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

Gilabert Aude, Rieux Adrien, Robert Stéphanie, Vitalis Renaud, Zapater Marie-Françoise, Abadie Catherine, Carlier Jean, Ravigné Virginie. 2023. Revisiting the historical scenario of a disease dissemination using genetic data and Approximate Bayesian Computation methodology: The case of Pseudocercospora fijiensis invasion in Africa. Ecology and Evolution, 13 (4):e10013, 17 p.

Url - jeu de données - Entrepôt autre : https://doi.org/10.5061/dryad.rn8pk0pgw

Résumé : The reconstruction of geographic and demographic scenarios of dissemination for invasive pathogens of crops is a key step toward 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 analyzed the genetic structure of eight populations from six eastern and western African countries, using 20 microsatellite markers and tested competing scenarios of population foundation using the ABC-RF methodology. We do find evidence for an invasion front consistent with the historical hypothesis, but also for the existence of another front never mentioned in historical records. We question the historical introduction point of the disease on the continent. Crucially, our results illustrate that even if ABC-RF inferences may sometimes fail to infer a single, well-supported scenario of invasion, they can be helpful in rejecting unlikely scenarios, which can prove much useful to shed light on disease dissemination routes.

Mots-clés Agrovoc : Musa acuminata, maladie des plantes, génétique des populations, champignon pathogène, transmission des maladies, Musa (bananes), théorie Bayésienne, Pseudocercospora

Mots-clés géographiques Agrovoc : Ouganda, Congo, Gabon, Cameroun, Nigéria, Côte d'Ivoire, Philippines

Mots-clés complémentaires : Pseudocercospora fijiensis

Mots-clés libres : Emerging disease, Population genetics, Approximate Bayesian Computation, Random Forest

Classification Agris : H20 - Maladies des plantes
U10 - Informatique, mathématiques et statistiques

Champ stratégique Cirad : CTS 4 (2019-) - Santé des plantes, des animaux et des écosystèmes

Agences de financement européennes : European Regional Development Fund

Agences de financement hors UE : Conseil Régional Languedoc-Roussillon, Agence Nationale de la Recherche, Agropolis Fondation, Conseil Général de La Réunion, Centre de Coopération Internationale en Recherche Agronomique pour le Développement

Projets sur financement : (FRA) Comprendre les émergences de maladies fongiques de plantes : vers une estimation des risques liés aux changements globaux, (FRA) Etude de Méthodes Inférentielles et Logiciels pour l'Evolution, (FRA) BIOFIS, (FRA) E-SPACE

Auteurs et affiliations

• Gilabert Aude, CIRAD-BIOS-UMR AGAP (FRA) ORCID: 0000-0003-0764-9171 - auteur correspondant
• Rieux Adrien, CIRAD-BIOS-UMR PVBMT (REU)
• Robert Stéphanie, Université de Montpellier (FRA)
• Vitalis Renaud, Université de Montpellier (FRA)
• Zapater Marie-Françoise, Université de Montpellier (FRA)
• Abadie Catherine, CIRAD-BIOS-UMR PHIM (FRA)
• Carlier Jean, CIRAD-BIOS-UMR PHIM (FRA) ORCID: 0000-0002-6967-1852
• Ravigné Virginie, CIRAD-BIOS-UMR PHIM (FRA) ORCID: 0000-0002-4252-2574

Source : Cirad-Agritrop (https://agritrop.cirad.fr/604584/)

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