2.9 Gene expression and weighted gene co-expression network analysis

A total of 21 transcriptomes from seven tissues (three biological replicates for each tissue) were used to obtain the gene expression and to perform the weighted gene co-expression network analysis (WGCNA). For each sample, RNA-seq short reads were filtered using fastp (Chen, Zhou, Chen, & Gu, 2018) with default parameters, and mapped to the S. tetraptera genome by HISAT2 (D. Kim et al., 2015). The transcripts per million (TPM) values for each gene were then extracted to measure their expression level by StringTie (Pertea et al., 2015). Differentially expressed genes (DEGs) between different tissues were identified by DESeq2 (R package) (Love, Huber, & Anders, 2014). The candidate genes with at least two-fold differential expression levels in various tissues and an FDR cut-off value of 0.05 were identified as DEGs. The weighted gene co-expression network analysis was then performed by WCGNA (R package) (Langfelder & Horvath, 2008). The generated network was visualized using Cytoscape (Smoot, Ono, Ruscheinski, Wang, & Ideker, 2011) v3.7.2.