RNA-seq analysis of rrp4-G226D cells reveal distinct transcriptomic changes compared to RRP4 cells. (A) Principal component analysis (PCA) of RNA-seq data collected from triplicate RRP4 and rrp4-G226D cell samples shows that the gene expression patterns from independent rrp4-G226D samples are similar and thus cluster together, but are distinct from RRP4 samples, which also cluster together. (B) A volcano plot of the differentially expressed transcripts in rrp4-G226D cells compared to RRP4 cells shows that 860 transcripts are significantly Up and 802 transcripts are Down by 1.5-fold or more in rrp4-G226D cells. Statistically significant fold changes in transcript levels (Down or Up) in rrp4-G226D cells relative to RRP4 cells are color coded (1.5–2 FC [blue]; 2–4 FC [orange]; ≥4 FC [purple]; P-value adjusted ≤0.05). Transcripts that were subsequently validated by RT-qPCR are labeled. (C) Pie charts of the percentages of different RNA classes within the 860 Up and 802 Down transcripts in rrp4-G226D cells reveal that increased transcripts are predominantly ncRNAs (CUTs; SUTs) and decreased transcripts are predominantly mRNAs. The RNA classes identified include messenger RNA (mRNA), small nuclear RNA (snRNA), small nucleolar RNA (snoRNA), transfer RNA (tRNA), cryptic unstable transcripts (CUTs; small, noncoding RNA), stable unannotated transcripts (SUTs; small, noncoding RNA), and other noncoding RNA (ncRNA; e.g., TLC1), (D) Gene ontology (GO) analysis for biological process in the Up and Down transcripts in rrp4-G226D cells reveals that ncRNA processing is significantly represented in the Up transcripts and translation is significantly represented in the Down transcripts. GO analysis was performed on coding (mRNA) and noncoding RNA (tRNAs, snoRNAs, and snRNAs) classes using the YeastEnrichr web server (Chen et al. 2013; Kuleshov et al. 2016, 2019). Gray bars represent the statistical significance of the biological process categories computed using combined score listed (log of the P-value from the Fisher exact test multiplied by the z-score of the deviation from the expected rank).
