Genome-wide RNA structure changes during human neurogenesis modulate gene regulatory networks

DeepFusion: A deep bimodal information fusion network for unraveling protein-RNA interactions using in vivo RNA structures

RNA-binding proteins (RBPs) are key post-transcriptional regulators, and the malfunctions of RBP-RNA binding lead to diverse human diseases. However, prediction of RBP binding sites is largely based on RNA sequence features, whereas in vivo RNA structural features based on high-throughput sequencing are rarely incorporated. Here, we designed a deep bimodal information fusion network called DeepFusion for unraveling protein-RNA interactions by incorporating structural features derived from DMS-seq data. DeepFusion integrates two sub-models to extract local motif-like information and long-term context information. We show that DeepFusion performs best compared with other cutting-edge methods with only sequence inputs on two datasets. DeepFusion's performance is further improved with bimodal input after adding in vivo DMS-seq structural features. Furthermore, DeepFusion can be used for analyzing RNA degradation, demonstrating significantly different RBP-binding scores in genes with slow degradation rates versus those with rapid degradation rates. DeepFusion thus provides enhanced abilities for further analysis of functional RNAs. DeepFusion's code and data are available at http://bioinfo.org/deepfusion/.

Long non-coding RNA H19 regulates neurogenesis of induced neural stem cells in a mouse model of closed head injury

Stem cell-based therapies have been proposed as a potential treatment for neural regeneration following closed head injury. We previously reported that induced neural stem cells exert beneficial effects on neural regeneration via cell replacement. However, the neural regeneration efficiency of induced neural stem cells remains limited. In this study, we explored differentially expressed genes and long non-coding RNAs to clarify the mechanism underlying the neurogenesis of induced neural stem cells. We found that H19 was the most downregulated neurogenesis-associated lncRNA in induced neural stem cells compared with induced pluripotent stem cells. Additionally, we demonstrated that H19 levels in induced neural stem cells were markedly lower than those in induced pluripotent stem cells and were substantially higher than those in induced neural stem cell-derived neurons. We predicted the target genes of H19 and discovered that H19 directly interacts with miR-325-3p, which directly interacts with Ctbp2 in induced pluripotent stem cells and induced neural stem cells. Silencing H19 or Ctbp2 impaired induced neural stem cell proliferation, and miR-325-3p suppression restored the effect of H19 inhibition but not the effect of Ctbp2 inhibition. Furthermore, H19 silencing substantially promoted the neural differentiation of induced neural stem cells and did not induce apoptosis of induced neural stem cells. Notably, silencing H19 in induced neural stem cell grafts markedly accelerated the neurological recovery of closed head injury mice. Our results reveal that H19 regulates the neurogenesis of induced neural stem cells. H19 inhibition may promote the neural differentiation of induced neural stem cells, which is closely associated with neurological recovery following closed head injury.

RNA structure profiling at single-cell resolution reveals new determinants of cell identity

RNA structure is critical for multiple steps in gene regulation. However, how the structures of transcripts differ both within and between individual cells is unknown. Here we develop a SHAPE-inspired method called single-cell structure probing of RNA transcripts that enables simultaneous determination of transcript secondary structure and abundance at single-cell resolution. We apply single-cell structure probing of RNA transcripts to human embryonic stem cells and differentiating neurons. Remarkably, RNA structure is more homogeneous in human embryonic stem cells compared with neurons, with the greatest homogeneity found in coding regions. More extensive heterogeneity is found within 3' untranslated regions and is determined by specific RNA-binding proteins. Overall RNA structure profiles better discriminate cell type identity and differentiation stage than gene expression profiles alone. We further discover a cell-type variable region of 18S ribosomal RNA that is associated with cell cycle and translation control. Our method opens the door to the systematic characterization of RNA structure-function relationships at single-cell resolution.

2'-OH as a universal handle for studying intracellular RNAs

RNA plays pivotal roles in most cellular processes, serving as both the traditional carrier of genetic information and as a key regulator of cellular functions. The advent of chemical technologies has contributed critically to the analysis of cellular RNA structures, functions, and interactions. Many of these methods and molecules involve the utilization of chemically reactive handles in RNAs, either introduced externally or inherent within the polymer itself. Among these handles, the 2'-hydroxyl (2'-OH) group has emerged as an exceptionally well-suited and general chemical moiety for the modification and profiling of RNAs in intracellular studies. In this review, we provide an overview of the recent advancements in intracellular applications of acylation at the 2'-OH group of RNA. We outline progress made in probing RNA structure and interactomes, controlling RNA function, RNA imaging, and analyzing RNA-small molecule interactions, all achieved in living cells through this simple chemical handle on the biopolymer.

Causes, functions, and therapeutic possibilities of RNA secondary structure ensembles and alternative states

RNA secondary structure plays essential roles in encoding RNA regulatory fate and function. Most RNAs populate ensembles of alternatively paired states and are continually unfolded and refolded by cellular processes. Measuring these structural ensembles and their contributions to cellular function has traditionally posed major challenges, but new methods and conceptual frameworks are beginning to fill this void. In this review, we provide a mechanism- and function-centric compendium of the roles of RNA secondary structural ensembles and minority states in regulating the RNA life cycle, from transcription to degradation. We further explore how dysregulation of RNA structural ensembles contributes to human disease and discuss the potential of drugging alternative RNA states to therapeutically modulate RNA activity. The emerging paradigm of RNA structural ensembles as central to RNA function provides a foundation for a deeper understanding of RNA biology and new therapeutic possibilities.

Emerging roles of RNA ac4C modification and NAT10 in mammalian development and human diseases

RNA ac4C modification is a novel and rare chemical modification observed in mRNA. Traditional biochemical studies had primarily associated ac4C modification with tRNA and rRNA until in 2018, Arango D et al. first reported the presence of ac4C modification on mRNA and demonstrated its critical role in mRNA stability and translation regulation. Furthermore, they established that the ac4C modification on mRNA is mediated by the classical N-acetyltransferase NAT10. Subsequent studies have underscored the essential implications of NAT10 and mRNA ac4C modification across both physiological and pathological regulatory processes. In this review, we aimed to explore the discovery history of RNA ac4C modification, its detection methods, and its regulatory mechanisms in disease and physiological development. We offer a forward-looking examination and discourse concerning the employment of RNA ac4C modification as a prospective therapeutic strategy across diverse diseases. Furthermore, we comprehensively summarize the functions and mechanisms of NAT10 in gene expression regulation and pathogenesis independent of RNA ac4C modification.

HNRNPC haploinsufficiency affects alternative splicing of intellectual disability-associated genes and causes a neurodevelopmental disorder

Heterogeneous nuclear ribonucleoprotein C (HNRNPC) is an essential, ubiquitously abundant protein involved in mRNA processing. Genetic variants in other members of the HNRNP family have been associated with neurodevelopmental disorders. Here, we describe 13 individuals with global developmental delay, intellectual disability, behavioral abnormalities, and subtle facial dysmorphology with heterozygous HNRNPC germline variants. Five of them bear an identical in-frame deletion of nine amino acids in the extreme C terminus. To study the effect of this recurrent variant as well as HNRNPC haploinsufficiency, we used induced pluripotent stem cells (iPSCs) and fibroblasts obtained from affected individuals. While protein localization and oligomerization were unaffected by the recurrent C-terminal deletion variant, total HNRNPC levels were decreased. Previously, reduced HNRNPC levels have been associated with changes in alternative splicing. Therefore, we performed a meta-analysis on published RNA-seq datasets of three different cell lines to identify a ubiquitous HNRNPC-dependent signature of alternative spliced exons. The identified signature was not only confirmed in fibroblasts obtained from an affected individual but also showed a significant enrichment for genes associated with intellectual disability. Hence, we assessed the effect of decreased and increased levels of HNRNPC on neuronal arborization and neuronal migration and found that either condition affects neuronal function. Taken together, our data indicate that HNRNPC haploinsufficiency affects alternative splicing of multiple intellectual disability-associated genes and that the developing brain is sensitive to aberrant levels of HNRNPC. Hence, our data strongly support the inclusion of HNRNPC to the family of HNRNP-related neurodevelopmental disorders.

RNA Structural Dynamics Modulate EGFR-TKI Resistance Through Controlling YRDC Translation in NSCLC Cells

Epidermal growth factor receptor-tyrosine kinase inhibitors (EGFR-TKIs) positively affect the initial control of non-small cell lung cancer (NSCLC). Rapidly acquired resistance to EGFR-TKIs is a major hurdle in successful treatment. However, the mechanisms that control the resistance of EGFR-TKIs remain largely unknown. RNA structures have widespread and crucial functions in many biological regulations; however, the functions of RNA structures in regulating cancer drug resistance remain unclear. Here, the psoralen analysis of RNA interactions and structures (PARIS) method is used to establish the higher-order RNA structure maps of EGFR-TKIs-resistant and -sensitive cells of NSCLC. Our results show that RNA structural regions are enriched in untranslated regions (UTRs) and correlate with translation efficiency (TE). Moreover, yrdC N6-threonylcarbamoyltransferase domain containing (YRDC) promotes resistance to EGFR-TKIs. RNA structure formation in YRDC 3' UTR suppresses embryonic lethal abnormal vision-like 1 (ELAVL1) binding, leading to EGFR-TKI sensitivity by impairing YRDC translation. A potential therapeutic strategy for cancer treatment is provided using antisense oligonucleotide (ASO) to perturb the interaction between RNA and protein. Our study reveals an unprecedented mechanism through which the RNA structure switch modulates EGFR-TKI resistance by controlling YRDC mRNA translation in an ELAVL1-dependent manner.

mRNA isoform balance in neuronal development and disease

Balanced mRNA isoform diversity and abundance are spatially and temporally regulated throughout cellular differentiation. The proportion of expressed isoforms contributes to cell type specification and determines key properties of the differentiated cells. Neurons are unique cell types with intricate developmental programs, characteristic cellular morphologies, and electrophysiological potential. Neuron-specific gene expression programs establish these distinctive cellular characteristics and drive diversity among neuronal subtypes. Genes with neuron-specific alternative processing are enriched in key neuronal functions, including synaptic proteins, adhesion molecules, and scaffold proteins. Despite the similarity of neuronal gene expression programs, each neuronal subclass can be distinguished by unique alternative mRNA processing events. Alternative processing of developmentally important transcripts alters coding and regulatory information, including interaction domains, transcript stability, subcellular localization, and targeting by RNA binding proteins. Fine-tuning of mRNA processing is essential for neuronal activity and maintenance. Thus, the focus of neuronal RNA biology research is to dissect the transcriptomic mechanisms that underlie neuronal homeostasis, and consequently, predispose neuronal subtypes to disease. This article is categorized under: RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

RNAvigator: A Pipeline to Identify Candidates for Functional RNA Structure Elements

Identifying structural elements in long and complex RNAs, such as long non-coding and RNA viruses, can shed light on the functionality and mechanisms of such RNAs. Here we present RNAvigator, a tool able to identify elements of structural importance by using experimental SHAPE data or SHAPE-like predictions in conjunction with stability and entropy assessments. RNAvigator recognizes regions that are the most stable, unambiguous, and structured on RNA molecules, and thus potentially functional. When relying on predictions, RNAvigator uses the CROSS algorithm, a neural network trained on experimental data that achieved an AUC of 0.74 on hepatitis C virus SHAPE-MaP data and which was able to improve the predictive power of Superfold. By using RNAvigator, we can identify known functional regions on the complete hepatitis C virus genome, including the regulatory regions CRE and IRES, and the 3’ UTR of dengue virus, a region known for the presence of structural elements essential for its replication, and functional regions of long non-coding RNAs such as XIST and HOTAIR. We envision that RNAvigator will be a useful tool for studying long and complex RNA molecules using known chemical probing data or, if they are not available, by employing predicted profiles.