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Polymerase chain reaction (PCR) products were pooled together and purified using an Agarose Gel DNA purification kit (Takara, Otsu, Japan). An equal amount of PCR products from each sample was combined in a single tube to be sequenced on a Roche FLX 454 pyrosequencing machine (454 Life Science, Branford, CT, USA). Processing of Pyrosequencing Data Sequences obtained by pyrosequencing were processed and analyzed following the standard operating procedure described in the website1 using Mothur program v.1.27.0 (Schloss et al., 2011). The denoising process was implemented using the shhh.flows command which is the Mothur implementation of the PyroNoise component of the AmpliconNoise suite of programs. Barcode and primer sequences were removed, and sequences shorter than 200 bp with homopolymers longer than 8 bp were removed at the same time. Next, the sequences were aligned against the SILVA-compatible alignment database and then trimmed, so that subsequent analyses were constrained to the same portion of the 16S rRNA gene. Chimeric sequences were detected using the chimera.uchime command that use the sequences as their own reference to run de novo detection and identified chimeras were removed after that. The remaining reads were preclustered using the pre-cluster command2 to remove erroneous sequences derived from sequencing errors and then clustered using Mothur��s average algorithm. Taxonomic assignment of each OTU (clustered at 97% sequence similarity) was obtained by classifying alignments against Silva reference bacterial taxonomy files using the classify command at 80% Bayesian bootstrap cutoff with 1000 iterations. Sequences were deposited to the MG-RAST metagenomics analysis server3 and are available to the public (accession numbers from 4565119.3 to 4565142.3). For community-level SB203580 cost composition and each calculated metric, we accounted for the difference in the sampling efforts among the samples by randomly subsampling 4,900 sequences per sample. The number of sequences for rarefaction was determined according to the sample that yielded the lowest number of sequences after quality filtering (Supplementary Table S3). Statistical Analysis The number of phylotypes (the number of OTUs) was used to estimate the community richness. We chose Faith��s (1992) phylogenetic diversity index values (calculated as the sum of branch lengths between root and tips for a community) to estimate the phylogenetic community diversity. To determine if the different elevation samples formed unique phylogenetically related clusters, principal co-ordinates analysis (PCoA) of the UniFrac distance matrices were performed.