HAC was the Milton E. Cassel scholar of the Rita Allen Foundation (http://www.ritaallenfoundation.org). This work was funded by grants to HAC from the National Institute of General Medical Sciences Center of Excellence grant P50 GM071508 (P.I. David Botstein), PhRMA Foundation grant 2007RSGl9572, National Science Foundation Grant OCI-1047879 to David August, National Institute of General Medical Sciences R01 GM081686, National Institute of General Medical Sciences R01 GM0866465, the Eli &#38; Edythe Broad Center of Regenerative Medicine &#38; Stem Cell Research, the Iris Cantor Women&#8217;s Health Center/UCLA CTSI NIH Grant UL1TR000124, and the Leukemia Lymphoma Society. Research reported in this publication was supported by the National Cancer Institute of the National Institutes of Health under Award Number P50CA092131. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript. HAC is a member of the Eli &#38; Edythe Broad Center of Regenerative Medicine &#38; Stem Cell Research, the UCLA Molecular Biology Institute, and the UCLA Bioinformatics Interdepartmental Program.

All experiments described were approved by Institutional Review Boards at Princeton University and the University of California, Los Angeles.
1. Prepare Proliferating and Contact-inhibited Fibroblasts for ActD Time Course
NOTE: This protocol uses a timecourse with four timepoints. Three biologically independent samples can be collected per timepoint by collecting different tissue culture plates in one experiment, or the experiment can be repeated multiple times with different cultures of cells. In our experience, one 10 cm (diameter) tissue culture dish (one plate) provides sufficient RNA for analysis. If needed, multiple tissue culture dishes can be pooled for each sample to increase the number of cells at each timepoint. In addition, the same experiment can be performed with fibroblasts isolated from different individuals as truly independent biological replicates.
<ol>
	<li>Establish proliferating and quiescent cultures of cells for the transcript decay analysis. For proliferating cells, split the cells every three days while the contact-inhibited cells are becoming contact-inhibited.
	<ol>
		<li>For the contact-inhibited cells, change the medium every 2 days for 7 days. Split the proliferating cells 2 days before the contact-inhibited fibroblasts are ready for collection. An example of a cell culture scheme is shown in Figure 1. The remaining steps in this section provide a detailed protocol for establishing and splitting the cells.</li>
	</ol>
	</li>
	<li>Isolate primary dermal fibroblasts from neonatal skin according to established protocols13. Passage fibroblasts to ensure a homogeneous population. 
	NOTE: Fibroblasts can be frozen and thawed, if needed.</li>
	<li>Thaw or replate fibroblasts, if needed. Grow fibroblasts in DMEM with 10% serum under sterile conditions in a tissue culture incubator at 37 &#176;C and 5% CO2. Use fibroblasts that have been grown for fewer than 10 passages. Fibroblasts should be &#60;80% confluent on the day of splitting cells to make proliferating and quiescent populations.</li>
	<li>To split a tissue culture plate into multiple plates, prewarm PBS, trypsin, and medium with serum in a 37 &#176;C water bath for 20 min.</li>
	<li>Aspirate or use a pipet to remove the medium from each tissue culture plate with cells to be replated.</li>
	<li>Pipet warm PBS onto each plate (10 mL of solution for a 150 mm plate, 5 mL of solution for a 100 mm plate, 2 mL for a well of a 6 well plate, and 1 mL for a well of a 12 well plate).</li>
	<li>Aspirate or pipet to remove PBS from each tissue culture plate.</li>
	<li>Gently pipet 1x Trypsin-EDTA onto each plate (8 mL of solution for a 150 mm plate, 3 mL of solution for a 100 mm plate, 2 mL for a well of a 6 well plate, and 1 mL for a well of a 12 well plate). 
	NOTE: Make 1x Trypsin-EDTA by diluting sterile 10x Trypsin-EDTA in sterile PBS. The final 1x solution should be 0.05% trypsin and 0.02% EDTA.</li>
	<li>Incubate trypsin with cells for 5 min.</li>
	<li>Gently tap the plate to dislodge cells from the plate.</li>
	<li>Pipet to resuspend cells into a single cell suspension.</li>
	<li>Transfer cells in trypsin solution to a conical tube containing the same volume of DMEM with 10% serum (8 mL of solution for a 150 mm plate, 3 mL of solution for a 100 mm plate, 2 mL for a well of a 6 well plate, and 1 mL for a well of a 12 well plate).</li>
	<li>Spin down cells at 4 &#176;C for 5 minutes at 1,000 x g to remove trypsin.</li>
	<li>Resuspend cells in an appropriate volume of medium and count with a hemacytometer to determine cell concentration.</li>
	<li>Seed 5 x 105 cells per 100 mm tissue culture plate for proliferating and contact-inhibited cells.</li>
	<li>Using this method, establish the proliferating and contact-inhibited samples required for analysis (Figure 1).</li>
</ol>
2. ActD Time Course
<ol>
	<li>Resuspend ActD at a stock concentration of 1 mg/mL (For 1 mg of ActD, use 950 &#181;L of sterile PBS and 50 &#181;L of sterile DMSO). 
	NOTE: Frozen stock solutions of ActD should be stable for a month at -20 &#176;C. Dilute solutions should be discarded and not stored for further use.</li>
	<li>Add ActD to the appropriate volume of prewarmed medium for all biological replicate cell culture plates that were set up for the 0, 120, 240, and 480 min timepoints (Figure 2). Add ActD at a concentration of 15 &#181;g per mL of medium. Mix well, aspirate off the old medium, and add ActD-containing medium to the cells.
	<ol>
		<li>For a 1 mg/mL stock, add 15 &#181;L ActD for each mL of medium, e.g., for 10 mL of medium for a 100 mm plate, add 150 &#181;L ActD.</li>
	</ol>
	</li>
	<li>To collect the zero timepoint sample, gently aspirate off the ActD medium, and pipet prewarmed PBS onto the cells. Pipet 10 mL of solution for a 150 mm plate, 5 mL of solution for a 100 mm plate, 2 mL for a well of a 6 well plate, and 1 mL for a well of a 12 well plate.</li>
	<li>Gently aspirate or pipet off the PBS. 
	NOTE: All steps involving RNA isolation should be performed with RNase-free water, RNase-free microcentrifuge tubes, and RNase-free pipettes. Gloves should be worn and changed frequently when working with RNA.</li>
	<li>Add phenol-guanidine isothiocyanate solution (1 mL/10-cm plate with 4 x 105 to 4 x 107 cells) directly to the tissue culture plate. 
	NOTE: Phenol-guanidine isothiocyanate solution is a monophasic solution that maintains RNA quality while lysing cells and separating RNA, DNA, and protein from each other. 
	CAUTION: Phenol and guanidine isothiocyanate are corrosive. Use appropriate protection.</li>
	<li>Pipet the phenol-guanidine isothiocyanate solution-cell mixture up and down several times to make a homogeneous mixture. 
	NOTE: Phenol-guanidine isothiocyanate solution lysate can be stored at 4 &#176;C overnight or at -20 &#176;C for up to a year.</li>
	<li>Collect each time point after the appropriate amount of time has passed using the method described in steps 2.3-2.6.</li>
</ol>
3. Isolation of Total RNA from Phenol-guanidine Isothiocyanate Solution Lysate
<ol>
	<li>Incubate samples at room temperature for 5 min to ensure the complete dissolution of RNA-protein complexes. 
	NOTE: The steps of the phenol-guanidine isothiocyanate solution protocol can be performed at room temperature unless otherwise noted.</li>
	<li>Introduce spike-in control transcripts that can be detected with the methodology used. Introduce these controls into each sample at a known quantity and concentration. 
	NOTE: The external RNA control consortium (ERCC) spike-in control mix14 has been specifically designed as a spike-in control for RNA-Seq. It can also be used for Northern blots or real-time qPCR. Spike-in controls specifically designed for microarray technologies are also available (see Table of Materials).</li>
	<li>Transfer the phenol-guanidine isothiocyanate solution mixture to a 2.0 mL microcentrifuge tube with a pipette. Add 0.2 mL chloroform to the Phenol-guanidine isothiocyanate solution mixture for every 1 mL of phenol-guanidine isothiocyanate solution used (e.g., add 0.3 mL chloroform to 1.5 mL phenol-guanidine isothiocyanate solution mixture).</li>
	<li>Shake the microcentrifuge tube vigorously for 15 s and then incubate chloroform-phenol-guanidine isothiocyanate mixture at room temperature for 3 min.</li>
	<li>Spin samples at 12,000 x g for 20 minutes at 4 &#176;C. 
	NOTE: After the initial spin, the sample should separate into 3 layers - a red organic layer at the bottom, a white/pink interphase in the middle, and a clear aqueous layer on the top (Figure 3).</li>
	<li>Transfer the aqueous layer to a new 2.0 mL microcentrifuge tube using a micropipette. 
	NOTE: Be careful not to disturb the interphase during this process. It is okay to leave some of the aqueous fraction. It is better to leave some of the aqueous fraction than to also include some of the interphase layers, as including the interphase layer would contaminate the RNA with DNA. The aqueous layer will be approximately half of the initial volume, so about 0.9 mL if the phenol-guanidine isothiocyanate solution/chloroform mixture was 1.8 mL.</li>
	<li>Discard the interphase and organic fractions.</li>
	<li>Add an equal volume of 2-propanol to the aqueous fraction and invert the tube 10 times. Add up to 1 &#181;L of 20 mg/mL aqueous solution of glycogen per 20 &#181;L of sample, especially if the yield is expected to be low because fewer than 106 cells were collected. 
	NOTE: This will result in a dense, solid pellet that is easy to monitor after the spin steps that follow.</li>
	<li>Incubate samples at room temperature for 10 min.</li>
	<li>Spin samples at 12,000 x g for 20 minutes at 4 &#176;C. Ensure that, at the end of this spin, the RNA has precipitated to form a white pellet at the bottom of the tube.</li>
	<li>With a pipette, remove and discard the supernatant taking special care not to disturb the white RNA pellet. 
	NOTE: A loose pipet tip held in hand can be used to remove excess ethanol. If the RNA pellet is disturbed, but not discarded, the investigator can repeat the spin and remove the supernatant again. Avoid discarding the pellet as this will require the investigator to repeat the entire procedure.</li>
	<li>Prepare a solution of 75% ethanol and 25% nuclease-free water. Add 1 mL of 75% ethanol per 1 mL of phenol-guanidine isothiocyanate solution reagent to wash the pellet.</li>
	<li>Spin samples at 12,000 x g for 10 min at 4 &#176;C.</li>
	<li>After removing most of the supernatant, use a pipet to remove as much ethanol as possible, while still taking care not to disturb the pellet. 
	NOTE: The RNA pellet is less compact at this step and tends to move. Be extra careful when handling the pellet at this point to avoid losing the RNA.</li>
	<li>Spin samples 12,000 x g for 2 min at room temperature to pellet all excess ethanol.</li>
	<li>Remove all excess ethanol from the tube using a micropipette taking care to not disturb the pellet.</li>
	<li>Let the RNA pellet air dry for 5 min.</li>
	<li>Add 50 &#181;L of nuclease-free water to the RNA pellet and resuspend the pellet in the nuclease-free water.</li>
	<li>Treat samples with 1 &#181;L DNase (2 units/&#181;L) to remove DNA and then inactivate DNase and cations (see Table of Materials).</li>
	<li>Store RNA samples in 2.0 mL microcentrifuge tubes at -80 &#176;C.</li>
</ol>
4. Analysis of Transcript Abundance
<ol>
	<li>Quantify RNA and check RNA for purity using a spectrophotometer. 
	NOTE: The ratio of absorbance at 260 nm to 280 nm should be approximately 2.0 for RNA.</li>
	<li>Analyze RNA with a 1% agarose gel or an equivalent technology to visualize the extent of degradation. 
	NOTE: Two clear bands representing 18S and 28S rRNA should be clearly visible (Figure 4). If these bands are not visible, the RNA may be degraded. Trouble shooting tips for RNA degradation are provided in the Discussion.</li>
	<li>Monitor transcript abundance in the collected aliquots of RNA compared with the spiked-in internal standard using microarrays15, RNA-Seq16, real-time qPCR17, or Northern blots18.
	<ol>
		<li>Determine the abundance for each transcript at each time point compared with a spiked-in control of known abundance. 
		NOTE: For microarrays, the values will be fluorescence intensities. For Northern blots, bands on the X-ray film can be quantified. For real-time qPCR, transcript abundance can be determined by comparison with known standards with the 2-&#963;&#963;CT method19. For RNA-Seq, normalized values can be determined as FPKM or fragments per kilobase of exon per million reads mapped. For isoform-specific decay rates, RNA-Seq data can be analyzed using isoform-aware methodologies such as DEXSeq20. Isoform-specific decay rates are best determined with RNA-Seq. If they are to be determined with microarray data, then the data must be analyzed on a probe-by-probe basis rather than a gene-by-gene basis. The analyst must be careful when interpreting information from a limited number of probes. For instance, there may be 5 or fewer probes that are informative about a particular isoform. In this case, the analyst will need to determine whether the behavior of these probes is sufficiently consistent so that the results are reliable.</li>
	</ol>
	</li>
	<li>Perform real-time qPCR on the isolated RNA17 in the collected samples to analyze rapidly decaying genes, like c-Myc and a slowly decaying gene like GAPDH, to gain confidence that transcript decay rates were accurately detected. 
	NOTE: For further confirmation, isoform-specific real-time qPCR probes can be developed and used to monitor the abundance of specific isoforms over time21.</li>
</ol>
5. Decay Rate Constant Determination
<ol>
	<li>For each timepoint, log-transform the abundance values for each transcript (gene-specific or isoform-specific). 
	NOTE: Log-transforming the values will convert exponential decay curves to lines that can be fit with a linear decay model22.</li>
	<li>Fit the expression profile for each transcript (gene-specific or isoform-specific) to a linear decay model. The formula for such a model is f(t) = C - r*t. In this equation, C is a constant that represents the starting amount of a transcript, r is the rate of decline, and t is the time since the beginning of the experiment. From this equation, determine the decay rate as r*ln(10) (see reference11). 
	NOTE: The maSigPro software package is a regression-based approach designed to detect significant gene expression profile differences in time course data23. Sample code and results for maSigPro are available at: https://www.bioconductor.org/packages/release/bioc/vignettes/maSigPro/inst/doc/maSigProUsersGuide.pdf.</li>
	<li>Filter out genes that fail to fit a log-linear decay model. This can be accomplished with an ANOVA F-test. 
	NOTE:The F test is based on the F-statistic, which is defined as the variation between sample means divided by the variation within samples. Correct the p-values for multiple comparisons by applying the linear step-up Benjamini and Hochberg false discovery procedure24. A q-value greater than 0.05 with the F-test can be used as a cutoff for genes that fail to fit a log-linear decay model.</li>
	<li>Perform an ANOVA F-test to determine transcripts with a significant interaction term between a categorical cell cycle condition and time (false discovery rate, FDR &#60;0.05).</li>
</ol>

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<li>Chen, C. Y., Ezzeddine, N., Shyu, A. B. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Messenger+RNA+half-life+measurements+in+mammalian+cells%5BTitle%5D)+AND+%22Methods+Enzymol%22%5BJournal%5D)">Messenger RNA half-life measurements in mammalian cells.</a> Methods Enzymol. 448, 335-357 (2008).</li>
<li>Gupta, I., Clauder-Munster, S., Klaus, B., Jarvelin, A. I., Aiyar, R. S., Benes, V., Wilkening, S., Huber, W., Pelechano, V., Steinmetz, L. M. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Alternative+polyadenylation+diversifies+post-transcriptional+regulation+by+selective+RNA-protein+interactions%5BTitle%5D)+AND+%22Mol+Syst+Biol%22%5BJournal%5D)">Alternative polyadenylation diversifies post-transcriptional regulation by selective RNA-protein interactions.</a> Mol Syst Biol. 10, 719(2014).</li>
<li>Geisberg, J. V., Moqtaderi, Z., Fan, X., Ozsolak, F., Struhl, K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Global+analysis+of+mRNA+isoform+half-lives+reveals+stabilizing+and+destabilizing+elements+in+yeast%5BTitle%5D)+AND+%22Cell%22%5BJournal%5D)">Global analysis of mRNA isoform half-lives reveals stabilizing and destabilizing elements in yeast.</a> Cell. 156 (4), 812-824 (2014).</li>
<li>Haruki, H., Nishikawa, J., Laemmli, U. K. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((The+anchor-away+technique%3A+rapid%2C+conditional+establishment+of+yeast+mutant+phenotypes%5BTitle%5D)+AND+%22Mol+Cell%22%5BJournal%5D)">The anchor-away technique: rapid, conditional establishment of yeast mutant phenotypes.</a> Mol Cell. 31 (6), 925-932 (2008).</li>
<li>Cleary, M. D., Meiering, C. D., Jan, E., Guymon, R., Boothroyd, J. C. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Biosynthetic+labeling+of+RNA+with+uracil+phosphoribosyltransferase+allows+cell-specific+microarray+analysis+of+mRNA+synthesis+and+decay%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">Biosynthetic labeling of RNA with uracil phosphoribosyltransferase allows cell-specific microarray analysis of mRNA synthesis and decay.</a> Nat Biotechnol. 23 (2), 232-237 (2005).</li>
<li>Rabani, M., Levin, J. Z., Fan, L., Adiconis, X., Raychowdhury, R., Garber, M., Gnirke, A., Nusbaum, C., Hacohen, N., Friedman, N., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Metabolic+labeling+of+RNA+uncovers+principles+of+RNA+production+and+degradation+dynamics+in+mammalian+cells%5BTitle%5D)+AND+%22Nat+Biotechnol%22%5BJournal%5D)">Metabolic labeling of RNA uncovers principles of RNA production and degradation dynamics in mammalian cells.</a> Nat Biotechnol. 29 (5), 436-442 (2011).</li>
<li>Marzi, M. J., Ghini, F., Cerruti, B., de Pretis, S., Bonetti, P., Giacomelli, C., Gorski, M. M., Kress, T., Pelizzola, M., Muller, H., et al. <a target="_blank" href="http://www.ncbi.nlm.nih.gov/pubmed?term=((Degradation+dynamics+of+microRNAs+revealed+by+a+novel+pulse-chase+approach%5BTitle%5D)+AND+%22Genome+Res%22%5BJournal%5D)">Degradation dynamics of microRNAs revealed by a novel pulse-chase approach.</a> Genome Res. 26 (4), 554-565 (2016).</li>
</ol>

The authors have no competing interests to disclose.

Quiescence can be induced by external signals including withdrawal of mitogens or serum, lack of cell adhesion, and contact inhibition. Contact inhibition, one of multiple possible methods for inducing quiescence, is a highly evolutionarily conserved process in which cells exit the proliferative cell cycle in response to cell-to-cell contact. We focus here on contact inhibition as an example of a method to induce quiescence. Previous studies have reported that cell-cell contact can affect microRNA biogenesis<sup class="x...

Steady state levels of transcripts reflect the contribution of both transcript synthesis and transcript decay. Regulated and coordinated transcript decay is an important mechanism for controlling biological processes1,2,3,4. For example, transcript decay rates have been shown to contribute to the temporal series of events following activation by the inflammatory cytokine tumor necrosis factor5.
We have previously shown that the transition between proliferation and quiescence in primary human fibroblasts is associated with changes in the transcript levels of many genes6. Some of these changes reflect differences in the activity of transcription factors between these two states.
Changes in a transcript&#39;s decay rate can also contribute to changes in the expression level of a transcript in two different states7,8. Based on our earlier findings that the transition between proliferation and quiescence is associated with changes in the levels of multiple microRNAs9, we asked whether there is also a contribution from differential transcript decay in the changes in gene expression in proliferating versus quiescent fibroblasts.
In order to monitor transcript stability, we determined the rate of decay of transcripts genome-wide in proliferating versus quiescent cells. To achieve this, we monitored decay rates in proliferating versus quiescent fibroblasts by introducing an inhibitor of new transcription and monitoring the rate at which individual transcripts disappeared over time. The advantage of this approach is that, as compared to methods that simply monitor overall gene expression, by inhibiting new transcript synthesis, we will be able to determine the decay rate for these transcripts separately from the rate at which they are transcribed.
ActD treatment to inhibit new transcription and determine transcript decay rates has been successfully applied in multiple previous studies. ActD has been used to dissect the importance of RNA stability in the changes in transcript abundance that result from treatment with pro-inflammatory cytokines5. A similar approach has also been used to dissect the differences in transcript decay rate in proliferating versus differentiated C2C12 cells as they adopt a differentiated muscle phenotype10. As another example, global mRNA half-lives have also been detected in pluripotent and differentiated mouse embryonic stem cells11. In these examples, mRNA decay has been shown to be important for regulating transcript abundance and for the transition of cells to different cell states.
Applying the methods described below, we discovered changes in transcript decay rates in approximately 500 genes when comparing fibroblasts in proliferating and quiescent states12. In particular, we discovered that the targets of the microRNA miR-29, which is downregulated in quiescent cells, are stabilized when cells transition to quiescence. We describe here the methodology we used to determine decay rates in proliferating and quiescent cells. This methodology is useful for comparing global mRNA decay rates in two distinct but similar conditions when information about rapidly decaying genes is sought. It could also be used to address other questions such as the effect of cell culture conditions on transcript decay, for instance, in two dimensional versus three dimensional cultures. Decay rates can be determined genome-wide with methods such as microarrays or RNA-Seq. Alternatively, real-time qPCR or Northern blotting can be used to determine decay rates on a gene-by-gene or isoform-by-isoform basis. These rates can then be used to calculate the half-life of each monitored gene and to identify genes with decay rates that are different in two conditions.

<table><tbody><tr><td>Centrifuges for microcentrifuge tubes capable of reaching 12,000 x g and 4&amp;deg;C</td><td></td><td></td><td></td></tr><tr><td>Equipment for running agarose gels</td><td></td><td></td><td></td></tr><tr><td>Sterile tissue culture plates and conical tubes</td><td></td><td></td><td></td></tr><tr><td>Dulbecco&#039;s Modified Eagle Medium</td><td>Life Technologies</td><td>11965-118</td><td></td></tr><tr><td>Fetal bovine serum</td><td>VWR</td><td>35-010-CV</td><td></td></tr><tr><td>Sterile serological pipets, pipettors and pipet tips for tissue culture</td><td></td><td></td><td></td></tr><tr><td>Individually wrapped, disposable Rnase-free pipettes, pipette tips and tubes for RNA isolation and analysis</td><td></td><td></td><td></td></tr><tr><td>Disposable gloves to be worn when handling reagents and RNA samples</td><td></td><td></td><td></td></tr><tr><td>RNaseZap</td><td>Invitrogen</td><td>AM9780</td><td>For decontaminating work surfaces from RNase</td></tr><tr><td>2.0 ml eppendorf tubes</td><td></td><td></td><td></td></tr><tr><td>Trypsin-EDTA&amp;nbsp; Solution 10X</td><td>Millipore Sigma</td><td>9002-07-07</td><td></td></tr><tr><td>Sterile PBS</td><td>Life Technologies</td><td>14190-250</td><td></td></tr><tr><td>Trizol</td><td>Thermo Fisher Scientific</td><td>15596018</td><td></td></tr><tr><td>Actinomycin D</td><td>Millipore Sigma</td><td>A1410-2 mg</td><td>inhibits transcription</td></tr><tr><td>Sterile DMSO</td><td>Fisher Scientific</td><td>31-761-00ML</td><td>solvent for actinomycin D</td></tr><tr><td>Chloroform</td><td>Thermo Fisher Scientific</td><td>ICN19400225</td><td>MP Biomedicals, Inc product</td></tr><tr><td>Isopropanol</td><td>Fisher Scientific</td><td>BP2618500</td><td>molecular biology grade</td></tr><tr><td>Ethanol</td><td>Fisher Scientific</td><td>BP28184</td><td>molecular biology grade</td></tr><tr><td>RNase-free Glycogen (20 mg/ml aqueous solution)</td><td>Thermo Fisher Scientific</td><td>R0551</td><td>carrier for RNA precipitation</td></tr><tr><td>TURBO DNA-free Kit</td><td>Thermo Fisher Scientific</td><td>AM1907</td><td>removes DNA with DNase, then, in a subsequent step,&amp;nbsp; inactivates DNA and removes divalent cations</td></tr><tr><td>Agarose</td><td>Thermo Fisher Scientific</td><td>ICN820721</td><td>MP Biomedicals, Inc product</td></tr><tr><td>Loading dye for RNA gel</td><td>Thermo Fisher Scientific</td><td>R0641</td><td>suitable even for denaturing electrophoresis</td></tr><tr><td>Millenium RNA markers</td><td>Thermo Fisher Scientific</td><td>AM7150</td><td>RNA ladder</td></tr><tr><td>One-color RNA Spike-in Kit</td><td>Agilent Technology</td><td>5188-5282</td><td>Example spike-in control for Agient microarray analysis</td></tr><tr><td>Tris base</td><td>Fisher Scientific</td><td>BP152-1</td><td>molecular biology grade, for TAE buffer</td></tr><tr><td>Glacial acetic acid</td><td>Fisher Scientific</td><td>A38-500</td><td>for TAE buffer</td></tr><tr><td>EDTA</td><td>Fisher Scientific</td><td>BP120-500</td><td>electrophoresis grade, for gels</td></tr><tr><td>Ethidium bromide</td><td>Millipore Sigma</td><td>E7637</td><td>for molecular biology</td></tr><tr><td>External RNA Controls Consortium RNA Spike-in Mix</td><td>Thermo Fisher Scientific</td><td>4456740</td><td>Spike-in control for RNA Seq</td></tr><tr><td>TruSeq Stranded mRNA Library Preparation Kit A (48 samples, 12 indexes)</td><td>Illumina</td><td>RS-122-2101</td><td>for RNA Seq</td></tr><tr><td>96-well 0.3 ml PCR plate</td><td>Thermo Fisher Scientific</td><td>AB-0600</td><td>for real-time qPCR</td></tr><tr><td>Microseal B adhesive seals</td><td>Bio-Rad</td><td>MSB1001</td><td>for real-time qPCR</td></tr><tr><td>Rnase/Dnase-free Reagent Reservoirs</td><td>VWR</td><td>89094-662</td><td>for real-time qPCR</td></tr><tr><td>Rnase/Dnase-free Eight tube strips and caps</td><td>Thermo Fisher Scientific</td><td>AM12230</td><td>for real-time qPCR</td></tr><tr><td>SuperScript Reverse Transcriptase</td><td>Invitrogen</td><td>18090010</td><td>for real-time qPCR</td></tr><tr><td>AMPure XP Beads</td><td>Beckman Coulter</td><td>A63880</td><td>for real-time qPCR</td></tr></tbody></table>

determining genome-wide transcript decay rates in proliferating and quiescent human fibroblasts

Quiescence is a temporary, reversible state in which cells have ceased cell division, but retain the capacity to proliferate. Multiple studies, including ours, have demonstrated that quiescence is associated with widespread changes in gene expression. Some of these changes occur through changes in the level or activity of proliferation-associated transcription factors, such as E2F and MYC. We have demonstrated that mRNA decay can also contribute to changes in gene expression between proliferating and quiescent cells. In this protocol, we describe the procedure for establishing proliferating and quiescent cultures of human dermal foreskin fibroblasts. We then describe the procedures for inhibiting new transcription in proliferating and quiescent cells with Actinomycin D (ActD). ActD treatment represents a straightforward and reproducible approach to dissociating new transcription from transcript decay. A disadvantage of ActD treatment is that the time course must be limited to a short time frame because ActD affects cell viability. Transcript levels are monitored over time to determine transcript decay rates. This procedure allows for the identification of genes and isoforms that exhibit differential decay in proliferating versus quiescent fibroblasts.

We have previously reported the results of microarray analyses of transcript decay rates in proliferating and contact-inhibited primary human fibroblasts over an 8-hour time course12. A list of genes with a significant change in transcript stability comparing proliferating and contact-inhibited fibroblasts is provided in Supplementary Table 1. The fluorescence intensities at time zero and over a time course after ActD treatment are provided. Genes ...

Watch this Scientific Journal Video about Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts at JoVE.com

Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts

We describe a protocol for generating proliferating and quiescent primary human dermal fibroblasts, monitoring transcript decay rates, and identifying differentially decaying genes.

Quiescence is a temporary, reversible state in which cells have ceased cell division, but retain the capacity to proliferate. Multiple studies, including ...

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Research

JoVE Journal

Genetics

6.2K Views.  University of California, Los Angeles. We beschrijven een protocol voor genereren prolifererende en zwakke primaire menselijke dermale fibroblasten, monitoring transcript verval tarieven en differentieel rottend genen te identificeren.

Video: Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts

Real-time Analysis of Transcription Factor Binding, Transcription, Translation, and Turnover to Display Global Events During Cellular Activation

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.
Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.
The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

This protocol describes the combinatorial use of ChIP-seq, 4sU-seq, total RNA-seq, and ribosome profiling for cell lines and primary cells. It enables tracking changes in transcription-factor binding, de novo transcription, RNA processing, turnover and translation over time, and displaying the overall course of events in activated and/or rapidly changing cells.

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for ...

Investigation of RNA Synthesis Using 5-Bromouridine Labelling and Immunoprecipitation

When steady state RNA levels are compared between two conditions, it is not possible to distinguish whether changes are caused by alterations in production or degradation of RNA. This protocol describes a method for measurement of RNA production, using 5-Bromouridine labelling of RNA followed by immunoprecipitation, which enables investigation of RNA synthesized within a short timeframe (e.g., 1 h). The advantage of 5-Bromouridine-labelling and immunoprecipitation over the use of toxic transcriptional inhibitors, such as &#945;-amanitin and actinomycin D, is that there are no or very low effects on cell viability during short-term use. However, because 5-Bromouridine-immunoprecipitation only captures RNA produced within the short labelling time, slowly produced as well as rapidly degraded RNA can be difficult to measure by this method. The 5-Bromouridine-labelled RNA captured by 5-Bromouridine-immunoprecipitation can be analyzed by reverse transcription, quantitative polymerase chain reaction, and next generation sequencing. All types of RNA can be investigated, and the method is not limited to measuring mRNA as is presented in this example.

This method can be used to measure RNA synthesis. 5-Bromouridine is added to cells and incorporated into synthesized RNA. RNA synthesis is measured by RNA extraction immediately after labelling, followed by 5-Bromouridine-targeted immunoprecipitation of labelled RNA and analysis by reverse transcription and quantitative polymerase chain reaction.

When steady state RNA levels are compared between two conditions, it is not possible to distinguish whether changes are caused by alterations in ...

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in mRNA synthesis has been shown to be compensated by a simultaneous decrease in mRNA degradation to restore normal steady-state levels. Hence, the genome-wide quantification of mRNA synthesis, independently from mRNA decay, is the best direct reflection of RNA polymerase II transcriptional activity. Here, we discuss a method using non-perturbing metabolic labeling of nascent RNAs in Saccharomyces cerevisiae (S. cerevisiae). Specifically, the cells are cultured for 6 min with a uracil analog, 4-thiouracil, and the labeled newly transcribed RNAs are purified and quantified to determine the synthesis rates of all individual mRNA. Moreover, using labeled Schizosaccharomyces pombe cells as internal standard allows comparing mRNA synthesis in different S. cerevisiae strains. Using this protocol and fitting the data with a dynamic kinetic model, the corresponding mRNA decay rates can be determined.

Saccharomyces cerevisiae Metabolic Labeling with 4-thiouracil and the Quantification of Newly Synthesized mRNA As a Proxy for RNA Polymerase II Activity

The protocol described here is based on the genome-wide quantification of newly synthesized mRNA purified from yeast cells labeled with 4-thiouracil. This method allows to measure mRNA synthesis uncoupled from mRNA decay and, thus, provides an accurate measurement of RNA polymerase II transcription.

Global defects in RNA polymerase II transcription might be overlooked by transcriptomic studies analyzing steady-state RNA. Indeed, the global decrease in ...

Efficient Transcriptionally Controlled Plasmid Expression System for Investigation of the Stability of mRNA Transcripts in Primary Alveolar Epithelial Cells

Studying posttranscriptional regulation is fundamental to understanding the modulation of a given messenger RNA (mRNA) and its impact on cell homeostasis and metabolism. Indeed, fluctuations in transcript expression could modify the translation efficiency and ultimately the cellular activity of a transcript. Several experimental approaches have been developed to investigate the half-life of mRNA although some of these methods have limitations that prevent the proper study of posttranscriptional modulation. A promoter induction system can express a gene of interest under the control of a synthetic tetracycline-regulated promoter. This method allows the half-life estimation of a given mRNA under any experimental condition without disturbing cell homeostasis. One major drawback of this method is the necessity to transfect cells, which limits the use of this technique in isolated primary cells that are highly resistant to conventional transfection techniques. Alveolar epithelial cells in primary culture have been used extensively to study the cellular and molecular biology of the alveolar epithelium. The unique characteristics and phenotype of primary alveolar cells make it essential to study the posttranscriptional modulations of genes of interest in these cells. Therefore, our aim was to develop a novel tool to investigate the posttranscriptional modulations of mRNAs of interest in alveolar epithelial cells in primary culture. We designed a fast and efficient transient transfection protocol to insert a transcriptionally controlled plasmid expression system into primary alveolar epithelial cells. This cloning strategy, using a viral epitope to tag the construct, allows for the easy discrimination of construct expression from that of endogenous mRNAs. Using a modified &#916;&#916; quantification cycle (Cq) method, the expression of the transcript can then be quantified at different time intervals to measure its half-life. Our data demonstrate the efficiency of this novel approach in studying posttranscriptional regulation in various pathophysiological conditions in primary alveolar epithelial cells.

Here, we present a tool that can be used to study the posttranscriptional modulation of a transcript in primary alveolar epithelial cells by using an inducible expression system coupled to a pipette electroporation technique.

Studying posttranscriptional regulation is fundamental to understanding the modulation of a given messenger RNA (mRNA) and its impact on cell homeostasis ...

Single-Cell Quantification of Protein Degradation Rates by Time-Lapse Fluorescence Microscopy in Adherent Cell Culture

Proteins are in a dynamic state of synthesis and degradation and their half-lives can be adjusted under various circumstances. However, most commonly used approaches to determine protein half-life are either limited to population averages from lysed cells or require the use of protein synthesis inhibitors. This protocol describes a method to measure protein half-lives in single living adherent cells, using SNAP-tag fusion proteins in combination with fluorescence time-lapse microscopy. Any protein of interest fused to a SNAP-tag can be covalently bound by a fluorescent, cell permeable dye that is coupled to a benzylguanine derivative, and the decay of the labeled protein population can be monitored after washout of the residual dye. Subsequent cell tracking and quantification of the integrated fluorescence intensity over time results in an exponential decay curve for each tracked cell, allowing for determining protein degradation rates in single cells by curve fitting. This method provides an estimate for the heterogeneity of half-lives in a population of cultured cells, which cannot easily be assessed by other methods. The approach presented here is applicable to any type of cultured adherent cells expressing a protein of interest fused to a SNAP-tag. Here we use mouse embryonic stem (ES) cells grown on E-cadherin-coated cell culture plates to illustrate how single cell degradation rates of proteins with a broad range of half-lives can be determined.

This protocol describes a method to determine protein half-lives in single living adherent cells, using pulse labeling and fluorescence time-lapse imaging of SNAP-tag fusion proteins.

Proteins are in a dynamic state of synthesis and degradation and their half-lives can be adjusted under various circumstances. However, most commonly used ...

Developmental Biology

Extremely Rapid and Specific Metabolic Labelling of RNA In Vivo with 4-Thiouracil (Ers4tU)

The nucleotide analogue, 4-thiouracil (4tU), is readily taken up by cells and incorporated into RNA as it is transcribed in vivo, allowing isolation of the RNA produced during a brief period of labelling. This is done by attaching a biotin moiety to the incorporated thio group and affinity purifying, using streptavidin coated beads. Achieving a good yield of pure, newly synthesized RNA that is free of pre-existing RNA makes shorter labelling times possible and permits increased temporal resolution in kinetic studies. This is a protocol for very specific, high yield purification of newly synthesized RNA. The protocol presented here describes how RNA is extracted from the yeast Saccharomyces cerevisiae. However, the protocol for purification of thiolated RNA from total RNA should be effective using RNA from any organism once it has been extracted from the cells. The purified RNA is suitable for analysis by many widely used techniques, such as reverse transcriptase-qPCR, RNA-seq and SLAM-seq. The specificity, sensitivity and flexibility of this technique allow unparalleled insights into RNA metabolism.

Extremely Rapid and Specific Metabolic Labelling of RNA In Vivo with 4-Thiouracil Ers4tU

The use of thiolated uracil to sensitively and specifically purify newly transcribed RNA from the yeast Saccharomyces cerevisiae.

The nucleotide analogue, 4-thiouracil (4tU), is readily taken up by cells and incorporated into RNA as it is transcribed in vivo, allowing isolation of ...

Biochemistry

Measurement of Protein Turnover Rates in Senescent and Non-Dividing Cultured Cells with Metabolic Labeling and Mass Spectrometry

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as Alzheimer&#39;s and Parkinson&#39;s diseases. Cellular senescence is a state of permanent cell cycle arrest that typically occurs in response to exposure to sub-lethal stresses. However, like other non-dividing cells, senescent cells remain metabolically active and carry out many functions that require unique transcriptional and translational demands and widespread changes in the intracellular and secreted proteomes. Understanding how protein synthesis and decay rates change during senescence can illuminate the underlying mechanisms of cellular senescence and find potential therapeutic avenues for diseases exacerbated by senescent cells. This paper describes a method for proteome-scale evaluation of protein half-lives in non-dividing cells using pulsed stable isotope labeling by amino acids in cell culture (pSILAC) in combination with mass spectrometry. pSILAC involves metabolic labeling of cells with stable heavy isotope-containing versions of amino acids. Coupled with modern mass spectrometry approaches, pSILAC enables the measurement of protein turnover of hundreds or thousands of proteins in complex mixtures. After metabolic labeling, the turnover dynamics of proteins can be determined based on the relative enrichment of heavy isotopes in peptides detected by mass spectrometry. In this protocol, a workflow is described for the generation of senescent fibroblast cultures and similarly arrested quiescent fibroblasts, as well as a simplified, single-time point pSILAC labeling time-course that maximizes coverage of anticipated protein turnover rates. Further, a pipeline is presented for the analysis of pSILAC mass spectrometry data and user-friendly calculation of protein degradation rates using spreadsheets. The application of this protocol can be extended beyond senescent cells to any non-dividing cultured cells such as neurons.

This protocol describes the workflow for metabolic labeling of senescent and non-dividing cells with pulsed SILAC, untargeted mass spectrometry analysis, and a streamlined calculation of protein half-lives.

Mounting evidence has shown that the accumulation of senescent cells in the central nervous system contributes to neurodegenerative disorders such as ...

Measuring the Kinetics of mRNA Transcription in Single Living Cells

The transcriptional activity of RNA polymerase II (Pol II) is a dynamic process and therefore measuring the kinetics of the transcriptional process in vivo is of importance. Pol II kinetics have been measured using biochemical or molecular methods.1-3 In recent years, with the development of new visualization methods, it has become possible to follow transcription as it occurs in real time in single living cells.4 Herein we describe how to perform analysis of Pol II elongation kinetics on a specific gene in living cells.5, 6 Using a cell line in which a specific gene locus (DNA), its mRNA product, and the final protein product can be fluorescently labeled and visualized in vivo, it is possible to detect the actual transcription of mRNAs on the gene of interest.7, 8 The mRNA is fluorescently tagged using the MS2 system for tagging mRNAs in vivo, where the 3'UTR of the mRNA transcripts contain 24 MS2 stem-loop repeats, which provide highly specific binding sites for the YFP-MS2 coat protein that labels the mRNA as it is transcribed.9 To monitor the kinetics of transcription we use the Fluorescence Recovery After Photobleaching (FRAP) method. By photobleaching the YFP-MS2-tagged nascent transcripts at the site of transcription and then following the recovery of this signal over time, we obtain the synthesis rate of the newly made mRNAs.5 In other words, YFP-MS2 fluorescence recovery reflects the generation of new MS2 stem-loops in the nascent transcripts and their binding by fluorescent free YFP-MS2 molecules entering from the surrounding nucleoplasm. The FRAP recovery curves are then analyzed using mathematical mechanistic models formalized by a series of differential equations, in order to retrieve the kinetic time parameters of transcription.

RNA polymerase II transcriptional kinetics are measured on specific genes in living cells. mRNAs transcribed from the gene of interest are fluorescently tagged and using Fluorescence Recovery After Photobleaching (FRAP) the in vivo kinetics of transcriptional elongation are obtained.

The transcriptional activity of RNA polymerase II (Pol II) is a dynamic process and therefore measuring the kinetics of the transcriptional process in ...

Biology

Metabolic Labeling of Newly Transcribed RNA for High Resolution Gene Expression Profiling of RNA Synthesis, Processing and Decay in Cell Culture

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene expression. Along with a better understanding of the involved molecular mechanisms, precise measurements of the underlying kinetics have become increasingly important. Here, these powerful methodologies face major limitations due to intrinsic properties of the template samples they study, i.e. total cellular RNA. In many cases changes in total cellular RNA occur either too slowly or too quickly to represent the underlying molecular events and their kinetics with sufficient resolution. In addition, the contribution of alterations in RNA synthesis, processing, and decay are not readily differentiated.
We recently developed high-resolution gene expression profiling to overcome these limitations. Our approach is based on metabolic labeling of newly transcribed RNA with 4-thiouridine (thus also referred to as 4sU-tagging) followed by rigorous purification of newly transcribed RNA using thiol-specific biotinylation and streptavidin-coated magnetic beads. It is applicable to a broad range of organisms including vertebrates, Drosophila, and yeast. We successfully applied 4sU-tagging to study real-time kinetics of transcription factor activities, provide precise measurements of RNA half-lives, and obtain novel insights into the kinetics of RNA processing. Finally, computational modeling can be employed to generate an integrated, comprehensive analysis of the underlying molecular mechanisms.

Total cellular RNA provides a poor template for studying short-term changes in RNA synthesis and decay as well as the kinetics of RNA processing. Here, we describe metabolic labeling of newly transcribed RNA with 4-thiouridine followed by thiol-specific biotinylation and purification of newly transcribed RNA allowing to overcome these limitations.

The development of whole-transcriptome microarrays and next-generation sequencing has revolutionized our understanding of the complexity of cellular gene ...

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this yeast model is relevant to many organisms, including humans, since DNA repair and DNA damage response factors are well conserved across diverse species. However, S. cerevisiae has not yet been used to fully address whether the rate of accumulating mutations changes with increasing replicative (mitotic) age due to technical constraints. For instance, measurements of yeast replicative lifespan through micromanipulation involve very small populations of cells, which prohibit detection of rare mutations. Genetic methods to enrich for mother cells in populations by inducing death of daughter cells have been developed, but population sizes are still limited by the frequency with which random mutations that compromise the selection systems occur. The current protocol takes advantage of magnetic sorting of surface-labeled yeast mother cells to obtain large enough populations of aging mother cells to quantify rare mutations through phenotypic selections. Mutation rates, measured through fluctuation tests, and mutation frequencies are first established for young cells and used to predict the frequency of mutations in mother cells of various replicative ages. Mutation frequencies are then determined for sorted mother cells, and the age of the mother cells is determined using flow cytometry by staining with a fluorescent reagent that detects bud scars formed on their cell surfaces during cell division. Comparison of predicted mutation frequencies based on the number of cell divisions to the frequencies experimentally observed for mother cells of a given replicative age can then identify whether there are age-related changes in the rate of accumulating mutations. Variations of this basic protocol provide the means to investigate the influence of alterations in specific gene functions or specific environmental conditions on mutation accumulation to address mechanisms underlying genome instability during replicative aging.

Combining Magnetic Sorting of Mother Cells and Fluctuation Tests to Analyze Genome Instability During Mitotic Cell Aging in Saccharomyces cerevisiae

Mutation rates in young Saccharomyces cerevisiae cells measured through fluctuation tests are used to predict mutation frequencies for mother cells of different replicative ages. Magnetic sorting and flow cytometry are then used to measure actual mutation frequencies and age of mother cells to identify any deviations from predicted mutation frequencies.

Saccharomyces cerevisiae has been an excellent model system for examining mechanisms and consequences of genome instability. Information gained from this ...

Determining Genome-wide Transcript Decay Rates in Proliferating and Quiescent Human Fibroblasts

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