Bacterial 16S rRNA Gene Sequencing and Data Analysis

Barcode tag amplification of the bacterial 16S ribosomal RNA (rRNA) gene was previously performed on soil gDNA using primers 28F and 519R (Bissett et al., 2016; Ji et al., 2020; Zhang et al., 2020). ARISA analysis confirmed that each set of triplicate gDNA extractions were significantly correlated (data not shown; van Dorst et al., 2014b; Ferrari et al., 2015). Therefore, 16S rRNA sequencing and all downstream analysis was performed using a single gDNA extract from each of the soil samples. Paired-end amplicon sequencing was performed using the Illumina MiSeq platform (Illumina, 312 California, US) in accordance with protocols from the Biome of Australia Soil Environments (BASE) project by Bioplatforms Australia (Bissett et al., 2016). The Antarctic and high Arctic data were downloaded together from the Australian Antarctic Datacentre¹, and the BASE repository². Amplicon sequencing data for the Tibetan Plateau soils was obtained from Ji et al. (2020) and analyzed separately. Open operational taxonomic unit (OTU) picking, assignment and classification were performed according to previously described methods (Zhang et al., 2020). In brief, USEARCH v10.0.240 (Edgar et al., 2011) and VSEARCH v2.8.0 (Torbjørn et al., 2016) were employed according to the UPARSE-OTU algorithm (Edgar, 2013). Sequences were quality filtered, trimmed, and clustered de novo to classify OTUs at 97% identity, and assigned to separate sample-by-OTU matrices where singletons were discarded manually. Sequences were then taxonomically classified against the SILVA v3.2.1323 SSU rRNA database (Quast et al., 2013).