Contributions of regulated transcription and mRNA decay to the dynamics of gene expression

Enhancing Transcriptome Mapping with Rapid PRO-seq Profiling of Nascent RNA

Precision nuclear run-on (PRO) sequencing (PRO-seq) is a powerful technique for mapping polymerase active sites with nucleotide resolution and measuring newly synthesized transcripts at both promoters and enhancer elements. The current PRO-seq protocol is time-intensive, technically challenging, and requires a large amount of starting material. To overcome these limitations, we developed rapid PRO-seq (rPRO-seq) which utilizes pre-adenylated single-stranded DNAs (AppDNA), a dimer blocking oligonucleotide (DBO), on-bead 5' RNA end repair, and column-based purification. These modifications enabled efficient transcriptome mapping within a single day (∼12 hours) increasing ligation efficiency, abolished adapter dimers, and reduced sample loss and RNA degradation. We demonstrate the reproducibility of rPRO-seq in measuring polymerases at promoters, gene bodies, and enhancers as compared to original PRO-seq protocols. Additionally, rPRO-seq is scalable, allowing for transcriptome mapping with as little as 25,000 cells. We apply rPRO-seq to study the role of Integrator in mouse hematopoietic stem and progenitor cell (mHSPC) homeostasis, identifying Ints11 as an essential component of transcriptional regulation and RNA processing in mHSPC homeostasis. Overall, rPRO-seq represents a significant advance in the field of nascent transcript analyses and will be a valuable tool for generating patient-specific genome-wide transcription profiles with minimal sample requirements.

Coordination of rhythmic RNA synthesis and degradation orchestrates 24- and 12-h RNA expression patterns in mouse fibroblasts

Circadian RNA expression is essential to ultimately regulate a plethora of downstream rhythmic biochemical, physiological, and behavioral processes. Both transcriptional and posttranscriptional mechanisms are considered important to drive rhythmic RNA expression; however, the extent to which each regulatory process contributes to the rhythmic RNA expression remains controversial. To systematically address this, we monitored RNA dynamics using metabolic RNA labeling technology during a circadian cycle in mouse fibroblasts. We find that rhythmic RNA synthesis is the primary contributor of 24-h RNA rhythms, while rhythmic degradation is more important for 12-h RNA rhythms. These rhythms were predominantly regulated by Bmal1 and/or the core clock mechanism, and the interplay between rhythmic synthesis and degradation has a significant impact in shaping rhythmic RNA expression patterns. Interestingly, core clock RNAs are regulated by multiple rhythmic processes and have the highest amplitude of synthesis and degradation, presumably critical to sustain robust rhythmicity of cell-autonomous circadian rhythms. Our study yields invaluable insights into the temporal dynamics of both 24- and 12-h RNA rhythms in mouse fibroblasts.

smFISH for Plants

Single-molecule fluorescence in situ hybridization (smFISH) is a powerful method for the visualization and quantification of individual RNA molecules within intact cells. With its ability to probe gene expression at the single cell and single-molecule level, the technique offers valuable insights into cellular processes and cell-to-cell heterogeneity. Although widely used in the animal field, its use in plants has been limited. Here, we present an experimental smFISH workflow that allows researchers to overcome hybridization and imaging challenges in plants, including sample preparation, probe hybridization, and signal detection. Overall, this protocol holds great promise for unraveling the intricacies of gene expression regulation and RNA dynamics at the single-molecule level in whole plants.

Enhancers associated with unstable RNAs are rare in plants

Unstable transcripts have emerged as markers of active enhancers in vertebrates and shown to be involved in many cellular processes and medical disorders. However, their prevalence and role in plants is largely unexplored. Here, we comprehensively captured all actively initiating ("nascent") transcripts across diverse crops and other plants using capped small (cs)RNA-seq. We discovered that unstable transcripts are rare, unlike in vertebrates, and often originate from promoters. Additionally, many "distal" elements in plants initiate tissue-specific stable transcripts and are likely bone fide promoters of yet-unannotated genes or non-coding RNAs, cautioning against using genome annotations to infer "enhancers" or transcript stability. To investigate enhancer function, we integrated STARR-seq data. We found that annotated promoters, and other regions that initiate stable transcripts rather than unstable transcripts, function as stronger enhancers in plants. Our findings underscore the blurred line between promoters and enhancers and suggest that cis-regulatory elements encompass diverse structures and mechanisms in eukaryotes.

Regulation of angiotensin-converting enzyme 2 isoforms by type 2 inflammation and viral infection in human airway epithelium

SARS-CoV-2 enters human cells through its main receptor, angiotensin-converting enzyme 2 (ACE2), which constitutes a limiting factor of infection. Recent findings demonstrating novel ACE2 isoforms implicate that this receptor is regulated in a more complex way than previously anticipated. However, it remains unknown how various inflammatory conditions influence the abundance of these ACE2 variants. Hence, we studied expression of ACE2 messenger RNA (mRNA) and protein isoforms, together with its glycosylation and spatial localization in primary human airway epithelium upon allergic inflammation and viral infection. We found that interleukin-13, the main type 2 cytokine, decreased expression of long ACE2 mRNA and reduced glycosylation of full-length ACE2 protein via alteration of N-linked glycosylation process, limiting its availability on the apical side of ciliated cells. House dust mite allergen did not affect the expression of ACE2. Rhinovirus infection increased short ACE2 mRNA, but it did not influence its protein expression. In addition, by screening other SARS-CoV-2 related host molecules, we found that interleukin-13 and rhinovirus significantly regulated mRNA, but not protein of transmembrane serine protease 2 and neuropilin 1. Regulation of ACE2 and other host proteins was comparable in healthy and asthmatic epithelium, underlining the lack of intrinsic differences but dependence on the inflammatory milieu in the airways.

Progression of the pluripotent epiblast depends upon the NMD factor UPF2

Nonsense-mediated RNA decay (NMD) is a highly conserved RNA turnover pathway that degrades RNAs harboring in-frame stop codons in specific contexts. Loss of NMD factors leads to embryonic lethality in organisms spanning the phylogenetic scale, but the mechanism remains unknown. Here, we report that the core NMD factor, UPF2, is required for expansion of epiblast cells within the inner cell mass of mice in vivo. We identify NMD target mRNAs in mouse blastocysts - both canonical and alternatively processed mRNAs - including those encoding cell cycle arrest and apoptosis factors, raising the possibility that NMD is essential for embryonic cell proliferation and survival. In support, the inner cell mass of Upf2-null blastocysts rapidly regresses with outgrowth and is incompetent for embryonic stem cell derivation in vitro. In addition, we uncovered concordant temporal- and lineage-specific regulation of NMD factors and mRNA targets, indicative of a shift in NMD magnitude during peri-implantation development. Together, our results reveal developmental and molecular functions of the NMD pathway in the early embryo.

Regulation of both transcription and RNA turnover contribute to germline specification

The nuanced mechanisms driving primordial germ cells (PGC) specification remain incompletely understood since genome-wide transcriptional regulation in developing PGCs has previously only been defined indirectly. Here, using SLAMseq analysis, we determined genome-wide transcription rates during the differentiation of embryonic stem cells (ESCs) to form epiblast-like (EpiLC) cells and ultimately PGC-like cells (PGCLCs). This revealed thousands of genes undergoing bursts of transcriptional induction and rapid shut-off not detectable by RNAseq analysis. Our SLAMseq datasets also allowed us to infer RNA turnover rates, which revealed thousands of mRNAs stabilized and destabilized during PGCLC specification. mRNAs tend to be unstable in ESCs and then are progressively stabilized as they differentiate. For some classes of genes, mRNA turnover regulation collaborates with transcriptional regulation, but these processes oppose each other in a surprisingly high frequency of genes. To test whether regulated mRNA turnover has a physiological role in PGC development, we examined three genes that we found were regulated by RNA turnover: Sox2, Klf2 and Ccne1. Circumvention of their regulated RNA turnover severely impaired the ESC-to-EpiLC and EpiLC-to-PGCLC transitions. Our study demonstrates the functional importance of regulated RNA stability in germline development and provides a roadmap of transcriptional and post-transcriptional regulation during germline specification.

StaRTrEK:in silico estimation of RNA half-lives from genome-wide time-course experiments without transcriptional inhibition

Background

Gene expression is the result of the balance between transcription and degradation. Recent experimental findings have shown fine and specific regulation of RNA degradation and the presence of various molecular machinery purposely devoted to this task, such as RNA binding proteins, non-coding RNAs, etc. A biological process can be studied by measuring time-courses of RNA abundance in response of internal and/or external stimuli, using recent technologies, such as the microarrays or the Next Generation Sequencing devices. Unfortunately, the picture provided by looking only at the transcriptome abundance may not gain insight into its dynamic regulation. By contrast, independent simultaneous measurement of RNA expression and half-lives could provide such valuable additional insight. A computational approach to the estimation of RNAs half-lives from RNA expression time profiles data, can be a low-cost alternative to its experimental measurement which may be also affected by various artifacts.

Results

Here we present a computational methodology, called StaRTrEK (STAbility Rates ThRough Expression Kinetics), able to estimate half-life values basing only on genome-wide gene expression time series without transcriptional inhibition. The StaRTrEK algorithm makes use of a simple first order kinetic model and of a \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$l_1$$\end{document}l1-norm regularized least square optimization approach to find its parameter values. Estimates provided by StaRTrEK are validated using simulated data and three independent experimental datasets of two short (6 samples) and one long (48 samples) time-courses.

Conclusions

We believe that our algorithm can be used as a fast valuable computational complement to time-course experimental gene expression studies by adding a relevant kinetic property, i.e. the RNA half-life, with a strong biological interpretation, thus providing a dynamic picture of what is going in a cell during the biological process under study.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12859-022-04730-x.

Long noncoding RNA and phase separation in cellular stress response

Stress response is important for sensing and adapting to environmental changes. Recently, RNA-protein condensates, which are a type of membrane-less organelle formed by liquid-liquid phase separation, have been proposed to regulate the stress response. Because RNA-protein condensates are formed through interactions between positively charged proteins and negatively charged RNAs, the ratio of proteins to RNAs is critical for phase-separated condensate formation. In particular, long noncoding RNAs (lncRNAs) can efficiently nucleate phase-separated RNA-protein condensates because of their secondary structure and long length. Therefore, increased attention has been paid to lncRNAs because of their potential role as a regulator of biological condensates by phase separation under stress response. In this review, we summarize the current research on the involvement of lncRNAs in the formation of RNA-protein condensates under stress response. We also demonstrate that lncRNA-driven phase separation provides a useful basis to understanding the response to several kinds of cellular stresses.

Analysis of mRNA Dynamics Using RNA Sequencing Data

The RNA abundance of each gene is determined by its rates of transcription and RNA decay. Biochemical experiments that measure these rates, including transcription inhibition and metabolic labelling, are challenging to perform and are largely limited to in vitro settings. Most transcriptomic studies have focused on analyzing changes in RNA abundances without attributing those changes to transcriptional or posttranscriptional regulation. Estimating differential transcription and decay rates of RNA molecules would enable the identification of regulatory factors, such as transcription factors, RNA binding proteins, and microRNAs, that govern large-scale shifts in RNA expression. Here, we describe a protocol for estimating differential stability of RNA molecules between conditions using standard RNA-sequencing data, without the need for transcription inhibition or metabolic labeling. We apply this protocol to in vivo RNA-seq data from individuals with Alzheimer's disease and demonstrate how estimates of differential stability can be leveraged to infer the regulatory factors underlying them.

Differential regulation of mRNA fate by the human Ccr4-Not complex is driven by coding sequence composition and mRNA localization

BACKGROUND

Regulation of protein output at the level of translation allows for a rapid adaptation to dynamic changes to the cell's requirements. This precise control of gene expression is achieved by complex and interlinked biochemical processes that modulate both the protein synthesis rate and stability of each individual mRNA. A major factor coordinating this regulation is the Ccr4-Not complex. Despite playing a role in most stages of the mRNA life cycle, no attempt has been made to take a global integrated view of how the Ccr4-Not complex affects gene expression.

RESULTS

This study has taken a comprehensive approach to investigate post-transcriptional regulation mediated by the Ccr4-Not complex assessing steady-state mRNA levels, ribosome position, mRNA stability, and protein production transcriptome-wide. Depletion of the scaffold protein CNOT1 results in a global upregulation of mRNA stability and the preferential stabilization of mRNAs enriched for G/C-ending codons. We also uncover that mRNAs targeted to the ER for their translation have reduced translational efficiency when CNOT1 is depleted, specifically downstream of the signal sequence cleavage site. In contrast, translationally upregulated mRNAs are normally localized in p-bodies, contain disorder-promoting amino acids, and encode nuclear localized proteins. Finally, we identify ribosome pause sites that are resolved or induced by the depletion of CNOT1.

CONCLUSIONS

We define the key mRNA features that determine how the human Ccr4-Not complex differentially regulates mRNA fate and protein synthesis through a mechanism linked to codon composition, amino acid usage, and mRNA localization.

A model explaining mRNA level fluctuations based on activity demands and RNA age

Cellular RNA levels typically fluctuate and are influenced by different transcription rates and RNA degradation rates. However, the understanding of the fundamental relationships between RNA abundance, environmental stimuli, RNA activities, and RNA age distributions is incomplete. Furthermore, the rates of RNA degradation and transcription are difficult to measure in transcriptomic experiments in living organisms, especially in studies involving humans. A model based on activity demands and RNA age was developed to explore the mechanisms of RNA level fluctuations. Using single-cell time-series gene expression experimental data, we assessed the transcription rates, RNA degradation rates, RNA life spans, RNA demand, accumulated transcription levels, and accumulated RNA degradation levels. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge.

Detected cellular RNA levels usually fluctuate. The understanding of the fundamental relationships between RNA level fluctuations, the rates of RNA degradation and transcription, environmental stimuli, RNA activities, and RNA age distributions is incomplete. In the present research, we developed a model based on the demands of RNA (related to intrinsic and/or extrinsic information), RNA age (determines the survival time and biological activity of an RNA), transcription, and RNA degradation to explain the mechanism underlying intracellular RNA level fluctuations. We also explored applicability of the model for analysing dynamic processes between interacting biomolecules, such as the relationship between RNA and protein level fluctuations. Using single-cell time-series gene expression experimental data, we assessed some biological parameters, such as transcription rates, RNA degradation rates, and RNA life spans. This model could also predict RNA levels under simulation backgrounds, such as stimuli that induce regular oscillations in RNA abundance, stable RNA levels over time that result from long-term shortage of total RNA activity or from uncontrollable transcription, and relationships between RNA/protein levels and metabolic rates. This information contributes to existing knowledge and provides a new perspective for future studies.

Systematic Analysis of Targets of Pumilio-Mediated mRNA Decay Reveals that PUM1 Repression by DNA Damage Activates Translesion Synthesis

RNA-binding proteins (RBPs) play a pivotal role in gene expression by modulating the stability of transcripts. However, the identification of degradation target mRNAs of RBPs remains difficult. By the combined analysis of transcriptome-wide mRNA stabilities and the binding of mRNAs to human Pumilio 1 (PUM1), we identify 48 mRNAs that both bind to PUM1 and exhibit PUM1-dependent degradation. Analysis of changes in the abundance of PUM1 and its degradation target mRNAs in RNA-seq data indicate that DNA-damaging agents negatively regulate PUM1-mediated mRNA decay. Cells exposed to cisplatin have reduced PUM1 abundance and increased PCNA and UBE2A mRNAs encoding proteins involved in DNA damage tolerance by translesion synthesis (TLS). Cells overexpressing PUM1 exhibit impaired DNA synthesis and TLS and increased sensitivity to the cytotoxic effect of cisplatin. Thus, our method identifies target mRNAs of PUM1-mediated decay and reveals that cells respond to DNA damage by inhibiting PUM1-mediated mRNA decay to activate TLS.

An integrative approach uncovers transcriptome-wide determinants of mRNA stability regulation in Saccharomyces cerevisiae

mRNA degradation rate is one of the key stages of gene expression regulation in eukaryotic cells. To date, intertwined processes of post-transcriptional control have been widely investigated, but focused rather on the examination of mechanisms controlling stability of particular protein-coding transcripts. Currently, a wealth of information from structural, biochemical, and high-throughput studies makes it tempting to define general rules governing mRNA stability that could be considered as versatile and valid on a genome-wide scale. Basu et al. analyzed multiple experimental and computational data on Saccharomyces cerevisiae mRNA half-lives as well as on secondary structures and protein-binding sites within transcripts, and collated it with available structures of ribonucleases, that is, enzymes responsible for mRNA degradation. This approach allowed to conclude how particular mRNA features such as lengths of unstructured terminal or internal regions or sequestration into ribonucleoprotein complexes impact half-lives of protein-coding transcripts and to define genome-scale principles of mRNA stability control in yeast.

Loss of the fragile X syndrome protein FMRP results in misregulation of nonsense-mediated mRNA decay

Loss of the fragile X protein FMRP is a leading cause of intellectual disability and autism^1,2, but the underlying mechanism remains poorly understood. We report that FMRP deficiency results in hyperactivated nonsense-mediated mRNA decay (NMD)^3,4 in human SH-SY5Y neuroblastoma cells and fragile X syndrome (FXS) fibroblast-derived induced pluripotent stem cells (iPSCs). We examined the underlying mechanism and found that the key NMD factor UPF1 binds directly to FMRP, promoting FMRP binding to NMD targets. Our data indicate that FMRP acts as an NMD repressor. In the absence of FMRP, NMD targets are relieved from FMRP-mediated translational repression so that their half-lives are decreased and, for those NMD targets encoding NMD factors, increased translation produces abnormally high factor levels despite their hyperactivated NMD. Transcriptome-wide alterations caused by NMD hyperactivation have a role in the FXS phenotype. Consistent with this, small-molecule-mediated inhibition of hyperactivated NMD, which typifies iPSCs derived from patients with FXS, restores a number of neurodifferentiation markers, including those not deriving from NMD targets. Our mechanistic studies reveal that many molecular abnormalities in FMRP-deficient cells are attributable-either directly or indirectly-to misregulated NMD.

Dynamic global analysis of transcription reveals the role of miRNAs in synergistic stabilization of gene expression

Buffering exogenous perturbation is crucial to maintain transcriptional homeostasis during development. While miRNAs have been speculated to play a role in stability maintenance, previous studies seeking to check this conjecture focused on measurements of transcript levels at steady state or involved individual miRNA targets. We measured whole-genome expression dynamics by introducing a transient perturbation and establishing a perturbation and recovery system in Drosophila larvae. We inhibited all transcription and assayed transcriptomes at several time points during recovery from inhibition. We performed these experiments in the wild type and miRNA-deficient genetic backgrounds. Consistent with theories about miRNAs' function in stabilizing the transcriptome, we find that attenuating miRNA expression leads to weak impairment in degradation of targets but strong destabilization of target genes when transcription is re-activated. We further fitted a model that captures the essential aspects of transcription dynamics in our experiments and found that the miRNA target transcripts uniformly overshoot the original steady state as they recover from a general inhibition of transcription if global miRNA levels are reduced. Collectively, our results provide experimental evidence for the idea that miRNAs act cumulatively to stabilize the transcriptional regulatory network. We therefore found a promising approach to assess the effect of these molecules on transcription dynamics.

Covalent labeling of nucleic acids

Labeling of nucleic acids is required for many studies aiming to elucidate their functions and dynamics in vitro and in cells. Out of the numerous labeling concepts that have been devised, covalent labeling provides the most stable linkage, an unrivaled choice of small and highly fluorescent labels and - thanks to recent advances in click chemistry - an incredible versatility. Depending on the approach, site-, sequence- and cell-specificity can be achieved. DNA and RNA labeling are rapidly developing fields that bring together multiple areas of research: on the one hand, synthetic and biophysical chemists develop new fluorescent labels and isomorphic nucleobases as well as faster and more selective bioorthogonal reactions. On the other hand, the number of enzymes that can be harnessed for post-synthetic and site-specific labeling of nucleic acids has increased significantly. Together with protein engineering and genetic manipulation of cells, intracellular and cell-specific labeling has become possible. In this review, we provide a structured overview of covalent labeling approaches for nucleic acids and highlight notable developments, in particular recent examples. The majority of this review will focus on fluorescent labeling; however, the principles can often be readily applied to other labels. We will start with entirely chemical approaches, followed by chemo-enzymatic strategies and ribozymes, and finish with metabolic labeling of nucleic acids. Each section is subdivided into direct (or one-step) and two-step labeling approaches and will start with DNA before treating RNA.

The Making and Breaking of RNAs: Dynamics of Rhythmic RNA Expression in Mammals

The identification and characterization of rhythmically expressed mRNAs have been an active area of research over the past 20 years, as these mRNAs are believed to produce the daily rhythms in a wide range of biological processes. Circadian transcriptome studies have used mature mRNA as a primary readout and focused largely on rhythmic RNA synthesis as a regulatory mechanism underlying rhythmic mRNA expression. However, RNA synthesis, RNA degradation, or a combination of both must be rhythmic to drive rhythmic RNA profiles, and it is still unclear to what extent rhythmic synthesis leads to rhythmic RNA profiles. In addition, circadian RNA expression is also often tissue specific. Although a handful of genes cycle in all or most tissues, others are rhythmic only in certain tissues, even though the same core clock mechanism is believed to control the rhythmic RNA profiles in all tissues. This review focuses on the dynamics of rhythmic RNA synthesis and degradation and discusses how these steps collectively determine the rhythmicity, phase, and amplitude of RNA accumulation. In particular, we highlight a possible role of RNA degradation in driving tissue-specific RNA rhythms. By unifying findings from experimental and theoretical studies, we will provide a comprehensive overview of how rhythmic gene expression can be achieved and how each regulatory step contributes to tissue-specific circadian transcriptome output in mammals.

Rapid and Scalable Profiling of Nascent RNA with fastGRO

Genome-wide profiling of nascent RNA has become a fundamental tool to study transcription regulation. Unlike steady-state RNA-sequencing (RNA-seq), nascent RNA profiling mirrors real-time activity of RNA polymerases and provides an accurate readout of transcriptome-wide variations. Some species of nuclear RNAs (i.e., large intergenic noncoding RNAs [lincRNAs] and eRNAs) have a short half-life and can only be accurately gauged by nascent RNA techniques. Furthermore, nascent RNA-seq detects post-cleavage RNA at termination sites and promoter-associated antisense RNAs, providing insights into RNA polymerase II (RNAPII) dynamics and processivity. Here, we present a run-on assay with 4-thio ribonucleotide (4-S-UTP) labeling, followed by reversible biotinylation and affinity purification via streptavidin. Our protocol allows streamlined sample preparation within less than 3 days. We named the technique fastGRO (fast Global Run-On). We show that fastGRO is highly reproducible and yields a more complete and extensive coverage of nascent RNA than comparable techniques can. Importantly, we demonstrate that fastGRO is scalable and can be performed with as few as 0.5 × 10⁶ cells.

Barbieri et al. developed fastGRO, a nascent RNA-sequencing technique based on nuclear run-on. Using a streamlined, under-3-days protocol, fastGRO tracks the activity of RNA polymerase for differential gene expression analysis, polymerase kinetic studies, and profiling of lowly expressed and unstable RNA species. A low-input fastGRO protocol profiles nascent RNA in as little as 0.5 × 10⁶ cells.

Navigation through the twists and turns of RNA sequencing technologies: Application to bacterial regulatory RNAs

Discovered in the 1980s, small regulatory RNAs (sRNAs) are now considered key actors in virtually all aspects of bacterial physiology and virulence. Together with transcriptional and translational regulatory proteins, they integrate and often are hubs of complex regulatory networks, responsible for bacterial response/adaptation to various perceived stimuli. The recent development of powerful RNA sequencing technologies has facilitated the identification and characterization of sRNAs (length, structure and expression conditions) and their RNA targets in several bacteria. Nevertheless, it could be very difficult for non-experts to understand the advantages and drawbacks related to each offered option and, consequently, to make an informed choice. Therefore, the main goal of this review is to provide a guide to navigate through the twists and turns of high-throughput RNA sequencing technologies, with a specific focus on those applied to the study of sRNAs. This article is part of a Special Issue entitled: RNA and gene control in bacteria edited by Dr. M. Guillier and F. Repoila.

Chemo-enzymatic treatment of RNA to facilitate analyses

Labeling RNA is a recurring problem to make RNA compatible with state-of-the-art methodology and comes in many flavors. Considering only cellular applications, the spectrum still ranges from site-specific labeling of individual transcripts, for example, for live-cell imaging of mRNA trafficking, to metabolic labeling in combination with next generation sequencing to capture dynamic aspects of RNA metabolism on a transcriptome-wide scale. Combining the specificity of RNA-modifying enzymes with non-natural substrates has emerged as a valuable strategy to modify RNA site- or sequence-specifically with functional groups suitable for subsequent bioorthogonal reactions and thus label RNA with reporter moieties such as affinity or fluorescent tags. In this review article, we will cover chemo-enzymatic approaches (a) for in vitro labeling of RNA for application in cells, (b) for treatment of total RNA, and (c) for metabolic labeling of RNA. This article is categorized under: RNA Processing < RNA Editing and Modification RNA Methods < RNA Analyses in vitro and In Silico RNA Methods < RNA Analyses in Cells.

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.