Library formation (polyA+, stranded) and sequencing were all performed according to Illumina’s specifications at the OHSU Massively Parallel Sequencing Shared Resource. Libraries were multiplexed six per lane, yielding approximately 25–30 million totals read per sample. FastQC was used for quality checks on the raw sequence data. Sequence data were then aligned using STAR [Spliced Transcripts Alignment to a Reference (Dobin et al., 2013)] allowing for a maximum of three mismatches per 100 bp read. For all samples >85% of the reads uniquely aligned. Using the featureCounts suite (Liao et al., 2014), reads were aligned to known genomic features to generate counts at the gene level. Gene expression data were imported into the R application environment; upper-quartile normalization was performed using the edgeR Bioconductor package (Robinson et al., 2010). The gene read density threshold for inclusion in the network analyses was an average of >1 count per million (CPM). Network connectivity for coexpression was calculated as described elsewhere (Colville et al., 2017). The expression data have been deposited to NCBI’s Gene Expression Omnibus1.
