To obtain high-quality clean reads, raw reads obtained from the sequencing machines were further filtered by fastp (version 0.18.0). Reads were mapped to the ribosome RNA (rRNA) database by using the short reads alignment tool Bowtie2 (version 2.2.8) to eliminate the rRNA mapped reads [18 (link)]. The remaining clean reads were further used in assembly and gene abundance calculation. An index of the reference genome was built, and paired-end clean reads were mapped to the reference genome using HISAT2. 2.4. For each transcriptional region, FPKM values (fragment per kilobase of transcript per million mapped reads) were calculated using StringTie (version 1.3.1) software to quantify expression abundance and variation [20 (link)].
RNA differential expression analysis was performed by DESeq2 software between two groups [21 (link)]. The transcripts with the parameter of FDR below 0.05 and absolute fold change ≥ 2 were considered as differentially expressed transcripts. Differential expression genes (DEGs) in two groups were functionally annotated by gene ontology (GO) enrichment analysis. Physiological metabolism events and signal pathways of the DEGs were assessed using KOBAS software to test the statistical enrichments of the DEGs in KEGG pathways. The calculated P-value was gone through FDR correction, taking FDR ≤ 0.05 as a threshold. Pathways of GO and KEGG analysis meeting this condition were defined as significantly enriched pathways in DEGs. After selecting the eleven genes that were enriched in the lipid-related pathway, we conducted quantitative real-time PCR (qPCR) to validate the expression.
The raw reads of transcriptome sequences were deposited into the NCBI SRA database (project number, PRJNA859628 and accession number, SRP386837).