Ten lessons with Carl Woese about RNA and comparative analysis

RNAhub-an automated pipeline to search and align RNA homologs with secondary structure assessment

The complexity in the generation of RNA multiple sequence alignments and assessment of the accuracy of such alignments contributes to the challenges in the utilization of RNA MSAs in diverse integrative methods. RNAhub is a freely available user-friendly web server for a reliable generation of RNA multiple sequence alignents and the detection of the presence of structural RNA utilizing evolutionary information. This web-based tool, developed by the integration of existing computational approaches, takes an RNA sequence as input and automatically retrieves and aligns sequences homologous to the input (query) RNA sequence through an iterative and structure-agnostic approach. Based on the alignment, this tool statistically assesses whether the query RNA sequence has a conserved RNA structure using covariation analysis. The web server allows the user to efficiently search the sequence of interest against carefully curated, ready-to-use genomic databases to produce an MSA. Using this alignment, our tool either detects the presence of a conserved structural RNA, finds evidence against the presence of a conserved structure, or cannot make any assessment due to a lack of sequence diversity in the alignment. The web server is freely available at https://rnahub.org.

RNAhub - an automated pipeline to search and align RNA homologs with secondary structure assessment

The complexity in the generation of RNA multiple sequence alignments and assessment of the accuracy of such alignments contributes to the challenges in the utilization of RNA alignments in diverse integrative methods. RNAhub is a freely available user-friendly web server for a reliable generation of RNA multiple sequence alignments and the detection of the presence of structural RNA utilizing evolutionary information. This web-based tool, developed by the integration of existing computational approaches, takes an RNA sequence as input and automatically retrieves and aligns sequences homologous to the input (query) RNA sequence through an iterative and structure-agnostic approach. Based on the alignment, this tool statistically assesses whether the query RNA sequence has a conserved RNA structure using covariation analysis. The web server allows the user to efficiently search the sequence of interest against carefully curated, ready-to-use genomic databases to produce a multiple sequence alignment. Using this alignment, our tool either detects the presence of a conserved structural RNA, finds evidence against the presence of a conserved structure, or cannot make any assessment due to a lack of sequence diversity in the alignment. The web server is freely available at https://rnahub.org.

Identification of leader-trailer helices of precursor ribosomal RNA in all phyla of bacteria and archaea

Ribosomal RNAs are transcribed as part of larger precursor molecules. In Escherichia coli, complementary RNA segments flank each rRNA and form long leader-trailer (LT) helices, which are crucial for subunit biogenesis in the cell. A previous study of 15 representative species suggested that most but not all prokaryotes contain LT helices. Here, we use a combination of in silico folding and covariation methods to identify and characterize LT helices in 4464 bacterial and 260 archaeal organisms. Our results suggest that LT helices are present in all phyla, including Deinococcota, which had previously been suspected to lack LT helices. In very few organisms, our pipeline failed to detect LT helices for both 16S and 23S rRNA. However, a closer case-by-case look revealed that LT helices are indeed present but escaped initial detection. Over 3600 secondary structure models, many well supported by nucleotide covariation, were generated. These structures show a high degree of diversity. Yet, all exhibit extensive base-pairing between the leader and trailer strands, in line with a common and essential function.

Apollon: a deoxyribozyme that generates a yellow product

Colorimetric assays in which the color of a solution changes in the presence of an input provide a simple and inexpensive way to monitor experimental readouts. In this study we used in vitro selection to identify a self-phosphorylating kinase deoxyribozyme that produces a colorimetric signal by converting the colorless substrate pNPP into the yellow product pNP. The minimized catalytic core, sequence requirements, secondary structure, and buffer requirements of this deoxyribozyme, which we named Apollon, were characterized using a variety of techniques including reselection experiments, high-throughput sequencing, comparative analysis, biochemical activity assays, and NMR. A bimolecular version of Apollon catalyzed multiple turnover phosphorylation and amplified the colorimetric signal. Engineered versions of Apollon could detect oligonucleotides with specific sequences as well as several different types of nucleases in homogenous assays that can be performed in a single tube without the need for washes or purifications. We anticipate that Apollon will be particularly useful to reduce costs in high-throughput screens and for applications in which specialized equipment is not available.

Aurora: a fluorescent deoxyribozyme for high-throughput screening

Fluorescence facilitates the detection, visualization, and tracking of molecules with high sensitivity and specificity. A functional DNA molecule that generates a robust fluorescent signal would offer significant advantages for many applications compared to intrinsically fluorescent proteins, which are expensive and labor intensive to synthesize, and fluorescent RNA aptamers, which are unstable under most conditions. Here, we describe a novel deoxyriboyzme that rapidly and efficiently generates a stable fluorescent product using a readily available coumarin substrate. An engineered version can detect picomolar concentrations of ribonucleases in a simple homogenous assay, and was used to rapidly identify novel inhibitors of the SARS-CoV-2 ribonuclease Nsp15 in a high-throughput screen. Our work adds an important new component to the toolkit of functional DNA parts, and also demonstrates how catalytic DNA motifs can be used to solve real-world problems.

In vivo structure probing of RNA in Archaea: novel insights into the ribosome structure of Methanosarcina acetivorans

Structure probing combined with next-generation sequencing (NGS) has provided novel insights into RNA structure-function relationships. To date, such studies have focused largely on bacteria and eukaryotes, with little attention given to the third domain of life, archaea. Furthermore, functional RNAs have not been extensively studied in archaea, leaving open questions about RNA structure and function within this domain of life. With archaeal species being diverse and having many similarities to both bacteria and eukaryotes, the archaea domain has the potential to be an evolutionary bridge. In this study, we introduce a method for probing RNA structure in vivo in the archaea domain of life. We investigated the structure of ribosomal RNA (rRNA) from Methanosarcina acetivorans, a well-studied anaerobic archaeal species, grown with either methanol or acetate. After probing the RNA in vivo with dimethyl sulfate (DMS), Structure-seq2 libraries were generated, sequenced, and analyzed. We mapped the reactivity of DMS onto the secondary structure of the ribosome, which we determined independently with comparative analysis, and confirmed the accuracy of DMS probing in M. acetivorans Accessibility of the rRNA to DMS in the two carbon sources was found to be quite similar, although some differences were found. Overall, this study establishes the Structure-seq2 pipeline in the archaea domain of life and informs about ribosomal structure within M. acetivorans.

Molecular Apomorphies in the Secondary and Tertiary Structures of Length-Variable Regions (LVRs) of 18S rRNA Shed Light on the Systematic Position of the Family Thaumastellidae (Hemiptera: Heteroptera: Pentatomoidea)

The SSU nrDNA, a small subunit of the nuclear ribosomal DNA (coding 18S rRNA), is one of the most frequently sequenced genes in molecular studies in Hexapoda. In insects, including true bugs (Hemiptera: Heteroptera), only its primary structures (i.e., aligned sequences) are predominantly used in phylogenetic reconstructions. It is known that including RNA secondary structures in the alignment procedure is essential for improving accuracy and robustness in phylogenetic tree reconstruction. Moreover, local plasticity in rRNAs might impact their tertiary structures and corresponding functions. To determine the systematic position of Thaumastellidae within the superfamily Pentatomoidea, the secondary and-for the first time among all Hexapoda-tertiary structures of 18S rRNAs in twelve pentatomoid families were compared and analysed. Results indicate that the shapes of the secondary and tertiary structures of the length-variable regions (LVRs) in the 18S rRNA are phylogenetically highly informative. Based on these results, it is suggested that the Thaumastellidae is maintained as an independent family within the superfamily Pentatomoidea, rather than as a part of the family Cydnidae. Moreover, the analyses indicate a close relationship between Sehirinae and Parastrachiidae, expressed in morpho-molecular synapomorphies in the predicted secondary and tertiary structures of the length-variable region L (LVR L).

Sequence similarity governs generalizability of de novo deep learning models for RNA secondary structure prediction

Making no use of physical laws or co-evolutionary information, de novo deep learning (DL) models for RNA secondary structure prediction have achieved far superior performances than traditional algorithms. However, their statistical underpinning raises the crucial question of generalizability. We present a quantitative study of the performance and generalizability of a series of de novo DL models, with a minimal two-module architecture and no post-processing, under varied similarities between seen and unseen sequences. Our models demonstrate excellent expressive capacities and outperform existing methods on common benchmark datasets. However, model generalizability, i.e., the performance gap between the seen and unseen sets, degrades rapidly as the sequence similarity decreases. The same trends are observed from several recent DL and machine learning models. And an inverse correlation between performance and generalizability is revealed collectively across all learning-based models with wide-ranging architectures and sizes. We further quantitate how generalizability depends on sequence and structure identity scores via pairwise alignment, providing unique quantitative insights into the limitations of statistical learning. Generalizability thus poses a major hurdle for deploying de novo DL models in practice and various pathways for future advances are discussed.

Predicting the Structure of a Viroid : Structure, Structure Distribution, Consensus Structure, and Structure Drawing

Viroids are small non-coding RNAs that require a special sequence and structure to be replicated and transported by the host machinery. Many of these features can be predicted and later experimentally verified. Here, we will present workflows to predict viroid structures and draw the predicted structures in a pleasing and descriptive way using recently developed software.

Evolutionary conservation of RNA sequence and structure

An RNA structure prediction from a single‐sequence RNA folding program is not evidence for an RNA whose structure is important for function. Random sequences have plausible and complex predicted structures not easily distinguishable from those of structural RNAs. How to tell when an RNA has a conserved structure is a question that requires looking at the evolutionary signature left by the conserved RNA. This question is important not just for long noncoding RNAs which usually lack an identified function, but also for RNA binding protein motifs which can be single stranded RNAs or structures. Here we review recent advances using sequence and structural analysis to determine when RNA structure is conserved or not. Although covariation measures assess structural RNA conservation, one must distinguish covariation due to RNA structure from covariation due to independent phylogenetic substitutions. We review a statistical test to measure false positives expected under the null hypothesis of phylogenetic covariation alone (specificity). We also review a complementary test that measures power, that is, expected covariation derived from sequence variation alone (sensitivity). Power in the absence of covariation signals the absence of a conserved RNA structure. We analyze artifacts that falsely identify conserved RNA structure such as the misuse of programs that do not assess significance, the use of inappropriate statistics confounded by signals other than covariation, or misalignments that induce spurious covariation. Among artifacts that obscure the signal of a conserved RNA structure, we discuss the inclusion of pseudogenes in alignments which increase power but destroy covariation.

This article is categorized under:

RNA Structure and Dynamics > RNA Structure, Dynamics and Chemistry

RNA Evolution and Genomics > Computational Analyses of RNA

RNA Evolution and Genomics > RNA and Ribonucleoprotein Evolution

Comparative RNA function analysis reveals high functional similarity between distantly related bacterial 16 S rRNAs

The 16 S rRNA sequence has long been used uncritically as a molecular clock to infer phylogenetic relationships among prokaryotes without fully elucidating the evolutionary changes that this molecule undergoes. In this study, we investigated the functional evolvability of 16 S rRNA, using comparative RNA function analyses between the 16 S rRNAs of Escherichia coli (Proteobacteria) and Acidobacteria (78% identity, 334 nucleotide differences) in the common genetic background of E. coli. While the growth phenotype of an E. coli mutant harboring the acidobacterial gene was disrupted significantly, it was restored almost completely following introduction of a 16 S rRNA sequence with a single base-pair variation in helix 44; the remaining 332 nucleotides were thus functionally similar to those of E. coli. Our results suggest that 16 S rRNAs share an inflexible cradle structure formed by ribosomal proteins and have evolved by accumulating species-specific yet functionally similar mutations. While this experimental evidence suggests the neutral evolvability of 16 S rRNA genes and hence satisfies the necessary requirements to use the sequence as a molecular clock, it also implies the promiscuous nature of the 16 S rRNA gene, i.e., the occurrence of horizontal gene transfer among bacteria.

Dawn of the in vivo RNA structurome and interactome

RNA is one of the most fascinating biomolecules in living systems given its structural versatility to fold into elaborate architectures for important biological functions such as gene regulation, catalysis, and information storage. Knowledge of RNA structures and interactions can provide deep insights into their functional roles in vivo For decades, RNA structural studies have been conducted on a transcript-by-transcript basis. The advent of next-generation sequencing (NGS) has enabled the development of transcriptome-wide structural probing methods to profile the global landscape of RNA structures and interactions, also known as the RNA structurome and interactome, which transformed our understanding of the RNA structure-function relationship on a transcriptomic scale. In this review, molecular tools and NGS methods used for RNA structure probing are presented, novel insights uncovered by RNA structurome and interactome studies are highlighted, and perspectives on current challenges and potential future directions are discussed. A more complete understanding of the RNA structures and interactions in vivo will help illuminate the novel roles of RNA in gene regulation, development, and diseases.