Bioinformatics
Bioinformatic processing was performed in QIIME1 (Caporaso et
al. , 2010) and QIIME 2 (Bolyen et al. , 2019). Samples were
demultiplexed according to their unique tag/index combinations
(Supporting Information Table S1), which were removed during the
process, together with the primer sequences (Supporting Information
Table S2). For subsequent analyses only forward reads were used, as
reverse reads often suffer from a lower PHRED quality and due to length
differences within the ITS gene region, which often prevents merging of
both reads. Three S. chirindensis samples which contained less
than 10 000 sequences were removed prior to downstream bioinformatic
analyses. The raw sequences from the remaining 183 samples were
subsequently passed through deblur (Amir et al. , 2017)
implemented in the QIIME 2 pipeline, which assigns raw sequence reads to
Amplicon Sequence Variants (ASVs). Reads were trimmed at 180 bp. The
UNITE database was used as reference sequences (version 8; 020219)
(https://unite.ut.ee/). Only ASVs which were classified as
belonging to the Kingdom Fungi were retained. Fungal ASVs were written
into a feature table, which was used for subsequent downstream analyses.
The full ASV feature table and all metadata relating to the manuscript
can be obtained from figshare:
10.6084/m9.figshare.14518200
– ASV feature table and
10.6084/m9.figshare.14518218
– metadata.
Analyses
All analyses were performed on the full, unrarified, ASV table. This was
done for two reasons. First, rarefying the ASV table to the smallest
sample size to account for differences in library sizes between samples
made no difference to the interpretation of the results (results not
shown). Second, from a statistical point of view, rarefaction is inept
for the comparison of relative abundances (McMurdie and Holmes, 2014;
Willis, 2019).
As predictor variables that are highly correlated can lead to spurious
effects on analyses, all continuous predictor variables were tested for
multi-collinearity prior to analyses (Supporting Information Table S3).
When two variables were highly correlated, i.e. r > ǀ0.75ǀ,
one of these variables was removed (Supporting Information Table S3).
Bush clump area, bush clump tree basal area and bush clump tree species
richness were highly correlated. Therefore, only bush clump tree basal
area was retained for analyses on endophyte composition and richness, as
bush clump tree basal area gives a good representation of available
woody tree host density within individual BCs. Bush clump area was only
retained in the analyses on successional trends, as BC area was a good
proxy for BC maturity and woody vegetation successional stage
(Jamison-Daniels et al. , 2021).