RNA Localization Research Articles

Small-Molecule Benzo-Phenoselenazine Derivatives for Multi-Subcellular Biomolecule Profiling.

Elucidating the subcellular localization of RNAs and proteins is fundamental to understanding their biological functions. Genetically encoded proteins/enzymes provide an attractive approach to target many proteins of interest, but are limited to specific cell lines. Although small-molecule-based methods have been explored, a comprehensive system for profiling multiple locations in living cells, comparable to fusion-protein techniques, is yet to be established. In this study, we introduce a novel proximity labeling strategy employing a suite of small molecules derived from benzophenoselenazine (e.g., selenium-containing Nile Blue [SeNB]), which achieves proximity labeling through singlet oxygen generation upon near-infrared light activation in the presence of propargylamine. These SeNB compounds allow forselective labeling of RNAs and proteins within living cells, exhibiting a distinct preference for organelle membranes, which are systematically investigated via in vitro, computational, and in cellulo examinations. Our findings highlight the capabilities of SeNB derivatives as wash-free and genetics-free approaches to illuminate the subcellular localization of biological molecules with deep penetration and high spatial resolution. Moreover, SeNB derivatives are capable of elucidating inter-organelle interactions at the molecular level, as evidenced by proteomic and transcriptomic analyses, thus holding significant potential for advancing our understanding of cellular processes related to disease progression and therapeutic development.

Enhanced HSP70 binding to m6A-methylated RNAs facilitates cold stress adaptation in mango seedlings

BackgroundCold stress poses a serious challenge to tropical fruit production, particularly in mango. N6-methyladenosine (m6A) modifications are key regulators of gene expression, enabling plants to respond to stress responses, enhance adaptation and improve resilience to environmental challenges.ResultsIn our study, transcriptome-wide m6A methylation profiling under cold stress identified 6,499 differentially methylated m6A peaks and 2,164 differentially expressed genes (DEGs) in mango seedlings. Among these genes, six exhibited both significant increases in m6A modification levels and gene expression, 21 showed a significant increase in m6A levels but a concurrent downregulation of gene expression, and 26 showed reduced m6A levels but exhibited increased gene expression, highlighting distinct regulatory patterns in m6A-mediated gene expression control. Gene Ontology (GO) enrichment analysis revealed significant involvement in pathways such as potassium ion import, nitrate response, and transcription regulation. Notably, HSP70 was one of the upregulated genes in response to cold stress. RNA immunoprecipitation (RNA-IP) assays confirmed the association of HSP70 with m6A-modified RNAs in vivo, supporting its role in regulating stress-responsive transcripts. Additionally, immunofluorescence analysis demonstrated the formation of HSP70 condensates in plant cells under cold stress, indicating a potential mechanism for localized RNA stabilization. Fluorescence polarization assays demonstrated that HSP70 binds preferentially to m6A-modified RNAs, suggesting its role in forming protective condensates under cold conditions. This interaction between m6A modification and HSP70 points to a potential mechanism that helps stabilize stress-responsive transcripts, contributing to the plant’s enhanced cold tolerance.Conclusionsm6A modifications play a vital role in regulating gene expression under cold stress, offering new insights into mango’s stress responses and potential breeding strategies for cold tolerance.

The improved de Bruijn graph for multitask learning: predicting functions, subcellular localization, and interactions of noncoding RNAs.

Noncoding RNA refers to RNA that does not encode proteins. The lncRNA and miRNA it contains play crucial regulatory roles in organisms, and their aberrant expression is closely related to various diseases. Traditional experimental methods for validating the interactions of these RNAs have limitations, and existing prediction models exhibit relatively limited functionality, relying on isolated feature extraction and performing poorly in handling various types of small sample tasks. This paper proposes an improved de Bruijn graph that can inject RNA structural information into the graph while preserving sequence information. Furthermore, the improved de Bruijn graph enables graph neural networks to learn broader dependencies and correlations among data by introducing richer edge relationships. Meanwhile, the multitask learning model, DVMnet, proposed in this paper can handle multiple related tasks, and we optimize model parameters by integrating the total loss of three tasks. This enables multitask prediction of RNA interactions, disease associations, and subcellular localization. Compared with the best existing models in this field, DVMnet has achieved the best performance with a 3% improvement in the area under the curve value and demonstrates robust results in predicting diseases and subcellular localization. The improved de Bruijn graph is also applicable to various scenarios and can unify the sequence and structural information of various nucleic acids into a single graph.

Transcription of a centromere-enriched retroelement and local retention of its RNA are significant features of the CENP-A chromatin landscape

BackgroundCentromeres depend on chromatin containing the conserved histone H3 variant CENP-A for function and inheritance, while the role of centromeric DNA repeats remains unclear. Retroelements are prevalent at centromeres across taxa and represent a potential mechanism for promoting transcription to aid in CENP-A incorporation or for generating RNA transcripts to maintain centromere integrity.ResultsIn this study, we probe into the transcription and RNA localization of the centromere-enriched retroelement G2/Jockey-3 (hereafter referred to as Jockey-3) in Drosophila melanogaster, currently the only in vivo model with assembled centromeres. We find that Jockey-3 is a major component of the centromeric transcriptome and produces RNAs that localize to centromeres in metaphase. Leveraging the polymorphism of Jockey-3 and a de novo centromere system, we show that these RNAs remain associated with their cognate DNA sequences in cis, suggesting they are unlikely to perform a sequence-specific function at all centromeres. We show that Jockey-3 transcription is positively correlated with the presence of CENP-A and that recent Jockey-3 transposition events have occurred preferentially at CENP-A-containing chromatin.ConclusionsWe propose that Jockey-3 preferentially inserts at the centromere to ensure its own selfish propagation, while contributing to transcription across these regions. Given the conservation of retroelements as centromere components through evolution, our findings may offer a basis for understanding similar associations in other species.

A Method for Bioluminescence-Based RNA Monitoring Using Split-Luciferase Reconstitution Techniques.

A bioluminescence-based RNA monitoring method in living cells was developed using a split NanoLuc (NLuc) reconstitution technique. For specific recognition of a target RNA sequence, a mutant PUM-HD (mPUM) was used. The method was applied to β-actin mRNA in various cells, including primary cultures of rat hippocampal neurons. It allowed for continuous observation of intracellular localization distribution of the target mRNA in living cells, providing insights into various biological phenomena involving intracellular RNA localization and dynamics.

Self‐Adaptive Activation of DNAzyme Nanoassembly for Synergistically Combined Gene Therapy

AbstractDNAzyme represents a promising gene silencing toolbox yet is obstructed by the poor substrate accessibility in specific cells. Herein, a compact DNA nanoassembly, incorporating multimeric therapeutic DNAzyme, was prepared for selective delivery of gene‐silencing DNAzyme with requisite cofactors and auxiliary chemo‐drugs. By virtue of the sequence‐conservative duplex‐specific nuclease, the endogenous miRNA catalyzes the successive and site‐specific cleavage of DNA nanoassembly substrate (nominated as the localized RNA walking machine) and thus ensures the liberation/activation of therapeutic agents with high accuracy and efficacy. The miR‐10b‐stimulated DNAzyme was designed to downregulate the TWIST transcription factor, an upstream promotor of miR‐10b, thus acquiring the self‐sufficient downregulation of TWIST/miR‐10b signaling nodes (self‐adaptive negative feedback loop) for abrogating tumor metastasis and chemo‐resistance issues.

Self-Adaptive Activation of DNAzyme Nanoassembly for Synergistically Combined Gene Therapy.

DNAzyme represents a promising gene silencing toolbox yet is obstructed by the poor substrate accessibility in specific cells. Herein, a compact DNA nanoassembly, incorporating multimeric therapeutic DNAzyme, was prepared for selective delivery of gene-silencing DNAzyme with requisite cofactors and auxiliary chemo-drugs. By virtue of the sequence-conservative duplex-specific nuclease, the endogenous miRNA catalyzes the successive and site-specific cleavage of DNA nanoassembly substrate (nominated as the localized RNA walking machine) and thus ensures the liberation/activation of therapeutic agents with high accuracy and efficacy. The miR-10b-stimulated DNAzyme was designed to downregulate the TWIST transcription factor, an upstream promotor of miR-10b, thus acquiring the self-sufficient downregulation of TWIST/miR-10b signaling nodes (self-adaptive negative feedback loop) for abrogating tumor metastasis and chemo-resistance issues.

Quantification of subcellular RNA localization through direct detection of RNA oxidation.

Across cell types and organisms, thousands of RNAs display asymmetric subcellular distributions. The study of this process often requires quantifying abundances of specific RNAs at precise subcellular locations. To analyze subcellular transcriptomes, multiple proximity-based techniques have been developed in which RNAs near a localized bait protein are specifically labeled, facilitating their biotinylation and purification. However, these complex methods are often laborious and require expensive enrichment reagents. To streamline the analysis of localized RNA populations, we developed Oxidation-Induced Nucleotide Conversion sequencing (OINC-seq). In OINC-seq, RNAs near a genetically encoded, localized bait protein are specifically oxidized in a photo-controllable manner. These oxidation events are then directly detected and quantified using high-throughput sequencing and our software package, PIGPEN, without the need for biotin-mediated enrichment. We demonstrate that OINC-seq can induce and quantify RNA oxidation with high specificity in a dose- and light-dependent manner. We further show the spatial specificity of OINC-seq by using it to quantify subcellular transcriptomes associated with the cytoplasm, ER, nucleus, and the inner and outer membranes of mitochondria. Finally, using transgenic zebrafish, we demonstrate that OINC-seq allows proximity-mediated RNA labeling in live animals. In sum, OINC-seq together with PIGPEN provide an accessible workflow for the analysis of localized RNAs across different biological systems.

Integrated Biochemical and Computational Methods for Deciphering RNA-Processing Codes.

RNA processing involves steps such as capping, splicing, polyadenylation, modification, and nuclear export. These steps are essential for transforming genetic information in DNA into proteins and contribute to RNA diversity and complexity. Many biochemical methods have been developed to profile and quantify RNAs, as well as to identify the interactions between RNAs and RNA-binding proteins (RBPs), especially when coupled with high-throughput sequencing technologies. With the rapid accumulation of diverse data, it is crucial to develop computational methods to convert the big data into biological knowledge. In particular, machine learning and deep learning models are commonly utilized to learn the rules or codes governing the transformation from DNA sequences to intriguing RNAs based on manually designed or automatically extracted features. When precise enough, the RNA codes can be incredibly useful for predicting RNA products, decoding the molecular mechanisms, forecasting the impact of disease variants on RNA processing events, and identifying driver mutations. In this review, we systematically summarize the biochemical and computational methods for deciphering five important RNA codes related to alternative splicing, alternative polyadenylation, RNA localization, RNA modifications, and RBP binding. For each code, we review the main types of experimental methods used to generate training data, as well as the key features, strategic model structures, and advantages of representative tools. We also discuss the challenges encountered in developing predictive models using large language models and extensive domain knowledge. Additionally, we highlight useful resources and propose ways to improve computational tools for studying RNA codes.

RNA modifications: emerging players in the regulation of reproduction and development.

The intricate world of RNA modifications, collectively termed the epitranscriptome, covers over 170 identified modifications and impacts RNA metabolism and, consequently, almost all biological processes. In this review, we focus on the regulatory roles and biological functions of a panel of dominant RNA modifications (including m 6A, m 5C, Ψ, ac 4C, m 1A, and m 7G) on three RNA types-mRNA, tRNA, and rRNA-in mammalian development, particularly in the context of reproduction as well as embryonic development. We discuss in detail how those modifications, along with their regulatory proteins, affect RNA processing, structure, localization, stability, and translation efficiency. We also highlight the associations among dysfunctions in RNA modification-related proteins, abnormal modification deposition and various diseases, emphasizing the roles of RNA modifications in critical developmental processes such as stem cell self-renewal and cell fate transition. Elucidating the molecular mechanisms by which RNA modifications influence diverse developmental processes holds promise for developing innovative strategies to manage developmental disorders. Finally, we outline several unexplored areas in the field of RNA modification that warrant further investigation.

IGF2BP1 phosphorylation in the disordered linkers regulates ribonucleoprotein condensate formation and RNA metabolism.

The insulin-like growth factor 2 mRNA binding protein 1 (IGF2BP1) is a conserved RNA-binding protein that regulates RNA stability, localization and translation. IGF2BP1 is part of various ribonucleoprotein (RNP) condensates. However, the mechanism that regulates its assembly into condensates remains unknown. By using proteomics, we demonstrate that phosphorylation of IGF2BP1 at S181 in a disordered linker is regulated in a stress-dependent manner. Phosphomimetic mutations in two disordered linkers, S181E and Y396E, modulate RNP condensate formation by IGF2BP1 without impacting its binding affinity for RNA. Intriguingly, the S181E mutant, which lies in linker 1, impairs IGF2BP1 condensate formation in vitro and in cells, whereas a Y396E mutant in the second linker increases condensate size and dynamics. Structural approaches show that the first linker binds RNAs nonspecifically through its RGG/RG motif, an interaction weakened in the S181E mutant. Notably, linker 2 interacts with IGF2BP1's folded domains and these interactions are partially impaired in the Y396E mutant. Importantly, the phosphomimetic mutants impact IGF2BP1's interaction with RNAs and remodel the transcriptome in cells. Our data reveal how phosphorylation modulates low-affinity interaction networks in disordered linkers to regulate RNP condensate formation and RNA metabolism.

Dynamics of RNA localization to nuclear speckles are connected to splicing efficiency.

Nuclear speckles are nuclear membraneless organelles in higher eukaryotic cells playing a vital role in gene expression. Using an in situ reverse transcription-based sequencing method, we study nuclear speckle-associated human transcripts. Our data indicate the existence of three gene groups whose transcripts demonstrate different speckle localization properties: stably enriched in nuclear speckles, transiently enriched in speckles at the pre-messenger RNA stage, and not enriched. We find that stably enriched transcripts contain inefficiently excised introns and that disruption of nuclear speckles specifically affects splicing of speckle-enriched transcripts. We further reveal RNA sequence features contributing to transcript speckle localization, indicating a tight interplay between transcript speckle enrichment, genome organization, and splicing efficiency. Collectively, our data highlight a role of nuclear speckles in both co- and posttranscriptional splicing regulation. Last, we show that genes with stably enriched transcripts are over-represented among genes with heat shock-up-regulated intron retention, hinting at a connection between speckle localization and cellular stress response.

Two riboswitch classes that share a common ligand-binding fold show major differences in the ability to accommodate mutations.

Riboswitches are structured RNAs that sense small molecules to control expression. Prequeuosine1 (preQ1)-sensing riboswitches comprise three classes (I, II and III) that adopt distinct folds. Despite this difference, class II and III riboswitches each use 10 identical nucleotides to bind the preQ1 metabolite. Previous class II studies showed high sensitivity to binding-pocket mutations, which reduced preQ1 affinity and impaired function. Here, we introduced four equivalent mutations into a class III riboswitch, which maintained remarkably tight preQ1 binding.Co-crystal structures of each class III mutant showed compensatory interactions that preserve the fold. Chemical modification analysis revealed localized RNA flexibility changes for each mutant, but molecular dynamics (MD) simulations suggested that each mutation was not overtly destabilizing. Although impaired, class III mutants retained tangible gene-regulatory activity in bacteria compared to equivalent preQ1-II variants; mutations in the preQ1-pocket floor were tolerated better than wall mutations. Principal component analysis of MD trajectories suggested that the most functionally deleterious wall mutation samples different motions compared to wildtype. Overall, the results reveal that formation of compensatory interactions depends on the context of mutations within the overall fold and that functionally deleterious mutations can alter long-range correlated motions that link the riboswitch binding pocket with distal gene-regulatory sequences.

RNALocate v3.0: Advancing the Repository of RNA Subcellular Localization with Dynamic Analysis and Prediction.

Subcellular localization of RNA is a crucial mechanism for regulating diverse biological processes within cells. Dynamic RNA subcellular localizations are essential for maintaining cellular homeostasis; however, their distribution and changes during development and differentiation remain largely unexplored. To elucidate the dynamic patterns of RNA distribution within cells, we have upgraded RNALocate to version 3.0, a repository for RNA-subcellular localization (http://www.rnalocate.org/ or http://www.rna-society.org/rnalocate/). RNALocate v3.0 incorporates and analyzes RNA subcellular localization sequencing data from over 850 samples, with a specific focus on the dynamic changes in subcellular localizations under various conditions. The species coverage has also been expanded to encompass mammals, non-mammals, plants and microbes. Additionally, we provide an integrated prediction algorithm for the subcellular localization of seven RNA types across eleven subcellular compartments, utilizing convolutional neural networks(CNNs) and transformer models. Overall, RNALocate v3.0 contains a total of 1 844 013 RNA-localization entries covering 26 RNA types, 242 species and 177 subcellular localizations. It serves as a comprehensive and readily accessible data resource for RNA-subcellular localization, facilitating the elucidation of cellular function and disease pathogenesis.

Maintenance of X chromosome inactivation after T cell activation requires NF-κB signaling.

X chromosome inactivation (XCI) balances X-linked gene dosage between sexes. Unstimulated T cells lack cytological enrichment of X-inactive specific transcript (Xist) RNA and heterochromatic modifications on the inactive X chromosome (Xi), which are involved in maintenance of XCI, and these modifications return to the Xi after stimulation. Here, we examined allele-specific gene expression and epigenomic profiles of the Xi in T cells. We found that the Xi in unstimulated T cells is largely dosage compensated and enriched with the repressive H3K27me3 modification but not the H2AK119-ubiquitin (Ub) mark. Upon T cell stimulation mediated by both CD3 and CD28, the Xi accumulated H2AK119-Ub at gene regions of previous H3K27me3 enrichment. T cell receptor (TCR) engagement, specifically NF-κB signaling downstream of the TCR, was required for Xist RNA localization to the Xi. Disruption of NF-κB signaling in mouse and human T cells using genetic deletion, chemical inhibitors, and patients with immunodeficiencies prevented Xist/XIST RNA accumulation at the Xi and altered X-linked gene expression. Our findings reveal a previously undescribed connection between NF-κB signaling pathways, which affects XCI maintenance in T cells in females.

Insulin-like growth factor 2 mRNA-binding protein 1 (IGF2BP1) in hematological diseases.

The oncofetal mRNA-binding protein IGF2BP1 belongs to a conserved family of RNA-binding proteins. It primarily promotes RNA stability, regulates translation and RNA localization, and mediates gene expression through its downstream effectors. Numerous studies have demonstrated that IGF2BP1 plays crucial roles in embryogenesis and carcinogenesis. IGF2BP1-modulated cell proliferation, invasion, and chemo-resistance in solid tumors have attracted researchers' attention. Additionally, several studies have highlighted the importance of IGF2BP1 in hematologic malignancies and hematological genetic diseases, positioning it as a promising therapeutic target for hematological disorders. However, there is a lack of systematic summaries regarding the IGF2BP1 gene within the hematological field. In this review, we provide a comprehensive overview of the discovery and molecular structure of IGF2BP1, along with recent studies on its role in regulating embryogenesis. We also focus on the mechanisms by which IGF2BP1 regulates hematological malignancies through its interactions with its targeted mRNAs. Furthermore, we systematically elucidate the function and mechanism of IGF2BP1 in promoting fetal hemoglobin expression in adult hematopoietic stem/progenitor cells. Finally, we discuss the limitations and challenges of IGF2BP1 as a therapeutic target, offering insights into its prospects.

APEX2 proximity labeling of RNA in bacteria.

Studies over the past several years have shown that distinct RNAs can be targeted to subcellular locations in bacterial cells. The ability to investigate localized RNAs in bacteria is currently limited to imaging-based approaches or to laborious procedures to isolate ribonucleoprotein complexes by grad-seq, HITS-CLIP, or Rloc-seq. However, a major challenge in studying mRNA localization in bacterial cells is that bacterial mRNAs typically last for only a few minutes in the cell, while experiments to investigate their localization or interaction partners can take much longer. Therefore, rapid methods of studying RNA localization are needed to bridge this technical challenge.

RNA in axons, dendrites, synapses and beyond.

In neurons, a diverse range of coding and non-coding RNAs localize to axons, dendrites, and synapses, where they facilitate rapid responses to local needs, such as axon and dendrite extension and branching, synapse formation, and synaptic plasticity. Here, we review the extent of our current understanding of RNA subclass diversity in these functionally demanding subcellular compartments. We discuss the similarities and differences identified between axonal, dendritic and synaptic local transcriptomes, and discuss the reported and hypothesized fates and functions of localized RNAs. Furthermore, we outline the RNA composition of exosomes that bud off from neurites, and their implications for the biology of neighboring cells. Finally, we highlight recent advances in third-generation sequencing technologies that will likely provide transformative insights into splice isoform and RNA modification diversity in local transcriptomes.

Subcellular Level Spatial Transcriptomics with PHOTON.

The subcellular localization of RNA is closely linked to its function. Many RNA species are partitioned into organelles and other subcellular compartments for storage, processing, translation, or degradation. Thus, capturing the subcellular spatial distribution of RNA would directly contribute to the understanding of RNA functions and regulation. Here, we present PHOTON (Photoselection of Transcriptome over Nanoscale), a method which combines high resolution imaging with high throughput sequencing to achieve spatial transcriptome profiling at subcellular resolution. We demonstrate PHOTON as a versatile tool to accurately capture the transcriptome of target cell types in situ at the tissue level such as granulosa cells in the ovary, as well as RNA content within subcellular compartments such as the nucleolus and the stress granule. Using PHOTON, we also reveal the functional role of m6A modification on mRNA partitioning into stress granules. These results collectively demonstrate that PHOTON is a flexible and generalizable platform for understanding subcellular molecular dynamics through the transcriptomic lens.

Role of the SAF-A SAP domain in X inactivation, transcription, splicing, and cell proliferation.

SAF-A is conserved throughout vertebrates and has emerged as an important factor regulating a multitude of nuclear functions, including lncRNA localization, gene expression, and splicing. SAF-A has several functional domains, including an N-terminal SAP domain that binds directly to DNA. Phosphorylation of SAP domain serines S14 and S26 are important for SAF-A localization and function during mitosis, however whether these serines are involved in interphase functions of SAF-A is not known. In this study we tested for the role of the SAP domain, and SAP domain serines S14 and S26 in X chromosome inactivation, protein dynamics, gene expression, splicing, and cell proliferation. Here we show that the SAP domain serines S14 and S26 are required to maintain XIST RNA localization and polycomb-dependent histone modifications on the inactive X chromosome in female cells. In addition, we present evidence that an Xi localization signal resides in the SAP domain. We found that that the SAP domain is not required to maintain gene expression and plays only a minor role in mRNA splicing. In contrast, the SAF-A SAP domain, in particular serines S14 and S26, are required for normal protein dynamics, and to maintain normal cell proliferation. We propose a model whereby dynamic phosphorylation of SAF-A serines S14 and S26 mediates rapid turnover of SAF-A interactions with DNA during interphase.