Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: the case of Pseudocercospora fijiensis invasion in Africa

The reconstruction of geographic and demographic scenarios of dissemination for invasive pathogens of crops is a key step towards improving the management of emerging infectious diseases. Nowadays, the reconstruction of biological invasions typically uses the information of both genetic and historical information to test for different hypotheses of colonization. The Approximate Bayesian Computation framework and its recent Random Forest development (ABC-RF) have been successfully used in evolutionary biology to decipher multiple histories of biological invasions. Yet, for some organisms, typically plant pathogens, historical data may not be reliable notably because of the difficulty to identify the organism and the delay between the introduction and the first mention. We investigated the history of the invasion of Africa by the fungal pathogen of banana, Pseudocercospora fijiensis, by testing the historical hypothesis against other plausible hypotheses. We analysed the genetic structure..., ,