Miseq 300 bp paired end reads platform

Total genomic DNA was extracted from 0.5 g of each soil sample using the MP FastDNA^® SPIN Kit for soil (MP Biochemicals, Solon, OH, USA) following the manufacturer’s instructions. The V4 and V5 hypervariable regions of the bacterial 16S rRNA gene were PCR amplified using the primer pair 515F and 907R^{7 (link)}. The purified PCR amplicons were sequenced using an Illumina Miseq (300-bp paired-end reads) platform (Illumina Inc., San Diego, CA, USA). The acquired sequences were filtered by quality according to Caporaso, et al.^{51 (link)}. Chimeric sequences were removed using the UCHIME algorithm^{52 (link)} in the USEARCH package v. 6.1544^{53 (link)}. Sequences were grouped by taxonomy and assigned to OTUs at the 97% sequence identity level using the UPARSE package (http://drive5.com/uparse/)^{54 (link)}. After singleton removal, representative sequences were taxonomically assigned using the Ribosomal Database Project naïve Bayesian rRNA classifier within the SILVA database (release 128) at an 80% confidence threshold^{51 (link)}. All sequences were deposited in the NCBI Sequence Read Archive database (Biosample number: SAMN06105854-SAMN06105874).

Soil samples (0.5 g) were used to extract microbial DNA according to the QIAmp DNA Stool Mini Kit. To explore the soil denitrifying bacteria communities at three invasive sites, the target fragment qnorB was amplified with barcoded 2F 5′-GGNCAYCARGGNTAYGA-3′ and 5R 5′-ACCCANAGRTGNACNACCCACCA-3′. PCR amplification was conducted in an eight-cycle and the PCR products were purified with a GeneJET Gel Extraction Kit (Thermo Scientific, Waltham, MA, USA). Subsequently, the PCR product from each sample was sequenced on the Illumina MiSeq (300-bp paired-end reads) platform (Illumina Inc., San Diego, CA, USA) at the TinyGene Bio-Tech Co., Ltd. (Shanghai, China). The reads were distinguished from each sample and any sequences of low quality were deleted with the ultra-fast sequence analysis (USEARCH). The splicing sequence was qualified and filtered to yield the optimized sequences. Furthermore, operational taxonomic units (OTU) were obtained at a 97% similarity level using the UPARSE pipeline [24 (link)].