SHAPEwarp-web: sequence-agnostic search for structurally homologous RNA regions across databases of chemical probing data.

RNA molecules perform a variety of functions in cells, many of which rely on their secondary and tertiary structures. Chemical probing methods coupled with high-throughput sequencing have significantly accelerated the mapping of RNA structures, and increasingly large datasets of transcriptome-wide RNA chemical probing data are becoming available. Analogously to what has been done for decades in the protein world, this RNA structural information can be leveraged to aid the discovery of structural similarity to a known RNA (or RNA family), which, in turn, can inform about the function of transcripts. We have previously developed SHAPEwarp, a sequence-agnostic method for the search of structurally homologous RNA segments in a database of reactivity profiles derived from chemical probing experiments. In its original implementation, however, SHAPEwarp required substantial computational resources, even for moderately sized databases, as well as significant Linux command line know-how. To address these limitations, we introduce here SHAPEwarp-web, a user-friendly web interface to rapidly query large databases of RNA chemical probing data for structurally similar RNAs. Aside from featuring a completely rewritten core, which speeds up by orders of magnitude the search inside large databases, the web server hosts several high-quality chemical probing databases across multiple species. SHAPEwarp-web is available from https://shapewarp.incarnatolab.com.

Genome-scale deconvolution of RNA structure ensembles.

RNA structure heterogeneity is a major challenge when querying RNA structures with chemical probing. We introduce DRACO, an algorithm for the deconvolution of coexisting RNA conformations from mutational profiling experiments. Analysis of the SARS-CoV-2 genome using dimethyl sulfate mutational profiling with sequencing (DMS-MaPseq) and DRACO, identifies multiple regions that fold into two mutually exclusive conformations, including a conserved structural switch in the 3' untranslated region. This work may open the way to dissecting the heterogeneity of the RNA structurome.

The acetyltransferase p300 is recruited in trans to multiple enhancer sites by lncSmad7.

The histone acetyltransferase p300 (also known as KAT3B) is a general transcriptional coactivator that introduces the H3K27ac mark on enhancers triggering their activation and gene transcription. Genome-wide screenings demonstrated that a large fraction of long non-coding RNAs (lncRNAs) plays a role in cellular processes and organ development although the underlying molecular mechanisms remain largely unclear (1,2). We found 122 lncRNAs that interacts directly with p300. In depth analysis of one of these, lncSmad7, is required to maintain ESC self-renewal and it interacts to the C-terminal domain of p300. lncSmad7 also contains predicted RNA-DNA Hoogsteen forming base pairing. Combined Chromatin Isolation by RNA precipitation followed by sequencing (ChIRP-seq) together with CRISPR/Cas9 mutagenesis of the target sites demonstrate that lncSmad7 binds and recruits p300 to enhancers in trans, to trigger enhancer acetylation and transcriptional activation of its target genes. Thus, these results unveil a new mechanism by which p300 is recruited to the genome.

In vivo analysis of influenza A mRNA secondary structures identifies critical regulatory motifs.

The influenza A virus (IAV) is a continuous health threat to humans as well as animals due to its recurring epidemics and pandemics. The IAV genome is segmented and the eight negative-sense viral RNAs (vRNAs) are transcribed into positive sense complementary RNAs (cRNAs) and viral messenger RNAs (mRNAs) inside infected host cells. A role for the secondary structure of IAV mRNAs has been hypothesized and debated for many years, but knowledge on the structure mRNAs adopt in vivo is currently missing. Here we solve, for the first time, the in vivo secondary structure of IAV mRNAs in living infected cells. We demonstrate that, compared to the in vitro refolded structure, in vivo IAV mRNAs are less structured but exhibit specific locally stable elements. Moreover, we show that the targeted disruption of these high-confidence structured domains results in an extraordinary attenuation of IAV replicative capacity. Collectively, our data provide the first comprehensive map of the in vivo structural landscape of IAV mRNAs, hence providing the means for the development of new RNA-targeted antivirals.

RNA Framework: an all-in-one toolkit for the analysis of RNA structures and post-transcriptional modifications.

RNA is emerging as a key regulator of a plethora of biological processes. While its study has remained elusive for decades, the recent advent of high-throughput sequencing technologies provided the unique opportunity to develop novel techniques for the study of RNA structure and post-transcriptional modifications. Nonetheless, most of the required downstream bioinformatics analyses steps are not easily reproducible, thus making the application of these techniques a prerogative of few laboratories. Here we introduce RNA Framework, an all-in-one toolkit for the analysis of most NGS-based RNA structure probing and post-transcriptional modification mapping experiments. To prove the extreme versatility of RNA Framework, we applied it to both an in-house generated DMS-MaPseq dataset, and to a series of literature available experiments. Notably, when starting from publicly available datasets, our software easily allows replicating authors' findings. Collectively, RNA Framework provides the most complete and versatile toolkit to date for a rapid and streamlined analysis of the RNA epistructurome. RNA Framework is available for download at: http://www.rnaframework.com.

In vivo probing of nascent RNA structures reveals principles of cotranscriptional folding.

Defining the in vivo folding pathway of cellular RNAs is essential to understand how they reach their final native conformation. We here introduce a novel method, named Structural Probing of Elongating Transcripts (SPET-seq), that permits single-base resolution analysis of transcription intermediates' secondary structures on a transcriptome-wide scale, enabling base-resolution analysis of the RNA folding events. Our results suggest that cotranscriptional RNA folding in vivo is a mixture of cooperative folding events, in which local RNA secondary structure elements are formed as they get transcribed, and non-cooperative events, in which 5'-halves of long-range helices get sequestered into transient non-native interactions until their 3' counterparts have been transcribed. Together our work provides the first transcriptome-scale overview of RNA cotranscriptional folding in a living organism.

High-throughput single-base resolution mapping of RNA 2΄-O-methylated residues.

Functional characterization of the transcriptome requires tools for the systematic investigation of RNA post-transcriptional modifications. 2΄-O-methylation (2΄-OMe) of the ribose moiety is one of the most abundant post-transcriptional modifications of RNA, although its systematic analysis is difficult due to the lack of reliable high-throughput mapping methods. We describe here a novel high-throughput approach, named 2OMe-seq, that enables fast and accurate mapping at single-base resolution, and relative quantitation, of 2΄-OMe modified residues. We compare our method to other state-of-art approaches, and show that it achieves higher sensitivity and specificity. By applying 2OMe-seq to HeLa cells, we show that it is able to recover the majority of the annotated 2΄-OMe sites on ribosomal RNA. By performing knockdown of the Fibrillarin methyltransferase in mouse embryonic stem cells (ESCs) we show the ability of 2OMe-seq to capture 2΄-O-Methylation level variations. Moreover, using 2OMe-seq data we here report the discovery of 12 previously unannotated 2΄-OMe sites across 18S and 28S rRNAs, 11 of which are conserved in both human and mouse cells, and assigned the respective snoRNAs for all sites. Our approach expands the repertoire of methods for transcriptome-wide mapping of RNA post-transcriptional modifications, and promises to provide novel insights into the role of this modification.

Hot spot mapping of protein surfaces with TEMPOL: Bovine pancreatic RNase A as a model system.

TEMPOL spin-label has been used to identify surface exposure of protein nuclei from NMR analysis of the induced paramagnetic relaxation enhancements (PRE). The absence of linear dependence between atom depths and observed PRE reveals that specific mechanisms drive the approach of the paramagnet to the protein surface. RNase A represents a unique protein system to explore the fine details of the information offered by TEMPOL induced PRE, due to the abundance of previous results, obtained in solution and in the crystal, dealing with surface dynamics behavior of this protein. MD simulations in explicit solvent have been performed, also in the presence of TEMPOL, in order to delineate the role of intermolecular hydrogen bonds (HB) on PRE extents. Comparison of our results with the ones obtained from multiple solvent crystal structure (MSCS) studies yields information on the specificities that these two techniques have for characterizing protein-ligand interactions, a fundamental step in the development of reliable surface druggability predictors.

Searching for protein binding sites from Molecular Dynamics simulations and paramagnetic fragment-based NMR studies.

Hotspot delineation on protein surfaces represents a fundamental step for targeting protein-protein interfaces. Disruptors of protein-protein interactions can be designed provided that the sterical features of binding pockets, including the transient ones, can be defined. Molecular Dynamics, MD, simulations have been used as a reliable framework for identifying transient pocket openings on the protein surface. Accessible surface area and intramolecular H-bond involvement of protein backbone amides are proposed as descriptors for characterizing binding pocket occurrence and evolution along MD trajectories. TEMPOL induced paramagnetic perturbations on (1)H-(15)N HSQC signals of protein backbone amides have been analyzed as a fragment-based search for surface hotspots, in order to validate MD predicted pockets. This procedure has been applied to CXCL12, a small chemokine responsible for tumor progression and proliferation. From combined analysis of MD data and paramagnetic profiles, two CXCL12 sites suitable for the binding of small molecules were identified. One of these sites is the already well characterized CXCL12 region involved in the binding to CXCR4 receptor. The other one is a transient pocket predicted by Molecular Dynamics simulations, which could not be observed from static analysis of CXCL12 PDB structures. The present results indicate how TEMPOL, instrumental in identifying this transient pocket, can be a powerful tool to delineate minor conformations which can be highly relevant in dynamic discovery of antitumoral drugs.

Cold Denaturation Unveiled: Molecular Mechanism of the Asymmetric Unfolding of Yeast Frataxin.

What is the mechanism that determines the denaturation of proteins at low temperatures, which is, by now, recognized as a fundamental property of all proteins? We present experimental evidence that clarifies the role of specific interactions that favor the entrance of water into the hydrophobic core, a mechanism originally proposed by Privalov but never proved experimentally. By using a combination of molecular dynamics simulation, molecular biology, and biophysics, we identified a cluster of negatively charged residues that represents a preferential gate for the entrance of water molecules into the core. Even single-residue mutations in this cluster, from acidic to neutral residues, affect cold denaturation much more than heat denaturation, suppressing cold denaturation at temperatures above zero degrees. The molecular mechanism of the cold denaturation of yeast frataxin is intrinsically different from that of heat denaturation.

SHAPE-guided RNA structure homology search and motif discovery.

The rapidly growing popularity of RNA structure probing methods is leading to increasingly large amounts of available RNA structure information. This demands the development of efficient tools for the identification of RNAs sharing regions of structural similarity by direct comparison of their reactivity profiles, hence enabling the discovery of conserved structural features. We here introduce SHAPEwarp, a largely sequence-agnostic SHAPE-guided algorithm for the identification of structurally-similar regions in RNA molecules. Analysis of Dengue, Zika and coronavirus genomes recapitulates known regulatory RNA structures and identifies novel highly-conserved structural elements. This work represents a preliminary step towards the model-free search and identification of shared and conserved RNA structural features within transcriptomes.

HaTSPiL: A modular pipeline for high-throughput sequencing data analysis.

BACKGROUND: Next generation sequencing methods are widely adopted for a large amount of scientific purposes, from pure research to health-related studies. The decreasing costs per analysis led to big amounts of generated data and to the subsequent improvement of software for the respective analyses. As a consequence, many approaches have been developed to chain different software in order to obtain reliable and reproducible workflows. However, the large range of applications for NGS approaches entails the challenge to manage many different workflows without losing reliability. METHODS: We here present a high-throughput sequencing pipeline (HaTSPiL), a Python-powered CLI tool designed to handle different approaches for data analysis with a high level of reliability. The software relies on the barcoding of filenames using a human readable naming convention that contains any information regarding the sample needed by the software to automatically choose different workflows and parameters. HaTSPiL is highly modular and customisable, allowing the users to extend its features for any specific need. CONCLUSIONS: HaTSPiL is licensed as Free Software under the MIT license and it is available at https://github.com/dodomorandi/hatspil.