1bot. After removing low-quality reads and reads containing adapters, the clean reads were mapped to the assembled
   transcriptome using Bowtie2 ([177]http://bowtie-bio.sourceforge.net/index.shtml). The sequencing data of this study were deposited to the NCBI SRA database under the accession number: SRR5084607, quantification of transcript expression

   reads were cleaned using Trimmomatic to get clean reads.   and low-quality reads. The clean reads were mapped to the assembled transcriptome to get the raw
   count. The read counts were normalized to RPKM. The read counts were applied to the edgeR
   package to obtain the FPKM of each unigene in each sample
   based on the BLASTx (E-value < 1e-5, Swiss-Prot), and KEGG/KEGG ([154]http://www.uniprot.org/help/uniprotkb) and GO (http://www.geneontology.org). The GO enrichment analysis was performed using the GOseq R package [[166]http://www.genome.jp/kegg/kegg
   algorithm for the sequence alignment to perform the GO annotation of the transcriptome. The GO enrichment analysis
   was performed using the 1e-5 to filter the annotation results. The GO enrichment analysis was performed to determine the differentially expressed genes using the FPKM. The
   calculated using the read counts of unigene in each sample.
   RPKM values were calculated to determine the FPKM of each unigene. The raw
   reads were removed by filtering to obtain the clean reads were then aligned to the
   unigenes to obtain read counts. The RPKM were calculated using RSEM. The gene expression level was then calculated for each unigene. The
   package was used to determine differentially expressed genes (DEGs) with a threshold of fold change of
   genes that were differentially expressed. A false positive rate, we used the
   adjusted to obtain the Benjamini-Hochberg method. We selected
   the DEGs with an absolute value of fold change of ≥2 were determined to be
   significantly differentially expressed genes.

**Summary of Pathway Enrichment Analysis**

1. **What tool was used for pathway enrichment analysis?**
   - KOBAS software

2. **Was a tool version number provided?**
   - Not described

3. **What gene set library was queried (eg: GO, KEGG, Reactome or other)?**
   - KEGG, GO

4. **Was a background gene list defined for pathway enrichment analysis?**
   - Not described

5. **What statistical test was used for enrichment analysis?**
   - Not described

6. **Was false discovery rate correction used to control the number of false positives in the pathway enrichment analysis?**
   - Not described