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Imaging-based spatial multi-omics technologies facilitate the analysis of higher-order genomic structures, gene transcription, and the localization of proteins and posttranslational modifications (PTMs) at the single-allele level, thereby enabling detailed observations of biological phenomena, including transcription machinery within cells and tissues. This chapter details the principles of such technologies, with a focus on DNA/RNA/immunofluorescence (IF) sequential fluorescence in situ hybridization (seqFISH). A comprehensive step-by-step protocol for image analysis is provided, covering image preprocessing, spot detection, and data visualization. For practical application, complete Jupyter Notebook codes are made available on GitHub ( https://github.com/Ochiai-Lab/seqFISH_analysis ).

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Imaging-based spatial transcriptomics technologies such as Multiplexed error-robust fluorescence in situ hybridization (MERFISH) can capture cellular processes in unparalleled detail. However, rigorous and robust analytical tools are needed to unlock their full potential for discovering subcellular biological patterns. We present Intracellular Spatial Transcriptomic Analysis Toolkit (InSTAnT), a computational toolkit for extracting molecular relationships from spatial transcriptomics data at single molecule resolution. InSTAnT employs specialized statistical tests and algorithms to detect gene pairs and modules exhibiting intriguing patterns of co-localization, both within individual cells and across the cellular landscape. We showcase the toolkit on five different datasets representing two different cell lines, two brain structures, two species, and three different technologies. We perform rigorous statistical assessment of discovered co-localization patterns, find supporting evidence from databases and RNA interactions, and identify associated subcellular domains. We uncover several cell type and region-specific gene co-localizations within the brain. Intra-cellular spatial patterns discovered by InSTAnT mirror diverse molecular relationships, including RNA interactions and shared sub-cellular localization or function, providing a rich compendium of testable hypotheses regarding molecular functions.

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Single-cell RNA sequencing (scRNA-seq) data, susceptible to noise arising from biological variability and technical errors, can distort gene expression analysis and impact cell similarity assessments, particularly in heterogeneous populations. Current methods, including deep learning approaches, often struggle to accurately characterize cell relationships due to this inherent noise. To address these challenges, we introduce scAMF (Single-cell Analysis via Manifold Fitting), a framework designed to enhance clustering accuracy and data visualization in scRNA-seq studies. At the heart of scAMF lies the manifold fitting module, which effectively denoises scRNA-seq data by unfolding their distribution in the ambient space. This unfolding aligns the gene expression vector of each cell more closely with its underlying structure, bringing it spatially closer to other cells of the same cell type. To comprehensively assess the impact of scAMF, we compile a collection of 25 publicly available scRNA-seq datasets spanning various sequencing platforms, species, and organ types, forming an extensive RNA data bank. In our comparative studies, benchmarking scAMF against existing scRNA-seq analysis algorithms in this data bank, we consistently observe that scAMF outperforms in terms of clustering efficiency and data visualization clarity. Further experimental analysis reveals that this enhanced performance stems from scAMF's ability to improve the spatial distribution of the data and capture class-consistent neighborhoods. These findings underscore the promising application potential of manifold fitting as a tool in scRNA-seq analysis, signaling a significant enhancement in the precision and reliability of data interpretation in this critical field of study.

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Double-strand breaks (DSBs) in DNA are challenging to repair. Cells employ at least three DSB-repair mechanisms, with a preference for non-homologous end joining (NHEJ) over homologous recombination (HR) and microhomology-mediated end joining (MMEJ). While most eukaryotic DNA is transcribed into RNA, providing complementary genetic information, much remains unknown about the direct impact of RNA on DSB-repair outcomes and its role in DSB-repair via end joining. Here, we show that both sense and antisense-transcript RNAs impact DSB repair in a sequence-specific manner in wild-type human and yeast cells. Depending on its sequence complementarity with the broken DNA ends, a transcript RNA can promote repair of a DSB or a double-strand gap in its DNA gene via NHEJ or MMEJ, independently from DNA synthesis. The results demonstrate a role of transcript RNA in directing the way DSBs are repaired in DNA, suggesting that RNA may directly modulate genome stability and evolution.

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Fibrosis is an abnormal tissue healing process characterized by the excessive accumulation of ECM components, such as COL I and COL III, in response to tissue injury or chronic inflammation. Recent advances in epitranscriptomics have underscored the importance of m6A modification in fibrosis. m6A, the most prevalent modification in eukaryotic RNA, is catalyzed by methyltransferases (e.g., METTL3), removed by demethylases (e.g., FTO), and recognized by reader proteins (e.g., YTHDF1/2). These modifications are crucial in regulating collagen metabolism and associated diseases. Understanding the role of m6A modification in fibrosis and other collagen-related conditions holds promise for developing targeted therapies. This review highlights the latest progress in this area.

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BACKGROUND: SmithRNAs (Small MITochondrial Highly-transcribed RNAs) are a novel class of small RNA molecules that are encoded in the mitochondrial genome and regulate the expression of nuclear transcripts. Initial evidence for their existence came from the Manila clam Ruditapes philippinarum, where they have been described and whose activity has been biologically validated through RNA injection experiments. Current evidence on the existence of these RNAs in other species is based only on small RNA sequencing. As a preliminary step to characterize smithRNAs across different metazoan lineages, a dedicated, unified, analytical workflow is needed. RESULTS: We propose a novel workflow specifically designed for smithRNAs. Sequence data (from small RNA sequencing) uniquely mapping to the mitochondrial genome are clustered into putative smithRNAs and prefiltered based on their abundance, presence in replicate libraries and 5' and 3' transcription boundary conservation. The surviving sequences are subsequently compared to the untranslated regions of nuclear transcripts based on seed pairing, overall match and thermodynamic stability to identify possible targets. Ample collateral information and graphics are produced to help characterize these molecules in the species of choice and guide the operator through the analysis. The workflow was tested on the original Manila clam data. Under basic settings, the results of the original study are largely replicated. The effect of additional parameter customization (clustering threshold, stringency, minimum number of replicates, seed matching) was further evaluated. CONCLUSIONS: The study of smithRNAs is still in its infancy and no dedicated analytical workflow is currently available. At its core, the SmithHunter workflow builds over the bioinformatic procedure originally applied to identify candidate smithRNAs in the Manila clam. In fact, this is currently the only evidence for smithRNAs that has been biologically validated and, therefore, the elective starting point for characterizing smithRNAs in other species. The original analysis was readapted using current software implementations and some minor issues were solved. Moreover, the workflow was improved by allowing the customization of different analytical parameters, mostly focusing on stringency and the possibility of accounting for a minimal level of genetic differentiation among samples.

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N6-methyladenosine (m6A) modification stands out among various RNA modifications as the predominant form within eukaryotic cells, influencing numerous cellular processes implicated in disease development. m6A modification has gained increasing attention in the development of atherosclerosis and has become a research hotspot in recent years. Programmed cell death (PCD), encompassing apoptosis, autophagy, pyroptosis, ferroptosis, and necroptosis, plays a pivotal role in atherosclerosis pathogenesis. In this review, we delve into the intricate interplay between m6A modification and diverse PCD pathways, shedding light on their complex association during the onset and progression of atherosclerosis. Clarifying the relationship between m6A and PCD in atherosclerosis is of great significance to provide novel strategies for cardiovascular disease treatment.

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Hepatocellular carcinoma (HCC) is a highly aggressive cancer with a poor prognosis. The molecular mechanisms underlying its development remain unclear. Recent studies have highlighted the crucial role of RNA modifications in HCC progression, which indicates their potential as therapeutic targets and biomarkers for managing HCC. In this review, we discuss the functional role and molecular mechanisms of RNA modifications in HCC through a review and summary of relevant literature, to explore the potential therapeutic agents and biomarkers for diagnostic and prognostic of HCC. This review indicates that specific RNA modification pathways, such as N6-methyladenosine, 5-methylcytosine, N7-methylguanosine, and N1-methyladenosine, are erroneously regulated and are involved in the proliferation, autophagy, innate immunity, invasion, metastasis, immune cell infiltration, and drug resistance of HCC. These findings provide a new perspective for understanding the molecular mechanisms of HCC, as well as potential targets for the diagnosis and treatment of HCC by targeting specific RNA-modifying enzymes or recognition proteins. More than ten RNA-modifying regulators showed the potential for use for the diagnosis, prognosis and treatment decision utility biomarkers of HCC. Their application value for HCC biomarkers necessitates extensive multi-center sample validation in the future. A growing number of RNA modifier inhibitors are being developed, but the lack of preclinical experiments and clinical studies targeting RNA modification in HCC poses a significant obstacle, and further research is needed to evaluate their application value in HCC treatment. In conclusion, this review provides an in-depth understanding of the complex interplay between RNA modifications and HCC while emphasizing the promising potential of RNA modifications as therapeutic targets and biomarkers for managing HCC.

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The coordinated action of transcriptional and post-transcriptional machineries shapes gene expression programs at steady state and determines their concerted response to perturbations. We have developed Nanodynamo, an experimental and computational workflow for quantifying the kinetic rates of nuclear and cytoplasmic steps of the RNA life cycle. Nanodynamo is based on mathematical modelling following sequencing of native RNA from cellular fractions and polysomes. We have applied this workflow to triple-negative breast cancer cells, revealing widespread post-transcriptional RNA processing that is mutually exclusive with its co-transcriptional counterpart. We used Nanodynamo to unravel the coupling between transcription, processing, export, decay and translation machineries. We have identified a number of coupling interactions within and between the nucleus and cytoplasm that largely contribute to coordinating how cells respond to perturbations that affect gene expression programs. Nanodynamo will be instrumental in unravelling the determinants and regulatory processes involved in the coordination of gene expression responses.

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Single-cell multi-omics sequencing is a powerful approach to analyze complex mechanisms underlying neuronal development and regeneration. However, current methods lack the ability to simultaneously profile RNA alternative splicing and chromatin accessibility at the single-cell level. We develop a technique, single-cell RNA isoform and chromatin accessibility sequencing (scRICA-seq), which demonstrates higher sensitivity and cost-effectiveness compared to existing methods. scRICA-seq can profile both isoforms and chromatin accessibility for up to 10,000 single cells in a single run. Applying this method to human retinal organoids, we construct a multi-omic cell atlas and reveal associations between chromatin accessibility, isoform expression of fate-determining factors, and alternative splicing events in their binding sites. This study provides insights into integrating epigenetics, transcription, and RNA splicing to elucidate the mechanisms underlying retinal neuronal development and fate determination.

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In vitro circular RNA (circRNA) preparation methods have been gaining a lot of attention recently as several reports suggest that circRNAs are more stable, with better performances in cells and in vivo, than linear RNAs in various biomedical applications. Self-splicing ribozymes are considered a major in vitro circRNA generation method for biomedical applications due to their simplicity and efficiency in the circularization of the gene of interest. This review summarizes, updates, and discusses the recently developed self-circularization methods based on the self-splicing ribozyme, such as group I and II intron ribozymes, and the pros and cons of each method in preparing circRNA in vitro.

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In samples of harmful algal blooms (HABs), seawater can contain a high abundance of microorganisms and elemental ions. Along with the hardness of the walls of key HAB dinoflagellates such as Prorocentrum triestinum, this makes RNA extraction very difficult. These components interfere with RNA isolation, causing its degradation, in addition to the complex seawater properties of HABs that could hinder RNA isolation for effective RNA sequencing and transcriptome profiling. In this study, an RNA isolation technique was established through the modification of the Trizol method by applying the Micropestle System on cell pellets of P. triestinum frozen at -20 °C, obtained from 400 mL of culture with a total of 107 cells/mL. The results of the modified Trizol protocol generated quality RNA samples for transcriptomics sequencing, as determined by their measurement in Analyzer Agilent 4150.

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Modern life is essentially homochiral, containing D-sugars in nucleic acid backbones and L-amino acids in proteins. Since coded proteins are theorized to have developed from a prebiotic RNA World, the homochirality of L-amino acids observed in all known life presumably resulted from chiral transfer from a homochiral D-RNA World. This transfer would have been mediated by aminoacyl-RNAs defining the genetic code. Previous work on aminoacyl transfer using tRNA mimics has suggested that aminoacylation using D-RNA may be inherently biased toward reactivity with L-amino acids, implying a deterministic path from a D-RNA World to L-proteins. Using a model system of self-aminoacylating D-ribozymes and epimerizable activated amino acid analogs, we test the chiral selectivity of 15 ribozymes derived from an exhaustive search of sequence space. All of the ribozymes exhibit detectable selectivity, and a substantial fraction react preferentially to produce the D-enantiomer of the product. Furthermore, chiral preference is conserved within sequence families. These results are consistent with the transfer of chiral information from RNA to proteins but do not support an intrinsic bias of D-RNA for L-amino acids. Different aminoacylation structures result in different directions of chiral selectivity, such that L-proteins need not emerge from a D-RNA World.

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Exploring the intricate interplay within and between nucleic acids, as well as their interactions with proteins, holds pivotal significance in unraveling the molecular complexities steering cancer initiation and progression. To investigate these interactions, a diverse array of highly specific and sensitive molecular techniques has been developed. The selection of a particular technique depends on the specific nature of the interactions. Typically, researchers employ an amalgamation of these different techniques to obtain a comprehensive and holistic understanding of inter- and intramolecular interactions involving DNA-DNA, RNA-RNA, DNA-RNA, or protein-DNA/RNA. Examining nucleic acid conformation reveals alternative secondary structures beyond conventional ones that have implications for cancer pathways. Mutational hotspots in cancer often lie within sequences prone to adopting these alternative structures, highlighting the importance of investigating intra-genomic and intra-transcriptomic interactions, especially in the context of mutations, to deepen our understanding of oncology. Beyond these intramolecular interactions, the interplay between DNA and RNA leads to formations like DNA:RNA hybrids (known as R-loops) or even DNA:DNA:RNA triplex structures, both influencing biological processes that ultimately impact cancer. Protein-nucleic acid interactions are intrinsic cellular phenomena crucial in both normal and pathological conditions. In particular, genetic mutations or single amino acid variations can alter a protein's structure, function, and binding affinity, thus influencing cancer progression. It is thus, imperative to understand the differences between wild-type (WT) and mutated (MT) genes, transcripts, and proteins. The review aims to summarize the frequently employed methods and techniques for investigating interactions involving nucleic acids and proteins, highlighting recent advancements and diverse adaptations of each technique.

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Thus far, multiple techniques for single cell analysis have been developed, yet we lack a relatively simple tool to assess DNA and RNA from the same cell at whole-transcriptome and whole-genome depths. Here we present an updated method for physical separation of cytoplasmic RNA from the nuclei, which allows for simultaneous studies of DNA and RNA from the same single cell. The method consists of three steps-(1) immobilization of a single cell on solid substrate, (2) hypotonic lysis of immobilized single cell, and (3) separation of cytosol containing aqueous phase and immobilized nucleus. We found that DNA and RNA extracted from single cell using our approach is suitable for downstream sequencing-based applications. We demonstrated that the coverage of transcriptome and genome sequencing data obtained after DNA/RNA separation is similar to that observed without separation. We also showed that the separation procedure does not create any noticeable bias in observed mutational load or mutation spectra. Thus, our method can serve as a tool for simultaneous complex analysis of the genome and transcriptome, providing necessary information on the relationship between somatic mutations and the regulation of gene expression.

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RNA modifications play a crucial role in cancer development, profoundly influencing various stages of the RNA lifecycle. These stages encompass nuclear processing, nuclear export, splicing, and translation in the cytoplasm. Among RNA modifications, RNA ac4C modification, also known as N4-acetylcytidine, stands out for its unique role in acetylation processes. Specific proteins regulate RNA ac4C modification, maintaining the dynamic and reversible nature of these changes. This review explores the molecular mechanisms and biological functions of RNA ac4C modification. It examines the intricate ways in which RNA ac4C modification influences the pathogenesis and progression of cancer. Additionally, the review provides an integrated overview of the current methodologies for detecting RNA ac4C modification. Exploring the potential applications of manipulating this modification suggests avenues for novel therapeutic strategies, potentially leading to more effective cancer treatments in the future.

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As advances in RNA modification research progress, the significance of 5-methylcytosine (m5C) modification is being increasingly acknowledged. m5C undergoes modification by the methyltransferase NOP2/Sun domain (NSUN) family/DNA methyltransferase (DNMT) family (writer) and is removed by demethylases (eraser), including the ten-eleven translocation (TET) family and Alkb homolog 1 (ALKBH1). Moreover, m5C interacts with RNA-binding proteins (reader), such as Y-box-binding protein 1 (YBX1) and Aly/REF export factor (ALYREF). Expanding on this structural framework, m5C modification possesses the capacity to regulate various physiological and pathological processes. Recent studies indicate that m5C plays a pivotal regulatory role in the central nervous system, and its dysregulation may correlate with the onset and progression of various central nervous system diseases. In this review, we summarize recent research on m5C components and delve into the potential mechanisms of m5C involvement in central nervous system disorders, such as Alzheimer's disease, brain tumors, epilepsy, and stroke.

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RNA interference (RNAi) is a powerful tool for sequence-specific gene knockdown in therapeutic and research applications. However, spatiotemporal control of RNAi is required to decrease nonspecific targeting, potential toxicity, and allow targeting of essential genes. Herein we describe a class of de-novo-designed RNA switches that enable sequence-specific regulation of RNAi in mammalian cells. Using cis-repressing RNA elements, we engineer RNA devices that only initiate microRNA biogenesis when binding with cognate trigger RNAs. We demonstrate that this conditional RNAi system, termed Orthogonal RNA Interference induced by Trigger RNA (ORIENTR), provides up to 14-fold increases in artificial miRNA biogenesis upon activation in orthogonal libraries. We show that integration of ORIENTR triggers with dCas13d enhances dynamic range to up to 31-fold. We further demonstrate that ORIENTR can be applied to detect endogenous RNA signals and to conditionally knockdown endogenous genes, thus enabling regulatory possibilities including cell-type-specific RNAi and rewiring of transcriptional networks via RNA profile.

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