Host ecology determines the dispersal patterns of a plant virus

Abstract

Since its isolation in 1966 in Kenya, rice yellow mottle virus (RYMV) has been reported throughout Africa resulting in one of the economically most important tropical plant emerging diseases. A thorough understanding of RYMV evolution and dispersal is critical to manage viral spread in tropical areas that heavily rely on agriculture for subsistence. Phylogenetic analyses have suggested a relatively recent expansion, perhaps driven by the intensification of agricultural practices, but this has not yet been examined in a coherent statistical framework. To gain insight into the historical spread of RYMV within Africa rice cultivations, we analyse a dataset of 300 coat protein gene sequences, sampled from East to West Africa over a 46-year period, using Bayesian evolutionary inference. Spatiotemporal reconstructions date the origin of RMYV back to 1852 (1791–1903) and confirm Tanzania as the most likely geographic origin. Following a single long-distance transmission event from East to West Africa, separate viral populations have been maintained for about a century. To identify the factors that shaped the RYMV distribution, we apply a generalised linear model (GLM) extension of discrete phylogenetic diffusion and provide strong support for distances measured on a rice connectivity landscape as the major determinant of RYMV spread. Phylogeographic estimates in continuous space further complement this by demonstrating more pronounced expansion dynamics in West Africa that are consistent with agricultural intensification and extensification. Taken together, our principled phylogeographic inference approach shows for the first time that host ecology dynamics have shaped the historical spread of a plant virus.

Identification of a Hypervirulent Pathotype of Rice yellow mottle virus: A Threat to Genetic Resistance Deployment in West-Central Africa

“…These differences can be explained by the crucial role of T49, identified as a preadaptation of RYMV to the African rice host, in the ability to overcome the resistance alleles of RYMV1 originating from O. glaberrima. Thus, after gathering the pathogenic data obtained from this study and previous studies (Pinel-Galzi et al 2007;Traoré et al 2010), as well as the spatial distribution of the RYMV strains and lineages in Africa (Fargette et al 2004;Pinel-Galzi et al 2009;Pinel-Galzi et al 2015;Traoré et al 2006a;Trovão et al 2015), a risk map of RYMV1 resistance breakdown was proposed (Fig. 4).…”

“…It has been detected in the neighboring countries Nigeria, Niger, and Togo, and its geographical distribution should be monitored, especially in Benin, Burkina-Faso, Cameroon, and Chad. The dispersal risk of RB genotypes can only be realistically estimated if taking into account the overall dispersal rate of the virus, the corridors of propagation, and the agroecological barriers to transmission, information made recently available for RYMV (Pinel-Galzi et al 2015;Trovão et al 2015). A spatiotemporal model for RYMV diffusion has been proposed, with an overall dispersal rate of approximately 15 km/ year (Trovão et al 2015).…”

“…The dispersal risk of RB genotypes can only be realistically estimated if taking into account the overall dispersal rate of the virus, the corridors of propagation, and the agroecological barriers to transmission, information made recently available for RYMV (Pinel-Galzi et al 2015;Trovão et al 2015). A spatiotemporal model for RYMV diffusion has been proposed, with an overall dispersal rate of approximately 15 km/ year (Trovão et al 2015). Strain circulation between West and WestCentral Africa was hindered for a long time by the scarcity of rice cultivation in the "yam belt" separating the two regions (Pinel-Galzi et al 2015).…”

“…Strain circulation between West and WestCentral Africa was hindered for a long time by the scarcity of rice cultivation in the "yam belt" separating the two regions (Pinel-Galzi et al 2015). This barrier is now fading with the current intensification of rice cultivation, especially along the Niger and Benue rivers, which is now an efficient corridor of propagation of the virus across the two regions (Trovão et al 2015). By contrast, the large forests of the Democratic Republic of the Congo, with sparse rice cultivation, still constitute an efficient barrier to the spread of RYMV between WestCentral and East Africa (Pinel-Galzi et al 2015;Trovão et al 2015).…”

“…By contrast, strain S2-S3, which is distributed in WestAfrica, harbors the derived trait T49. This region is the geographical distribution area of O. glaberrima (Traoré et al 2005;Trovão et al 2015). Additionally, the S1 strain is divided into two main lineages, S1wa and S1ca, which correlate to their spatial distribution in West and West-Central Africa, respectively.…”