4-thiouridine inhibits rRNA synthesis and causes a nucleolar stress response

Alterations of signaling pathways in response to chemical perturbations used to measure mRNA decay rates in yeast

Assessing variations in mRNA stability typically involves inhibiting transcription either globally or in a gene-specific manner. Alternatively, mRNA pulse-labeling strategies offer a means to calculate mRNA stability without inhibiting transcription. However, key stress-responsive cell signaling pathways, which affect mRNA stability, may themselves be perturbed by the approaches used to measure mRNA stability, leading to artifactual results. Here, we have focused on common strategies to measure mRNA half-lives in yeast and determined that commonly used transcription inhibitors thiolutin and 1,10 phenanthroline inhibit TORC1 signaling, PKC signaling, and partially activate HOG signaling. Additionally, 4-thiouracil (4tU), a uracil analog used in mRNA pulse-labeling approaches, modestly induces P-bodies, mRNA-protein granules implicated in storage and decay of nontranslating mRNA. Thiolutin also induces P-bodies, whereas phenanthroline has no effect. Doxycycline, which controls "Tet On/Tet Off" regulatable promoters, shows no impact on the above signaling pathways or P-bodies. In summary, our data argues that broad-acting transcriptional inhibitors are problematic for determining mRNA half-life, particularly if studying the impacts of the TORC1, HOG, or PKC pathway on mRNA stability. Regulatable promoter systems are a preferred approach for individual mRNA half-life studies, with 4tU labeling representing a good approach to global mRNA half-life analysis, despite modestly inducing P-bodies.

LYAR potentiates rRNA synthesis by recruiting BRD2/4 and the MYST-type acetyltransferase KAT7 to rDNA

Activation of ribosomal RNA (rRNA) synthesis is pivotal during cell growth and proliferation, but its aberrant upregulation may promote tumorigenesis. Here, we demonstrate that the candidate oncoprotein, LYAR, enhances ribosomal DNA (rDNA) transcription. Our data reveal that LYAR binds the histone-associated protein BRD2 without involvement of acetyl-lysine-binding bromodomains and recruits BRD2 to the rDNA promoter and transcribed regions via association with upstream binding factor. We show that BRD2 is required for the recruitment of the MYST-type acetyltransferase KAT7 to rDNA loci, resulting in enhanced local acetylation of histone H4. In addition, LYAR binds a complex of BRD4 and KAT7, which is then recruited to rDNA independently of the BRD2-KAT7 complex to accelerate the local acetylation of both H4 and H3. BRD2 also helps recruit BRD4 to rDNA. By contrast, LYAR has no effect on rDNA methylation or the binding of RNA polymerase I subunits to rDNA. These data suggest that LYAR promotes the association of the BRD2-KAT7 and BRD4-KAT7 complexes with transcription-competent rDNA loci but not to transcriptionally silent rDNA loci, thereby increasing rRNA synthesis by altering the local acetylation status of histone H3 and H4.

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.

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.

Sequencing cell-type-specific transcriptomes with SLAM-ITseq

Analysis of cell-type-specific transcriptomes is vital for understanding the biology of tissues and organs in the context of multicellular organisms. In this Protocol Extension, we combine a previously developed cell-type-specific metabolic RNA labeling method (thiouracil (TU) tagging) and a pipeline to detect the labeled transcripts by a novel RNA sequencing (RNA-seq) method, SLAMseq (thiol (SH)-linked alkylation for the metabolic sequencing of RNA). By injecting a uracil analog, 4-thiouracil, into transgenic mice that express cell-type-specific uracil phosphoribosyltransferase (UPRT), an enzyme required for 4-thiouracil incorporation into newly synthesized RNA, only cells expressing UPRT synthesize thiol-containing RNA. Total RNA isolated from a tissue of interest is then sequenced with SLAMseq, which introduces thymine to cytosine (T>C) conversions at the sites of the incorporated 4-thiouracil. The resulting sequencing reads are then mapped with the T>C-aware alignment software, SLAM-DUNK, which allows mapping of reads containing T>C mismatches. The number of T>C conversions per transcript is further analyzed to identify which transcripts are synthesized in the UPRT-expressing cells. Thus, our method, SLAM-ITseq (SLAMseq in tissue), enables cell-specific transcriptomics without laborious FACS-based cell sorting or biochemical isolation of the labeled transcripts used in TU tagging. In the murine tissues we assessed previously, this method identified ~5,000 genes that are expressed in a cell type of interest from the total RNA pool from the tissue. Any laboratory with access to a high-throughput sequencer and high-power computing can adapt this protocol with ease, and the entire pipeline can be completed in <5 d.

CLIPick: a sensitive peak caller for expression-based deconvolution of HITS-CLIP signals

High-throughput sequencing of RNAs isolated by crosslinking immunoprecipitation (HITS-CLIP, also called CLIP-Seq) has been used to map global RNA–protein interactions. However, a critical caveat of HITS-CLIP results is that they contain non-linear background noise—different extent of non-specific interactions caused by individual transcript abundance—that has been inconsiderately normalized, resulting in sacrifice of sensitivity. To properly deconvolute RNA–protein interactions, we have implemented CLIPick, a flexible peak calling pipeline for analyzing HITS-CLIP data, which statistically determines the signal-to-noise ratio for each transcript based on the expression-dependent background simulation. Comprising of streamlined Python modules with an easy-to-use standalone graphical user interface, CLIPick robustly identifies significant peaks and quantitatively defines footprint regions within which RNA–protein interactions were occurred. CLIPick outperforms other peak callers in accuracy and sensitivity, selecting the largest number of peaks particularly in lowly expressed transcripts where such marginal signals are hard to discriminate. Specifically, the application of CLIPick to Argonaute (Ago) HITS-CLIP data were sensitive enough to uncover extended features of microRNA target sites, and these sites were experimentally validated. CLIPick enables to resolve critical interactions in a wide spectrum of transcript levels and extends the scope of HITS-CLIP analysis. CLIPick is available at: http://clip.korea.ac.kr/clipick/

A Peptidylic Inhibitor for Neutralizing r(GGGGCC)exp-Associated Neurodegeneration in C9ALS-FTD

One drug, two diseases is a rare and economical therapeutic strategy that is highly desirable in the pharmaceutical industry. We previously reported a 21-amino acid peptide named beta-structured inhibitor for neurodegenerative diseases (BIND) that can effectively inhibit expanded CAG trinucleotide toxicity in polyglutamine (polyQ) diseases. Here we report that BIND also effectively inhibits GGGGCC repeat-mediated neurodegeneration in vitro and in vivo. When fused with a cell-penetrating peptide derived from the transactivator of transcription (TAT) protein of the HIV, TAT-BIND reduces cell death, formation of GGGGCC RNA foci, and levels of poly-GR, poly-GA, and poly-GP dipeptide proteins in cell models of C9ORF72-associated amyotrophic lateral sclerosis and frontotemporal dementia (C9ALS-FTD). We showed that TAT-BIND disrupts the interaction between GGGGCC RNA and nucleolin protein, restores rRNA maturation, and inhibits mislocalization of nucleolin and B23, which eventually suppresses nucleolar stress in C9ALS-FTD. In a Drosophila model of C9ALS-FTD, TAT-BIND suppresses retinal degeneration, rescues climbing ability, and extends the lifespan of flies. In contrast, TAT-BIND has no effect on UAS-poly-glycine-arginine (poly-GR)₁₀₀-expressing flies, which generate only poly-GR protein toxicity, indicating BIND ameliorates toxicity in C9ALS-FTD models via a _r(GGGGCC)_exp-dependent inhibitory mechanism. Our findings demonstrated that, apart from being a potential therapeutic for polyQ diseases, BIND is also a potent peptidylic inhibitor that suppresses expanded GGGGCC RNA-mediated neurodegeneration, highlighting its potential application in C9ALS-FTD treatment.

Computational approaches for the analysis of RNA-protein interactions: A primer for biologists

RNA-binding proteins (RBPs) play important roles in the control of gene expression and the coordination of different layers of post-transcriptional regulation. Interactions between certain RBPs and mRNA transcripts are notoriously difficult to predict, as any given protein-RNA interaction may rely not only on RNA sequence, but also on three-dimensional RNA structures, competitive inhibition from other RBPs, and input from cellular signaling pathways. Advanced and high-throughput technologies for the identification of RNA-protein interactions have come to the rescue, but the identification of binding sites and downstream functional effects of RBPs from the resulting data can be challenging. In this review, we discuss statistical inference and machine-learning approaches and tools relevant for the study of RBPs and the analysis of large-scale RNA-protein interaction datasets. This primer is intended for life scientists who are interested in incorporating these tools into their own research. We begin with the demystification of regression models, as used in the analysis of next-generation sequencing data, and progress to a discussion of Hidden Markov Models, which are of particular value in analyzing cross-linking followed by immunoprecipitation data. We then continue with examples of machine learning techniques, such as support vector machines and gradient tree boosting. We close with a brief discussion of current trends in the field, including deep learning architectures.

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.

Discovery of RNA-binding proteins and characterization of their dynamic responses by enhanced RNA interactome capture

Following the realization that eukaryotic RNA-binding proteomes are substantially larger than anticipated, we must now understand their detailed composition and dynamics. Methods such as RNA interactome capture (RIC) have begun to address this need. However, limitations of RIC have been reported. Here we describe enhanced RNA interactome capture (eRIC), a method based on the use of an LNA-modified capture probe, which yields numerous advantages including greater specificity and increased signal-to-noise ratios compared to existing methods. In Jurkat cells, eRIC reduces the rRNA and DNA contamination by >10-fold compared to RIC and increases the detection of RNA-binding proteins. Due to its low background, eRIC also empowers comparative analyses of changes of RNA-bound proteomes missed by RIC. For example, in cells treated with dimethyloxalylglycine, which inhibits RNA demethylases, eRIC identifies m6A-responsive RNA-binding proteins that escape RIC. eRIC will facilitate the unbiased characterization of RBP dynamics in response to biological and pharmacological cues.

RNA interactome capture allows the detailed investigation of RNA-bound proteomes. Here the authors describe enhanced RNA-interactome capture using LNA-modified probes for increased sensitivity and specificity.

The Future of Cross-Linking and Immunoprecipitation (CLIP)

To understand the assembly and functional outcomes of protein-RNA regulation, it is crucial to precisely identify the positions of such interactions. Cross-linking and immunoprecipitation (CLIP) serves this purpose by exploiting covalent protein-RNA cross-linking and RNA fragmentation, along with a series of stringent purification and quality control steps to prepare complementary DNA (cDNA) libraries for sequencing. Here we describe the core steps of CLIP, its primary variations, and the approaches to data analysis. We present the application of CLIP to studies of specific cell types in genetically engineered mice and discuss the mechanistic and physiologic insights that have already been gained from studies using CLIP. We conclude by discussing the future opportunities for CLIP, including studies of human postmortem tissues from disease patients and controls, RNA epigenetic modifications, and RNA structure. These and other applications of CLIP will continue to unravel fundamental gene regulatory mechanisms while providing important biologic and clinically relevant insights.

CLIP-related methodologies and their application to retrovirology

Virtually every step of HIV-1 replication and numerous cellular antiviral defense mechanisms are regulated by the binding of a viral or cellular RNA-binding protein (RBP) to distinct sequence or structural elements on HIV-1 RNAs. Until recently, these protein-RNA interactions were studied largely by in vitro binding assays complemented with genetics approaches. However, these methods are highly limited in the identification of the relevant targets of RBPs in physiologically relevant settings. Development of crosslinking-immunoprecipitation sequencing (CLIP) methodology has revolutionized the analysis of protein-nucleic acid complexes. CLIP combines immunoprecipitation of covalently crosslinked protein-RNA complexes with high-throughput sequencing, providing a global account of RNA sequences bound by a RBP of interest in cells (or virions) at near-nucleotide resolution. Numerous variants of the CLIP protocol have recently been developed, some with major improvements over the original. Herein, we briefly review these methodologies and give examples of how CLIP has been successfully applied to retrovirology research.

Plant Ribonomics: Proteins in Search of RNA Partners

Research into the regulation of gene expression underwent a shift from focusing on DNA-binding proteins as key transcriptional regulators to RNA-binding proteins (RBPs) that come into play once transcription has been initiated. RBPs orchestrate all RNA-processing steps in the cell. To obtain a global view of in vivo targets, the RNA complement associated with particular RBPs is determined via immunoprecipitation of the RBP and subsequent identification of bound RNAs via RNA-seq. Here, we describe technical advances in identifying RBP in vivo targets and their binding motifs. We provide an up-to-date view of targets of nucleocytoplasmic RBPs collected in arabidopsis. We also discuss current experimental limitations and provide an outlook on how the approaches may advance our understanding of post-transcriptional networks.

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

Upon activation, cells rapidly change their functional programs and, thereby, their gene expression profile. Massive changes in gene expression occur, for example, during cellular differentiation, morphogenesis, and functional stimulation (such as activation of immune cells), or after exposure to drugs and other factors from the local environment. Depending on the stimulus and cell type, these changes occur rapidly and at any possible level of gene regulation. Displaying all molecular processes of a responding cell to a certain type of stimulus/drug is one of the hardest tasks in molecular biology. Here, we describe a protocol that enables the simultaneous analysis of multiple layers of gene regulation. We compare, in particular, transcription factor binding (Chromatin-immunoprecipitation-sequencing (ChIP-seq)), de novo transcription (4-thiouridine-sequencing (4sU-seq)), mRNA processing, and turnover as well as translation (ribosome profiling). By combining these methods, it is possible to display a detailed and genome-wide course of action.

Sequencing newly transcribed RNA is especially recommended when analyzing rapidly adapting or changing systems, since this depicts the transcriptional activity of all genes during the time of 4sU exposure (irrespective of whether they are up- or downregulated). The combinatorial use of total RNA-seq and ribosome profiling additionally allows the calculation of RNA turnover and translation rates. Bioinformatic analysis of high-throughput sequencing results allows for many means for analysis and interpretation of the data. The generated data also enables tracking co-transcriptional and alternative splicing, just to mention a few possible outcomes.

The combined approach described here can be applied for different model organisms or cell types, including primary cells. Furthermore, we provide detailed protocols for each method used, including quality controls, and discuss potential problems and pitfalls.

Circadian clock-dependent and -independent posttranscriptional regulation underlies temporal mRNA accumulation in mouse liver

Rhythms in gene expression propelled by the circadian clock and environmental signals are ubiquitous across cells and tissues. In particular, in mouse tissues, thousands of transcripts show oscillations with a period of 24 hours. Keys question are how such rhythms propagate and eventually exert functions, but also how these are generated. Here, we developed a mathematical model based on total RNA-seq to classify genes according to the respective contributions of transcriptional and posttranscriptional regulation toward mRNA expression profiles. We found that about one-third of rhythmically accumulating mRNA are under posttranscriptional regulation. Such regulation is only partially dependent on the circadian clock, showing that systemic pathways and feeding patterns contribute important posttranscriptional control of gene expression in liver.

The mammalian circadian clock coordinates physiology with environmental cycles through the regulation of daily oscillations of gene expression. Thousands of transcripts exhibit rhythmic accumulations across mouse tissues, as determined by the balance of their synthesis and degradation. While diurnally rhythmic transcription regulation is well studied and often thought to be the main factor generating rhythmic mRNA accumulation, the extent of rhythmic posttranscriptional regulation is debated, and the kinetic parameters (e.g., half-lives), as well as the underlying regulators (e.g., mRNA-binding proteins) are relatively unexplored. Here, we developed a quantitative model for cyclic accumulations of pre-mRNA and mRNA from total RNA-seq data, and applied it to mouse liver. This allowed us to identify that about 20% of mRNA rhythms were driven by rhythmic mRNA degradation, and another 15% of mRNAs regulated by both rhythmic transcription and mRNA degradation. The method could also estimate mRNA half-lives and processing times in intact mouse liver. We then showed that, depending on mRNA half-life, rhythmic mRNA degradation can either amplify or tune phases of mRNA rhythms. By comparing mRNA rhythms in wild-type and Bmal1^−/− animals, we found that the rhythmic degradation of many transcripts did not depend on a functional BMAL1. Interestingly clock-dependent and -independent degradation rhythms peaked at distinct times of day. We further predicted mRNA-binding proteins (mRBPs) that were implicated in the posttranscriptional regulation of mRNAs, either through stabilizing or destabilizing activities. Together, our results demonstrate how posttranscriptional regulation temporally shapes rhythmic mRNA accumulation in mouse liver.

Uncovering cell type-specific complexities of gene expression and RNA metabolism by TU-tagging and EC-tagging

Cell type-specific transcription is a key determinant of cell fate and function. An ongoing challenge in biology is to develop robust and stringent biochemical methods to explore gene expression with cell type specificity. This challenge has become even greater as researchers attempt to apply high-throughput RNA analysis methods under in vivo conditions. TU-tagging and EC-tagging are in vivo biosynthetic RNA tagging techniques that allow spatial and temporal specificity in RNA purification. Spatial specificity is achieved through targeted expression of pyrimidine salvage enzymes (uracil phosphoribosyltransferase and cytosine deaminase) and temporal specificity is achieved by controlling exposure to bioorthogonal substrates of these enzymes (4-thiouracil and 5-ethynylcytosine). Tagged RNAs can be purified from total RNA extracted from an animal or tissue and used in transcriptome profiling analyses. In addition to identifying cell type-specific mRNA profiles, these techniques are applicable to noncoding RNAs and can be used to measure RNA transcription and decay. Potential applications of TU-tagging and EC-tagging also include fluorescent RNA imaging and selective definition of RNA-protein interactions. TU-tagging and EC-tagging hold great promise for supporting research at the intersection of RNA biology and developmental biology. This article is categorized under: Technologies > Analysis of the Transcriptome.

Metabolic Labeling of Newly Synthesized RNA with 4sU to in Parallel Assess RNA Transcription and Decay

The development of genome-wide RNA profiling technologies greatly facilitates the global analysis of gene expression. However, such technologies alone could not distinguish the contribution to cellular RNA abundance by transcription versus decay. To overcome such limitation, metabolic labeling of newly synthesized RNA with 4-thiouridine (4sU) combined with genome-wide RNA profiling was used to in parallel measure RNA transcription and decay. Here, we describe the detailed protocol for using metabolic labeling with 4sU to separate newly synthesized RNA from the preexisting RNA in mammalian cells.

Impact of Methods on the Measurement of mRNA Turnover

The turnover of the RNA molecules is determined by the rates of transcription and RNA degradation. Several methods have been developed to study RNA turnover since the beginnings of molecular biology. Here we summarize the main methods to measure RNA half-life: transcription inhibition, gene control, and metabolic labelling. These methods were used to detect the cellular activity of the mRNAs degradation machinery, including the exo-ribonuclease Xrn1 and the exosome. On the other hand, the study of the differential stability of mature RNAs has been hampered by the fact that different methods have often yielded inconsistent results. Recent advances in the systematic comparison of different method variants in yeast have permitted the identification of the least invasive methodologies that reflect half-lives the most faithfully, which is expected to open the way for a consistent quantitative analysis of the determinants of mRNA stability.

Thiol-linked alkylation of RNA to assess expression dynamics

Gene expression profiling by high-throughput sequencing reveals qualitative and quantitative changes in RNA species at steady state but obscures the intracellular dynamics of RNA transcription, processing and decay. We developed thiol(SH)-linked alkylation for the metabolic sequencing of RNA (SLAM seq), an orthogonal-chemistry-based RNA sequencing technology that detects 4-thiouridine (s4U) incorporation in RNA species at single-nucleotide resolution. In combination with well-established metabolic RNA labeling protocols and coupled to standard, low-input, high-throughput RNA sequencing methods, SLAM seq enabled rapid access to RNA-polymerase-II-dependent gene expression dynamics in the context of total RNA. We validated the method in mouse embryonic stem cells by showing that the RNA-polymerase-II-dependent transcriptional output scaled with Oct4/Sox2/Nanog-defined enhancer activity, and we provide quantitative and mechanistic evidence for transcript-specific RNA turnover mediated by post-transcriptional gene regulatory pathways initiated by microRNAs and N6-methyladenosine. SLAM seq facilitates the dissection of fundamental mechanisms that control gene expression in an accessible, cost-effective and scalable manner.

Osmium-Mediated Transformation of 4-Thiouridine to Cytidine as Key To Study RNA Dynamics by Sequencing

To understand the functional roles of RNA in the cell, it is essential to elucidate the dynamics of their production, processing and decay. A recent method for assessing mRNA dynamics is metabolic labeling with 4-thiouridine (4sU), followed by thio-selective attachment of affinity tags. Detection of labeled transcripts by affinity purification and hybridization to microarrays or by deep sequencing then reveals RNA expression levels. Here, we present a novel sequencing method (TUC-seq) that eliminates affinity purification and allows for direct assessment of 4sU-labeled RNA. It employs an OsO4 -mediated transformation to convert 4sU into cytosine. We exemplify the utility of the new method for verification of endogenous 4sU in tRNAs and for the detection of pulse-labeled mRNA of seven selected genes in mammalian cells to determine the relative abundance of the new transcripts. The results prove TUC-seq as a straight-forward and highly versatile method for studies of cellular RNA dynamics.

Advances and challenges in the detection of transcriptome-wide protein-RNA interactions

RNA binding proteins (RBPs) play key roles in determining cellular behavior by manipulating the processing of target RNAs. Robust methods are required to detect the numerous binding sites of RBPs across the transcriptome. RNA‐immunoprecipitation followed by sequencing (RIP‐seq) and crosslinking followed by immunoprecipitation and sequencing (CLIP‐seq) are state‐of‐the‐art methods used to identify the RNA targets and specific binding sites of RBPs. Historically, CLIP methods have been confounded with challenges such as the requirement for tens of millions of cells per experiment, low RNA yields resulting in libraries that contain a high number of polymerase chain reaction duplicated reads, and technical inconveniences such as radioactive labeling of RNAs. However, recent improvements in the recovery of bound RNAs and the efficiency of converting isolated RNAs into a library for sequencing have enhanced our ability to perform the experiment at scale, from less starting material than has previously been possible, and resulting in high quality datasets for the confident identification of protein binding sites. These, along with additional improvements to protein capture, removal of nonspecific signals, and methods to isolate noncanonical RBP targets have revolutionized the study of RNA processing regulation, and reveal a promising future for mapping the human protein‐RNA regulatory network. WIREs RNA 2018, 9:e1436. doi: 10.1002/wrna.1436

This article is categorized under: 1

RNA Interactions with Proteins and Other Molecules > Protein–RNA Recognition

2

RNA Interactions with Proteins and Other Molecules > Protein–RNA Interactions: Functional Implications

3

RNA Methods > RNA Analyses in Cells

Zygotic Genome Activation in Vertebrates

The first major developmental transition in vertebrate embryos is the maternal-to-zygotic transition (MZT) when maternal mRNAs are degraded and zygotic transcription begins. During the MZT, the embryo takes charge of gene expression to control cell differentiation and further development. This spectacular organismal transition requires nuclear reprogramming and the initiation of RNAPII at thousands of promoters. Zygotic genome activation (ZGA) is mechanistically coordinated with other embryonic events, including changes in the cell cycle, chromatin state, and nuclear-to-cytoplasmic component ratios. Here, we review progress in understanding vertebrate ZGA dynamics in frogs, fish, mice, and humans to explore differences and emphasize common features.

Rapid Genome-wide Recruitment of RNA Polymerase II Drives Transcription, Splicing, and Translation Events during T Cell Responses

Activation of immune cells results in rapid functional changes, but how such fast changes are accomplished remains enigmatic. By combining time courses of 4sU-seq, RNA-seq, ribosome profiling (RP), and RNA polymerase II (RNA Pol II) ChIP-seq during T cell activation, we illustrate genome-wide temporal dynamics for ∼10,000 genes. This approach reveals not only immediate-early and posttranscriptionally regulated genes but also coupled changes in transcription and translation for >90% of genes. Recruitment, rather than release of paused RNA Pol II, primarily mediates transcriptional changes. This coincides with a genome-wide temporary slowdown in cotranscriptional splicing, even for polyadenylated mRNAs that are localized at the chromatin. Subsequent splicing optimization correlates with increasing Ser-2 phosphorylation of the RNA Pol II carboxy-terminal domain (CTD) and activation of the positive transcription elongation factor (pTEFb). Thus, rapid de novo recruitment of RNA Pol II dictates the course of events during T cell activation, particularly transcription, splicing, and consequently translation.

Toward Time-Resolved Analysis of RNA Metabolism in Archaea Using 4-Thiouracil

Archaea are widespread organisms colonizing almost every habitat on Earth. However, the molecular biology of archaea still remains relatively uncharacterized. RNA metabolism is a central cellular process, which has been extensively analyzed in both bacteria and eukarya. In contrast, analysis of RNA metabolism dynamic in archaea has been limited to date. To facilitate analysis of the RNA metabolism dynamic at a system-wide scale in archaea, we have established non-radioactive pulse labeling of RNA, using the nucleotide analog 4-thiouracil (4TU) in two commonly used model archaea: the halophile Euryarchaeota Haloferax volcanii, and the thermo-acidophile Crenarchaeota Sulfolobus acidocaldarius. In this work, we show that 4TU pulse labeling can be efficiently performed in these two organisms in a dose- and time-dependent manner. In addition, our results suggest that uracil prototrophy had no critical impact on the overall 4TU incorporation in RNA molecules. Accordingly, our work suggests that 4TU incorporation can be widely performed in archaea, thereby expanding the molecular toolkit to analyze archaeal gene expression network dynamic in unprecedented detail.

Screening the Molecular Framework Underlying Local Dendritic mRNA Translation

In the last decade, bioinformatic analyses of high-throughput proteomics and transcriptomics data have enabled researchers to gain insight into the molecular networks that may underlie lasting changes in synaptic efficacy. Development and utilization of these techniques have advanced the field of learning and memory significantly. It is now possible to move from the study of activity-dependent changes of a single protein to modeling entire network changes that require local protein synthesis. This data revolution has necessitated the development of alternative computational and statistical techniques to analyze and understand the patterns contained within. Thus, the focus of this review is to provide a synopsis of the journey and evolution toward big data techniques to address still unanswered questions regarding how synapses are modified to strengthen neuronal circuits. We first review the seminal studies that demonstrated the pivotal role played by local mRNA translation as the mechanism underlying the enhancement of enduring synaptic activity. In the interest of those who are new to the field, we provide a brief overview of molecular biology and biochemical techniques utilized for sample preparation to identify locally translated proteins using RNA sequencing and proteomics, as well as the computational approaches used to analyze these data. While many mRNAs have been identified, few have been shown to be locally synthesized. To this end, we review techniques currently being utilized to visualize new protein synthesis, a task that has proven to be the most difficult aspect of the field. Finally, we provide examples of future applications to test the physiological relevance of locally synthesized proteins identified by big data approaches.

Metabolic labeling and recovery of nascent RNA to accurately quantify mRNA stability

Changes in the rate of mRNA decay are closely coordinated with transcriptional changes and together these events have profound effects on gene expression during development and disease. Traditional approaches to assess mRNA decay have relied on inhibition of transcription, which can alter mRNA decay rates and confound interpretation. More recently, metabolic labeling combined with chemical modification and fractionation of labeled RNAs has allowed the isolation of nascent transcripts and the subsequent calculation of mRNA decay rates. This approach has been widely adopted for measuring mRNA half-lives on a global scale, but has proven challenging to use for analysis of single genes. We present a series of normalization and quality assurance steps to be used in combination with 4-thiouridine pulse labeling of cultured eukaryotic cells. Importantly, we demonstrate how the relative amount of 4sU-labeled nascent RNA influences accurate quantification. The approach described facilitates reproducible measurement of individual mRNA half-lives using 4-thiouridine and could be adapted for use with other nucleoside analogs.

Isolation of Newly Transcribed RNA Using the Metabolic Label 4-Thiouridine

Isolation of newly transcribed RNA is an invaluable approach that can be used to study the dynamic life of RNA in cellulo. Traditional methods of whole-cell RNA extraction limit subsequent gene expression analyses to the steady-state levels of RNA abundance, which often masks changes in RNA synthesis and processing. This chapter describes a methodology with low cytotoxicity that permits the labeling and isolation of nascent pre-mRNA in cell culture. The resulting isolate is suitable for use in a series of downstream applications aimed at studying changes in RNA synthesis, processing, or stability.

RNA interactome capture in yeast

RNA-binding proteins (RBPs) are key players in post-transcriptional regulation of gene expression in eukaryotic cells. To be able to unbiasedly identify RBPs in Saccharomyces cerevisiae, we developed a yeast RNA interactome capture protocol which employs RNA labeling, covalent UV crosslinking of RNA and proteins at 365 nm wavelength (photoactivatable-ribonucleoside-enhanced crosslinking, PAR-CL) and finally purification of the protein-bound mRNA. The method can be easily implemented in common workflows and takes about 3 days to complete. Next to a comprehensive explanation of the method, we focus on our findings about the choice of crosslinking in yeast and discuss the rationale of individual steps in the protocol.

Enriching s4 U-RNA Using Methane Thiosulfonate (MTS) Chemistry

Metabolic labeling of cellular RNA is a useful approach to study RNA biology. 4-Thiouridine (s⁴ U) is a convenient nucleoside for metabolic labeling because it is cell permeable and is incorporated into newly transcribed RNA, and the sulfur moiety provides a handle for biochemical purification. However, a critical step in the purification of s⁴ U-RNA is the efficiency of the chemistry used to enrich s⁴ U-RNA. Here, we present a protocol for s⁴ U-RNA enrichment that includes efficient and reversible covalent chemistry to biotinylate s⁴ U-RNA using the activated disulfide methane thiosulfonate conjugated to biotin (MTS-biotin), followed by enrichment on streptavidin beads. The efficiency of this chemistry reduces enrichment bias and requires less starting material, thereby expanding the utility of s⁴ U to study RNA biology. © 2016 by John Wiley & Sons, Inc.

Measures of RNA metabolism rates: Toward a definition at the level of single bonds

We give an overview of experimental and computational methods to estimate RNA metabolism rates genome-wide. We then advocate a local definition of RNA metabolism rate at the level of individual phosphodiester bonds. Rates of formation and disappearance of individual bonds are unambiguously defined, in contrast to rates of complete transcripts. We show that over previous approaches, the recently developed transient transcriptome sequencing (TT-seq) protocol allows for estimation of metabolism rates of individual bonds with least positional bias.

Increase in the photoreactivity of uracil derivatives by doubling thionation

The ability of 4-thiouracil to strongly absorb UVA radiation and to populate a reactive triplet state in high yield has enabled its use as a versatile photocrosslinker for nearly 50 years. In this contribution, we present a detailed spectroscopic and photochemical investigation of the 2-thiouracil, 4-thiouracil, and 2,4-dithiouracil series in an effort to further advance this chemistry and to scrutinize the photoreactivity of 2,4-dithiouracil. Our results reveal that excitation of 2,4-dithiouracil leads to intersystem crossing to the triplet manifold in 220 ± 40 fs, which enables the population of the reactive triplet state with near unity yield (ΦT = 0.90 ± 0.15) and ultimately leads to a ca. 50% singlet oxygen generation (ΦΔ = 0.49 ± 0.02)-one of the highest singlet oxygen yields reported to date for a photoexcited thiobase. In addition, the long-lived triplet state of 2,4-dithiouracil reacts efficiently with the nucleic acid base adenine 5'-monophosphate through a direct, oxygen-independent photocycloaddition mechanism and at a rate that is at least 3-fold faster than that of 4-thiouracil under equal conditions. The new physico-chemical insights reported for these RNA-thiobase derivatives are compared to those of the DNA and RNA bases and the DNA-thiobase derivatives. Furthermore, the strong near-visible absorption and increased photoreactivity measured for 2,4-dithiouracil lays a solid foundation for developing RNA-targeted photocrosslinking and phototherapeutic agents that are more effective than those currently available.

Human Argonaute 2 Is Tethered to Ribosomal RNA through MicroRNA Interactions

The primary role of the RNAi machinery is to promote mRNA degradation within the cytoplasm in a microRNA-dependent manner. However, both Dicer and the Argonaute protein family have expanded roles in gene regulation within the nucleus. To further our understanding of this role, we have identified chromatin binding sites for AGO2 throughout the 45S region of the human rRNA gene. The location of these sites was mirrored by the positions of AGO2 cross-linking sites identified via PAR-CLIP-seq. AGO2 binding to the rRNA within the nucleus was confirmed by RNA immunoprecipitation and quantitative-PCR. To explore a possible mechanism by which AGO2 could be recruited to the rRNA, we identified 1174 regions within the 45S rRNA transcript that have the ability to form a perfect duplex with position 2-6 (seed sequence) of each microRNA expressed in HEK293T cells. Of these potential AGO2 binding sites, 479 occurred within experimentally verified AGO2-rRNA cross-linking sites. The ability of AGO2 to cross-link to rRNA was almost completely lost in a DICER knock-out cell line. The transfection of miR-92a-2-3p into the noDICE cell line facilitated AGO2 cross-linking at a region of the rRNA that has a perfect seed match at positions 3-8, including a single G-U base pair. Knockdown of AGO2 within HEK293T cells causes a slight, but statistically significant increase in the overall rRNA synthesis rate but did not impact the ratio of processing intermediates or the recruitment of the Pol I transcription factor UBTF.

Tiny giants of gene regulation: experimental strategies for microRNA functional studies

The discovery over two decades ago of short regulatory microRNAs (miRNAs) has led to the inception of a vast biomedical research field dedicated to understanding these powerful orchestrators of gene expression. Here we aim to provide a comprehensive overview of the methods and techniques underpinning the experimental pipeline employed for exploratory miRNA studies in animals. Some of the greatest challenges in this field have been uncovering the identity of miRNA-target interactions and deciphering their significance with regard to particular physiological or pathological processes. These endeavors relied almost exclusively on the development of powerful research tools encompassing novel bioinformatics pipelines, high-throughput target identification platforms, and functional target validation methodologies. Thus, in an unparalleled manner, the biomedical technology revolution unceasingly enhanced and refined our ability to dissect miRNA regulatory networks and understand their roles in vivo in the context of cells and organisms. Recurring motifs of target recognition have led to the creation of a large number of multifactorial bioinformatics analysis platforms, which have proved instrumental in guiding experimental miRNA studies. Subsequently, the need for discovery of miRNA-target binding events in vivo drove the emergence of a slew of high-throughput multiplex strategies, which now provide a viable prospect for elucidating genome-wide miRNA-target binding maps in a variety of cell types and tissues. Finally, deciphering the functional relevance of miRNA post-transcriptional gene silencing under physiological conditions, prompted the evolution of a host of technologies enabling systemic manipulation of miRNA homeostasis as well as high-precision interference with their direct, endogenous targets. For further resources related to this article, please visit the WIREs website.

Degradation dynamics of microRNAs revealed by a novel pulse-chase approach

The regulation of miRNAs is critical to the definition of cell identity and behavior in normal physiology and disease. To date, the dynamics of miRNA degradation and the mechanisms involved in remain largely obscure, in particular, in higher organisms. Here, we developed a pulse-chase approach based on metabolic RNA labeling to calculate miRNA decay rates at genome-wide scale in mammalian cells. Our analysis revealed heterogeneous miRNA half-lives, with many species behaving as stable molecules (T_1/2 > 24 h), while others, including passenger miRNAs and a number (25/129) of guide miRNAs, are quickly turned over (T_1/2 = 4–14 h). Decay rates were coupled with other features, including genomic organization, transcription rates, structural heterogeneity (isomiRs), and target abundance, measured through quantitative experimental approaches. This comprehensive analysis highlighted functional mechanisms that mediate miRNA degradation, as well as the importance of decay dynamics in the regulation of the miRNA pool under both steady-state conditions and during cell transitions.

A Nonradioactive Assay to Measure Production and Processing of Ribosomal RNA by 4sU-Tagging

In vivo metabolic pulse labeling is a classical approach to assess production and processing of ribosomal RNA (rRNA). However, conventional labeling techniques can be indirect and require work with radioactivity. Here, we describe in detail a protocol for in vivo metabolic labeling, purification, and readout of nascent rRNA by 4-thiouridine (4sU). We propose 4sU labeling as standard nonradioactive technique for the analysis of rRNA metabolism during ribosome biogenesis.

Transcriptome-wide RNA processing kinetics revealed using extremely short 4tU labeling

BACKGROUND

RNA levels detected at steady state are the consequence of multiple dynamic processes within the cell. In addition to synthesis and decay, transcripts undergo processing. Metabolic tagging with a nucleotide analog is one way of determining the relative contributions of synthesis, decay and conversion processes globally.

RESULTS

By improving 4-thiouracil labeling of RNA in Saccharomyces cerevisiae we were able to isolate RNA produced during as little as 1 minute, allowing the detection of nascent pervasive transcription. Nascent RNA labeled for 1.5, 2.5 or 5 minutes was isolated and analyzed by reverse transcriptase-quantitative polymerase chain reaction and RNA sequencing. High kinetic resolution enabled detection and analysis of short-lived non-coding RNAs as well as intron-containing pre-mRNAs in wild-type yeast. From these data we measured the relative stability of pre-mRNA species with different high turnover rates and investigated potential correlations with sequence features.

CONCLUSIONS

Our analysis of non-coding RNAs reveals a highly significant association between non-coding RNA stability, transcript length and predicted secondary structure. Our quantitative analysis of the kinetics of pre-mRNA splicing in yeast reveals that ribosomal protein transcripts are more efficiently spliced if they contain intron secondary structures that are predicted to be less stable. These data, in combination with previous results, indicate that there is an optimal range of stability of intron secondary structures that allows for rapid splicing.

A Method that Will Captivate U

In an age of next-generation sequencing, the ability to purify RNA transcripts has become a critical issue. In this issue, Duffy et al. (2015) improve on a pre-existing technique of RNA labeling and purification by 4-thiouridine tagging. By increasing the efficiency of RNA capture, this method will enhance the ability to study RNA dynamics, especially for transcripts normally inefficiently captured by previous methods.

Tracking Distinct RNA Populations Using Efficient and Reversible Covalent Chemistry

We describe a chemical method to label and purify 4-thiouridine (s(4)U)-containing RNA. We demonstrate that methanethiosulfonate (MTS) reagents form disulfide bonds with s(4)U more efficiently than the commonly used HPDP-biotin, leading to higher yields and less biased enrichment. This increase in efficiency allowed us to use s(4)U labeling to study global microRNA (miRNA) turnover in proliferating cultured human cells without perturbing global miRNA levels or the miRNA processing machinery. This improved chemistry will enhance methods that depend on tracking different populations of RNA, such as 4-thiouridine tagging to study tissue-specific transcription and dynamic transcriptome analysis (DTA) to study RNA turnover.

Measuring Transcription Rate Changes via Time-Course 4-Thiouridine Pulse-Labelling Improves Transcriptional Target Identification

Identifying changes in the transcriptional regulation of target genes from high-throughput studies is important for unravelling molecular mechanisms controlled by a given perturbation. When measuring global transcript levels only, the effect of the perturbation [e.g., transcription factor (TF) overexpression or drug treatment] on its target genes is often obscured by delayed feedback and secondary effects until the changes are fully propagated. As a proof of principle, we show that selective measuring of transcripts that are only synthesised after a perturbation [4-thiouridine (4sU) sequencing (4sU-seq)] is a more sensitive method to identify targets and time-dependent transcriptional responses than global transcript profiling. By metabolically labelling RNA in a time-course setup, we could vastly increase the sensitivity of MYCN target gene detection compared to traditional RNA sequencing. The validity of targets identified by 4sU-seq was demonstrated using chromatin immunoprecipitation sequencing and neuroblastoma microarray tumour data. Here, we describe the methodology, both molecular biology and computational aspects, required to successfully apply this 4sU-seq approach.

RNA-binding proteins in neurodegeneration: Seq and you shall receive

As critical players in gene regulation, RNA binding proteins (RBPs) are taking center stage in our understanding of cellular function and disease. In our era of bench-top sequencers and unprecedented computational power, biological questions can be addressed in a systematic, genome-wide manner. Development of high-throughput sequencing (Seq) methodologies provides unparalleled potential to discover new mechanisms of disease-associated perturbations of RNA homeostasis. Complementary to candidate single-gene studies, these innovative technologies may elicit the discovery of unexpected mechanisms, and enable us to determine the widespread influence of the multifunctional RBPs on their targets. Given that the disruption of RNA processing is increasingly implicated in neurological diseases, these approaches will continue to provide insights into the roles of RBPs in disease pathogenesis.

DEAD-box helicase DDX27 regulates 3' end formation of ribosomal 47S RNA and stably associates with the PeBoW-complex

PeBoW, a trimeric complex consisting of pescadillo (Pes1), block of proliferation (Bop1), and the WD repeat protein 12 (WDR12), is essential for processing and maturation of mammalian 5.8S and 28S ribosomal RNAs. Applying a mass spectrometric analysis, we identified the DEAD-box helicase DDX27 as stably associated factor of the PeBoW-complex. DDX27 interacts with the PeBoW-complex via an evolutionary conserved F×F motif in the N-terminal domain and is recruited to the nucleolus via its basic C-terminal domain. This recruitment is RNA-dependent and occurs independently of the PeBoW-complex. Interestingly, knockdown of DDX27, but not of Pes1, induces the accumulation of an extended form of the primary 47S rRNA. We conclude that DDX27 can interact specifically with the Pes1 and Bop1 but fulfils critical function(s) for proper 3' end formation of 47S rRNA independently of the PeBoW-complex.

Transcription-coupled RNA surveillance in human genetic diseases caused by splice site mutations

Current estimates indicate that approximately one-third of all disease-causing mutations are expected to disrupt splicing. Abnormal splicing often leads to disruption of the reading frame with introduction of a premature termination codon (PTC) that targets the mRNA for degradation in the cytoplasm by nonsense mediated decay (NMD). In addition to NMD there are RNA surveillance mechanisms that act in the nucleus while transcripts are still associated with the chromatin template. However, the significance of nuclear RNA quality control in the context of human genetic diseases is unknown. Here we used patient-derived lymphoblastoid cell lines as disease models to address how biogenesis of mRNAs is affected by splice site mutations. We observed that most of the mutations analyzed introduce PTCs and trigger mRNA degradation in the cytoplasm. However, for some mutant transcripts, RNA levels associated with chromatin were found down-regulated. Quantification of nascent transcripts further revealed that a subset of genes containing splicing mutations (SM) have reduced transcriptional activity. Following treatment with the translation inhibitor cycloheximide the cytoplasmic levels of mutant RNAs increased, while the levels of chromatin-associated transcripts remained unaltered. These results suggest that transcription-coupled surveillance mechanisms operate independently from NMD to reduce cellular levels of abnormal RNAs caused by SM.

ELAVL1 modulates transcriptome-wide miRNA binding in murine macrophages

Posttranscriptional gene regulation by miRNAs and RNA binding proteins (RBP) is important in development, physiology, and disease. To examine the interplay between miRNAs and the RBP ELAVL1 (HuR), we mapped miRNA binding sites at the transcriptome-wide scale in wild-type and Elavl1 knockout murine bone-marrow-derived macrophages. Proximity of ELAVL1 binding sites attenuated miRNA binding to transcripts and promoted gene expression. Transcripts that regulate angiogenesis and macrophage/endothelial crosstalk were preferentially targeted by miRNAs, suggesting that ELAVL1 promotes angiogenesis, at least in part by antagonism of miRNA function. We found that ELAVL1 antagonized binding of miR-27 to the 3' UTR of Zfp36 mRNA and alleviated miR-27-mediated suppression of the RBP ZFP36 (Tristetraprolin). Thus, the miR-27-regulated mechanism synchronizes the expression of ELAVL1 and ZFP36. This study provides a resource for systems-level interrogation of posttranscriptional gene regulation in macrophages, a key cell type in inflammation, angiogenesis, and tissue homeostasis.

Genome-wide mapping of yeast RNA polymerase II termination

Yeast RNA polymerase II (Pol II) terminates transcription of coding transcripts through the polyadenylation (pA) pathway and non-coding transcripts through the non-polyadenylation (non-pA) pathway. We have used PAR-CLIP to map the position of Pol II genome-wide in living yeast cells after depletion of components of either the pA or non-pA termination complexes. We show here that Ysh1, responsible for cleavage at the pA site, is required for efficient removal of Pol II from the template. Depletion of Ysh1 from the nucleus does not, however, lead to readthrough transcription. In contrast, depletion of the termination factor Nrd1 leads to widespread runaway elongation of non-pA transcripts. Depletion of Sen1 also leads to readthrough at non-pA terminators, but in contrast to Nrd1, this readthrough is less processive, or more susceptible to pausing. The data presented here provide delineation of in vivo Pol II termination regions and highlight differences in the sequences that signal termination of different classes of non-pA transcripts.

Transcription termination is an important regulatory event for both non-coding and coding transcripts. Using high-throughput sequencing, we have mapped RNA Polymerase II's position in the genome after depletion of termination factors from the nucleus. We found that depletion of Ysh1 and Sen1 cause build up of polymerase directly downstream of coding and non-coding genes, respectively. Depletion of Nrd1 causes an increase in polymerase that is distributed up to 1,000 bases downstream of non-coding genes. The depletion of Nrd1 helped us to identify more than 250 unique termination regions for non-coding RNAs. Within this set of newly identified non-coding termination regions, we are further able to classify them based on sequence motif similarities, suggesting a functional role for different terminator motifs. The role of these factors in transcriptional termination of coding and/or non-coding transcripts can be inferred from the effect of polymerase's position downstream of given termination sites. This method of depletion and sequencing can be used to further elucidate other factors whose importance to transcription has yet to be determined.