To start to spot situations you to definitely manage which 1 / 2 of-life range, we compared all of our decay dataset with other transcriptome-wide datasets of various mRNA specifications (Shape dos). Our decay data clustered that have transcript abundance, metrics of codon use (stabilized translational show (nTE) and codon variation index (CAI)), including translational efficiency mentioned by ribosome footprinting (Pechmann and Frydman, 2013; Drummond et al., 2006). The good dating ranging from abundance and 1 / 2 of-life supporting the notion one mRNA levels are not just primarily dictated because of the price out-of synthesis, but one to differential mRNA stability contributes to brand new control out of transcript abundance too. , 2014).

Relationship out-of mRNA have.

(A) Spearman review relationship coefficients were determined to possess pairs from mRNA parameters regarding balance (half-life), translation efficiency (TE), polyA tail length, codon optimality (CAI), tRNA optimality (nTE), variety, UTR lengths, GC stuff and you may ORF length and you can plotted because good heatmap. Datasets had been hierarchically clustered based on Euclidian ranges. Tangerine represents self-confident relationship and bluish represents bad correlation. Correlations ranging from the same datasets is actually colored into the grey. Look for Secondary file step 1 to possess sources of genome wide studies.

Our very own correlation analyses support past really works pointing to help you mRNA interpretation results because a critical determinant off mRNA 50 % of-lifetime. The above mentioned stalled ribosome-triggered decay and you will translation basis-shelter habits you will need to explain the self-confident correlations anywhere between mRNA half of-lifetime and you will codon need and you may mRNA half-lifestyle and translation abilities correspondingly (Profile 3A). These models make clear and contrary predictions for how perturbing the new procedure of interpretation elongation otherwise initiation impacts transcript balance. The brand new stalled ribosome-brought about rust model forecasts you to mRNAs are destabilized through to slowing elongation whereas the latest interpretation grounds-shelter model forecasts the opposite due to the fact much slower elongating ribosomes manage gather with the confirmed transcript which means that bring deeper steric exception regarding decay situations. However, whenever interpretation initiation cost is actually attenuated, new stalled ribosome-triggered decay model forecasts one to transcripts do either have the same stability or maybe even enhanced balance because since the sure ribosomes over interpretation, the fresh new nude mRNA might possibly be freed from rust-creating ribosomes. Brand new interpretation factor-coverage model again predicts the opposite result: reducing the rates where translation is initiated leaves the fresh new 5′ limit even more exposed to Gay dating service new decapping machinery and you can a lot fewer piled ribosomes lets the decay circumstances greater the means to access the fresh new transcript culminating within the an overall total reduced amount of transcript stability.

mRNAs are normalized because of the reduced elongating ribosomes and you will destabilized whenever interpretation initiation are restricted.

(A) Cartoon depictions of the stalled ribosome-triggered decay and translation factor-protection models. (B) Wild-type cells (KWY165) were subjected to mRNA stability profiling immediately after addition of 0.1% DMSO or 0.2 ?g/mL cycloheximide in 0.1% DMSO. Data on ACT1, CIS3 and RPL25 mRNAs were collected and plotted. See Figure 3-figure supplement 4A for biological replicates. P-values are computed using a one-sided paired t-test for both the stalled ribosome-triggered decay model (p(SR)) as well as the translation factor-protection model (p(TP)). P-values less than 0.05 are significant. (C) Wild-type cells (KWY165) were subjected to mRNA stability profiling 33 min after addition of 0.1% ethanol or 1.5 ?g/mL sordarin in 0.1% ethanol (note that this is the timepoint when a growth defect is manifested, see Figure 3-figure supplement 1C). Data were collected, analyzed and plotted as in Figure 3B. See Figure 3-figure supplement 4B for biological replicates. (D–G) HIS3 gcn2? cells (KWY7337) were subjected to mRNA stability profiling immediately after non-addition (mock) or addition of 5 mM 3AT. Data were collected, analyzed and plotted as in Figure 3B. See Figure 3-figure supplement 4C for biological replicates. (H) mRNA samples collected from the experiment described in Figure 3D–G were subjected to global mRNA stability profiling. Cumulative frequencies of transcript half-life are plotted. (I) Wild-type cells (KWY165) were subjected to mRNA stability profiling immediately after addition of 0.1% DMSO or 10 ?M hippuristanol. Data were collected, analyzed and plotted as in Figure 3B. p-values were not computed for the stalled ribosome-triggered decay model as this model does not make a clear prediction as to how mRNA stability is affected when translation initiation is perturbed. See Figure 3-figure supplement 5A for biological replicates. (J) pGPD1-LexA-EBD-B112 CDC33-3V5-IAA7 pRS425 cells (KWY7336: control) and pGPD1-LexA-EBD-B112 CDC33-3V5-IAA7 pGPD1-OsTIR1 pRS425-p4xLexOcyc1-CDC33 ?CAP cells (KWY7334: eIF4E/G down ) were grown in CSM-LEU-0.5xURA pH5.5 media and subjected to mRNA stability profiling immediately after addition of 10 nM ?-estradiol, 100 ?M 3-indoleacetic acid and 4 ?M IP₆. Data were collected, analyzed and plotted as in Figure 3I. See Figure 3-figure supplement 5B for biological replicates. (K) Wild-type cells (KWY165) were subjected to global mRNA stability profiling immediately after addition of 0.1% DMSO (gray) or 2.6 ?M hippuristanol (orange) or 0.2 ?g/mL cycloheximide (blue). Cumulative frequencies of transcript half-life are plotted.