Folding and finding RNA secondary structure

Therapeutic Antisense Oligonucleotides in Oncology: From Bench to Bedside

Advancements in our comprehension of tumor biology and chemoresistance have spurred the development of treatments that precisely target specific molecules within the body. Despite the expanding landscape of therapeutic options, there persists a demand for innovative approaches to address unmet clinical needs. RNA therapeutics have emerged as a promising frontier in this realm, offering novel avenues for intervention such as RNA interference and the utilization of antisense oligonucleotides (ASOs). ASOs represent a versatile class of therapeutics capable of selectively targeting messenger RNAs (mRNAs) and silencing disease-associated proteins, thereby disrupting pathogenic processes at the molecular level. Recent advancements in chemical modification and carrier molecule design have significantly enhanced the stability, biodistribution, and intracellular uptake of ASOs, thereby bolstering their therapeutic potential. While ASO therapy holds promise across various disease domains, including oncology, coronary angioplasty, neurological disorders, viral, and parasitic diseases, our review manuscript focuses specifically on the application of ASOs in targeted cancer therapies. Through a comprehensive examination of the latest research findings and clinical developments, we delve into the intricacies of ASO-based approaches to cancer treatment, shedding light on their mechanisms of action, therapeutic efficacy, and prospects.

Exploring functional conservation in silico: a new machine learning approach to RNA-editing

Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed, with a remarkable impact in the increase of the complexity of the transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with an attention layer. These algorithms, combined with RNA-editing data coming from databases and variant calling from same-individual RNA and DNA-seq experiments from different species, allowed us to predict RNA-editing events using both primary sequence and secondary structure. Then, we devised a method for assessing conservation or divergence in the molecular mechanisms of editing completely in silico: the cross-testing analysis. This novel method not only helps to understand the conservation of the editing mechanism through evolution but could set the basis for achieving a better understanding of the adenosine-targeting mechanism in other fields.

Structural Impact of the Interaction of the Influenza A Virus Nucleoprotein with Genomic RNA Segments

Influenza A viruses (IAVs) possess a segmented genome consisting of eight viral RNAs (vRNAs) associated with multiple copies of viral nucleoprotein (NP) and a viral polymerase complex. Despite the crucial role of RNA structure in IAV replication, the impact of NP binding on vRNA structure is not well understood. In this study, we employed SHAPE chemical probing to compare the structure of NS and M vRNAs of WSN IAV in various states: before the addition of NP, in complex with NP, and after the removal of NP. Comparison of the RNA structures before the addition of NP and after its removal reveals that NP, while introducing limited changes, remodels local structures in both vRNAs and long-range interactions in the NS vRNA, suggesting a potentially biologically relevant RNA chaperone activity. In contrast, NP significantly alters the structure of vRNAs in vRNA/NP complexes, though incorporating experimental data into RNA secondary structure prediction proved challenging. Finally, our results suggest that NP not only binds single-stranded RNA but also helices with interruptions, such as bulges or small internal loops, with a preference for G-poor and C/U-rich regions.

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

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

Exploring the adaptability of the secondary structure of mRNA to temperature in intertidal snails based on SHAPE experiments

RNA-based thermal regulation is an important strategy for organisms to cope with temperature changes. Inhabiting the intertidal rocky shore, a key interface of the ocean, atmosphere and terrestrial environments, intertidal species have developed variable thermal adaptation mechanisms; however, adaptions at the RNA level remain largely uninvestigated. To examine the relationship between mRNA structural stability and species distribution, in the present study, the secondary structure of cytosolic malate dehydrogenase (cMDH) mRNA of Echinolittorina malaccana, Echinolittorina radiata and Littorina brevicula was determined using selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE), and the change in folding free energy of formation (ΔGfold) was calculated. The results showed that ΔGfold increased as the temperature increased. The difference in ΔGfold (ΔΔGfold) between two specific temperatures (25 versus 0°C, 37 versus 0°C and 57 versus 0°C) differed among the three species, and the ΔΔGfold value of E. malaccana was significantly lower than those of E. radiata and L. brevicula. The number of stems of cMDH mRNA of the snails decreased with increasing temperature, and the breakpoint temperature of E. malaccana was the highest among these. The number of loops was also reduced with increasing temperature, while the length of the loop structure increased accordingly. Consequently, these structural changes can potentially affect the translational efficiency of mRNA. These results imply that there were interspecific differences in the thermal stability of RNA secondary structures in intertidal snails, and these differences may be related to snail distribution.

RNA-Selective Small-Molecule Ligands: Recent Advances in Live-Cell Imaging and Drug Discovery

RNA structures, including those formed from coding and noncoding RNAs, alternative to protein-based drug targets, could be a promising target of small molecules for drug discovery against various human diseases, particularly in anticancer, antibacterial and antivirus development. The normal cellular activity of cells is critically dependent on the function of various RNA molecules generated from DNA transcription. Moreover, many studies support that mRNA-targeting small molecules may regulate the synthesis of disease-related proteins via the non-covalent mRNA-ligand interactions that do not involve gene modification. RNA-ligand interaction is thus an attractive approach to address the challenge of "undruggable" proteins in drug discovery because the intracellular activity of these proteins is hard to be suppressed with small molecule ligands. We selectively surveyed a specific area of RNA structure-selective small molecule ligands in fluorescence live cell imaging and drug discovery because the area was currently underexplored. This state-of-the-art review thus mainly focuses on the research published within the past three years and aims to provide the most recent information on this research area; hopefully, it could be complementary to the previously reported reviews and give new insights into the future development on RNA-specific small molecule ligands for live cell imaging and drug discovery.

Dissecting the energetic architecture within an RNA tertiary structural motif via high-throughput thermodynamic measurements

Structured RNAs and RNA/protein complexes perform critical cellular functions. They often contain structurally conserved tertiary contact "motifs," whose occurrence simplifies the RNA folding landscape. Prior studies have focused on the conformational and energetic modularity of intact motifs. Here, we turn to the dissection of one common motif, the 11nt receptor (11ntR), using quantitative analysis of RNA on a massively parallel array to measure the binding of all single and double 11ntR mutants to GAAA and GUAA tetraloops, thereby probing the energetic architecture of the motif. While the 11ntR behaves as a motif, its cooperativity is not absolute. Instead, we uncovered a gradient from high cooperativity amongst base-paired and neighboring residues to additivity between distant residues. As expected, substitutions at residues in direct contact with the GAAA tetraloop resulted in the largest decreases to binding, and energetic penalties of mutations were substantially smaller for binding to the alternate GUAA tetraloop, which lacks tertiary contacts present with the canonical GAAA tetraloop. However, we found that the energetic consequences of base partner substitutions are not, in general, simply described by base pair type or isostericity. We also found exceptions to the previously established stability-abundance relationship for 11ntR sequence variants. These findings of "exceptions to the rule" highlight the power of systematic high-throughput approaches to uncover novel variants for future study in addition to providing an energetic map of a functional RNA.

In vivo single-molecule RNA structural profiling

Cellular RNAs exhibit substantial heterogeneity in structure and function. Recently, Yang et al. developed an in vivo single-molecule RNA structure profiling methodology and revealed that individual isoforms of noncoding transcripts adopt multiple diverse and functionally relevant structural conformations, which change in abundance and structure in response to temperature conditions.

RNA Structure Determination by High-Throughput Structural Analysis

RNA functions are closely linked with their structures. Therefore, elucidating the secondary structure of RNAs provides crucial information regarding their function. The chemical modification or RNase-mediated digestion of single-stranded RNA has been utilized to experimentally reveal RNA secondary structures. Owing to advances in high-throughput sequencing technology and chemical analysis, RNA structural analyses that enable structural profiling at the transcriptomic scale in living cells have been developed. Here, we provide an overview of the high-throughput RNA structural (HTS) analyses and describe the computational processing steps of recent HTS analysis pipelines: PROBer, BUMHMM, and reactIDR.

In vivo single-molecule analysis reveals COOLAIR RNA structural diversity

Cellular RNAs are heterogeneous with respect to their alternative processing and secondary structures, but the functional importance of this complexity is still poorly understood. A set of alternatively processed antisense non-coding transcripts, which are collectively called COOLAIR, are generated at the Arabidopsis floral-repressor locus FLOWERING LOCUS C (FLC)1. Different isoforms of COOLAIR influence FLC transcriptional output in warm and cold conditions2-7. Here, to further investigate the function of COOLAIR, we developed an RNA structure-profiling method to determine the in vivo structure of single RNA molecules rather than the RNA population average. This revealed that individual isoforms of the COOLAIR transcript adopt multiple structures with different conformational dynamics. The major distally polyadenylated COOLAIR isoform in warm conditions adopts three predominant structural conformations, the proportions and conformations of which change after cold exposure. An alternatively spliced, strongly cold-upregulated distal COOLAIR isoform6 shows high structural diversity, in contrast to proximally polyadenylated COOLAIR. A hyper-variable COOLAIR structural element was identified that was complementary to the FLC transcription start site. Mutations altering the structure of this region changed FLC expression and flowering time, consistent with an important regulatory role of the COOLAIR structure in FLC transcription. Our work demonstrates that isoforms of non-coding RNA transcripts adopt multiple distinct and functionally relevant structural conformations, which change in abundance and shape in response to external conditions.

The Potential Role of RNA Structure in Crop Molecular Breeding

The continually growing human population creates a concomitantly increasing demand for nutritious crops with high yields. Advances in high throughput sequencing technologies have revealed the genetic architecture of major crops. This includes extensive information enabling comprehensive genetic markers for breeding selection, new gene discoveries, and novel gene regulatory strategies for crop editing. RNA structure is an important type of genetic feature, essential for post-transcriptional regulation of gene expression. Here, we summarize recent advances in genome-wide RNA structure studies in crops and review the associated RNA structure-mediated regulation of gene expression. We also discuss the functional importance of those single nucleotide variations that induce large RNA structure disparities. Lastly, we discuss the potential role of RNA structure in crop molecular breeding.

UFold: fast and accurate RNA secondary structure prediction with deep learning

For many RNA molecules, the secondary structure is essential for the correct function of the RNA. Predicting RNA secondary structure from nucleotide sequences is a long-standing problem in genomics, but the prediction performance has reached a plateau over time. Traditional RNA secondary structure prediction algorithms are primarily based on thermodynamic models through free energy minimization, which imposes strong prior assumptions and is slow to run. Here, we propose a deep learning-based method, called UFold, for RNA secondary structure prediction, trained directly on annotated data and base-pairing rules. UFold proposes a novel image-like representation of RNA sequences, which can be efficiently processed by Fully Convolutional Networks (FCNs). We benchmark the performance of UFold on both within- and cross-family RNA datasets. It significantly outperforms previous methods on within-family datasets, while achieving a similar performance as the traditional methods when trained and tested on distinct RNA families. UFold is also able to predict pseudoknots accurately. Its prediction is fast with an inference time of about 160 ms per sequence up to 1500 bp in length. An online web server running UFold is available at https://ufold.ics.uci.edu. Code is available at https://github.com/uci-cbcl/UFold.

Structural DNA nanotechnology: Immobile Holliday junctions to artificial robots

DNA nanotechnology marvels the scientific world with its capabilities to design, engineer, and demonstrate nanoscale shapes. This review is a condensed version walking the reader through the structural developments in the field over the past 40 years starting from the basic design rules of the double-stranded building block to the most recent advancements in self-assembled hierarchically achieved structures to date. It builds off from the fundamental motivation of building 3-dimensional (3D) lattice structures of tunable cavities going all the way up to artificial nanorobots fighting cancer. The review starts by covering the most important developments from the fundamental bottom-up approach of building structures, which is the 'tile' based approach covering 1D, 2D, and 3D building blocks, after which, the top-down approach using DNA origami and DNA bricks is also covered. Thereafter, DNA nanostructures assembled using not so commonly used (yet promising) techniques like i-motifs, quadruplexes, and kissing loops are covered. Highlights from the field of dynamic DNA nanostructures have been covered as well, walking the reader through the various approaches used within the field to achieve movement. The article finally concludes by giving the authors a view of what the future of the field might look like while suggesting in parallel new directions that fellow/future DNA nanotechnologists could think about.

PRKCE non-coding variants influence on transcription as well as translation of its gene

Untranslated regions of the gene play a crucial role in gene expression regulation at mRNA and protein levels. Mutations at UTRs impact expression by altering transcription factor binding, transcriptional/translational efficacy, miRNA-mediated gene regulation, mRNA secondary structure, ribosomal translocation, and stability. PKCε, a serine/threonine kinase, is aberrantly expressed in numerous diseases such as cardiovascular disorders, neurological disorders, and cancers; its probable cause is unknown. Therefore, in the current study, the influence of PRKCE 5'-and 3'UTR variants was explored for their potential impact on its transcription and translation through several bioinformatics approaches. UTR variants data was obtained through different databases and initially evaluated for their regulatory function. Variants with regulatory function were then studied for their effect on PRKCE binding with transcription factors (TF) and miRNAs, as well as their impact on mRNA secondary structure. Study outcomes indicated the regulatory function of 73 5'UTR and 17 3'UTR variants out of 376. 5'UTR variants introduced AP1 binding sites and promoted the PRKCE transcription. Four 3'UTR variants introduced a circular secondary structure, increasing PRKCE translational efficacy. A region in 5'UTR position 45,651,564 to 45,651,644 was found where variants readily influenced the miRNA-PRKCE mRNA binding. The study further highlighted a PKCε-regulated feedback loop mechanism that induces the activity of TFs, promoting its gene transcription. The study provides foundations for experimentation to understand these variants' role in diseases. These variants can also serve as the genetic markers for different diseases' diagnoses after validation at the cell and population levels.

Universal and strain specific structure features of segment 8 genomic RNA of influenza A virus-application of 4-thiouridine photocrosslinking

RNA structure in the influenza A virus (IAV) has been the focus of several studies that have shown connections between conserved secondary structure motifs and their biological function in the virus replication cycle. Questions have arisen on how to best recognize and understand the pandemic properties of IAV strains from an RNA perspective, but determination of the RNA secondary structure has been challenging. Herein, we used chemical mapping to determine the secondary structure of segment 8 viral RNA (vRNA) of the pandemic A/California/04/2009 (H1N1) strain of IAV. Additionally, this long, naturally occurring RNA served as a model to evaluate RNA mapping with 4-thiouridine (4sU) crosslinking. We explored 4-thiouridine as a probe of nucleotides in close proximity, through its incorporation into newly transcribed RNA and subsequent photoactivation. RNA secondary structural features both universal to type A strains and unique to the A/California/04/2009 (H1N1) strain were recognized. 4sU mapping confirmed and facilitated RNA structure prediction, according to several rules: 4sU photocross-linking forms efficiently in the double-stranded region of RNA with some flexibility, in the ends of helices, and across bulges and loops when their structural mobility is permitted. This method highlighted three-dimensional properties of segment 8 vRNA secondary structure motifs and allowed to propose several long-range three-dimensional interactions. 4sU mapping combined with chemical mapping and bioinformatic analysis could be used to enhance the RNA structure determination as well as recognition of target regions for antisense strategies or viral RNA detection.

LazySampling and LinearSampling: Fast Stochastic Sampling of RNA Secondary Structure with Applications to SARS-CoV-2

Many RNAs fold into multiple structures at equilibrium. The classical stochastic sampling algorithm can sample secondary structures according to their probabilities in the Boltzmann ensemble, and is widely used. However, this algorithm, consisting of a bottom-up partition function phase followed by a top-down sampling phase, suffers from three limitations: (a) the formulation and implementation of the sampling phase are unnecessarily complicated; (b) the sampling phase repeatedly recalculates many redundant recursions already done during the partition function phase; (c) the partition function runtime scales cubically with the sequence length. These issues prevent stochastic sampling from being used for very long RNAs such as the full genomes of SARS-CoV-2. To address these problems, we first adopt a hypergraph framework under which the sampling algorithm can be greatly simplified. We then present three sampling algorithms under this framework, among which the LazySampling algorithm is the fastest by eliminating redundant work in the sampling phase via on-demand caching. Based on LazySampling, we further replace the cubic-time partition function by a linear-time approximate one, and derive LinearSampling, an end-to-end linear-time sampling algorithm that is orders of magnitude faster than the standard one. For instance, LinearSampling is 176Ã- faster (38.9s vs. 1.9h) than Vienna RNAsubopt on the full genome of Ebola virus (18,959 nt ). More importantly, LinearSampling is the first RNA structure sampling algorithm to scale up to the full-genome of SARS-CoV-2 without local window constraints, taking only 69.2 seconds on its reference sequence (29,903 nt ). The resulting sample correlates well with the experimentally-guided structures. On the SARS-CoV-2 genome, LinearSampling finds 23 regions of 15 nt with high accessibilities, which are potential targets for COVID-19 diagnostics and drug design. See code: https://github.com/LinearFold/LinearSampling.

Mechanisms and applications of peptide nucleic acids selectively binding to double-stranded RNA

RNAs form secondary structures containing double-stranded base paired regions and single-stranded regions. Probing, detecting and modulating RNA structures and dynamics requires the development of molecular sensors that can differentiate the sequence and structure of RNAs present in viruses and cells, as well as in extracellular space. In this review, we summarize the recent progress on the development of chemically modified peptide nucleic acids (PNAs) for the selective recognition of double-stranded RNA (dsRNA) sequences over both single-stranded RNA (ssRNA) and double-stranded DNA (dsDNA) sequences. We also briefly discuss the applications of sequence-specific dsRNA-binding PNAs in sensing and stabilizing dsRNA structures and inhibiting dsRNA-protein interactions.

Conservation in the Iron Responsive Element Family

Iron responsive elements (IREs) are mRNA stem-loop targets for translational control by the two iron regulatory proteins IRP1 and IRP2. They are found in the untranslated regions (UTRs) of genes that code for proteins involved in iron metabolism. There are ten “classic” IRE types that define the conserved secondary and tertiary structure elements necessary for proper IRP binding, and there are 83 published “IRE-like” sequences, most of which depart from the established IRE model. Here are structurally-guided discussions regarding the essential features of an IRE and what is important for IRE family membership.

Structural evolution of SLA promoter in mosquito-borne flaviviruses: A sequence-structure based phylogenetic framework

All the flaviviruses have a Y-shaped stem-loop secondary structure known as the SLA element, and the structural features of this element are crucial to initiating the infection cycle. The present study particularly investigated how flaviviruses retained the common core SLA element secondary structure during the species evolution by selecting mosquito-borne flaviviruses (MBFVs) as a case study. The detailed search of nucleotide substitutions in species-wise consensus SLA secondary structure models suggested that the compensatory and hemi-compensatory base changes in the helices are crucial to preserving the common core secondary structure. In contrast to the coding region-based phylogeny, the SLA sequence-structure-based phylogenetic tree revealed an intriguing evolutionary relationship among MBFVs. Overall, this paper demonstrated for the first time the efficacy of RNA secondary structures as a phylogenetic marker to study the RNA virus evolution.

ncRDense: A novel computational approach for classification of non-coding RNA family by deep learning

With the rapidly growing importance of biological research, non-coding RNAs (ncRNA) attract more attention in biology and bioinformatics. They play vital roles in biological processes such as transcription and translation. Classification of ncRNAs is essential to our understanding of disease mechanisms and treatment design. Many approaches to ncRNA classification have been developed, several of which use machine learning and deep learning. In this paper, we construct a novel deep learning-based architecture, ncRDense, to effectively classify and distinguish ncRNA families. In a comparative study, our model produces comparable results with existing state-of-the-art methods. Finally, we built a freely accessible web server for the ncRDense tool, which is available at http://nsclbio.jbnu.ac.kr/tools/ncRDense/.

Selection of aptamers against triple negative breast cancer cells using high throughput sequencing

Triple-negative breast cancer is the most aggressive subtype of invasive breast cancer with a poor prognosis and no approved targeted therapy. Hence, the identification of new and specific ligands is essential to develop novel targeted therapies. In this study, we aimed to identify new aptamers that bind to highly metastatic breast cancer MDA-MB-231 cells using the cell-SELEX technology aided by high throughput sequencing. After 8 cycles of selection, the aptamer pool was sequenced and the 25 most frequent sequences were aligned for homology within their variable core region, plotted according to their free energy and the key nucleotides possibly involved in the target binding site were analyzed. Two aptamer candidates, Apt1 and Apt2, binding specifically to the target cells with \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$K_{d}$$\end{document}Kd values of 44.3 ± 13.3 nM and 17.7 ± 2.7 nM, respectively, were further validated. The binding analysis clearly showed their specificity to MDA-MB-231 cells and suggested the targeting of cell surface receptors. Additionally, Apt2 revealed no toxicity in vitro and showed potential translational application due to its affinity to breast cancer tissue sections. Overall, the results suggest that Apt2 is a promising candidate to be used in triple-negative breast cancer treatment and/or diagnosis.

IoT Platform for COVID-19 Prevention and Control: A Survey

As a result of the worldwide transmission of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), coronavirus disease 2019 (COVID-19) has evolved into an unprecedented pandemic. Currently, with unavailable pharmaceutical treatments and low vaccination rates, this novel coronavirus results in a great impact on public health, human society, and global economy, which is likely to last for many years. One of the lessons learned from the COVID-19 pandemic is that a long-term system with non-pharmaceutical interventions for preventing and controlling new infectious diseases is desirable to be implemented. Internet of things (IoT) platform is preferred to be utilized to achieve this goal, due to its ubiquitous sensing ability and seamless connectivity. IoT technology is changing our lives through smart healthcare, smart home, and smart city, which aims to build a more convenient and intelligent community. This paper presents how the IoT could be incorporated into the epidemic prevention and control system. Specifically, we demonstrate a potential fog-cloud combined IoT platform that can be used in the systematic and intelligent COVID-19 prevention and control, which involves five interventions including COVID-19 Symptom Diagnosis, Quarantine Monitoring, Contact Tracing & Social Distancing, COVID-19 Outbreak Forecasting, and SARS-CoV-2 Mutation Tracking. We investigate and review the state-of-the-art literatures of these five interventions to present the capabilities of IoT in countering against the current COVID-19 pandemic or future infectious disease epidemics.

Potential of long non-coding RNAs as a therapeutic target and molecular markers in glioblastoma pathogenesis

Glioblastoma (GB) is by far the most hostile type of malignant tumor that primarily affects the brain and spine, derived from star-shaped glial cells that are astrocytes and oligodendrocytes. Despite of significant efforts in recent years in glioblastoma research, the clinical efficacy of existing medical intervention is still limited and very few potential diagnostic markers are available. Long non-coding RNAs (lncRNAs) that lacks protein-coding capabilities were previously thought to be "junk sequences" in mammalian genomes are quite indispensible epigenetic regulators that can positively or negatively regulate gene expression and nuclear architecture, with significant roles in the initiation and development of tumors. Nevertheless, the precise mechanism of these distortedly expressed lncRNAs in glioblastoma pathogenesis is not yet fully understood. Since the advent of high-throughput sequencing technologies, more and more research have elucidated that lncRNAs are one of the most promising prognostic biomarkers and therapeutic targets for glioblastoma. In this paper, I briefly outlined the existing findings of lncRNAs. And also summarizes the profiles of different lncRNAs that have been broadly classified in glioblastoma research, with emphasis on both their prognostic and therapeutic values.

Identification of Natural Antisense Transcripts in Mouse Brain and Their Association With Autism Spectrum Disorder Risk Genes

Genome-wide sequencing technologies have greatly contributed to our understanding of the genetic basis of neurodevelopmental disorders such as autism spectrum disorder (ASD). Interestingly, a number of ASD-related genes express natural antisense transcripts (NATs). In some cases, these NATs have been shown to play a regulatory role in sense strand gene expression and thus contribute to brain function. However, a detailed study examining the transcriptional relationship between ASD-related genes and their NAT partners is lacking. We performed strand-specific, deep RNA sequencing to profile expression of sense and antisense reads with a focus on 100 ASD-related genes in medial prefrontal cortex (mPFC) and striatum across mouse post-natal development (P7, P14, and P56). Using de novo transcriptome assembly, we generated a comprehensive long non-coding RNA (lncRNA) transcriptome. We conducted BLAST analyses to compare the resultant transcripts with the human genome and identified transcripts with high sequence similarity and coverage. We assembled 32861 de novo antisense transcripts mapped to 12182 genes, of which 1018 are annotated by Ensembl as lncRNA. We validated the expression of a subset of selected ASD-related transcripts by PCR, including Syngap1 and Cntnap2. Our analyses revealed that more than 70% (72/100) of the examined ASD-related genes have one or more expressed antisense transcripts, suggesting more ASD-related genes than previously thought could be subject to NAT-mediated regulation in mice. We found that expression levels of antisense contigs were mostly positively correlated with their cognate coding sense strand RNA transcripts across developmental age. A small fraction of the examined transcripts showed brain region specific enrichment, indicating possible circuit-specific roles. Our BLAST analyses identified 110 of 271 ASD-related de novo transcripts with >90% identity to the human genome at >90% coverage. These findings, which include an assembled de novo antisense transcriptome, contribute to the understanding of NAT regulation of ASD-related genes in mice and can guide NAT-mediated gene regulation strategies in preclinical investigations toward the ultimate goal of developing novel therapeutic targets for ASD.

Molecular and Functional Characterization of an Anti-lipopolysaccharide Factor Mm-ALF from Speckled Shrimp Metapenaeus monoceros

Anti-lipopolysaccharide factors (ALFs) are antimicrobial peptides of approximately 100 amino acid residues with a broad spectrum of antimicrobial activity. It is an amphipathic peptide with an N-terminal hydrophobic region and a lipopolysaccharide binding domain (LBD). In the present study, we report an isoform of the anti-lipopolysaccharide factor (Mm-ALF) from the speckled shrimp, Metapenaeus monoceros. A 359 bp cDNA encoded 119 amino acids, and the sequence showed 99.16% similarity to ALF from the shrimp Fenneropenaeus indicus. The mature peptide of 94 amino acids has a net charge of +8, molecular weight 10.62 kDa, and pI 10.11. The mature peptide Mm-ALF was recombinantly expressed in E. coli Rosetta-gami cells, and the peptide was isolated and purified. The rMm-ALF exhibited notable antibacterial activity against Gram-positive (Staphylococcus aureus and Bacillus cereus) and Gram-negative (Escherichia coli, Edwardsiella tarda, Aeromonas hydrophila, Pseudomonas aeruginosa, Vibrio parahaemolyticus, Vibrio harveyi, Vibrio alginolyticus, Vibrio proteolyticus, Vibrio cholerae and Vibrio fluvialis) bacteria.

Structural and Functional Characteristics of miRNAs in Five Strategic Millet Species and Their Utility in Drought Tolerance

Millets are the strategic food crops in arid and drought-prone ecologies. Millets, by virtue of nature, are very well-adapted to drought conditions and able to produce sustainable yield. Millets have important nutrients that can help prevent micro-nutrient malnutrition. As a result of the adverse effect of climate change and widespread malnutrition, millets have attained a strategic position to sustain food and nutritional security. Although millets can adapt well to the drought ecologies where other cereals fail completely, the yield level is very low under stress. There is a tremendous opportunity to increase the genetic potential of millet crops in dry lands when the genetics of the drought-tolerance mechanism is fully explained. MicroRNAs (miRNAs) are the class of small RNAs that control trait expression. They are part of the gene regulation but little studied in millets. In the present study, novel miRNAs and gene targets were identified from the genomic resources of pearl millet, sorghum, foxtail millet, finger millet, and proso millet through in silico approaches. A total of 1,002 miRNAs from 280 families regulating 23,158 targets were identified using different filtration criteria in five millet species. The unique as well as conserved structural features and functional characteristics of miRNA across millets were explained. About 84 miRNAs were conserved across millets in different species combinations, which explained the evolutionary relationship of the millets. Further, 215 miRNAs controlling 155 unique major drought-responsive genes, transcription factors, and protein families revealed the genetics of drought tolerance that are accumulated in the millet genomes. The miRNAs regulating the drought stress through specific targets or multiple targets showed through a network analysis. The identified genes regulated by miRNA genes could be useful in developing functional markers and used for yield improvement under drought in millets as well as in other crops.

A Comprehensive Analysis of cis-Acting RNA Elements in the SARS-CoV-2 Genome by a Bioinformatics Approach

The emergence of a new coronavirus (CoV), severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), responsible for severe respiratory disease in humans termed coronavirus disease of 2019 (COVID-19), became a new global threat for health and the economy. The SARS-CoV-2 genome is about a 29,800-nucleotide-long plus-strand RNA that can form functionally important secondary and higher-order structures called cis-acting RNA elements. These elements can interact with viral proteins, host proteins, or other RNAs and be involved in regulating translation and replication processes of the viral genome and encapsidation of the virus. However, the cis-acting RNA elements and their biological roles in SARS-CoV-2 as well as their comparative analysis in the closely related viral genome have not been well explored, which is very important to understand the molecular mechanism of viral infection and pathogenies. In this study, we used a bioinformatics approach to identify the cis-acting RNA elements in the SARS-CoV-2 genome. Initially, we aligned the full genomic sequence of six different CoVs, and a phylogenetic analysis was performed to understand their evolutionary relationship. Next, we predicted the cis-acting RNA elements in the SARS-CoV-2 genome using the structRNAfinder tool. Then, we annotated the location of these cis-acting RNA elements in different genomic regions of SARS-CoV-2. After that, we analyzed the sequence conservation patterns of each cis-acting RNA element among the six CoVs. Finally, the presence of cis-acting RNA elements across different CoV genomes and their comparative analysis was performed. Our study identified 12 important cis-acting RNA elements in the SARS-CoV-2 genome; among them, Corona_FSE, Corona_pk3, and s2m are highly conserved across most of the studied CoVs, and Thr_leader, MAT2A_D, and MS2 are uniquely present in SARS-CoV-2. These RNA structure elements can be involved in viral translation, replication, and encapsidation and, therefore, can be potential targets for better treatment of COVID-19. It is imperative to further characterize these cis-acting RNA elements experimentally for a better mechanistic understanding of SARS-CoV-2 infection and therapeutic intervention.

Structural modularity of the XIST ribonucleoprotein complex

Long noncoding RNAs are thought to regulate gene expression by organizing protein complexes through unclear mechanisms. XIST controls the inactivation of an entire X chromosome in female placental mammals. Here we develop and integrate several orthogonal structure-interaction methods to demonstrate that XIST RNA-protein complex folds into an evolutionarily conserved modular architecture. Chimeric RNAs and clustered protein binding in fRIP and eCLIP experiments align with long-range RNA secondary structure, revealing discrete XIST domains that interact with distinct sets of effector proteins. CRISPR-Cas9-mediated permutation of the Xist A-repeat location shows that A-repeat serves as a nucleation center for multiple Xist-associated proteins and m6A modification. Thus modular architecture plays an essential role, in addition to sequence motifs, in determining the specificity of RBP binding and m6A modification. Together, this work builds a comprehensive structure-function model for the XIST RNA-protein complex, and suggests a general strategy for mechanistic studies of large ribonucleoprotein assemblies.

Hierarchical natural move Monte Carlo refines flexible RNA structures into cryo-EM densities

Ribonucleic acids (RNAs) play essential roles in living cells. Many of them fold into defined three-dimensional (3D) structures to perform functions. Recent advances in single-particle cryo-electron microscopy (cryo-EM) have enabled structure determinations of RNA to atomic resolutions. However, most RNA molecules are structurally flexible, limiting the resolution of their structures solved by cryo-EM. In modeling these molecules, several computational methods are limited by the requirement of massive computational resources and/or the low efficiency in exploring large-scale structural variations. Here we use hierarchical natural move Monte Carlo (HNMMC), which takes advantage of collective motions for groups of nucleic acid residues, to refine RNA structures into their cryo-EM maps, preserving atomic details in the models. After validating the method on a simulated density map of tRNA, we applied it to objectively obtain the model of the folding intermediate for the specificity domain of ribonuclease P from Bacillus subtilis and refine a flexible ribosomal RNA (rRNA) expansion segment from the Mycobacterium tuberculosis (Mtb) ribosome in different conformational states. Finally, we used HNMMC to model atomic details and flexibility for two distinct conformations of the complete genomic RNA (gRNA) inside MS2, a single-stranded RNA virus, revealing multiple pathways for its capsid assembly.

Lead-seq: transcriptome-wide structure probing in vivo using lead(II) ions

The dynamic conformation of RNA molecules within living cells is key to their function. Recent advances in probing the RNA structurome in vivo, including the use of SHAPE (Selective 2'-Hydroxyl Acylation analyzed by Primer Extension) or kethoxal reagents or DMS (dimethyl sulfate), provided unprecedented insights into the architecture of RNA molecules in the living cell. Here, we report the establishment of lead probing in a global RNA structuromics approach. In order to elucidate the transcriptome-wide RNA landscape in the enteric pathogen Yersinia pseudotuberculosis, we combined lead(II) acetate-mediated cleavage of single-stranded RNA regions with high-throughput sequencing. This new approach, termed 'Lead-seq', provides structural information independent of base identity. We show that the method recapitulates secondary structures of tRNAs, RNase P RNA, tmRNA, 16S rRNA and the rpsT 5'-untranslated region, and that it reveals global structural features of mRNAs. The application of Lead-seq to Y. pseudotuberculosis cells grown at two different temperatures unveiled the first temperature-responsive in vivo RNA structurome of a bacterial pathogen. The translation of candidate genes derived from this approach was confirmed to be temperature regulated. Overall, this study establishes Lead-seq as complementary approach to interrogate intracellular RNA structures on a global scale.

Non-coding RNAs in cancer: platforms and strategies for investigating the genomic "dark matter"

The discovery of the role of non-coding RNAs (ncRNAs) in the onset and progression of malignancies is a promising frontier of cancer genetics. It is clear that ncRNAs are candidates for therapeutic intervention, since they may act as biomarkers or key regulators of cancer gene network. Recently, profiling and sequencing of ncRNAs disclosed deep deregulation in human cancers mostly due to aberrant mechanisms of ncRNAs biogenesis, such as amplification, deletion, abnormal epigenetic or transcriptional regulation. Although dysregulated ncRNAs may promote hallmarks of cancer as oncogenes or antagonize them as tumor suppressors, the mechanisms behind these events remain to be clarified. The development of new bioinformatic tools as well as novel molecular technologies is a challenging opportunity to disclose the role of the "dark matter" of the genome. In this review, we focus on currently available platforms, computational analyses and experimental strategies to investigate ncRNAs in cancer. We highlight the differences among experimental approaches aimed to dissect miRNAs and lncRNAs, which are the most studied ncRNAs. These two classes indeed need different investigation taking into account their intrinsic characteristics, such as length, structures and also the interacting molecules. Finally, we discuss the relevance of ncRNAs in clinical practice by considering promises and challenges behind the bench to bedside translation.

A report on DNA sequence determinants in gene expression

The biased usage of nucleotides in coding sequence and its correlation with gene expression has been observed in several studies. A complex set of interactions between genes and other components of the expression system determine the amount of proteins produced from coding sequences. It is known that the elongation rate of polypeptide chain is affected by both codon usage bias and specific amino acid compositional constraints. Therefore, it is of interest to review local DNA-sequence elements and other positional as well as combinatorial constraints that play significant role in gene expression.

Antisense regulation of atrial natriuretic peptide expression

The cardiac hormone atrial natriuretic peptide (ANP) is a central regulator of blood volume and a therapeutic target in hypertension and heart failure. Enhanced ANP activity in such conditions through inhibition of the degradative enzyme neprilysin has shown clinical efficacy but is complicated by consequences of simultaneous accumulation of a heterogeneous array of other hormones. Targets for specific ANP enhancement have not been available. Here, we describe a cis-acting antisense transcript (NPPA-AS1), which negatively regulates ANP expression in human cardiomyocytes. We show that NPPA-AS1 regulates ANP expression via facilitating NPPA repressor RE1-silencing transcription factor (REST) binding to its promoter, rather than forming an RNA duplex with ANP mRNA. Expression of ANP mRNA and NPPA-AS1 was increased and correlated in isolated strained human cardiomyocytes and in hearts from patients with advanced heart failure. Further, inhibition of NPPA-AS1 in vitro and in vivo resulted in increased myocardial expression of ANP, increased circulating ANP, increased renal cGMP, and lower blood pressure. The effects of NPPA-AS1 inhibition on NPPA expression in human cardiomyocytes were further marked under cell-strain conditions. Collectively, these results implicate the antisense transcript NPPA-AS1 as part of a physiologic self-regulatory ANP circuit and a viable target for specific ANP augmentation.

Invited Review: Long non-coding RNAs: important regulators in the development, function and disorders of the central nervous system

Genome-wide transcriptional studies have demonstrated that tens of thousands of long non-coding RNAs (lncRNA) genes are expressed in the central nervous system (CNS) and that they exhibit tissue- and cell-type specificity. Their regulated and dynamic expression and their co-expression with protein-coding gene neighbours have led to the study of the functions of lncRNAs in CNS development and disorders. In this review, we describe the general characteristics, localization and classification of lncRNAs. We also elucidate the examples of the molecular mechanisms of nuclear and cytoplasmic lncRNA actions in the CNS and discuss common experimental approaches used to identify and unveil the functions of lncRNAs. Additionally, we provide examples of lncRNA studies of cell differentiation and CNS disorders including CNS injuries and neurodegenerative diseases. Finally, we review novel lncRNA-based therapies. Overall, this review highlights the important biological roles of lncRNAs in CNS functions and disorders.

The RNA encoding the microtubule-associated protein tau has extensive structure that affects its biology

Tauopathies are neurodegenerative diseases that affect millions of people worldwide including those with Alzheimer’s disease. While many efforts have focused on understanding the role of tau protein in neurodegeneration, there has been little done to systematically analyze and study the structures within tau’s encoding RNA and their connection to disease pathology. Knowledge of RNA structure can provide insights into disease mechanisms and how to affect protein production for therapeutic benefit. Using computational methods based on thermodynamic stability and evolutionary conservation, we identified structures throughout the tau pre-mRNA, especially at exon-intron junctions and within the 5′ and 3′ untranslated regions (UTRs). In particular, structures were identified at twenty exon-intron junctions. The 5′ UTR contains one structured region, which lies within a known internal ribosome entry site. The 3′ UTR contains eight structured regions, including one that contains a polyadenylation signal. A series of functional experiments were carried out to assess the effects of mutations associated with mis-regulation of alternative splicing of exon 10 and to identify regions of the 3′ UTR that contain cis-regulatory elements. These studies defined novel structural regions within the mRNA that affect stability and pre-mRNA splicing and may lead to new therapeutic targets for treating tau-associated diseases.

Computational approaches for the discovery of splicing regulatory RNA structures

Global RNA structure and local functional motifs mediate interactions important in determining the rates and patterns of mRNA splicing. In this review, we overview approaches for the computational prediction of RNA secondary structure with a special emphasis on the discovery of motifs important to RNA splicing. The process of identifying and modeling potential splicing regulatory structures is illustrated using a recently-developed approach for RNA structural motif discovery, the ScanFold pipeline, which is applied to the identification of a known splicing regulatory structure in influenza virus.

OSTRFPD: Multifunctional Tool for Genome-Wide Short Tandem Repeat Analysis for DNA, Transcripts, and Amino Acid Sequences with Integrated Primer Designer

Microsatellite mining is a common outcome of the in silico approach to genomic studies. The resulting short tandemly repeated DNA could be used as molecular markers for studying polymorphism, genotyping and forensics. The omni short tandem repeat finder and primer designer (OSTRFPD) is among the few versatile, platform-independent open-source tools written in Python that enables researchers to identify and analyse genome-wide short tandem repeats in both nucleic acids and protein sequences. OSTRFPD is designed to run either in a user-friendly fully featured graphical interface or in a command line interface mode for advanced users. OSTRFPD can detect both perfect and imperfect repeats of low complexity with customisable scores. Moreover, the software has built-in architecture to simultaneously filter selection of flanking regions in DNA and generate microsatellite-targeted primers implementing the Primer3 platform. The software has built-in motif-sequence generator engines and an additional option to use the dictionary mode for custom motif searches. The software generates search results including general statistics containing motif categorisation, repeat frequencies, densities, coverage, guanine–cytosine (GC) content, and simple text-based imperfect alignment visualisation. Thus, OSTRFPD presents users with a quick single-step solution package to assist development of microsatellite markers and categorise tandemly repeated amino acids in proteome databases. Practical implementation of OSTRFPD was demonstrated using publicly available whole-genome sequences of selected Plasmodium species. OSTRFPD is freely available and open-sourced for improvement and user-specific adaptation.

How to benchmark RNA secondary structure prediction accuracy

RNA secondary structure prediction is widely used. As new methods are developed, these are often benchmarked for accuracy against existing methods. This review discusses good practices for performing these benchmarks, including the choice of benchmarking structures, metrics to quantify accuracy, the importance of allowing flexibility for pairs in the accepted structure, and the importance of statistical testing for significance.

Sequence- And Structure-Specific Probing of RNAs by Short Nucleobase-Modified dsRNA-Binding PNAs Incorporating a Fluorescent Light-up Uracil Analog

RNAs are emerging as important biomarkers and therapeutic targets. The strategy of directly targeting double-stranded RNA (dsRNA) by triplex-formation is relatively underexplored mainly due to the weak binding at physiological conditions for the traditional triplex-forming oligonucleotides (TFOs). Compared to DNA and RNA, peptide nucleic acids (PNAs) are chemically stable and have a neutral peptide-like backbone, and thus, they show significantly enhanced binding to natural nucleic acids. We have successfully developed nucleobase-modified dsRNA-binding PNAs (dbPNAs) to facilitate structure-specific and selective recognition of dsRNA over single-stranded RNA (ssRNA) and dsDNA regions at near-physiological conditions. The triplex formation strategy facilitates the targeting of not only the sequence but also the secondary structure of RNA. Here, we report the development of novel dbPNA-based fluorescent light-up probes through the incorporation of A-U pair-recognizing 5-benzothiophene uracil (^btU). The incorporation of ^btU into dbPNAs does not affect the binding affinity toward dsRNAs significantly, in most cases, as evidenced by our nondenaturing gel shift assay data. The blue fluorescence emission intensity of ^btU-modified dbPNAs is sequence- and structure-specifically enhanced by dsRNAs, including the influenza viral RNA panhandle duplex and HIV-1-1 ribosomal frameshift-inducing RNA hairpin, but not ssRNAs or DNAs, at 200 mM NaCl, pH 7.5. Thus, dbPNAs incorporating ^btU-modified and other further modified fluorescent nucleobases will be useful biochemical tools for probing and detecting RNA structures, interactions, and functions.

A Short Chemically Modified dsRNA-Binding PNA (dbPNA) Inhibits Influenza Viral Replication by Targeting Viral RNA Panhandle Structure

RNAs play critical roles in diverse catalytic and regulatory biological processes and are emerging as important disease biomarkers and therapeutic targets. Thus, developing chemical compounds for targeting any desired RNA structures has great potential in biomedical applications. The viral and cellular RNA sequence and structure databases lay the groundwork for developing RNA-binding chemical ligands through the recognition of both RNA sequence and RNA structure. Influenza A virion consists of eight segments of negative-strand viral RNA (vRNA), all of which contain a highly conserved panhandle duplex structure formed between the first 13 nucleotides at the 5' end and the last 12 nucleotides at the 3' end. Here, we report our binding and cell culture anti-influenza assays of a short 10-mer chemically modified double-stranded RNA (dsRNA)-binding peptide nucleic acid (PNA) designed to bind to the panhandle duplex structure through novel major-groove PNA·RNA₂ triplex formation. We demonstrated that incorporation of chemically modified PNA residues thio-pseudoisocytosine (L) and guanidine-modified 5-methyl cytosine (Q) previously developed by us facilitates the sequence-specific recognition of Watson-Crick G-C and C-G pairs, respectively, at physiologically relevant conditions. Significantly, the chemically modified dsRNA-binding PNA (dbPNA) shows selective binding to the dsRNA region in panhandle structure over a single-stranded RNA (ssRNA) and a dsDNA containing the same sequence. The panhandle structure is not accessible to traditional antisense DNA or RNA with a similar length. Conjugation of the dbPNA with an aminosugar neamine enhances the cellular uptake. We observed that 2-5 μM dbPNA-neamine conjugate results in a significant reduction of viral replication. In addition, the 10-mer dbPNA inhibits innate immune receptor RIG-I binding to panhandle structure and thus RIG-I ATPase activity. These findings would provide the foundation for developing novel dbPNAs for the detection of influenza viral RNAs and therapeutics with optimal antiviral and immunomodulatory activities.

Structural Differences between Pri-miRNA Paralogs Promote Alternative Drosha Cleavage and Expand Target Repertoires

MicroRNA (miRNA) processing begins with Drosha cleavage, the fidelity of which is critical for downstream processing and mature miRNA target specificity. To understand how pri-miRNA sequence and structure influence Drosha cleavage, we studied the maturation of three pri-miR-9 paralogs, which encode the same mature miRNA but differ in the surrounding scaffold. We show that pri-miR-9-1 has a unique Drosha cleavage profile due to its distorted and flexible stem structure. Cleavage of pri-miR-9-1, but not pri-miR-9-2 or pri-miR-9-3, generates an alternative miR-9 with a shifted seed sequence that expands the scope of its target RNAs. Analyses of low-grade glioma patient samples indicate that the alternative-miR-9 has a potential role in tumor progression. Furthermore, we provide evidence that distortion of pri-miRNA stems induced by asymmetric internal loops correlates with Drosha cleavage at non-canonical sites. Our studies reveal that pri-miRNA paralogs can have distinct functions via differential Drosha processing.

ScanFold: an approach for genome-wide discovery of local RNA structural elements-applications to Zika virus and HIV

In addition to encoding RNA primary structures, genomes also encode RNA secondary and tertiary structures that play roles in gene regulation and, in the case of RNA viruses, genome replication. Methods for the identification of functional RNA structures in genomes typically rely on scanning analysis windows, where multiple partially-overlapping windows are used to predict RNA structures and folding metrics to deduce regions likely to form functional structure. Separate structural models are produced for each window, where the step size can greatly affect the returned model. This makes deducing unique local structures challenging, as the same nucleotides in each window can be alternatively base paired. We are presenting here a new approach where all base pairs from analysis windows are considered and weighted by favorable folding. This results in unique base pairing throughout the genome and the generation of local regions/structures that can be ranked by their propensity to form unusually thermodynamically stable folds. We applied this approach to the Zika virus (ZIKV) and HIV-1 genomes. ZIKV is linked to a variety of neurological ailments including microcephaly and Guillain-Barré syndrome and its (+)-sense RNA genome encodes two, previously described, functionally essential structured RNA regions. HIV, the cause of AIDS, contains multiple functional RNA motifs in its genome, which have been extensively studied. Our approach is able to successfully identify and model the structures of known functional motifs in both viruses, while also finding additional regions likely to form functional structures. All data have been archived at the RNAStructuromeDB (www.structurome.bb.iastate.edu), a repository of RNA folding data for humans and their pathogens.

The RNA Base-Pairing Problem and Base-Pairing Solutions

RNA molecules are folded into structures and complexes to perform a wide variety of functions. Determination of RNA structures and their interactions is a fundamental problem in RNA biology. Most RNA molecules in living cells are large and dynamic, posing unique challenges to structure analysis. Here we review progress in RNA structure analysis, focusing on methods that use the "cross-link, proximally ligate, and sequence" principle for high-throughput detection of base-pairing interactions in living cells. Beginning with a comparison of commonly used methods in structure determination and a brief historical account of psoralen cross-linking studies, we highlight the important features of cross-linking methods and new biological insights into RNA structures and interactions from recent studies. Further improvement of these cross-linking methods and application to previously intractable problems will shed new light on the mechanisms of the "modern RNA world."

Evolutionary Divergence of Brain-specific Precursor miRNAs Drives Efficient Processing and Production of Mature miRNAs in Human

The hallmark of human evolution encompasses the dramatic increase in brain size and complexity. The intricate interplays of micro-RNAs (miRNAs) and their target genes are indispensable in brain development. Sequence divergence in distinct structural regions of Brain-specific precursor miRNAs (pre-miRNAs) and its consequence in the production of corresponding mature miRNAs in human are unknown. To address these questions, first we classified miRNAs into three categories based on tissue expression: Brain-specific (expressed exclusively in brain), Non-brain (expressed in Non-brain tissues) and Common (expressed in all tissues) and compared the sequence divergence of different structural regions (basal segment, lower and upper stem, internal and terminal loop) of categorized pre-miRNAs across human, non-human primates and rodents. Our analysis revealed that unpaired regions of Brain-specific pre-miRNAs in human bear traces of relatively high rate of evolutionary divergence compared to those in other species. Cross-tissue expression analysis unveiled the higher expression of the Brain-specific miRNAs in human compared to other species. Intriguingly, in human brain, expression levels of these miRNAs superseded the levels of the ubiquitously expressed "Common-miRNAs". Further analysis revealed that presence of certain motif and nucleotide preference in the Brain-specific pre-miRNAs may favor DROSHA and DICER to ameliorate miRNA processing. The higher processing efficiency of human Brain-specific miRNAs was reflected as an elevated production of corresponding mature miRNAs in the human brain. Finally, re-construction of gene-regulatory network uncovers different pathways driven by Brain-specific miRNAs that may contribute to the development of brain in human.

Incorporating uracil and 5-halouracils into short peptide nucleic acids for enhanced recognition of A-U pairs in dsRNAs

Double-stranded RNA (dsRNA) structures form triplexes and RNA-protein complexes through binding to single-stranded RNA (ssRNA) regions and proteins, respectively, for diverse biological functions. Hence, targeting dsRNAs through major-groove triplex formation is a promising strategy for the development of chemical probes and potential therapeutics. Short (e.g., 6-10 mer) chemically-modified Peptide Nucleic Acids (PNAs) have been developed that bind to dsRNAs sequence specifically at physiological conditions. For example, a PNA incorporating a modified base thio-pseudoisocytosine (L) has an enhanced recognition of a G-C pair in an RNA duplex through major-groove L·G-C base triple formation at physiological pH, with reduced pH dependence as observed for C+·G-C base triple formation. Currently, an unmodified T base is often incorporated into PNAs to recognize a Watson-Crick A-U pair through major-groove T·A-U base triple formation. A substitution of the 5-methyl group in T by hydrogen and halogen atoms (F, Cl, Br, and I) causes a decrease of the pKa of N3 nitrogen atom, which may result in improved hydrogen bonding in addition to enhanced base stacking interactions. Here, we synthesized a series of PNAs incorporating uracil and halouracils, followed by binding studies by non-denaturing polyacrylamide gel electrophoresis, circular dichroism, and thermal melting. Our results suggest that replacing T with uracil and halouracils may enhance the recognition of an A-U pair by PNA·RNA2 triplex formation in a sequence-dependent manner, underscoring the importance of local stacking interactions. Incorporating bromouracils and chlorouracils into a PNA results in a significantly reduced pH dependence of triplex formation even for PNAs containing C bases, likely due to an upshift of the apparent pKa of N3 atoms of C bases. Thus, halogenation and other chemical modifications may be utilized to enhance hydrogen bonding of the adjacent base triples and thus triplex formation. Furthermore, our experimental and computational modelling data suggest that PNA·RNA2 triplexes may be stabilized by incorporating a BrUL step but not an LBrU step, in dsRNA-binding PNAs.

The ensemble diversity of non-coding RNA structure is lower than random sequence

In addition to energetically optimal structures, RNAs can fold into near energy suboptimal conformations that may be populated and play functional roles. The diversity of this structural ensemble can be estimated using a metric derived from the calculated RNA partition function: the ensemble diversity. In this report, 10 classes of functional RNAs were analyzed: the 5.8S and 5S rRNAs, ribozyme, RNase P, snoRNA, snRNA, SRP RNA, tmRNA, Vault RNA and Y RNA. Representative sequences from each class were mutagenized in two ways: firstly, all possible point mutations were generated and secondly, wild type sequences were randomized to generate multiple scrambled mutants. Compared to the mutants, the native RNA ensemble diversity was predicted to be lower. This finding held true when all available sequences (378,455 sequences) for each RNA class (archived in the RNAcentral database) were analyzed. This suggests that a compact structural ensemble is an evolved characteristic of functional RNAs.