Molecular biology: A second layer of information in RNA

Prokaryotic ncRNAs: Master regulators of gene expression

ncRNA plays a very pivotal role in various biological activities ranging from gene regulation to controlling important developmental networks. It is imperative to note that this small molecule is not only present in all three domains of cellular life, but is an important modulator of gene regulation too in all these domains. In this review, we discussed various aspects of ncRNA biology, especially their role in bacteria. The last two decades of scientific research have proved that this molecule plays an important role in the modulation of various regulatory pathways in bacteria including the adaptive immune system and gene regulation. It is also very surprising to note that this small molecule is also employed in various processes related to the pathogenicity of virulent microorganisms.

Expansion of the RNAStructuromeDB to include secondary structural data spanning the human protein-coding transcriptome

RNA plays vital functional roles in almost every component of biology, and these functional roles are often influenced by its folding into secondary and tertiary structures. An important role of RNA secondary structure is in maintaining proper gene regulation; therefore, making accurate predictions of the structures involved in these processes is important. In this study, we have expanded on our previous work that led to the creation of the RNAStructuromeDB. Unlike this previous study that analyzed the human genome at low resolution, we have now scanned the protein-coding human transcriptome at high (single nt) resolution. This provides more robust structure predictions for over 100,000 isoforms of known protein-coding genes. Notably, we also utilize the motif identification tool, ScanFold, to model structures with high propensity for ordered/evolved stability. All data have been uploaded to the RNAStructuromeDB, allowing for easy searching of transcripts, visualization of data tracks (via the Integrative Genomics Viewer or IGV), and download of ScanFold data—including unique highly-ordered motifs. Herein, we provide an example analysis of MAT2A to demonstrate the utility of ScanFold at finding known and novel secondary structures, highlighting regions of potential functionality, and guiding generation of functional hypotheses through use of the data.

G-Quadruplexes in RNA Biology: Recent Advances and Future Directions

RNA G-quadruplexes (RG4s) are four-stranded structures known to control gene expression mechanisms, from transcription to protein synthesis, and DNA-related processes. Their potential impact on RNA biology allows these structures to shape cellular processes relevant to disease development, making their targeting for therapeutic purposes an attractive option. We review here the current knowledge on RG4s, focusing on the latest breakthroughs supporting the notion of transient structures that fluctuate dynamically in cellulo, their interplay with RNA modifications, their role in cell compartmentalization, and their deregulation impacting the host immune response. We emphasize RG4-binding proteins as determinants of their transient conformation and effectors of their biological functions.

Does mRNA structure contain genetic information for regulating co-translational protein folding?

Currently many facets of genetic information are illdefined. In particular, how protein folding is genetically regulated has been a long-standing issue for genetics and protein biology. And a generic mechanistic model with supports of genomic data is still lacking. Recent technological advances have enabled much needed genome-wide experiments. While putting the effect of codon optimality on debate, these studies have supplied mounting evidence suggesting a role of mRNA structure in the regulation of protein folding by modulating translational elongation rate. In conjunctions with previous theories, this mechanistic model of protein folding guided by mRNA structure shall expand our understandings of genetic information and offer new insights into various biomedical puzzles.

Role of mRNA structure in the control of protein folding

Specific structures in mRNA modulate translation rate and thus can affect protein folding. Using the protein structures from two eukaryotes and three prokaryotes, we explore the connections between the protein compactness, inferred from solvent accessibility, and mRNA structure, inferred from mRNA folding energy (ΔG). In both prokaryotes and eukaryotes, the ΔG value of the most stable 30 nucleotide segment of the mRNA (ΔGmin) strongly, positively correlates with protein solvent accessibility. Thus, mRNAs containing exceptionally stable secondary structure elements typically encode compact proteins. The correlations between ΔG and protein compactness are much more pronounced in predicted ordered parts of proteins compared to the predicted disordered parts, indicative of an important role of mRNA secondary structure elements in the control of protein folding. Additionally, ΔG correlates with the mRNA length and the evolutionary rate of synonymous positions. The correlations are partially independent and were used to construct multiple regression models which explain about half of the variance of protein solvent accessibility. These findings suggest a model in which the mRNA structure, particularly exceptionally stable RNA structural elements, act as gauges of protein co-translational folding by reducing ribosome speed when the nascent peptide needs time to form and optimize the core structure.

Recruitment, Duplex Unwinding and Protein-Mediated Inhibition of the Dead-Box RNA Helicase Dbp2 at Actively Transcribed Chromatin

RNA helicases play fundamental roles in modulating RNA structures and facilitating RNA-protein (RNP) complex assembly in vivo. Previously, our laboratory demonstrated that the DEAD-box RNA helicase Dbp2 in Saccharomyces cerevisiae is required to promote efficient assembly of the co-transcriptionally associated mRNA-binding proteins Yra1, Nab2, and Mex67 onto poly(A)(+)RNA. We also found that Yra1 associates directly with Dbp2 and functions as an inhibitor of Dbp2-dependent duplex unwinding, suggestive of a cycle of unwinding and inhibition by Dbp2. To test this, we undertook a series of experiments to shed light on the order of events for Dbp2 in co-transcriptional mRNP assembly. We now show that Dbp2 is recruited to chromatin via RNA and forms a large, RNA-dependent complex with Yra1 and Mex67. Moreover, single-molecule fluorescence resonance energy transfer and bulk biochemical assays show that Yra1 inhibits unwinding in a concentration-dependent manner by preventing the association of Dbp2 with single-stranded RNA. This inhibition prevents over-accumulation of Dbp2 on mRNA and stabilization of a subset of RNA polymerase II transcripts. We propose a model whereby Yra1 terminates a cycle of mRNP assembly by Dbp2.

Protein synthesis as an integral quality control mechanism during ageing

Ageing is manifested as functional and structural deterioration that affects cell and tissue physiology. mRNA translation is a central cellular process, supplying cells with newly synthesized proteins. Accumulating evidence suggests that alterations in protein synthesis are not merely a corollary but rather a critical factor for the progression of ageing. Here, we survey protein synthesis regulatory mechanisms and focus on the pre-translational regulation of the process exerted by non-coding RNA species, RNA binding proteins and alterations of intrinsic RNA properties. In addition, we discuss the tight relationship between mRNA translation and two central pathways that modulate ageing, namely the insulin/IGF-1 and TOR signalling cascades. A thorough understanding of the complex interplay between protein synthesis regulation and ageing will provide critical insights into the pathogenesis of age-related disorders, associated with impaired proteostasis and protein quality control.

The potential of the riboSNitch in personalized medicine

RNA conformation plays a significant role in stability, ligand binding, transcription, and translation. Single nucleotide variants (SNVs) have the potential to disrupt specific structural elements because RNA folds in a sequence-specific manner. A riboSNitch is an element of RNA structure with a specific function that is disrupted by an SNV or a single nucleotide polymorphism (SNP; or polymorphism; SNVs occur with low frequency in the population, <1%). The riboSNitch is analogous to a riboswitch, where binding of a small molecule rather than mutation alters the structure of the RNA to control gene regulation. RiboSNitches are particularly relevant to interpreting the results of genome-wide association studies (GWAS). Often GWAS identify SNPs associated with a phenotype mapping to noncoding regions of the genome. Because a majority of the human genome is transcribed, significant subsets of GWAS SNPs are putative riboSNitches. The extent to which the transcriptome is tolerant of SNP-induced structure change is still poorly understood. Recent advances in ultra high-throughput structure probing begin to reveal the structural complexities of mutation-induced structure change. This review summarizes our current understanding of SNV and SNP-induced structure change in the human transcriptome and discusses the importance of riboSNitch discovery in interpreting GWAS results and massive sequencing projects.

Detecting riboSNitches with RNA folding algorithms: a genome-wide benchmark

Ribonucleic acid (RNA) secondary structure prediction continues to be a significant challenge, in particular when attempting to model sequences with less rigidly defined structures, such as messenger and non-coding RNAs. Crucial to interpreting RNA structures as they pertain to individual phenotypes is the ability to detect RNAs with large structural disparities caused by a single nucleotide variant (SNV) or riboSNitches. A recently published human genome-wide parallel analysis of RNA structure (PARS) study identified a large number of riboSNitches as well as non-riboSNitches, providing an unprecedented set of RNA sequences against which to benchmark structure prediction algorithms. Here we evaluate 11 different RNA folding algorithms’ riboSNitch prediction performance on these data. We find that recent algorithms designed specifically to predict the effects of SNVs on RNA structure, in particular remuRNA, RNAsnp and SNPfold, perform best on the most rigorously validated subsets of the benchmark data. In addition, our benchmark indicates that general structure prediction algorithms (e.g. RNAfold and RNAstructure) have overall better performance if base pairing probabilities are considered rather than minimum free energy calculations. Although overall aggregate algorithmic performance on the full set of riboSNitches is relatively low, significant improvement is possible if the highest confidence predictions are evaluated independently.