Nuclear Retention of mRNA in Mammalian Tissues

Regulation of RNA polymerase II transcription through re-initiation and bursting

The regulation of RNA polymerase II (RNAPII) activity requires orchestrated responses among genomic regulatory sequences and an expansive set of proteins and protein complexes. Despite intense study over five decades, mechanistic insights continue to emerge. Within the past 10 years, live-cell imaging and single-cell transcriptomics experiments have yielded new information about enhancer-promoter communication, transcription factor dynamics, and the kinetics of RNAPII transcription activation. These insights have established RNAPII re-initiation and bursting as a common regulatory phenomenon with widespread implications for gene regulation in health and disease. Here, we summarize regulatory strategies that help control RNAPII bursting in eukaryotic cells, which is defined as short periods of active transcription followed by longer periods of inactivity. We focus on RNAPII re-initiation (i.e., a "burst" of two or more polymerases that initiate from the same promoter), with an emphasis on molecular mechanisms, open questions, and controversies surrounding this distinct regulatory stage.

Exploring the central dogma through the lens of gene expression noise

Over the past two decades, cell-to-cell heterogeneity has garnered increasing attention due to its critical role in both developmental and pathological processes. This growing interest has been driven, in part, by the advancements in live-cell and single-molecule imaging techniques. These techniques have provided mechanistic insights into how processes, transcription in particular, contribute to gene expression noise and, ultimately, cell-to-cell heterogeneity. More recently, however, research has expanded to explore how downstream steps in the central dogma influence gene expression noise. In this review, we mostly examine the impact of transcriptional processes on the generation of gene expression noise but also discuss how post-transcriptional mechanisms modulate noise and its propagation to the protein level. This evaluation emphasizes the need for further investigation into how processes beyond transcription shape gene expression noise, highlighting unanswered questions that remain in the field.

Spatial genomics: Mapping the landscape of fibrosis

Organ fibrosis causes major morbidity and mortality worldwide. Treatments for fibrosis are limited, with organ transplantation being the only cure. Here, we review how various state-of-the-art spatial genomics approaches are being deployed to interrogate fibrosis across multiple organs, providing exciting insights into fibrotic disease pathogenesis. These include the detailed topographical annotation of pathogenic cell populations and states, detection of transcriptomic perturbations in morphologically normal tissue, characterization of fibrotic and homeostatic niches and their cellular constituents, and in situ interrogation of ligand-receptor interactions within these microenvironments. Together, these powerful readouts enable detailed analysis of fibrosis evolution across time and space.

Single-cell analyses reveal increased gene expression variability in human neurodevelopmental conditions

Interindividual variation in phenotypic penetrance and severity is found in many neurodevelopmental conditions, although the underlying mechanisms remain largely unresolved. Within individuals, homogeneous cell types (i.e., genetically identical and in similar environments) can differ in molecule abundance. Here, we investigate the hypothesis that neurodevelopmental conditions can drive increased variability in gene expression, not just differential gene expression. Leveraging independent single-cell and single-nucleus RNA sequencing datasets derived from human brain-relevant cell and tissue types, we identify a significant increase in gene expression variability driven by the autosomal aneuploidy trisomy 21 (T21) as well as autism-associated chromodomain helicase DNA binding protein 8 (CHD8) haploinsufficiency. Our analyses are consistent with a global and, in part, stochastic increase in variability, which is uncoupled from changes in transcript abundance. Highly variable genes tend to be cell-type specific with modest enrichment for repressive H3K27me3, while least variable genes are more likely to be constrained and associated with active histone marks. Our results indicate that human neurodevelopmental conditions can drive increased gene expression variability in brain cell types, with the potential to contribute to diverse phenotypic outcomes. These findings also provide a scaffold for understanding variability in disease, essential for deeper insights into genotype-phenotype relationships.

Intron Retention, an Orchestrated Program of Gene Expression Regulation

Intron retention (IR), a well-conserved form of alternative splicing, is widespread among eukaryotic organisms. It serves as an orchestrated program for regulating gene expression. A previously reported role of IR is to induce intron-retained transcript (IRT) degradation via the nonsense-mediated mRNA decay (NMD) pathway, resulting in the downregulation of gene expression. However, accumulating evidence indicates that most IRTs are detained in the nucleus, and thus, IR can downregulate gene expression through the storage of IRTs in the nucleus. Although the importance of IRTs in gene expression regulation is well established, the detailed mechanisms remain unclear. Here, we propose a potential model to explain how IRTs are retained in the nucleus and respond to environmental changes or developmental transitions. Plenty of future studies are still ahead of us to fully dissect the biological function of IR and the underlying mechanisms.

The ATP-dependent DEAD-box RNA helicase Dbp2 regulates the glucose/nitrogen stress response in baker's yeast by modulating reversible nuclear retention and decay of SKS1 mRNA

In Saccharomyces cerevisiae, SKS1 mRNA encoding a glucose-sensing serine/threonine kinase belongs to "nucleus-retained" (NR) mRNAs representing a subset of otherwise normal transcripts, which exhibits slow nuclear export and excessively long nuclear dwell time. Nuclear retention of the SKS1 mRNA triggered by a 202 nt "export-retarding" nuclear zip code element promotes its rapid degradation in the nucleus by the nuclear exosome/CTEXT. In this investigation, we demonstrate that Dbp2p, an ATP-dependent DEAD-box RNA helicase binds to SKS1 and other NR-mRNAs and thereby inhibits their export by antagonizing with the binding of the export factors Mex67p/Yra1p. Consistent with this observation, a significant portion of these NR-mRNAs was found to localize into the cytoplasm in a yeast strain carrying a deletion in the DBP2 gene with the concomitant enhancement of its steady-state level and stability. This observation supports the view that Dbp2p promotes the nuclear retention of NR-mRNAs to trigger their subsequent nuclear degradation. Further analysis revealed that Dbp2p-dependent nuclear retention of SKS1 mRNA is reversible, which plays a crucial role in the adaptability and viability of the yeast cells in low concentrations of glucose/nitrogen in the growth medium. At high nutrient levels when the function of Sks1p is not necessary, SKS1 mRNA is retained in the nucleus and degraded. In contrast, during low glucose/nitrogen levels when Sks1p is vital to respond to such situations, the nuclear retention of SKS1 mRNA is relieved to permit its increased nuclear export and translation leading to a huge burst of cytoplasmic Sks1p.

An atlas of RNA-dependent proteins in cell division reveals the riboregulation of mitotic protein-protein interactions

Ribonucleoprotein complexes are dynamic assemblies of RNA with RNA-binding proteins, which modulate the fate of RNA. Inversely, RNA riboregulates the interactions and functions of the associated proteins. Dysregulation of ribonucleoprotein functions is linked to diseases such as cancer and neurological disorders. In dividing cells, RNA and RNA-binding proteins are present in mitotic structures, but their impact on cell division remains unclear. By applying the proteome-wide R-DeeP strategy to cells synchronized in mitosis versus interphase integrated with the RBP2GO knowledge, we provided an atlas of RNA-dependent proteins in cell division, accessible at R-DeeP3.dkfz.de. We uncovered AURKA, KIFC1 and TPX2 as unconventional RNA-binding proteins. KIFC1 was identified as a new substrate of AURKA, and new TPX2-interacting protein. Their pair-wise interactions were RNA dependent. In addition, RNA stimulated AURKA kinase activity and stabilized its conformation. In this work, we highlighted riboregulation of major mitotic factors as an additional complexity level of cell division.

Seq-Scope: repurposing Illumina sequencing flow cells for high-resolution spatial transcriptomics

Spatial transcriptomics technologies aim to advance gene expression studies by profiling the entire transcriptome with intact spatial information from a single histological slide. However, the application of spatial transcriptomics is limited by low resolution, limited transcript coverage, complex procedures, poor scalability and high costs of initial setup and/or individual experiments. Seq-Scope repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, overcoming these limitations. It offers submicrometer resolution, high capture efficiency, rapid turnaround time and precise annotation of histopathology at a much lower cost than commercial alternatives. This protocol details the implementation of Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell, allowing the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. We describe the preparation of a fresh-frozen tissue section for both histological imaging and sequencing library preparation and provide a streamlined computational pipeline with comprehensive instructions to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single-cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Aside from array production and sequencing, which can be done in batches, tissue processing, library preparation and running the computational pipeline can be completed within 3 days by researchers with experience in molecular biology, histology and basic Unix skills. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.

A statistical framework for quantifying the nuclear export rate of influenza viral mRNAs

Influenza A virus transcribes viral mRNAs from the eight segmented viral genome when it infects. The kinetics of viral transcription, nuclear export of viral transcripts, and their potential variation between the eight segments are poorly characterised. Here, we introduce a statistical framework for estimating the nuclear export rate of each segment from a snapshot of in situ mRNA localisation. This exploits the cell-to-cell variation at a single time point observed by an imaging-based in situ transcriptome assay. Using our model, we revealed the variation in the mRNA nuclear export rate of the eight viral segments. Notably, the two influenza viral antigens hemagglutinin and neuraminidase were the slowest segments in the nuclear export, suggesting the possibility that influenza A virus uses the nuclear retention of viral transcripts to delay the expression of antigenic molecules. Our framework presented in this study can be widely used for investigating the nuclear retention of nascent transcripts produced in a transcription burst.

Multimodal screen identifies noise-regulatory proteins

Gene-expression noise can influence cell-fate choices across pathology and physiology. However, a crucial question persists: do regulatory proteins or pathways exist that control noise independently of mean expression levels? Our integrative approach, combining single-cell RNA sequencing with proteomics and regulator enrichment analysis, identifies 32 putative noise regulators. SON, a nuclear speckle-associated protein, alters transcriptional noise without changing mean expression levels. Furthermore, SON's noise control can propagate to the protein level. Long-read and total RNA sequencing shows that SON's noise control does not significantly change isoform usage or splicing efficiency. Moreover, SON depletion reduces state switching in pluripotent mouse embryonic stem cells and impacts their fate choice during differentiation. Collectively, we demonstrate a class of proteins that control noise orthogonally to mean expression levels. This work serves as a proof of concept that can identify other functional noise regulators throughout development and disease progression.

Phosphorylation of a nuclear condensate regulates cohesion and mRNA retention

Nuclear speckles are membraneless organelles that associate with active transcription sites and participate in post-transcriptional mRNA processing. During the cell cycle, nuclear speckles dissolve following phosphorylation of their protein components. Here, we identify the PP1 family as the phosphatases that counteract kinase-mediated dissolution. PP1 overexpression increases speckle cohesion and leads to retention of mRNA within speckles and the nucleus. Using APEX2 proximity labeling combined with RNA-sequencing, we characterize the recruitment of specific RNAs. We find that many transcripts are preferentially enriched within nuclear speckles compared to the nucleoplasm, particularly chromatin- and nucleus-associated transcripts. While total polyadenylated RNA retention increases with nuclear speckle cohesion, the ratios of most mRNA species to each other are constant, indicating non-selective retention. We further find that cellular responses to heat shock, oxidative stress, and hypoxia include changes to the phosphorylation and cohesion of nuclear speckles and to mRNA retention. Our results demonstrate that tuning the material properties of nuclear speckles provides a mechanism for the acute control of mRNA localization.

Detection and Automated Quantification of Nucleocytoplasmic RNA Fractions in Arabidopsis Using smFISH

Subcellular RNA localization is an underexplored regulatory layer crucial for properly adapting cells to cellular or environmental conditions. Most studies describing RNA localization have been performed by cell fractionation and subsequent RNA quantification from pools of cells, thereby missing information about cell-to-cell variability. RNA single-molecule fluorescent in situ hybridization (smFISH) is an effective technique for detecting single RNA molecules and identifying subcellular accumulation patterns. Nevertheless, obtaining quantitative results from smFISH can be challenging in tissues with high autofluorescence, like in plants. Here, we describe an automated pipeline to detect and quantify nucleocytoplasmic RNA levels from Arabidopsis root smFISH images. This pipeline utilizes free image preprocessing, segmentation, and RNA detection software. The method permits users with any programming skills to analyze batches of images. Suggestions and recommendations for image acquisition, processing, and data analysis are included. This pipeline allows quantitative differences in nucleocytoplasmic distribution at the single-cell level to be studied under different cellular, environmental, and genetic contexts.

Gene expression patterns of the LDL receptor and its inhibitor Pcsk9 in the adult zebrafish brain suggest a possible role in neurogenesis

The low-density lipoprotein receptor (LDLr) is the first member of a closely related transmembrane protein family. It is known for its involvement in various physiological processes, mainly in the regulation of lipid metabolism, especially in the brains of mammals and zebrafish. In zebrafish, two ldlr genes (ldlra and b) have been identified and their distribution in the brain is not well documented. Recently, the roles of ldlr and its inhibitor pcsk9 in regenerative process after telencephalic brain injury have been discussed. In this study, we explored the expression patterns of these genes during zebrafish development. We found that ldlra expression was detected at the end of the pharyngula period (48 hpf) and increased during the larval stage. Conversely, ldlrb expression was observed from zygotic to larval stages. Using techniques like in situ hybridization and taking advantage of transgenic fish, we demonstrated the widespread distribution of ldlra, ldlrb and pcsk9 in the brain of adult zebrafish. Specifically, these genes were expressed in neurons and neural stem cells and also at lower levels in endothelial cells. As expected, intraperitoneal injection of fluorescent-labelled LDLs resulted in their uptake by cerebral endothelial cells in a homeostatic context, whereas they diffused within the brain parenchyma after telencephalic injury. However, after intracerebroventricular injections into animals, LDL particles were not taken up by neural stem cells. In conclusion, our results provide additional evidence for LDLr expression in the brain of adult zebrafish. These results raise the question of the role of LDLr in the cholesterol/lipid imbalance in cerebral complications.

Modeling of mRNA deadenylation rates reveal a complex relationship between mRNA deadenylation and decay

Complete cytoplasmic polyadenosine tail (polyA-tail) deadenylation is thought to be essential for initiating mRNA decapping and subsequent degradation. To investigate this prevalent model, we conducted direct RNA sequencing of S. cerevisiae mRNAs derived from chase experiments under steady-state and stress condition. Subsequently, we developed a numerical model based on a modified gamma distribution function, which estimated the transcriptomic deadenylation rate at 10 A/min. A simplified independent method, based on the delineation of quantile polyA-tail values, showed a correlation between the decay and deadenylation rates of individual mRNAs, which appeared consistent within functional transcript groups and associated with codon optimality. Notably, these rates varied during the stress response. Detailed analysis of ribosomal protein-coding mRNAs (RPG mRNAs), constituting 40% of the transcriptome, singled out this transcript group. While deadenylation and decay of RPG mRNAs accelerated under heat stress, their degradation could proceed even when deadenylation was blocked, depending entirely on ongoing nuclear export. Our findings support the general primary function of deadenylation in dictating the onset of decapping, while also demonstrating complex relations between these processes.

Subcellular mRNA kinetic modeling reveals nuclear retention as rate-limiting

Eukaryotic mRNAs are transcribed, processed, translated, and degraded in different subcellular compartments. Here, we measured mRNA flow rates between subcellular compartments in mouse embryonic stem cells. By combining metabolic RNA labeling, biochemical fractionation, mRNA sequencing, and mathematical modeling, we determined the half-lives of nuclear pre-, nuclear mature, cytosolic, and membrane-associated mRNAs from over 9000 genes. In addition, we estimated transcript elongation rates. Many matured mRNAs have long nuclear half-lives, indicating nuclear retention as the rate-limiting step in the flow of mRNAs. In contrast, mRNA transcripts coding for transcription factors show fast kinetic rates, and in particular short nuclear half-lives. Differentially localized mRNAs have distinct rate constant combinations, implying modular regulation. Membrane stability is high for membrane-localized mRNA and cytosolic stability is high for cytosol-localized mRNA. mRNAs encoding target signals for membranes have low cytosolic and high membrane half-lives with minor differences between signals. Transcripts of nuclear-encoded mitochondrial proteins have long nuclear retention and cytoplasmic kinetics that do not reflect co-translational targeting. Our data and analyses provide a useful resource to study spatiotemporal gene expression regulation.

Dynamic changes in mRNA nucleocytoplasmic localization in the nitrate response of Arabidopsis roots

Nitrate is a nutrient and signal that regulates gene expression. The nitrate response has been extensively characterized at the organism, organ, and cell-type-specific levels, but intracellular mRNA dynamics remain unexplored. To characterize nuclear and cytoplasmic transcriptome dynamics in response to nitrate, we performed a time-course expression analysis after nitrate treatment in isolated nuclei, cytoplasm, and whole roots. We identified 402 differentially localized transcripts (DLTs) in response to nitrate treatment. Induced DLT genes showed rapid and transient recruitment of the RNA polymerase II, together with an increase in the mRNA turnover rates. DLTs code for genes involved in metabolic processes, localization, and response to stimulus indicating DLTs include genes with relevant functions for the nitrate response that have not been previously identified. Using single-molecule RNA FISH, we observed early nuclear accumulation of the NITRATE REDUCTASE 1 (NIA1) transcripts in their transcription sites. We found that transcription of NIA1, a gene showing delayed cytoplasmic accumulation, is rapidly and transiently activated; however, its transcripts become unstable when they reach the cytoplasm. Our study reveals the dynamic localization of mRNAs between the nucleus and cytoplasm as an emerging feature in the temporal control of gene expression in response to nitrate treatment in Arabidopsis roots.

From Cell to Gene: Deciphering the Mechanism of Heart Failure With Single-Cell Sequencing

Heart failure (HF) is a prevalent cardiovascular disease with significant morbidity and mortality rates worldwide. Due to the intricate structure of the heart, diverse cell types, and the complex pathogenesis of HF, further in-depth investigation into the underlying mechanisms  is required. The elucidation of the heterogeneity of cardiomyocytes and the intercellular communication network is particularly important. Traditional high-throughput sequencing methods provide an average measure of gene expression, failing to capture the "heterogeneity" between cells and impacting the accuracy of gene function knowledge. In contrast, single-cell sequencing techniques allow for the amplification of the entire genome or transcriptome at the individual cell level, facilitating the examination of gene structure and expression with unparalleled precision. This approach offers valuable insights into disease mechanisms, enabling the identification of changes in cellular components and gene expressions during hypertrophy associated with HF. Moreover, it reveals distinct cell populations and their unique roles in the HF microenvironment, providing a comprehensive understanding of the cellular landscape that underpins HF pathogenesis. This review focuses on the insights provided by single-cell sequencing techniques into the mechanisms underlying HF and discusses the challenges encountered in current cardiovascular research.

An atlas of RNA-dependent proteins in cell division reveals the riboregulation of mitotic protein-protein interactions

Ribonucleoprotein complexes are dynamic assemblies of RNA with RNA-binding proteins (RBPs), which can modulate the fate of the RNA molecules from transcription to degradation. Vice versa, RNA can regulate the interactions and functions of the associated proteins. Dysregulation of RBPs is linked to diseases such as cancer and neurological disorders. RNA and RBPs are present in mitotic structures like the centrosomes and spindle microtubules, but their influence on mitotic spindle integrity remains unknown. Thus, we applied the R-DeeP strategy for the proteome-wide identification of RNA-dependent proteins and complexes to cells synchronized in mitosis versus interphase. The resulting atlas of RNA-dependent proteins in cell division can be accessed through the R-DeeP 3.0 database (R-DeeP3.dkfz.de). It revealed key mitotic factors as RNA-dependent such as AURKA, KIFC1 and TPX2 that were linked to RNA despite their lack of canonical RNA-binding domains. KIFC1 was identified as a new interaction partner and phosphorylation substrate of AURKA at S349 and T359. In addition, KIFC1 interacted with both, AURKA and TPX2, in an RNA-dependent manner. Our data suggest a riboregulation of mitotic protein-protein interactions during spindle assembly, offering new perspectives on the control of cell division processes by RNA-protein complexes.

ELLA: Modeling Subcellular Spatial Variation of Gene Expression within Cells in High-Resolution Spatial Transcriptomics

Spatial transcriptomic technologies are becoming increasingly high-resolution, enabling precise measurement of gene expression at the subcellular level. Here, we introduce a computational method called subcellular expression localization analysis (ELLA), for modeling the subcellular localization of mRNAs and detecting genes that display spatial variation within cells in high-resolution spatial transcriptomics. ELLA creates a unified cellular coordinate system to anchor diverse cell shapes and morphologies, utilizes a nonhomogeneous Poisson process to model spatial count data, leverages an expression gradient function to characterize subcellular expression patterns, and produces effective control of type I error and high statistical power. We illustrate the benefits of ELLA through comprehensive simulations and applications to four spatial transcriptomics datasets from distinct technologies, where ELLA not only identifies genes with distinct subcellular localization patterns but also associates these patterns with unique mRNA characteristics. Specifically, ELLA shows that genes enriched in the nucleus exhibit an abundance of long noncoding RNAs or protein-coding mRNAs, often characterized by longer gene lengths. Conversely, genes containing signal recognition peptides, encoding ribosomal proteins, or involved in membrane related activities tend to enrich in the cytoplasm or near the cellular membrane. Furthermore, ELLA reveals dynamic subcellular localization patterns during the cell cycle, with certain genes showing decreased nuclear enrichment in the G1 phase while others maintain their enrichment patterns throughout the cell cycle. Overall, ELLA represents a calibrated, powerful, robust, scalable, and versatile tool for modeling subcellular spatial expression variation across diverse high-resolution spatial transcriptomic platforms.

Mapping the cellular expression patterns of vascular endothelial growth factor aa and bb genes and their receptors in the adult zebrafish brain during constitutive and regenerative neurogenesis

The complex interplay between vascular signaling and neurogenesis in the adult brain remains a subject of intense research. By exploiting the unique advantages of the zebrafish model, in particular the persistent activity of neural stem cells (NSCs) and the remarkable ability to repair brain lesions, we investigated the links between NSCs and cerebral blood vessels. In this study, we first examined the gene expression profiles of vascular endothelial growth factors aa and bb (vegfaa and vegfbb), under physiological and regenerative conditions. Employing fluorescence in situ hybridization combined with immunostaining and histology techniques, we demonstrated the widespread expression of vegfaa and vegfbb across the brain, and showed their presence in neurons, microglia/immune cells, endothelial cells and NSCs. At 1 day post-lesion (dpl), both vegfaa and vegfbb were up-regulated in neurons and microglia/peripheral immune cells (macrophages). Analysis of vegf receptors (vegfr) revealed high expression throughout the brain under homeostatic conditions, with vegfr predominantly expressed in neurons and NSCs and to a lower extent in microglia/immune cells and endothelial cells. These findings were further validated by Vegfr3 and Vegfr4 immunostainings, which showed significant expression in neurogenic radial glial cells.Following brain lesion (1 dpl), while vegfr gene expression remained stable, vegfr transcripts were detected in proliferative cells within the injured parenchyma. Collectively, our results provide a first overview of Vegf/Vegfr signaling in the brain and suggest important roles for Vegf in neurogenesis and regenerative processes.

Nascent RNA kinetics with complex promoter architecture: Analytic results and parameter inference

Transcription is a stochastic process that involves several downstream operations which make it difficult to model and infer transcription kinetics from mature RNA numbers in individual cell. However, recent advances in single-cell technologies have enabled a more precise measurement of the fluctuations of nascent RNA that closely reflect transcription kinetics. In this paper we introduce a general stochastic model to mimic nascent RNA kinetics with complex promoter architecture. We derive the exact distribution and moments of nascent RNA using queuing theory techniques, which provide valuable insights into the effect of the molecular memory created by the multistep activation and deactivation on the stochastic kinetics of nascent RNA. Moreover, based on the analytical results, we develop a statistical method to infer the promoter memory from stationary nascent RNA distributions. Data analysis of synthetic data and a realistic example, the HIV-1 gene, verifies the validity of this inference method.

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.

Living in a noisy world-origins of gene expression noise and its impact on cellular decision-making

The expression level of a gene can vary between genetically identical cells under the same environmental condition-a phenomenon referred to as gene expression noise. Several studies have now elucidated a central role of transcription factors in the generation of expression noise. Transcription factors, as the key components of gene regulatory networks, drive many important cellular decisions in response to cellular and environmental signals. Therefore, a very relevant question is how expression noise impacts gene regulation and influences cellular decision-making. In this Review, we summarize the current understanding of the molecular origins of expression noise, highlighting the role of transcription factors in this process, and discuss the ways in which noise can influence cellular decision-making. As advances in single-cell technologies open new avenues for studying expression noise as well as gene regulatory circuits, a better understanding of the influence of noise on cellular decisions will have important implications for many biological processes.

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.

RNAi-based drug design: considerations and future directions

More than 25 years after its discovery, the post-transcriptional gene regulation mechanism termed RNAi is now transforming pharmaceutical development, proved by the recent FDA approval of multiple small interfering RNA (siRNA) drugs that target the liver. Synthetic siRNAs that trigger RNAi have the potential to specifically silence virtually any therapeutic target with unprecedented potency and durability. Bringing this innovative class of medicines to patients, however, has been riddled with substantial challenges, with delivery issues at the forefront. Several classes of siRNA drug are under clinical evaluation, but their utility in treating extrahepatic diseases remains limited, demanding continued innovation. In this Review, we discuss principal considerations and future directions in the design of therapeutic siRNAs, with a particular emphasis on chemistry, the application of informatics, delivery strategies and the importance of careful target selection, which together influence therapeutic success.

Seq-Scope Protocol: Repurposing Illumina Sequencing Flow Cells for High-Resolution Spatial Transcriptomics

Spatial transcriptomics (ST) technologies represent a significant advance in gene expression studies, aiming to profile the entire transcriptome from a single histological slide. These techniques are designed to overcome the constraints faced by traditional methods such as immunostaining and RNA in situ hybridization, which are capable of analyzing only a few target genes simultaneously. However, the application of ST in histopathological analysis is also limited by several factors, including low resolution, a limited range of genes, scalability issues, high cost, and the need for sophisticated equipment and complex methodologies. Seq-Scope-a recently developed novel technology-repurposes the Illumina sequencing platform for high-resolution, high-content spatial transcriptome analysis, thereby overcoming these limitations. Here we provide a detailed step-by-step protocol to implement Seq-Scope with an Illumina NovaSeq 6000 sequencing flow cell that allows for the profiling of multiple tissue sections in an area of 7 mm × 7 mm or larger. In addition to detailing how to prepare a frozen tissue section for both histological imaging and sequencing library preparation, we provide comprehensive instructions and a streamlined computational pipeline to integrate histological and transcriptomic data for high-resolution spatial analysis. This includes the use of conventional software tools for single cell and spatial analysis, as well as our recently developed segmentation-free method for analyzing spatial data at submicrometer resolution. Given its adaptability across various biological tissues, Seq-Scope establishes itself as an invaluable tool for researchers in molecular biology and histology.

Studying relative RNA localization From nucleus to the cytosol

The precise coordination of important biological processes, such as differentiation and development, is highly dependent on the regulation of expression of the genetic information. The flow of the genetic information is tightly regulated on multiple levels. Among them, RNA export to cytosol is an essential step for the production of proteins in eukaryotic cells. Hence, estimating the relative concentration of RNA molecules of a given transcript species in the nucleus and in the cytosol is of major significance as it contributes to the understanding of the dynamics of RNA trafficking between the nucleus and the cytosol. The most efficient way to estimate the levels of RNA species genome-wide is through RNA sequencing (RNAseq). While RNAseq can be performed separately in the nucleus and in the cytosol, because measured transcript levels are relative to the total volume of RNA in these compartments, and because this volume is usually unknown, the transcript levels in the nucleus and in the cytosol cannot be directly compared. Here we show theoretically that if, in addition to nuclear and cytosolic RNA-seq, whole cell RNA-seq is also performed, then accurate estimations of the localization of transcripts can be obtained. Based on this, we designed a method that estimates, first the fraction of the total RNA volume in the cytosol (nucleus), and then, this fraction for every transcript. We evaluate our methodology on simulated data and nuclear and cytosolic single cell data available. Finally, we use our method to investigate the cellular localization of transcripts using bulk RNAseq data from the ENCODE project.

A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X

The road from transcription to protein synthesis is paved with many obstacles, allowing for several modes of post-transcriptional regulation of gene expression. A fundamental player in mRNA biology is DDX3X, an RNA binding protein that canonically regulates mRNA translation. By monitoring dynamics of mRNA abundance and translation following DDX3X depletion, we observe stabilization of translationally suppressed mRNAs. We use interpretable statistical learning models to uncover GC content in the coding sequence as the major feature underlying RNA stabilization. This result corroborates GC content-related mRNA regulation detectable in other studies, including hundreds of ENCODE datasets and recent work focusing on mRNA dynamics in the cell cycle. We provide further evidence for mRNA stabilization by detailed analysis of RNA-seq profiles in hundreds of samples, including a Ddx3x conditional knockout mouse model exhibiting cell cycle and neurogenesis defects. Our study identifies a ubiquitous feature underlying mRNA regulation and highlights the importance of quantifying multiple steps of the gene expression cascade, where RNA abundance and protein production are often uncoupled.

TREX tetramer disruption alters RNA processing necessary for corticogenesis in THOC6 Intellectual Disability Syndrome

THOC6 variants are the genetic basis of autosomal recessive THOC6 Intellectual Disability Syndrome (TIDS). THOC6 is critical for mammalian Transcription Export complex (TREX) tetramer formation, which is composed of four six-subunit THO monomers. The TREX tetramer facilitates mammalian RNA processing, in addition to the nuclear mRNA export functions of the TREX dimer conserved through yeast. Human and mouse TIDS model systems revealed novel THOC6-dependent, species-specific TREX tetramer functions. Germline biallelic Thoc6 loss-of-function (LOF) variants result in mouse embryonic lethality. Biallelic THOC6 LOF variants reduce the binding affinity of ALYREF to THOC5 without affecting the protein expression of TREX members, implicating impaired TREX tetramer formation. Defects in RNA nuclear export functions were not detected in biallelic THOC6 LOF human neural cells. Instead, mis-splicing was detected in human and mouse neural tissue, revealing novel THOC6-mediated TREX coordination of mRNA processing. We demonstrate that THOC6 is required for key signaling pathways known to regulate the transition from proliferative to neurogenic divisions during human corticogenesis. Together, these findings implicate altered RNA processing in the developmental biology of TIDS neuropathology.

Glucose stress causes mRNA retention in nuclear Nab2 condensates

Nuclear mRNA export via nuclear pore complexes is an essential step in eukaryotic gene expression. Although factors involved in mRNA transport have been characterized, a comprehensive mechanistic understanding of this process and its regulation is lacking. Here, we use single-RNA imaging in yeast to show that cells use mRNA retention to control mRNA export during stress. We demonstrate that, upon glucose withdrawal, the essential RNA-binding factor Nab2 forms RNA-dependent condensate-like structures in the nucleus. This coincides with a reduced abundance of the DEAD-box ATPase Dbp5 at the nuclear pore. Depleting Dbp5, and consequently blocking mRNA export, is necessary and sufficient to trigger Nab2 condensation. The state of Nab2 condensation influences the extent of nuclear mRNA accumulation and can be recapitulated in vitro, where Nab2 forms RNA-dependent liquid droplets. We hypothesize that cells use condensation to regulate mRNA export and control gene expression during stress.

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'.

A ubiquitous GC content signature underlies multimodal mRNA regulation by DDX3X

The road from transcription to protein synthesis is paved with many obstacles, allowing for several modes of post-transcriptional regulation of gene expression. A fundamental player in mRNA biology is DDX3X, an RNA binding protein that canonically regulates mRNA translation. By monitoring dynamics of mRNA abundance and translation following DDX3X depletion, we observe stabilization of translationally suppressed mRNAs. We use interpretable statistical learning models to uncover GC content in the coding sequence as the major feature underlying RNA stabilization. This result corroborates GC content-related mRNA regulation detectable in other studies, including hundreds of ENCODE datasets and recent work focusing on mRNA dynamics in the cell cycle. We provide further evidence for mRNA stabilization by detailed analysis of RNA-seq profiles in hundreds of samples, including a Ddx3x conditional knockout mouse model exhibiting cell cycle and neurogenesis defects. Our study identifies a ubiquitous feature underlying mRNA regulation and highlights the importance of quantifying multiple steps of the gene expression cascade, where RNA abundance and protein production are often uncoupled.

Stochastic modeling of the mRNA life process: A generalized master equation

The mRNA life cycle is a complex biochemical process, involving transcription initiation, elongation, termination, splicing, and degradation. Each of these molecular events is multistep and can create a memory. The effect of this molecular memory on gene expression is not clear, although there are many related yet scattered experimental reports. To address this important issue, we develop a general theoretical framework formulated as a master equation in the sense of queue theory, which can reduce to multiple previously studied gene models in limiting cases. This framework allows us to interpret experimental observations, extract kinetic parameters from experimental data, and identify how the mRNA kinetics vary under regulatory influences. Notably, it allows us to evaluate the influences of elongation processes on mature RNA distribution; e.g., we find that the non-exponential elongation time can induce the bimodal mRNA expression and there is an optimal elongation noise intensity such that the mature RNA noise achieves the lowest level. In a word, our framework can not only provide insight into complex mRNA life processes but also bridge a dialogue between theoretical studies and experimental data.

Technical Advances and Applications of Spatial Transcriptomics

Transcriptomics is one of the largest areas of research in biological sciences. Aside from RNA expression levels, the significance of RNA spatial context has also been unveiled in the recent decade, playing a critical role in diverse biological processes, from subcellular kinetic regulation to cell communication, from tissue architecture to tumor microenvironment, and more. To systematically unravel the positional patterns of RNA molecules across subcellular, cellular, and tissue levels, spatial transcriptomics techniques have emerged and rapidly became an irreplaceable tool set. Herein, we review and compare current spatial transcriptomics techniques on their methods, advantages, and limitations, as well as applications across a wide range of biological investigations. This review serves as a comprehensive guide to spatial transcriptomics for researchers interested in adopting this powerful suite of technologies.

Mechanisms of mRNA processing defects in inherited THOC6 intellectual disability syndrome

THOC6 is the genetic basis of autosomal recessive THOC6 Intellectual Disability Syndrome (TIDS). THOC6 facilitates the formation of the Transcription Export complex (TREX) tetramer, composed of four THO monomers. The TREX tetramer supports mammalian mRNA processing that is distinct from yeast TREX dimer functions. Human and mouse TIDS model systems allow novel THOC6-dependent TREX tetramer functions to be investigated. Biallelic loss-of-functon(LOF) THOC6 variants do not influence the expression and localization of TREX members in human cells, but our data suggests reduced binding affinity of ALYREF. Impairment of TREX nuclear export functions were not detected in cells with biallelic THOC6 LOF. Instead, mRNA mis-splicing was observed in human and mouse neural tissue, revealing novel insights into THOC6-mediated TREX coordination of mRNA processing. We demonstrate that THOC6 is required for regulation of key signaling pathways in human corticogenesis that dictate the transition from proliferative to neurogenic divisions that may inform TIDS neuropathology.

Uncovering Critical Roles for RNA in Neurodegeneration

RNA-binding proteins, in particular TDP-43, are key players in neurodegenerative disorders, mainly amyotrophic lateral sclerosis and frontotemporal dementia. We aim to elucidate how TDP-43 dysfunction alters cell metabolism and to identify mechanisms linked to aberrant behavior. We find that RNA binding plays a key role in maintaining TDP-43 homeostasis and in controlling cellular organization, two processes of essential importance to TDP-43 pathology. This research will provide insight into pathogenesis and help develop therapeutic interventions.

Analysis of subcellular RNA fractions demonstrates significant genetic regulation of gene expression in human brain post-transcriptionally

Gaining insight into the genetic regulation of gene expression in human brain is key to the interpretation of genome-wide association studies for major neurological and neuropsychiatric diseases. Expression quantitative trait loci (eQTL) analyses have largely been used to achieve this, providing valuable insights into the genetic regulation of steady-state RNA in human brain, but not distinguishing between molecular processes regulating transcription and stability. RNA quantification within cellular fractions can disentangle these processes in cell types and tissues which are challenging to model in vitro. We investigated the underlying molecular processes driving the genetic regulation of gene expression specific to a cellular fraction using allele-specific expression (ASE). Applying ASE analysis to genomic and transcriptomic data from paired nuclear and cytoplasmic fractions of anterior prefrontal cortex, cerebellar cortex and putamen tissues from 4 post-mortem neuropathologically-confirmed control human brains, we demonstrate that a significant proportion of genetic regulation of gene expression occurs post-transcriptionally in the cytoplasm, with genes undergoing this form of regulation more likely to be synaptic. These findings have implications for understanding the structure of gene expression regulation in human brain, and importantly the interpretation of rapidly growing single-nucleus brain RNA-sequencing and eQTL datasets, where cytoplasm-specific regulatory events could be missed.

Noise Minimization in Cell-Free Gene Expression

Biochemical reactions that involve small numbers of molecules are accompanied by a degree of inherent randomness that results in noisy reaction outcomes. In synthetic biology, the ability to minimize noise particularly during the reconstitution of future synthetic protocells is an outstanding challenge to secure robust and reproducible behavior. Here we show that by encapsulation of a bacterial cell-free gene expression system in water-in-oil droplets, in vitro-synthesized MazF reduces cell-free gene expression noise >2-fold. With stochastic simulations we identify that this noise minimization acts through both increased degradation and the autoregulatory feedback of MazF. Specifically, we find that the expression of MazF enhances the degradation rate of mRNA up to 18-fold in a sequence-dependent manner. This sequence specificity of MazF would allow targeted noise control, making it ideal to integrate into synthetic gene networks. Therefore, including MazF production in synthetic biology can significantly minimize gene expression noise, impacting future design principles of more complex cell-free gene circuits.

Influence of HIV-1 Genomic RNA on the Formation of Gag Biomolecular Condensates

Biomolecular condensates (BMCs) play an important role in the replication of a growing number of viruses, but many important mechanistic details remain to be elucidated. Previously, we demonstrated that the pan-retroviral nucleocapsid (NC) and HIV-1 pr55Gag (Gag) proteins phase separate into condensates, and that HIV-1 protease (PR)-mediated maturation of Gag and Gag-Pol precursor proteins yields self-assembling BMCs that have HIV-1 core architecture. Using biochemical and imaging techniques, we aimed to further characterize the phase separation of HIV-1 Gag by determining which of its intrinsically disordered regions (IDRs) influence the formation of BMCs, and how the HIV-1 viral genomic RNA (gRNA) could influence BMC abundance and size. We found that mutations in the Gag matrix (MA) domain or the NC zinc finger motifs altered condensate number and size in a salt-dependent manner. Gag BMCs were also bimodally influenced by the gRNA, with a condensate-promoting regime at lower protein concentrations and a gel dissolution at higher protein concentrations. Interestingly, incubation of Gag with CD4+ T cell nuclear lysates led to the formation of larger BMCs compared to much smaller ones observed in the presence of cytoplasmic lysates. These findings suggest that the composition and properties of Gag-containing BMCs may be altered by differential association of host factors in nuclear and cytosolic compartments during virus assembly. This study significantly advances our understanding of HIV-1 Gag BMC formation and provides a foundation for future therapeutic targeting of virion assembly.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Gene expression inherently gives rise to stochastic variation ("noise") in the production of gene products. Minimizing noise is crucial for ensuring reliable cellular functions. However, noise cannot be suppressed below a certain intrinsic limit. For constitutively expressed genes, this limit is typically assumed to be Poissonian noise, wherein the variance in mRNA numbers is equal to their mean. Here, we demonstrate that several cell division genes in fission yeast exhibit mRNA variances significantly below this limit. The reduced variance can be explained by a gene expression model incorporating multiple transcription and mRNA degradation steps. Notably, in this sub-Poissonian regime, distinct from Poissonian or super-Poissonian regimes, cytoplasmic noise is effectively suppressed through a higher mRNA export rate. Our findings redefine the lower limit of eukaryotic gene expression noise and uncover molecular requirements for achieving ultralow noise, which is expected to be important for vital cellular functions.

Integration of a multi-omics stem cell differentiation dataset using a dynamical model

Stem cell differentiation is a highly dynamic process involving pervasive changes in gene expression. The large majority of existing studies has characterized differentiation at the level of individual molecular profiles, such as the transcriptome or the proteome. To obtain a more comprehensive view, we measured protein, mRNA and microRNA abundance during retinoic acid-driven differentiation of mouse embryonic stem cells. We found that mRNA and protein abundance are typically only weakly correlated across time. To understand this finding, we developed a hierarchical dynamical model that allowed us to integrate all data sets. This model was able to explain mRNA-protein discordance for most genes and identified instances of potential microRNA-mediated regulation. Overexpression or depletion of microRNAs identified by the model, followed by RNA sequencing and protein quantification, were used to follow up on the predictions of the model. Overall, our study shows how multi-omics integration by a dynamical model could be used to nominate candidate regulators.

Spatiotemporally resolved transcriptomics reveals the subcellular RNA kinetic landscape

Spatiotemporal regulation of the cellular transcriptome is crucial for proper protein expression and cellular function. However, the intricate subcellular dynamics of RNA remain obscured due to the limitations of existing transcriptomics methods. Here, we report TEMPOmap-a method that uncovers subcellular RNA profiles across time and space at the single-cell level. TEMPOmap integrates pulse-chase metabolic labeling with highly multiplexed three-dimensional in situ sequencing to simultaneously profile the age and location of individual RNA molecules. Using TEMPOmap, we constructed the subcellular RNA kinetic landscape in various human cells from transcription and translocation to degradation. Clustering analysis of RNA kinetic parameters across single cells revealed 'kinetic gene clusters' whose expression patterns were shaped by multistep kinetic sculpting. Importantly, these kinetic gene clusters are functionally segregated, suggesting that subcellular RNA kinetics are differentially regulated in a cell-state- and cell-type-dependent manner. Spatiotemporally resolved transcriptomics provides a gateway to uncovering new spatiotemporal gene regulation principles.

Upregulation of non-canonical and canonical inflammasome genes associates with pathological features in Krabbe disease and related disorders

Infantile Krabbe disease is a rapidly progressive and fatal disorder of myelin, caused by inherited deficiency of the lysosomal enzyme β-galactocerebrosidase. Affected children lose their motor skills and other faculties; uncontrolled seizures are a frequent terminal event. Overexpression of the sphingolipid metabolite psychosine is a pathogenic factor, but does not fully account for the pleiotropic manifestations and there is a clear need to investigate additional pathological mechanisms. We examined innate immunity, caspase-11 and associated inflammatory pathways in twitcher mice, an authentic model of Krabbe disease. Combined use of molecular tools, RNAscope in situ hybridization and immunohistochemical staining established that the expression of pro-inflammatory non-canonical caspase-11, canonical caspase-1, gasdermin D and cognate genes is induced in nervous tissue. Early onset and progressive upregulation of these genes accompany demyelination and gliosis and although the molecules are scant in healthy tissue, abundance of the respective translation products is greatly increased in diseased animals. Caspase-11 is found in reactive microglia/macrophages as well as astrocytes but caspase-1 and gasdermin D are restricted to reactive microglia/macrophages. The inflammasome signature is not unique to Krabbe disease; to varying degrees, this signature is also prominent in other lysosomal diseases, Sandhoff and Niemann-Pick Type-C1, and the lysolecithin toxin model of focal demyelination. Given the potent inflammatory response here identified in Krabbe disease and the other neurodegenerative disorders studied, a broad induction of inflammasomes is likely to be a dominant factor in the pathogenesis, and thus represents a platform for therapeutic exploration.

Parallel recovery of chromatin accessibility and gene expression dynamics from frozen human regulatory T cells

Epigenetic features such as DNA accessibility dictate transcriptional regulation in a cell type- and cell state- specific manner, and mapping this in health vs. disease in clinically relevant material is opening the door to new mechanistic insights and new targets for therapy. Assay for Transposase Accessible Chromatin Sequencing (ATAC-seq) allows chromatin accessibility profiling from low cell input, making it tractable on rare cell populations, such as regulatory T (Treg) cells. However, little is known about the compatibility of the assay with cryopreserved rare cell populations. Here we demonstrate the robustness of an ATAC-seq protocol comparing primary Treg cells recovered from fresh or cryopreserved PBMC samples, in the steady state and in response to stimulation. We extend this method to explore the feasibility of conducting simultaneous quantitation of chromatin accessibility and transcriptome from a single aliquot of 50,000 cryopreserved Treg cells. Profiling of chromatin accessibility and gene expression in parallel within the same pool of cells controls for cellular heterogeneity and is particularly beneficial when constrained by limited input material. Overall, we observed a high correlation of accessibility patterns and transcription factor dynamics between fresh and cryopreserved samples. Furthermore, highly similar transcriptomic profiles were obtained from whole cells and from the supernatants recovered from ATAC-seq reactions. We highlight the feasibility of applying these techniques to profile the epigenomic landscape of cells recovered from cryopreservation biorepositories.

Nuclei on the Rise: When Nuclei-Based Methods Meet Next-Generation Sequencing

In the last decade, we have witnessed an upsurge in nuclei-based studies, particularly coupled with next-generation sequencing. Such studies aim at understanding the molecular states that exist in heterogeneous cell populations by applying increasingly more affordable sequencing approaches, in addition to optimized methodologies developed to isolate and select nuclei. Although these powerful new methods promise unprecedented insights, it is important to understand and critically consider the associated challenges. Here, we provide a comprehensive overview of the rise of nuclei-based studies and elaborate on their advantages and disadvantages, with a specific focus on their utility for transcriptomic sequencing analyses. Improved designs and appropriate use of the various experimental strategies will result in acquiring biologically accurate and meaningful information.

The minimal intrinsic stochasticity of constitutively expressed eukaryotic genes is sub-Poissonian

Stochastic variation in gene products ("noise") is an inescapable by-product of gene expression. Noise must be minimized to allow for the reliable execution of cellular functions. However, noise cannot be suppressed beyond an intrinsic lower limit. For constitutively expressed genes, this limit is believed to be Poissonian, meaning that the variance in mRNA numbers cannot be lower than their mean. Here, we show that several cell division genes in fission yeast have mRNA variances significantly below this limit, which cannot be explained by the classical gene expression model for low-noise genes. Our analysis reveals that multiple steps in both transcription and mRNA degradation are essential to explain this sub-Poissonian variance. The sub-Poissonian regime differs qualitatively from previously characterized noise regimes, a hallmark being that cytoplasmic noise is reduced when the mRNA export rate increases. Our study re-defines the lower limit of eukaryotic gene expression noise and identifies molecular requirements for ultra-low noise which are expected to support essential cell functions.

Influence of HIV-1 genomic RNA on the formation of Gag biomolecular condensates

Biomolecular condensates (BMCs) play an important role in the replication of a growing number of viruses, but many important mechanistic details remain to be elucidated. Previously, we demonstrated that pan-retroviral nucleocapsid (NC) and the HIV-1 pr55 ^Gag (Gag) proteins phase separate into condensates, and that HIV-1 protease (PR)-mediated maturation of Gag and Gag-Pol precursor proteins yield self-assembling BMCs having HIV-1 core architecture. Using biochemical and imaging techniques, we aimed to further characterize the phase separation of HIV-1 Gag by determining which of its intrinsically disordered regions (IDRs) influence the formation of BMCs and how the HIV-1 viral genomic RNA (gRNA) could influence BMC abundance and size. We found that mutations in the Gag matrix (MA) domain or the NC zinc finger motifs altered condensate number and size in a salt-dependent manner. Gag BMCs were also bimodally influenced by the gRNA, with a condensate-promoting regime at lower protein concentrations and a gel dissolution at higher protein concentrations. Interestingly, incubation of Gag with CD4 ⁺ T cell nuclear lysates led to the formation of larger BMCs as compared to much smaller ones observed in the presence of cytoplasmic lysates. These findings suggests that the composition and properties of Gag-containing BMCs may be altered by differential association of host factors in nuclear and cytosolic compartments during virus assembly. This study significantly advances our understanding of HIV-1 Gag BMC formation and provides a foundation for future therapeutic targeting of virion assembly.

Single-cell transcriptomics shows dose-dependent disruption of hepatic zonation by TCDD in mice

2,3,7,8-Tetrachlorodibenzo-p-dioxin (TCDD) dose-dependently induces the development of hepatic fat accumulation and inflammation with fibrosis in mice initially in the portal region. Conversely, differential gene and protein expression is first detected in the central region. To further investigate cell-specific and spatially resolved dose-dependent changes in gene expression elicited by TCDD, single-nuclei RNA sequencing and spatial transcriptomics were used for livers of male mice gavaged with TCDD every 4 days for 28 days. The proportion of 11 cell (sub)types across 131 613 nuclei dose-dependently changed with 68% of all portal and central hepatocyte nuclei in control mice being overtaken by macrophages following TCDD treatment. We identified 368 (portal fibroblasts) to 1339 (macrophages) differentially expressed genes. Spatial analyses revealed initial loss of portal identity that eventually spanned the entire liver lobule with increasing dose. Induction of R-spondin 3 (Rspo3) and pericentral Apc, suggested dysregulation of the Wnt/β-catenin signaling cascade in zonally resolved steatosis. Collectively, the integrated results suggest disruption of zonation contributes to the pattern of TCDD-elicited NAFLD pathologies.

Transcripts of the Prostate Cancer-Associated Gene ANO7 Are Retained in the Nuclei of Prostatic Epithelial Cells

Prostate cancer affects millions of men globally. The prostate cancer-associated gene ANO7 is downregulated in advanced prostate cancer, whereas benign tissue and low-grade cancer display varying expression levels. In this study, we assess the spatial correlation between ANO7 mRNA and protein using fluorescent in situ hybridization and immunohistochemistry for the detection of mRNA and protein in parallel sections of tissue microarrays prepared from radical prostatectomy samples. We show that ANO7 mRNA and protein expression correlate in prostate tissue. Furthermore, we show that ANO7 mRNA is enriched in the nuclei of the luminal cells at 89% in benign ducts and low-grade cancer, and at 78% in high-grade cancer. The nuclear enrichment of ANO7 mRNA was validated in prostate cancer cell lines 22Rv1 and MDA PCa 2b using droplet digital polymerase chain reaction (ddPCR) on RNA isolated from nuclear and cytoplasmic fractions of the cells. The nuclear enrichment of ANO7 mRNA was compared to the nuclearly-enriched lncRNA MALAT1, confirming the surprisingly high nuclear retention of ANO7 mRNA. ANO7 has been suggested to be used as a diagnostic marker and a target for immunotherapy, but a full comprehension of its role in prostate cancer progression is currently lacking. Our results contribute to a better understanding of the dynamics of ANO7 expression in prostatic tissue.

LAFITE Reveals the Complexity of Transcript Isoforms in Subcellular Fractions

Characterization of the subcellular distribution of RNA is essential for understanding the molecular basis of biological processes. Here, the subcellular nanopore direct RNA-sequencing (DRS) of four lung cancer cell lines (A549, H1975, H358, and HCC4006) is performed, coupled with a computational pipeline, Low-abundance Aware Full-length Isoform clusTEr (LAFITE), to comprehensively analyze the full-length cytoplasmic and nuclear transcriptome. Using additional DRS and orthogonal data sets, it is shown that LAFITE outperforms current methods for detecting full-length transcripts, particularly for low-abundance isoforms that are usually overlooked due to poor read coverage. Experimental validation of six novel isoforms exclusively identified by LAFITE further confirms the reliability of this pipeline. By applying LAFITE to subcellular DRS data, the complexity of the nuclear transcriptome is revealed in terms of isoform diversity, 3'-UTR usage, m6A modification patterns, and intron retention. Overall, LAFITE provides enhanced full-length isoform identification and enables a high-resolution view of the RNA landscape at the isoform level.