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.