Subcellular mRNA localization in animal cells and why it matters

Tetrahydropyrimidine Ionizable Lipids for Efficient mRNA Delivery

Lipid nanoparticles (LNPs) have emerged as an effective and promising technology for messenger RNA (mRNA) delivery, offering a potential solution to physiological barriers and providing an alternative approach to gene therapy without the drawbacks associated with viral delivery. However, efficiently delivering mRNA remains a significant challenge in nucleic acid-based therapies due to the limitations of current LNP platforms in achieving optimal endosomal escape and mRNA release, which largely relies on finding a suitable ionizable lipid. Additionally, the synthesis of these ionizable lipids involves multiple chemical reactions, often making the process time-consuming and difficult to translate. In this study, we employed a facile, catalyst-free, and versatile one-pot multicomponent reaction (MCR) to develop a library of ionizable lipids featuring a pharmacologically significant tetrahydropyrimidine (THP) backbone, tailored for enhanced mRNA delivery. A library of 26 THP ionizable lipids was systematically synthesized in just 3 h and formulated with luciferase mRNA for initial in vitro screening. The THP LNPs exhibited tunable particle sizes, favorable ζ-potentials, and high encapsulation efficiencies. Among them, THP1 demonstrated the highest transfection efficiency both in vitro and in vivo after intramuscular administration, comparable to DLin-MC3-DMA (MC3), a conventional benchmark. Further optimization of THP1 with phospholipids significantly enhanced intramuscular mRNA delivery and showed sustained protein expression in vivo for up to 5 days. More importantly, it demonstrated successful intravenous delivery in a dose-dependent manner with minimal toxicity, as indicated by hematological, histopathological, and proinflammatory cytokine assessments. Furthermore, THP1 LNPs also demonstrated the ability to edit genes in specific liver tissues in a tdTomato transgenic mouse model, highlighting their precision and utility in targeted therapeutic applications. These findings position THP1 LNPs as promising candidates for advancing mRNA-based therapies, with significant implications for clinical translation in vaccine delivery and CRISPR/Cas9-mediated gene editing in the liver.

RNA granules in flux: dynamics to balance physiology and pathology

The life cycle of an mRNA is a complex process that is tightly regulated by interactions between the mRNA and RNA-binding proteins, forming molecular machines known as RNA granules. Various types of these membrane-less organelles form inside cells, including neurons, and contribute critically to various physiological processes. RNA granules are constantly in flux, change dynamically and adapt to their local environment, depending on their intracellular localization. The discovery that RNA condensates can form by liquid-liquid phase separation expanded our understanding of how compartments may be generated in the cell. Since then, a plethora of new functions have been proposed for distinct condensates in cells that await their validation in vivo. The finding that dysregulation of RNA granules (for example, stress granules) is likely to affect neurodevelopmental and neurodegenerative diseases further boosted interest in this topic. RNA granules have various physiological functions in neurons and in the brain that we would like to focus on. We outline examples of state-of-the-art experiments including timelapse microscopy in neurons to unravel the precise functions of various types of RNA granule. Finally, we distinguish physiologically occurring RNA condensation from aberrant aggregation, induced by artificial RNA overexpression, and present visual examples to discriminate both forms in neurons.

Answering open questions in biology using spatial genomics and structured methods

Genomics methods have uncovered patterns in a range of biological systems, but obscure important aspects of cell behavior: the shapes, relative locations, movement, and interactions of cells in space. Spatial technologies that collect genomic or epigenomic data while preserving spatial information have begun to overcome these limitations. These new data promise a deeper understanding of the factors that affect cellular behavior, and in particular the ability to directly test existing theories about cell state and variation in the context of morphology, location, motility, and signaling that could not be tested before. Rapid advancements in resolution, ease-of-use, and scale of spatial genomics technologies to address these questions also require an updated toolkit of statistical methods with which to interrogate these data. We present a framework to respond to this new avenue of research: four open biological questions that can now be answered using spatial genomics data paired with methods for analysis. We outline spatial data modalities for each open question that may yield specific insights, discuss how conflicting theories may be tested by comparing the data to conceptual models of biological behavior, and highlight statistical and machine learning-based tools that may prove particularly helpful to recover biological understanding.

Deciphering 3'UTR Mediated Gene Regulation Using Interpretable Deep Representation Learning

The 3' untranslated regions (3'UTRs) of messenger RNAs contain many important cis-regulatory elements that are under functional and evolutionary constraints. It is hypothesized that these constraints are similar to grammars and syntaxes in human languages and can be modeled by advanced natural language techniques such as Transformers, which has been very effective in modeling complex protein sequence and structures. Here 3UTRBERT is described, which implements an attention-based language model, i.e., Bidirectional Encoder Representations from Transformers (BERT). 3UTRBERT is pre-trained on aggregated 3'UTR sequences of human mRNAs in a task-agnostic manner; the pre-trained model is then fine-tuned for specific downstream tasks such as identifying RBP binding sites, m6A RNA modification sites, and predicting RNA sub-cellular localizations. Benchmark results show that 3UTRBERT generally outperformed other contemporary methods in each of these tasks. More importantly, the self-attention mechanism within 3UTRBERT allows direct visualization of the semantic relationship between sequence elements and effectively identifies regions with important regulatory potential. It is expected that 3UTRBERT model can serve as the foundational tool to analyze various sequence labeling tasks within the 3'UTR fields, thus enhancing the decipherability of post-transcriptional regulatory mechanisms.

Centrocortin potentiates co-translational localization of its mRNA to the centrosome via dynein

Centrosomes rely upon proteins within the pericentriolar material to nucleate and organize microtubules. Several mRNAs also reside at centrosomes, although less is known about how and why they accumulate there. We previously showed that local Centrocortin (Cen) mRNA supports centrosome separation, microtubule organization, and viability in Drosophila embryos. Here, using Cen mRNA as a model, we examine mechanisms of centrosomal mRNA localization. We find that while the Cen N'-terminus is sufficient for protein enrichment at centrosomes, multiple domains cooperate to concentrate Cen mRNA at this location. We further identify an N'-terminal motif within Cen that is conserved among dynein cargo adaptor proteins and test its contribution to RNA localization. Our results support a model whereby Cen protein enables the accumulation of its own mRNA to centrosomes through a mechanism requiring active translation, microtubules, and the dynein motor complex. Taken together, our data uncover the basis of translation-dependent localization of a centrosomal RNA required for mitotic integrity.

Transcriptomics : Approaches to Quantifying Gene Expression and Their Application to Studying the Human Brain

To date, the field of transcriptomics has been characterized by rapid methods development and technological advancement, with new technologies continuously rendering older ones obsolete.This chapter traces the evolution of approaches to quantifying gene expression and provides an overall view of the current state of the field of transcriptomics, its applications to the study of the human brain, and its place in the broader emerging multiomics landscape.

Orchestrated centers for the production of proteins or "translation factories"

The mechanics of how proteins are generated from mRNA is increasingly well understood. However, much less is known about how protein production is coordinated and orchestrated within the crowded intracellular environment, especially in eukaryotic cells. Recent studies suggest that localized sites exist for the coordinated production of specific proteins. These sites have been termed "translation factories" and roles in protein complex formation, protein localization, inheritance, and translation regulation have been postulated. In this article, we review the evidence supporting the translation of mRNA at these sites, the details of their mechanism of formation, and their likely functional significance. Finally, we consider the key uncertainties regarding these elusive structures in cells. This article is categorized under: Translation Translation > Mechanisms RNA Export and Localization > RNA Localization Translation > Regulation.

mRCat: A Novel CatBoost Predictor for the Binary Classification of mRNA Subcellular Localization by Fusing Large Language Model Representation and Sequence Features

The subcellular localization of messenger RNAs (mRNAs) is a pivotal aspect of biomolecules, tightly linked to gene regulation and protein synthesis, and offers innovative insights into disease diagnosis and drug development in the field of biomedicine. Several computational methods have been proposed to predict the subcellular localization of mRNAs within cells. However, there remains a deficiency in the accuracy of these predictions. In this study, we propose an mRCat predictor based on the gradient boosting tree algorithm specifically to predict whether mRNAs are localized in the nucleus or in the cytoplasm. This predictor firstly uses large language models to thoroughly explore hidden information within sequences and then integrates traditional sequence features to collectively characterize mRNA gene sequences. Finally, it employs CatBoost as the base classifier for predicting the subcellular localization of mRNAs. The experimental validation on an independent test set demonstrates that mRCat obtained accuracy of 0.761, F1 score of 0.710, MCC of 0.511, and AUROC of 0.751. The results indicate that our method has higher accuracy and robustness compared to other state-of-the-art methods. It is anticipated to offer deep insights for biomolecular research.

MulStack: An ensemble learning prediction model of multilabel mRNA subcellular localization

Subcellular localization of mRNA is related to protein synthesis, cell polarity, cell movement and other biological regulation mechanisms. The distribution of mRNAs in subcellulars is similar to that of proteins, and most mRNAs are distributed in multiple subcellulars. Recently, some computational methods have been designed to predict the subcellular localization of mRNA. However, these methods only employed a sin-gle level of mRNA features and did not employ the position encoding of nucleotides in mRNA. In this paper, an ensemble learning prediction model is proposed, named MulStack, which is based on random forest and deep learning for multilabel mRNA subcellular localization. The proposed method employs two levels of mRNA features, including sequence-level and residue-level features, and position encoding is employed for the first time in the field of subcellular localization of mRNA. Random forest is employed to learn mRNA sequence-level feature, deep learning is employed to learn mRNA sequence-level feature and mRNA residue-level combined with position encoding. And the outputs of random forest and deep learning model will be weighted sum as the prediction probability. Compared with existing methods, the results show that MulStack is the best in the localization of the nucleus, cytosol and exosome. In addition, position weight matrices (PWMs) are extracted by convolutional neural networks (CNNs) that can be matched with known RNA binding protein motifs. Gene ontology (GO) enrichment analysis shows biological processes, molecular functions and cellular components of mRNA genes. The prediction web server of MulStack is freely accessible at http://bliulab.net/MulStack.

Ago2/CAV1 interaction potentiates metastasis via controlling Ago2 localization and miRNA action

Ago2 differentially regulates oncogenic and tumor-suppressive miRNAs in cancer cells. This discrepancy suggests a secondary event regulating Ago2/miRNA action in a context-dependent manner. We show here that a positive charge of Ago2 K212, that is preserved by SIR2-mediated Ago2 deacetylation in cancer cells, is responsible for the direct interaction between Ago2 and Caveolin-1 (CAV1). Through this interaction, CAV1 sequesters Ago2 on the plasma membranes and regulates miRNA-mediated translational repression in a compartment-dependent manner. Ago2/CAV1 interaction plays a role in miRNA-mediated mRNA suppression and in miRNA release via extracellular vesicles (EVs) from tumors into the circulation, which can be used as a biomarker of tumor progression. Increased Ago2/CAV1 interaction with tumor progression promotes aggressive cancer behaviors, including metastasis. Ago2/CAV1 interaction acts as a secondary event in miRNA-mediated suppression and increases the complexity of miRNA actions in cancer.

SparseRNAfolD: optimized sparse RNA pseudoknot-free folding with dangle consideration

MOTIVATION

Computational RNA secondary structure prediction by free energy minimization is indispensable for analyzing structural RNAs and their interactions. These methods find the structure with the minimum free energy (MFE) among exponentially many possible structures and have a restrictive time and space complexity ( O ( n 3 ) time and O ( n 2 ) space for pseudoknot-free structures) for longer RNA sequences. Furthermore, accurate free energy calculations, including dangle contributions can be difficult and costly to implement, particularly when optimizing for time and space requirements.

RESULTS

Here we introduce a fast and efficient sparsified MFE pseudoknot-free structure prediction algorithm, SparseRNAFolD, that utilizes an accurate energy model that accounts for dangle contributions. While the sparsification technique was previously employed to improve the time and space complexity of a pseudoknot-free structure prediction method with a realistic energy model, SparseMFEFold, it was not extended to include dangle contributions due to the complexity of computation. This may come at the cost of prediction accuracy. In this work, we compare three different sparsified implementations for dangle contributions and provide pros and cons of each method. As well, we compare our algorithm to LinearFold, a linear time and space algorithm, where we find that in practice, SparseRNAFolD has lower memory consumption across all lengths of sequence and a faster time for lengths up to 1000 bases.

CONCLUSION

Our SparseRNAFolD algorithm is an MFE-based algorithm that guarantees optimality of result and employs the most general energy model, including dangle contributions. We provide a basis for applying dangles to sparsified recursion in a pseudoknot-free model that has the potential to be extended to pseudoknots.

MRSLpred-a hybrid approach for predicting multi-label subcellular localization of mRNA at the genome scale

In the past, several methods have been developed for predicting the single-label subcellular localization of messenger RNA (mRNA). However, only limited methods are designed to predict the multi-label subcellular localization of mRNA. Furthermore, the existing methods are slow and cannot be implemented at a transcriptome scale. In this study, a fast and reliable method has been developed for predicting the multi-label subcellular localization of mRNA that can be implemented at a genome scale. Machine learning-based methods have been developed using mRNA sequence composition, where the XGBoost-based classifier achieved an average area under the receiver operator characteristic (AUROC) of 0.709 (0.668-0.732). In addition to alignment-free methods, we developed alignment-based methods using motif search techniques. Finally, a hybrid technique that combines the XGBoost model and the motif-based approach has been developed, achieving an average AUROC of 0.742 (0.708-0.816). Our method-MRSLpred-outperforms the existing state-of-the-art classifier in terms of performance and computation efficiency. A publicly accessible webserver and a standalone tool have been developed to facilitate researchers (webserver: https://webs.iiitd.edu.in/raghava/mrslpred/).

The role of midbody-associated mRNAs in regulating abscission

Midbodies function during telophase to regulate the abscission step of cytokinesis. Until recently, it was thought that abscission-regulating proteins, such as ESCRT-III complex subunits, accumulate at the MB by directly or indirectly binding to the MB resident protein, CEP55. However, recent studies have shown that depletion of CEP55 does not fully block ESCRT-III targeting the MB. Here, we show that MBs contain mRNAs and that these MB-associated mRNAs can be locally translated, resulting in the accumulation of abscission-regulating proteins. We demonstrate that localized MB-associated translation of CHMP4B is required for its targeting to the abscission site and that 3' UTR-dependent CHMP4B mRNA targeting to the MB is required for successful completion of cytokinesis. Finally, we identify regulatory cis-elements within RNAs that are necessary and sufficient for mRNA trafficking to the MB. We propose a novel method of regulating cytokinesis and abscission by MB-associated targeting and localized translation of selective mRNAs.

RNA trafficking and subcellular localization-a review of mechanisms, experimental and predictive methodologies

RNA localization is essential for regulating spatial translation, where RNAs are trafficked to their target locations via various biological mechanisms. In this review, we discuss RNA localization in the context of molecular mechanisms, experimental techniques and machine learning-based prediction tools. Three main types of molecular mechanisms that control the localization of RNA to distinct cellular compartments are reviewed, including directed transport, protection from mRNA degradation, as well as diffusion and local entrapment. Advances in experimental methods, both image and sequence based, provide substantial data resources, which allow for the design of powerful machine learning models to predict RNA localizations. We review the publicly available predictive tools to serve as a guide for users and inspire developers to build more effective prediction models. Finally, we provide an overview of multimodal learning, which may provide a new avenue for the prediction of RNA localization.

Physiological and engineered tRNA aminoacylation

Aminoacyl-tRNA synthetases form the protein family that controls the interpretation of the genetic code, with tRNA aminoacylation being the key chemical step during which an amino acid is assigned to a corresponding sequence of nucleic acids. In consequence, aminoacyl-tRNA synthetases have been studied in their physiological context, in disease states, and as tools for synthetic biology to enable the expansion of the genetic code. Here, we review the fundamentals of aminoacyl-tRNA synthetase biology and classification, with a focus on mammalian cytoplasmic enzymes. We compile evidence that the localization of aminoacyl-tRNA synthetases can be critical in health and disease. In addition, we discuss evidence from synthetic biology which made use of the importance of subcellular localization for efficient manipulation of the protein synthesis machinery. This article is categorized under: RNA Processing Translation > Translation Regulation RNA Processing > tRNA Processing RNA Export and Localization > RNA Localization.

Control of mRNA fate by its encoded nascent polypeptide

Cells tightly regulate mRNA processing, localization, and stability to ensure accurate gene expression in diverse cellular states and conditions. Most of these regulatory steps have traditionally been thought to occur before translation by the action of RNA-binding proteins. Several recent discoveries highlight multiple co-translational mechanisms that modulate mRNA translation, localization, processing, and stability. These mechanisms operate by recognition of the nascent protein, which is necessarily coupled to its encoding mRNA during translation. Hence, the distinctive sequence or structure of a particular nascent chain can recruit recognition factors with privileged access to the corresponding mRNA in an otherwise crowded cellular environment. Here, we draw on both well-established and recent examples to provide a conceptual framework for how cells exploit nascent protein recognition to direct mRNA fate. These mechanisms allow cells to dynamically and specifically regulate their transcriptomes in response to changes in cellular states to maintain protein homeostasis.

Developmental Genetic Basis of Hoxd9 Homeobox Domain Deletion in Pampus argenteus Pelvic Fin Deficiency

Pampus argenteus is important for commercial fishery catch species and is an emerging target for aquaculture production. Notably, P. argenteus has a bizarre morphology and lacks pelvic fins. However, the reason for the lack of pelvic fins remains unclear, ultimately leading to frequent upside-down floating of P. argenteus during breeding and marked consumption of physical energy. Some lineages, including whales, fugu, snakes, and seahorse, independently lost the pelvic appendages over evolutionary time. Do different taxa employ the same molecular genetic pathways when they independently evolve similar developmental morphologies? Through analysis of the gene responsible for appendage localization, Hoxd9, it was discovered that the Hox domain was absent in the Hoxd9 gene of P. argenteus, and the Hoxd9b gene lacked the Hox9 activation region, a feature not observed in the Hoxd9 gene of other fish species. Interestingly, those distinctive characteristics are not observed in the Hoxd9 gene of other fish species. To determine the association between the Hoxd9 gene characteristics and the pelvic fin deletion in P. argenteus, the full-length cDNA of the Hoxd9a gene was cloned, and morphological observations of the species' juveniles were performed using stereomicroscopy and scanning electron microscopy. Thereafter, the tissue localization of Hoxd9a in the species was analyzed at the gene and protein levels. Based on the results, deletion of the Hoxd9a structural domain possibly leads to disruptions in the protein translation and the pelvic fin localization in P. argenteus during its early ontogenetic developmental stage, resulting in the absence of pelvic fins.

RNA binding proteins in senescence: A potential common linker for age-related diseases?

Aging represents the major risk factor for the onset and/or progression of various disorders including neurodegenerative diseases, metabolic disorders, and bone-related defects. As the average age of the population is predicted to exponentially increase in the coming years, understanding the molecular mechanisms underlying the development of aging-related diseases and the discovery of new therapeutic approaches remain pivotal. Well-reported hallmarks of aging are cellular senescence, genome instability, autophagy impairment, mitochondria dysfunction, dysbiosis, telomere attrition, metabolic dysregulation, epigenetic alterations, low-grade chronic inflammation, stem cell exhaustion, altered cell-to-cell communication and impaired proteostasis. With few exceptions, however, many of the molecular players implicated within these processes as well as their role in disease development remain largely unknown. RNA binding proteins (RBPs) are known to regulate gene expression by dictating at post-transcriptional level the fate of nascent transcripts. Their activity ranges from directing primary mRNA maturation and trafficking to modulation of transcript stability and/or translation. Accumulating evidence has shown that RBPs are emerging as key regulators of aging and aging-related diseases, with the potential to become new diagnostic and therapeutic tools to prevent or delay aging processes. In this review, we summarize the role of RBPs in promoting cellular senescence and we highlight their dysregulation in the pathogenesis and progression of the main aging-related diseases, with the aim of encouraging further investigations that will help to better disclose this novel and captivating molecular scenario.

Apicobasal RNA asymmetries regulate cell fate in the early mouse embryo

The spatial sorting of RNA transcripts is fundamental for the refinement of gene expression to distinct subcellular regions. Although, in non-mammalian early embryogenesis, differential RNA localisation presages cell fate determination, in mammals it remains unclear. Here, we uncover apical-to-basal RNA asymmetries in outer blastomeres of 16-cell stage mouse preimplantation embryos. Basally directed RNA transport is facilitated in a microtubule- and lysosome-mediated manner. Yet, despite an increased accumulation of RNA transcripts in basal regions, higher translation activity occurs at the more dispersed apical RNA foci, demonstrated by spatial heterogeneities in RNA subtypes, RNA-organelle interactions and translation events. During the transition to the 32-cell stage, the biased inheritance of RNA transcripts, coupled with differential translation capacity, regulates cell fate allocation of trophectoderm and cells destined to form the pluripotent inner cell mass. Our study identifies a paradigm for the spatiotemporal regulation of post-transcriptional gene expression governing mammalian preimplantation embryogenesis and cell fate.

The nexus between RNA-binding proteins and their effectors

RNA-binding proteins (RBPs) regulate essentially every event in the lifetime of an RNA molecule, from its production to its destruction. Whereas much has been learned about RNA sequence specificity and general functions of individual RBPs, the ways in which numerous RBPs instruct a much smaller number of effector molecules, that is, the core engines of RNA processing, as to where, when and how to act remain largely speculative. Here, we survey the known modes of communication between RBPs and their effectors with a particular focus on converging RBP-effector interactions and their roles in reducing the complexity of RNA networks. We discern the emerging unifying principles and discuss their utility in our understanding of RBP function, regulation of biological processes and contribution to human disease.

DeepmRNALoc: A Novel Predictor of Eukaryotic mRNA Subcellular Localization Based on Deep Learning

The subcellular localization of messenger RNA (mRNA) precisely controls where protein products are synthesized and where they function. However, obtaining an mRNA's subcellular localization through wet-lab experiments is time-consuming and expensive, and many existing mRNA subcellular localization prediction algorithms need to be improved. In this study, a deep neural network-based eukaryotic mRNA subcellular location prediction method, DeepmRNALoc, was proposed, utilizing a two-stage feature extraction strategy that featured bimodal information splitting and fusing for the first stage and a VGGNet-like CNN module for the second stage. The five-fold cross-validation accuracies of DeepmRNALoc in the cytoplasm, endoplasmic reticulum, extracellular region, mitochondria, and nucleus were 0.895, 0.594, 0.308, 0.944, and 0.865, respectively, demonstrating that it outperforms existing models and techniques.

Light and temperature regulate m6A-RNA modification to regulate growth in plants

N6-methyladenosine is a highly dynamic, abundant mRNA modification which is an excellent potential mechanism for fine tuning gene expression. Plants adapt to their surrounding light and temperature environment using complex gene regulatory networks. The role of m6A in controlling gene expression in response to variable environmental conditions has so far been unexplored. Here, we map the transcriptome-wide m6A landscape under various light and temperature environments. Identified m6A-modifications show a highly specific spatial distribution along transcripts with enrichment occurring in 5'UTR regions and around transcriptional end sites. We show that the position of m6A modifications on transcripts might influence cellular transcript localization and the presence of m6A-modifications is associated with alternative polyadenylation, a process which results in multiple RNA isoforms with varying 3'UTR lengths. RNA with m6A-modifications exhibit a higher preference for shorter 3'UTRs. These shorter 3'UTR regions might directly influence transcript abundance and localization by including or excluding cis-regulatory elements. We propose that environmental stimuli might change the m6A landscape of plants as one possible way of fine tuning gene regulation through alternative polyadenylation and transcript localization.

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.

Spatially resolved transcriptomics: advances and applications

Spatial transcriptomics, which is capable of both measuring all gene activity in a tissue sample and mapping where this activity occurs, is vastly improving our understanding of biological processes and disease. The field has expanded rapidly in recent years, and the development of several new technologies has resulted in spatially resolved transcriptomics (SRT) becoming highly multiplexed, high-resolution, and high-throughput. Here, we summarize and compare the major methods of SRT, including imaging-based methods, sequencing-based methods, and in situ sequencing methods. We also highlight some typical applications of SRT in neuroscience, cancer biology, developmental biology, and hematology. Finally, we discuss future possibilities for improving spatially resolved transcriptomic methods and the expected applications of such methods, especially in the adult bone marrow, anticipating that new developments will unlock the full potential of spatially resolved multi-omics in both biological research and the clinic.

Regulation of RNA localization during oocyte maturation by dynamic RNA-ER association and remodeling of the ER

Asymmetric localization of mRNAs is crucial for cell polarity and cell fate determination. By performing fractionation RNA-seq, we report here that a large number of maternal RNAs are associated with the ER in Xenopus oocytes but are released into the cytosol after oocyte maturation. We provide evidence that the majority of ER-associated RNA-binding proteins (RBPs) remain associated with the ER after oocyte maturation. However, all ER-associated RBPs analyzed exhibit reduced binding to some of their target RNAs after oocyte maturation. Our results further show that the ER is remodeled massively during oocyte maturation, leading to the formation of a widespread tubular ER network in the animal hemisphere that is required for the asymmetric localization of mRNAs in mature eggs. Thus, our findings demonstrate that dynamic regulation of RNA-ER association and remodeling of the ER are important for the asymmetric localization of RNAs during development.

RNA-Binding Proteins as Epigenetic Regulators of Brain Functions and Their Involvement in Neurodegeneration

A central aspect of nervous system development and function is the post-transcriptional regulation of mRNA fate, which implies time- and site-dependent translation, in response to cues originating from cell-to-cell crosstalk. Such events are fundamental for the establishment of brain cell asymmetry, as well as of long-lasting modifications of synapses (long-term potentiation: LTP), responsible for learning, memory, and higher cognitive functions. Post-transcriptional regulation is in turn dependent on RNA-binding proteins that, by recognizing and binding brief RNA sequences, base modifications, or secondary/tertiary structures, are able to control maturation, localization, stability, and translation of the transcripts. Notably, most RBPs contain intrinsically disordered regions (IDRs) that are thought to be involved in the formation of membrane-less structures, probably due to liquid-liquid phase separation (LLPS). Such structures are evidenced as a variety of granules that contain proteins and different classes of RNAs. The other side of the peculiar properties of IDRs is, however, that, under altered cellular conditions, they are also prone to form aggregates, as observed in neurodegeneration. Interestingly, RBPs, as part of both normal and aggregated complexes, are also able to enter extracellular vesicles (EVs), and in doing so, they can also reach cells other than those that produced them.

A massively parallel reporter assay reveals focused and broadly encoded RNA localization signals in neurons

Asymmetric subcellular mRNA localization allows spatial regulation of gene expression and functional compartmentalization. In neurons, localization of specific mRNAs to neurites is essential for cellular functioning. However, it is largely unknown how transcript sorting works in a sequence-specific manner. Here, we combined subcellular transcriptomics and massively parallel reporter assays and tested ∼50 000 sequences for their ability to localize to neurites. Mapping the localization potential of >300 genes revealed two ways neurite targeting can be achieved: focused localization motifs and broadly encoded localization potential. We characterized the interplay between RNA stability and localization and identified motifs able to bias localization towards neurite or soma as well as the trans-acting factors required for their action. Based on our data, we devised machine learning models that were able to predict the localization behavior of novel reporter sequences. Testing this predictor on native mRNA sequencing data showed good agreement between predicted and observed localization potential, suggesting that the rules uncovered by our MPRA also apply to the localization of native full-length transcripts.

An introduction to spatial transcriptomics for biomedical research

Single-cell transcriptomics (scRNA-seq) has become essential for biomedical research over the past decade, particularly in developmental biology, cancer, immunology, and neuroscience. Most commercially available scRNA-seq protocols require cells to be recovered intact and viable from tissue. This has precluded many cell types from study and largely destroys the spatial context that could otherwise inform analyses of cell identity and function. An increasing number of commercially available platforms now facilitate spatially resolved, high-dimensional assessment of gene transcription, known as 'spatial transcriptomics'. Here, we introduce different classes of method, which either record the locations of hybridized mRNA molecules in tissue, image the positions of cells themselves prior to assessment, or employ spatial arrays of mRNA probes of pre-determined location. We review sizes of tissue area that can be assessed, their spatial resolution, and the number and types of genes that can be profiled. We discuss if tissue preservation influences choice of platform, and provide guidance on whether specific platforms may be better suited to discovery screens or hypothesis testing. Finally, we introduce bioinformatic methods for analysing spatial transcriptomic data, including pre-processing, integration with existing scRNA-seq data, and inference of cell-cell interactions. Spatial -omics methods are already improving our understanding of human tissues in research, diagnostic, and therapeutic settings. To build upon these recent advancements, we provide entry-level guidance for those seeking to employ spatial transcriptomics in their own biomedical research.

KnotAli: informed energy minimization through the use of evolutionary information

BACKGROUND

Improving the prediction of structures, especially those containing pseudoknots (structures with crossing base pairs) is an ongoing challenge. Homology-based methods utilize structural similarities within a family to predict the structure. However, their prediction is limited to the consensus structure, and by the quality of the alignment. Minimum free energy (MFE) based methods, on the other hand, do not rely on familial information and can predict structures of novel RNA molecules. Their prediction normally suffers from inaccuracies due to their underlying energy parameters.

RESULTS

We present a new method for prediction of RNA pseudoknotted secondary structures that combines the strengths of MFE prediction and alignment-based methods. KnotAli takes a multiple RNA sequence alignment as input and uses covariation and thermodynamic energy minimization to predict possibly pseudoknotted secondary structures for each individual sequence in the alignment. We compared KnotAli's performance to that of three other alignment-based programs, two that can handle pseudoknotted structures and one control, on a large data set of 3034 RNA sequences with varying lengths and levels of sequence conservation from 10 families with pseudoknotted and pseudoknot-free reference structures. We produced sequence alignments for each family using two well-known sequence aligners (MUSCLE and MAFFT).

CONCLUSIONS

We found KnotAli's performance to be superior in 6 of the 10 families for MUSCLE and 7 of the 10 for MAFFT. While both KnotAli and Cacofold use background noise correction strategies, we found KnotAli's predictions to be less dependent on the alignment quality. KnotAli can be found online at the Zenodo image: https://doi.org/10.5281/zenodo.5794719.

Signed, sealed, and delivered: RNA localization and translation at centrosomes

Protein localization is intrinsic to cellular function and specialized activities, such as migration or proliferation. Many localized proteins enrich at defined organelles, forming subdomains of functional activity further specified by interacting protein assemblies. One well-studied organelle showing dynamic, functional changes in protein composition is the centrosome. Centrosomes are microtubule-organizing centers with diverse cellular functions largely defined by the composition of the pericentriolar material, an ordered matrix of proteins organized around a central pair of centrioles. Also localizing to the pericentriolar material are mRNAs. Although RNA was identified at centrosomes decades ago, the characterization of specific RNA transcripts and their functional contributions to centrosome biology remained largely unstudied. While the identification of RNA localized to centrosomes accelerated with the development of high-throughput screening methods, this discovery still outpaces functional characterization. Recent work indicates RNA localized to centrosomes is biologically significant and further implicates centrosomes as sites for local protein synthesis. Distinct RNA localization and translational activities likely contribute to the diversity of centrosome functions within cells.

The Physiological Roles of the Exon Junction Complex in Development and Diseases

The exon junction complex (EJC) becomes an increasingly important regulator of early gene expression in the central nervous system (CNS) and other tissues. The EJC is comprised of three core proteins: RNA-binding motif 8A (RBM8A), Mago homolog (MAGOH), eukaryotic initiation factor 4A3 (EIF4A3), and a peripheral EJC factor, metastatic lymph node 51 (MLN51), together with various auxiliary factors. The EJC is assembled specifically at exon-exon junctions on mRNAs, hence the name of the complex. The EJC regulates multiple levels of gene expression, from splicing to translation and mRNA degradation. The functional roles of the EJC have been established as crucial to the normal progress of embryonic and neurological development, with wide ranging implications on molecular, cellular, and organism level function. Dysfunction of the EJC has been implicated in multiple developmental and neurological diseases. In this review, we discuss recent progress on the EJC’s physiological roles.

How to assemble a scale-invariant gradient

Intracellular protein gradients serve a variety of functions, such as the establishment of cell polarity or to provide positional information for gene expression in developing embryos. Given that cell size in a population can vary considerably, for the protein gradients to work properly they often have to be scaled to the size of the cell. Here, we examine a model of protein gradient formation within a cell that relies on cytoplasmic diffusion and cortical transport of proteins toward a cell pole. We show that the shape of the protein gradient is determined solely by the cell geometry. Furthermore, we show that the length scale over which the protein concentration in the gradient varies is determined by the linear dimensions of the cell, independent of the diffusion constant or the transport speed. This gradient provides scale-invariant positional information within a cell, which can be used for assembly of intracellular structures whose size is scaled to the linear dimensions of the cell, such as the cytokinetic ring and actin cables in budding yeast cells.

Application of RNA subcellular fraction estimation method to explore RNA localization regulation

RNA localization is involved in multiple biological processes. Recent advances in subcellular fractionation-based sequencing approaches uncovered localization pattern on a global scale. Most of existing methods adopt relative localization ratios (such as ratios of separately normalized transcripts per millions of different subcellular fractions without considering the difference in total RNA abundances in different fractions), however, absolute ratios may yield different results on the preference to different cellular compartment. Experimentally, adding external Spike-in RNAs to different fractionation can be used to obtain absolute ratios. In addition, a spike-in independent computational approach based on multiple linear regression model can also be used. However, currently, no custom tool is available. To solve this problem, we developed a method called subcellular fraction abundance estimator to correctly estimate relative RNA abundances of different subcellular fractionations. The ratios estimated by our method were consistent with existing reports. By applying the estimated ratios for different fractions, we explored the RNA localization pattern in cell lines and also predicted RBP motifs that were associated with different localization patterns. In addition, we showed that different isoforms of same genes could exhibit distinct localization patterns. To conclude, we believed our tool will facilitate future subcellular fractionation-related sequencing study to explore the function of RNA localization in various biological problems.

In Vitro Reconstitution of Kinesin-Based, Axonal mRNA Transport

Motor protein-driven transport of mRNAs on microtubules and their local translation underlie important neuronal functions such as development, growth cone steering, and synaptic plasticity. While there is abundant data on how membrane-bound cargoes such as vesicles, endosomes, or mitochondria are coupled to motor proteins, surprisingly little is known on the direct interactions of RNA-protein complexes and kinesins or dynein. Provided the potential building blocks are identified, in vitro reconstitutions coupled to Total Internal Reflection Microscopy (TIRF-M) are a powerful and highly sensitive tool to understand how single molecules dynamically interact to assemble into functional complexes. Here we describe how we assemble TIRF-M imaging chambers suitable for the imaging of single protein-RNA complexes. We give advice on optimal sample preparation procedures and explain how a minimal axonal mRNA transport complex can be assembled in vitro. As these assays work at picomolar-range concentrations of proteins and RNAs, they allow the investigation of molecules that cannot be obtained at high concentrations, such as many large or disordered proteins. This now opens the possibility to study how RNA-binding proteins (RBPs), RNAs, and microtubule-associated proteins act together in real-time at single-molecule sensitivity to create cytoplasmic mRNA distributions.

Exploring the Diverse Functional and Regulatory Consequences of Alternative Splicing in Development and Disease

Alternative splicing is a fundamental mechanism of eukaryotic RNA regulation that increases the transcriptomic and proteomic complexity within an organism. Moreover, alternative splicing provides a framework for generating unique yet complex tissue- and cell type-specific gene expression profiles, despite using a limited number of genes. Recent efforts to understand the negative consequences of aberrant splicing have increased our understanding of developmental and neurodegenerative diseases such as spinal muscular atrophy, frontotemporal dementia and Parkinsonism linked to chromosome 17, myotonic dystrophy, and amyotrophic lateral sclerosis. Moreover, these studies have led to the development of innovative therapeutic treatments for diseases caused by aberrant splicing, also known as spliceopathies. Despite this, a paucity of information exists on the physiological roles and specific functions of distinct transcript spliceforms for a given gene. Here, we will highlight work that has specifically explored the distinct functions of protein-coding spliceforms during development. Moreover, we will discuss the use of alternative splicing of noncoding exons to regulate the stability and localization of RNA transcripts.

Axonal mRNA localization and translation: local events with broad roles

Messenger RNA (mRNA) can be transported and targeted to different subcellular compartments and locally translated. Local translation is an evolutionally conserved mechanism that in mammals, provides an important tool to exquisitely regulate the subcellular proteome in different cell types, including neurons. Local translation in axons is involved in processes such as neuronal development, function, plasticity, and diseases. Here, we summarize the current progress on axonal mRNA transport and translation. We focus on the regulatory mechanisms governing how mRNAs are transported to axons and how they are locally translated in axons. We discuss the roles of axonally synthesized proteins, which either function locally in axons, or are retrogradely trafficked back to soma to achieve neuron-wide gene regulation. We also examine local translation in neurological diseases. Finally, we give a critical perspective on the remaining questions that could be answered to uncover the fundamental rules governing local translation, and discuss how this could lead to new therapeutic targets for neurological diseases.

In vivo discovery of RNA proximal proteins via proximity-dependent biotinylation

RNA molecules function as messenger RNAs (mRNAs) that encode proteins and noncoding transcripts that serve as adaptor molecules, structural components, and regulators of genome organization and gene expression. Their function and regulation are largely mediated by RNA binding proteins (RBPs). Here we present RNA proximity labelling (RPL), an RNA-centric method comprising the endonuclease-deficient Type VI CRISPR-Cas protein dCas13b fused to engineered ascorbate peroxidase APEX2. RPL discovers target RNA proximal proteins in vivo via proximity-based biotinylation. RPL applied to U1 identified proteins involved in both U1 canonical and noncanonical functions. Profiling of poly(A) tail proximal proteins uncovered expected categories of RBPs and provided additional evidence for 5'-3' proximity and unexplored subcellular localizations of poly(A)+ RNA. Our results suggest that RPL allows rapid identification of target RNA binding proteins in native cellular contexts, and is expected to pave the way for discovery of novel RNA-protein interactions important for health and disease.

RGS4 RNA Secondary Structure Mediates Staufen2 RNP Assembly in Neurons

RNA-binding proteins (RBPs) act as posttranscriptional regulators controlling the fate of target mRNAs. Unraveling how RNAs are recognized by RBPs and in turn are assembled into neuronal RNA granules is therefore key to understanding the underlying mechanism. While RNA sequence elements have been extensively characterized, the functional impact of RNA secondary structures is only recently being explored. Here, we show that Staufen2 binds complex, long-ranged RNA hairpins in the 3′-untranslated region (UTR) of its targets. These structures are involved in the assembly of Staufen2 into RNA granules. Furthermore, we provide direct evidence that a defined Rgs4 RNA duplex regulates Staufen2-dependent RNA localization to distal dendrites. Importantly, disrupting the RNA hairpin impairs the observed effects. Finally, we show that these secondary structures differently affect protein expression in neurons. In conclusion, our data reveal the importance of RNA secondary structure in regulating RNA granule assembly, localization and eventually translation. It is therefore tempting to speculate that secondary structures represent an important code for cells to control the intracellular fate of their mRNAs.

The Identification and Functional Analysis of mRNA Localizing to Centrosomes

Centrosomes are multifunctional organelles tasked with organizing the microtubule cytoskeleton required for genome stability, intracellular trafficking, and ciliogenesis. Contributing to the diversity of centrosome functions are cell cycle-dependent oscillations in protein localization and post-translational modifications. Less understood is the role of centrosome-localized messenger RNA (mRNA). Since its discovery, the concept of nucleic acids at the centrosome was controversial, and physiological roles for centrosomal mRNAs remained muddled and underexplored. Over the past decades, however, transcripts, RNA-binding proteins, and ribosomes were detected at the centrosome in various organisms and cell types, hinting at a conservation of function. Indeed, recent work defines centrosomes as sites of local protein synthesis, and defined mRNAs were recently implicated in regulating centrosome functions. In this review, we summarize the evidence for the presence of mRNA at the centrosome and the current work that aims to unravel the biological functions of mRNA localized to centrosomes.

Linking transport and translation of mRNAs with endosomes and mitochondria

In eukaryotic cells, proteins are targeted to their final subcellular locations with precise timing. A key underlying mechanism is the active transport of cognate mRNAs, which in many systems can be linked intimately to membrane trafficking. A prominent example is the long-distance endosomal transport of mRNAs and their local translation. Here, we describe current highlights of fundamental mechanisms of the underlying transport process as well as of biological functions ranging from endosperm development in plants to fungal pathogenicity and neuronal processes. Translation of endosome-associated mRNAs often occurs at the cytoplasmic surface of endosomes, a process that is needed for membrane-assisted formation of heteromeric protein complexes and for accurate subcellular targeting of proteins. Importantly, endosome-coupled translation of mRNAs encoding mitochondrial proteins, for example, seems to be particularly important for efficient organelle import and for regulating subcellular mitochondrial activity. In essence, these findings reveal a new mechanism of loading newly synthesised proteins onto endocytic membranes enabling intimate crosstalk between organelles. The novel link between endosomes and mitochondria adds an inspiring new level of complexity to trafficking and organelle biology.

Non-coding RNA Regulated Cross-Talk Between Mitochondria and Other Cellular Compartments

Mitochondria are the main hubs for cellular energy production. Metabolites produced in mitochondria not only feed many important biosynthesis pathways but also function as signaling molecules. Mitochondrial biosynthesis requires collaboration of both nuclear and mitochondrial gene expression systems. In addition, mitochondria have to quickly respond to changes inside and outside the cells and have their own functional states reported to the nucleus and other cellular compartments. The underlying molecular mechanisms of these complex regulations have not been well understood. Recent evidence indicates that in addition to small molecules, non-coding RNAs may contribute to the communication between mitochondria and other cellular compartments and may even serve as signals. In this review, we summarize the current knowledge about mitochondrial non-coding RNAs (including nucleus-encoded non-coding RNAs that are imported into mitochondria and mitochondrion-encoded non-coding RNAs that are exported), their trafficking and their functions in co-regulation of mitochondrial and other cellular processes.

Connexin mRNA distribution in adult mouse kidneys

Kidneys are thought to express eight different connexin isoforms (i.e., Cx 26, 30, 32, 37, 40, 43, 45, and 46), which form either hemichannels or gap junctions serving to intercellular communication and functional synchronization. Proper function of connexins has already been shown to be crucial for regulation of renal hemodynamics and renin secretion, and there is also growing evidence for connexins to play a role in pathologic conditions such as renal fibrosis or diabetic nephropathy. Therefore, exact intrarenal localization of the different connexin isoforms gains particular interest. Until now intrarenal expression of connexins has mainly been examined by immunohistochemistry, which in part generated conflicting results depending on antibodies and fixation protocols used. In this work, we used fluorescent RNAscope as an alternative technical approach to localize renal connexin mRNAs in healthy mouse kidneys. Addition of RNAscope probes for cell type specific mRNAs was used to assign connexin mRNA signals to specific cell types. We hereby found Cx26 mRNA strongly expressed in proximal tubules, Cx30 mRNA was selectively detected in the urothelium, and Cx32 mRNA was found in proximal tubules and to a lesser extent also in collecting ducts. Cx37 mRNA was mainly associated with vascular endothelium, Cx40 mRNA was largely found in glomerular mesangial and less in vascular endothelial cells, Cx43 mRNA was sparsely expressed by interstitial cells of all kidney zones, and Cx45 mRNA was predominantly found in smooth muscle cell layers of both blood vessels and ureter as well as in mesangial and interstitial (fibroblastic) cells. Cx46 mRNA could not be detected. In summary our results essentially confirm previous data on connexin expression in the renal vasculature and in glomeruli. In addition, they demonstrate strong connexin gene expression in proximal tubules, and they suggest significant connexin expression in resident tubulointerstitial cells.

mRNA distribution in skeletal muscle is associated with mRNA size

Skeletal muscle myofibers are large and elongated cells with multiple and evenly distributed nuclei. Nuclear distribution suggests that each nucleus influences a specific compartment within the myofiber and implies a functional role for nuclear positioning. Compartmentalization of specific mRNAs and proteins has been reported at the neuromuscular and myotendinous junctions, but mRNA distribution in non-specialized regions of the myofibers remains largely unexplored. We report that the bulk of mRNAs are enriched around the nucleus of origin and that this perinuclear accumulation depends on recently transcribed mRNAs. Surprisingly, mRNAs encoding large proteins - giant mRNAs - are spread throughout the cell and do not exhibit perinuclear accumulation. Furthermore, by expressing exogenous transcripts with different sizes we found that size contributes to mRNA spreading independently of mRNA sequence. Both these mRNA distribution patterns depend on microtubules and are independent of nuclear dispersion, mRNA expression level and stability, and the characteristics of the encoded protein. Thus, we propose that mRNA distribution in non-specialized regions of skeletal muscle is size selective to ensure cellular compartmentalization and simultaneous long-range distribution of giant mRNAs.

mLoc-mRNA: predicting multiple sub-cellular localization of mRNAs using random forest algorithm coupled with feature selection via elastic net

BACKGROUND

Localization of messenger RNAs (mRNAs) plays a crucial role in the growth and development of cells. Particularly, it plays a major role in regulating spatio-temporal gene expression. The in situ hybridization is a promising experimental technique used to determine the localization of mRNAs but it is costly and laborious. It is also a known fact that a single mRNA can be present in more than one location, whereas the existing computational tools are capable of predicting only a single location for such mRNAs. Thus, the development of high-end computational tool is required for reliable and timely prediction of multiple subcellular locations of mRNAs. Hence, we develop the present computational model to predict the multiple localizations of mRNAs.

RESULTS

The mRNA sequences from 9 different localizations were considered. Each sequence was first transformed to a numeric feature vector of size 5460, based on the k-mer features of sizes 1-6. Out of 5460 k-mer features, 1812 important features were selected by the Elastic Net statistical model. The Random Forest supervised learning algorithm was then employed for predicting the localizations with the selected features. Five-fold cross-validation accuracies of 70.87, 68.32, 68.36, 68.79, 96.46, 73.44, 70.94, 97.42 and 71.77% were obtained for the cytoplasm, cytosol, endoplasmic reticulum, exosome, mitochondrion, nucleus, pseudopodium, posterior and ribosome respectively. With an independent test set, accuracies of 65.33, 73.37, 75.86, 72.99, 94.26, 70.91, 65.53, 93.60 and 73.45% were obtained for the respective localizations. The developed approach also achieved higher accuracies than the existing localization prediction tools.

CONCLUSIONS

This study presents a novel computational tool for predicting the multiple localization of mRNAs. Based on the proposed approach, an online prediction server "mLoc-mRNA" is accessible at http://cabgrid.res.in:8080/mlocmrna/ . The developed approach is believed to supplement the existing tools and techniques for the localization prediction of mRNAs.

DM3Loc: multi-label mRNA subcellular localization prediction and analysis based on multi-head self-attention mechanism

Subcellular localization of messenger RNAs (mRNAs), as a prevalent mechanism, gives precise and efficient control for the translation process. There is mounting evidence for the important roles of this process in a variety of cellular events. Computational methods for mRNA subcellular localization prediction provide a useful approach for studying mRNA functions. However, few computational methods were designed for mRNA subcellular localization prediction and their performance have room for improvement. Especially, there is still no available tool to predict for mRNAs that have multiple localization annotations. In this paper, we propose a multi-head self-attention method, DM3Loc, for multi-label mRNA subcellular localization prediction. Evaluation results show that DM3Loc outperforms existing methods and tools in general. Furthermore, DM3Loc has the interpretation ability to analyze RNA-binding protein motifs and key signals on mRNAs for subcellular localization. Our analyses found hundreds of instances of mRNA isoform-specific subcellular localizations and many significantly enriched gene functions for mRNAs in different subcellular localizations.

The GUL-1 Protein Binds Multiple RNAs Involved in Cell Wall Remodeling and Affects the MAK-1 Pathway in Neurospora crassa

The Neurospora crassa GUL-1 is part of the COT-1 pathway, which plays key roles in regulating polar hyphal growth and cell wall remodeling. We show that GUL-1 is a bona fide RNA-binding protein (RBP) that can associate with 828 "core" mRNA species. When cell wall integrity (CWI) is challenged, expression of over 25% of genomic RNA species are modulated (2,628 mRNAs, including the GUL-1 mRNA). GUL-1 binds mRNAs of genes related to translation, cell wall remodeling, circadian clock, endoplasmic reticulum (ER), as well as CWI and MAPK pathway components. GUL-1 interacts with over 100 different proteins, including stress-granule and P-body proteins, ER components and components of the MAPK, COT-1, and STRIPAK complexes. Several additional RBPs were also shown to physically interact with GUL-1. Under stress conditions, GUL-1 can localize to the ER and affect the CWI pathway-evident via altered phosphorylation levels of MAK-1, interaction with mak-1 transcript, and involvement in the expression level of the transcription factor adv-1. We conclude that GUL-1 functions in multiple cellular processes, including the regulation of cell wall remodeling, via a mechanism associated with the MAK-1 pathway and stress-response.

RNAs as Regulators of Cellular Matchmaking

RNA molecules are increasingly being identified as facilitating or impeding the interaction of proteins and nucleic acids, serving as so-called scaffolds or decoys. Long non-coding RNAs have been commonly implicated in such roles, particularly in the regulation of nuclear processes including chromosome topology, regulation of chromatin state and gene transcription, and assembly of nuclear biomolecular condensates such as paraspeckles. Recently, an increased awareness of cytoplasmic RNA scaffolds and decoys has begun to emerge, including the identification of non-coding regions of mRNAs that can also function in a scaffold-like manner to regulate interactions of nascently translated proteins. Collectively, cytoplasmic RNA scaffolds and decoys are now implicated in processes such as mRNA translation, decay, protein localization, protein degradation and assembly of cytoplasmic biomolecular condensates such as P-bodies. Here, we review examples of RNA scaffolds and decoys in both the nucleus and cytoplasm, illustrating common themes, the suitability of RNA to such roles, and future challenges in identifying and better understanding RNA scaffolding and decoy functions.

mRNALocater: Enhance the prediction accuracy of eukaryotic mRNA subcellular localization by using model fusion strategy

The functions of mRNAs are closely correlated with their locations in cells. Knowledge about the subcellular locations of mRNA is helpful to understand their biological functions. In recent years, it has become a hot topic to develop effective computational models to predict eukaryotic mRNA subcellular localizations. However, existing state-of-the-art models still have certain deficiencies in terms of prediction accuracy and generalization ability. Therefore, it is urgent to develop novel methods to accurately predict mRNA subcellular localizations. In this study, a novel method called mRNALocater was proposed to detect the subcellular localization of eukaryotic mRNA by adopting the model fusion strategy. To fully extract information from mRNA sequences, the electron-ion interaction pseudopotential and pseudo k-tuple nucleotide composition were used to encode the sequences. Moreover, the correlation coefficient filtering algorithm and feature forward search technology were used to mine hidden feature information, which guarantees that mRNALocater can be more effectively applied to new sequences. The results based on the independent dataset tests demonstrate that mRNALocater yields promising performances for predicting eukaryotic mRNA subcellular localizations and is a powerful tool in practical applications. A freely available online web server for mRNALocater has been established at http://bio-bigdata.cn/mRNALocater.

Aberrant cytoplasmic intron retention is a blueprint for RNA binding protein mislocalization in VCP-related amyotrophic lateral sclerosis

We recently described aberrantly increased cytoplasmic SFPQ intron-retaining transcripts (IRTs) and concurrent SFPQ protein mislocalization as new hallmarks of amyotrophic lateral sclerosis (ALS). However, the generalizability and potential roles of cytoplasmic IRTs in health and disease remain unclear. Here, using time-resolved deep sequencing of nuclear and cytoplasmic fractions of human induced pluripotent stem cells undergoing motor neurogenesis, we reveal that ALS-causing VCP gene mutations lead to compartment-specific aberrant accumulation of IRTs. Specifically, we identify >100 IRTs with increased cytoplasmic abundance in ALS samples. Furthermore, these aberrant cytoplasmic IRTs possess sequence-specific attributes and differential predicted binding affinity to RNA binding proteins. Remarkably, TDP-43, SFPQ and FUS—RNA binding proteins known for nuclear-to-cytoplasmic mislocalization in ALS—abundantly and specifically bind to this aberrant cytoplasmic pool of IRTs. Our data are therefore consistent with a novel role for cytoplasmic IRTs in regulating compartment-specific protein abundance. This study provides new molecular insight into potential pathomechanisms underlying ALS and highlights aberrant cytoplasmic IRTs as potential therapeutic targets.