Additional file 1 of Revealing microbial consortia that interfere with grapevine downy mildew through microbiome epidemiology
Creators: name: Fournier, Paola
name: Pellan, Lucile
name: Jaswa, Aarti
name: Cambon, Marine C.
name: Chataigner, Alexandre
name: Bonnard, Olivier
name: Raynal, Marc
name: Debord, Christian
name: Poeydebat, Charlotte
name: Labarthe, Simon
name: Delmotte, François
name: This, Patrice
name: Vacher, Corinne
Publisher: name: figshare
Year: 2025
Subjects: subject: Microbiology
subject: FOS: Biological sciences
subject: Plant Biology

description: Supplementary Material 1. Methods S1: Amplification trial with the primer pair ITS1catta—ITS2ngs. Methods S2: Custom reference database built from a microbial culture collection. Methods S3: Taxonomic assignments using both public and custom reference databases. Figure S1: Map of vineyard plots monitored for downy mildew incidence and severity. Figure S2: Sampling design. Figure S3: Comparison of microbial community profiles for the leaf endosphere depending on the primer pair. Figure S4: Oomycetes detected in the leaf endosphere using the ITS1catta-ITS2ngs primer pair. Figure S5: Decision tree for assigning fungal (nrDNA ITS gene) and bacterial (16S rRNA gene) sequences. Figure S6: Disease progression curves for the 7 plot pairs. Figure S7: Variation in downy mildew primary inoculum in topsoil. Figure S8: Microbial community profiles depending on downy mildew incidence and severity in vineyard plots. Figure S9: Variation in microbial community composition across vineyard plots. Figure S10: Environmental factors driving variation in microbial community composition in 2022. Figure S11: Environmental factors driving variation in microbial community composition in 2023. Figure S12: Variations in the diversity of microbial communities depending on downy mildew incidence and severity in vineyard plots (2022 data). Figure S13: Variations in the diversity of microbial communities depending on downy mildew incidence and severity in vineyard plots (2023 data). Figure S14: Endosphere fungal taxa that vary in abundance with downy mildew incidence and severity. Figure S15: Topsoil fungal taxa that vary in abundance with downy mildew incidence and severity. Figure S16: Phyllosphere bacterial taxa that vary in abundance with downy mildew incidence and severity. Figure S17: Random Forest algorithm performance in predicting grapevine downy mildew incidence and severity using leaf microbiota composition. Figure S18: Random Forest algorithm performance in predicting grapevine downy mildew incidence and severity using topsoil microbiota data year-to-year. Figure S19: Random Forest algorithm performance in predicting grapevine downy mildew incidence and severity using leaf microbiota data year-to-year. Table S1: Environmental variables used to explain the variation in microbiota composition. Table S2: Factors driving variation in downy mildew inoculum in topsoil. Table S3: Summary of read and ASV loss during data processing. Table S4: Most abundant fungal species in the topsoil, phyllosphere and leaf endosphere of vineyard plots (2022 data). Table S5: Most abundant bacterial genera in the topsoil, phyllosphere and leaf endosphere of vineyard plots (2022 data). Table S6: Most abundant fungal species in the topsoil, phyllosphere and leaf endosphere of vineyard plots (2023 data). Table S7: Most abundant bacterial genera in the topsoil, phyllosphere and leaf endosphere of vineyard plots (2023 data). Table S8: Factors driving variation in microbiota alpha diversity (2022 data). Table S9: Factors driving variation in microbiota alpha diversity (2023 data). Table S10: Fungal taxa indicators of low downy mildew primary inoculum in topsoil. Table S11: Bacterial taxa indicators of low downy mildew primary inoculum in topsoil.