Computational protocol: Bacterial Community Responses to Soils along a Latitudinal and Vegetation Gradient on the Loess Plateau, China

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Protocol publication

[…] Several statistical analyses were performed separately on the soil property datasets using the statistical package for the social sciences (SPSS version 20.0 for Windows), including one-way ANOVA and S-K-N multiple range comparison (P = 0.05). The relationships between soil bacterial composition and the environmental factors were tested using linear regression analyses using SPSS 20.0 for Windows. The relationships between the soil bacterial composition and properties were evaluated using R.The resulting sequences were processed using Mothur software []. Briefly, the raw reads were first assigned to samples according to their tags and then the standard primers and barcodes were trimmed off, after which reads with length less than 200 bp or with ambiguous characters were removed. The chimeric sequences were also excluded by the chimera.uchime command with default parameters. After removing the barcode and primer sequences, the unique sequences were aligned against the reference sequence database (Silva database). The remaining reads were pre-clustered (http://www.mothur.org/wiki/Pre.cluster) and then clustered using uncorrected pairwise algorithm. In addition, Operational taxonomic units (OTUs) were defined as sharing >97% sequence identity using Furthest neighbor method (http://www.mothur.org/wiki/Cluster). An OTU-based analysis was performed to calculate the richness and diversity indices (Ace, Coverage, Chao, Simpson and Shannon) with a cutoff of 3% dissimilarity. Raw sequence data in FASTQ format are accessible from the NCBI SRA study number SRP070625, accession numbers SRX1602057- SRX16072. […]

Pipeline specifications

Software tools mothur, UCHIME
Application 16S rRNA-seq analysis
Organisms Bacteria, Bacteroidetes