Additional file 1 of Spatio-temporal variation in the root-associated microbiota of orchard-grown apple trees
Creators: name: Becker, Maximilian Fernando
name: Hellmann, Manfred
name: Knief, Claudia
Publisher: name: figshare
Year: 2022
Subjects: subject: Plant Biology
subject: FOS: Biological sciences

description: Additional file 1. Figure S1. Photographs showing the root system of a fully grown commercial apple tree (top) and two rows of an apple orchard (bottom). Figure S2. Differential abundance analysis of the loosely (L) and tightly (T) associated bacteria in the three experimental field trials using ANCOM-BC. The heatmap shows the coefficients obtained from the ANCOM-BC log-linear model divided by their standard error (called W-value) with red indicating enrichment in the T-compartment. A is shown if ANCOM-BC showed significant differences using the padj-value in this comparison. The mean abundance of the families in their respective trial are shown in the adjacent barplot as % and only families with mean abundances ≥ 0.5% are shown (ST refers to the spatio-temporal trial). A greyed-out field means that this family is below the 0.5% threshold in a trial. The families in the heatmap rows are separated by the phylum they belong to and displayed in different colours. Figure S3. Root-associated bacterial community composition of the loosely (L) and tightly (T) associated bacteria in four different root size sections and the bulk soil (b) of four apple trees analysed in the spatial trial. Constrained analysis of principle coordinates (CAP; based on DEICODE distance matrix and the variables compartment, tree and root quadrant) to assess the relevance of those variables on variation in bacterial community composition. Figure S4. Root-associated bacterial community composition of bulk soil near the apple trees analysed in the spatial trial. Constrained analysis of principle coordinates (CAP; based on DEICODE distance matrix and the variables tree and root quadrant) to assess the relevance of those variables on variation in bacterial community composition. Figure S5. Differential abundance analysis of the loosely (L) and tightly (T) associated bacteria and the bulk soil (B) in four different trees (T1 to T4) of the spatial trial using ANCOM-BC. The heat map shows the coefficients obtained from the ANCOM-BC log-linear model divided by their standard error (called W-value). A “*” is shown if ANCOM-BC showed significant differences using the padj-value in this comparison. The colour code indicates differential abundances between two samples with red indicating enrichment in the larger root sections. A grey colour indicates that this ASV was not detected in the respective compartment. The mean relative abundance of the ASVs in the entire compartment is shown as % and ASVs with mean abundances ≥ 0.1% in either compartment are displayed. The ASVs in the rows of the heat map are separated according to phylum. Figure S6. Pairwise PERMANOVA for comparison of time points in the temporal trial in the L- and T-compartment in the upper (A) and lower (B) panel, respectively. The colour codes for the R2-value and ‘.’ indicates a p-value between 0.05 and 0.1, ‘*’ indicates a p-value between 0.01 and 0.05, ‘**’ a p-value between 0.01 and 0.001. The padj-values using Benjamini–Hochberg correction for multiple testing are not displayed as they were all non-significant. Figure S7. Comparison of the T-compartment of six tree individuals in the temporal trial. Trees 1 to 3 and trees 4 to 6 were standing adjacently in separate opposite rows. (A) Pairwise PERMANOVA with p-values adjusted using Benjamini–Hochberg correction for multiple testing. The colour codes for the R2-value and ‘.’ indicates a padj-value between 0.05 and 0.1, ‘*’ indicates a padj-value between 0.01 and 0.05. (B) Differentially abundant ASVs identified by ANCOM-BC. The heat map shows the coefficients obtained from the ANCOM-BC log-linear model divided by their standard error (called W-value). A “*” is shown if ANCOM-BC showed significant differences using the padj-value in this comparison. The colour code indicates differential abundances between two samples with red indicating enrichment in the tree with the higher identifier number. The mean relative abundance of the ASVs in the T-compartment is shown as % and ASVs with mean abundances ≥0.3% are displayed. The ASVs in the rows of the heat map are separated according to phylum. Figure S8. Differentially abundant ASVs in the L- and T-compartment (upper and lower panel, respectively) for two different root size sections at four different time points according to ANCOM-BC. Fine roots had a diameter between 1 and 3 mm and thick roots between 3 and 6 mm. Samples were taken at four time points (TP1: 21.03.2019; TP2: 15.04.2019; TP3: 05.06.2019 and TP4: 20.08.2019). The first four columns compare the fine to the thick roots at each time point, the next three the different time points in the fine roots and the last three columns compare the thick roots at each time point. The heat map shows the coefficients obtained from the ANCOM-BC log-linear model divided by their standard error (called W-value). The colour code indicates differential abundances between two factors with red indicating enrichment in the second mentioned factor. A “*” is shown if ANCOM-BC showed significant differences using padj-values in this comparison. The mean abundance of the ASVs in the entire compartment is shown as % and only ASVs with mean abundances ≥ 0.3% are shown. Table S1. The sampling time points of the temporal trial (left) and the spatio-temporal (ST) trial (right). Table S2. Sequences of bar coded forward primers targeting the 16SrRNA gene. Primers include a bar code (8 bp) and the primer sequence itself. The reverse primer was not modified. Table S3. The hierarchies in each of the trials with the number of samples. Total read number after quality filtering, mean number of reads per sample and the number of samples remaining after quality filtering. Table S4. The ten most prominent genera in each trial with their mean relative abundance and standard deviation (SD). Table S5. Differences in bacterial beta diversity independence on tree individual and root size section in the loosely (L) and tightly (T) associated root microbiota in the spatial trial. Effect sizes in beta diversity were assessed by pairwise PERMANOVA based on DEICODE distance matrices and padj-values calculated using Bonferroni’s algorithm. Table S6. Significant differences in the apple root-associated bacterial community structure due to temporal, root size and spatial effects. The spatial effects in terms of tree-to-tree variation, longitudinal position of the tree and row of the tree were analysed separately. Effect sizes were analysed by PERMANOVA based on DEICODE distance matrices. Significant results are printed in bold.