Database for mRNA half-life of 19 977 genes obtained by DNA microarray analysis of pluripotent and differentiating mouse embryonic stem cells

Genome-wide quantification of RNA flow across subcellular compartments reveals determinants of the mammalian transcript life cycle

Dissecting the regulatory mechanisms controlling mammalian transcripts from production to degradation requires quantitative measurements of mRNA flow across the cell. We developed subcellular TimeLapse-seq to measure the rates at which RNAs are released from chromatin, exported from the nucleus, loaded onto polysomes, and degraded within the nucleus and cytoplasm in human and mouse cells. These rates varied substantially, yet transcripts from genes with related functions or targeted by the same transcription factors and RNA-binding proteins flowed across subcellular compartments with similar kinetics. Verifying these associations uncovered a link between DDX3X and nuclear export. For hundreds of RNA metabolism genes, most transcripts with retained introns were degraded by the nuclear exosome, while the remaining molecules were exported with stable cytoplasmic lifespans. Transcripts residing on chromatin for longer had extended poly(A) tails, whereas the reverse was observed for cytoplasmic mRNAs. Finally, machine learning identified molecular features that predicted the diverse life cycles of mRNAs.

Multi-dataset Integration and Residual Connections Improve Proteome Prediction from Transcriptomes using Deep Learning

Proteomes are well known to poorly correlate with transcriptomes measured from the same sample. While connected, the complex processes that impact the relationships between transcript and protein quantities remains an open research topic. Many studies have attempted to predict proteomes from transcriptomes with limited success. Here we use publicly available data from the Clinical Proteomics Tumor Analysis Consortium to show that deep learning models designed by neural architecture search (NAS) achieve improved prediction accuracy of proteome quantities from transcriptomics. We find that this benefit is largely due to including a residual connection in the architecture that allows input information to be remembered near the end of the network. Finally, we explore which groups of transcripts are functionally important for protein prediction using model interpretation with SHAP.

Impact of DEHP on mitochondria-associated endoplasmic reticulum membranes and reproductive toxicity in ovary

Di(2-ethylhexyl) phthalate (DEHP) is a widely recognized environmental endocrine disruptor that potentially impacts female reproductive function, although the specific mechanisms leading to such impairment remain unclear. A growing body of research has revealed that the endoplasmic reticulum and mitochondrial function significantly influence oocyte quality. The structure of mitochondria-associated endoplasmic reticulum membranes (MAMs) is crucial for facilitating the exchange of Ca2+, lipids, and metabolites. This study aimed to investigate the alterations in the composition and function of MAMs after DEHP exposure and to elucidate the underlying mechanisms of ovarian toxicity. The female mice were exposed to DEHP at doses of 5 and 500 mg/kg/day for one month. The results revealed that DEHP exposure led to reduced serum anti-Müllerian hormone levels and increased atretic follicles in mice. DEHP induced endoplasmic reticulum stress and disrupted calcium homeostasis in oocytes. Furthermore, DEHP impaired the mitochondrial function of oocytes and reduced their membrane potential, and promoting apoptosis. Similar results were observed in human granulosa cells after exposure to mono-(2-ethylhexyl) phthalate (MEHP, metabolites of DEHP) in vitro. Proteomic analysis and transmission electron microscopy revealed modifications in the functional proteins and structure of the MAMs, and the suppression of oxidative phosphorylation pathways. The findings of this investigation provide a new perspective on the mechanism underlying the reproductive toxicity of DEHP in females.

Alternative splicing coupled to nonsense-mediated decay coordinates downregulation of non-neuronal genes in developing mouse neurons

BACKGROUND

The functional coupling between alternative pre-mRNA splicing (AS) and the mRNA quality control mechanism called nonsense-mediated decay (NMD) can modulate transcript abundance. Previous studies have identified several examples of such a regulation in developing neurons. However, the systems-level effects of AS-NMD in this context are poorly understood.

RESULTS

We developed an R package, factR2, which offers a comprehensive suite of AS-NMD analysis functions. Using this tool, we conducted a longitudinal analysis of gene expression in pluripotent stem cells undergoing induced neuronal differentiation. Our analysis uncovers hundreds of AS-NMD events with significant potential to regulate gene expression. Notably, this regulation is significantly overrepresented in specific functional groups of developmentally downregulated genes. Particularly strong association with gene downregulation is detected for alternative cassette exons stimulating NMD upon their inclusion into mature mRNA. By combining bioinformatic analyses with CRISPR/Cas9 genome editing and other experimental approaches we show that NMD-stimulating cassette exons regulated by the RNA-binding protein PTBP1 dampen the expression of their genes in developing neurons. We also provided evidence that the inclusion of NMD-stimulating cassette exons into mature mRNAs is temporally coordinated with NMD-independent gene repression mechanisms.

CONCLUSIONS

Our study provides an accessible workflow for the discovery and prioritization of AS-NMD targets. It further argues that the AS-NMD pathway plays a widespread role in developing neurons by facilitating the downregulation of functionally related non-neuronal genes.

Isoform and pathway-specific regulation of post-transcriptional RNA processing in human cells

Steady-state levels of RNA transcripts are controlled by their rates of synthesis and degradation. Here we used nascent RNA Bru-seq and BruChase-seq to profile RNA dynamics across 16 human cell lines as part of ENCODE4 Deeply Profiled Cell Lines collection. We show that RNA turnover dynamics differ widely between transcripts of different genes and between different classes of RNA. Gene set enrichment analysis (GSEA) revealed that transcripts encoding proteins belonging to the same pathway often show similar turnover dynamics. Furthermore, transcript isoforms show distinct dynamics suggesting that RNA turnover is important in regulating mRNA isoform choice. Finally, splicing across newly made transcripts appears to be cooperative with either all or none type splicing. These data sets generated as part of ENCODE4 illustrate the intricate and coordinated regulation of RNA dynamics in controlling gene expression to allow for the precise coordination of cellular functions.

Advances in non-viral mRNA delivery to the spleen

Developing safe and effective delivery strategies for localizing messenger RNA (mRNA) payloads to the spleen is an important goal in the field of genetic medicine. Accomplishing this goal is challenging due to the instability, size, and charge of mRNA payloads. Here, we provide an analysis of non-viral delivery technologies that have been developed to deliver mRNA payloads to the spleen. Specifically, our review begins by outlining the unique anatomy and potential targets for mRNA delivery within the spleen. Next, we describe approaches in mRNA sequence engineering that can be used to improve mRNA delivery to the spleen. Then, we describe advances in non-viral carrier systems that can package and deliver mRNA payloads to the spleen, highlighting key advances in the literature in lipid nanoparticle (LNP) and polymer nanoparticle (PNP) technology platforms. Finally, we provide commentary and outlook on how splenic mRNA delivery may afford next-generation treatments for autoimmune disorders and cancers. In undertaking this approach, our goal with this review is to both establish a fundamental understanding of drug delivery challenges associated with localizing mRNA payloads to the spleen, while also broadly highlighting the potential to use these genetic medicines to treat disease.

Repair of CRISPR-guided RNA breaks enables site-specific RNA excision in human cells

Genome editing with CRISPR RNA-guided endonucleases generates DNA breaks that are resolved by cellular DNA repair machinery. However, analogous methods to manipulate RNA remain unavailable. We show that site-specific RNA breaks generated with type-III CRISPR complexes are repaired in human cells and that this repair can be used for programmable deletions in human transcripts to restore gene function. Collectively, this work establishes a technology for precise RNA manipulation with potential therapeutic applications.

"Oh, Dear We Are in Tribble": An Overview of the Oncogenic Functions of Tribbles 1

Pseudokinases are catalytically inactive proteins in the human genome that lack the ability to transfer phosphate from ATP to their substrates. The Tribbles family of pseudokinases contains three members: Tribbles 1, 2, and 3. Tribbles 1 has recently gained importance because of its involvement in various diseases, including cancer. It acts as a scaffolding protein that brings about the degradation of its substrate proteins, such as C/EBPα/β, MLXIPL, and RAR/RXRα, among others, via the ubiquitin proteasome system. It also serves as an adapter protein, which sequesters different protein molecules and activates their downstream signaling, leading to processes, such as cell survival, cell proliferation, and lipid metabolism. It has been implicated in cancers such as AML, prostate cancer, breast cancer, CRC, HCC, and glioma, where it activates oncogenic signaling pathways such as PI3K-AKT and MAPK and inhibits the anti-tumor function of p53. TRIB1 also causes treatment resistance in cancers such as NSCLC, breast cancer, glioma, and promyelocytic leukemia. All these effects make TRIB1 a potential drug target. However, the lack of a catalytic domain renders TRIB1 "undruggable", but knowledge about its structure, conformational changes during substrate binding, and substrate binding sites provides an opportunity to design small-molecule inhibitors against specific TRIB1 interactions.

Reconstructing developmental trajectories using latent dynamical systems and time-resolved transcriptomics

The snapshot nature of single-cell transcriptomics presents a challenge for studying the dynamics of cell fate decisions. Metabolic labeling and splicing can provide temporal information at single-cell level, but current methods have limitations. Here, we present a framework that overcomes these limitations: experimentally, we developed sci-FATE2, an optimized method for metabolic labeling with increased data quality, which we used to profile 45,000 embryonic stem (ES) cells differentiating into neural tube identities. Computationally, we developed a two-stage framework for dynamical modeling: VelvetVAE, a variational autoencoder (VAE) for velocity inference that outperforms all other tools tested, and VelvetSDE, a neural stochastic differential equation (nSDE) framework for simulating trajectory distributions. These recapitulate underlying dataset distributions and capture features such as decision boundaries between alternative fates and fate-specific gene expression. These methods recast single-cell analyses from descriptions of observed data to models of the dynamics that generated them, providing a framework for investigating developmental fate decisions.

Gene-specific RNA homeostasis revealed by perturbation of coactivator complexes

Transcript buffering entails the reciprocal modulation of mRNA synthesis and degradation rates to maintain stable RNA levels under varying cellular conditions. Current research supports a global, non-sequence-specific connection between mRNA synthesis and degradation, but the underlying mechanisms are still unclear. In this study, we investigated changes in RNA metabolism following acute depletion of TIP60/KAT5, the acetyltransferase subunit of the NuA4 transcriptional coactivator complex, in mouse embryonic stem cells. By combining RNA sequencing of nuclear, cytoplasmic, and newly synthesised transcript fractions with biophysical modelling, we demonstrate that TIP60 predominantly enhances transcription of numerous genes, while a smaller set of genes undergoes TIP60-dependent transcriptional repression. Surprisingly, transcription changes caused by TIP60 depletion were offset by corresponding changes in RNA nuclear export and cytoplasmic stability, indicating gene-specific buffering mechanisms. Similarly, disruption of the unrelated ATAC coactivator complex also resulted in gene-specific transcript buffering. These findings reveal that transcript buffering functions at a gene-specific level and suggest that cells dynamically adjust RNA splicing, export, and degradation in response to individual RNA synthesis alterations, thereby sustaining cellular homeostasis.

Optimizing retinal ganglion cell nuclear staining for automated cell counting

The retinal ganglion cells (RGCs) serve as the critical pathway for transmitting visual information from the retina to the brain, yet they can be dramatically impacted by diseases such as glaucoma. When investigating disease processes affecting RGCs in mouse models, accurately quantifying affected cells becomes essential. However, the use of pan RGC markers like RBPMS or THY1 presents challenges in accurate total cell counting. While Brn3a serves as a reliable RGC nuclear marker for automated counting, it fails to encompass all RGC subtypes in mice. To address this limitation and enable precise automated counting, our research endeavors to develop a method for labeling nuclei in all RGC subtypes. Investigating RGC subtypes labeled with the nuclear marker POU6F2 revealed that numerous RGCs unlabeled by Brn3a were, in fact, labeled with POU6F2. We hypothesize that using antibodies against both Brn3a and POU6F2 would label virtually all RGC nuclei in the mouse retina. Our experiments confirmed that staining retinas with both markers resulted in the labeling of all RGCs. Additionally, when using the cell body marker RBPMS known to label all mouse RGCs, all RBPMS-labeled cells also exhibited Brn3a or POU6F2 labeling. This combination of Brn3a and POU6F2 antibodies provides a pan-RGC nuclear stain, facilitating accurate automated counting by labeling cell nuclei in the retina.

Impacts of the feedback loop between sense-antisense RNAs in regulating circadian rhythms

Antisense transcripts are a unique group of non-coding RNAs that are transcribed from the opposite strand of a sense coding gene in an antisense orientation. Even though they do not encode a protein, these transcripts play a regulatory role in a variety of biological processes, including circadian rhythms. We and others found an antisense transcript, Per2AS , that is transcribed from the strand opposite the sense transcript Period2 ( Per2 ) and exhibits a rhythmic and antiphasic expression pattern compared to Per2 in mouse. By assuming that Per2AS and Per2 mutually repress each other, our previous mathematical model predicted that Per2AS regulates the robustness and the amplitude of circadian rhythms. In this study, we revised our previous model and developed a new mathematical model that mechanistically described the mutually repressive relationship between Per2 and Per2AS via transcriptional interference. We found that the simulation results are largely consistent with experimental observations including the counterintuitive ones that could not be fully explained by our previous model. These results indicate that our revised model serves as a foundation to build more detailed models in the future to better understand the impact of Per2AS-Per2 interaction in the mammalian circadian clock. Our mechanistic description of Per2AS-Per2 interaction can also be extended to other mathematical models that involve sense-antisense RNA pairs that mutually repress each other.

The molecular mechanisms underpinning maternal mRNA dormancy

A large number of mRNAs of maternal origin are produced during oogenesis and deposited in the oocyte. Since transcription stops at the onset of meiosis during oogenesis and does not resume until later in embryogenesis, maternal mRNAs are the only templates for protein synthesis during this period. To ensure that a protein is made in the right place at the right time, the translation of maternal mRNAs must be activated at a specific stage of development. Here we summarize our current understanding of the sophisticated mechanisms that contribute to the temporal repression of maternal mRNAs, termed maternal mRNA dormancy. We discuss mechanisms at the level of the RNA itself, such as the regulation of polyadenine tail length and RNA modifications, as well as at the level of RNA-binding proteins, which often block the assembly of translation initiation complexes at the 5' end of an mRNA or recruit mRNAs to specific subcellular compartments. We also review microRNAs and other mechanisms that contribute to repressing translation, such as ribosome dormancy. Importantly, the mechanisms responsible for mRNA dormancy during the oocyte-to-embryo transition are also relevant to cellular quiescence in other biological contexts.

Control of cell state transitions by post-transcriptional regulation

Cell state transitions are prevalent in biology, playing a fundamental role in development, homeostasis and repair. Dysregulation of cell state transitions can lead to or occur in a wide range of diseases. In this letter, I explore and highlight the role of post-transcriptional regulatory mechanisms in determining the dynamics of cell state transitions. I propose that regulation of protein levels after transcription provides an under-appreciated regulatory route to obtain fast and sharp transitions between distinct cell states. This article is part of a discussion meeting issue 'Causes and consequences of stochastic processes in development and disease'.

Engineered mRNA Delivery Systems for Biomedical Applications

Messenger RNA (mRNA)-based therapeutic strategies have shown remarkable promise in preventing and treating a staggering range of diseases. Optimizing the structure and delivery system of engineered mRNA has greatly improved its stability, immunogenicity, and protein expression levels, which has led to a wider range of uses for mRNA therapeutics. Herein, a thorough analysis of the optimization strategies used in the structure of mRNA is first provided and delivery systems are described in great detail. Furthermore, the latest advancements in biomedical engineering for mRNA technology, including its applications in combatting infectious diseases, treating cancer, providing protein replacement therapy, conducting gene editing, and more, are summarized. Lastly, a perspective on forthcoming challenges and prospects concerning the advancement of mRNA therapeutics is offered. Despite these challenges, mRNA-based therapeutics remain promising, with the potential to revolutionize disease treatment and contribute to significant advancements in the biomedical field.

Regulation of Versican Expression in Macrophages is Mediated by Canonical Type I Interferon Signaling via ISGF3

Growing evidence supports a role for versican as an important component of the inflammatory response, with both pro- and anti-inflammatory roles depending on the specific context of the system or disease under investigation. Our goal is to understand the regulation of macrophage-derived versican and the role it plays in innate immunity. In previous work, we showed that LPS triggers a signaling cascade involving TLR4, the Trif adaptor, type I interferons, and the type I interferon receptor, leading to increased versican expression by macrophages. In the present study, we used a combination of chromatin immunoprecipitation, siRNA, chemical inhibitors, and mouse model approaches to investigate the regulatory events downstream of the type I interferon receptor to better define the mechanism controlling versican expression. Results indicate that transcriptional regulation by canonical type I interferon signaling via the heterotrimeric transcription factor, ISGF3, controls versican expression in macrophages exposed to LPS. This pathway is not dependent on MAPK signaling, which has been shown to regulate versican expression in other cell types. The stability of versican mRNA may also contribute to prolonged versican expression in macrophages. These findings strongly support a role for macrophage-derived versican as a type I interferon-stimulated gene and further our understanding of versican's role in regulating inflammation.

Predicting cell population-specific gene expression from genomic sequence

Most regulatory elements, especially enhancer sequences, are cell population-specific. One could even argue that a distinct set of regulatory elements is what defines a cell population. However, discovering which non-coding regions of the DNA are essential in which context, and as a result, which genes are expressed, is a difficult task. Some computational models tackle this problem by predicting gene expression directly from the genomic sequence. These models are currently limited to predicting bulk measurements and mainly make tissue-specific predictions. Here, we present a model that leverages single-cell RNA-sequencing data to predict gene expression. We show that cell population-specific models outperform tissue-specific models, especially when the expression profile of a cell population and the corresponding tissue are dissimilar. Further, we show that our model can prioritize GWAS variants and learn motifs of transcription factor binding sites. We envision that our model can be useful for delineating cell population-specific regulatory elements.

The Ribosome Hypothesis: Decoding Mood Disorder Complexity

Several types of mood disorders lie along a continuum, with nebulous boundaries between them. Understanding the mechanisms that contribute to mood disorder complexity is critical for effective treatment. However, present treatments are largely centered around neurotransmission and receptor-based hypotheses, which, given the high instance of treatment resistance, fail to adequately explain the complexities of mood disorders. In this opinion piece, based on our recent results, we propose a ribosome hypothesis of mood disorders. We suggest that any hypothesis seeking to explain the diverse nature of mood disorders must incorporate infrastructure diversity that results in a wide range of effects. Ribosomes, with their mobility across neurites and complex composition, have the potential to become specialized during stress; thus, ribosome diversity and dysregulation are well suited to explaining mood disorder complexity. Here, we first establish a framework connecting ribosomes to the current state of knowledge associated with mood disorders. Then, we describe the potential mechanisms through which ribosomes could homeostatically regulate systems to manifest diverse mood disorder phenotypes and discuss approaches for substantiating the ribosome hypothesis. Investigating these mechanisms as therapeutic targets holds promise for transdiagnostic avenues targeting mood disorders.

Emerging tools for uncovering genetic and transcriptomic heterogeneities in bacteria

Bacterial communities display an astonishing degree of heterogeneities among their constituent cells across both the genomic and transcriptomic levels, giving rise to diverse social interactions and stress-adaptation strategies indispensable for proliferating in the natural environment (Ackermann in Nat Rev Microbiol 13:497-508, 2015). Our knowledge about bacterial heterogeneities and their physiological ramifications critically depends on our ability to unambiguously resolve the genetic and phenotypic states of the individual cells that make up the population. In this short review, I highlight several recently developed methods for studying bacterial heterogeneities, primarily focusing on single-cell techniques based on advanced sequencing and microscopy technologies. I will discuss the working principle of each technique as well as the types of problems each technique is best positioned to address. With significant improvements in resolution and throughput, these emerging tools together offer unprecedented and complementary views of various types of heterogeneities found within bacterial populations, paving the way for mechanistic dissections and systematic interventions in laboratory and clinical settings.

Differential sensitivity to longitudinal and transverse stretch mediates transcriptional responses in mouse neonatal ventricular myocytes

To identify how cardiomyocyte mechanosensitive signaling pathways are regulated by anisotropic stretch, micropatterned mouse neonatal cardiomyocytes were stretched primarily longitudinally or transversely to the myofiber axis. Four hours of static, longitudinal stretch induced differential expression of 557 genes, compared with 30 induced by transverse stretch, measured using RNA-seq. A logic-based ordinary differential equation model of the cardiac myocyte mechanosignaling network, extended to include the transcriptional regulation and expression of 784 genes, correctly predicted measured expression changes due to anisotropic stretch with 69% accuracy. The model also predicted published transcriptional responses to mechanical load in vitro or in vivo with 63-91% accuracy. The observed differences between transverse and longitudinal stretch responses were not explained by differential activation of specific pathways but rather by an approximately twofold greater sensitivity to longitudinal stretch than transverse stretch. In vitro experiments confirmed model predictions that stretch-induced gene expression is more sensitive to angiotensin II and endothelin-1, via RhoA and MAP kinases, than to the three membrane ion channels upstream of calcium signaling in the network. Quantitative cardiomyocyte gene expression differs substantially with the axis of maximum principal stretch relative to the myofilament axis, but this difference is due primarily to differences in stretch sensitivity rather than to selective activation of mechanosignaling pathways.NEW & NOTEWORTHY Anisotropic stretch applied to micropatterned neonatal mouse ventricular myocytes induced markedly greater acute transcriptional responses when the major axis of stretch was parallel to the myofilament axis than when it was transverse. Analysis with a novel quantitative network model of mechanoregulated cardiomyocyte gene expression suggests that this difference is explained by higher cell sensitivity to longitudinal loading than transverse loading than by the activation of differential signaling pathways.

Phase separation as a possible mechanism for dosage sensitivity

BACKGROUND

Deletion of haploinsufficient genes or duplication of triplosensitive ones results in phenotypic effects in a concentration-dependent manner, and the mechanisms underlying these dosage-sensitive effects remain elusive. Phase separation drives functional compartmentalization of biomolecules in a concentration-dependent manner as well, which suggests a potential link between these two processes, and warrants further systematic investigation.

RESULTS

Here we provide bioinformatic and experimental evidence to show a close link between phase separation and dosage sensitivity. We first demonstrate that haploinsufficient or triplosensitive gene products exhibit a higher tendency to undergo phase separation. Assessing the well-established dosage-sensitive genes HNRNPK, PAX6, and PQBP1 with experiments, we show that these proteins undergo phase separation. Critically, pathogenic variations in dosage-sensitive genes disturb the phase separation process either through reduced protein levels, or loss of phase-separation-prone regions. Analysis of multi-omics data further demonstrates that loss-of-function genetic perturbations on phase-separating genes cause similar dysfunction phenotypes as dosage-sensitive gene perturbations. In addition, dosage-sensitive scores derived from population genetics data predict phase-separating proteins with much better performance than available sequence-based predictors, further illustrating close ties between these two parameters.

CONCLUSIONS

Together, our study shows that phase separation is functionally linked to dosage sensitivity and provides novel insights for phase-separating protein prediction from the perspective of population genetics data.

mRNA nuclear export: how mRNA identity features distinguish functional RNAs from junk transcripts

The division of the cellular space into nucleoplasm and cytoplasm promotes quality control mechanisms that prevent misprocessed mRNAs and junk RNAs from gaining access to the translational machinery. Here, we explore how properly processed mRNAs are distinguished from both misprocessed mRNAs and junk RNAs by the presence or absence of various 'identity features'.

Intrinsic factors behind long COVID: III. Persistence of SARS-CoV-2 and its components

Considerable research has been done in investigating SARS-CoV-2 infection, its characteristics, and host immune response. However, debate is still ongoing over the emergence of post-acute sequelae of SARS-CoV-2 infection (PASC). A multitude of long-lasting symptoms have been reported several weeks after the primary acute SARS-CoV-2 infection that resemble several other viral infections. Thousands of research articles have described various post-COVID-19 conditions. Yet, the evidence around these ongoing health problems, the reasons behind them, and their molecular underpinnings are scarce. These persistent symptoms are also known as long COVID-19. The persistence of SARS-CoV-2 and/or its components in host tissues can lead to long COVID. For example, the presence of viral nucleocapsid protein and RNA was detected in the skin, appendix, and breast tissues of some long COVID patients. The persistence of viral RNA was reported in multiple anatomic sites, including non-respiratory tissues such as the adrenal gland, ocular tissue, small intestine, lymph nodes, myocardium, and sciatic nerve. Distinctive viral spike sequence variants were also found in non-respiratory tissues. Interestingly, prolonged detection of viral subgenomic RNA was observed across all tissues, sometimes in multiple tissues of the same patient, which likely reflects recent but defective viral replication. Moreover, the persistence of SARS-CoV-2 RNA was noticed throughout the brain at autopsy, as late as 230 days following symptom onset among unvaccinated patients who died of severe infection. Here, we review the persistence of SARS-CoV-2 and its components as an intrinsic factor behind long COVID. We also highlight the immunological consequences of this viral persistence.

Exploring the role of transcriptional and post-transcriptional processes in mRNA co-expression

Co-expression of two or more genes at the single-cell level is usually associated with functional co-regulation. While mRNA co-expression-measured as the correlation in mRNA levels-can be influenced by both transcriptional and post-transcriptional events, transcriptional regulation is typically considered dominant. We review and connect the literature describing transcriptional and post-transcriptional regulation of co-expression. To enhance our understanding, we integrate four datasets spanning single-cell gene expression data, single-cell promoter activity data and individual transcript half-lives. Confirming expectations, we find that positive co-expression necessitates promoter coordination and similar mRNA half-lives. Surprisingly, negative co-expression is favored by differences in mRNA half-lives, contrary to initial predictions from stochastic simulations. Notably, this association manifests specifically within clusters of genes. We further observe a striking compensation between promoter coordination and mRNA half-lives, which additional stochastic simulations suggest might give rise to the observed co-expression patterns. These findings raise intriguing questions about the functional advantages conferred by this compensation between distal kinetic steps.

mRNA as a medicine in nephrology: the future is now

The successful employment of messenger RNA (mRNA) as vaccine therapy for the prevention of COVID-19 infection has spotlighted the attention of scientific community onto the potential clinical application of these molecules as innovative and alternative therapeutic approaches in different fields of medicine. As therapy, mRNAs may be advantageous due to their unique biological properties of targeting almost any genetic component within the cell, many of which may be unreachable using other pharmacological/therapeutic approaches, and encoding any proteins and peptides without the need for their transport into the nuclei of the target cells. Additionally, these molecules may be rapidly designed/produced and clinically tested. Once the chemistry of the RNA and its delivery system are optimized, the cost of developing novel variants of these medications for new selected clinical disorders is significantly reduced. However, although potentially useful as new therapeutic weapons against several kidney diseases, the complex architecture of kidney and the inability of nanoparticles that accommodate oligonucleotides to cross the integral glomerular filtration barrier have largely decreased their potential employment in nephrology. However, in the next few years, the technical improvements in mRNA that increase translational efficiency, modulate innate and adaptive immunogenicity, and increase their delivery at the site of action will overcome these limitations. Therefore, this review has the scope of summarizing the key strengths of these RNA-based therapies and illustrating potential future directions and challenges of this promising technology for widespread therapeutic use in nephrology.

MiREx: mRNA levels prediction from gene sequence and miRNA target knowledge

Messenger RNA (mRNA) has an essential role in the protein production process. Predicting mRNA expression levels accurately is crucial for understanding gene regulation, and various models (statistical and neural network-based) have been developed for this purpose. A few models predict mRNA expression levels from the DNA sequence, exploiting the DNA sequence and gene features (e.g., number of exons/introns, gene length). Other models include information about long-range interaction molecules (i.e., enhancers/silencers) and transcriptional regulators as predictive features, such as transcription factors (TFs) and small RNAs (e.g., microRNAs - miRNAs). Recently, a convolutional neural network (CNN) model, called Xpresso, has been proposed for mRNA expression level prediction leveraging the promoter sequence and mRNAs' half-life features (gene features). To push forward the mRNA level prediction, we present miREx, a CNN-based tool that includes information about miRNA targets and expression levels in the model. Indeed, each miRNA can target specific genes, and the model exploits this information to guide the learning process. In detail, not all miRNAs are included, only a selected subset with the highest impact on the model. MiREx has been evaluated on four cancer primary sites from the genomics data commons (GDC) database: lung, kidney, breast, and corpus uteri. Results show that mRNA level prediction benefits from selected miRNA targets and expression information. Future model developments could include other transcriptional regulators or be trained with proteomics data to infer protein levels.

Assessing Markovian and Delay Models for Single-Nucleus RNA Sequencing

The serial nature of reactions involved in the RNA life-cycle motivates the incorporation of delays in models of transcriptional dynamics. The models couple a transcriptional process to a fairly general set of delayed monomolecular reactions with no feedback. We provide numerical strategies for calculating the RNA copy number distributions induced by these models, and solve several systems with splicing, degradation, and catalysis. An analysis of single-cell and single-nucleus RNA sequencing data using these models reveals that the kinetics of nuclear export do not appear to require invocation of a non-Markovian waiting time.

Physical modeling of ribosomes along messenger RNA: Estimating kinetic parameters from ribosome profiling experiments using a ballistic model

Gene expression is the synthesis of proteins from the information encoded on DNA. One of the two main steps of gene expression is the translation of messenger RNA (mRNA) into polypeptide sequences of amino acids. Here, by taking into account mRNA degradation, we model the motion of ribosomes along mRNA with a ballistic model where particles advance along a filament without excluded volume interactions. Unidirectional models of transport have previously been used to fit the average density of ribosomes obtained by the experimental ribo-sequencing (Ribo-seq) technique in order to obtain the kinetic rates. The degradation rate is not, however, accounted for and experimental data from different experiments are needed to have enough parameters for the fit. Here, we propose an entirely novel experimental setup and theoretical framework consisting in splitting the mRNAs into categories depending on the number of ribosomes from one to four. We solve analytically the ballistic model for a fixed number of ribosomes per mRNA, study the different regimes of degradation, and propose a criterion for the quality of the inverse fit. The proposed method provides a high sensitivity to the mRNA degradation rate. The additional equations coming from using the monosome (single ribosome) and polysome (arbitrary number) ribo-seq profiles enable us to determine all the kinetic rates in terms of the experimentally accessible mRNA degradation rate.

High-resolution kinetic characterization of the RIG-I-signaling pathway and the antiviral response

RIG-I recognizes viral dsRNA and activates a cell-autonomous antiviral response. Upon stimulation, it triggers a signaling cascade leading to the production of type I and III IFNs. IFNs are secreted and signal to elicit the expression of IFN-stimulated genes, establishing an antiviral state of the cell. The topology of this pathway has been studied intensively, however, its exact dynamics are less understood. Here, we employed electroporation to synchronously activate RIG-I, enabling us to characterize cell-intrinsic innate immune signaling at a high temporal resolution. Employing IFNAR1/IFNLR-deficient cells, we could differentiate primary RIG-I signaling from secondary signaling downstream of the IFN receptors. Based on these data, we developed a comprehensive mathematical model capable of simulating signaling downstream of dsRNA recognition by RIG-I and the feedback and signal amplification by IFN. We further investigated the impact of viral antagonists on signaling dynamics. Our work provides a comprehensive insight into the signaling events that occur early upon virus infection and opens new avenues to study and disentangle the complexity of the host-virus interface.

Ribosomal dysregulation: A conserved pathophysiological mechanism in human depression and mouse chronic stress

The underlying biological mechanisms that contribute to the heterogeneity of major depressive disorder (MDD) presentation remain poorly understood, highlighting the need for a conceptual framework that can explain this variability and bridge the gap between animal models and clinical endpoints. Here, we hypothesize that comparative analysis of molecular data from different experimental systems of chronic stress, and MDD has the potential to provide insight into these mechanisms and address this gap. Thus, we compared transcriptomic profiles of brain tissue from postmortem MDD subjects and from mice exposed to chronic variable stress (CVS) to identify orthologous genes. Ribosomal protein genes (RPGs) were down-regulated, and associated ribosomal protein (RP) pseudogenes were up-regulated in both conditions. A seeded gene co-expression analysis using altered RPGs common between the MDD and CVS groups revealed that down-regulated RPGs homeostatically regulated the synaptic changes in both groups through a RP-pseudogene-driven mechanism. In vitro analysis demonstrated that the RPG dysregulation was a glucocorticoid-driven endocrine response to stress. In silico analysis further demonstrated that the dysregulation was reversed during remission from MDD and selectively responded to ketamine but not to imipramine. This study provides the first evidence that ribosomal dysregulation during stress is a conserved phenotype in human MDD and chronic stress-exposed mouse. Our results establish a foundation for the hypothesis that stress-induced alterations in RPGs and, consequently, ribosomes contribute to the synaptic dysregulation underlying MDD and chronic stress-related mood disorders. We discuss the role of ribosomal heterogeneity in the variable presentations of depression and other mood disorders.

Lipid nanoparticles (LNPs) for in vivo RNA delivery and their breakthrough technology for future applications

RNA therapeutics show a significant breakthrough for the treatment of otherwise incurable diseases and genetic disorders by regulating disease-related gene expression. The successful development of COVID-19 mRNA vaccines further emphasizes the potential of RNA therapeutics in the prevention of infectious diseases as well as in the treatment of chronic diseases. However, the efficient delivery of RNA into cells remains a challenge, and nanoparticle delivery systems such as lipid nanoparticles (LNPs) are necessary to fully realize the potential of RNA therapeutics. While LNPs provide a highly efficient platform for the in vivo delivery of RNA by overcoming various biological barriers, several challenges remain to be resolved for further development and regulatory approval. These include a lack of targeted delivery to extrahepatic organs and a gradual loss of therapeutic potency with repeated doses. In this review, we highlight the fundamental aspects of LNPs and their uses in the development of novel RNA therapeutics. Recent advances in LNP-based therapeutics and preclinical/clinical studies are overviewed. Lastly, we discuss the current limitations of LNPs and introduce breakthrough technologies that might overcome these challenges in future applications.

Competition between transcription and loop extrusion modulates promoter and enhancer dynamics

The spatiotemporal configuration of genes with distal regulatory elements, and the impact of chromatin mobility on transcription, remain unclear. Loop extrusion is an attractive model for bringing genetic elements together, but how this functionally interacts with transcription is also largely unknown. We combine live tracking of genomic loci and nascent transcripts with molecular dynamics simulations to assess the spatiotemporal arrangement of the Sox2 gene and its enhancer, in response to a battery of perturbations. We find a close link between chromatin mobility and transcriptional status: active elements display more constrained mobility, consistent with confinement within specialized nuclear sites, and alterations in enhancer mobility distinguish poised from transcribing alleles. Strikingly, we find that whereas loop extrusion and transcription factor-mediated clustering contribute to promoter-enhancer proximity, they have antagonistic effects on chromatin dynamics. This provides an experimental framework for the underappreciated role of chromatin dynamics in genome regulation.

Protein restriction impairs the response activation/responsivity of MAPK signaling pathway of hematopoietic stem cells

Protein restriction (PR) leads to bone marrow hypoplasia with changes in stromal cellularity components of the extracellular matrix in hematopoietic stem cells (HSCs). However, the underlying signaling mechanisms are poorly understood. We hypothesize that PR impairs the HSC mitogen-activated protein kinase (MAPK) signaling pathway response activation. Our aim is to evaluate the activation of MAPK and interleukin-3 (IL-3) proteins in HSC to explain PR-induced bone marrow hypoplasia, which causes altered proliferation and differentiation. C57BL/6 male mice were subjected to a low-protein diet (2% protein) or normoproteic (12% protein). PKC, PLCγ2, CaMKII, AKT, STAT3/5, ERK1/2, JNK, and p38d phosphorylation were evaluated by flow cytometry, and GATA1/2, PU.1, C/EBPα, NF-E2, and Ikz-3 genes (mRNAs) assessed by quantitative real-time-polymerase chain reaction. Pathway proteins, such as PLCγ2, JAK2, STAT3/5, PKC, and RAS do not respond to the IL-3 stimulus in PR, leading to lower activation of ERK1/2 and Ca2+ signaling pathways, consequently lowering the production of hematopoietic transcription factors. Colony forming units granulocyte-macrophage and colony forming units macrophage formation are impaired in PR even after being stimulated with IL-3. Long-term hematopoietic stem cells, short-term hematopoietic stem cells, granulocyte myeloid progenitor, and megakaryocyte-erythroid progenitor cells were significantly reduced in PR animals. This study shows for the first time that activation of MAPK pathway key proteins in HSCs is impaired in cases of PR. Several pathway proteins, such as PLCγ2, JAK2, STAT3, PKC, and RAS do not respond to IL-3 stimulation, leading to lower activation of extracellular signal-regulated protein kinase 1/2 and consequently lower production of hematopoietic transcription factors GATA1/2, PU.1, C/EBPa, NF-E2, and Ikz3. These changes result in a reduction in colony-forming units, proliferation, and differentiation, leading to hypocellularity.

Aberrant DNA N6 -methyladenine incorporation via adenylate kinase 1 is suppressed by ADAL deaminase-dependent 2'-deoxynucleotide pool sanitation

Intracellular decay of N6 -methyladenine (m6A)-containing RNA potentially induces aberrant N6 -methyl-2'-adenine (6mdA) misincorporation into DNA. Biophysically, misincorporated 6mdA may destabilize the DNA duplex in a manner similar to bona fide methylated 6mdA DNA, thereby affecting DNA replication and transcription. Utilizing heavy stable isotope labeling and ultrasensitive UHPLC-MS/MS assay, we demonstrate that intracellular m6A-RNA decay does not generate free 6mdA species, nor lead to any misincorporated DNA 6mdA in most mammalian cell lines tested, unveiling the existence of a sanitation mechanism that prevents 6mdA misincorporation. Depletion of deaminase ADAL increases the levels of free 6mdA species, concomitant with the presence of DNA-misincorporated 6mdA resulting from intracellular RNA m6A decay, suggesting that ADAL catabolizes 6mdAMP in vivo. Furthermore, we show that the overexpression of adenylate kinase 1 (AK1) promotes 6mdA misincorporation, while AK1 knockdown diminishes 6mdA incorporation, in ADAL-deficient cells. We conclude that ADAL together with other factors (such as MTH1) contributes to 2'-deoxynucleotide pool sanitation in most cells but compromised sanitation (e.g., in NIH3T3 cells) and increased AK1 expression may facilitate aberrant 6mdA incorporation. This sanitation mechanism may provide a framework for the maintenance of the epigenetic 6mdA landscape.

Oncogenic K-Ras suppresses global miRNA function

K-Ras frequently acquires gain-of-function mutations (K-RasG12D being the most common) that trigger significant transcriptomic and proteomic changes to drive tumorigenesis. Nevertheless, oncogenic K-Ras-induced dysregulation of post-transcriptional regulators such as microRNAs (miRNAs) during oncogenesis is poorly understood. Here, we report that K-RasG12D promotes global suppression of miRNA activity, resulting in the upregulation of hundreds of targets. We constructed a comprehensive profile of physiological miRNA targets in mouse colonic epithelium and tumors expressing K-RasG12D using Halo-enhanced Argonaute pull-down. Combining this with parallel datasets of chromatin accessibility, transcriptome, and proteome, we uncovered that K-RasG12D suppressed the expression of Csnk1a1 and Csnk2a1, subsequently decreasing Ago2 phosphorylation at Ser825/829/832/835. Hypo-phosphorylated Ago2 increased binding to mRNAs while reducing its activity to repress miRNA targets. Our findings connect a potent regulatory mechanism of global miRNA activity to K-Ras in a pathophysiological context and provide a mechanistic link between oncogenic K-Ras and the post-transcriptional upregulation of miRNA targets.

Low RNA stability signifies increased post-transcriptional regulation of cell identity genes

Cell identity genes are distinct from other genes with respect to the epigenetic mechanisms to activate their transcription, e.g. by super-enhancers and broad H3K4me3 domains. However, it remains unclear whether their post-transcriptional regulation is also unique. We performed a systematic analysis of transcriptome-wide RNA stability in nine cell types and found that unstable transcripts were enriched in cell identity-related pathways while stable transcripts were enriched in housekeeping pathways. Joint analyses of RNA stability and chromatin state revealed significant enrichment of super-enhancers and broad H3K4me3 domains at the gene loci of unstable transcripts. Intriguingly, the RNA m6A methyltransferase, METTL3, preferentially binds to chromatin at super-enhancers, broad H3K4me3 domains and their associated genes. METTL3 binding intensity is positively correlated with RNA m6A methylation and negatively correlated with RNA stability of cell identity genes, probably due to co-transcriptional m6A modifications promoting RNA decay. Nanopore direct RNA-sequencing showed that METTL3 knockdown has a stronger effect on RNA m6A and mRNA stability for cell identity genes. Our data suggest a run-and-brake model, where cell identity genes undergo both frequent transcription and fast RNA decay to achieve precise regulation of RNA expression.

Variability of the innate immune response is globally constrained by transcriptional bursting

Transcription of almost all mammalian genes occurs in stochastic bursts, however the fundamental control mechanisms that allow appropriate single-cell responses remain unresolved. Here we utilise single cell genomics data and stochastic models of transcription to perform global analysis of the toll-like receptor (TLR)-induced gene expression variability. Based on analysis of more than 2000 TLR-response genes across multiple experimental conditions we demonstrate that the single-cell, gene-by-gene expression variability can be empirically described by a linear function of the population mean. We show that response heterogeneity of individual genes can be characterised by the slope of the mean-variance line, which captures how cells respond to stimulus and provides insight into evolutionary differences between species. We further demonstrate that linear relationships theoretically determine the underlying transcriptional bursting kinetics, revealing different regulatory modes of TLR response heterogeneity. Stochastic modelling of temporal scRNA-seq count distributions demonstrates that increased response variability is associated with larger and more frequent transcriptional bursts, which emerge via increased complexity of transcriptional regulatory networks between genes and different species. Overall, we provide a methodology relying on inference of empirical mean-variance relationships from single cell data and new insights into control of innate immune response variability.

mRNA Regulation by RNA Modifications

Chemical modifications on mRNA represent a critical layer of gene expression regulation. Research in this area has continued to accelerate over the last decade, as more modifications are being characterized with increasing depth and breadth. mRNA modifications have been demonstrated to influence nearly every step from the early phases of transcript synthesis in the nucleus through to their decay in the cytoplasm, but in many cases, the molecular mechanisms involved in these processes remain mysterious. Here, we highlight recent work that has elucidated the roles of mRNA modifications throughout the mRNA life cycle, describe gaps in our understanding and remaining open questions, and offer some forward-looking perspective on future directions in the field.

METTL3 Reduces Oxidative Stress-induced Apoptosis in Presbycusis by Regulating the N6-methyladenosine Level of SIRT1 mRNA

N6-methyl adenosine (m6A) modification is known to play a crucial role in various aging-related diseases. However, its involvement in presbycusis, a type of age-related hearing loss, is not yet clear. We examined the changes in oxidative stress levels in both plasma of presbycusis patients and mice. To determine the expression of m6A and its functional enzymes, we used liquid chromatography tandem-mass spectrometry (LC-MS/MS), enzyme-linked immunosorbent assay (ELISA), and RT-PCR to analyze the total RNA of presbycusis patients blood cells (n = 8). Additionally, we detected the expression of m6A functional enzymes in the cochlea of presbycusis mice using immunohistochemistry. We assessed the effects of m6A methyltransferase METTL3 on SIRT1 protein expression, reactive oxygen species (ROS) levels, and apoptosis in an oxidative stress model of organ of Corti 1 (OC1) cells. To observe the effect on SIRT1 protein expression, we interfered with the m6A recognition protein IGF2BP3 using siRNA. In both presbycusis patients and mice, there was an increased level of oxidative stress in plasma.There was a decrease in the expression of m6A, METTL3, and IGF2BP3 in presbycusis patients blood cells. The expression of METTL3 and IGF2BP3 was also reduced in the cochlea of presbycusis mice. In OC1 cells, METTL3 positively regulated SIRT1 protein levels, while reversely regulated the level of ROS and apoptosis. IGF2BP3 was found to be involved in the regulation of SIRT1 protein expression. In addition, METTL3 may play a protective role in oxidative stress-induced injury of OC1 cells, while both METTL3 and IGF2BP3 cooperatively regulate the level of m6A and the fate of SIRT1 mRNA in OC1 cells.

Nightshift work can induce oxidative DNA damage: a pilot study

BACKGROUND

Regular sleep is very important for human health; however, the short-term and long-term effects of nightshift with sleep deprivation and disturbance on human metabolism, such as oxidative stress, have not been effectively evaluated based on a realistic cohort. We conducted the first long-term follow-up cohort study to evaluate the effect of nightshift work on DNA damage.

METHODS

We recruited 16 healthy volunteers (aged 33 ± 5 years) working night shifts at the Department of Laboratory Medicine at a local hospital. Their matched serum and urine samples were collected at four time points: before, during (twice), and after the nightshift period. The levels of 8-oxo-7,8-dihydroguanosine (8-oxoG) and 8-oxo-7,8-dihydro-2'-deoxyguanosine (8-oxodG), two important nucleic-acid damage markers, were accurately determined based on a robust self-established LC‒MS/MS method. The Mann-Whitney U or Kruskal-Wallis test was used for comparisons, and Pearson's or Spearman's correlation analysis was used to calculate the correlation coefficients.

RESULTS

The levels of serum 8-oxodG, estimated glomerular filtration rate-corrected serum 8-oxodG, and the serum-to-urine 8-oxodG ratio significantly increased during the nightshift period. These levels were significantly higher than pre-nightshift work level even after 1 month of discontinuation, but no such significant change was found for 8-oxoG. Moreover, 8-oxoG and 8-oxodG levels were significantly positively associated with many routine biomarkers, such as total bilirubin and urea levels, and significantly negatively associated with serum lipids, such as total cholesterol levels.

CONCLUSION

The results of our cohort study suggested that working night shifts may increase oxidative DNA damage even after a month of discontinuing nightshift work. Further studies with large-scale cohorts, different nightshift modes, and longer follow-up times are needed to clarify the short- and long-term effects of night shifts on DNA damage and find effective solutions to combat the negative effects.

Viral persistence, reactivation, and mechanisms of long COVID

The COVID-19 global pandemic caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection has infected hundreds of millions of individuals. Following COVID-19 infection, a subset can develop a wide range of chronic symptoms affecting diverse organ systems referred to as post-acute sequelae of SARS-CoV-2 infection (PASC), also known as long COVID. A National Institutes of Health-sponsored initiative, RECOVER: Researching COVID to Enhance Recovery, has sought to understand the basis of long COVID in a large cohort. Given the range of symptoms that occur in long COVID, the mechanisms that may underlie these diverse symptoms may also be diverse. In this review, we focus on the emerging literature supporting the role(s) that viral persistence or reactivation of viruses may play in PASC. Persistence of SARS-CoV-2 RNA or antigens is reported in some organs, yet the mechanism by which they do so and how they may be associated with pathogenic immune responses is unclear. Understanding the mechanisms of persistence of RNA, antigen or other reactivated viruses and how they may relate to specific inflammatory responses that drive symptoms of PASC may provide a rationale for treatment.

Competition between transcription and loop extrusion modulates promoter and enhancer dynamics

The spatiotemporal configuration of genes with distal regulatory elements, and the impact of chromatin mobility on transcription, remain unclear. Loop extrusion is an attractive model for bringing genetic elements together, but how this functionally interacts with transcription is also largely unknown. We combine live tracking of genomic loci and nascent transcripts with molecular dynamics simulations to assess the 4D arrangement of the Sox2 gene and its enhancer, in response to a battery of perturbations. We find that alterations in chromatin mobility, not promoter-enhancer distance, is more informative about transcriptional status. Active elements display more constrained mobility, consistent with confinement within specialized nuclear sites, and alterations in enhancer mobility distinguish poised from transcribing alleles. Strikingly, we find that whereas loop extrusion and transcription factor-mediated clustering contribute to promoter-enhancer proximity, they have antagonistic effects on chromatin dynamics. This provides an experimental framework for the underappreciated role of chromatin dynamics in genome regulation.

Cell-to-cell variability in Myc dynamics drives transcriptional heterogeneity in cancer cells

Cell-to-cell heterogeneity is vital for tumor evolution and survival. How cancer cells achieve and exploit this heterogeneity remains an active area of research. Here, we identify c-Myc as a highly heterogeneously expressed transcription factor and an orchestrator of transcriptional and phenotypic diversity in cancer cells. By monitoring endogenous c-Myc protein in individual living cells, we report the surprising pulsatile nature of c-Myc expression and the extensive cell-to-cell variability in its dynamics. We further show that heterogeneity in c-Myc dynamics leads to variable target gene transcription and that timing of c-Myc expression predicts cell-cycle progression rates and drug sensitivities. Together, our data advocate for a model in which cancer cells increase the heterogeneity of functionally diverse transcription factors such as c-Myc to rapidly survey transcriptional landscapes and survive stress.

Evaluation and Verification of a microRNA Panel Using Quadratic Discriminant Analysis for the Classification of Human Body Fluids in DNA Extracts

There is significant interest in the use of miRNA analysis for forensic body fluid identification. Demonstrated co-extraction and detection in DNA extracts could make the use of miRNAs a more streamlined molecular body fluid identification method than other RNA-based methods. We previously reported a reverse transcription-quantitative PCR (RT-qPCR) panel of eight miRNAs that classified venous and menstrual blood, feces, urine, saliva, semen, and vaginal secretions using a quadratic discriminant analysis (QDA) model with 93% accuracy in RNA extracts. Herein, miRNA expression in DNA extracts from 50 donors of each body fluid were tested using the model. Initially, a classification rate of 87% was obtained, which increased to 92% when three additional miRNAs were added. Body fluid identification was found to be reliable across population samples of mixed ages, ethnicities, and sex, with 72-98% of the unknown samples classifying correctly. The model was then tested against compromised samples and over biological cycles, where classification accuracy varied, depending on the body fluid. In conclusion, we demonstrated the ability to classify body fluids using miRNA expression from DNA extracts, eliminating the need for RNA extraction, greatly reducing evidentiary sample consumption and processing time in forensic laboratories, but acknowledge that compromised semen and saliva samples can fail to classify properly, and mixed sample classification remains untested and may have limitations.

Transcriptional kinetic synergy: A complex landscape revealed by integrating modeling and synthetic biology

Transcription factors (TFs) control gene expression, often acting synergistically. Classical thermodynamic models offer a biophysical explanation for synergy based on binding cooperativity and regulated recruitment of RNA polymerase. Because transcription requires polymerase to transition through multiple states, recent work suggests that "kinetic synergy" can arise through TFs acting on distinct steps of the transcription cycle. These types of synergy are not mutually exclusive and are difficult to disentangle conceptually and experimentally. Here, we model and build a synthetic circuit in which TFs bind to a single shared site on DNA, such that TFs cannot synergize by simultaneous binding. We model mRNA production as a function of both TF binding and regulation of the transcription cycle, revealing a complex landscape dependent on TF concentration, DNA binding affinity, and regulatory activity. We use synthetic TFs to confirm that the transcription cycle must be integrated with recruitment for a quantitative understanding of gene regulation.

Fear Conditioning Leads to Enduring Alterations in RNA Transcripts in Hippocampal Neuropil that are Dependent on EphB2 Forward Signaling

Alterations in mRNA transcription have been associated with changes in brain functions. We wanted to examine if fear conditioning causes long-term changes in transcriptome profiles in the basolateral amygdala (BLA) and hippocampus using RNA-Seq and laser microdissection microscopy. We further aimed to uncover whether these changes are involved in memory formation by monitoring their levels in EphB2^lacZ/lacZ mice, which lack EphB2 forward signaling and can form short-term fear conditioning memory but not long-term fear conditioning memory. We found transcriptome signatures unique to each brain region that are comprise of specific cellular pathways. We also revealed that fear conditioning leads to alterations in mRNAs levels 24 h after training in hippocampal neuropil, but not in hippocampal cell layers or BLA. The two main groups of altered mRNAs encode proteins involved in neuronal transmission, neuronal morphogenesis and neuronal development and the vast majority are known to be enriched in neurons. None of these mRNAs levels were altered by fear conditioning in EphB2^lacZ/lacZ mice, which were also impaired in long-term fear memory. We show here that fear conditioning leads to an enduring alteration in mRNAs levels in hippocampal neuropil that is dependent on processes mediated by EphB2 that are needed for long-term memory formation.

Upregulation of Tribbles decreases body weight and increases sleep duration

Eukaryotic Tribbles proteins are pseudoenzymes that regulate multiple aspects of intracellular signalling. Both Drosophila melanogaster and mammalian members of this family of pseudokinases act as negative regulators of insulin signalling. Mammalian tribbles pseudokinase (TRIB) genes have also been linked to insulin resistance and type 2 diabetes mellitus. Type 2 diabetes mellitus is associated with increased body weight, sleep problems and increased long-term mortality. Here, we investigated how manipulating the expression of Tribbles impacts body weight, sleep and mortality. We showed that the overexpression of Drosophila tribbles (trbl) in the fly fat body reduces both body weight and lifespan in adult flies without affecting food intake. Furthermore, it decreases the levels of Drosophila insulin-like peptide 2 (DILP2; ILP2) and increases night-time sleep. The three genes encoding TRIBs of mammals, TRIB1, TRIB2 and TRIB3, show both common and unique features. As the three human TRIB genes share features with Drosophila trbl, we further explored the links between TRIB genetic variants and both body weight and sleep in the human population. We identified associations between the polymorphisms and expression levels of the pseudokinases and markers of body weight and sleep duration. We conclude that Tribbles pseudokinases are involved in the control of body weight, lifespan and sleep.

Comparative analysis between single-cell RNA-seq and single-molecule RNA FISH indicates that the pyrimidine nucleobase idoxuridine (IdU) globally amplifies transcriptional noise

Stochastic fluctuations (noise) in transcription generate substantial cell-to-cell variability, but the physiological roles of noise have remained difficult to determine in the absence of generalized noise-modulation approaches. Previous single-cell RNA-sequencing (scRNA-seq) suggested that the pyrimidine-base analog (5'-iodo-2'-deoxyuridine, IdU) could generally amplify noise without substantially altering mean-expression levels but scRNA-seq technical drawbacks potentially obscured the penetrance of IdU-induced transcriptional noise amplification. Here we quantify global-vs.-partial penetrance of IdU-induced noise amplification by assessing scRNA-seq data using numerous normalization algorithms and directly quantifying noise using single-molecule RNA FISH (smFISH) for a panel of genes from across the transcriptome. Alternate scRNA-seq analyses indicate IdU-induced noise amplification for ~90% of genes, and smFISH data verified noise amplification for ~90% of tested genes. Collectively, this analysis indicates which scRNA-seq algorithms are appropriate for quantifying noise and argues that IdU is a globally penetrant noise-enhancer molecule that could enable investigations of the physiological impacts of transcriptional noise.

Adolescent binge ethanol impacts H3K36me3 regulation of synaptic genes

Adolescence is marked in part by the ongoing development of the prefrontal cortex (PFC). Binge ethanol use during this critical stage in neurodevelopment induces significant structural changes to the PFC, as well as cognitive and behavioral deficits that can last into adulthood. Previous studies showed that adolescent binge ethanol causes lasting deficits in working memory, decreases in the expression of chromatin remodeling genes responsible for the methylation of histone 3 lysine 36 (H3K36), and global decreases in H3K36 in the PFC. H3K36me3 is present within the coding region of actively-transcribed genes, and safeguards against aberrant, cryptic transcription by RNA Polymerase II. We hypothesize that altered methylation of H3K36 could play a role in adolescent binge ethanol-induced memory deficits. To investigate this at the molecular level, ethanol (4 g/kg, i.g.) or water was administered intermittently to adolescent mice. RNA-and ChIP-sequencing were then performed within the same tissue to determine gene expression changes and identify genes and loci where H3K36me3 was disrupted by ethanol. We further assessed ethanol-induced changes at the transcription level with differential exon-use and cryptic transcription analysis - a hallmark of decreased H3K36me3. Here, we found ethanol-induced changes to the gene expression and H3K36me3-regulation of synaptic-related genes in all our analyses. Notably, H3K36me3 was differentially trimethylated between ethanol and control conditions at synaptic-related genes, and Snap25 and Cplx1 showed evidence of cryptic transcription in males and females treated with ethanol during adolescence. Our results provide preliminary evidence that ethanol-induced changes to H3K36me3 during adolescent neurodevelopment may be linked to synaptic dysregulation at the transcriptional level, which may explain the reported ethanol-induced changes to PFC synaptic function.