High-resolution gene expression profiling for simultaneous kinetic parameter analysis of RNA synthesis and decay

Time-resolved scRNA-seq reveals transcription dynamics of polarized macrophages with influenza A virus infection and antigen presentation to T cells

Throughout history, the influenza A virus has caused numerous devastating global pandemics. Macrophages, as pivotal innate immune cells, exhibit a wide range of immune functions characterized by distinct polarization states, reflecting their intricate heterogeneity. In this study, we employed the time-resolved single-cell sequencing technique coupled with metabolic RNA labelling to elucidate the dynamic transcriptional changes in distinct polarized states of bone marrow-derived macrophages (BMDMs) upon infection with the influenza A virus. Our approach not only captures the temporal dimension of transcriptional activity, which is lacking in conventional scRNA-seq methods, but also reveals that M2-polarized Arg1_macrophage cluster is the sole state supporting successful replication of influenza A virus. Furthermore, we identified distinct antigen presentation capabilities to CD4+ T and CD8+ T cells across diverse polarized states of macrophages. Notably, the M1 phenotype, exhibited by (BMDMs) and murine alveolar macrophages (AMs), demonstrated superior conventional and cross-presentation abilities for exogenous antigens, with a particular emphasis on cross-presentation capacity. Additionally, as CD8+ T cell differentiation progressed, M1 polarization exhibited an enhanced capacity for cross-presentation. All three phenotypes of BMDMs, including M1, demonstrated robust presentation to CD4+ regulatory T cells, while displaying limited ability to present to naive CD4+ T cells. These findings offer novel insights into the immunological regulatory mechanisms governing distinct polarized states of macrophages, particularly their roles in restricting the replication of influenza A virus and modulating antigen-specific T cell responses through innate immunity.

Deep learning and direct sequencing of labeled RNA captures transcriptome dynamics

In eukaryotes, genes produce a variety of distinct RNA isoforms, each with potentially unique protein products, coding potential or regulatory signals such as poly(A) tail and nucleotide modifications. Assessing the kinetics of RNA isoform metabolism, such as transcription and decay rates, is essential for unraveling gene regulation. However, it is currently impeded by lack of methods that can differentiate between individual isoforms. Here, we introduce RNAkinet, a deep convolutional and recurrent neural network, to detect nascent RNA molecules following metabolic labeling with the nucleoside analog 5-ethynyl uridine and long-read, direct RNA sequencing with nanopores. RNAkinet processes electrical signals from nanopore sequencing directly and distinguishes nascent from pre-existing RNA molecules. Our results show that RNAkinet prediction performance generalizes in various cell types and organisms and can be used to quantify RNA isoform half-lives. RNAkinet is expected to enable the identification of the kinetic parameters of RNA isoforms and to facilitate studies of RNA metabolism and the regulatory elements that influence it.

Transcriptional noise, gene activation, and roles of SAGA and Mediator Tail measured using nucleotide recoding single-cell RNA-seq

We describe a time-resolved nascent single-cell RNA sequencing (RNA-seq) approach that measures gene-specific transcriptional noise and the fraction of active genes in S. cerevisiae. Most genes are expressed with near-constitutive behavior, while a subset of genes show high mRNA variance suggestive of transcription bursting. Transcriptional noise is highest in the cofactor/coactivator-redundant (CR) gene class (dependent on both SAGA and TFIID) and strongest in TATA-containing CR genes. Using this approach, we also find that histone gene transcription switches from a low-level, low-noise constitutive mode during M and M/G1 to an activated state in S phase that shows both an increase in the fraction of active promoters and a switch to a noisy and bursty transcription mode. Rapid depletion of cofactors SAGA and MED Tail indicates that both factors play an important role in stimulating the fraction of active promoters at CR genes, with a more modest role in transcriptional noise.

Novel function of U7 snRNA in the repression of HERV1/LTR12s and lincRNAs in human cells

U7 snRNA is part of the U7 snRNP complex, required for the 3' end processing of replication-dependent histone pre-mRNAs in S phase of the cell cycle. Here, we show that U7 snRNA plays another function in inhibiting the expression of a subset of long terminal repeats of human endogenous retroviruses (HERV1/LTR12s) and LTR12-containing long intergenic noncoding RNAs (lincRNAs), both bearing sequence motifs that perfectly match the 5' end of U7 snRNA. We demonstrate that U7 snRNA inhibits LTR12 and lincRNA transcription and propose a mechanism in which U7 snRNA hampers the binding/activity of the NF-Y transcription factor to CCAAT motifs within LTR12 elements. Thereby, U7 snRNA plays a protective role in maintaining the silencing of deleterious genetic elements in selected types of cells.

Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

We present a combinatorial indexing method, PerturbSci-Kinetics, for capturing whole transcriptomes, nascent transcriptomes and single guide RNA (sgRNA) identities across hundreds of genetic perturbations at the single-cell level. Profiling a pooled CRISPR screen targeting various biological processes, we show the gene expression regulation during RNA synthesis, processing and degradation, miRNA biogenesis and mitochondrial mRNA processing, systematically decoding the genome-wide regulatory network that underlies RNA temporal dynamics at scale.

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.

Notch induces transcription by stimulating release of paused RNA Polymerase II

Notch proteins undergo ligand-induced proteolysis to release a nuclear effector that influences a wide range of cellular processes by regulating transcription. Despite years of study, however, how Notch induces the transcription of its target genes remains unclear. Here, we comprehensively examined the response to human Notch1 across a time course of activation using high-resolution genomic assays of chromatin accessibility and nascent RNA production. Our data reveal that Notch induces target gene transcription primarily by releasing paused RNA polymerase II (RNAPII). Moreover, in contrast to prevailing models suggesting that Notch acts by promoting chromatin accessibility, we found that open chromatin was established at Notch-responsive regulatory elements prior to Notch signal induction, through SWI/SNF-mediated remodeling. Together, these studies show that the nuclear response to Notch signaling is dictated by the pre-existing chromatin state and RNAPII distribution at the time of signal activation.

Interferon-Regulated Expression of Cellular Splicing Factors Modulates Multiple Levels of HIV-1 Gene Expression and Replication

Type I interferons (IFN-Is) are pivotal in innate immunity against human immunodeficiency virus I (HIV-1) by eliciting the expression of IFN-stimulated genes (ISGs), which encompass potent host restriction factors. While ISGs restrict the viral replication within the host cell by targeting various stages of the viral life cycle, the lesser-known IFN-repressed genes (IRepGs), including RNA-binding proteins (RBPs), affect the viral replication by altering the expression of the host dependency factors that are essential for efficient HIV-1 gene expression. Both the host restriction and dependency factors determine the viral replication efficiency; however, the understanding of the IRepGs implicated in HIV-1 infection remains greatly limited at present. This review provides a comprehensive overview of the current understanding regarding the impact of the RNA-binding protein families, specifically the two families of splicing-associated proteins SRSF and hnRNP, on HIV-1 gene expression and viral replication. Since the recent findings show specifically that SRSF1 and hnRNP A0 are regulated by IFN-I in various cell lines and primary cells, including intestinal lamina propria mononuclear cells (LPMCs) and peripheral blood mononuclear cells (PBMCs), we particularly discuss their role in the context of the innate immunity affecting HIV-1 replication.

Chemical Synthesis of Modified RNA

Ribonucleic acids (RNAs) play a vital role in living organisms. Many of their cellular functions depend critically on chemical modification. Methods to modify RNA in a controlled manner-both in vitro and in vivo-are thus essential to evaluate and understand RNA biology at the molecular and mechanistic levels. The diversity of modifications, combined with the size and uniformity of RNA (made up of only 4 nucleotides) makes its site-specific modification a challenging task that needs to be addressed by complementary approaches. One such approach is solid-phase RNA synthesis. We discuss recent developments in this field, starting with new protection concepts in the ongoing effort to overcome current size limitations. We continue with selected modifications that have posed significant challenges for their incorporation into RNA. These include deazapurine bases required for atomic mutagenesis to elucidate mechanistic aspects of catalytic RNAs, and RNA containing xanthosine, N4-acetylcytidine, 5-hydroxymethylcytidine, 3-methylcytidine, 2'-OCF3, and 2'-N3 ribose modifications. We also discuss the all-chemical synthesis of 5'-capped mRNAs and the enzymatic ligation of chemically synthesized oligoribonucleotides to obtain long RNA with multiple distinct modifications, such as those needed for single-molecule FRET studies. Finally, we highlight promising developments in RNA-catalyzed RNA modification using cofactors that transfer bioorthogonal functionalities.

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.

Time-resolved profiling of RNA binding proteins throughout the mRNA life cycle

mRNAs continually change their protein partners throughout their lifetimes, yet our understanding of mRNA-protein complex (mRNP) remodeling is limited by a lack of temporal data. Here, we present time-resolved mRNA interactome data by performing pulse metabolic labeling with photoactivatable ribonucleoside in human cells, UVA crosslinking, poly(A)+ RNA isolation, and mass spectrometry. This longitudinal approach allowed the quantification of over 700 RNA binding proteins (RBPs) across ten time points. Overall, the sequential order of mRNA binding aligns well with known functions, subcellular locations, and molecular interactions. However, we also observed RBPs with unexpected dynamics: the transcription-export (TREX) complex recruited posttranscriptionally after nuclear export factor 1 (NXF1) binding, challenging the current view of transcription-coupled mRNA export, and stress granule proteins prevalent in aged mRNPs, indicating roles in late stages of the mRNA life cycle. To systematically identify mRBPs with unknown functions, we employed machine learning to compare mRNA binding dynamics with Gene Ontology (GO) annotations. Our data can be explored at chronology.rna.snu.ac.kr.

Nuclear export is a limiting factor in eukaryotic mRNA metabolism

The eukaryotic mRNA life cycle includes transcription, nuclear mRNA export and degradation. To quantify all these processes simultaneously, we perform thiol-linked alkylation after metabolic labeling of RNA with 4-thiouridine (4sU), followed by sequencing of RNA (SLAM-seq) in the nuclear and cytosolic compartments of human cancer cells. We develop a model that reliably quantifies mRNA-specific synthesis, nuclear export, and nuclear and cytosolic degradation rates on a genome-wide scale. We find that nuclear degradation of polyadenylated mRNA is negligible and nuclear mRNA export is slow, while cytosolic mRNA degradation is comparatively fast. Consequently, an mRNA molecule generally spends most of its life in the nucleus. We also observe large differences in the nuclear export rates of different 3'UTR transcript isoforms. Furthermore, we identify genes whose expression is abruptly induced upon metabolic labeling. These transcripts are exported substantially faster than average mRNAs, suggesting the existence of alternative export pathways. Our results highlight nuclear mRNA export as a limiting factor in mRNA metabolism and gene regulation.

Correcting 4sU induced quantification bias in nucleotide conversion RNA-seq data

Nucleoside analogues like 4-thiouridine (4sU) are used to metabolically label newly synthesized RNA. Chemical conversion of 4sU before sequencing induces T-to-C mismatches in reads sequenced from labelled RNA, allowing to obtain total and labelled RNA expression profiles from a single sequencing library. Cytotoxicity due to extended periods of labelling or high 4sU concentrations has been described, but the effects of extensive 4sU labelling on expression estimates from nucleotide conversion RNA-seq have not been studied. Here, we performed nucleotide conversion RNA-seq with escalating doses of 4sU with short-term labelling (1h) and over a progressive time course (up to 2h) in different cell lines. With high concentrations or at later time points, expression estimates were biased in an RNA half-life dependent manner. We show that bias arose by a combination of reduced mappability of reads carrying multiple conversions, and a global, unspecific underrepresentation of labelled RNA emerging during library preparation and potentially global reduction of RNA synthesis. We developed a computational tool to rescue unmappable reads, which performed favourably compared to previous read mappers, and a statistical method, which could fully remove remaining bias. All methods developed here are freely available as part of our GRAND-SLAM pipeline and grandR package.

Target-directed microRNA degradation: Mechanisms, significance, and functional implications

MicroRNAs (miRNAs) are small non-coding RNAs that play a fundamental role in enabling miRNA-mediated target repression, a post-transcriptional gene regulatory mechanism preserved across metazoans. Loss of certain animal miRNA genes can lead to developmental abnormalities, disease, and various degrees of embryonic lethality. These short RNAs normally guide Argonaute (AGO) proteins to target RNAs, which are in turn translationally repressed and destabilized, silencing the target to fine-tune gene expression and maintain cellular homeostasis. Delineating miRNA-mediated target decay has been thoroughly examined in thousands of studies, yet despite these exhaustive studies, comparatively less is known about how and why miRNAs are directed for decay. Several key observations over the years have noted instances of rapid miRNA turnover, suggesting endogenous means for animals to induce miRNA degradation. Recently, it was revealed that certain targets, so-called target-directed miRNA degradation (TDMD) triggers, can "trigger" miRNA decay through inducing proteolysis of AGO and thereby the bound miRNA. This process is mediated in animals via the ZSWIM8 ubiquitin ligase complex, which is recruited to AGO during engagement with triggers. Since its discovery, several studies have identified that ZSWIM8 and TDMD are indispensable for proper animal development. Given the rapid expansion of this field of study, here, we summarize the key findings that have led to and followed the discovery of ZSWIM8-dependent TDMD. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNAs RNA Turnover and Surveillance > Turnover/Surveillance Mechanisms RNA in Disease and Development > RNA in Development.

Past, present, and future of CRISPR genome editing technologies

Genome editing has been a transformative force in the life sciences and human medicine, offering unprecedented opportunities to dissect complex biological processes and treat the underlying causes of many genetic diseases. CRISPR-based technologies, with their remarkable efficiency and easy programmability, stand at the forefront of this revolution. In this Review, we discuss the current state of CRISPR gene editing technologies in both research and therapy, highlighting limitations that constrain them and the technological innovations that have been developed in recent years to address them. Additionally, we examine and summarize the current landscape of gene editing applications in the context of human health and therapeutics. Finally, we outline potential future developments that could shape gene editing technologies and their applications in the coming years.

Development and Comparison of 4-Thiouridine to Cytidine Base Conversion Reaction

To study transcriptome dynamics without harming cells, it is essential to convert chemical bases. 4-Thiouridine (4sU) is a biocompatible uridine analogue that can be converted into a cytidine analogue. Although several reactions can convert 4sU into a cytidine analogue, few studies have compared the features of these reactions. In this study, we performed three reported base conversion reactions, including osmium tetroxide, iodoacetamide, and sodium periodate treatment, as well as a new reaction using 2,4-dinitrofluorobenzene. We compared the reaction time, conversion efficacy, and effects on reverse transcription. These reactions successfully converted 4sU into a cytidine analogue quantitatively using trinucleotides. However, the conversion efficacy and effect on reverse transcription vary depending on the reaction with the RNA transcript. OsO4 treatment followed by NH4Cl treatment showed the best base-conversion efficiency. Nevertheless, each reaction has its own advantages and disadvantages as a tool for studying the transcriptome. Therefore, it is crucial to select the appropriate reaction for the target of interest.

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

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

The ncBAF Complex Regulates Transcription in AML Through H3K27ac Sensing by BRD9

The non-canonical BAF complex (ncBAF) subunit BRD9 is essential for acute myeloid leukemia (AML) cell viability but has an unclear role in leukemogenesis. Because BRD9 is required for ncBAF complex assembly through its DUF3512 domain, precise bromodomain inhibition is necessary to parse the role of BRD9 as a transcriptional regulator from that of a scaffolding protein. To understand the role of BRD9 bromodomain function in regulating AML, we selected a panel of five AML cell lines with distinct driver mutations, disease classifications, and genomic aberrations and subjected these cells to short-term BRD9 bromodomain inhibition. We examined the bromodomain-dependent growth of these cell lines, identifying a dependency in AML cell lines but not HEK293T cells. To define a mechanism through which BRD9 maintains AML cell survival, we examined nascent transcription, chromatin accessibility, and ncBAF complex binding genome-wide after bromodomain inhibition. We identified extensive regulation of transcription by BRD9 bromodomain activity, including repression of myeloid maturation factors and tumor suppressor genes, while standard AML chemotherapy targets were repressed by inhibition of the BRD9 bromodomain. BRD9 bromodomain activity maintained accessible chromatin at both gene promoters and gene-distal putative enhancer regions, in a manner that qualitatively correlated with enrichment of BRD9 binding. Furthermore, we identified reduced chromatin accessibility at GATA, ETS, and AP-1 motifs and increased chromatin accessibility at SNAIL-, HIC-, and TP53-recognized motifs after BRD9 inhibition. These data suggest a role for BRD9 in regulating AML cell differentiation through modulation of accessibility at hematopoietic transcription factor binding sites.

SIGNIFICANCE

The bromodomain-containing protein BRD9 is essential for AML cell viability, but it is unclear whether this requirement is due to the protein's role as an epigenetic reader. We inhibited this activity and identified altered gene-distal chromatin regulation and transcription consistent with a more mature myeloid cell state.

Late consolidation of rRNA structure during co-transcriptional assembly in E. coli by time-resolved DMS footprinting

The production of new ribosomes requires proper folding of the rRNA and the addition of more than 50 ribosomal proteins. The structures of some assembly intermediates have been determined by cryo-electron microscopy, yet these structures do not provide information on the folding dynamics of the rRNA. To visualize the changes in rRNA structure during ribosome assembly in E. coli cells, transcripts were pulse-labeled with 4-thiouridine and the structure of newly made rRNA probed at various times by dimethyl sulfate modification and mutational profiling sequencing (4U-DMS-MaPseq). The in-cell DMS modification patterns revealed that many long-range rRNA tertiary interactions and protein binding sites through the 16S and 23S rRNA remain partially unfolded 1.5 min after transcription. By contrast, the active sites were continually shielded from DMS modification, suggesting that these critical regions are guarded by cellular factors throughout assembly. Later, bases near the peptidyl tRNA site exhibited specific rearrangements consistent with the binding and release of assembly factors. Time-dependent structure-probing in cells suggests that many tertiary interactions throughout the new ribosomal subunits remain mobile or unfolded until the late stages of subunit maturation.

Lipin-2 regulates the antiviral and anti-inflammatory responses to interferon

Interferons (IFN) are crucial antiviral and immunomodulatory cytokines that exert their function through the regulation of a myriad of genes, many of which are not yet characterized. Here, we reveal that lipin-2, a phosphatidic acid phosphatase whose mutations produce an autoinflammatory syndrome known as Majeed syndrome in humans, is regulated by IFN in a STAT-1-dependent manner. Lipin-2 inhibits viral replication both in vitro and in vivo. Moreover, lipin-2 also acts as a regulator of inflammation in a viral context by reducing the signaling through TLR3 and the generation of ROS and release of mtDNA that ultimately activate the NLRP3 inflammasome. Inhibitors of mtDNA release from mitochondria restrict IL-1β production in lipin-2-deficient animals in a model of viral infection. Finally, analyses of databases from COVID-19 patients show that LPIN2 expression levels negatively correlate with the severity of the disease. Overall, these results uncover novel regulatory mechanisms of the IFN response driven by lipin-2 and open new perspectives for the future management of patients with LPIN2 mutations.

hnRNPA1 SUMOylation promotes cold hypersensitivity in chronic inflammatory pain by stabilizing TRPA1 mRNA

TRPA1 is pivotal in cold hypersensitivity, but its regulatory mechanisms in inflammatory cold hyperalgesia remain poorly understood. We show here that the upregulation of SUMO1-conjugated protein levels in a complete Freund's adjuvant (CFA)-induced inflammatory pain model enhances TRPA1 mRNA stability, ultimately leading to increased expression levels. We further demonstrate that hnRNPA1 binds to TRPA1 mRNA, and its SUMOylation, upregulated in CFA-induced inflammatory pain, contributes to stabilizing TRPA1 mRNA by accumulating hnRNPA1 in the cytoplasm. Moreover, we find that wild-type hnRNPA1 viral infection in dorsal root ganglia neurons, and not infection with the SUMOylation-deficient hnRNPA1 mutant, can rescue the reduced ability of hnRNPA1-knockdown mice to develop inflammatory cold pain hypersensitivity. These results suggest that hnRNPA1 is a regulator of TRPA1 mRNA stability, the capability of which is enhanced upon SUMO1 conjugation at lysine 3 in response to peripheral inflammation, and the increased expression of TRPA1 in turn underlies the development of chronic inflammatory cold pain hypersensitivity.

Deep learning and direct sequencing of labeled RNA captures transcriptome dynamics

Quantification of the dynamics of RNA metabolism is essential for understanding gene regulation in health and disease. Existing methods rely on metabolic labeling of nascent RNAs and physical separation or inference of labeling through PCR-generated mutations, followed by short-read sequencing. However, these methods are limited in their ability to identify transient decay intermediates or co-analyze RNA decay with cis-regulatory elements of RNA stability such as poly(A) tail length and modification status, at single molecule resolution. Here we use 5-ethynyl uridine (5EU) to label nascent RNA followed by direct RNA sequencing with nanopores. We developed RNAkinet, a deep convolutional and recurrent neural network that processes the electrical signal produced by nanopore sequencing to identify 5EU-labeled nascent RNA molecules. RNAkinet demonstrates generalizability to distinct cell types and organisms and reproducibly quantifies RNA kinetic parameters allowing the combined interrogation of RNA metabolism and cis-acting RNA regulatory elements.

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.

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

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

FACT regulates pluripotency through proximal and distal regulation of gene expression in murine embryonic stem cells

BACKGROUND

The FACT complex is a conserved histone chaperone with critical roles in transcription and histone deposition. FACT is essential in pluripotent and cancer cells, but otherwise dispensable for most mammalian cell types. FACT deletion or inhibition can block induction of pluripotent stem cells, yet the mechanism through which FACT regulates cell fate decisions remains unclear.

RESULTS

To explore the mechanism for FACT function, we generated AID-tagged murine embryonic cell lines for FACT subunit SPT16 and paired depletion with nascent transcription and chromatin accessibility analyses. We also analyzed SPT16 occupancy using CUT&RUN and found that SPT16 localizes to both promoter and enhancer elements, with a strong overlap in binding with OCT4, SOX2, and NANOG. Over a timecourse of SPT16 depletion, nucleosomes invade new loci, including promoters, regions bound by SPT16, OCT4, SOX2, and NANOG, and TSS-distal DNaseI hypersensitive sites. Simultaneously, transcription of Pou5f1 (encoding OCT4), Sox2, Nanog, and enhancer RNAs produced from these genes' associated enhancers are downregulated.

CONCLUSIONS

We propose that FACT maintains cellular pluripotency through a precise nucleosome-based regulatory mechanism for appropriate expression of both coding and non-coding transcripts associated with pluripotency.

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

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

bakR: uncovering differential RNA synthesis and degradation kinetics transcriptome-wide with Bayesian hierarchical modeling

Differential expression analysis of RNA sequencing (RNA-seq) data can identify changes in cellular RNA levels, but provides limited information about the kinetic mechanisms underlying such changes. Nucleotide recoding RNA-seq methods (NR-seq; e.g., TimeLapse-seq, SLAM-seq, etc.) address this shortcoming and are widely used approaches to identify changes in RNA synthesis and degradation kinetics. While advanced statistical models implemented in user-friendly software (e.g., DESeq2) have ensured the statistical rigor of differential expression analyses, no such tools that facilitate differential kinetic analysis with NR-seq exist. Here, we report the development of Bayesian analysis of the kinetics of RNA (bakR; https:// github.com/simonlabcode/bakR), an R package to address this need. bakR relies on Bayesian hierarchical modeling of NR-seq data to increase statistical power by sharing information across transcripts. Analyses of simulated data confirmed that bakR implementations of the hierarchical model outperform attempts to analyze differential kinetics with existing models. bakR also uncovers biological signals in real NR-seq data sets and provides improved analyses of existing data sets. This work establishes bakR as an important tool for identifying differential RNA synthesis and degradation kinetics.

grandR: a comprehensive package for nucleotide conversion RNA-seq data analysis

Metabolic labeling of RNA is a powerful technique for studying the temporal dynamics of gene expression. Nucleotide conversion approaches greatly facilitate the generation of data but introduce challenges for their analysis. Here we present grandR, a comprehensive package for quality control, differential gene expression analysis, kinetic modeling, and visualization of such data. We compare several existing methods for inference of RNA synthesis rates and half-lives using progressive labeling time courses. We demonstrate the need for recalibration of effective labeling times and introduce a Bayesian approach to study the temporal dynamics of RNA using snapshot experiments.

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

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

PerturbSci-Kinetics: Dissecting key regulators of transcriptome kinetics through scalable single-cell RNA profiling of pooled CRISPR screens

Here we described PerturbSci-Kinetics, a novel combinatorial indexing method for capturing three-layer single-cell readout (i.e., whole transcriptomes, nascent transcriptomes, sgRNA identities) across hundreds of genetic perturbations. Through PerturbSci-Kinetics profiling of pooled CRISPR screens targeting a variety of biological processes, we were able to decipher the complexity of RNA regulations at multiple levels (e.g., synthesis, processing, degradation), and revealed key regulators involved in miRNA and mitochondrial RNA processing pathways. Our technique opens the possibility of systematically decoding the genome-wide regulatory network underlying RNA temporal dynamics at scale and cost-effectively.

U1 snRNP increases RNA Pol II elongation rate to enable synthesis of long genes

The expansion of introns within mammalian genomes poses a challenge for the production of full-length messenger RNAs (mRNAs), with increasing evidence that these long AT-rich sequences present obstacles to transcription. Here, we investigate RNA polymerase II (RNAPII) elongation at high resolution in mammalian cells and demonstrate that RNAPII transcribes faster across introns. Moreover, we find that this acceleration requires the association of U1 snRNP (U1) with the elongation complex at 5' splice sites. The role of U1 to stimulate elongation rate through introns reduces the frequency of both premature termination and transcriptional arrest, thereby dramatically increasing RNA production. We further show that changes in RNAPII elongation rate due to AT content and U1 binding explain previous reports of pausing or termination at splice junctions and the edge of CpG islands. We propose that U1-mediated acceleration of elongation has evolved to mitigate the risks that long AT-rich introns pose to transcript completion.

Single-molecule imaging reveals translation-dependent destabilization of mRNAs

The relationship between mRNA translation and decay is incompletely understood, with conflicting reports suggesting that translation can either promote decay or stabilize mRNAs. The effect of translation on mRNA decay has mainly been studied using ensemble measurements and global transcription and translation inhibitors, which can have pleiotropic effects. We developed a single-molecule imaging approach to control the translation of a specific transcript that enabled simultaneous measurement of translation and mRNA decay. Our results demonstrate that mRNA translation reduces mRNA stability, and mathematical modeling suggests that this process is dependent on ribosome flux. Furthermore, our results indicate that miRNAs mediate efficient degradation of both translating and non-translating target mRNAs and reveal a predominant role for mRNA degradation in miRNA-mediated regulation. Simultaneous observation of translation and decay of single mRNAs provides a framework to directly study how these processes are interconnected in cells.

Determining RNA Natural Modifications and Nucleoside Analog-Labeled Sites by a Chemical/Enzyme-Induced Base Mutation Principle

The natural chemical modifications of messenger RNA (mRNA) in living organisms have shown essential roles in both physiology and pathology. The mapping of mRNA modifications is critical for interpreting their biological functions. In another dimension, the synthesized nucleoside analogs can enable chemical labeling of cellular mRNA through a metabolic pathway, which facilitates the study of RNA dynamics in a pulse-chase manner. In this regard, the sequencing tools for mapping both natural modifications and nucleoside tags on mRNA at single base resolution are highly necessary. In this work, we review the progress of chemical sequencing technology for determining both a variety of naturally occurring base modifications mainly on mRNA and a few on transfer RNA and metabolically incorporated artificial base analogs on mRNA, and further discuss the problems and prospects in the field.

Rapid nuclear deadenylation of mammalian messenger RNA

Poly(A) tails protect RNAs from degradation and their deadenylation rates determine RNA stability. Although poly(A) tails are generated in the nucleus, deadenylation of tails has mostly been investigated within the cytoplasm. Here, we combined long-read sequencing with metabolic labeling, splicing inhibition and cell fractionation experiments to quantify, separately, the genesis and trimming of nuclear and cytoplasmic tails in vitro and in vivo. We present evidence for genome-wide, nuclear synthesis of tails longer than 200 nt, which are rapidly shortened after transcription. Our data suggests that rapid deadenylation is a nuclear process, and that different classes of transcripts and even transcript isoforms have distinct nuclear tail lengths. For example, many long-noncoding RNAs retain long poly(A) tails. Modeling deadenylation dynamics predicts nuclear deadenylation about 10 times faster than cytoplasmic deadenylation. In summary, our data suggests that nuclear deadenylation might be a key mechanism for regulating mRNA stability, abundance, and subcellular localization.

Computational Integration of HSV-1 Multi-omics Data

Functional genomics techniques based on next-generation sequencing provide new avenues for studying host responses to viral infections at multiple levels, including transcriptional and translational processes and chromatin organization. This chapter provides an overview on the computational integration of multiple types of "omics" data on lytic herpes simplex virus 1 (HSV-1) infection. It summarizes methods developed and applied in two publications that combined 4sU-seq for studying de novo transcription, ribosome profiling for investigating active translation, RNA-seq of subcellular RNA fractions for determining subcellular location of transcripts, and ATAC-seq for profiling chromatin accessibility genome-wide. These studies revealed an unprecedented disruption of transcription termination in HSV-1 infection resulting in widespread read-through transcription beyond poly(A) sites for most but not all host genes. This impacts chromatin architecture by increasing chromatin accessibility selectively in downstream regions of affected genes. In this way, computational integration of multi-omics data identified novel and unsuspected mechanisms at play in lytic HSV-1 infection.

Unscheduled epigenetic modifications cause genome instability and sterility through aberrant R-loops following starvation

During starvation, organisms modify both gene expression and metabolism to adjust to the energy stress. We previously reported that Caenorhabditis elegans lacing AMP-activated protein kinase (AMPK) exhibit transgenerational reproductive defects associated with abnormally elevated trimethylated histone H3 at lysine 4 (H3K4me3) levels in the germ line following recovery from acute starvation. Here, we show that these H3K4me3 marks are significantly increased at promoters, driving aberrant transcription elongation resulting in the accumulation of R-loops in starved AMPK mutants. DNA-RNA immunoprecipitation followed by high-throughput sequencing (DRIP-seq) analysis demonstrated that a significant proportion of the genome was affected by R-loop formation. This was most pronounced in the promoter-transcription start site regions of genes, in which the chromatin was modified by H3K4me3. Like H3K4me3, the R-loops were also found to be heritable, likely contributing to the transgenerational reproductive defects typical of these mutants following starvation. Strikingly, AMPK mutant germ lines show considerably more RAD-51 (the RecA recombinase) foci at sites of R-loop formation, potentially sequestering them from their roles at meiotic breaks or at sites of induced DNA damage. Our study reveals a previously unforeseen role of AMPK in maintaining genome stability following starvation. The downstream effects of R-loops on DNA damage sensitivity and germline stem cell integrity may account for inappropriate epigenetic modification that occurs in numerous human disorders, including various cancers.

PABPC1--mRNA stability, protein translation and tumorigenesis

Mammalian poly A-binding proteins (PABPs) are highly conserved multifunctional RNA-binding proteins primarily involved in the regulation of mRNA translation and stability, of which PABPC1 is considered a central regulator of cytoplasmic mRNA homing and is involved in a wide range of physiological and pathological processes by regulating almost every aspect of RNA metabolism. Alterations in its expression and function disrupt intra-tissue homeostasis and contribute to the development of various tumors. There is increasing evidence that PABPC1 is aberrantly expressed in a variety of tumor tissues and cancers such as lung, gastric, breast, liver, and esophageal cancers, and PABPC1 might be used as a potential biomarker for tumor diagnosis, treatment, and clinical application in the future. In this paper, we review the abnormal expression, functional role, and molecular mechanism of PABPC1 in tumorigenesis and provide directions for further understanding the regulatory role of PABPC1 in tumor cells.

The genetic and biochemical determinants of mRNA degradation rates in mammals

BACKGROUND

Degradation rate is a fundamental aspect of mRNA metabolism, and the factors governing it remain poorly characterized. Understanding the genetic and biochemical determinants of mRNA half-life would enable more precise identification of variants that perturb gene expression through post-transcriptional gene regulatory mechanisms.

RESULTS

We establish a compendium of 39 human and 27 mouse transcriptome-wide mRNA decay rate datasets. A meta-analysis of these data identified a prevalence of technical noise and measurement bias, induced partially by the underlying experimental strategy. Correcting for these biases allowed us to derive more precise, consensus measurements of half-life which exhibit enhanced consistency between species. We trained substantially improved statistical models based upon genetic and biochemical features to better predict half-life and characterize the factors molding it. Our state-of-the-art model, Saluki, is a hybrid convolutional and recurrent deep neural network which relies only upon an mRNA sequence annotated with coding frame and splice sites to predict half-life (r=0.77). The key novel principle learned by Saluki is that the spatial positioning of splice sites, codons, and RNA-binding motifs within an mRNA is strongly associated with mRNA half-life. Saluki predicts the impact of RNA sequences and genetic mutations therein on mRNA stability, in agreement with functional measurements derived from massively parallel reporter assays.

CONCLUSIONS

Our work produces a more robust ground truth for transcriptome-wide mRNA half-lives in mammalian cells. Using these revised measurements, we trained Saluki, a model that is over 50% more accurate in predicting half-life from sequence than existing models. Saluki succinctly captures many of the known determinants of mRNA half-life and can be rapidly deployed to predict the functional consequences of arbitrary mutations in the transcriptome.

Multiomics analysis couples mRNA turnover and translational control of glutamine metabolism to the differentiation of the activated CD4+ T cell

The ZFP36 family of RNA-binding proteins acts post-transcriptionally to repress translation and promote RNA decay. Studies of genes and pathways regulated by the ZFP36 family in CD4⁺ T cells have focussed largely on cytokines, but their impact on metabolic reprogramming and differentiation is unclear. Using CD4⁺ T cells lacking Zfp36 and Zfp36l1, we combined the quantification of mRNA transcription, stability, abundance and translation with crosslinking immunoprecipitation and metabolic profiling to determine how they regulate T cell metabolism and differentiation. Our results suggest that ZFP36 and ZFP36L1 act directly to limit the expression of genes driving anabolic processes by two distinct routes: by targeting transcription factors and by targeting transcripts encoding rate-limiting enzymes. These enzymes span numerous metabolic pathways including glycolysis, one-carbon metabolism and glutaminolysis. Direct binding and repression of transcripts encoding glutamine transporter SLC38A2 correlated with increased cellular glutamine content in ZFP36/ZFP36L1-deficient T cells. Increased conversion of glutamine to α-ketoglutarate in these cells was consistent with direct binding of ZFP36/ZFP36L1 to Gls (encoding glutaminase) and Glud1 (encoding glutamate dehydrogenase). We propose that ZFP36 and ZFP36L1 as well as glutamine and α-ketoglutarate are limiting factors for the acquisition of the cytotoxic CD4⁺ T cell fate. Our data implicate ZFP36 and ZFP36L1 in limiting glutamine anaplerosis and differentiation of activated CD4⁺ T cells, likely mediated by direct binding to transcripts of critical genes that drive these processes.

The industrial genomic revolution: A new era in neuroimmunology

Recent discoveries have highlighted the importance of understanding the complex interactions between the brain and immune systems in health and neurodegenerative disease. In this Primer, we outline single-cell multiomics approaches. Applied to patient samples with rich metadata, functional organoids, and animal models, single-cell studies will facilitate the next big leap in translational neuro-immune research. We believe this will pave the way for reshaping our understanding of the neuro-immune interplay: from descriptive to functional, from broad cell types to effective pathways, spatial organization, biomarkers, and targets, toward a comprehensive mechanistic understanding that will be the impetus for drug discovery and therapeutic breakthroughs. We envision that in the near future, single-cell multiomics technologies, along with the advances in immunotherapy development, will become a major driving force and fully integrated resource in the toolset for the development of therapeutic agents in neuroimmunology, which will revolutionize drug development for treating neurodegenerative diseases.

Robust synthesis of 2'-azido modified RNA from 2'-amino precursors by diazotransfer reaction

Azides are versatile bioorthogonal reporter moieties that are commonly used for site-specific labeling and functionalization of RNA to probe its biology. The preparation of azido modified nucleic acids by solid-phase synthesis is problematic due to the inherent reactivity of P(III) species with azides according to the Staudinger reaction. Various strategies have been developed to bypass this limitation and are often time-consuming, low-yielding and labor-intensive. In particular, the synthesis of RNA with internal 2'-azido modifications is restricted to a single approach that employs P(V) chemistry instead of the widely used P(III) phosphoramidite chemistry. To fill this methodological gap, we present a novel convenient path toward 2'-azido RNA from readily accessible 2'-amino RNA through treatment with the diazotizing reagent fluorosulfuryl azide (FSO₂N₃). A diazotransfer reaction was established for oligoribonucleotides of different lengths and secondary structures. The robustness of the approach was further demonstrated for RNAs containing multiple 2'-azido moieties and for RNAs containing other sensitive modifications such as thiouridine or methylated nucleobases with a positive charge. The synthetic ease of generating 2'-azido RNA will pave the way for biotechnological applications, in particular for siRNA technologies and for referencing the growing number of RNA metabolic labeling approaches that rely on 2'-azido nucleosides.

Transcript-specific determinants of pre-mRNA splicing revealed through in vivo kinetic analyses of the 1st and 2nd chemical steps

We generate high-precision measurements of the in vivo rates of both chemical steps of pre-mRNA splicing across the genome-wide complement of substrates in yeast by coupling metabolic labeling, multiplexed primer-extension sequencing, and kinetic modeling. We demonstrate that the rates of intron removal vary widely, splice-site sequences are primary determinants of 1st step but have little apparent impact on 2nd step rates, and the 2nd step is generally faster than the 1st step. Ribosomal protein genes (RPGs) are spliced faster than non-RPGs at each step, and RPGs share evolutionarily conserved properties that may contribute to their faster splicing. A genetic variant defective in the 1st step of the pathway reveals a genome-wide defect in the 1st step but an unexpected, transcript-specific change in the 2nd step. Our work demonstrates that extended co-transcriptional association is an important determinant of splicing rate, a conclusion at odds with recent claims of ultra-fast splicing.

Geneticin reduces mRNA stability

Messenger RNA (mRNA) translation can lead to higher rates of mRNA decay, suggesting the ribosome plays a role in mRNA destruction. Furthermore, mRNA features, such as codon identities, which are directly probed by the ribosome, correlate with mRNA decay rates. Many amino acids are encoded by synonymous codons, some of which are decoded by more abundant tRNAs leading to more optimal translation and increased mRNA stability. Variable translation rates for synonymous codons can lead to ribosomal collisions as ribosomes transit regions with suboptimal codons, and ribosomal collisions can promote mRNA decay. In addition to different translation rates, the presence of certain codons can also lead to higher or lower rates of amino acid misincorporation which could potentially lead to protein misfolding if a substituted amino acid fails to make critical contacts in a structure. Here, we test whether Geneticin—G418, an aminoglycoside antibiotic known to promote amino acid misincorporation—affects mRNA stability. We observe that G418 decreases firefly luciferase mRNA stability in an in vitro translation system and also reduces mRNA stability in mouse embryonic stem cells (mESCs). G418-sensitive mRNAs are enriched for certain optimal codons that contain G or C in the wobble position, arguing that G418 blunts the stabilizing effects of codon optimality.

Regulation of both transcription and RNA turnover contribute to germline specification

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

The Analysis of the Human Megakaryocyte and Platelet Coding Transcriptome in Healthy and Diseased Subjects

Platelets are generated and released into the bloodstream from their precursor cells, megakaryocytes that reside in the bone marrow. Though platelets have no nucleus or DNA, they contain a full transcriptome that, during platelet formation, is transported from the megakaryocyte to the platelet. It has been described that transcripts in platelets can be translated into proteins that influence platelet response. The platelet transcriptome is highly dynamic and has been extensively studied using microarrays and, more recently, RNA sequencing (RNA-seq) in relation to diverse conditions (inflammation, obesity, cancer, pathogens and others). In this review, we focus on bulk and single-cell RNA-seq studies that have aimed to characterize the coding transcriptome of healthy megakaryocytes and platelets in humans. It has been noted that bulk RNA-seq has limitations when studying in vitro-generated megakaryocyte cultures that are highly heterogeneous, while single-cell RNA-seq has not yet been applied to platelets due to their very limited RNA content. Next, we illustrate how these methods can be applied in the field of inherited platelet disorders for gene discovery and for unraveling novel disease mechanisms using RNA from platelets and megakaryocytes and rare disease bioinformatics. Next, future perspectives are discussed on how this field of coding transcriptomics can be integrated with other next-generation technologies to decipher unexplained inherited platelet disorders in a multiomics approach.

Mpe1 senses the binding of pre-mRNA and controls 3' end processing by CPF

Most eukaryotic messenger RNAs (mRNAs) are processed at their 3' end by the cleavage and polyadenylation specificity factor (CPF/CPSF). CPF mediates the endonucleolytic cleavage of the pre-mRNA and addition of a polyadenosine (poly(A)) tail, which together define the 3' end of the mature transcript. The activation of CPF is highly regulated to maintain the fidelity of RNA processing. Here, using cryo-EM of yeast CPF, we show that the Mpe1 subunit directly contacts the polyadenylation signal sequence in nascent pre-mRNA. The region of Mpe1 that contacts RNA also promotes the activation of CPF endonuclease activity and controls polyadenylation. The Cft2 subunit of CPF antagonizes the RNA-stabilized configuration of Mpe1. In vivo, the depletion or mutation of Mpe1 leads to widespread defects in transcription termination by RNA polymerase II, resulting in transcription interference on neighboring genes. Together, our data suggest that Mpe1 plays a major role in accurate 3' end processing, activating CPF, and ensuring timely transcription termination.

Functional RNA Dynamics Are Progressively Governed by RNA Destabilization during the Adaptation to Chronic Hypoxia

Previous studies towards reduced oxygen availability have mostly focused on changes in total mRNA expression, neglecting underlying transcriptional and post-transcriptional events. Therefore, we generated a comprehensive overview of hypoxia-induced changes in total mRNA expression, global de novo transcription, and mRNA stability in monocytic THP-1 cells. Since hypoxic episodes often persist for prolonged periods, we further compared the adaptation to acute and chronic hypoxia. While total mRNA changes correlated well with enhanced transcription during short-term hypoxia, mRNA destabilization gained importance under chronic conditions. Reduced mRNA stability not only added to a compensatory attenuation of immune responses, but also, most notably, to the reduction in nuclear-encoded mRNAs associated with various mitochondrial functions. These changes may prevent the futile production of new mitochondria under conditions where mitochondria cannot exert their full metabolic function and are indeed actively removed by mitophagy. The post-transcriptional mode of regulation might further allow for the rapid recovery of mitochondrial capacities upon reoxygenation. Our results provide a comprehensive resource of functional mRNA expression dynamics and underlying transcriptional and post-transcriptional regulatory principles during the adaptation to hypoxia. Furthermore, we uncover that RNA stability regulation controls mitochondrial functions in the context of hypoxia.

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

Background

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

Methods

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

Results

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

Conclusions

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

Supplementary Information

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

A bifunctional chemical signature enabling RNA 4-thiouridine enrichment sequencing with single-base resolution

Both sequence enrichment and base resolution are essential for accurate sequencing analysis of low-abundance RNA. Yet they are hindered by the lack of molecular tools. Here we report a bifunctional chemical signature for RNA 4-thiouridine (4sU) enrichment sequencing with single-base resolution. This chemical signature is designed for specific 4sU labeling with two functional parts. One part is a distal alkynyl group for the biotin-assisted pulldown enrichment of target molecules via click chemistry crosslinking. The other part is a -NH group proximal to the pyrimidine ring of 4sU. It allows 4sU-to-cytosine transition during the polymerase-catalyzed extension reaction based on altering hydrogen-bonding patterns. Ultimately, the 4sU-containing RNA molecules can be enriched and accurately analyzed by single-base resolution sequencing. The proposed method also holds great potential to investigate transcriptome dynamics integrated with high-throughput sequencing.