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Supplementary Information
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PCR cycling conditions
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Each PCR reaction contained DNA (2 ng), 200 nM of each primer, 0.25 µl MyTaqTM DNA
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polymerase (Bioline, Alexandria, Australia), 1 x of the supplied buffer, and 250 µM of each
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dNTP. The cycling conditions used for 16S rRNA gene amplification were as follows: 94oC
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for 2 minutes (one cycle), 98oC for 30s, 55oC for 30s, 72oC for 30s (28 cycles), and a final
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extension step of 72oC for 10 minutes. Fungal ITS1 region was amplified using the same
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conditions except that the annealing temperature used was 53oC. After amplification PCR
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products were cleaned with Agencourt® AMPure® beads (Beckman Coulter, Lane Cove,
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Australia) and quantified using Quant-iTTM Picogreen® dsDNA quantification kit (Life
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TechnologiesTM, Mulgrave, Australia) according to the manufacturer’s instructions and DNA
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concentration was normalised to 4 ng µl-1.
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T-RFLP
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Restriction digest were performed as follows: 25 ng of PCR product was added to a reaction
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mixture containing sterile water, 20 units of restriction enzyme AluI (New England Biolabs,
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Ipswich, MA) and 4 µl of the specified buffer. Reaction mixtures were incubated at 37°C for
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3 hours and subsequently stored at 4°C. Digests were desalted by precipitation by incubation
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with ice cold 150 µl of 75% isopropanol (Sigma-Aldrich, Sydney, Australia) (v/v) for 30
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minutes followed by centrifugation at 4000 rpm for 45 minutes. Digested and purified PCR
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products were re-suspended in nuclease-free sterile water. Digested PCR products were added
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to a 10 µl reaction mixture containing 9.7 µl of M Hidi formamide and 0.3 µl of GeneScanTM
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600 LIZ size standard (Applied Biosystems, Mulgrave, Australia) and denatured at 94°C for 3
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minutes. Fragment lengths were determined by electrophoresis using an AB3031xl Genetic
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Analyzer (Applied Biosystems).
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T-RFLP data processing
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Bacterial 16S rRNA gene T-RFLP profiles were processed by removing peaks smaller than
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29 bp and larger than 500 bp. The Interactive Binner R script (Ramette 2009) was used to bin
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the resulting fragments using a sliding window approach, with minimum and maximum size
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cut-offs of 40 and 500 bp respectively, minimum RFI (relative fluorescence intensity) of 0.09,
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a window size of 1.5 bp and a shift size of 0.15 bp. Fungal ITS T-RFLP profiles were treated
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similarly except that minimum and maximum size cut-offs were 30 and 600 bp, and a window
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size and a shift size of 1 and 0.1 bp were used respectively. T-RFLP analysis generated
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profiles of the relative abundance of ribotypes per samples (ribotypes represent a unit of
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microbial diversity obtained with T-RFLP corresponding to DNA fragments of specific size
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resulting from endonuclease digestion of PCR products).
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qPCR cycling conditions
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Bacterial 16S rRNA gene and fungal ITS1 region were quantified in triplicate reactions
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containing 1x SsoAdvancedTM SYBR® green Supermix (Bio-Rad, Hercules, CA), 400 nM
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primers, 2 µl DNA (diluted 1 in 10) and H2O to 10 µl. Cycling conditions were as follows: for
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16S rRNA gene, 95oC for 1 minute (one cycle), 95oC for 15s and 56oC for 20s (39 cycles); for
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ITS1, 95oC for 1 minute (one cycle), 95oC for 5s and 53oC for 20s and extension at 72oC (39
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cycles). A melt curve from 65oC to 95oC was added at the end of the amplification cycles.
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Standards were run in triplicates in each qPCR plate with 10-fold dilution series from 108 to
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100 copies µl-1 of purified PCR product from Pseudomonas fluorescens strain 5.2 or
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Fusarium oxysporum vasinfectum. Amplification efficiencies were > 90% and R2 were > 0.99
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for all bacterial and fungal calibration curves.
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WCNA analysis
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Weighted correlation network analysis was developed with the aim of reducing and
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integrating highly dimensional data in order to allow more robust associations to be drawn
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between biological and non-biological components of complex systems (Langfelder and
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Horvath, 2008). To build the network, the absolute value of the correlation coefficient
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between the abundance profiles of each ribotype was calculated, generating an abundance
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profile similarity matrix. A soft-thresholding procedure was applied to the abundance
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similarity matrix to calculate the adjacency matrix which expresses the connection strength
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between the ribotypes. Scale-free topology is thought to be a universal property of modular
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biological systems, as is the case of soil microbial communities (Barberán et al. 2012, Zhou et
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al. 2011). The soft-thresholding procedure leads to an emphasis of stronger over weaker
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connections between nodes (genes, OTUs or ribotypes) in order to detect robust, biologically
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meaningful modules within the network (Langfelder and Horvath 2008). In WCNA, node
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linkages vary continuously, and node membership in a module is also continuous, or fuzzy.
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Weighted networks will therefore better represent biological processes that vary continuously
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(Langfelder and Horvath, 2008). In WCNA-generated networks, modules are groups of nodes
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(genes, OTUs or ribotypes) of strong topological overlap, which is interpreted as nodes that
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co-correlate strongly (Yip and Horvath, 2007). The modules are detected using average
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linkage hierarchical clustering coupled with topological overlap matrix (TOM) based
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dissimilarity, and correspond therefore to branches in a node (OTUs, genes or ribotypes)
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hierarchical clustering tree.
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Supplementary references
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Barberán A, Bates ST, Casamayor EO, Fierer N (2012). Using network analysis to explore co-
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occurrence patterns in soil microbial communities. ISME Journal 6: 343-351.
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Langfelder P, Horvath S (2008). WGCNA: an R package for weighted correlation network analysis.
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BMC Bioinformatics 9: 559.
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Ramette A (2009). Quantitative community fingerprinting methods for estimating the abundance of
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operational taxonomic units in natural microbial communities. Applied and Environmental
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Microbiology 75: 2495-2505.
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Yip AM, Horvath S (2007). Gene network interconnectedness and the generalized topological overlap
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measure. BMC Bioinformatics 8: 22.
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Zhou J, Deng Y, Luo F, He Z, Yang Y (2011). Phylogenetic molecular ecological network of soil
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microbial communities in response to elevated CO2. MBio 2: pii: e00122-00111. doi:
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00110.01128/mBio.00122-00111.
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Supplentary Figure legends
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Figure S1: Map showing sampling locations
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