SUPPLEMENTARY METHODS
Multiplex 454 pyrosequencing data processing
Multiplex tag pyrosequencing was performed by the Research and Testing Laboratory (Lubbock,
Texas, USA) using the 454 FLX titanium platform (Roche, Branford, CT, USA). Bacterial and
fungal assemblages were taxonomically characterised by sequencing of the bacterial 16S rRNA
genes amplified using primers 28F and 519R (Quere et al. 2005), and the fungal ITS region using
primers ITS1 (Gardes and Bruns 1993) and ITS4R (White et al. 1990) respectively. Sequence data
were analysed using the MOTHUR pipeline (Schloss et al. 2009). Raw data were provided as
standard flowgram format files, and were extracted and error-checked via the Pyronoise algorithm
(Quince et al. 2011). Sequence data were further quality screened by removing short reads (<150
bp), long homopolymers (>8 repeats) and truncation of 16S reads (>450 bp). The sequence data
was checked for chimeras using UCHIME algorithm (Edgar et al. 2011), and then were
preclustered at 1% to account for 454’s titanium instrument error rate. Datasets were initially
subsampled to equal depth; however, after determining no significant impact between
sub-sampled and non-subsampled datasets, the dataset was left intact.
Bacterial sequences were aligned to the curated SILVA secondary structure alignment (Pruesse et
al. 2007), and then clustered into operational taxonomic units (OTUs) based on 96% sequence
similarity (Kim et al. 2011). The taxonomic position of identified bacterial OTUs was assigned
using the Greengenes database (2013 May version) ((McDonald et al. 2012, Werner et al. 2012))
that was trimmed to the same region as the amplicons (V1-V3). An OTU abundance-by sample
matrix was generated from the bacterial dataset, and then the singletons were removed from
sample matrix.
For fungal amplicons, after the ITS1 region was extracted from the amplicon using software
package developed by Nilsson (in press), USEARCH software package (Edgar 2010) was used to
cluster fungal ITS1 sequences at 97% sequence similarity to loosely define OTUs. The
representative sequence were picked by MATTF v6 (Katoh and Toh 2008), and they were then
compared against UNITE fungal ITS database (Koljalg et al. 2005) by BLASTn (Altschul et al.
1990), and the top 15 matches were retrieved. To correct the clustering error, OTUs that shared
over 50% identical top matches were grouped together manually. The resulting OTU abundance
matrix was generated from the fungal community data with QIIME package (Caporaso et al.
2010).
Reference
Caporaso JG et al (2010) QIIME allows analysis of high-throughput community sequencing data.
Nat Meth 7:335-336
Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics
26: 2460-2461
Edgar RC (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics
27:2194-2200
Altschul SF et al (1990) Basic local alignment search tool. J. Mol. Biol. 215(3):403-410
Gardes M and Bruns TD (1993) ITS primers with enhanced specificity for basidiomycetes‐
application to the identification of mycorrhizae and rusts. Microb Ecol 2(2):113-118
Koljalg U et al (2005) UNITE: a database providing web-based methods for the molecular
identification of ectomycorrhizal fungi. New Phytol 166:1063-1068
Katoh K, Toh H (2008) Recent developments in the MAFFT multiple sequence alignment
program. Brief Bioinform 9:286-298
McDonald D et al (2012) An improved Greengenes taxonomy with explicit ranks for ecological
and evolutionary analyses of bacteria and archaea. ISME J 6:610-618
Nilsson RH et al (in press) An ITS1/ITS2 extractor for the fungal ITS region. Fungal Ecology
Pruesse E et al (2007) SILVA: a comprehensive online resource for quality checked and aligned
ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35:7188-7196
Kim M et al (2011) Evaluation of different partial 16S rRNA gene sequence regions for
phylogenetic analysis of microbiomes. J Microbiol Methods 84:81-87
Quince C et al (2011) Removing noise from pyrosequenced amplicons." BMC Bioinform 12(1):
38
Quere CL et al (2005) Ecosystem dynamics based on plankton functional types for global ocean
biogeochemistry models. Glob Chang Biol 11(11):2016-2040
Schloss PD et al (2009) Introducing mothur: open-source, platform-independent,
community-supported software for describing and comparing microbial communities. Appl
Environ Microbiol 75(23):7537-7541. doi:10.1128/aem.01541-09
Werner JJ et al (2012) Impact of training sets on classification of high-throughput bacterial 16s
rRNA gene surveys. ISME J 6:94-103
White TJ et al (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for
phylogenetics. PCR protocols: a guide to methods and applications 18:315-322