## 2 Results
### Gene Annotation and Functional Classification  
After transcripts were clustered and corrected, functional annotations (NCBI non-redundant protein sequences(NR), NCBI non-redundant nucleotide sequences(NT), Gene ontology(GO), EuKaryotic Orthologous Groups(KOG), KEGG, SwissProt, Interpro) were performed using BLAST, Blast2 GO and InterProScan5, and a total of 104,062 transcripts were annotated (Figure 2A). The total number of transcripts annotated by any database was 94,025, accounting for 90.53% of all transcripts. The NR database had the highest annotation rate, accounting for 85.52% of all transcripts and the GO database had the lowest annotation rate, accounting for 34.26% of all transcripts. The total number of transcripts annotated by all seven databases was 21,781, accounting for 20.93% of all transcripts. The overall status of the annotations is shown in Table S2. To better understand the full-length transcripts that were obtained, their functions were investigated using the KEGG pathway database; a total of 104,062 genes were involved in 19 metabolic pathways. The unigenes were divided into six branches according to the KEGG metabolic pathway: organismal systems (A), metabolism (B), human diseases (C), genetic information processing (D), environmental information processing (E), and cellular processes (F). It was found that 1495 unigenes were enriched in the metabolic pathways of terpenoids and polyketides (Figure 2B). The obtained unigenes were GO annotated, and the genes that were annotated successfully were classified according to the 54 biological functional classifications under the three major GO categories: biological process, cellular component and molecular function. In the biological process category, there were relatively high numbers of genes involved in the cellular process, metabolic process, and single-organism process classifications. In the cellular component category, there were more genes involved in the cell, cell part, membrane, and binding processes classifications than in other classifications. In the molecular function category, genes were mainly classified into catalytic activity, structural molecule activity and transporter activity (Figure 2C). The above results reveal a comprehensive functional characterization of the full-length _C. porrectum_ transcriptome, and will help further study on gene functions. Figure 2: _Cont._The Identification of Relative DEGs in C. porrectum Chemotypes and Enrichment Analysis of Transcripts  
The expression profiles of the _C. porrectum_ leaf tissues from the eucalypt, linalool and camphor chemotypes underwent sequencing analysis. The flux and quality of the RNA-Seq data are shown in Table 4. There was a total of 384.31 M clean read data obtained from the three different chemotypes with three biological repetitions, and the total degree of mapping was between 73% and 82%. To fully explore the potential differential gene expression between the linalool and eucalypt chemotypes, between the camphor and linalool chemotypes, and between the camphor and eucalypt chemotypes, the clean reads were mapped to the unigene database. Gene expression data were standardized using a variety of calibration methods, and the DEGs between different chemical types were characterized by differentially expressed sequence (DESeq) with a _Q_-value \(<\) 0.05 and [log2. Fold_change] \(>\) 1 [41]. In the eucalypt chemotype and linalool chemotype comparis