Computational protocol: Key Microbiota Identification Using Functional Gene Analysis during Pepper (Piper nigrum L.) Peeling

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[…] Raw sequence data were trimmed to remove low-quality sequences, and the pair-end reads were merged by IDBA (v 1.0) software. Bioinformatic analyses were performed using QIIME (v1.6) [] on the extracted high-quality sequences. Briefly, the sequences were aligned using PyNAST [] and clustered under 100% sequence identity using UCLUST [] to obtain the unique V3-V4 sequence set. After representative sequences were selected, the unique sequence set was classified into operational taxonomic units (OTUs) with a 97% threshold identity using UCLUST. ChimeraSlayer [] was employed to remove any potentially chimeric sequences in the representative set of OTUs. The taxonomy of each OTU representative sequence was assigned using the Ribosomal Database Project [] classifier with a minimum bootstrap threshold of 80%. OTUs that occurred only once or twice were discarded. A de novo taxonomic tree was constructed using a chimera-checked OTU representative set in FastTree [] for downstream analyses, including alpha and beta diversity calculations. To evaluate alpha diversity, Shannon–Wiener and Simpson’s diversity indices, and the Chao1 and rarefaction estimators were calculated. UniFrac [] metrics were calculated to evaluate beta diversity. Both weighted and unweighted calculations were performed prior to a principal coordinate analysis (PCoA).All statistical analyses were performed using R software. PCoA and Procrustes analyses were performed in R using the ade4-package. Correlation core OTUs were calculated by Spearman’s rank correlation coefficient and visualized as a heatmap in R using the “pheatmap” package. Mantel test analyses were performed in R using the vegan package.The sequence data reported in this paper have been deposited in the NCBI database (Accession Numbers: SRA: SRR2976395). […]

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