Global transcriptional profiling reveals common and distinct features
A. Schematic highlighting key experimental steps for mRNA-Seq and differential gene expression (DGE) analysis. NucDD and CytoDD cells were grown separately to log phase growth in the presence of Shield-1 in the media. Shield-1 was withdrawn to expose cells to unfolded DD for the indicated duration, then cells were harvested for total RNA. Each timepoint was prepared with 5 biological replicates. During cDNA library preparation, each sample received a unique index. Sequencing was performed on the NovaSeq 6000 platform. Transcripts were quantified using Salmon and differential gene expression analysis was performed using DESeq2.
B. Quantification of differentially expressed genes (DEG) at each timepoint. Only genes that exhibited fold change (FC) >1.4 increase or decrease relative to 0 min at FDR < 0.01 were counted as significant. For each timepoint, genes were classified as ‘common’ genes (meets criteria in both NucDD and CytoDD) or ‘distinct’ genes (meets criteria in only 1 cell line).
C. Principal component analysis (PCA) of all timepoints and replicates based on the top 10% most variable genes (approximately 1000 genes). Left, NucDD and CytoDD samples plotted on the same space. Center, only NucDD samples. Right, only CytoDD samples. Center and right, connecting arrows added to highlight time course progression.
D. Hierarchical clustering of ‘common’ set DEGs that exhibited similar changes in response to NucDD (left) and CytoDD (right). Each row is a unique gene and gene expression is represented by a normalized row Z score relative to the 0-minute timepoint for each cell line. The dendrogram branches show the relationships of the top-level clusters.
E. Hierarchical clustering of ‘distinct’ set DEGs that were differentially changed by NucDD and CytoDD, as in panel C.