manejadas por el hombre (monocultivos y huertos familiares). Entre los virus analizados, los begomovirus mostraron la mayor incidencia, detectándose en todas las poblaciones y años de muestreo. Las únicas dos especies de begomovirus que se encontraron infectando al chiltepín fueron: el virus del mosaico dorado del chile (Pepper golden mosaic virus, PepGMV) y el virus huasteco del amarilleo de venas del chile (Pepper huasteco yellow vein virus, PHYVV). Por ello, todos los análisis realizados en esta tesis se centran en estas dos especies de virus. La incidencia de PepGMV y PHYVV, tanto en infecciones simples como mixtas, aumento cuanto mayor fue el nivel de intervención humana en las poblaciones de chiltepín, lo que a su vez se asoció con una menor biodiversidad y una mayor densidad de plantas. Además, la incidencia de infecciones mixtas, altamente relacionada con la presencia de síntomas, fue también mayor en las poblaciones cultivadas. La incidencia de estos dos virus también varió en función de la población de chiltepín y de la provincia biogeográfica. Por tanto, estos resultados apoyan una de las hipótesis XVI clásicas de la Patología Vegetal según la cual la simplificación de los ecosistemas naturales debida a la intervención humana conduce a un mayor riesgo de enfermedad de las plantas, e ilustran sobre la importancia de la heterogeneidad del paisaje a diferentes escalas en la determinación de patrones epidemiológicos. La heterogeneidad del paisaje no solo afectó a la epidemiología de PepGMV y PHYVV, sino también a la estructura genética de sus poblaciones. En ambos virus, el nivel de diferenciación genética mayor fue la población, probablemente asociado a la capacidad de migración de su vector Bemisia tabaci; y en segundo lugar la provincia biogeográfica, lo que podría estar relacionado con el papel del ser humano como agente dispersor de PepGMV y PHYVV. La estima de las tasas de sustitución nucleotídica de las poblaciones de PepGMV y PHYVV mostró una rápida dinámica evolutiva. Los árboles filogenéticos de ambos virus presentaron una topología en estrella, lo que sugiere una expansión reciente en las poblaciones de chiltepín. La reconstrucción de los patrones de migración de ambos virus indicó que ésta expansión parece haberse producido desde la zona central de México siguiendo un patrón radial, y en los últimos 30 años. Es importante tener en cuenta que el patrón espacial de la diversidad genética de las poblaciones de PepGMV y PHYVV es similar al descrito previamente para el chiltepín lo que podría dar lugar a la congruencia de las genealogías del huésped y la de los virus. Dicha congruencia se encontró cuando se tuvieron en cuenta únicamente las poblaciones de hábitats silvestres y tolerados, lo que probablemente se debe a una codivergencia en el espacio pero no en el tiempo, dado que la evolución de virus y huésped han ocurrido a escalas temporales muy diferentes. Finalmente, el análisis de la frecuencia de recombinación en PepGMV y PHYVV indicó que esta juega un papel importante en la evolución de ambos virus, dependiendo su importancia del nivel de intervención humana de la población de chiltepín. Este factor afectó también a la intensidad de la selección a la que se ven sometidos los genomas de PepGMV y PHYVV. Los resultados de esta tesis ponen de manifiesto la importancia que la reducción de la biodiversidad asociada al nivel de intervención humana de las poblaciones de plantas y la heterogeneidad del paisaje tiene en la emergencia de nuevas enfermedades virales. Por tanto, es necesario considerar estos factores ambientales a la hora de comprender la epidemiologia y la evolución de los virus de plantas.XVII SUMMARY Plant viruses play a key role as modulators of the spatio-temporal dynamics of their host populations, due to their negative impact in plant fitness. Knowledge on the genetic and environmental factors that determine the epidemiology and the genetic structure of virus populations may help to understand the ecological role of viral infections. However, few experimental works have addressed this issue. This thesis analyses the effect of landscape heterogeneity in the prevalence of viruses and the genetic structure of their populations. Also, how these environmental factors influence the relative importance of the main mechanisms for generating genetic variability (mutation, recombination and migration) during virus evolution is explored. To do so, the begomoviruses infecting chiltepin (Capsicum annuum var. aviculare (Dierbach) D'Arcy & Eshbaugh) populations in Mexico were used. Incidence of different viruses in chiltepin populations of six biogeographical provinces representing the species distribution in Mexico was determined. Populations belonged to different habitats according to the level of human management: populations with no human intervention (Wild); populations naturally dispersed and tolerated in managed habitats (let-standing), and human managed populations (cultivated). Among the analyzed viruses, the begomoviruses showed the highest prevalence, being detected in all populations and sampling years. Only two begomovirus species infected chiltepin: Pepper golden mosaic virus, PepGMV and Pepper huasteco yellow vein virus, PHYVV. Therefore, all the analyses presented in this thesis are focused in these two viruses. The prevalence of PepGMV and PHYVV, in single and mixed infections, increased with higher levels of human management of the host population, which was associated with decreased biodiversity and increased plant density. Furthermore, cultivated populations showed higher prevalence of mixed infections and symptomatic plants. The prevalence of the two viruses also varied depending on the chiltepin population and on the biogeographical province. Therefore, these results support a classical hypothesis of Plant Pathology stating that simplification of natural ecosystems due to human management leads to an increased disease risk, and illustrate on the importance of landscape heterogeneity in determining epidemiological patterns. Landscape heterogeneity not only affected the epidemiology of PepGMV and PHYVV, but also the genetic structure of their populations. Both viruses had the highest level of genetic differentiation at the population scale, probably associated with the XVIII migration patterns of its vector Bemisia tabaci, and a second level at the biogeographical province scale, which could be related to the role of humans as dispersal agents of PepGMV and PHYVV. The estimates of nucleotide substitution rates of the virus populations indicated rapid evolutionary dynamics. Accordingly, phylogenetic trees of both viruses showed a star topology, suggesting a recent diversification in the chiltepin populations. Reconstruction of PepGMV and PHYVV migration patterns indicated that they expanded from central Mexico following a radial pattern during the last 30 years. Importantly, the spatial genetic structures of the virus populations were similar to that described previously for the chiltepin, which may result in the congruence of the host and virus genealogies. Such congruence was found only in wild and let-standing populations. This is probably due to a co-divergence in space but not in time, given the different evolutionary time scales of the host and virus populations. Finally, the frequency of recombination detected in the PepGMV and PHYVV populations indicated that this mechanism plays an important role in the evolution of both viruses at the intra-specific scale. The level of human management had a minor effect on the frequency of recombination, but influenced the strength of negative selective pressures in the viral genomes. The results of this thesis highlight the importance of decreased biodiversity in plant populations associated with the level of human management and of landscape heterogeneity on the emergence of new viral diseases. Therefore it is necessary to consider these environmental factors in order to fully understand the epidemiology and evolution of plant viruses

Bivariate relationships between ecological factors and disease/infection risk.

<p>Significant regressions of each ecological factor and the prevalence of symptomatic plants (A), and of begomovirus (B) and CMV infection (C), are represented according to the level of human management: Wild (green triangles), let-standing (red squares), and cultivated (blue dots). PCs with the highest association with each ecological factor are shown in parenthesis. <i>SR</i> = Species richness expressed as number of species, <i>H_e</i> = Host genetic diversity expressed as expected heterozygosity, <i>d</i> = Host plant density. Note the different scales in the X-axis depending on the ecological factor. The Y-axis represents marginal mean prevalence values for each population over the monitored period.</p

Geographic location of chiltepin populations, and prevalence of symptomatic plants, begomoviruses and CMV.

<p>Map shows the location of populations from wild (W), let standing (LSP, LSF), and cultivated (CMC, CHG) populations within six biogeographical provinces in Mexico. Bar graphics show the average prevalence of symptomatic (grey) and asymptomatic (black) plants, as well as the prevalence of begomovirus (green) and CMV (blue) infection, for each chiltepin population. Boxes group populations from the same biogeographical province, and are colored accordingly.</p

Laboratory-determined prevalence of begomoviruses and CMV infection in Mexican chiltepin populations.

<p>CMV-infected plants were detected by ELISA-DAS. Begomovirus infected plants were detected by PCR with specific primers in a subset of 1081 plants of the 1820 plants sampled (see Material and Methods).</p>1<p>Habitats belonged to three levels of human management.</p>2<p>Populations are designated with the first three letters of the name of the nearest village, plus a code indicating the habitat: W = wild, LSP = Let standing, pasture; LSF = Let standing, living fence; CHG = Cultivated, home garden; CMC = Cultivated, monoculture.</p>3<p>Total number of analysed plants per population.</p>4<p>Percentage of analysed plants detected as begomovirus-infected.</p>5<p>Percentage of analysed plants detected as CMV-infected.</p