Patterns of seed dispersal in the wild sea beet (Beta vulgaris ssp. maritima) are predicted to be influenced by marine currents because populations are widely distributed along the European Atlantic coast. We investigated the potential influence of marine currents on the pattern of spatial genetic structuring in natural populations of sea beet. Populations were located along the French coasts of the Anglo-Norman gulf that features peculiar marine currents in the Channel. Thirty-three populations were sampled, among which 23 were continental and 10 were insular populations located in Jersey, Guernsey and Chausey, for a total of 1224 plants genotyped. To validate the coastal topography influence and the possibility of marine current orientated gene flow on the genetic features of sea beet populations, we assessed patterns of genetic structuring of cytoplasmic and nuclear diversity by: (i) searching for an isolation-by-distance (IBD) pattern using spatial autocorrelation tools; (ii) using the Monmonier algorithm to identify genetic boundaries in the area studied; and (iii) performing assignment tests that are based on multilocus genotype information to ascertain population membership of individuals. Our results showed a highly contrasted cytoplasmic and nuclear genetic differentiation and highlighted the peculiar situation of island populations. Beyond a classical isolation-by-distance due to short-range dispersal, genetic barriers fitting the orientation of marine currents were clearly identified. This suggests the occurrence of long-distance seed dispersal events and an asymmetrical gene flow separating the eastern and western part of the Anglo-Norman gulf.

Plant-inhabiting microorganisms interact directly with each other, forming complex microbial interaction networks. These interactions can either prevent or facilitate the establishment of new microbial species, such as a pathogen infecting the plant. Here, our aim was to identify the most likely interactions between Erysiphe alphitoides, the causal agent of oak powdery mildew, and other foliar microorganisms of pedunculate oak (Quercus robur L.). We combined metabarcoding techniques and a Bayesian method of network inference to decipher these interactions. Our results indicate that infection with E. alphitoides is accompanied by significant changes in the composition of the foliar fungal and bacterial communities. They also highlight 13 fungal operational taxonomic units (OTUs) and 13 bacterial OTUs likely to interact directly with E. alphitoides. Half of these OTUs, including the fungal endophytes Mycosphaerella punctiformis and Monochaetia kansensis, could be antagonists of E. alphitoides according to the inferred microbial network. Further studies will be required to validate these potential interactions experimentally. Overall, we showed that a combination of metabarcoding and network inference, by highlighting potential antagonists of pathogen species, could potentially improve the biological control of plant diseases.

No abstract