Rate Of RNA Degradation Research Articles

Storm: Incorporating transient stochastic dynamics to infer the RNA velocity with metabolic labeling information

The time-resolved scRNA-seq (tscRNA-seq) provides the possibility to infer physically meaningful kinetic parameters, e.g., the transcription, splicing or RNA degradation rate constants with correct magnitudes, and RNA velocities by incorporating temporal information. Previous approaches utilizing the deterministic dynamics and steady-state assumption on gene expression states are insufficient to achieve favorable results for the data involving transient process. We present a dynamical approach, Storm (Stochastic models of RNA metabolic-labeling), to overcome these limitations by solving stochastic differential equations of gene expression dynamics. The derivation reveals that the new mRNA sequencing data obeys different types of cell-specific Poisson distributions when jointly considering both biological and cell-specific technical noise. Storm deals with measured counts data directly and extends the RNA velocity methodology based on metabolic labeling scRNA-seq data to transient stochastic systems. Furthermore, we relax the constant parameter assumption over genes/cells to obtain gene-cell-specific transcription/splicing rates and gene-specific degradation rates, thus revealing time-dependent and cell-state-specific transcriptional regulations. Storm will facilitate the study of the statistical properties of tscRNA-seq data, eventually advancing our understanding of the dynamic transcription regulation during development and disease.

Minimal Perturbation Analysis of mRNA Degradation Rates with Tet-Off and RT-qPCR.

Messenger RNA stability is an important variable in gene expression and its dynamics. High stability ensures a constant level of synthesized protein, whereas mRNA instability can be critical for regulatory processes in which protein production needs to be stopped, such as development, inflammation, or adaptation to stress. Accurate measurements of RNA degradation rates are important for understanding how RNA features and RNA binding proteins affect the posttranscriptional life of an mRNA. As an alternative to global transcriptional inhibition methods, the use of a Tet-off repressible promoter has the advantage that cells are minimally perturbed by the addition of doxycyclin during the assay. We illustrate the use of a reporter mRNA expressed from a plasmid in Saccharomyces cerevisiae cells, but similar methods can be applied to other regulated promoters, on plasmids or by genome editing, and in other organisms. RNA levels are measured by reverse transcription followed by quantitative PCR. An exponential decay law is then used to estimate how well the measurements follow this expected trend for the simplest possible mechanism of RNA degradation, where the decay is proportional to the amount of RNA present at any given time.

DeepKINET: a deep generative model for estimating single-cell RNA splicing and degradation rates

Messenger RNA splicing and degradation are critical for gene expression regulation, the abnormality of which leads to diseases. Previous methods for estimating kinetic rates have limitations, assuming uniform rates across cells. DeepKINET is a deep generative model that estimates splicing and degradation rates at single-cell resolution from scRNA-seq data. DeepKINET outperforms existing methods on simulated and metabolic labeling datasets. Applied to forebrain and breast cancer data, it identifies RNA-binding proteins responsible for kinetic rate diversity. DeepKINET also analyzes the effects of splicing factor mutations on target genes in erythroid lineage cells. DeepKINET effectively reveals cellular heterogeneity in post-transcriptional regulation.

SLAM-Drop-seq reveals mRNA kinetic rates throughout the cell cycle

RNA abundance is tightly regulated in eukaryotic cells by modulating the kinetic rates of RNA production, processing, and degradation. To date, little is known about time-dependent kinetic rates during dynamic processes. Here, we present SLAM-Drop-seq, a method that combines RNA metabolic labeling and alkylation of modified nucleotides in methanol-fixed cells with droplet-based sequencing to detect newly synthesized and preexisting mRNAs in single cells. As a first application, we sequenced 7280 HEK293 cells and calculated gene-specific kinetic rates during the cell cycle using the novel package Eskrate. Of the 377 robust-cycling genes that we identified, only a minor fraction is regulated solely by either dynamic transcription or degradation (6 and 4%, respectively). By contrast, the vast majority (89%) exhibit dynamically regulated transcription and degradation rates during the cell cycle. Our study thus shows that temporally regulated mRNA degradation is fundamental for the correct expression of a majority of cycling genes. SLAM-Drop-seq, combined with Eskrate, is a powerful approach to understanding the underlying mRNA kinetics of single-cell gene expression dynamics in continuous biological processes.

Abstract P3072: Effects Of Antiviral Innate Immune Activation On Cytokine Secretion And Function Of Human Ipsc-derived Cardiomyocytes

Introduction: Acute and long-term cardiovascular complications of COVID-19 have been reported, ranging from arrhythmias, ischemic heart disease, and heart failure to cerebrovascular and cardiometabolic disorders, yet the underlying molecular mechanisms are not well understood. Here, we examine the effects of stimulating the double-stranded RNA (dsRNA) pattern recognition receptor pathway, which is strongly induced to activate interferon-stimulated gene (ISG) expression in the heart during COVID-19, on excitation-contraction coupling and mitochondrial function. While providing antiviral protection, we hypothesize that, even in the absence of cardiac viral replication, this pathway might contribute to COVID-19-related cardiac dysfunction. Results: We used the viral dsRNA mimetic polyinosinic: polycytidylic (PIC) to induce a type I interferon response in iPSC-CM or A549 (lung epithelial) cells. In iPSC-CM, PIC induced robust protein expression of STAT1/pSTAT1, OAS2, OAS3, IRF7, pIRF7, IRF9 and MX1. A marked increase in cytokine protein secretion was also observed, with significant increases in CXCL-10 (~160 fold), IL6, CCL5 (~20-fold) IL8 (15-fold), and CXCL1 (~10-fold), and a 2-5-fold increase in ~30 other cytokines. Negative effects on excitation-contraction coupling were observed after 72 hours of PIC treatment, manifested as a 25% reduction in iPSC-CM Ca2+ transient amplitude. Microelectrode array analysis of iPSC-CM monolayers revealed electrophysiological dysfunction: PIC treatment increased cardiac field potential duration and spike amplitude, but reduced beat periods. A549 cells also showed increases in interferon pathway genes (STAT1, pSTAT1, IRF3, pIRF3, OAS1,2,3 and IFNb1), along with increased rates of RNA degradation after PIC treatment, consistent with activation of the OAS/RNAseL dsRNA sensor pathway. PIC-treated A549 cells also showed a large decrease in oxidative phosphorylation (maximal respiration and spare respiratory capacity), which was prevented by the mitochondrial antioxidant, mitoTEMPO. Conclusions: Activation of the viral dsRNA innate immune sensor pathway, even in the absence of active cardiac viral replication, might contribute to mitochondrial and cardiac dysfunction in COVID-19.

Abstract P6-14-12: Evaluation of changes in sequencing quality and transcriptomic profiles with increasing post-mortem interval: results from an optimization experiment within the UPTIDER tissue donation program

Abstract Background. Postmortem tissue donation programs can importantly enhance sample access for translational research on metastatic disease. However, this post-mortem setting poses logistical and technical challenges in terms of preserving nucleic acid quality and in particular RNA. Here we present the results of an experiment within our breast cancer tissue donation program UPTIDER (NCT04531696), aiming at assessing RNA degradation rates and expression profile changes in function of tissue type and sample-specific postmortem interval (ssPMI). Patients & Methods. For 7 patients, bulk RNA sequencing was performed using the Lexogen protocol on fresh frozen samples from healthy or tumour tissues taken repeatedly (at 1.5h time intervals) during the autopsy. ssPMI was defined as the time between the death of the patient and the freezing of the sample. Quality threshold was set at 0.5 million (M) of assigned reads (AR). Other quality metrics included number of expressed genes, evolution of proliferation-, hypoxia-, stromal- and immune-related transcriptional signatures (PMID:18698033, 20087356) with increasing ssPMI. Associations between quality metrics and ssPMI were assessed by linear regressions for longitudinal data, with quality metrics as dependent variable, time as independent variable and accounting for the clustering of the data by patient and organ using the generalized estimating equation method. Three nested models - with constant, linear and non-linear relationship - were compared using ANOVA testing strategy. Non-linearity was rendered by a restrict cubic spline with three knots. All tests were performed by the Wald test on regression coefficients. Results. Ninety samples (67 healthy, 23 tumour) were analyzed. Median ssPMI was 7.50 hours (range: 3.07-11.12). Most (87%) samples passed quality thresholds, with median AR being 1.70M (interquartile range: [0.70M-3.57M]). No association was found between quality metrics and time in healthy samples. In tumor samples, regarding sequencing quality, negative associations with increasing time were found for AR and for number of expressed genes with an average decay of 242308 reads per hour (95 confidence interval (95CI): [94415.62-390200.50], p-value=.001) and 251 genes per hour (95CI: [17.30-485], p-value=.035), respectively. At the transcriptomic level, potential subtle changes were observed regarding immune (e.g. STAT1 signature: -0.02, 95CI: [-0.05;0.00]) and hypoxia-related signatures (e.g. PGAM1 signature: -0.03, 95CI [-0.05;-0.01]), while no effect of time was seen for the proliferation and stromal-related signatures. Sample size precluded organ specific analyses. Conclusion. A decrease in the number of AR and number of expressed genes with increasing ssPMI was found in tumor samples leading to subtle changes in few transcriptional programs. Healthy samples showed stable quality metrics over time possibly explained by a lower cell activity in healthy as compared to tumour cells. Knowledge derived from this study will be integrated in the upcoming transcriptomic analyses of the samples collected within UPTIDER. Citation Format: François Richard, Tatjana Geukens, Giuseppe Marano, Wouter Van Den Bogaert, Maxim De Schepper, Marion Maetens, Amena Mahdami, Karen Van Baelen, Ha-Linh Nguyen, Anirudh Pabba, Sophia Leduc, Edoardo Isnaldi, Maysam Hajipirloo, Imane Bachir, Evy Vanderheyden, Bram Boeckx, Diether Lambrechts, Ann Smeets, Ines Nevelsteen, Kevin Punie, Patrick Neven, Hans Wildiers, Elia Biganzoli, Giuseppe Floris, Christine Desmedt. Evaluation of changes in sequencing quality and transcriptomic profiles with increasing post-mortem interval: results from an optimization experiment within the UPTIDER tissue donation program [abstract]. In: Proceedings of the 2022 San Antonio Breast Cancer Symposium; 2022 Dec 6-10; San Antonio, TX. Philadelphia (PA): AACR; Cancer Res 2023;83(5 Suppl):Abstract nr P6-14-12.

Escherichia coli protein synthesis is limited by mRNA availability rather than ribosomal capacity during phosphate starvation.

Protein synthesis is the most energetically costly process in the cell. Consequently, it is a tightly regulated process, and regulation of the resources allocated to the protein synthesis machinery is at the heart of bacterial growth optimization theory. However, the molecular mechanisms that result in dynamic downregulation of protein synthesis in response to nutrient starvation are not well described. Here, we first quantify the Escherichia coli response to phosphate starvation at the level of accumulation rates for protein, RNA and DNA. Escherichia coli maintains a low level of protein synthesis for hours after the removal of phosphate while the RNA contents decrease, primarily as a consequence of ribosomal RNA degradation combined with a reduced RNA synthesis rate. To understand the molecular basis for the low protein synthesis rate of phosphate-starved cells, template mRNA for translation was overproduced in the form of a highly induced long-lived mRNA. Remarkably, starved cells increased the rate of protein synthesis and reduced the rate of ribosomal RNA degradation upon mRNA induction. These observations suggest that protein synthesis in phosphate-starved cells is primarily limited by the availability of template, and does not operate at the maximum capacity of the ribosomes. We suggest that mRNA limitation is an adaptive response to phosphate starvation that prevents the deleterious consequences of overcommitting resources to protein synthesis. Moreover, our results support the model that degradation of ribosomal RNA occurs as a consequence of the availability of idle ribosomal subunits.

High-purity isolation platelets by gradient centrifugation plus filtration.

Platelets can be used as a liquid biopsy source to provide rapid, up-to-date, and relevant information on tumor pathology and treatment response. However, there is still a lack of high efficiency methods for platelet isolation with high purity. Three platelet isolation methods were evaluated by platelet recovery and purity. The platelet inhibition cocktail (PIC) was added into peripheral blood, or was not allowed to access the effect of the platelet activation. The CD61, CD45, and CD62P labelled platelets, leukocytes and activated platelets were detected by flow cytometry. Quantitative polymerase chain reaction (qPCR) and next-generation sequencing (NGS) were employed to determine the gene expression levels. A time-dependent experiment combined with qPCR was used to determine the time limit for platelet isolation at room temperature. Compared to the gradient centrifugation alone, and gradient centrifugation plus filtration and magnetic beads separation, gradient centrifugation plus filtration was the preferred method for more efficient and high-purity platelet isolation, with a recovery rate of 9.1% and a purity of 99.98%. Furthermore, there was no difference in platelet activation level, regardless of whether PIC was used. Moreover, the rate of platelet RNA degradation did not differ when platelets were isolated within 48 h of blood collection. Gradient centrifugation plus filtration at room temperature within 48 h of blood collection, without PIC, is a novel protocol with high recovery and purity rate to isolate platelets.

Observation of conformational changes that underlie the catalytic cycle of Xrn2.

Nuclear magnetic resonance (NMR) methods that quantitatively probe motions on molecular and atomic levels have propelled the understanding of biomolecular processes for which static structures cannot provide a satisfactory description. In this work, we studied the structure and dynamics of the essential 100-kDa eukaryotic 5′→3′ exoribonuclease Xrn2. A combination of complementary fluorine and methyl-TROSY NMR spectroscopy reveals that the apo enzyme is highly dynamic around the catalytic center. These observed dynamics are in agreement with a transition of the enzyme from the ground state into a catalytically competent state. We show that the conformational equilibrium in Xrn2 shifts substantially toward the active state in the presence of substrate and magnesium. Finally, our data reveal that the dynamics in Xrn2 correlate with the RNA degradation rate, as a mutation that attenuates motions also affects catalytic activity. In that light, our results stress the importance of studies that go beyond static structural information.

The estimation of bloodstain age utilizing circRNAs and mRNAs biomarkers

Determining the time since deposition (TsD) of bloodstains can provide forensic investigators with additional clues, as it can corroborate eyewitness accounts, limit the number of suspects, and help confirm alibis. Bloodstains are the most common bodily fluid stains at crime scenes. In this study, we examined the relative expression levels (REs) of circRNAs and mRNAs data in bloodstains over ten time points by Real-time quantitative polymerase chain reaction (qPCR), to determine the utility of the relative expression levels of RNA markers for TsD estimation. Forensic samples more than just appear in indoor settings, we also evaluated the use of RNA degradation rate to indicate the age of bloodstains in different environments including indoor and outdoor conditions. The expression levels of six blood-specific mRNA markers (GYPA, CD93, ALAS2, SPTB, HBB, HBA), three highly expressed circRNAs in human peripheral blood (hsa_circ_0001445, hsa_circ_0000972, hsa_circ_0000095) and three reference genes (18 S, ACTB and U6) were analyzed across numerous ageing time points. Analysis of the degradation rates of individual RNAs under indoor and outdoor conditions showed that they exhibited a unique degradation profile during the four-month storage interval, with both circRNAs and mRNAs linearly showing continuous degradation, while U6 is more stable than other reference gene markers. In the current study, we firstly used circRNAs as additional novel biomarkers for bloodstain age estimation, and at the same time proved that different environments had a significant impact on the REs of certain blood biomarkers, and sex differences did not affect the age estimation of bloodstains. The REs of the selected RNA molecules in this study showed a non-linear relationship with bloodstain age and the mathematical formula for estimating the bloodstain age based on the relative expression levels of hsa_circ_0001445, ALAS2 and HBB can be used to estimate the TsD of bloodstains from the REs of bloodstains of unknown age, which represent a potentially effective approach to looking for time-dependent changes and TsD estimation.

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

BackgroundOver 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.MethodsOur 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.ResultsOur 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.ConclusionsIn 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.

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.

Comprehensive Pan-Cancer Analysis of the Prognostic and Immunological Roles of the METTL3/lncRNA-SNHG1/miRNA-140-3p/UBE2C Axis.

Growing evidence has demonstrated that UBE2C plays a critical role in cancer progression, but there is no study focusing on the prognosis, upstream regulation mechanism, and immunological roles of UBE2C across diverse tumor types. In this study, we found that UBE2C was elevated in this human pan-cancer analysis, and high expression of UBE2C was correlated with poor prognosis. In addition, UBE2C expression was markedly associated with tumor mutation burden (TMB), microsatellite instability (MSI), immune cell infiltration, and diverse drug sensitivities. Finally, we showed that the METTL3/SNHG1/miRNA-140-3p axis could potentially regulate UBE2C expression. N(6)-Methyladenosine (m6A) modifications improved the stability of methylated SNHG1 transcripts by decreasing the rate of RNA degradation, which lead to upregulation of SNHG1 in non-small cell lung cancer (NSCLC). In vitro functional experiments showed that SNHG1, as a competing endogenous RNA, sponges miR-140-3p to increase UBE2C expression in NSCLC cell lines. Our study elucidates the clinical importance and regulatory mechanism of the METTL3/SNHG1/miRNA-140-3p/UBE2C axis in NSCLC and provides a prognostic indicator, as well as a promising therapeutic target for patients with NSCLC.

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.

Human spliceosomal snRNA sequence variants generate variant spliceosomes.

Human pre-mRNA splicing is primarily catalyzed by the major spliceosome, comprising five small nuclear ribonucleoprotein complexes, U1, U2, U4, U5, and U6 snRNPs, each of which contains the corresponding U-rich snRNA. These snRNAs are encoded by large gene families exhibiting significant sequence variation, but it remains unknown if most human snRNA genes are untranscribed pseudogenes or produce variant snRNAs with the potential to differentially influence splicing. Since gene duplication and variation are powerful mechanisms of evolutionary adaptation, we sought to address this knowledge gap by systematically profiling human U1, U2, U4, and U5 snRNA variant gene transcripts. We identified 55 transcripts that are detectably expressed in human cells, 38 of which incorporate into snRNPs and spliceosomes in 293T cells. All U1 snRNA variants are more than 1000-fold less abundant in spliceosomes than the canonical U1, whereas at least 1% of spliceosomes contain a variant of U2 or U4. In contrast, eight U5 snRNA sequence variants occupy spliceosomes at levels of 1% to 46%. Furthermore, snRNA variants display distinct expression patterns across five human cell lines and adult and fetal tissues. Different RNA degradation rates contribute to the diverse steady state levels of snRNA variants. Our findings suggest that variant spliceosomes containing noncanonical snRNAs may contribute to different tissue- and cell-type–specific alternative splicing patterns.

In search of the RNA world on Mars.

Advances in origins of life research and prebiotic chemistry suggest that life as we know it may have emerged from an earlier RNA World. However, it has been difficult to reconcile the conditions used in laboratory experiments with real‐world geochemical environments that may have existed on the early Earth and hosted the origin(s) of life. This challenge is due to geologic resurfacing and recycling that have erased the overwhelming majority of the Earth's prebiotic history. We therefore propose that Mars, a planet frozen in time, comprised of many surfaces that have remained relatively unchanged since their formation > 4 Gya, is the best alternative to search for environments consistent with geochemical requirements imposed by the RNA world. In this study, we synthesize in situ and orbital observations of Mars and modeling of its early atmosphere into solutions containing a range of pHs and concentrations of prebiotically relevant metals (Fe2+, Mg2+, and Mn2+) spanning various candidate aqueous environments. We then experimentally determine RNA degradation kinetics due to metal‐catalyzed hydrolysis (cleavage) and evaluate whether early Mars could have been permissive toward the accumulation of long‐lived RNA polymers. Our results indicate that a Mg2+‐rich basalt sourcing metals to a slightly acidic (pH 5.4) environment mediates the slowest rates of RNA cleavage, though geologic evidence and basalt weathering models suggest aquifers on Mars would be near neutral (pH ~ 7). Moreover, the early onset of oxidizing conditions on Mars has major consequences regarding the availability of oxygen‐sensitive metals (i.e., Fe2+ and Mn2+) due to increased RNA degradation rates and precipitation. Overall, (a) low pH decreases RNA cleavage at high metal concentrations; (b) acidic to neutral pH environments with Fe2+ or Mn2+ cleave more RNA than Mg2+; and (c) alkaline environments with Mg2+ dramatically cleaves more RNA while precipitates were observed for Fe2+ and Mn2+.

Fluorescence In Situ Hybridization of Small Non-Coding RNAs.

The determination of the cellular localization of a noncoding RNA (ncRNA) is highly helpful to decipher its function. RNA-FISH is a powerful method to detect specific RNAs in fixed cells. It allows both localization and quantification of RNA molecules within individual cells and tissues. Refined RNA-FISH methods have also been developed to determine RNA transcription and degradation rates. This chapter describes an RNA-FISH protocol that we developed to study the expression and localization of satellite III (SATIII) RNAs. This specific class of ncRNAs is expressed in response to various cellular stresses, including heat shock. The protocol is based on the use of a biotinylated LNA probe subsequently detected by a Streptavidin, Alexa Fluor® 488 conjugate. A protocol allowing efficient coupling of RNA-FISH and protein detection by immunofluorescence is also described as well as the bioinformatics pipeline, Substructure Analyzer, we recently developed to automate fluorescence signal analysis.

The effect of environmental conditions on the rate of RNA degradation in dried blood stains

The relationship between RNA degradation and the age of a bloodstain has been suggested by the work of several investigators. A prior study from this laboratory described a qPCR assay that was effective at estimating the age of bloodstains stored in an environmentally controlled laboratory for periods of up to one year. In this study, the effect of the environmental conditions on the rate of RNA degradation during storage was analyzed. Bloodstains were prepared on stain cards and stored in one of 9 different environments for periods of up to 24 weeks. At selected times during the storage term, RNA was extracted, reverse transcribed, and the integrity of select transcripts analyzed. Three temperatures (37 °C, 20 °C, and 4 °C) and three relative humidities (rH) (75 %, 35 %, and 10 %) were combined pairwise. The rate of RNA degradation was found to increase 5–10 fold in stains stored at 37 °C versus those stored at 20 °C. The rate of RNA degradation was faster for stains stored at 20 °C compared to 4 °C but differed only 2–4 fold. Multivariate regression analysis suggests elevations in temperature or rH will accelerate RNA degradation and will do so to a similar extent. It is clear from the data that the integrity of the transcriptome in dried bloodstains is better preserved in a cold and dry environment. Investigations are ongoing to develop an approach for the estimation of sample age that incorporates the environmental conditions of a crime scene into the age estimate.

Widespread Protection of RNA Cleavage Sites by a Riboswitch Aptamer that Folds as a Compact Obstacle to Scanning by RNase E

Riboswitches are thought generally to function by modulating transcription elongation or translation initiation. In rare instances, ligand binding to a riboswitch has been found to alter the rate of RNA degradation by directly stimulating or inhibiting nearby cleavage. Here, we show that guanidine-induced pseudoknot formation by the aptamer domain of a guanidine III riboswitch from Legionella pneumophila has a different effect, stabilizing mRNA by protecting distal cleavage sites en masse from ribonuclease attack. It does so by creating a coaxially base-paired obstacle that impedes scanning from a monophosphorylated 5' end to those sites by the regulatory endonuclease RNase E. Ligand binding by other riboswitch aptamers peripheral to the path traveled by RNase E does not inhibit distal cleavage. These findings reveal that a riboswitch aptamer can function independently of any overlapping expression platform to regulate gene expression by acting directly to prolong mRNA longevity in response to ligand binding.

Genome-wide dynamics of RNA synthesis, processing, and degradation without RNA metabolic labeling.

The quantification of the kinetic rates of RNA synthesis, processing, and degradation are largely based on the integrative analysis of total and nascent transcription, the latter being quantified through RNA metabolic labeling. We developed INSPEcT−, a computational method based on the mathematical modeling of premature and mature RNA expression that is able to quantify kinetic rates from steady-state or time course total RNA-seq data without requiring any information on nascent transcripts. Our approach outperforms available solutions, closely recapitulates the kinetic rates obtained through RNA metabolic labeling, improves the ability to detect changes in transcript half-lives, reduces the cost and complexity of the experiments, and can be adopted to study experimental conditions in which nascent transcription cannot be readily profiled. Finally, we applied INSPEcT− to the characterization of post-transcriptional regulation landscapes in dozens of physiological and disease conditions. This approach was included in the INSPEcT Bioconductor package, which can now unveil RNA dynamics from steady-state or time course data, with or without the profiling of nascent RNA.