Are Argonaute-Associated Tiny RNAs Junk, Inferior miRNAs, or a New Type of Functional RNAs?

The biosynthesis pathways of microRNAs (miRNAs) have been well characterized with the identification of the required components. miRNAs are synthesized from the transcripts of miRNA genes and other RNAs, such as introns, transfer RNAs, ribosomal RNAs, small nucleolar RNAs, and even viral miRNAs. These small RNAs are loaded into Argonaute (AGO) proteins and recruit the effector complexes to target mRNAs, repressing their gene expression post-transcriptionally. While mature miRNAs were defined as 19–23 nucleotides (nt), tiny RNAs (tyRNAs) shorter than 19 nt have been found to bind AGOs as equivalent or lesser miRNAs compared to their full-length mature miRNAs. In contrast, my recent study revealed that when human AGO3 loads 14 nt cleavage-inducing tyRNAs (cityRNAs), comprised of the first 14 nt of their corresponding mature miRNA, it can become a comparable slicer to AGO2. This observation raises the possibility that tyRNAs play distinct roles from their mature form. This minireview focuses on human AGO-associated tyRNAs shorter than 19 nt and discusses their possible biosynthesis pathways and physiological benefits, including how tyRNAs could avoid target-directed miRNA degradation accompanied by AGO polyubiquitination.

Nonenzymatic loop-closing ligation generates RNA hairpins and is a template-free way to assemble functional RNAs

RNA hairpin loops are the predominant element of secondary structure in functional RNAs. The emergence of primordial functional RNAs, such as ribozymes that fold into complex structures that contain multiple hairpin loops, is generally thought to have been supported by template-directed ligation. However, template inhibition and RNA misfolding problems impede the emergence of function. Here we demonstrate that RNA hairpin loops can be synthesized directly from short RNA duplexes with single-stranded overhangs by nonenzymatic loop-closing ligation chemistry. We show that loop-closing ligation allows full-length functional ribozymes containing a hairpin loop to be assembled free of inhibitory template strands. This approach to the assembly of structurally complex RNAs suggests a plausible pathway for the emergence of functional RNAs before a full-length RNA copying process became available.

LncRNAs LY86-AS1 and VIM-AS1 Distinguish Plasma Cell Leukemia Patients from Multiple Myeloma Patients

Long non-coding RNAs (lncRNAs) are functional RNAs longer than 200 nucleotides. Due to modern genomic techniques, the involvement of lncRNAs in tumorigenesis has been revealed; however, information concerning lncRNA interplay in multiple myeloma (MM) and plasma cell leukemia (PCL) is virtually absent. Herein, we aimed to identify the lncRNAs involved in MM to PCL progression. We investigated representative datasets of MM and PCL patients using next-generation sequencing. In total, 13 deregulated lncRNAs (p < 0.00025) were identified; four of them were chosen for further validation in an independent set of MM and PCL patients by RT-qPCR. The obtained results proved the significant downregulation of lymphocyte antigen antisense RNA 1 (LY86-AS1) and VIM antisense RNA 1 (VIM-AS1) in PCL compared to MM. Importantly, these two lncRNAs could be involved in the progression of MM into PCL; thus, they could serve as promising novel biomarkers of MM progression.

Variety of Non-Coding RNAs in Eukaryotic Genomes

The genomes of large multicellular eukaryotes mainly consist of DNA that encodes not proteins, but RNAs. The unexpected discovery of approximately the same number of protein genes in Homo sapiens and Caenorhabditis elegans led to the understanding that it is not the number of proteins that determines the complexity of the development and functioning of an organism. The phenomenon of pervasive transcription of genomes is finding more and more confirmation. Data are emerging on new types of RNA that work in different cell compartments, are expressed at different stages of development, in different tissues and perform various functions. Their main purpose is fine regulation of the main cellular processes. The presence of a rich arsenal of regulators that can interact with each other and work on the principle of interchangeability determines the physiological complexity of the organism and its ability to adapt to changing environmental conditions. An overview of the currently known functional RNAs expressed in eukaryotic genomes is presented here. There is no doubt that in the near future, using high-tech transcriptome technologies, many new RNAs will be identified and characterized. But it is likely that many of the expressed transcripts do not have a function, but are an evolutionary reserve of organisms.

Sub-3 Angstrom cryo-EM structure of RNA enabled by engineered homomeric self-assembly

Many functional RNAs fold into intricate and precise 3D architectures, and high-resolution structures are required to understand their underlying mechanistic principles. However, RNA structural determination is difficult. Herein, we present a nanoarchitectural strategy to enable the efficient single-particle cryogenic electron microscopy (cryo-EM) analysis of RNA-only structures. This strategy, termed RNA oligomerization-enabled cryo-EM via installing kissing-loops (ROCK), involves the engineering of target RNAs by installing kissing-loop sequences onto functionally nonessential stems for the assembly into closed homomeric nanoarchitectures. Assembly with geometric restraints leads to (1) molecular weight multiplication and (2) structural flexibility mitigation, both beneficial for cryo-EM analysis. Together with construct optimization and symmetry-expansion reconstruction, ROCK yields the cryo-EM reconstruction of the Tetrahymena group I intron at an overall resolution of 2.98 Angstrom (2.85 Angstrom resolution for the core domains), enabling the de novo model building of the complete intron RNA including previously unknown peripheral domains. When applied to smaller RNAs, ROCK readily produces modest-resolution maps, revealing the conformational rearrangement of the Azoarcus group I intron and the bound ligand in the FMN riboswitch. Our work unleashes the largely unexplored potential of cryo-EM in RNA structural studies.

High-throughput dissection of the thermodynamic and conformational properties of a ubiquitous class of RNA tertiary contact motifs

Despite RNA’s diverse secondary and tertiary structures and its complex conformational changes, nature utilizes a limited set of structural “motifs”—helices, junctions, and tertiary contact modules—to build diverse functional RNAs. Thus, in-depth descriptions of a relatively small universe of RNA motifs may lead to predictive models of RNA tertiary conformational landscapes. Motifs may have different properties depending on sequence and secondary structure, giving rise to subclasses that expand the universe of RNA building blocks. Yet we know very little about motif subclasses, given the challenges in mapping conformational properties in high throughput. Previously, we used “RNA on a massively parallel array” (RNA-MaP), a quantitative, high-throughput technique, to study thousands of helices and two-way junctions. Here, we adapt RNA-MaP to study the thermodynamic and conformational properties of tetraloop/tetraloop receptor (TL/TLR) tertiary contact motifs, analyzing 1,493 TLR sequences from different classes. Clustering analyses revealed variability in TL specificity, stability, and conformational behavior. Nevertheless, natural GAAA/11ntR TL/TLRs, while varying in tertiary stability by ∼2.5 kcal/mol, exhibited conserved TL specificity and conformational properties. Thus, RNAs may tune stability without altering the overall structure of these TL/TLRs. Furthermore, their stability correlated with natural frequency, suggesting thermodynamics as the dominant selection pressure. In contrast, other TL/TLRs displayed heterogenous conformational behavior and appear to not be under strong thermodynamic selection. Our results build toward a generalizable model of RNA-folding thermodynamics based on the properties of isolated motifs, and our characterized TL/TLR library can be used to engineer RNAs with predictable thermodynamic and conformational behavior.

Diagnosis and Therapeutic Management of Liver Fibrosis by microRNA

Remarkable progress has been made in the treatment and control of hepatitis B and C viral infections. However, fundamental treatments for diseases in which liver fibrosis is a key factor, such as cirrhosis, alcoholic/nonalcoholic steatohepatitis, autoimmune hepatitis, primary biliary cholangitis, and primary sclerosing cholangitis, are still under development and remain an unmet medical need. To solve this problem, it is essential to elucidate the pathogenesis of liver fibrosis in detail from a molecular and cellular perspective and to develop targeted therapeutic agents based on this information. Recently, microRNAs (miRNAs), functional RNAs of 22 nucleotides, have been shown to be involved in the pathogenesis of liver fibrosis. In addition, extracellular vesicles called “exosomes” have been attracting attention, and research is being conducted to establish noninvasive and extremely sensitive biomarkers using miRNAs in exosomes. In this review, we summarize miRNAs directly involved in liver fibrosis, miRNAs associated with diseases leading to liver fibrosis, and miRNAs related to complications of cirrhosis. We will also discuss the efficacy of each miRNA as a biomarker of liver fibrosis and pathology, and its potential application as a therapeutic agent.

Arabidopsis Disulfide Reductase, Trx-h2, Functions as an RNA Chaperone under Cold Stress

The thioredoxin-h (Trx-h) family of Arabidopsis thaliana comprises cytosolic disulfide reductases. However, the physiological function of Trx-h2, which contains an additional 19 amino acids at its N-terminus, remains unclear. In this study, we investigated the molecular function of Trx-h2 both in vitro and in vivo and found that Arabidopsis Trx-h2 overexpression (Trx-h2OE) lines showed significantly longer roots than wild-type plants under cold stress. Therefore, we further investigated the role of Trx-h2 under cold stress. Our results revealed that Trx-h2 functions as an RNA chaperone by melting misfolded and non-functional RNAs, and by facilitating their correct folding into active forms with native conformation. We showed that Trx-h2 binds to and efficiently melts nucleic acids (ssDNA, dsDNA, and RNA), and facilitates the export of mRNAs from the nucleus to the cytoplasm under cold stress. Moreover, overexpression of Trx-h2 increased the survival rate of the cold-sensitive E. coli BX04 cells under low temperature. Thus, our data show that Trx-h2 performs function as an RNA chaperone under cold stress, thus increasing plant cold tolerance.

Circulating MicroRNAs in Gastrointestinal Cancer

Gastrointestinal cancer (GIC) is a common disease and is considered to be the leading cause of cancer-related death worldwide; thus, new diagnostic and therapeutic strategies for GIC are urgently required. Noncoding RNAs (ncRNAs) are functional RNAs that are transcribed from the genome but do not encode proteins. MicroRNAs (miRNAs) are short ncRNAs that are reported to function as both oncogenes and tumor suppressors. Moreover, several miRNA-based drugs are currently proceeding to clinical trials for various diseases, including cancer. In recent years, the stability of circulating miRNAs in blood has been demonstrated. This is of interest because these miRNAs could be potential noninvasive biomarkers of cancer. In this review, we focus on circulating miRNAs associated with GIC and discuss their potential as novel biomarkers.

A convolutional neural network for the prediction and forward design of ribozyme-based gene-control elements

Ribozyme switches are a class of RNA-encoded genetic switch that support conditional regulation of gene expression across diverse organisms. An improved elucidation of the relationships between sequence, structure, and activity can improve our capacity for de novo rational design of ribozyme switches. Here, we generated data on the activity of hundreds of thousands of ribozyme sequences. Using automated structural analysis and machine learning, we leveraged these large datasets to develop predictive models that estimate the in vivo gene-regulatory activity of a ribozyme sequence. These models supported the de novo design of ribozyme libraries with low mean basal gene-regulatory activities and new ribozyme switches that exhibit changes in gene-regulatory activity in the presence of a target ligand, producing functional switches for four out of five aptamers. Our work examines how biases in the model and the dataset that affect prediction accuracy can arise and demonstrates that machine learning can be applied to RNA sequences to predict gene-regulatory activity, providing the basis for design tools for functional RNAs.