3D exploration of gene expression in chicken embryos through combined RNA fluorescence in situ hybridization, immunofluorescence, and clearing.

BACKGROUND: Fine characterization of gene expression patterns is crucial to understand many aspects of embryonic development. The chicken embryo is a well-established and valuable animal model for developmental biology. The period spanning from the third to sixth embryonic days (E3 to E6) is critical for many organ developments. Hybridization chain reaction RNA fluorescent in situ hybridization (HCR RNA-FISH) enables multiplex RNA detection in thick samples including embryos of various animal models. However, its use is limited by tissue opacity. RESULTS: We optimized HCR RNA-FISH protocol to efficiently label RNAs in whole mount chicken embryos from E3.5 to E5.5 and adapted it to ethyl cinnamate (ECi) tissue clearing. We show that light sheet imaging of HCR RNA-FISH after ECi clearing allows RNA expression analysis within embryonic tissues with good sensitivity and spatial resolution. Finally, whole mount immunofluorescence can be performed after HCR RNA-FISH enabling as exemplified to assay complex spatial relationships between axons and their environment or to monitor GFP electroporated neurons. CONCLUSIONS: We could extend the use of HCR RNA-FISH to older chick embryos by optimizing HCR RNA-FISH and combining it with tissue clearing and 3D imaging. The integration of immunostaining makes possible to combine gene expression with classical cell markers, to correlate expressions with morphological differentiation and to depict gene expressions in gain or loss of function contexts. Altogether, this combined procedure further extends the potential of HCR RNA-FISH technique for chicken embryology.

Role of epigenetics and alterations in RNA metabolism in leukodystrophies.

Leukodystrophies are a class of rare heterogeneous disorders which affect the white matter of the brain, ultimately leading to a disruption in brain development and a damaging effect on cognitive, motor and social-communicative development. These disorders present a great clinical heterogeneity, along with a phenotypic overlap and this could be partially due to contributions from environmental stimuli. It is in this context that there is a great need to investigate what other factors may contribute to both disease insurgence and phenotypical heterogeneity, and novel evidence are raising the attention toward the study of epigenetics and transcription mechanisms that can influence the disease phenotype beyond genetics. Modulation in the epigenetics machinery including histone modifications, DNA methylation and non-coding RNAs dysregulation, could be crucial players in the development of these disorders, and moreover an aberrant RNA maturation process has been linked to leukodystrophies. Here, we provide an overview of these mechanisms hoping to supply a closer step toward the analysis of leukodystrophies not only as genetically determined but also with an added level of complexity where epigenetic dysregulation is of key relevance. This article is categorized under: Regulatory RNAs/RNAi/Riboswitches > Regulatory RNA RNA in Disease and Development > RNA in Disease RNA in Disease and Development > RNA in Development.

Nonspecific Interactions in Transcription Regulation and Organization of Transcriptional Condensates.

Eukaryotic cells are characterized by a high degree of compartmentalization of their internal contents, which ensures precise and controlled regulation of intracellular processes. During many processes, including different stages of transcription, dynamic membraneless compartments termed biomolecular condensates are formed. Transcription condensates contain various transcription factors and RNA polymerase and are formed by high- and low-specificity interactions between the proteins, DNA, and nearby RNA. This review discusses recent data demonstrating important role of nonspecific multivalent protein-protein and RNA-protein interactions in organization and regulation of transcription.

Sample-Wise and Gene-Wise Comparisons Confirm a Greater Similarity of RNA and Protein Expression Data at the Level of Molecular Pathways and Suggest an Approach for the Data Quality Check in High-Throughput Expression Databases.

Identification of genes and molecular pathways with congruent profiles in the proteomic and transcriptomic datasets may result in the discovery of promising transcriptomic biomarkers that would be more relevant to phenotypic changes. In this study, we conducted comparative analysis of 943 paired RNA and proteomic profiles obtained for the same samples of seven human cancer types from The Cancer Genome Atlas (TCGA) and NCI Clinical Proteomic Tumor Analysis Consortium (CPTAC) [two major open human cancer proteomic and transcriptomic databases] that included 15,112 protein-coding genes and 1611 molecular pathways. Overall, our findings demonstrated statistically significant improvement of the congruence between RNA and proteomic profiles when performing analysis at the level of molecular pathways rather than at the level of individual gene products. Transition to the molecular pathway level of data analysis increased the correlation to 0.19-0.57 (Pearson) and 0.14-057 (Spearman), or 2-3-fold for some cancer types. Evaluating the gain of the correlation upon transition to the data analysis the pathway level can be used to refine the omics data by identifying outliers that can be excluded from the comparison of RNA and proteomic profiles. We suggest using sample- and gene-wise correlations for individual genes and molecular pathways as a measure of quality of RNA/protein paired molecular data. We also provide a database of human genes, molecular pathways, and samples related to the correlation between RNA and protein products to facilitate an exploration of new cancer transcriptomic biomarkers and molecular mechanisms at different levels of human gene expression.

Causal gene regulatory analysis with RNA velocity reveals an interplay between slow and fast transcription factors.

Single-cell expression dynamics, from differentiation trajectories or RNA velocity, have the potential to reveal causal links between transcription factors (TFs) and their target genes in gene regulatory networks (GRNs). However, existing methods either overlook these expression dynamics or necessitate that cells be ordered along a linear pseudotemporal axis, which is incompatible with branching trajectories. We introduce Velorama, an approach to causal GRN inference that represents single-cell differentiation dynamics as a directed acyclic graph of cells, constructed from pseudotime or RNA velocity measurements. Additionally, Velorama enables the estimation of the speed at which TFs influence target genes. Applying Velorama, we uncover evidence that the speed of a TF's interactions is tied to its regulatory function. For human corticogenesis, we find that slow TFs are linked to gliomas, while fast TFs are associated with neuropsychiatric diseases. We expect Velorama to become a critical part of the RNA velocity toolkit for investigating the causal drivers of differentiation and disease.

RNA tailing machinery drives amyloidogenic phase transition.

The RNA tailing machinery adds nucleotides to the 3'-end of RNA molecules that are implicated in various biochemical functions, including protein synthesis and RNA stability. Here, we report a role for the RNA tailing machinery as enzymatic modifiers of intracellular amyloidogenesis. A targeted RNA interference screen identified Terminal Nucleotidyl-transferase 4b (TENT4b/Papd5) as an essential participant in the amyloidogenic phase transition of nucleoli into solid-like Amyloid bodies. Full-length-and-mRNA sequencing uncovered starRNA, a class of unusually long untemplated RNA molecules synthesized by TENT4b. StarRNA consists of short rRNA fragments linked to long, linear mixed tails that operate as polyanionic stimulators of amyloidogenesis in cells and in vitro. Ribosomal intergenic spacer noncoding RNA (rIGSRNA) recruit TENT4b in intranucleolar foci to coordinate starRNA synthesis driving their amyloidogenic phase transition. The exoribonuclease RNA Exosome degrades starRNA and functions as a general suppressor of cellular amyloidogenesis. We propose that amyloidogenic phase transition is under tight enzymatic control by the RNA tailing and exosome axis.

The RNA-DNA world and the emergence of DNA-encoded heritable traits.

The RNA world hypothesis confers a central role to RNA molecules in information encoding and catalysis. Even though evidence in support of this hypothesis has accumulated from both experiments and computational modelling, the transition from an RNA world to a world where heritable genetic information is encoded in DNA remains an open question. Recent experiments show that both RNA and DNA templates can extend complementary primers using free RNA/DNA nucleotides, either non-enzymatically or in the presence of a replicase ribozyme. Guided by these experiments, we analyse protocellular evolution with an expanded set of reaction pathways made possible through the presence of DNA nucleotides. By encapsulating these reactions inside three different types of protocellular compartments, each subject to distinct modes of selection, we show how protocells containing DNA-encoded replicases in low copy numbers and replicases in high copy numbers can dominate the population. This is facilitated by a reaction that leads to auto-catalytic synthesis of replicase ribozymes from DNA templates encoding the replicase after the chance emergence of a replicase through non-enzymatic reactions. Our work unveils a pathway for the transition from an RNA world to a mixed RNA-DNA world characterized by Darwinian evolution, where DNA sequences encode heritable phenotypes.

Structures, mechanisms and applications of RNA-centric CRISPR-Cas13.

Prokaryotes are equipped with a variety of resistance strategies to survive frequent viral attacks or invading mobile genetic elements. Among these, CRISPR-Cas surveillance systems are abundant and have been studied extensively. This Review focuses on CRISPR-Cas type VI Cas13 systems that use single-subunit RNA-guided Cas endonucleases for targeting and subsequent degradation of foreign RNA, thereby providing adaptive immunity. Notably, distinct from single-subunit DNA-cleaving Cas9 and Cas12 systems, Cas13 exhibits target RNA-activated substrate RNase activity. This Review outlines structural, biochemical and cell biological studies toward elucidation of the unique structural and mechanistic principles underlying surveillance effector complex formation, precursor CRISPR RNA (pre-crRNA) processing, self-discrimination and RNA degradation in Cas13 systems as well as insights into suppression by bacteriophage-encoded anti-CRISPR proteins and regulation by endogenous accessory proteins. Owing to its programmable ability for RNA recognition and cleavage, Cas13 provides powerful RNA targeting, editing, detection and imaging platforms with emerging biotechnological and therapeutic applications.

Comprehensive review on lipid metabolism and RNA methylation: Biological mechanisms, perspectives and challenges.

Adipose tissue plays a crucial role in maintaining energy balance, regulating hormones, and promoting metabolic health. To address disorders related to obesity and develop effective therapies, it is essential to have a deep understanding of adipose tissue biology. In recent years, RNA methylation has emerged as a significant epigenetic modification involved in various cellular functions and metabolic pathways. Particularly in the realm of adipogenesis and lipid metabolism, extensive research is ongoing to uncover the mechanisms and functional importance of RNA methylation. Increasing evidence suggests that RNA methylation plays a regulatory role in adipocyte development, metabolism, and lipid utilization across different organs. This comprehensive review aims to provide an overview of common RNA methylation modifications, their occurrences, and regulatory mechanisms, focusing specifically on their intricate connections to fat metabolism. Additionally, we discuss the research methodologies used in studying RNA methylation and highlight relevant databases that can aid researchers in this rapidly advancing field.

Unveiling the mystery of nuclear RNA homeostasis.

How nuclear RNA homeostasis impacts cellular functions remains elusive. In this issue of Cell Stem Cell, Han et al.1 utilized a controllable protein degradation system targeting EXOSC2 to perturb RNA homeostasis in mouse pluripotent embryonic stem cells, revealing its vital role in orchestrating crucial nuclear events for cellular fitness.

Zinc N,N-bis(2-picolyl)amine Chelates Show Substitution-Dependent Cleavage of Phosphodiesters in Models as Well as of PNAzyme-RNA Bulges.

PNAzymes are a group of artificial enzymes which show promising results in selective and efficient cleavage of RNA targets. In the present study, we introduce a series of metal chelating groups based on N,N-bis(2-picolyl) groups (parent, 6-methyl and 6-amino substituted) as the active sites of novel PNAzymes. An improved synthetic route for the 6-amino analogues is described. The catalytic activity of the chelating groups for cleaving phosphodiesters were assessed with the model substrate 2-hydroxypropyl p-nitrophenyl phosphate (HPNPP), confirming that the zinc complexes have the reactivity order of parent < 2-methyl < 2-amino. The three ligands were conjugated to a PNA oligomer to form three PNAzymes which showed the same order of reactivity and some sensitivity to the size of the RNA bulge designed into the catalyst-substrate complex. This work demonstrates that the kinetic activity observed for the model substrate HPNPP could be translated onto the PNAzymes, but that more reactive Zn complexes are required for such PNAzymes to be viable therapeutic agents.

Subcellular localization of circular RNAs: Where and why.

Localization of RNAs at specific subcellular locations regulating various local cellular events has gained much attention recently. Like most other classes of RNAs, the function of newly discovered circular RNAs (circRNAs) is predominantly determined by their association with different cellular factors in the cell. CircRNAs function as transcriptional and posttranscriptional regulators of gene expression by interacting with transcription factors, splicing regulators, RNA-binding proteins, and microRNAs or by translating into functional polypeptides. Hence, studying their subcellular localization to assess their function is essential. The discovery of more than a million circRNA and increasing evidence of their involvement in development and diseases require a thorough analysis of their subcellular localization linking to their biological functions. Here, we summarize current knowledge of circRNA localization in cells and extracellular vesicles, factors regulating their subcellular localization, and the implications of circRNA localization on their cellular functions. Given the discovery of many circRNAs in all life forms and their implications in pathophysiology, we discuss the challenges in studying circRNA localization and the opportunities for unlocking the mystery of circRNA functions.

Characterisation of the Arabidopsis thaliana telomerase TERT-TR complex.

Most eukaryotic organisms employ a telomerase complex for the maintenance of chromosome ends. The core of this complex is composed of telomerase reverse transcriptase (TERT) and telomerase RNA (TR) subunits. The TERT reverse transcriptase (RT) domain synthesises telomeric DNA using the TR template sequence. The other TERT domains contribute to this process in different ways. In particular, the TERT RNA-binding domain (TRBD) interacts with specific TR motif(s). Using a yeast 3-hybrid system, we show the critical role of Arabidopsis thaliana (At) TRBD and embryophyta-conserved KRxR motif in the unstructured linker preceding the TRBD domain for binding to the recently identified AtTR subunit. We also show the essential role of the predicted P4 stem and pseudoknot AtTR structures and provide evidence for the binding of AtTRBD to pseudoknot and KRxR motif stabilising interaction with the P4 stem structure. Our results thus provide the first insight into the core part of the plant telomerase complex.

Transfer learning enables identification of multiple types of RNA modifications using nanopore direct RNA sequencing.

Nanopore direct RNA sequencing (DRS) has emerged as a powerful tool for RNA modification identification. However, concurrently detecting multiple types of modifications in a single DRS sample remains a challenge. Here, we develop TandemMod, a transferable deep learning framework capable of detecting multiple types of RNA modifications in single DRS data. To train high-performance TandemMod models, we generate in vitro epitranscriptome datasets from cDNA libraries, containing thousands of transcripts labeled with various types of RNA modifications. We validate the performance of TandemMod on both in vitro transcripts and in vivo human cell lines, confirming its high accuracy for profiling m6A and m5C modification sites. Furthermore, we perform transfer learning for identifying other modifications such as m7G, Ψ, and inosine, significantly reducing training data size and running time without compromising performance. Finally, we apply TandemMod to identify 3 types of RNA modifications in rice grown in different environments, demonstrating its applicability across species and conditions. In summary, we provide a resource with ground-truth labels that can serve as benchmark datasets for nanopore-based modification identification methods, and TandemMod for identifying diverse RNA modifications using a single DRS sample.

Dynamic changes in RNA m6A and 5 hmC influence gene expression programs during macrophage differentiation and polarisation.

RNA modifications are essential for the establishment of cellular identity. Although increasing evidence indicates that RNA modifications regulate the innate immune response, their role in monocyte-to-macrophage differentiation and polarisation is unclear. While m6A has been widely studied, other RNA modifications, including 5 hmC, remain poorly characterised. We profiled m6A and 5 hmC epitranscriptomes, transcriptomes, translatomes and proteomes of monocytes and macrophages at rest and pro- and anti-inflammatory states. Transcriptome-wide mapping of m6A and 5 hmC reveals enrichment of m6A and/or 5 hmC on specific categories of transcripts essential for macrophage differentiation. Our analyses indicate that m6A and 5 hmC modifications are present in transcripts with critical functions in pro- and anti-inflammatory macrophages. Notably, we also discover the co-occurrence of m6A and 5 hmC on alternatively-spliced isoforms and/or opposing ends of the untranslated regions (UTR) of mRNAs with key roles in macrophage biology. In specific examples, RNA 5 hmC controls the decay of transcripts independently of m6A. This study provides (i) a comprehensive dataset to interrogate the role of RNA modifications in a plastic system (ii) a resource for exploring different layers of gene expression regulation in the context of human monocyte-to-macrophage differentiation and polarisation, (iii) new insights into RNA modifications as central regulators of effector cells in innate immunity.

Special Issue "Bioinformatics of Unusual DNA and RNA Structures".

Nucleic acids are not only static carriers of genetic information but also play vital roles in controlling cellular lifecycles through their fascinating structural diversity [...].

MLm5C: A high-precision human RNA 5-methylcytosine sites predictor based on a combination of hybrid machine learning models.

RNA modification serves as a pivotal component in numerous biological processes. Among the prevalent modifications, 5-methylcytosine (m5C) significantly influences mRNA export, translation efficiency and cell differentiation and are also associated with human diseases, including Alzheimer's disease, autoimmune disease, cancer, and cardiovascular diseases. Identification of m5C is critically responsible for understanding the RNA modification mechanisms and the epigenetic regulation of associated diseases. However, the large-scale experimental identification of m5C present significant challenges due to labor intensity and time requirements. Several computational tools, using machine learning, have been developed to supplement experimental methods, but identifying these sites lack accuracy and efficiency. In this study, we introduce a new predictor, MLm5C, for precise prediction of m5C sites using sequence data. Briefly, we evaluated eleven RNA sequence-derived features with four basic machine learning algorithms to generate baseline models. From these 44 models, we ranked them based on their performance and subsequently stacked the Top 20 baseline models as the best model, named MLm5C. The MLm5C outperformed the-state-of-the-art predictors. Notably, the optimization of the sequence length surrounding the modification sites significantly improved the prediction performance. MLm5C is an invaluable tool in accelerating the detection of m5C sites within the human genome, thereby facilitating in the characterization of their roles in post-transcriptional regulation.

Simultaneous Detection of Adenosine-to-Inosine Editing and N6-Methyladenosine at Identical RNA Sites through Deamination-Assisted Reverse Transcription Stalling.

Adenosine-to-inosine (A-to-I) editing and N6-methyladenosine (m6A) modifications are pivotal RNA modifications with widespread functional significance in physiological and pathological processes. Although significant effort has been dedicated to developing methodologies for identifying and quantifying these modifications, traditional approaches have often focused on each modification independently, neglecting the potential co-occurrence of A-to-I editing and m6A modifications at the same adenosine residues. This limitation has constrained our understanding of the intricate regulatory mechanisms governing RNA function and the interplay between different types of RNA modifications. To address this gap, we introduced an innovative technique called deamination-assisted reverse transcription stalling (DARTS), specifically designed for the simultaneous quantification of A-to-I editing and m6A at the same RNA sites. DARTS leverages the selective deamination activity of the engineered TadA-TadA8e protein, which converts adenosine residues to inosine, in combination with the unique property of Bst 2.0 DNA polymerase, which stalls when encountering inosine during reverse transcription. This approach enables the accurate quantification of A-to-I editing, m6A, and unmodified adenosine at identical RNA sites. The DARTS method is remarkable for its ability to directly quantify two distinct types of RNA modifications simultaneously, a capability that has remained largely unexplored in the field of RNA biology. By facilitating a comprehensive analysis of the co-occurrence and interaction between A-to-I editing and m6A modifications, DARTS opens new avenues for exploring the complex regulatory networks modulated by different RNA modifications.