DOI: 10.5281/zenodo.18665560
title: Integrated plant metabolic and microbiome signatures distinguish phytoprotection mechanisms underpinning single- vs dual-pathosystem soil suppressiveness

description: This repositery accompanies the submitted manuscript "Integrated plant metabolic and microbiome signatures distinguish phytoprotection mechanisms underpinning single- vs dual-pathosystem soil suppressiveness".

Data

Sequencing data is available under the BioProject accessions PRJNA1224598 and PRJNA1414627.

Plant health

Wheat crown rot severity and plant health measures (fresh shoot and root biomass, mortality) per soil, condition and replicate.

Metagenomics





Tobacco_Wheat_COG_rpkm_by_superkingdom.tsv : COGs abundance in read per kilobase million (RPKM), by superkingdom




kegg_count_taxa_pathways.RData : abundance of KOs and their associated pathway (in read count)




kegg_rpkm_taxa_pathways.RData : abundance of KOs and their associated pathway (in RPKM)




Tobacco_Wheat_COG_rpkm_by_order_SPO.tsv : RPKM for selected sporulation-related COGs, per bacterial order




Tobacco_Wheat_COG_rpkm_by_family_SPO.tsv : RPKM for selected sporulation-related COGs, per bacterial family




Tobacco_Wheat_COG_rpkm_by_genus_SPO.tsv : RPKM for selected sporulation-related COGs, per bacterial genus




Tobacco_fungi_KO_count_Savoie_mat.txt : Fungal KO abundance matrix (read count) for Savoie soils samples – associated metadata is stored in pheno_Tobacco_Fungi_Savoie.txt




Tobacco_fungi_KO_count_CH_mat.txt : Fungal KO abundance matrix (read count) for Swiss soils samples – associated metadata is stored in pheno_Tobacco_Fungi_CH.txt




Tobacco_fungi_KO_count_MS16_mat.txt : Fungal KO abundance matrix (read count) for Swiss suppressive soil MS16 samples – associated metadata is stored in pheno_Tobacco_Fungi_MS16.txt




Tobacco_fungi_KO_count_Ysa5.txt : Fungal KO abundance matrix (read count) for Savoie suppressive soil Ysa5 samples – associated metadata is stored in pheno_Tobacco_Fungi_Ysa5.txt




Tobacco_only_prok_COG_count_Savoie_mat.txt : Prokaryotic COG abundance matrix (read count) for Savoie soils samples – associated metadata is stored in pheno_Tobacco_only_Savoie.txt




Tobacco_only_prok_COG_count_CH_mat.txt : Prokaryotic COG abundance matrix (read count) for Swiss soils samples – associated metadata is stored in pheno_Tobacco_only_Switzerland.txt




Tobacco_only_prok_COG_count_MS16_mat.txt : Prokaryotic COG abundance matrix (read count) for Swiss suppressive soil MS16 samples – associated metadata is stored in pheno_Tobacco_only_MS16.txt




Tobacco_only_prok_COG_count_Ysa5_mat.txt : Prokaryotic COG abundance matrix (read count) for Savoie suppressive soil Ysa5 samples – associated metadata is stored in pheno_Tobacco_only_Ysa5.txt



Corresponding files for the wheat samples are stored in Wheat_<fungi_KO/only_prok_COG>count<Savoie/CH/MS16/Ysa5>, with associated metadata files.



listCOGs.txt : list of COGs of interest – related to sporulation, nitrogen fixation, and NRPS, polyketide and siderophore production

bestHits_id50_bins_COGs_selected.tsv : abundance of each COG of interest in contigs belonging to reconstructed bins

bin_statistics_TW_reformatted.tsv : bin statistics (completeness, contamination)

contig2bin.tsv : assignment of contigs to bins

contigs_antismash_TW.txt : abundance contigs belonging to reconstructed bins, and in which an antiSMASH cluster was annotated

tob_wheat_bins_counts.rds : abundance of bins in the tobacco and wheat rhizosphere metagenomes

totNreads_allSamples.txt : total number of reads in each sample


Metabolomics



Globale_NI_et_I_dataMatrix_racines.tabular : Wheat root metabolomes with ion abundance per sample (soil, condition and replicate)

sig_annotated_ions_wheat_roots.csv : log2-transformed fold change (FC) for compounds differentiating suppressive and conducive soils

Ions_Heatmap_Racines_Ble.xlsx : annotation of compounds differentiating suppressive and conducive soils


Metabarcoding



16S



ASV_rare_16S.RData: rarefied 16S ASV table

jki_seq13_metadata_french_swiss_Tobacco_Wheat.xls : metadata for 16S metabarcoding samples (wheat and tobacco rhizosphere)

metadata_16S.RData : additional metadata for 16S samples

jki_seq13_otu_curated.xlsx : abundance of 16S ASVs (read counts)

jki_seq13_taxa_curated.xlsx : taxonomic assignation of 16S ASVs



ITS



01_rarefied_ASVs_ed.txt : rarefied ITS ASV table with metadata

ASVs_v2.txt : non-rarefied ITS ASV table with metadata




Scripts

Plant health

wheatCrownRot_plots.R : Perform statistical analysis and plot figures related to disease severity and plant health measures (biomass, mortality).

Metagenomics



COG_bacteria_Savoie.R : Performs statistical analyses and plots figures for metagenome functional data for prokaryotes (with COG data) in Savoie soils. Statistics entail the CSS normalization of COGs, PERMANOVA and NMDS and identification of differentially abundant COGs.

COG_bacteria_Switzerland.R : Performs statistical analyses and plots figures for metagenome functional data for prokaryotes (with COG data) in Swiss soils. Statistics entail the CSS normalization of COGs and identification of differentially abundant COGs.

KO_Fungi_Savoie.R : Performs statistical analyses and plots figures for metagenome functional data for fungi (with KO data) in Savoie soils. Statistics entail the CSS normalization of KOs, PERMANOVA and NMDS and identification of differentially abundant COGs.

KO_Fungi_Switzerland.R : Performs statistical analyses and plots figures for metagenome functional data for fungi (with KO data) in Swiss soils. Statistics entail the CSS normalization of KOs and identification of differentially abundant COGs.

metagenomics_inoc_vs_non-inoc.R : Performs statistical analyses to compare the differences in functional potential in inoculated vs non-inoculated samples, in the Swiss and Savoie suppressive soil.

bins_stats_tobWheat.R : Performs statistical analyses and plots figures for the analyses of bins reconstructed from the metagenomes. Filters bin by contamination and completion, gets bins that are significantly differently abundant between soils of different status, and make bin abundance heatmap and heatmap for COG and antiSMASH annotations.


Metabarcoding



16S



rarefaction_16S_TobWheat.R : rarefies 16S metabarcoding data.

script_div_indices_16.R : computes diversity indices with the 16S metabarcoding data, assess impact of factors on community diversity (PERMANOVAs), boxplot representation

script_multidimensional_16S.R : assess impact of factors on community structure (PERMANOVAs), view community similarity between samples (NMDS), differential abundance analyses and upset plot representations



ITS



script_div_indices_ITS.R : computes diversity indices with the ITS metabarcoding data, assess impact of factors on community diversity (PERMANOVAs), boxplot representations

script_multidimensional_ITS.R : assess impact of factors on community structure (PERMANOVAs), view community similarity between samples (NMDS), differential abundance analyses and upset plot representations




Metabolomics

Wheat_roots_metabolomics.Rmd : Computes and plot PCA of wheat root metabolomes, and assess impact of factors on soil metabolome (PERMANOVAs). Compute and plot OPLS-DA with ion abundance in the root metabolomes, as well as the heatmap of annotated molecules which discriminate suppressive and conducive soil samples (from OPLS-DA results).

Final material paper

Figures presented in the submitted manuscript.

Tables

Tables presented in the submitted manuscript.