2.4 Sequence processing and data analysis
The raw reads were filtered through trimming and quality control steps prior to taxonomic assignment according to the QIIME v.1.7.0 quality control process (Caporaso et al. 2012). Adaptor/primer regions were removed, and potential chimeras were removed using USEARCHv9.2 (Edgar 2013). Reads were clustered at 97% into Molecular Operational Taxonomic Units (MOTUs) according to the standard setting in USEARCHv9.2 (Edgar 2013). High-quality clean reads that passed quality filtering were queried against the full NCBI database using BLASTn according to previous study (Berry et al. 2017). MOTUs were resolved to species, genus, or higher, for COΙ animals or rbcL plants primer assays based on the percent similarity threshold: Sequences with identity ≥ 99% to a single species were considered as a “species match,” and as a “genus match” if sequences had ≥ 98% similarity to one or more species within the same genus. DNA sequences in this study were deposited into the NCBI Sequence Read Archive (SRA) under accession number: PRJNA637184.
Alpha diversity (i.e., Chao1, Shannon and Simpson) matrices were performed using QIIME and displayed using R v.3.3.3. software. To evaluate the pattern of dispersion of samples within each season, beta diversity was calculated with the euclidean distance. Beta diversity was calculated using QIIME and visualized by two-dimensional principal coordinate analysis (PCoA). Diversity was compared between different seasons to assess temporal differences in diet composition. We also compared the relative abundance of food items at various taxonomic levels and at different seasons based on the linear discriminatory analysis (LDA) effect size (LEfSe) method using LEfSe software.