Supplementary Figure 11: Global and transcript-specific mRNA stability in mESCs.
From: Thiol-linked alkylation of RNA to assess expression dynamics
(a) Experimental setup for profiling mRNA stability by SLAMseq. mESCs were subjected to metabolic labeling with s4U (100 μM final conc.) in 3h intervals for a total of 24 h, followed by a chase with unlabeled uridine (10 mM final conc.) for 0, 0.5, 1, 3, 6, 12, and 24 h, followed by total RNA preparation and SLAMseq. (b) Representative genome browser plots of the indicated genes represent SLAMseq data prepared from mESCs subjected to s4U-pulse/chase labeling as shown in (a). Sequencing data mapping to defined counting windows in libraries prepared from the indicated timepoint of the chase are shown. All mapped reads (steady-state, in RPM) are shown in black; T>C conversion-containing reads (labeled, in RPM) are indicated in red. (c) Global analysis of mRNA stability in mESCs. Correlation of steady-state gene expression (all reads) or T>C conversion containing reads at the indicated time with steady-state expression at time 0 of the chase. (d) Relationship between transcript-specific mRNA half-life and its physiological function. Genes associated with the GO terms “Regulation of Transcription” (GO:0006357), “Cell cycle” (GO:0007049), “Translation” (GO:0006412) and “Extracellular Matrix” (GO:0031012) was tested for enrichment among transcripts ranked according to stability determined by SLAMseq by GSEA (Subramanian et al., 2005). Normalized enrichment score (NES) and associated p-Value is shown. (e) Messenger RNA half-life measured by SLAMseq correlates with mRNA stabilities determined by transcriptional inhibition. mESCs were treated with Actinomycin D (ActD) to inhibit transcription, followed by Quant-seq analysis of gene expression. Half-life was determined from global transcription inhibition data by normalizing gene expression to the 50 most stable transcripts. Half-lives for 6665 transcripts are shown. Spearman correlation coefficient (rS) and associated p-Value are indicated.
Subramanian, A. et al. Gene set enrichment analysis: a knowledge-based approach for interpreting genome-wide expression profiles. Proc Natl Acad Sci USA 102, 15545–15550 (2005).
