ProbeAlign: incorporating high-throughput sequencing-based structure probing information into ncRNA homology search

Background: Recent advances in RNA structure probing technologies, including the ones based on high-throughput sequencing, have improved the accuracy of thermodynamic folding with quantitative nucleotide-resolution structural information. Results: In this paper, we present a novel approach, ProbeAlign, to incorporate the reactivities from high-throughput RNA structure probing into ncRNA homology search for functional annotation. To reduce the overhead of structure alignment on large-scale data, the specific pairing patterns in the query sequences are ignored. On the other hand, the partial structural information of the target sequences embedded in probing data is retrieved to guide the alignment. Thus the structure alignment problem is transformed into a sequence alignment problem with additional reactivity information. The benchmark results show that the prediction accuracy of ProbeAlign outperforms filter-based CMsearch with high computational efficiency. The application of ProbeAlign to the FragSeq data, which is based on genome-wide structure probing, has demonstrated its capability to search ncRNAs in a large-scale dataset from high-throughput sequencing. Conclusions: By incorporating high-throughput sequencing-based structure probing information, ProbeAlign can improve the accuracy and efficiency of ncRNA homology search. It is a promising tool for ncRNA functional annotation on genome-wide datasets

Computational approaches for RNA structure ensemble deconvolution from structure probing data

RNA structure probing experiments have emerged over the last decade as a straightforward way to determine the structure of RNA molecules in a number of different contexts. Although powerful, the ability of RNA to dynamically interconvert between, and to simultaneously populate, alternative structural configurations, poses a nontrivial challenge to the interpretation of data derived from these experiments. Recent efforts aimed at developing computational methods for the reconstruction of coexisting alternative RNA conformations from structure probing data are paving the way to the study of RNA structure ensembles, even in the context of living cells. In this review, we critically discuss these methods, their limitations and possible future improvements

In Vitro Studies of the Prp9·Prp11·Prp21 Complex Indicate a Pathway for U2 Small Nuclear Ribonucleoprotein Activation

Pre-mRNA splicing takes place on a large ribonucleoprotein particle, the spliceosome which contains the five small nuclear ribonucleoproteins (snRNPs), U1, U2, U4, U5, and U6. In Saccharomyces cerevisiae the mRNA splicing factors, Prp9, Prp11, and Prp21, are necessary for addition of the U2 snRNP to the pre-mRNA in an early step of spliceosome assembly. This paper describes a study of interactions between these proteins and their role in spliceosome assembly. The proteins were expressed in Escherichia coli. Prp9 and Prp11 were purified by metal affinity chromatography. Prp21 was purified using a solubilization/renaturation protocol. We have combined these separately purified proteins and present direct evidence of a Prp9·Prp11·Prp21 protein complex that is functional in in vitro splicing assays. Characteristics of this Prp9·Prp11·Prp21 complex were further investigated using proteins synthesized in vitro. In addition, we found that Prp9, Prp11, and Prp21 influence the structure of the U2 snRNP in a manner that alters the accessibility of the branch point pairing region of the U2 snRNA to oligonucleotide-directed RNaseH cleavage. We present a model, based on the data presented here and in the accompanying paper, for a combined role of Prp9, Prp11, Prp21, and Prp5 in activating the U2 snRNP for assembly into the pre-spliceosome

Computational investigations of structure probing experiments for RNA structure prediction

Ribonucleic acids (RNA) transcripts, and in particular non-coding RNAs, play fundamental roles in cellular metabolism, as they are involved in protein synthesis, catalysis, and regulation of gene expression. In some cases, an RNA\u2019s biological function is mostly dependent on a specific active conformation, making the identification of this single stable structure crucial to identify the role of the RNA and the relationships between its mutations and diseases. On the other hand, RNAs are often found in a dynamic equilibrium of multiple interconverting conformations, that is necessary to regulate their functional activity. In these cases it becomes fundamental to gain knowledge of RNA\u2019s structural ensembles, in order to fully determine its mechanism of action. The current structure determination techniques, both for single-state models such as X-ray crystallography, and for multi-state models such as nuclear magnetic resonance and single-molecule methods, despite proving accurate and reliable in many cases, are extremely slow and costly. In contrast, chemical probing is a class of experimental techniques that provide structural information at single-nucleotide resolution at significantly lower costs in terms of time and required infrastructures. In particular, selective 2\u2032 hydroxyl acylation analyzed via primer extension (SHAPE) has proved a valid chemical mapping technique to probe RNA structure even in vivo. This thesis reports a systematic investi- gation of chemical probing experiments based on two different approaches. The first approach, presented in Chapter 2, relies on machine-learning techniques to optimize a model for mapping experimental data into structural information. The model relies also on co-evolutionary data, in the form of direct coupling analysis (DCA) couplings. The inclusion of this kind of data is chosen in the same spirit of reducing the costs of structure probing, as co-evolutionary analysis relies only on sequencing techniques. The resulting model is proposed as a candidate standard tool for prediction of RNA secondary structure, and some insight in the mechanism of chemical probing is gained by interpreting back its features. Importantly, this work has been developed in the per- spective of building a framework for future refinement and improvement. In this spirit, all the used data and scripts are available at https://github.com/bussilab/shape-dca-data, and the model can be easily retrained and adapted to incorporate arbitrary experimental informa- tion. As the interpretation of the model features suggests the possible emergence of cooperative effects involving RNA nucleotides interacting with SHAPE reagents, a second approach based on Molecular Dynamics simulations is proposed to investigate this hypothesis. The results, along with an originally developed methodology to analyse Molecular Dynamics simulations at variable number of particles, are presented in Chapter 3

RNA systems biology: uniting functional discoveries and structural tools to understand global roles of RNAs

RNAs assume sophisticated structures that are active in myriad cellular processes. In this review, we highlight newly identified ribozymes, riboswitches, and small RNAs, some of which control the function of cellular metabolic and gene expression networks. We then examine recent developments in genome-wide RNA structure probing technologies that are yielding new insights into the structural landscape of the transcriptome. Finally, we discuss how these RNA ‘structomic’ methods can address emerging questions in RNA systems biology, from the mechanisms behind long non-coding RNAs to new bases for human diseases

Regulation of mRNA translation by a photoriboswitch.

Optogenetic tools have revolutionized the study of receptor-mediated processes, but such tools are lacking for RNA-controlled systems. In particular, light-activated regulatory RNAs are needed for spatiotemporal control of gene expression. To fill this gap, we used in vitro selection to isolate a novel riboswitch that selectively binds the trans isoform of a stiff-stilbene (amino-tSS)-a rapidly and reversibly photoisomerizing small molecule. Structural probing revealed that the RNA binds amino-tSS about 100-times stronger than the cis photoisoform (amino-cSS). In vitro and in vivo functional analysis showed that the riboswitch, termed Werewolf-1 (Were-1), inhibits translation of a downstream open reading frame when bound to amino-tSS. Photoisomerization of the ligand with a sub-millisecond pulse of light induced the protein expression. In contrast, amino-cSS supported protein expression, which was inhibited upon photoisomerization to amino-tSS. Reversible photoregulation of gene expression using a genetically encoded RNA will likely facilitate high-resolution spatiotemporal analysis of complex RNA processes