An expanding universe of noncoding RNAs

Relaxation Optimized Heteronuclear Experiments for Extending the Size Limit of RNA Nuclear Magnetic Resonance

The application of NMR to large RNAs has been limited by the inability to perform heteronuclear correlation experiments essential for resolving overlapping 1H NMR signals, determining interproton distance restraints and interhelical orientations for structure calculations, and evaluating conformational dynamics. Approaches exploiting 1H-13C correlations that are routinely applied to proteins and small RNAs of ∼60 nucleotides or fewer are impractical for larger RNAs due to rapid dipolar relaxation of protons by their attached carbons. Here we report a 2H-enhanced, 1H-15N correlation approach that enables atom-specific NMR characterization of much larger RNAs. Purine H8 transverse relaxation rates are reduced ∼20-fold with ribose perdeuteration, enabling efficient magnetization transfer via two-bond 1H-15N couplings. We focus on H8-N9 correlation spectra which benefit from favorable N9 chemical shift anisotropy. Chemical shift assignment is enabled by retention of protons at the C1' position, which allow measurement of two-bond H1'-N9 and through-space H1'-H8 correlations with only a minor effect on H8 relaxation. The approach is demonstrated for the 232 nucleotide HIV-1 Rev response element, where chemical shift assignments, 15N-edited nuclear Overhauser effects, and 1H-15N residual dipolar couplings are readily obtained from sensitive, high-resolution spectra. Heteronuclear correlated NMR methods that have been essential for the study of proteins can now be extended to RNAs of at least 78 kDa.

Decoding resilience: ecology, regulation, and evolution of biosynthetic gene clusters

Secondary metabolism is crucial for plant survival and can generate chemistry with nutritional, therapeutic, and industrial value. Biosynthetic genes of selected secondary metabolites cluster within localised chromosomal regions. The arrangement of these biosynthetic gene clusters (BGCs) challenges the long-held model of random gene order in eukaryotes, raising questions about their regulation, ecological significance, and evolution. In this review, we address these questions by exploring the contribution of BGCs to ecologically relevant plant-biotic interactions, while also evaluating the molecular-(epi)genetic mechanisms controlling their coordinated stress- and tissue-specific expression. Based on evidence that BGCs have distinct chromatin signatures and are enriched with transposable elements (TEs), we integrate emerging hypotheses into an updated evolutionary model emphasising how stress-induced epigenetic processes have shaped BGC formation.

ZUGC-RNA degradation generates immunosuppressor to evade immune responses in eukaryotes

Among the hundreds of modified nucleosides identified in terrestrial life, 2-amino-6-aminopurine (Z) is widely recognized as a prominent modified purine. Recently, RNA written with the ZUGC alphabet shows significant potential in RNA therapeutics as a synthetic biosystem. Here, we demonstrate that ZUGC-RNA can evade immune recognition in eukaryotes, independent of factors such as RNA length, sequence, 5'-triphosphate, modified uridine, and secondary structure. Notably, we discovered that both the degradation of ZUGC-RNA and metabolites of Z-nucleotides can function as immunosuppressors, silencing TLR7 sensing to block immune responses. This mechanism differs from that of pseudo-uridine (Ψ) modified RNA currently in use. ZUGC-RNAs also demonstrate broad applicability across multiple neural cell types. Our findings provide valuable insights for developing more tolerable RNA-based drugs and designing immunomodulators targeting TLR7. In addition to the potential prebiotic relevance of Z, our finding not only contributes to understanding the RNA world hypothesis but also provides new insights into the exploration of the origin of life.

A Glimpse of Noncoding RNAs: Secondary Structure, Emerging Trends, and Potential Applications in Human Diseases

An appealing strategy for the treatment of several diseases is the therapeutic targeting of noncoding RNAs (ncRNAs), such as microRNAs (miRNAs) and long noncoding RNAs (lncRNAs). Many antisense oligonucleotides and small interfering RNAs have been tested in clinical studies over the past 10 years, and several of these have received FDA approval. However, trial results have thus far been mixed, with some studies reporting strong effects and others showing low effectiveness or side effects, including toxicity. Clinical trials for alternative entities like antimiRNAs are underway, and interest in lncRNA-based therapies is constantly growing. From this perspective, we discuss the basic overview of ncRNAs, their significant role as therapeutic biomarkers against different diseases, and the role of secondary structure in noncoding RNAs.

HOTAIR in cancer: diagnostic, prognostic, and therapeutic perspectives

The long non-coding RNA HOTAIR is overexpressed in many cancers and is associated with several cancer-promoting effects, including increased cell proliferation, migration and treatment resistance. HOTAIR levels correlate with tumor stage, lymph node metastasis and overall survival in patients with various types of cancer. This highlights the potential uses of HOTAIR, including early cancer detection, predicting patient outcome, identifying high-risk individuals and assisting in therapy selection and monitoring. The aim of this review is to provide a comprehensive summary of the research progress, molecular mechanisms and clinical significance of HOTAIR in various human cancers. In addition, the clinical applications of HOTAIR, such as targeted therapy, radiotherapy, chemotherapy and immunotherapy, are discussed, and relevant information on the potential future advances of HOTAIR in cancer research is provided.

The interregulatory circuit between non-coding RNA and apoptotic signaling in diabetic cardiomyopathy

Diabetes mellitus has surged in prevalence, emerging as a prominent epidemic and assuming a foremost position among prevalent medical disorders. Diabetes constitutes a pivotal risk element for cardiovascular maladies, with diabetic cardiomyopathy (DCM) standing out as a substantial complication encountered by individuals with diabetes. Apoptosis represents a physiological phenomenon observed throughout the aging and developmental stages, giving rise to the programmed cell death, which is implicated in DCM. Non-coding RNAs assume significant functions in modulation of gene expression. Their deviant expression of ncRNAs is implicated in overseeing diverse cellular attributes such as proliferation, apoptosis, and has been postulated to play a role in the progression of DCM. Notably, ncRNAs and the process of apoptosis can mutually influence and cooperate in shaping the destiny of human cardiac tissues. Therefore, the exploration of the interplay between apoptosis and non-coding RNAs holds paramount importance in the formulation of efficacious therapeutic and preventive approaches for managing DCM. In this review, we provide a comprehensive overview of the apoptotic signaling pathways relevant to DCM and subsequently delve into the reciprocal regulation between apoptosis and ncRNAs in DCM. These insights contribute to an enhanced comprehension of DCM and the development of therapeutic strategies.

Roles of noncoding RNAs in diabetic retinopathy: Mechanisms and therapeutic implications

Diabetic retinopathy (DR) is a microvascular complication of diabetes that leads to vision loss. The striking features of DR are hard exudate, cotton-wool spots, hemorrhage, and neovascularization. The dysregulated retinal cells, encompassing microvascular endothelial cells, pericytes, Müller cells, and adjacent retinal pigment epithelial cells, are involved in the pathological processes of DR. According to recent research, oxidative stress, inflammation, ferroptosis, pyroptosis, apoptosis, and angiogenesis contribute to DR. Recent advancements have highlighted that noncoding RNAs could regulate diverse targets in pathological processes that contribute to DR. Noncoding RNAs, including long noncoding RNAs, microRNAs (miRNA), and circular RNAs, are dysregulated in DR, and interact with miRNA, mRNA, or proteins to control the pathological processes of DR. Hence, modulation of noncoding RNAs may have therapeutic effects on DR. Small extracellular vesicles may be valuable tools for transferring noncoding RNAs and regulating the genes involved in progression of DR. However, the roles of noncoding RNA in developing DR are not fully understood; it is critical to summarize the mechanisms for noncoding RNA regulation of pathological processes and pathways related to DR. This review provides a fundamental understanding of the relationship between noncoding RNAs and DR, exploring the mechanism of how noncoding RNA modulates different signaling pathways, and pave the way for finding potential therapeutic strategies for DR.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini

Despite the numerous sequencing methods available, the diversity in RNA size and chemical modification makes it difficult to capture all RNAs in a cell. We developed a method that combines quasi-random priming with template switching to construct sequencing libraries from RNA molecules of any length and with any type of 3' modifications, allowing for the sequencing of virtually all RNA species. Our ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to identify and quantify all classes of coding and non-coding RNAs. With LIDAR, we comprehensively characterized the transcriptomes of mouse embryonic stem cells, neural progenitor cells, mouse tissues, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared with traditional ligation-dependent sequencing methods and uncovered tDRs with blocked 3' ends that had previously escaped detection. Therefore, LIDAR can capture all RNAs in a sample and uncover RNA species with potential regulatory functions.

RNAMotifProfile: a graph-based approach to build RNA structural motif profiles

RNA structural motifs are the recurrent segments in RNA three-dimensional structures that play a crucial role in the functional diversity of RNAs. Understanding the similarities and variations within these recurrent motif groups is essential for gaining insights into RNA structure and function. While recurrent structural motifs are generally assumed to be composed of the same isosteric base interactions, this consistent pattern is not observed across all examples of these motifs. Existing methods for analyzing and comparing RNA structural motifs may overlook variations in base interactions and associated nucleotides. RNAMotifProfile is a novel profile-to-profile alignment algorithm that generates a comprehensive profile from a group of structural motifs, incorporating all base interactions and associated nucleotides at each position. By structurally aligning input motif instances using a guide-tree-based approach, RNAMotifProfile captures the similarities and variations within recurrent motif groups. Additionally, RNAMotifProfile can function as a motif search tool, enabling the identification of instances of a specific motif family by searching with the corresponding profile. The ability to generate accurate and comprehensive profiles for RNA structural motif families, and to search for these motifs, facilitates a deeper understanding of RNA structure-function relationships and potential applications in RNA engineering and therapeutic design.

Nucleic acid-responsive smart systems for controlled cargo delivery

Stimulus-responsive delivery systems allow controlled, highly regulated, and efficient delivery of various cargos while minimizing side effects. Owing to the unique properties of nucleic acids, including the ability to adopt complex structures by base pairing, their easy synthesis, high specificity, shape memory, and configurability, they have been employed in autonomous molecular motors, logic circuits, reconfigurable nanoplatforms, and catalytic amplifiers. Moreover, the development of nucleic acid (NA)-responsive intelligent delivery vehicles is a rapidly growing field. These vehicles have attracted much attention in recent years due to their programmable, controllable, and reversible properties. In this work, we review several types of NA-responsive controlled delivery vehicles based on locks and keys, including DNA/RNA-responsive, aptamer-responsive, and CRISPR-responsive, and summarize their advantages and limitations.

A comprehensive survey on deep learning-based identification and predicting the interaction mechanism of long non-coding RNAs

Long noncoding RNAs (lncRNAs) have been discovered to be extensively involved in eukaryotic epigenetic, transcriptional, and post-transcriptional regulatory processes with the advancements in sequencing technology and genomics research. Therefore, they play crucial roles in the body's normal physiology and various disease outcomes. Presently, numerous unknown lncRNA sequencing data require exploration. Establishing deep learning-based prediction models for lncRNAs provides valuable insights for researchers, substantially reducing time and costs associated with trial and error and facilitating the disease-relevant lncRNA identification for prognosis analysis and targeted drug development as the era of artificial intelligence progresses. However, most lncRNA-related researchers lack awareness of the latest advancements in deep learning models and model selection and application in functional research on lncRNAs. Thus, we elucidate the concept of deep learning models, explore several prevalent deep learning algorithms and their data preferences, conduct a comprehensive review of recent literature studies with exemplary predictive performance over the past 5 years in conjunction with diverse prediction functions, critically analyze and discuss the merits and limitations of current deep learning models and solutions, while also proposing prospects based on cutting-edge advancements in lncRNA research.

miR-193b-3p and miR-346 Exert Antihypertensive Effects in the Rostral Ventrolateral Medulla

BACKGROUND

Rostral ventrolateral medulla (RVLM) neuron hyperactivity raises sympathetic outflow, causing hypertension. MicroRNAs (miRNAs) contribute to diverse biological processes, but their influence on RVLM neuronal excitability and blood pressure (BP) remains widely unexplored.

METHODS AND RESULTS

The RVLM miRNA profiles in spontaneously hypertensive rats were unveiled using RNA sequencing. Potential effects of these miRNAs in reducing neuronal excitability and BP and underlying mechanisms were investigated through various experiments. Six hundred thirty-seven miRNAs were identified, and reduced levels of miR-193b-3p and miR-346 were observed in the RVLM of spontaneously hypertensive rats. Increased miR-193b-3p and miR-346 expression in RVLM lowered neuronal excitability, sympathetic outflow, and BP in spontaneously hypertensive rats. In contrast, suppressing miR-193b-3p and miR-346 expression in RVLM increased neuronal excitability, sympathetic outflow, and BP in Wistar Kyoto and Sprague-Dawley rats. Cdc42 guanine nucleotide exchange factor (Arhgef9) was recognized as a target of miR-193b-3p. Overexpressing miR-193b-3p caused an evident decrease in Arhgef9 expression, resulting in the inhibition of neuronal apoptosis. By contrast, its downregulation produced the opposite effects. Importantly, the decrease in neuronal excitability, sympathetic outflow, and BP observed in spontaneously hypertensive rats due to miR-193b-3p overexpression was greatly counteracted by Arhgef9 upregulation.

CONCLUSIONS

miR-193b-3p and miR-346 are newly identified factors in RVLM that hinder hypertension progression, and the miR-193b-3p/Arhgef9/apoptosis pathway presents a potential mechanism, highlighting the potential of targeting miRNAs for hypertension prevention.

Genome assembly of Melilotus officinalis provides a new reference genome for functional genomics

BACKGROUND

Sweet yellow clover (Melilotus officinalis) is a diploid plant (2n = 16) that is native to Europe. It is an excellent legume forage. It can both fix nitrogen and serve as a medicine. A genome assembly of Melilotus officinalis that was collected from Best corporation in Beijing is available based on Nanopore sequencing. The genome of Melilotus officinalis was sequenced, assembled, and annotated.

RESULTS

The latest PacBio third generation HiFi assembly and sequencing strategies were used to produce a Melilotus officinalis genome assembly size of 1,066 Mbp, contig N50 = 5 Mbp, scaffold N50 = 130 Mbp, and complete benchmarking universal single-copy orthologs (BUSCOs) = 96.4%. This annotation produced 47,873 high-confidence gene models, which will substantially aid in our research on molecular breeding. A collinear analysis showed that Melilotus officinalis and Medicago truncatula shared conserved synteny. The expansion and contraction of gene families showed that Melilotus officinalis expanded by 565 gene families and shrank by 56 gene families. The contacted gene families were associated with response to stimulus, nucleotide binding, and small molecule binding. Thus, it is related to a family of genes associated with peptidase activity, which could lead to better stress tolerance in plants.

CONCLUSIONS

In this study, the latest PacBio technology was used to assemble and sequence the genome of the Melilotus officinalis and annotate its protein-coding genes. These results will expand the genomic resources available for Melilotus officinalis and should assist in subsequent research on sweet yellow clover plants.

Non-coding RNAs and neuroinflammation: implications for neurological disorders

Neuroinflammation is considered a balanced inflammatory response important in the intrinsic repair process after injury or infection. Under chronic states of disease, injury, or infection, persistent neuroinflammation results in a heightened presence of cytokines, chemokines, and reactive oxygen species that result in tissue damage. In the CNS, the surrounding microglia normally contain macrophages and other innate immune cells that perform active immune surveillance. The resulting cytokines produced by these macrophages affect the growth, development, and responsiveness of the microglia present in both white and gray matter regions of the CNS. Controlling the levels of these cytokines ultimately improves neurocognitive function and results in the repair of lesions associated with neurologic disease. MicroRNAs (miRNAs) are master regulators of the genome and subsequently control the activity of inflammatory responses crucial in sustaining a robust and acute immunological response towards an acute infection while dampening pathways that result in heightened levels of cytokines and chemokines associated with chronic neuroinflammation. Numerous reports have directly implicated miRNAs in controlling the abundance and activity of interleukins, TGF-B, NF-kB, and toll-like receptor-signaling intrinsically linked with the development of neurological disorders such as Parkinson's, ALS, epilepsy, Alzheimer's, and neuromuscular degeneration. This review is focused on discussing the role miRNAs play in regulating or initiating these chronic neurological states, many of which maintain the level and/or activity of neuron-specific secondary messengers. Dysregulated miRNAs present in the microglia, astrocytes, oligodendrocytes, and epididymal cells, contribute to an overall glial-specific inflammatory niche that impacts the activity of neuronal conductivity, signaling action potentials, neurotransmitter robustness, neuron-neuron specific communication, and neuron-muscular connections. Understanding which miRNAs regulate microglial activation is a crucial step forward in developing non-coding RNA-based therapeutics to treat and potentially correct the behavioral and cognitive deficits typically found in patients suffering from chronic neuroinflammation.

Genome assembly provides insights into the genome evolution of Baccaurea ramiflora Lour

Baccaurea ramiflora Lour., an evergreen tree of the Baccaurea genus of the Phyllanthaceae family, is primarily distributed in South Asia, Southeast Asia, and southern China, including southern Yunnan Province. It is a wild or semi-cultivated tree species with ornamental, edible, and medicinal value, exhibiting significant development potential. In this study, we present the whole-genome sequencing of B. ramiflora, employing a combination of PacBio SMRT and Illumina HiSeq 2500 sequencing techniques. The assembled genome size was 975.8 Mb, with a contig N50 of 509.33 kb and the longest contig measuring 7.74 Mb. The genome comprises approximately 73.47% highly repetitive sequences, of which 52.1% are long terminal repeat-retrotransposon sequences. A total of 29,172 protein-coding genes were predicted, of which 25,980 (89.06%) have been annotated, Additionally, 3452 non-coding RNAs were identified. Comparative genomic analysis revealed a close relationship between B. ramiflora and the Euphorbiaceae family, with both being sister groups that diverged approximately 59.9 million years ago. During the evolutionary process, B. ramiflora exhibited positive selection in 278 candidate genes. Synonymous substitution rate and collinearity analysis demonstrated that B. ramiflora underwent a single ancient genome-wide triploidization event, without recent genome-wide duplication events. This high-quality B. ramiflora genome provides a valuable resource for basic research and tree improvement programs focusing on the Phyllanthaceae family.

An Integrated Affinity Chromatography-Based Approach to Unravel the sRNA Interactome in Nitrogen-Fixing Rhizobia

The activity mechanism and function of bacterial base-pairing small non-coding RNA regulators (sRNAs) are largely shaped by their main interacting cellular partners, i.e., proteins and mRNAs. We describe here an MS2 affinity chromatography-based procedure adapted to unravel the sRNA interactome in nitrogen-fixing legume endosymbiotic bacteria. The method consists of tagging of the bait sRNA at its 5'-end with the MS2 aptamer followed by pulse overexpression and immobilization of the chimeric transcript from cell lysates by an MS2-MBP fusion protein conjugated to an amylose resin. The sRNA-binding proteins and target mRNAs are further profiled by mass spectrometry and RNAseq, respectively.

Deciphering shared attributes of plant long non-coding RNAs through a comparative computational approach

Over the past decade, long non-coding RNA (lncRNA), which lacks protein-coding potential, has emerged as an essential regulator of the genome. The present study examined 13,599 lncRNAs in Arabidopsis thaliana, 11,565 in Oryza sativa, and 32,397 in Zea mays for their characteristic features and explored the associated genomic and epigenomic features. We found lncRNAs were distributed throughout the chromosomes and the Helitron family of transposable elements (TEs) enriched, while the terminal inverted repeat depleted in lncRNA transcribing regions. Our analyses determined that lncRNA transcribing regions show rare or weak signals for most epigenetic marks except for H3K9me2 and cytosine methylation in all three plant species. LncRNAs showed preferential localization in the nucleus and cytoplasm; however, the distribution ratio in the cytoplasm and nucleus varies among the studied plant species. We identified several conserved endogenous target mimic sites in the lncRNAs among the studied plants. We found 233, 301, and 273 unique miRNAs, potentially targeting the lncRNAs of A. thaliana, O. sativa, and Z. mays, respectively. Our study has revealed that miRNAs, which interact with lncRNAs, target genes that are involved in a diverse array of biological and molecular processes. The miRNA-targeted lncRNAs displayed a strong affinity for several transcription factors, including ERF and BBR-BPC, mutually present in all three plants, advocating their conserved functions. Overall, the present study showed that plant lncRNAs exhibit conserved genomic and epigenomic characteristics and potentially govern the growth and development of plants.

The mechanisms and factors that induce trained immunity in arthropods and mollusks

Besides dividing the organism's immune system into adaptive and innate immunity, it has long been thought that only adaptive immunity can establish immune memory. However, many studies have shown that innate immunity can also build immunological memory through epigenetic reprogramming and modifications to resist pathogens' reinfection, known as trained immunity. This paper reviews the role of mitochondrial metabolism and epigenetic modifications and describes the molecular foundation in the trained immunity of arthropods and mollusks. Mitochondrial metabolism and epigenetic modifications complement each other and play a key role in trained immunity.

Advances, Applications, and Perspectives in Small-Angle X-ray Scattering of RNA

RNAs exhibit a plethora of functions far beyond transmitting genetic information. Often, RNA functions are entailed in their structure, be it as a regulatory switch, protein binding site, or providing catalytic activity. Structural information is a prerequisite for a full understanding of RNA-regulatory mechanisms. Owing to the inherent dynamics, size, and instability of RNA, its structure determination remains challenging. Methods such as NMR spectroscopy, X-ray crystallography, and cryo-electron microscopy can provide high-resolution structures; however, their limitations make structure determination, even for small RNAs, cumbersome, if at all possible. Although at a low resolution, small-angle X-ray scattering (SAXS) has proven valuable in advancing structure determination of RNAs as a complementary method, which is also applicable to large-sized RNAs. Here, we review the technological and methodological advancements of RNA SAXS. We provide examples of the powerful inclusion of SAXS in structural biology and discuss possible future applications to large RNAs.

RNAMotifComp: a comprehensive method to analyze and identify structurally similar RNA motif families

MOTIVATION

The 3D structures of RNA play a critical role in understanding their functionalities. There exist several computational methods to study RNA 3D structures by identifying structural motifs and categorizing them into several motif families based on their structures. Although the number of such motif families is not limited, a few of them are well-studied. Out of these structural motif families, there exist several families that are visually similar or very close in structure, even with different base interactions. Alternatively, some motif families share a set of base interactions but maintain variation in their 3D formations. These similarities among different motif families, if known, can provide a better insight into the RNA 3D structural motifs as well as their characteristic functions in cell biology.

RESULTS

In this work, we proposed a method, RNAMotifComp, that analyzes the instances of well-known structural motif families and establishes a relational graph among them. We also have designed a method to visualize the relational graph where the families are shown as nodes and their similarity information is represented as edges. We validated our discovered correlations of the motif families using RNAMotifContrast. Additionally, we used a basic Naïve Bayes classifier to show the importance of RNAMotifComp. The relational analysis explains the functional analogies of divergent motif families and illustrates the situations where the motifs of disparate families are predicted to be of the same family.

AVAILABILITY AND IMPLEMENTATION

Source code publicly available at https://github.com/ucfcbb/RNAMotifFamilySimilarity.

A ligation-independent sequencing method reveals tRNA-derived RNAs with blocked 3' termini

Despite the numerous sequencing methods available, the vast diversity in size and chemical modifications of RNA molecules makes the capture of the full spectrum of cellular RNAs a difficult task. By combining quasi-random hexamer priming with a custom template switching strategy, we developed a method to construct sequencing libraries from RNA molecules of any length and with any type of 3' terminal modification, allowing the sequencing and analysis of virtually all RNA species. Ligation-independent detection of all types of RNA (LIDAR) is a simple, effective tool to comprehensively characterize changes in small non-coding RNAs and mRNAs simultaneously, with performance comparable to separate dedicated methods. With LIDAR, we comprehensively characterized the coding and non-coding transcriptome of mouse embryonic stem cells, neural progenitor cells, and sperm. LIDAR detected a much larger variety of tRNA-derived RNAs (tDRs) compared to traditional ligation-dependent sequencing methods, and uncovered the presence of tDRs with blocked 3' ends that had previously escaped detection. Our findings highlight the potential of LIDAR to systematically detect all RNAs in a sample and uncover new RNA species with potential regulatory functions.

Spatiotemporal Monitoring of Subcellular mRNAs In Situ via Polyadenine-Mediated Dual-Color Sticky Flares

Spatiotemporal monitoring of multiple low-abundance messenger RNAs (mRNAs) is vitally important for the diagnosis and pathologic analysis of cancer. However, it remains a clinical challenge to monitor and track multiple mRNAs location simultaneously in situ at subcellular level with high efficiency. Herein, we proposed polyA-mediated dual-color sticky flares for simultaneous imaging of two kinds of intracellular mRNA biomarkers. Two kinds of fluorescent DNA specific for GalNac-T mRNA and c-Myc mRNA were functionalized onto gold nanoparticles (AuNPs) through efficient polyadenine (polyA) attachment. By tuning polyA length, the lateral spacing and densities of DNA on AuNPs could be precisely engineered. Compared to the traditional thio-DNA-modified nanoprobes, the uniformity, detection sensitivity, and response kinetics of sticky flares were greatly improved, which enables live-cell imaging of mRNAs with enhanced efficiency. With a sticky-end design, the fluorescent DNA could dynamically trace mRNAs after binding with target mRNAs, which realized spatiotemporal monitoring of subcellular mRNAs in situ. Compared to one target mRNA imaging mode, the multiple target imaging mode allows more accurate diagnosis of cancer. Furthermore, the proposed polyA-mediated dual-color sticky flares exhibit excellent cell entry efficiency and low cytotoxicity with a low-cost and simple assembling process, which provide a pivotal tool for multiple targets imaging in living cells.

REDfold: accurate RNA secondary structure prediction using residual encoder-decoder network

BACKGROUND

As the RNA secondary structure is highly related to its stability and functions, the structure prediction is of great value to biological research. The traditional computational prediction for RNA secondary prediction is mainly based on the thermodynamic model with dynamic programming to find the optimal structure. However, the prediction performance based on the traditional approach is unsatisfactory for further research. Besides, the computational complexity of the structure prediction using dynamic programming is [Formula: see text]; it becomes [Formula: see text] for RNA structure with pseudoknots, which is computationally impractical for large-scale analysis.

RESULTS

In this paper, we propose REDfold, a novel deep learning-based method for RNA secondary prediction. REDfold utilizes an encoder-decoder network based on CNN to learn the short and long range dependencies among the RNA sequence, and the network is further integrated with symmetric skip connections to efficiently propagate activation information across layers. Moreover, the network output is post-processed with constrained optimization to yield favorable predictions even for RNAs with pseudoknots. Experimental results based on the ncRNA database demonstrate that REDfold achieves better performance in terms of efficiency and accuracy, outperforming the contemporary state-of-the-art methods.

Non-coding RNA alterations in extracellular vesicles from bronchoalveolar lavage fluid contribute to mechanical ventilation-induced pulmonary fibrosis

Objective

For respiratory failure patients, mechanical ventilation (MV) is a life-saving therapy to maintain respiratory function. However, MV could also cause damage to pulmonary structures, result in ventilator-induced lung injury (VILI) and eventually progress to mechanical ventilation-induced pulmonary fibrosis (MVPF). Mechanically ventilated patients with MVPF are closely related to increased mortality and poor quality of life in long-term survival. Thus, a thorough understanding of the involved mechanism is necessary.

Methods

We used next-generation sequencing to identify differentially expressed non-coding RNAs (ncRNAs) in BALF EVs which were isolated from Sham and MV mice. Bioinformatics analysis was conducted to identify the engaged ncRNAs and related signaling pathways in the process of MVPF.

Results

We found 1801 messenger RNAs (mRNA), 53 micro RNAs (miRNA), 273 circular RNAs (circRNA) and 552 long non-coding RNAs (lncRNA) in mice BALF EVs of two groups, which showed significant differential expression. TargetScan predicted that 53 differentially expressed miRNAs targeted 3105 mRNAs. MiRanda revealed that 273 differentially expressed circRNAs were associated with 241 mRNAs while 552 differentially expressed lncRNAs were predicated to target 20528 mRNAs. GO, KEGG pathway analysis and KOG classification showed that these differentially expressed ncRNA-targeted mRNAs were enriched in fibrosis related signaling pathways and biological processes. By taking the intersection of miRNAs target genes, circRNAs target genes and lncRNAs target genes, we found 24 common key genes and 6 downregulated genes were confirmed by qRT-PCR.

Conclusions

Changes in BALF-EV ncRNAs may contribute to MVPF. Identification of key target genes involved in the pathogenesis of MVPF could lead to interventions that slow or reverse fibrosis progression.

Methods and Applications in Proteins and RNAs

Proteins and RNAs are primary biomolecules that are involved in most biological processes [...]

RHAU Peptides Specific for Parallel G-Quadruplexes: Potential Applications in Chemical Biology

G-quadruplexes (G4s) are non-canonical nucleic acid structures formed by guanine (G)-rich sequences, which are ubiquitously found in the human genome and transcriptome. Targeting G4s by specific ligands provides a powerful tool to monitor and regulate G4s-associated biological processes. RHAU peptides, derived from the G4-binding motif of "RNA Helicase associated with AU-rich element" (RHAU), have emerged as extraordinary ligands for specific recognition of parallel G4s. This review highlights the significances of recent studies investigating potential applications of the engineered RHAU peptides incorporated to different functional moieties.

Identification and Characterization of Long Non-Coding RNAs: Implicating Insights into Their Regulatory Role in Kiwifruit Ripening and Softening during Low-Temperature Storage

Long non-coding RNAs (lncRNAs) are crucial players regulating many biological processes in plants. However, limited knowledge is available regarding their roles in kiwifruit ripening and softening. In this study, using lncRNA-seq technology, 591 differentially expressed (DE) lncRNAs (DELs) and 3107 DE genes (DEGs) were identified from kiwifruit stored at 4 °C for 1, 2, and 3 weeks in comparison with non-treated control fruits. Of note, 645 DEGs were predicted to be targets of DELs (DEGTLs), including some DE protein-coding genes (such as β-amylase and pectinesterase). DEGTL-based GO enrichment analysis revealed that these genes were significantly enriched in cell wall modification and pectinesterase activity in 1 W vs. CK and 3 W vs. CK, which might be closely related to the fruit softening during low-temperature storage. Moreover, KEGG enrichment analysis revealed that DEGTLs were significantly associated with starch and sucrose metabolism. Our study revealed that lncRNAs play critical regulatory roles in kiwifruit ripening and softening under low-temperature storage, mainly by mediating the expression of starch and sucrose metabolism and cell wall modification related genes.

Approaches for sRNA Analysis of Human RNA-Seq Data: Comparison, Benchmarking

Expression analysis of small noncoding RNA (sRNA), including microRNA, piwi-interacting RNA, small rRNA-derived RNA, and tRNA-derived small RNA, is a novel and quickly developing field. Despite a range of proposed approaches, selecting and adapting a particular pipeline for transcriptomic analysis of sRNA remains a challenge. This paper focuses on the identification of the optimal pipeline configurations for each step of human sRNA analysis, including reads trimming, filtering, mapping, transcript abundance quantification and differential expression analysis. Based on our study, we suggest the following parameters for the analysis of human sRNA in relation to categorical analyses with two groups of biosamples: (1) trimming with the lower length bound = 15 and the upper length bound = Read length - 40% Adapter length; (2) mapping on a reference genome with bowtie aligner with one mismatch allowed (-v 1 parameter); (3) filtering by mean threshold > 5; (4) analyzing differential expression with DESeq2 with adjusted p-value < 0.05 or limma with p-value < 0.05 if there is very little signal and few transcripts.

sORFPred: A Method Based on Comprehensive Features and Ensemble Learning to Predict the sORFs in Plant LncRNAs

Long non-coding RNAs (lncRNAs) are important regulators of biological processes. It has recently been shown that some lncRNAs include small open reading frames (sORFs) that can encode small peptides of no more than 100 amino acids. However, existing methods are commonly applied to human and animal datasets and still suffer from low feature representation capability. Thus, accurate and credible prediction of sORFs with coding ability in plant lncRNAs is imperative. This paper proposes a new method termed sORFPred, in which we design a model named MCSEN by combining multi-scale convolution and Squeeze-and-Excitation Networks to fully mine distinct information embedded in sORFs, integrate and optimize multiple sequence-based and physicochemical feature descriptors, and built a two-layer prediction classifier based on Bayesian optimization algorithm and Extra Trees. sORFPred has been evaluated on sORFs datasets of three species and experimentally validated sORFs dataset. Results indicate that sORFPred outperforms existing methods and achieves 97.28% accuracy, 97.06% precision, 97.52% recall, and 97.29% F1-score on Arabidopsis thaliana, which shows a significant improvement in prediction performance compared to various conventional shallow machine learning and deep learning models.

Non-complementary strand commutation as a fundamental alternative for information processing by DNA and gene regulation

The discovery of the DNA double helix has revolutionized our understanding of data processing in living systems, with the complementarity of the two DNA strands providing a reliable mechanism for the storage of hereditary information. Here I reveal the 'strand commutation' phenomenon-a fundamentally different mechanism of information storage and processing by DNA/RNA based on the reversible low-affinity interactions of essentially non-complementary nucleic acids. I demonstrate this mechanism by constructing a memory circuit, a 5-min square-root circuit for 4-bit inputs comprising only nine processing ssDNAs, simulating a 572-input AND gate (surpassing the bitness of current electronic computers), and elementary algebra systems with continuously changing variables. Most importantly, I show potential pathways of gene regulation with strands of maximum non-complementarity to the gene sequence that may be key to the reduction of off-target therapeutic effects. This Article uncovers the information-processing power of the low-affinity interactions that may underlie major processes in an organism-from short-term memory to cancer, ageing and evolution.

Biomarkers (mRNAs and non-coding RNAs) for the diagnosis and prognosis of rheumatoid arthritis

In recent years, diagnostic and therapeutic approaches for rheumatoid arthritis (RA) have continued to improve. However, in the advanced stages of the disease, patients are unable to achieve long-term clinical remission and often suffer from systemic multi-organ damage and severe complications. Patients with RA usually have no overt clinical manifestations in the early stages, and by the time a definitive diagnosis is made, the disease is already at an advanced stage. RA is diagnosed clinically and with laboratory tests, including the blood markers C-reactive protein (CRP) and erythrocyte sedimentation rate (ESR) and the autoantibodies rheumatoid factor (RF) and anticitrullinated protein antibodies (ACPA). However, the presence of RF and ACPA autoantibodies is associated with aggravated disease, joint damage, and increased mortality, and these autoantibodies have low specificity and sensitivity. The etiology of RA is unknown, with the pathogenesis involving multiple factors and clinical heterogeneity. The early diagnosis, subtype classification, and prognosis of RA remain challenging, and studies to develop minimally invasive or non-invasive biomarkers in the form of biofluid biopsies are becoming more common. Non-coding RNA (ncRNA) molecules are composed of long non-coding RNAs, small nucleolar RNAs, microRNAs, and circular RNAs, which play an essential role in disease onset and progression and can be used in the early diagnosis and prognosis of RA. In this review of the diagnostic and prognostic approaches to RA disease, we provide an overview of the current knowledge on the subject, focusing on recent advances in mRNA-ncRNA as diagnostic and prognostic biomarkers from the biofluid to the tissue level.

A de novo assembled high-quality chromosome-scale Trifolium pratense genome and fine-scale phylogenetic analysis

BACKGROUND

Red clover (Trifolium pratense L.) is a diploid perennial temperate legume with 14 chromosomes (2n = 14) native to Europe and West Asia, with high nutritional and economic value. It is a very important forage grass and is widely grown in marine climates, such as the United States and Sweden. Genetic research and molecular breeding are limited by the lack of high-quality reference genomes. In this study, we used Illumina, PacBio HiFi, and Hi-C to obtain a high-quality chromosome-scale red clover genome and used genome annotation results to analyze evolutionary relationships among related species.

RESULTS

The red clover genome obtained by PacBio HiFi assembly sequencing was 423 M. The assembly quality was the highest among legume genome assemblies published to date. The contig N50 was 13 Mb, scaffold N50 was 55 Mb, and BUSCO completeness was 97.9%, accounting for 92.8% of the predicted genome. Genome annotation revealed 44,588 gene models with high confidence and 52.81% repetitive elements in red clover genome. Based on a comparison of genome annotation results, red clover was closely related to Trifolium medium and distantly related to Glycine max, Vigna radiata, Medicago truncatula, and Cicer arietinum among legumes. Analyses of gene family expansions and contractions and forward gene selection revealed gene families and genes related to environmental stress resistance and energy metabolism.

CONCLUSIONS

We report a high-quality de novo genome assembly for the red clover at the chromosome level, with a substantial improvement in assembly quality over those of previously published red clover genomes. These annotated gene models can provide an important resource for molecular genetic breeding and legume evolution studies. Furthermore, we analyzed the evolutionary relationships among red clover and closely related species, providing a basis for evolutionary studies of clover leaf and legumes, genomics analyses of forage grass, the improvement of agronomic traits.

Comparative Profiling of Circulating Exosomal Small RNAs Derived From Peruvian Patients With Tuberculosis and Pulmonary Adenocarcinoma

Tuberculosis (TB) is one of the most fatal infectious diseases, caused by the aerobic bacteria Mycobacterium tuberculosis. It is estimated that one-third of the world’s population is infected with the latent (LTB) version of this disease, with only 5-10% of infected individuals developing its active (ATB) form. Pulmonary adenocarcinoma (PA) is the most common and diverse form of primary lung carcinoma. The simultaneous or sequential occurrence of TB and lung cancer in patients has been widely reported and is known to be an issue for diagnosis and surgical treatment. Raising evidence shows that patients cured of TB represent a group at risk for developing PA. In this work, using sRNA-sequencing, we evaluated the expression patterns of circulating small RNAs available in exosomes extracted from blood samples of Peruvian patients affected by latent tuberculosis, active tuberculosis, or pulmonary adenocarcinoma. Differential expression analysis revealed a set of 24 microRNAs perturbed in these diseases, revealing potential biomarker candidates for the Peruvian population. Most of these miRNAs are normally expressed in healthy lung tissue and are potential regulators of different shared and unique KEGG pathways related to cancers, infectious diseases, and immunology.

ITAS: Integrated Transcript Annotation for Small RNA

Transcriptomics analysis of various small RNA (sRNA) biotypes is a new and rapidly developing field. Annotations for microRNAs, tRNAs, piRNAs and rRNAs contain information on transcript sequences and loci that is vital for downstream analyses. Several databases have been established to provide this type of data for specific RNA biotypes. However, these sources often contain data in different formats, which makes the bulk analysis of several sRNA biotypes in a single pipeline challenging. Information on some transcripts may be incomplete or conflicting with other entries. To overcome these challenges, we introduce ITAS, or Integrated Transcript Annotation for Small RNA, a filtered, corrected and integrated transcript annotation containing information on several types of small RNAs, including tRNA-derived small RNA, for several species (Homo sapiens, Rattus norvegicus, Mus musculus, Drosophila melanogaster, Caenorhabditis elegans). ITAS is presented in a format applicable for the vast majority of bioinformatic transcriptomics analysis, and it was tested in several case studies for human-derived data against existing alternative databases.

Transcription of ncRNAs promotes repair of UV induced DNA lesions in Saccharomyces cerevisiae subtelomeres

Ultraviolet light causes DNA lesions that are removed by nucleotide excision repair (NER). The efficiency of NER is conditional to transcription and chromatin structure. UV induced photoproducts are repaired faster in the gene transcribed strands than in the non-transcribed strands or in transcriptionally inactive regions of the genome. This specificity of NER is known as transcription-coupled repair (TCR). The discovery of pervasive non-coding RNA transcription (ncRNA) advocates for ubiquitous contribution of TCR to the repair of UV photoproducts, beyond the repair of active gene-transcribed strands. Chromatin rules transcription, and telomeres form a complex structure of proteins that silences nearby engineered ectopic genes. The essential protective function of telomeres also includes preventing unwanted repair of double-strand breaks. Thus, telomeres were thought to be transcriptionally inert, but more recently, ncRNA transcription was found to initiate in subtelomeric regions. On the other hand, induced DNA lesions like the UV photoproducts must be recognized and repaired also at the ends of chromosomes. In this study, repair of UV induced DNA lesions was analyzed in the subtelomeric regions of budding yeast. The T4-endonuclease V nicking-activity at cyclobutene pyrimidine dimer (CPD) sites was exploited to monitor CPD formation and repair. The presence of two photoproducts, CPDs and pyrimidine (6,4)-pyrimidones (6-4PPs), was verified by the effective and precise blockage of Taq DNA polymerase at these sites. The results indicate that UV photoproducts in silenced heterochromatin are slowly repaired, but that ncRNA transcription enhances NER throughout one subtelomeric element, called Y’, and in distinct short segments of the second, more conserved element, called X. Therefore, ncRNA-transcription dependent TCR assists global genome repair to remove CPDs and 6-4PPs from subtelomeric DNA.

Our skin is constantly exposed to sunlight and the ultraviolet component of it can severely damage the DNA of our chromosomes. If that damage is not efficiently repaired, the cells’ physiology becomes deregulated and very often cancer ensues. The specific molecular mechanism that will remove this damage is called nucleotide excision repair or NER. NER is conserved from humans to yeast, and it is much more efficient on DNA that is transcribed into RNA. Here we report how NER acts at the very ends of the chromosomes, the telomeres. In particular, the results show that in this area of the chromosomes with very few genes and where transcription is kept very low, the remaining transcription of non-coding RNAs such as TERRAs still stimulates NER and therefore helps guarding the integrity of DNA. These findings therefore suggest that the spurious transcription of subtelomeric DNA has a very positive impact on DNA repair efficiency. Hence, in addition to the known functions of TERRA and other ncRNAs in telomere maintenance, their transcription per se can be viewed as a genome stabilizing function.

High-quality chromosome-scale de novo assembly of the Paspalum notatum 'Flugge' genome

BACKGROUND

Paspalum notatum 'Flugge' is a diploid with 20 chromosomes (2n = 20) multi-purpose subtropical herb native to South America and has a high ecological significance. It is currently widely planted in tropical and subtropical regions. Despite the gene pool of P. notatum 'Flugge' being unearthed to a large extent in the past decade, no details about the genomic information of relevant species in Paspalum have been reported. In this study, the complete genome information of P. notatum was established and annotated through sequencing and de novo assembly of its genome.

RESULTS

The latest PacBio third-generation HiFi assembly and sequencing revealed that the genome size of P. notatum 'Flugge' is 541 M. The assembly result is the higher index among the genomes of the gramineous family published so far, with a contig N50 = 52Mbp, scaffold N50 = 49Mbp, and BUSCOs = 98.1%, accounting for 98.5% of the estimated genome. Genome annotation revealed 36,511 high-confidence gene models, thus providing an important resource for future molecular breeding and evolutionary research. A comparison of the genome annotation results of P. notatum 'Flugge' with other closely related species revealed that it had a close relationship with Zea mays but not close compared to Brachypodium distachyon, Setaria viridis, Oryza sativa, Puccinellia tenuiflora, Echinochloa crusgalli. An analysis of the expansion and contraction of gene families suggested that P. notatum 'Flugge' contains gene families associated with environmental resistance, increased reproductive ability, and molecular evolution, which explained its excellent agronomic traits.

CONCLUSION

This study is the first to report the high-quality chromosome-scale-based genome of P. notatum 'Flugge' assembled using the latest PacBio third-generation HiFi sequencing reads. The study provides an excellent genetic resource bank for gramineous crops and invaluable perspectives regarding the evolution of gramineous plants.

Antitumor Activities of tRNA-Derived Fragments and tRNA Halves from Non-pathogenic Escherichia coli Strains on Colorectal Cancer and Their Structure-Activity Relationship

tRNAs purified from non-pathogenic Escherichia coli strains (NPECSs) possess cytotoxic properties on colorectal cancer cells. In the present study, the bioactivity of tRNA halves and tRNA fragments (tRFs) derived from NPECSs are investigated for their anticancer potential. Both the tRNA halves and tRF mimics studied exhibited significant cytotoxicity on colorectal cancer cells, with the latter being more effective, suggesting that tRFs may be important contributors to the bioactivities of tRNAs derived from the gut microbiota. Through high-throughput screening, the EC83 mimic, a double-strand RNA with a 22-nucleotide (nt) 5′-tRF derived from tRNA-Leu(CAA) as an antisense chain, was identified as the one with the highest potency (50% inhibitory concentration [IC₅₀] = 52 nM). Structure-activity investigations revealed that 2′-O-methylation of the ribose of guanosine (Gm) may enhance the cytotoxic effects of the EC83 mimic via increasing the stability of its tertiary structure, which is consistent with the results of in vivo investigations showing that the EC83-M2 mimic (Gm modified) exhibited stronger antitumor activity against both HCT-8 and LoVo xenografts. Consistently, 4-thiouridine modification does not. This provides the first evidence that the bioactivity of tRF mimics would be impacted by chemical modifications. Furthermore, the present study provides the first evidence to suggest that novel tRNA fragments derived from the gut microbiota may possess anticancer properties and have the potential to be potent and selective therapeutic molecules.

IMPORTANCE While the gut microbiota has been increasingly recognized to be of vital importance for human health and disease, the current literature shows that there is a lack of attention given to non-pathogenic Escherichia coli strains. Moreover, the biological activities of tRNA fragments (tRFs) derived from bacteria have rarely been investigated. The findings from this study revealed tRFs as a new class of bioactive constituents derived from gut microorganisms, suggesting that studies on biological functional molecules in the intestinal microbiota should not neglect tRFs. Research on tRFs would play an important role in the biological research of gut microorganisms, including bacterium-bacterium interactions, the gut-brain axis, and the gut-liver axis, etc. Furthermore, the guidance on the rational design of tRF therapeutics provided in this study indicates that further investigations should pay more attention to these therapeutics from probiotics. The innovative drug research of tRFs as potent druggable RNA molecules derived from intestinal microorganisms would open a new area in biomedical sciences.

Weight Change Alters the Small RNA Profile of Urinary Extracellular Vesicles in Obesity

INTRODUCTION

Various kidney diseases reportedly show different urinary extracellular vesicle (EV) RNA profiles. Although obesity is one of the main causes of chronic kidney disease, the expression pattern of urinary EV RNA in obesity is uncertain. Our aim was to sequence the small RNA profiles of urinary EVs in obese patients before and after weight reduction and compare them to those of healthy volunteers (HVs).

METHODS

We recruited age-sex-matched obese patients and HVs. The small RNA profiles of urinary EVs were analyzed using RNA sequencing. To evaluate the effect of weight reduction, small RNA profiles of urinary EVs 6 months after bariatric surgery were also analyzed.

RESULTS

The proportion of urinary EVs transfer RNA and microRNA of obese patients differed from that of HVs. Obese patients showed differential expression of 1,343 small RNAs in urinary EVs compared to HVs (fold change ≥2 and p value <0.05). Among those, 61 small RNAs were upregulated in obese patients and downregulated after weight reduction, whereas 167 small RNAs were downregulated in obese patients and upregulated after weight reduction. RNA sequencing revealed the correlation between the specific urinary EV small RNAs and clinical parameters including body weight, low-density lipoprotein cholesterol, triglyceride, high-density lipoprotein cholesterol, serum glucose, estimated glomerular filtration rate, and albuminuria.

CONCLUSION

Obese patients showed distinct urinary EV small RNA profiles compared to HVs. Weight reduction altered urinary EV small-RNA profiles in obese patients.

Sulfur atom modification on thymine improves the specificity and sensitivity of DNA polymerization and detection

The incorporation of STTP can significantly reduce the non-specific amplification products in DNA polymerase reaction.

Pancreatic stellate cells - rising stars in pancreatic pathologies

Pluripotent pancreatic stellate cells (PSCs) receive growing interest in past decades. Two types of PSCs are recognized –vitamin A accumulating quiescent PSCs and activated PSCs- the main producents of extracellular matrix in pancreatic tissue. PSCs plays important role in pathogenesis of pancreatic fibrosis in pancreatic cancer and chronic pancreatitis. PSCs are intensively studied as potential therapeutical target because of their important role in developing desmoplastic stroma in pancreatic cancer. There also exists evidence that PSC are involved in other pathologies like type-2 diabetes mellitus. This article brings brief characteristics of PSCs and recent advances in research of these cells.

Exploring Evidence of Non-coding RNA Translation With Trips-Viz and GWIPS-Viz Browsers

Detection of translation in so-called non-coding RNA provides an opportunity for identification of novel bioactive peptides and microproteins. The main methods used for these purposes are ribosome profiling and mass spectrometry. A number of publicly available datasets already exist for a substantial number of different cell types grown under various conditions, and public data mining is an attractive strategy for identification of translation in non-coding RNAs. Since the analysis of publicly available data requires intensive data processing, several data resources have been created recently for exploring processed publicly available data, such as OpenProt, GWIPS-viz, and Trips-Viz. In this work we provide a detailed demonstration of how to use the latter two tools for exploring experimental evidence for translation of RNAs hitherto classified as non-coding. For this purpose, we use a set of transcripts with substantially different patterns of ribosome footprint distributions. We discuss how certain features of these patterns can be used as evidence for or against genuine translation. During our analysis we concluded that the MTLN mRNA, previously misannotated as lncRNA LINC00116, likely encodes only a short proteoform expressed from shorter RNA transcript variants.

Possible Roles of tRNA Fragments, as New Regulatory ncRNAs, in the Pathogenesis of Rheumatoid Arthritis

Understanding the pathophysiology of rheumatoid arthritis (RA) has led to the successful development of molecule-targeted drugs for the treatment of RA. However, some RA patients are refractory to these treatments, suggesting that the pathological mechanism of the disease is not entirely understood. Genome and transcriptome analysis is essential for understanding the unknown pathophysiology of human diseases. Rapid and more comprehensive gene analysis technologies have revealed notable changes in the expression of coding RNA and non-coding RNA in RA patients. This review focuses on the current state of non-coding RNA research in relation to RA, especially on tRNA fragments. Interestingly, it has been found that tRNA fragments repress translation and are antiapoptotic. The association between tRNA fragments and various diseases has been studied, and this article reviews the possible role of tRNA fragments in RA.

Evaluation of RNA isolation methods for microRNA quantification in a range of clinical biofluids

BACKGROUND

Extracellular microRNAs (miRNAs), released from cells into biofluids, have emerged as promising biomarkers for diagnostic and prognostic purposes. Several RNA isolation methods are available for the analysis of these cell-free miRNAs by RT-qPCR. Not all methods, however, are equally suitable for different biofluids. Here, we extracted total RNA from four very diverse biofluids: serum, urine, bile, and graft preservation fluid (perfusate). Four different protocols were used: a phenol-chloroform extraction and alcohol precipitation in combination with a precipitation carrier (QP) and three different column-based isolation methods, one with phenol-chloroform extraction (RN) and two without (NG and CU). For this range of clinical biofluid samples, we evaluated the potential of these different RNA isolation methods assessing recovery efficiency and the co-purification of RT-qPCR inhibiting compounds.

RESULTS

Differences were observed between each of the RNA isolation methods in the recovery of cel-miR-39, a synthetic miRNA spiked in during the workup procedure, and for endogenous miRNAs. Co-purification of heparin, a known RT-qPCR inhibitor, was assessed using heparinase I during cDNA synthesis. RT-qPCR detection of synthetic miRNAs cel-miR-39, spiked in during RNA workup, cel-miR-54, spiked in during cDNA synthesis, and endogenous miRNAs was strongly improved in the presence of heparinase I for some, but not all, isolation methods. Other, co-isolated RT-qPCR inhibitors were not identified, except for biliverdin, which co-isolated from some bile samples with one of the methods. In addition, we observed that serum and urine contain compounds that enhance the binding of heparin to certain solid-phase columns.

CONCLUSIONS

For reliable measurements of miRNA-based biomarkers in biofluids, optimization of RNA isolation procedures is recommended as methods can differ in miRNA detection and in co-purification of RT-qPCR inhibitory compounds. Heparinase I treatment confirmed that heparin appeared to be the major RT-qPCR inhibiting compound, but also biliverdin, co-isolated from bile, could interfere with detection.

Synthetase of the methyl donor S-adenosylmethionine from nitrogen-fixing α-rhizobia can bind functionally diverse RNA species

Function of bacterial small non-coding RNAs (sRNAs) and overall RNA metabolism is largely shaped by a vast diversity of RNA-protein interactions. However, in non-model bacteria with defined non-coding transcriptomes the sRNA interactome remains almost unexplored. We used affinity chromatography to capture proteins associated in vivo with MS2-tagged trans-sRNAs that regulate nutrient uptake (AbcR2 and NfeR1) and cell cycle (EcpR1) mRNAs by antisense-based translational inhibition in the nitrogen-fixing α-rhizobia Sinorhizobium meliloti. The three proteomes were rather distinct, with that of EcpR1 particularly enriched in cell cycle-related enzymes, whilst sharing several transcription/translation-related proteins recurrently identified associated with sRNAs. Strikingly, MetK, the synthetase of the major methyl donor S-adenosylmethionine, was reliably recovered as a binding partner of the three sRNAs, which reciprocally co-immunoprecipitated with a FLAG-tagged MetK variant. Induced (over)expression of the trans-sRNAs and MetK depletion did not influence canonical riboregulatory traits, `for example, protein titration or sRNA stability, respectively. An in vitro filter assay confirmed binding of AbcR2, NfeR1 and EcpR1 to MetK and further revealed interaction of the protein with other non-coding and coding transcripts but not with the 5S rRNA. These findings uncover a broad specificity for RNA binding as an unprecedented feature of this housekeeping prokaryotic enzyme.

RNAMotifContrast: a method to discover and visualize RNA structural motif subfamilies

Understanding the 3D structural properties of RNAs will play a critical role in identifying their functional characteristics and designing new RNAs for RNA-based therapeutics and nanotechnology. While several existing computational methods can help in the analysis of RNA properties by recognizing structural motifs, they do not provide the means to compare and contrast those motifs extensively. We have developed a new method, RNAMotifContrast, which focuses on analyzing the similarities and variations of RNA structural motif characteristics. In this method, a graph is formed to represent the similarities among motifs, and a new traversal algorithm is applied to generate visualizations of their structural properties. Analyzing the structural features among motifs, we have recognized and generalized the concept of motif subfamilies. To asses its effectiveness, we have applied RNAMotifContrast on a dataset of known RNA structural motif families. From the results, we observed that the derived subfamilies possess unique structural variations while holding standard features of the families. Overall, the visualization approach of this method presents a new perspective to observe the relation among motifs more closely, and the discovered subfamilies provide opportunities to achieve valuable insights into RNA’s diverse roles.

The Toolbox of Methods for Multidirectional Characterization of Dietary Nucleic Acids; Verification for Raw and Processed Food Products

Currently, the nutritional value of food is associated mainly with components such as proteins, carbohydrates, and lipids. However, another important macromolecules present in many foods are dietary nucleic acids (dietNA), i.e., DNA as well as both coding and non-coding RNAs. In the context of food chemistry and nutrition, dietNA are nowadays vastly neglected. In consequence, there are no dedicated methodologies to characterize dietNA. In this study, using raw or processed meat and plant products as model foodstuffs, we developed a toolbox of methods borrowed from other fields (histology, toxicology, molecular biology) that enable the initial characterization of dietNA as a necessary step on the way to systematic evaluation of their nutritional role. The proposed set of methods embraces (i) paraffin embedding of food samples and their staining to visualize the distribution and variety of dietNA in situ; (ii) comet assay to assess integrity of nuclear DNA with possible detection of DNA damage; (iii) dietNA isolation with and without RNAse digestion to determine the content of both DNA and RNA; (iv) electrophoretic separation of isolates to profile dietNA fragments. Such a combined methodological approach revealed clear differences between dietNA derived from raw and processed food products. We believe that the presented set of methods will encourage the broader research on dietNA to understand their role as a nutritionally relevant food component.

Selenium-atom-modified thymidine enhances the specificity and sensitivity of DNA polymerization and detection

Nucleobase mismatches can jeopardize DNA polymerization specificity, causing mutations and errors in DNA replication and detection. Herein we report the first synthesis of novel 2-Se-thymidine triphosphate (SeTTP), describe the single-selenium atom-specific modification strategy (SAM) against T/G mismatches, and demonstrate SAM-assisted polymerization and detection with much higher specificity and sensitivity. SAM can effectively suppress the formation of non-specific products in DNA polymerization and detection. Thus, SAM enhances the specificity of DNA synthesis by approximately 10 000 fold, and in turn, it allows the detection of clinical COVID-19 viral RNA in low copy numbers (single-digit copies), while the conventional RT-qPCR does not.

Triazole-Modified Nucleic Acids for the Application in Bioorganic and Medicinal Chemistry

This review covers studies which exploit triazole-modified nucleic acids in the range of chemistry and biology to medicine. The 1,2,3-triazole unit, which is obtained via click chemistry approach, shows valuable and unique properties. For example, it does not occur in nature, constitutes an additional pharmacophore with attractive properties being resistant to hydrolysis and other reactions at physiological pH, exhibits biological activity (i.e., antibacterial, antitumor, and antiviral), and can be considered as a rigid mimetic of amide linkage. Herein, it is presented a whole area of useful artificial compounds, from the clickable monomers and dimers to modified oligonucleotides, in the field of nucleic acids sciences. Such modifications of internucleotide linkages are designed to increase the hybridization binding affinity toward native DNA or RNA, to enhance resistance to nucleases, and to improve ability to penetrate cell membranes. The insertion of an artificial backbone is used for understanding effects of chemically modified oligonucleotides, and their potential usefulness in therapeutic applications. We describe the state-of-the-art knowledge on their implications for synthetic genes and other large modified DNA and RNA constructs including non-coding RNAs.