Determination of in vivo RNA kinetics using RATE-seq

Modeling of mRNA deadenylation rates reveal a complex relationship between mRNA deadenylation and decay

Complete cytoplasmic polyadenosine tail (polyA-tail) deadenylation is thought to be essential for initiating mRNA decapping and subsequent degradation. To investigate this prevalent model, we conducted direct RNA sequencing of S. cerevisiae mRNAs derived from chase experiments under steady-state and stress condition. Subsequently, we developed a numerical model based on a modified gamma distribution function, which estimated the transcriptomic deadenylation rate at 10 A/min. A simplified independent method, based on the delineation of quantile polyA-tail values, showed a correlation between the decay and deadenylation rates of individual mRNAs, which appeared consistent within functional transcript groups and associated with codon optimality. Notably, these rates varied during the stress response. Detailed analysis of ribosomal protein-coding mRNAs (RPG mRNAs), constituting 40% of the transcriptome, singled out this transcript group. While deadenylation and decay of RPG mRNAs accelerated under heat stress, their degradation could proceed even when deadenylation was blocked, depending entirely on ongoing nuclear export. Our findings support the general primary function of deadenylation in dictating the onset of decapping, while also demonstrating complex relations between these processes.

The DNA damage response and RNA Polymerase II regulator Def1 has posttranscriptional functions in the cytoplasm

Yeast Def1 mediates RNA polymerase II degradation and transcription elongation during stress. Def1 is predominantly cytoplasmic, and DNA damage signals cause its proteolytic processing, liberating its N-terminus to enter the nucleus. Cytoplasmic functions for this abundant protein have not been identified. Proximity-labeling (BioID) experiments indicate that Def1 binds to an array of proteins involved in posttranscriptional control and translation of mRNAs. Deleting DEF1 reduces both mRNA synthesis and decay rates, indicating transcript buffering in the mutant. Directly tethering Def1 to a reporter mRNA suppressed expression, suggesting that Def1 directly regulates mRNAs. Surprisingly, we found that Def1 interacts with polyribosomes, which requires its ubiquitin-binding domain located in its N-terminus. The binding of Def1 to ribosomes requires the ubiquitylation of eS7a (Rsp7A) in the small subunit by the Not4 protein in the Ccr4-Not complex. Not4 ubiquitylation of the ribosome regulates translation quality control and co-translational mRNA decay. The polyglutamine-rich unstructured C-terminus of Def1 is required for its interaction with decay and translation factors, suggesting that Def1 acts as a ubiquitin-dependent scaffold to link translation status to mRNA decay. Thus, we have identified a novel function for this transcription and DNA damage response factor in posttranscriptional regulation in the cytoplasm and establish Def1 as a master regulator of gene expression, functioning during transcription, mRNA decay, and translation.

Simple protocol for combined extraction of exocrine secretions and RNA in small arthropods

The integration of data from multiple sources and analytical techniques to obtain novel insights and answer challenging questions is a hallmark of modern science. In arthropods, exocrine secretions may act as pheromones, defensive substances, antibiotics, as well as surface protectants, and as such they play a crucial role in ecology and evolution. Exocrine chemical compounds are frequently characterized by gas chromatography-mass spectrometry. Technological advances of recent years now allow us to routinely characterize the total gene complement transcribed in a particular biological tissue, often in the context of experimental treatment, via RNAseq. We here introduce a novel methodological approach to successfully characterize exocrine secretions and full transcriptomes of one and the same individual of oribatid mites. We found that chemical extraction prior to RNA extraction had only minor effects on the total RNA integrity. De novo transcriptomes obtained from such combined extractions were of comparable quality to those assembled for samples that were subject to RNA extraction only, indicating that combined chemical/RNA extraction is perfectly suitable for phylotranscriptomic studies. However, in-depth analysis of RNA expression analysis indicates that chemical extraction prior to RNAseq may affect transcript degradation rates, similar to the effects reported in previous studies comparing RNA extraction protocols. With this pilot study, we demonstrate that profiling chemical secretions and RNA expression levels from the same individual is methodologically feasible, paving the way for future research to understand the genes and pathways underlying the syntheses of biogenic chemical compounds. Our approach should be applicable broadly to most arachnids, insects, and other arthropods.

Yeast poly(A)-binding protein (Pab1) controls translation initiation in vivo primarily by blocking mRNA decapping and decay

Poly(A)-binding protein (Pab1 in yeast) is involved in mRNA decay and translation initiation, but its molecular functions are incompletely understood. We found that auxin-induced degradation of Pab1 reduced bulk mRNA and polysome abundance in a manner suppressed by deleting the catalytic subunit of decapping enzyme (dcp2Δ), demonstrating that enhanced decapping/degradation is the major driver of reduced mRNA abundance and protein synthesis at limiting Pab1 levels. An increased median poly(A) tail length conferred by Pab1 depletion was also nullified by dcp2Δ, suggesting that mRNA isoforms with shorter tails are preferentially decapped/degraded at limiting Pab1. In contrast to findings on mammalian cells, the translational efficiencies (TEs) of many mRNAs were altered by Pab1 depletion; however, these changes were broadly diminished by dcp2∆, suggesting that reduced mRNA abundance is a major driver of translational reprogramming at limiting Pab1. Thus, assembly of the closed-loop mRNP via PABP-eIF4G interaction appears to be dispensable for normal translation of most yeast mRNAs in vivo. Interestingly, histone mRNAs and proteins are preferentially diminished on Pab1 depletion dependent on Dcp2, accompanied by activation of internal cryptic promoters in the manner expected for reduced nucleosome occupancies, revealing a new layer of post-transcriptional control of histone gene expression.

A kinetic dichotomy between mitochondrial and nuclear gene expression processes

Oxidative phosphorylation (OXPHOS) complexes, encoded by both mitochondrial and nuclear DNA, are essential producers of cellular ATP, but how nuclear and mitochondrial gene expression steps are coordinated to achieve balanced OXPHOS subunit biogenesis remains unresolved. Here, we present a parallel quantitative analysis of the human nuclear and mitochondrial messenger RNA (mt-mRNA) life cycles, including transcript production, processing, ribosome association, and degradation. The kinetic rates of nearly every stage of gene expression differed starkly across compartments. Compared with nuclear mRNAs, mt-mRNAs were produced 1,100-fold more, degraded 7-fold faster, and accumulated to 160-fold higher levels. Quantitative modeling and depletion of mitochondrial factors LRPPRC and FASTKD5 identified critical points of mitochondrial regulatory control, revealing that the mitonuclear expression disparities intrinsically arise from the highly polycistronic nature of human mitochondrial pre-mRNA. We propose that resolving these differences requires a 100-fold slower mitochondrial translation rate, illuminating the mitoribosome as a nexus of mitonuclear co-regulation.

Transcriptome-Wide Analysis of mRNA Adenylation Status in Yeast Using Nanopore Sequencing

There are multiple methods for studying deadenylation, either in vitro or in vivo, which allow for observation of mRNA abundance or poly(A) tail dynamics. However, direct RNA sequencing using the Oxford Nanopore Technologies (ONT) platform makes it possible to conduct transcriptome-wide analyses at the single-molecule level without the PCR bias introduced by other methods. In this chapter, we provide a protocol to measure both RNA levels and poly(A)-tail lengths in the yeast Saccharomyces cerevisiae using ONT.

Single-molecule quantitation of RNA-binding protein occupancy and stoichiometry defines a role for Yra1 (Aly/REF) in nuclear mRNP organization

RNA-binding proteins (RBPs) interact with mRNA to form supramolecular complexes called messenger ribonucleoprotein (mRNP) particles. These dynamic assemblies direct and regulate individual steps of gene expression; however, their composition and functional importance remain largely unknown. Here, we develop a total internal reflection fluorescence-based single-molecule imaging assay to investigate stoichiometry and co-occupancy of 15 RBPs within mRNPs from Saccharomyces cerevisiae. We show compositional heterogeneity of single mRNPs and plasticity across different growth conditions, with major co-occupants of mRNPs containing the nuclear cap-binding complex identified as Yra1 (1-10 copies), Nab2 (1-6 copies), and Npl3 (1-6 copies). Multicopy Yra1-bound mRNPs are specifically co-occupied by the THO complex and assembled on mRNAs biased by transcript length and RNA secondary structure. Yra1 depletion results in decreased compaction of nuclear mRNPs demonstrating a packaging function. Together, we provide a quantitative framework for gene- and condition-dependent RBP occupancy and stoichiometry in individual nuclear mRNPs.

Examining SRP pathway function in mRNA localization to the endoplasmic reticulum

Signal recognition particle (SRP) pathway function in protein translocation across the endoplasmic reticulum (ER) is well established; its role in RNA localization to the ER remains, however, unclear. In current models, mRNAs undergo translation- and SRP-dependent trafficking to the ER, with ER localization mediated via interactions between SRP-bound translating ribosomes and the ER-resident SRP receptor (SR), a heterodimeric complex comprising SRA, the SRP-binding subunit, and SRB, an integral membrane ER protein. To study SRP pathway function in RNA localization, SR knockout (KO) mammalian cell lines were generated and the consequences of SR KO on steady-state and dynamic mRNA localization examined. CRISPR/Cas9-mediated SRPRB KO resulted in profound destabilization of SRA. Pairing siRNA silencing of SRPRA in SRPRB KO cells yielded viable SR KO cells. Steady-state mRNA compositions and ER-localization patterns in parental and SR KO cells were determined by cell fractionation and deep sequencing. Notably, steady-state cytosol and ER mRNA compositions and partitioning patterns were largely unaltered by loss of SR expression. To examine SRP pathway function in RNA localization dynamics, the subcellular trafficking itineraries of newly exported mRNAs were determined by 4-thiouridine (4SU) pulse-labeling/4SU-seq/cell fractionation. Newly exported mRNAs were distinguished by high ER enrichment, with ER localization being SR-independent. Intriguingly, under conditions of translation initiation inhibition, the ER was the default localization site for all newly exported mRNAs. These data demonstrate that mRNA localization to the ER can be uncoupled from the SRP pathway function and reopen questions regarding the mechanism of RNA localization to the ER.

The LARP1 homolog Slr1p controls the stability and expression of proto-5'TOP mRNAs in fission yeast

Messenger RNAs (mRNAs) in higher eukaryotes that encode proteins important for the assembly of the translational apparatus (e.g., ribosomal proteins) often harbor a pyrimidine-rich motif at the extreme 5' end known as a 5' terminal oligopyrimidine (5'TOP) sequence. Members of the La-related protein 1 (LARP1) family control 5'TOP expression through a conserved DM15 motif, but the mechanism is not well understood. 5'TOP motifs have not been described in many lower organisms, and fission yeast harbors a LARP1 homolog that also lacks a DM15 motif. In this work, we show that the fission yeast LARP1 homolog, Slr1p, controls the translation and stability of mRNAs encoding proteins analogous to 5'TOP mRNAs in higher eukaryotes, which we thus refer to as proto-5'TOPs. Our data suggest that the LARP1 DM15 motif and the mRNA 5'TOP motif may be features that were scaffolded over a more fundamental mechanism of LARP1-associated control of gene expression.

Translation factor and RNA binding protein mRNA interactomes support broader RNA regulons for posttranscriptional control

The regulation of translation provides a rapid and direct mechanism to modulate the cellular proteome. In eukaryotes, an established model for the recruitment of ribosomes to mRNA depends upon a set of conserved translation initiation factors. Nevertheless, how cells orchestrate and define the selection of individual mRNAs for translation, as opposed to other potential cytosolic fates, is poorly understood. We have previously found significant variation in the interaction between individual mRNAs and an array of translation initiation factors. Indeed, mRNAs can be separated into different classes based upon these interactions to provide a framework for understanding different modes of translation initiation. Here, we extend this approach to include new mRNA interaction profiles for additional proteins involved in shaping the cytoplasmic fate of mRNAs. This work defines a set of seven mRNA clusters, based on their interaction profiles with 12 factors involved in translation and/or RNA binding. The mRNA clusters share both physical and functional characteristics to provide a rationale for the interaction profiles. Moreover, a comparison with mRNA interaction profiles from a host of RNA binding proteins suggests that there are defined patterns in the interactions of functionally related mRNAs. Therefore, this work defines global cytoplasmic mRNA binding modules that likely coordinate the synthesis of functionally related proteins.

Polysome propensity and tunable thresholds in coding sequence length enable differential mRNA stability

The half-life of mRNAs, as well as their translation, increases in proportion to the optimal codons, indicating a tight coupling of codon-dependent differential translation and degradation. Little is known about the regulation of this coupling. We found that the mRNA stability gain in yeast depends on the mRNA coding sequence length. Below a critical length, codon optimality fails to affect the stability of mRNAs although they can be efficiently translated into short peptides and proteins. Above this threshold length, codon optimality-dependent differential mRNA stability emerges in a switch-like fashion, which coincides with a similar increase in the polysome propensity of the mRNAs. This threshold length can be tuned by the untranslated regions (UTR). Some of these UTRs can destabilize mRNAs without reducing translation, which plays a role in controlling the amplitude of the oscillatory expression of cell cycle genes. Our findings help understand the translation of short peptides from noncoding RNAs and the translation by localized monosomes in neurons.

Simultaneous estimation of gene regulatory network structure and RNA kinetics from single cell gene expression

Cells respond to environmental and developmental stimuli by remodeling their transcriptomes through regulation of both mRNA transcription and mRNA decay. A central goal of biology is identifying the global set of regulatory relationships between factors that control mRNA production and degradation and their target transcripts and construct a predictive model of gene expression. Regulatory relationships are typically identified using transcriptome measurements and causal inference algorithms. RNA kinetic parameters are determined experimentally by employing run-on or metabolic labeling (e.g. 4-thiouracil) methods that allow transcription and decay rates to be separately measured. Here, we develop a deep learning model, trained with single-cell RNA-seq data, that both infers causal regulatory relationships and estimates RNA kinetic parameters. The resulting in silico model predicts future gene expression states and can be perturbed to simulate the effect of transcription factor changes. We acquired model training data by sequencing the transcriptomes of 175,000 individual Saccharomyces cerevisiae cells that were subject to an external perturbation and continuously sampled over a one hour period. The rate of change for each transcript was calculated on a per-cell basis to estimate RNA velocity. We then trained a deep learning model with transcriptome and RNA velocity data to calculate time-dependent estimates of mRNA production and decay rates. By separating RNA velocity into transcription and decay rates, we show that rapamycin treatment causes existing ribosomal protein transcripts to be rapidly destabilized, while production of new transcripts gradually slows over the course of an hour. The neural network framework we present is designed to explicitly model causal regulatory relationships between transcription factors and their genes, and shows superior performance to existing models on the basis of recovery of known regulatory relationships. We validated the predictive power of the model by perturbing transcription factors in silico and comparing transcriptome-wide effects with experimental data. Our study represents the first step in constructing a complete, predictive, biophysical model of gene expression regulation.

Copy number variation alters local and global mutational tolerance

Copy number variants (CNVs), duplications and deletions of genomic sequences, contribute to evolutionary adaptation but can also confer deleterious effects and cause disease. Whereas the effects of amplifying individual genes or whole chromosomes (i.e., aneuploidy) have been studied extensively, much less is known about the genetic and functional effects of CNVs of differing sizes and structures. Here, we investigated Saccharomyces cerevisiae (yeast) strains that acquired adaptive CNVs of variable structures and copy numbers following experimental evolution in glutamine-limited chemostats. Although beneficial in the selective environment, CNVs result in decreased fitness compared with the euploid ancestor in rich media. We used transposon mutagenesis to investigate mutational tolerance and genome-wide genetic interactions in CNV strains. We find that CNVs increase mutational target size, confer increased mutational tolerance in amplified essential genes, and result in novel genetic interactions with unlinked genes. We validated a novel genetic interaction between different CNVs and BMH1 that was common to multiple strains. We also analyzed global gene expression and found that transcriptional dosage compensation does not affect most genes amplified by CNVs, although gene-specific transcriptional dosage compensation does occur for ∼12% of amplified genes. Furthermore, we find that CNV strains do not show previously described transcriptional signatures of aneuploidy. Our study reveals the extent to which local and global mutational tolerance is modified by CNVs with implications for genome evolution and CNV-associated diseases, such as cancer.

Dynamically regulated transcription factors are encoded by highly unstable mRNAs in the Drosophila larval brain

The level of each RNA species depends on the balance between its rates of production and decay. Although previous studies have measured RNA decay across the genome in tissue culture and single-celled organisms, few experiments have been performed in intact complex tissues and organs. It is therefore unclear whether the determinants of RNA decay found in cultured cells are preserved in an intact tissue, and whether they differ between neighboring cell types and are regulated during development. To address these questions, we measured RNA synthesis and decay rates genome wide via metabolic labeling of whole cultured Drosophila larval brains using 4-thiouridine. Our analysis revealed that decay rates span a range of more than 100-fold, and that RNA stability is linked to gene function, with mRNAs encoding transcription factors being much less stable than mRNAs involved in core metabolic functions. Surprisingly, among transcription factor mRNAs there was a clear demarcation between more widely used transcription factors and those that are expressed only transiently during development. mRNAs encoding transient transcription factors are among the least stable in the brain. These mRNAs are characterized by epigenetic silencing in most cell types, as shown by their enrichment with the histone modification H3K27me3. Our data suggest the presence of an mRNA destabilizing mechanism targeted to these transiently expressed transcription factors to allow their levels to be regulated rapidly with high precision. Our study also demonstrates a general method for measuring mRNA transcription and decay rates in intact organs or tissues, offering insights into the role of mRNA stability in the regulation of complex developmental programs.

Evolutionary trade-off and mutational bias could favor transcriptional over translational divergence within paralog pairs

How changes in the different steps of protein synthesis-transcription, translation and degradation-contribute to differences of protein abundance among genes is not fully understood. There is however accumulating evidence that transcriptional divergence might have a prominent role. Here, we show that yeast paralogous genes are more divergent in transcription than in translation. We explore two causal mechanisms for this predominance of transcriptional divergence: an evolutionary trade-off between the precision and economy of gene expression and a larger mutational target size for transcription. Performing simulations within a minimal model of post-duplication evolution, we find that both mechanisms are consistent with the observed divergence patterns. We also investigate how additional properties of the effects of mutations on gene expression, such as their asymmetry and correlation across levels of regulation, can shape the evolution of paralogs. Our results highlight the importance of fully characterizing the distributions of mutational effects on transcription and translation. They also show how general trade-offs in cellular processes and mutation bias can have far-reaching evolutionary impacts.

Improving the study of RNA dynamics through advances in RNA-seq with metabolic labeling and nucleotide-recoding chemistry

RNA metabolic labeling using 4-thiouridine (s4U) captures the dynamics of RNA synthesis and decay. The power of this approach is dependent on appropriate quantification of labeled and unlabeled sequencing reads, which can be compromised by the apparent loss of s4U-labeled reads in a process we refer to as dropout. Here we show that s4U-containing transcripts can be selectively lost when RNA samples are handled under sub-optimal conditions, but that this loss can be minimized using an optimized protocol. We demonstrate a second cause of dropout in nucleotide recoding and RNA sequencing (NR-seq) experiments that is computational and downstream of library preparation. NR-seq experiments involve chemically converting s4U from a uridine analog to a cytidine analog and using the apparent T-to-C mutations to identify the populations of newly synthesized RNA. We show that high levels of T-to-C mutations can prevent read alignment with some computational pipelines, but that this bias can be overcome using improved alignment pipelines. Importantly, kinetic parameter estimates are affected by dropout independent of the NR chemistry employed, and all chemistries are practically indistinguishable in bulk, short-read RNA-seq experiments. Dropout is an avoidable problem that can be identified by including unlabeled controls, and mitigated through improved sample handing and read alignment that together improve the robustness and reproducibility of NR-seq experiments.

Transcriptional buffering and 3'UTR lengthening are shaped during human neurodevelopment by shifts in mRNA stability and microRNA load

The contribution of mRNA half-life is commonly overlooked when examining changes in mRNA abundance during development. mRNA levels of some genes are regulated by transcription rate only, but others may be regulated by mRNA half-life only shifts. Furthermore, transcriptional buffering is predicted when changes in transcription rates have compensating shifts in mRNA half-life resulting in no change to steady-state levels. Likewise, transcriptional boosting should result when changes in transcription rate are accompanied by amplifying half-life shifts. During neurodevelopment there is widespread 3'UTR lengthening that could be shaped by differential shifts in the stability of existing short or long 3'UTR transcript isoforms. We measured transcription rate and mRNA half-life changes during induced human Pluripotent Stem Cell (iPSC)-derived neuronal development using RATE-seq. During transitions to progenitor and neuron stages, transcriptional buffering occurred in up to 50%, and transcriptional boosting in up to 15%, of genes with changed transcription rates. The remaining changes occurred by transcription rate only or mRNA half-life only shifts. Average mRNA half-life decreased two-fold in neurons relative to iPSCs. Short gene isoforms were more destabilized in neurons and thereby increased the average 3'UTR length. Small RNA sequencing captured an increase in microRNA copy number per cell during neurodevelopment. We propose that mRNA destabilization and 3'UTR lengthening are driven in part by an increase in microRNA load in neurons. Our findings identify mRNA stability mechanisms in human neurodevelopment that regulate gene and isoform level abundance and provide a precedent for similar post-transcriptional regulatory events as other tissues develop.

Sequence features around cleavage sites are highly conserved among different species and a critical determinant for RNA cleavage position across eukaryotes

RNA degradation is one of the critical steps for control of gene expression, and endonucleolytic cleavage-dependent RNA degradation is conserved among eukaryotes. Some cleavage sites are secondarily capped in the cytoplasm and identified using the Cap analysis of gene expression (CAGE) method. Although uncapped cleavage sites are widespread in eukaryotes, comparatively little information has been obtained about these sites using CAGE-based degradome analysis. Previously, we developed the truncated RNA-end sequencing (TREseq) method in plant species and used it to acquire comprehensive information about uncapped cleavage sites; we observed G-rich sequences near cleavage sites. However, it remains unclear whether this finding is general to other eukaryotes. In this study, we conducted TREseq analyses in fruit flies (Drosophila melanogaster) and budding yeast (Saccharomyces cerevisiae). The results revealed specific sequence features related to RNA cleavage in D. melanogaster and S. cerevisiae that were similar to sequence patterns in Arabidopsis thaliana. Although previous studies suggest that ribosome movements are important for determining cleavage position, feature selection using a random forest classifier showed that sequences around cleavage sites were major determinant for cleaved or uncleaved sites. Together, our results suggest that sequence features around cleavage sites are critical for determining cleavage position, and that sequence-specific endonucleolytic cleavage-dependent RNA degradation is highly conserved across eukaryotes.

Mitotic checkpoint gene expression is tuned by codon usage bias

The mitotic checkpoint (also called spindle assembly checkpoint, SAC) is a signaling pathway that safeguards proper chromosome segregation. Correct functioning of the SAC depends on adequate protein concentrations and appropriate stoichiometries between SAC proteins. Yet very little is known about the regulation of SAC gene expression. Here, we show in the fission yeast Schizosaccharomyces pombe that a combination of short mRNA half-lives and long protein half-lives supports stable SAC protein levels. For the SAC genes mad2+ and mad3+ , their short mRNA half-lives are caused, in part, by a high frequency of nonoptimal codons. In contrast, mad1+ mRNA has a short half-life despite a higher frequency of optimal codons, and despite the lack of known RNA-destabilizing motifs. Hence, different SAC genes employ different strategies of expression. We further show that Mad1 homodimers form co-translationally, which may necessitate a certain codon usage pattern. Taken together, we propose that the codon usage of SAC genes is fine-tuned to ensure proper SAC function. Our work shines light on gene expression features that promote spindle assembly checkpoint function and suggests that synonymous mutations may weaken the checkpoint.

Clinical and Molecular Characterization of a Rare Case of BNT162b2 mRNA COVID-19 Vaccine-Associated Myositis

Initial clinical trials and surveillance data have shown that the most commonly administered BNT162b2 COVID-19 mRNA vaccine is effective and safe. However, several cases of mRNA vaccine-induced mild to moderate adverse events were recently reported. Here, we report a rare case of myositis after injection of the first dose of BNT162b2 COVID-19 mRNA vaccine into the left deltoid muscle of a 34-year-old, previously healthy woman who presented progressive proximal muscle weakness, progressive dysphagia, and dyspnea with respiratory failure. One month after vaccination, BNT162b2 vaccine mRNA expression was detected in a tissue biopsy of the right deltoid and quadriceps muscles. We propose this case as a rare example of COVID-19 mRNA vaccine-induced myositis. This study comprehensively characterizes the clinical and molecular features of BNT162b2 mRNA vaccine-associated myositis in which the patient was severely affected.

Global SLAM-seq for accurate mRNA decay determination and identification of NMD targets

Gene expression analysis requires accurate measurements of global RNA degradation rates, earlier problematic with methods disruptive to cell physiology. Recently, metabolic RNA labeling emerged as an efficient and minimally invasive technique applied in mammalian cells. Here, we have adapted SH-linked alkylation for the metabolic sequencing of RNA (SLAM-seq) for a global mRNA stability study in yeast using 4-thiouracil pulse-chase labeling. We assign high-confidence half-life estimates for 67.5% of expressed ORFs, and measure a median half-life of 9.4 min. For mRNAs where half-life estimates exist in the literature, their ranking order was in good agreement with previous data, indicating that SLAM-seq efficiently classifies stable and unstable transcripts. We then leveraged our yeast protocol to identify targets of the nonsense-mediated decay (NMD) pathway by measuring the change in RNA half-lives, instead of steady-state RNA level changes. With SLAM-seq, we assign 580 transcripts as putative NMD targets, based on their measured half-lives in wild-type and upf3Δ mutants. We find 225 novel targets, and observe a strong agreement with previous reports of NMD targets, 61.2% of our candidates being identified in previous studies. This indicates that SLAM-seq is a simpler and more economic method for global quantification of mRNA half-lives. Our adaptation for yeast yielded global quantitative measures of the NMD effect on transcript half-lives, high correlation with RNA half-lives measured previously with more technically challenging protocols, and identification of novel NMD regulated transcripts that escaped prior detection.

Estimating RNA dynamics using one time point for one sample in a single-pulse metabolic labeling experiment

Background

Over the past decade, experimental procedures such as metabolic labeling for determining RNA turnover rates at the transcriptome-wide scale have been widely adopted and are now turning to single cell measurements. Several computational methods to estimate RNA synthesis, processing and degradation rates from such experiments have been suggested, but they all require several RNA sequencing samples. Here we present a method that can estimate those three rates from a single sample.

Methods

Our method relies on the analytical solution to the Zeisel model of RNA dynamics. It was validated on metabolic labeling experiments performed on mouse embryonic stem cells. Resulting degradation rates were compared both to previously published rates on the same system and to a state-of-the-art method applied to the same data.

Results

Our method is computationally efficient and outputs rates that correlate well with previously published data sets. Using it on a single sample, we were able to reproduce the observation that dynamic biological processes tend to involve genes with higher metabolic rates, while stable processes involve genes with lower rates. This supports the hypothesis that cells control not only the mRNA steady-state abundance, but also its responsiveness, i.e., how fast steady state is reached. Moreover, degradation rates obtained with our method compare favourably with the other tested method.

Conclusions

In addition to saving experimental work and computational time, estimating rates for a single sample has several advantages. It does not require an error-prone normalization across samples and enables the use of replicates to estimate uncertainty and assess sample quality. Finally the method and theoretical results described here are general enough to be useful in other contexts such as nucleotide conversion methods and single cell metabolic labeling experiments.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04672-4.

In Situ Visualizing Nascent RNA by Exploring DNA-Templated Oxidative Amination of 4-Thiouridine

Tracking and mapping the nascent RNA molecules in cells is essential for deciphering embryonic development and neuronal differentiation. Here, we utilized 4-thiouridine (s4U) as a metabolic tag to label nascent RNA and developed a fluorescence imaging method based on the DNA-templated oxidative amination (DTOA) reaction of s4U. The DTOA reaction occurred between amine-modified DNA and s4U-containing RNA with high sequence specificity and chemical selectivity. Target nascent mRNAs in HeLa cells, including those encoding green fluorescent proteins (GFPs) and endogenous BAG-1, were thus lit up selectively by DTOA-based fluorescence in situ hybridization (DTOA FISH). We believe the DTOA conjugation chemistry shown in this study could be generally applied to investigate the spatial distribution of nascent transcription dynamics in cellular processes.

Heterogeneous recruitment abilities to RNA polymerases generate nonlinear scaling of gene expression with cell volume

While most genes' expression levels are proportional to cell volumes, some genes exhibit nonlinear scaling between their expression levels and cell volume. Therefore, their mRNA and protein concentrations change as the cell volume increases, which often have crucial biological functions such as cell-cycle regulation. However, the biophysical mechanism underlying the nonlinear scaling between gene expression and cell volume is still unclear. In this work, we show that the nonlinear scaling is a direct consequence of the heterogeneous recruitment abilities of promoters to RNA polymerases based on a gene expression model at the whole-cell level. Those genes with weaker (stronger) recruitment abilities than the average ability spontaneously exhibit superlinear (sublinear) scaling with cell volume. Analysis of the promoter sequences and the nonlinear scaling of Saccharomyces cerevisiae's mRNA levels shows that motifs associated with transcription regulation are indeed enriched in genes exhibiting nonlinear scaling, in concert with our model.

Integrated multi-omics reveals common properties underlying stress granule and P-body formation

Non-membrane-bound compartments such as P-bodies (PBs) and stress granules (SGs) play important roles in the regulation of gene expression following environmental stresses. We have systematically and quantitatively determined the protein and mRNA composition of PBs and SGs formed before and after nutrient stress. We find that high molecular weight (HMW) complexes exist prior to glucose depletion that we propose may act as seeds for further condensation of proteins forming mature PBs and SGs. We identify an enrichment of proteins with low complexity and RNA binding domains, as well as long, structured mRNAs that are poorly translated following nutrient stress. Many proteins and mRNAs are shared between PBs and SGs including several multivalent RNA binding proteins that promote condensate interactions during liquid-liquid phase separation. We uncover numerous common protein and RNA components across PBs and SGs that support a complex interaction profile during the maturation of these biological condensates. These interaction networks represent a tuneable response to stress, highlighting previously unrecognized condensate heterogeneity. These studies therefore provide an integrated and quantitative understanding of the dynamic nature of key biological condensates.

Mutually Orthogonal Bioconjugation of Vinyl Nucleosides for RNA Metabolic Labeling

We report a strategy for the orthogonal conjugation of the vinyl nucleosides, 5-vinyluridine (5-VU) and 2-vinyladenosine (2-VA), via selective reactivity with maleimide and tris(2-carboxyethyl)phosphine (TCEP), respectively. The orthogonality was investigated using density functional theory (DFT) and confirmed by reactions with vinyl nucleosides. Further, these chemistries were used to modify RNA for fluorescent cell imaging. These reactions allow for the expanded use of RNA metabolic labeling to study nascent RNA expression within different RNA populations.

Global view on the metabolism of RNA poly(A) tails in yeast Saccharomyces cerevisiae

The polyadenosine tail (poly[A]-tail) is a universal modification of eukaryotic messenger RNAs (mRNAs) and non-coding RNAs (ncRNAs). In budding yeast, Pap1-synthesized mRNA poly(A) tails enhance export and translation, whereas Trf4/5-mediated polyadenylation of ncRNAs facilitates degradation by the exosome. Using direct RNA sequencing, we decipher the extent of poly(A) tail dynamics in yeast defective in all relevant exonucleases, deadenylases, and poly(A) polymerases. Predominantly ncRNA poly(A) tails are 20-60 adenosines long. Poly(A) tails of newly transcribed mRNAs are 50 adenosine long on average, with an upper limit of 200. Exonucleolysis by Trf5-assisted nuclear exosome and cytoplasmic deadenylases trim the tails to 40 adenosines on average. Surprisingly, PAN2/3 and CCR4-NOT deadenylase complexes have a large pool of non-overlapping substrates mainly defined by expression level. Finally, we demonstrate that mRNA poly(A) tail length strongly responds to growth conditions, such as heat and nutrient deprivation.

mRNA vaccines for COVID-19: what, why and how

The Coronavirus disease-19 (COVID-19) pandemic, caused by severe acute respiratory syndrome coronavirus -2 (SARS-CoV-2), has impacted human lives in the most profound ways with millions of infections and deaths. Scientists and pharmaceutical companies have been in race to produce vaccines against SARS-CoV-2. Vaccine generation usually demands years of developing and testing for efficacy and safety. However, it only took less than one year to generate two mRNA vaccines from their development to deployment. The rapid production time, cost-effectiveness, versatility in vaccine design, and clinically proven ability to induce cellular and humoral immune response have crowned mRNA vaccines with spotlights as most promising vaccine candidates in the fight against the pandemic. In this review, we discuss the general principles of mRNA vaccine design and working mechanisms of the vaccines, and provide an up-to-date summary of pre-clinical and clinical trials on seven anti-COVID-19 mRNA candidate vaccines, with the focus on the two mRNA vaccines already licensed for vaccination. In addition, we highlight the key strategies in designing mRNA vaccines to maximize the expression of immunogens and avoid intrinsic innate immune response. We also provide some perspective for future vaccine development against COVID-19 and other pathogens.

Reprogramming of translation in yeast cells impaired for ribosome recycling favors short, efficiently translated mRNAs

In eukaryotes, 43S preinitiation complex (PIC) formation is a rate-determining step of translation. Ribosome recycling following translation termination produces free 40S subunits for re-assembly of 43S PICs. Yeast mutants lacking orthologs of mammalian eIF2D (Tma64), and either MCT-1 (Tma20) or DENR (Tma22), are broadly impaired for 40S recycling; however, it was unknown whether this defect alters the translational efficiencies (TEs) of particular mRNAs. Here, we conducted ribosome profiling of a yeast tma64∆/tma20∆ double mutant and observed a marked reprogramming of translation, wherein the TEs of the most efficiently translated ('strong') mRNAs increase, while those of 'weak' mRNAs generally decline. Remarkably, similar reprogramming was seen on reducing 43S PIC assembly by inducing phosphorylation of eIF2α or by decreasing total 40S subunit levels by depleting Rps26. Our findings suggest that strong mRNAs outcompete weak mRNAs in response to 43S PIC limitation achieved in various ways, in accordance with previous mathematical modeling.

A Trans-Omics Comparison Reveals Common Gene Expression Strategies in Four Model Organisms and Exposes Similarities and Differences between Them

The ultimate goal of gene expression regulation is on the protein level. However, because the amounts of mRNAs and proteins are controlled by their synthesis and degradation rates, the cellular amount of a given protein can be attained by following different strategies. By studying omics data for six expression variables (mRNA and protein amounts, plus their synthesis and decay rates), we previously demonstrated the existence of common expression strategies (CESs) for functionally related genes in the yeast Saccharomyces cerevisiae. Here we extend that study to two other eukaryotes: the yeast Schizosaccharomyces pombe and cultured human HeLa cells. We also use genomic data from the model prokaryote Escherichia coli as an external reference. We show that six-variable profiles (6VPs) can be constructed for every gene and that these 6VPs are similar for genes with similar functions in all the studied organisms. The differences in 6VPs between organisms can be used to establish their phylogenetic relationships. The analysis of the correlations among the six variables supports the hypothesis that most gene expression control occurs in actively growing organisms at the transcription rate level, and that translation plays a minor role. We propose that living organisms use CESs for the genes acting on the same physiological pathways, especially for those belonging to stable macromolecular complexes, but CESs have been modeled by evolution to adapt to the specific life circumstances of each organism.

Cellular quiescence in budding yeast

Cellular quiescence, the temporary and reversible exit from proliferative growth, is the predominant state of all cells. However, our understanding of the biological processes and molecular mechanisms that underlie cell quiescence remains incomplete. As with the mitotic cell cycle, budding and fission yeast are preeminent model systems for studying cellular quiescence owing to their rich experimental toolboxes and the evolutionary conservation across eukaryotes of pathways and processes that control quiescence. Here, we review current knowledge of cell quiescence in budding yeast and how it pertains to cellular quiescence in other organisms, including multicellular animals. Quiescence entails large-scale remodeling of virtually every cellular process, organelle, gene expression, and metabolic state that is executed dynamically as cells undergo the initiation, maintenance, and exit from quiescence. We review these major transitions, our current understanding of their molecular bases, and highlight unresolved questions. We summarize the primary methods employed for quiescence studies in yeast and discuss their relative merits. Understanding cell quiescence has important consequences for human disease as quiescent single-celled microbes are notoriously difficult to kill and quiescent human cells play important roles in diseases such as cancer. We argue that research on cellular quiescence will be accelerated through the adoption of common criteria, and methods, for defining cell quiescence. An integrated approach to studying cell quiescence, and a focus on the behavior of individual cells, will yield new insights into the pathways and processes that underlie cell quiescence leading to a more complete understanding of the life cycle of cells. TAKE AWAY: Quiescent cells are viable cells that have reversibly exited the cell cycle Quiescence is induced in response to a variety of nutrient starvation signals Quiescence is executed dynamically through three phases: initiation, maintenance, and exit Quiescence entails large-scale remodeling of gene expression, organelles, and metabolism Single-cell approaches are required to address heterogeneity among quiescent cells.

Genome-scale molecular principles of mRNA half-life regulation in yeast

Precise control of protein and messenger RNA (mRNA) degradation is essential for cellular metabolism and homeostasis. Controlled and specific degradation of both molecular species necessitates their engagements with the respective degradation machineries; this engagement involves a disordered/unstructured segment of the substrate traversing the degradation tunnel of the machinery and accessing the catalytic sites. However, while molecular factors influencing protein degradation have been extensively explored on a genome scale, and in multiple organisms, such a comprehensive understanding remains missing for mRNAs. Here, we analyzed multiple genome-scale experimental yeast mRNA half-life data in light of experimentally derived mRNA secondary structures and protein binding data, along with high-resolution X-ray crystallographic structures of the RNase machines. Results unraveled a consistent genome-scale trend that mRNAs comprising longer terminal and/or internal unstructured segments have significantly shorter half-lives; the lengths of the 5'-terminal, 3'-terminal, and internal unstructured segments that affect mRNA half-life are compatible with molecular structures of the 5' exo-, 3' exo-, and endoribonuclease machineries. Sequestration into ribonucleoprotein complexes elongates mRNA half-life, presumably by burying ribonuclease engagement sites under oligomeric interfaces. After gene duplication, differences in terminal unstructured lengths, proportions of internal unstructured segments, and oligomerization modes result in significantly altered half-lives of paralogous mRNAs. Side-by-side comparison of molecular principles underlying controlled protein and mRNA degradation in yeast unravels their remarkable mechanistic similarities and suggests how the intrinsic structural features of the two molecular species, at two different levels of the central dogma, regulate their half-lives on genome scale.

FMRP links optimal codons to mRNA stability in neurons

Fragile X syndrome (FXS) is caused by inactivation of the FMR1 gene and loss of encoded FMRP, an RNA binding protein that represses translation of some of its target transcripts. Here we use ribosome profiling and RNA sequencing to investigate the dysregulation of translation in the mouse brain cortex. We find that most changes in ribosome occupancy on hundreds of mRNAs are largely driven by dysregulation in transcript abundance. Many down-regulated mRNAs, which are mostly responsible for neuronal and synaptic functions, are highly enriched for FMRP binding targets. RNA metabolic labeling demonstrates that, in FMRP-deficient cortical neurons, mRNA down-regulation is caused by elevated degradation and is correlated with codon optimality. Moreover, FMRP preferentially binds mRNAs with optimal codons, suggesting that it stabilizes such transcripts through direct interactions via the translational machinery. Finally, we show that the paradigm of genetic rescue of FXS-like phenotypes in FMRP-deficient mice by deletion of the Cpeb1 gene is mediated by restoration of steady-state RNA levels and consequent rebalancing of translational homeostasis. Our data establish an essential role of FMRP in codon optimality-dependent mRNA stability as an important factor in FXS.

Global Profiling of Cellular Substrates of Human Dcp2

Decapping is the first committed step in 5'-to-3' RNA decay, and in the cytoplasm of human cells, multiple decapping enzymes regulate the stabilities of distinct subsets of cellular transcripts. However, the complete set of RNAs regulated by any individual decapping enzyme remains incompletely mapped, and no consensus sequence or property is currently known to unambiguously predict decapping enzyme substrates. Dcp2 was the first-identified and best-studied eukaryotic decapping enzyme, but it has been shown to regulate the stability of <400 transcripts in mammalian cells to date. Here, we globally profile changes in the stability of the human transcriptome in Dcp2 knockout cells via TimeLapse-seq. We find that P-body enrichment is the strongest correlate of Dcp2-dependent decay and that modification with m⁶A exhibits an additive effect with P-body enrichment for Dcp2 targeting. These results are consistent with a model in which P-bodies represent sites where translationally repressed transcripts are sorted for decay by soluble cytoplasmic decay complexes through additional molecular marks.

Comparison of RNA isolation methods on RNA-Seq: implications for differential expression and meta-analyses

BACKGROUND

The increasing number of transcriptomic datasets has allowed for meta-analyses, which can be valuable due to their increased statistical power. However, meta-analyses can be confounded by so-called "batch effects," where technical variation across different batches of RNA-seq experiments can clearly produce spurious signals of differential expression and reduce our power to detect true differences. While batch effects can sometimes be accounted for, albeit with caveats, a better strategy is to understand their sources to better avoid them. In this study, we examined the effects of RNA isolation method as a possible source of batch effects in RNA-seq design.

RESULTS

Based on the different chemistries of "classic" hot phenol extraction of RNA compared to common commercial RNA isolation kits, we hypothesized that specific mRNAs may be preferentially extracted depending upon method, which could masquerade as differential expression in downstream RNA-seq analyses. We tested this hypothesis using the Saccharomyces cerevisiae heat shock response as a well-validated environmental response. Comparing technical replicates that only differed in RNA isolation method, we found over one thousand transcripts that appeared "differentially" expressed when comparing hot phenol extraction with the two kits. Strikingly, transcripts with higher abundance in the phenol-extracted samples were enriched for membrane proteins, suggesting that indeed the chemistry of hot phenol extraction better solubilizes those species of mRNA.

CONCLUSIONS

Within a self-contained experimental batch (e.g. control versus treatment), the method of RNA isolation had little effect on the ability to identify differentially expressed transcripts. However, we suggest that researchers performing meta-analyses across different experimental batches strongly consider the RNA isolation methods for each experiment.

Simultaneous Measurement of Transcriptional and Post-transcriptional Parameters by 3' End RNA-Seq

Cellular RNA levels are determined by transcription and decay rates, which are fundamental in understanding gene expression regulation. Measurement of these two parameters is usually performed independently, complicating analysis as well as introducing methodological biases and batch effects that hamper direct comparison. Here, we present a simple approach of concurrent sequencing of S. cerevisiae poly(A)⁺ and poly(A)^- RNA 3' ends to simultaneously estimate total RNA levels, transcription, and decay rates from the same RNA sample. The transcription data generated correlate well with reported estimates and also reveal local RNA polymerase stalling and termination sites with high precision. Although the method by design uses brief metabolic labeling of newly synthesized RNA with 4-thiouracil, the results demonstrate that transcription estimates can also be gained from unlabeled RNA samples. These findings underscore the potential of the approach, which should be generally applicable to study a range of biological questions in diverse organisms.

Global Identification of Human Exosome Substrates Using RNA Interference and RNA Sequencing

The RNA exosome is involved in RNA processing and quality control. In humans, it consists of an enzymatically inactive nine-subunit core, with ribonucleolytic activity contributed by one or two additional components. Moreover, several protein cofactors interact with the exosome to enable and specify its recruitment to a wide range of substrates. A common strategy to identify these substrates has been to deplete an exosome subunit or a cofactor and subsequently interrogate which transcripts become stabilized. Here, we describe an experimental pipeline including siRNA-mediated depletion of the RNA exosome or its cofactors in HeLa cells, confirmation of the knockdown efficiencies, and the manual or high-throughput identification of exosome targets.

Homeostasis in the Central Dogma of molecular biology: the importance of mRNA instability

Cell survival requires the control of biomolecule concentration, i.e. biomolecules should approach homeostasis. With information-carrying macromolecules, the particular concentration variation ranges depend on each type: DNA is not buffered, but mRNA and protein concentrations are homeostatically controlled, which leads to the ribostasis and proteostasis concepts. In recent years, we have studied the particular features of mRNA ribostasis and proteostasis in the model organism S. cerevisiae. Here we extend this study by comparing published data from three other model organisms: E. coli, S. pombe and cultured human cells. We describe how mRNA ribostasis is less strict than proteostasis. A constant ratio appears between the average decay and dilution rates during cell growth for mRNA, but not for proteins. We postulate that this is due to a trade-off between the cost of synthesis and the response capacity. This compromise takes place at the transcription level, but is not possible at the translation level as the high stability of proteins, versus that of mRNAs, precludes it. We hypothesize that the middle-place role of mRNA in the Central Dogma of Molecular Biology and its chemical instability make it more suitable than proteins for the fast changes needed for gene regulation.

Global analyses of the dynamics of mammalian microRNA metabolism

Rates of production and degradation together specify microRNA (miRNA) abundance and dynamics. Here, we used approach-to-steady-state metabolic labeling to assess these rates for 176 miRNAs in contact-inhibited mouse embryonic fibroblasts (MEFs), 182 miRNAs in dividing MEFs, and 127 miRNAs in mouse embryonic stem cells (mESCs). MicroRNA duplexes, each comprising a mature miRNA and its passenger strand, are produced at rates as fast as 110 ± 50 copies/cell/min, which exceeds rates reported for any mRNAs. These duplexes are rapidly loaded into Argonaute, with <30 min typically required for duplex loading and silencing-complex maturation. Within Argonaute, guide strands have stabilities that vary by 100-fold. Half-lives also vary globally between cell lines, with median values ranging from 11 to 34 h in mESCs and contact-inhibited MEFs, respectively. Moreover, relative half-lives for individual miRNAs vary between cell types, implying the influence of cell-specific factors in dictating turnover rate. The apparent influence of miRNA regions most important for targeting, together with the effect of one target on miR-7 accumulation, suggest that targets fulfill this role. Analysis of the tailing and trimming of miRNA 3' termini showed that the flux was typically greatest through the isoform tailed with a single uridine, although changes in this flux did not correspond to changes in stability, which suggested that the processes of tailing and trimming might be independent from that of decay. Together, these results establish a framework for describing the dynamics and regulation of miRNAs throughout their life cycle.

Codon stabilization coefficient as a metric to gain insights into mRNA stability and codon bias and their relationships with translation

The codon stabilization coefficient (CSC) is derived from the correlation between each codon frequency in transcripts and mRNA half-life experimental data. In this work, we used this metric as a reference to compare previously published Saccharomyces cerevisiae mRNA half-life datasets and investigate how codon composition related to protein levels. We generated CSCs derived from nine studies. Four datasets produced similar CSCs, which also correlated with other independent parameters that reflected codon optimality, such as the tRNA abundance and ribosome residence time. By calculating the average CSC for each gene, we found that most mRNAs tended to have more non-optimal codons. Conversely, a high proportion of optimal codons was found for genes coding highly abundant proteins, including proteins that were only transiently overexpressed in response to stress conditions. We also used CSCs to identify and locate mRNA regions enriched in non-optimal codons. We found that these stretches were usually located close to the initiation codon and were sufficient to slow ribosome movement. However, in contrast to observations from reporter systems, we found no position-dependent effect on the mRNA half-life. These analyses underscore the value of CSCs in studies of mRNA stability and codon bias and their relationships with protein expression.

Condition-Specific Modeling of Biophysical Parameters Advances Inference of Regulatory Networks

Large-scale inference of eukaryotic transcription-regulatory networks remains challenging. One underlying reason is that existing algorithms typically ignore crucial regulatory mechanisms, such as RNA degradation and post-transcriptional processing. Here, we describe InfereCLaDR, which incorporates such elements and advances prediction in Saccharomyces cerevisiae. First, InfereCLaDR employs a high-quality Gold Standard dataset that we use separately as prior information and for model validation. Second, InfereCLaDR explicitly models transcription factor activity and RNA half-lives. Third, it introduces expression subspaces to derive condition-responsive regulatory networks for every gene. InfereCLaDR’s final network is validated by known data and trends and results in multiple insights. For example, it predicts long half-lives for transcripts of the nucleic acid metabolism genes and members of the cytosolic chaperonin complex as targets of the proteasome regulator Rpn4p. InfereCLaDR demonstrates that more biophysically realistic modeling of regulatory networks advances prediction accuracy both in eukaryotes and prokaryotes.

Methods for the analysis of transcriptome dynamics

The transcriptome is the complete set of transcripts in a cell or tissue and includes ribosomal RNA (rRNA), messenger RNA (mRNA), transfer RNA (tRNA), and regulatory noncoding RNA. At steady-state, the transcriptome results from a compensatory variation of the transcription and decay rate to maintain the RNA concentration constant. RNA transcription constitutes the first stage in gene expression, and thus is a major and primary mode of gene expression control. Nevertheless, regulation of RNA decay is also a key factor in gene expression control, involving either selective RNA stabilization or enhanced degradation. Transcriptome analysis allows the identification of gene expression alterations, providing new insights regarding the pathways and mechanisms involved in physiological and pathological processes. Upon perturbation of cell homeostasis, rapid changes in gene expression are required to adapt to new conditions. Thus, to better understand the regulatory mechanisms associated with gene expression alterations, it is vital to acknowledge the relative contribution of RNA synthesis and decay to the transcriptome. To the toxicology field, the study of gene expression regulation mechanisms can help identify the early and mechanistic relevant cellular events associated with a particular response. This review aims to provide a critical comparison of the available methods used to analyze the contribution of RNA transcription and decay to gene expression dynamics. Notwithstanding, an integration of the data obtained is necessary to understand the entire repercussions of gene transcription changes at a system-level. Thus, a brief overview of the methods available for the integration and analysis of the data obtained from transcriptome analysis will also be provided.

Measuring RNA polymerase activity genome-wide with high-resolution run-on-based methods

The biogenesis of RNAs is a multi-layered and highly regulated process that involves a diverse set of players acting in an orchestrated manner throughout the transcription cycle. Transcription initiation, elongation and termination factors act on RNA polymerases to modulate their movement along the DNA template in a very precise manner, more complex than previously anticipated. Genome-scale run-on-based methodologies have been developed to study in detail the position of transcriptionally-engaged RNA polymerases. Genomic run-on (GRO), and its many variants and refinements made over the years, are helping the community to address an increasing amount of scientific questions, spanning an increasing range of organisms and systems. In this review, we aim to summarize the most relevant high throughput methodologies developed to study nascent RNA by run-on methods, compare their main features, advantages and limitations, while putting them in context with alternative ways of studying the transcriptional process.

Preparation of RNA 3' End Sequencing Libraries of Total and 4-thiouracil Labeled RNA for Simultaneous Measurement of Transcription, RNA Synthesis and Decay in S. cerevisiae

Cellular RNA levels are determined by the rates of RNA transcription from the gene template and subsequent RNA stability. Knowledge about both transcription and RNA decay is, therefore, necessary to interpret RNA levels and gene expression, especially during cellular processes where these parameters change. Numerous experimental strategies have been developed to measure transcription and RNA decay rates. However, to our knowledge, none of those techniques can simultaneously interrogate transcription and RNA decay. The presented protocol allows this and provides a simple approach to simultaneously estimate total RNA levels, transcription and decay rates from the same RNA sample. It is based on brief metabolic labeling of RNA and subsequent concurrent sequencing of polyA⁺ and polyA^- RNA 3' ends. The protocol was developed in S. cerevisiae and should be broadly applicable.

Global analysis of RNA metabolism using bio-orthogonal labeling coupled with next-generation RNA sequencing

Many open questions in RNA biology relate to the kinetics of gene expression and the impact of RNA binding regulatory factors on processing or decay rates of particular transcripts. Steady state measurements of RNA abundance obtained from RNA-seq approaches are not able to separate the effects of transcription from those of RNA decay in the overall abundance of any given transcript, instead only giving information on the (presumed steady-state) abundances of transcripts. Through the combination of metabolic labeling and high-throughput sequencing, several groups have been able to measure both transcription rates and decay rates of the entire transcriptome of an organism in a single experiment. This review focuses on the methodology used to specifically measure RNA decay at a global level. By comparing and contrasting approaches and describing the experimental protocols in a modular manner, we intend to provide both experienced and new researchers to the field the ability to combine aspects of various protocols to fit the unique needs of biological questions not addressed by current methods.

Gaining insight into transcriptome-wide RNA population dynamics through the chemistry of 4-thiouridine

Cellular RNA levels are the result of a juggling act between RNA transcription, processing, and degradation. By tuning one or more of these parameters, cells can rapidly alter the available pool of transcripts in response to stimuli. While RNA sequencing (RNA-seq) is a vital method to quantify RNA levels genome-wide, it is unable to capture the dynamics of different RNA populations at steady-state or distinguish between different mechanisms that induce changes to the steady-state (i.e., altered rate of transcription vs. degradation). The dynamics of different RNA populations can be studied by targeted incorporation of noncanonical nucleosides. 4-Thiouridine (s⁴ U) is a commonly used and versatile RNA metabolic label that allows the study of many properties of RNA metabolism from synthesis to degradation. Numerous experimental strategies have been developed that leverage the power of s⁴ U to label newly transcribed RNA in whole cells, followed by enrichment with activated disulfides or chemistry to induce C mutations at sites of s⁴ U during sequencing. This review presents existing methods to study RNA population dynamics genome-wide using s⁴ U metabolic labeling, as well as a discussion of considerations and challenges when designing s⁴ U metabolic labeling experiments. This article is categorized under: RNA Methods > RNA Analyses in Cells RNA Turnover and Surveillance > Regulation of RNA Stability.

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.

Non-invasive measurement of mRNA decay reveals translation initiation as the major determinant of mRNA stability

The cytoplasmic abundance of mRNAs is strictly controlled through a balance of production and degradation. Whereas the control of mRNA synthesis through transcription has been well characterized, less is known about the regulation of mRNA turnover, and a consensus model explaining the wide variations in mRNA decay rates remains elusive. Here, we combine non-invasive transcriptome-wide mRNA production and stability measurements with selective and acute perturbations to demonstrate that mRNA degradation is tightly coupled to the regulation of translation, and that a competition between translation initiation and mRNA decay -but not codon optimality or elongation- is the major determinant of mRNA stability in yeast. Our refined measurements also reveal a remarkably dynamic transcriptome with an average mRNA half-life of only 4.8 min - much shorter than previously thought. Furthermore, global mRNA destabilization by inhibition of translation initiation induces a dose-dependent formation of processing bodies in which mRNAs can decay over time.