Transcriptomic analyses of the virus-vector-plant interactions in the rhizomania pathosystem

For many years, the rhizomania was considered as one of the most damaging disease in the sugar beet production. The disease, caused by the causal agent beet necrotic yellow vein virus and dispersed by the plasmodiophorid Polymyxa betae, is responsible notably for reduced taproot and rootlets proliferation, resulting in high yield losses. So far, the only efficient control against the disease is the use of resistant varieties against the virus. However, the observation of resistance breaking by some virus strains threaten this solution and therefore, it is now crucial to find new ways to control the disease. Because of the lack of information on the interactions between the three actors of the rhizomania disease, it is difficult to fully understand the rhizomania pathosystem. So far, remain many interrogations about the nature of the relationship of the vector and the plant it infects. The impact of the virus on its plant host is largely studied, but the interaction between the virus and the vector is not elucidated. Therefore, better understanding the interactions between the three actors in the pathosystem is essential to identify new efficient control strategies. This thesis aims to help deciphering the vector-host-virus interactions, using transcriptomic analysis of the sugar beet and the vector in the presence or in the absence of the virus. Because the rhizomania disease is the result of host-vector-virus interactions, it was important to study the disease in conditions the closest to reality. The main difficulty of the experimental design was that the BNYVV must be acquired and transmitted naturally by P. betae to its host in a fully controlled soil-free system. We demonstrated in this thesis that the experimental design and conditions used were adapted for a BNYVV acquisition and transmission by P. betae. Two normalization methods were evaluated for RNAseq read counts normalization: The Trimmed Mean of M-values (TMM) method and a novel normalization method using gene markers fetched with the tool mOTUs adapted from Marsh et al. (2018). We determined that the second method was not adapted in this case. At the end of this thesis, we managed to produce information on the sugar beet gene regulations during the infection of P. betae alone and the infection of P. betae and BNYVV compared to healthy sugar beets. After a gene ontology analysis, we identified that the functions related to oxidative stress, cell wall organization and ion transports were disturbed by the presence of P. betae and/or BNYVV. Functions were down-regulated in P. betae infected sugar beets, suggesting that the protist can hide from the plant defenses. Functions were in general up-regulated in BNYVV and P. betae infected plants. The up-regulation of pathogenesis-related genes suggests that the plant is reacting to a pathogen attack when both organisms are combined.