Ecological Archives E096-014-A1

Daniel C. Schlatter, Matthew G. Bakker, James M. Bradeen, and Linda L. Kinkel. 2015. Plant community richness and microbial interactions structure bacterial communities in soil. Ecology 96:134142. http://dx.doi.org/10.1890/13-1648.1

Appendix A. Supplemental methods and 454 data processing.

Raw flowgrams were denoised using the AmpliconNoise V1.24 algorithm (Quince et al., 2011). Next, barcodes were trimmed, reads were truncated to 315 bp, and the Seqnoise and Perseus algorithms were used to correct PCR errors and remove expected chimeras in the AmpliconNoise pipeline. The resulting FASTA file was further processed in mothur v1.22.2 (Schloss et al. 2009) using the Schloss SOPs as a guideline (Schloss et al., 2011). The reverse complements of unique sequences were aligned to the SILVA database using the Needleman-Wunsch algorithm with a kmer size of 8. To retain only the highest quality sequences in the alignment, the alignment was optimized to keep the longest 85% of overlapping sequences from the start of the sequencing read (338R primer). The alignment was filtered to remove gaps common to all sequences and sequences were classified using the Ribosomal Database Project naïve Bayesian classifier (Wang et al., 2007). After sequences classified as chloroplasts were removed, sequences were clustered into operational taxonomic units (OTUs) at 97% similarity using the average neighbor method. The consensus taxonomy was determined for each OTU. In order to equalize the depth of sampling for community structure and diversity analyses, 6,837 sequences were randomly sub-sampled without replacement from each biological replicate. The sub-sampled OTU table was used to determine the observed and estimated (Chao1) OTU richness and the inverse Simpson's (1/D) index of diversity for each sample. Finally, the Yue & Clayton index of similarity (ThetaYC) was used to explore community structure among samples. Sequence data are available in the NCBI Sequence Read Archive under accession SRR786944.

Literature cited

Quince, C., A. Lanzen, R. J. Davenport, and P. J. Turnbaugh. 2011. Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12: doi:10.1186/1471-2105-12-38.

Schloss, P. D., D. Gevers, and S. L. Westcott. 2011. Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNA-based studies. PLoS ONE 6:e27310.

Schloss, P. D., S.L. Westcott, T. Ryabin, J. R. Hall, M. Hartmann, E. B. Hollister, R. A. Lesniewski, B. B. Oakley, D. H. Parks, C. J. Robinson, J. W. Sahl, B. Stres, G. G. Thallinger, D. J. Van Horn, and C. F. Weber. 2009. Introducing mother: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and Environmental Microbiology 75:7537–7541.

Wang, Q., G. M. Garrity, J. M. Tiedje, and J. R. Cole. 2007. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Applied and Environmental Microbiology 73:5261–5267.


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