nextPARS: parallel probing of RNA structures in Illumina

Probing RNA structural landscapes across Candida yeast genomes

Understanding the intricate roles of RNA molecules in virulence and host-pathogen interactions can provide valuable insights into combatting infections and improving human health. Although much progress has been achieved in understanding transcriptional regulation during host-pathogen interactions in diverse species, more is needed to know about the structure of pathogen RNAs. This is particularly true for fungal pathogens, including pathogenic yeasts of the Candida genus, which are the leading cause of hospital-acquired fungal infections. Our work addresses the gap between RNA structure and their biology by employing genome-wide structure probing to comprehensively explore the structural landscape of mRNAs and long non-coding RNAs (lncRNAs) in the four major Candida pathogens. Specifically focusing on mRNA, we observe a robust correlation between sequence conservation and structural characteristics in orthologous transcripts, significantly when sequence identity exceeds 50%, highlighting structural feature conservation among closely related species. We investigate the impact of single nucleotide polymorphisms (SNPs) on mRNA secondary structure. SNPs within 5' untranslated regions (UTRs) tend to occur in less structured positions, suggesting structural constraints influencing transcript regulation. Furthermore, we compare the structural properties of coding regions and UTRs, noting that coding regions are generally more structured than UTRs, consistent with similar trends in other species. Additionally, we provide the first experimental characterization of lncRNA structures in Candida species. Most lncRNAs form independent subdomains, similar to human lncRNAs. Notably, we identify hairpin-like structures in lncRNAs, a feature known to be functionally significant. Comparing hairpin prevalence between lncRNAs and protein-coding genes, we find enrichment in lncRNAs across Candida species, humans, and Arabidopsis thaliana, suggesting a conserved role for these structures. In summary, our study offers valuable insights into the interplay between RNA sequence, structure, and function in Candida pathogens, with implications for gene expression regulation and potential therapeutic strategies against Candida infections.

A hybrid approach to assess the structural impact of long noncoding RNA mutations uncovers key NEAT1 interactions in colorectal cancer

Long noncoding RNAs (lncRNAs) are emerging players in cancer and they entail potential as prognostic biomarkers or therapeutic targets. Earlier studies have identified somatic mutations in lncRNAs that are associated with tumor relapse after therapy, but the underlying mechanisms behind these associations remain unknown. Given the relevance of secondary structure for the function of some lncRNAs, some of these mutations may have a functional impact through structural disturbance. Here, we examined the potential structural and functional impact of a novel A > G point mutation in NEAT1 that has been recurrently observed in tumors of colorectal cancer patients experiencing relapse after treatment. Here, we used the nextPARS structural probing approach to provide first empirical evidence that this mutation alters NEAT1 structure. We further evaluated the potential effects of this structural alteration using computational tools and found that this mutation likely alters the binding propensities of several NEAT1-interacting miRNAs. Differential expression analysis on these miRNA networks shows upregulation of Vimentin, consistent with previous findings. We propose a hybrid pipeline that can be used to explore the potential functional effects of lncRNA somatic mutations.

Non-coding RNAs in human health and disease: potential function as biomarkers and therapeutic targets

Human diseases have been a critical threat from the beginning of human history. Knowing the origin, course of action and treatment of any disease state is essential. A microscopic approach to the molecular field is a more coherent and accurate way to explore the mechanism, progression, and therapy with the introduction and evolution of technology than a macroscopic approach. Non-coding RNAs (ncRNAs) play increasingly important roles in detecting, developing, and treating all abnormalities related to physiology, pathology, genetics, epigenetics, cancer, and developmental diseases. Noncoding RNAs are becoming increasingly crucial as powerful, multipurpose regulators of all biological processes. Parallel to this, a rising amount of scientific information has revealed links between abnormal noncoding RNA expression and human disorders. Numerous non-coding transcripts with unknown functions have been found in addition to advancements in RNA-sequencing methods. Non-coding linear RNAs come in a variety of forms, including circular RNAs with a continuous closed loop (circRNA), long non-coding RNAs (lncRNA), and microRNAs (miRNA). This comprises specific information on their biogenesis, mode of action, physiological function, and significance concerning disease (such as cancer or cardiovascular diseases and others). This study review focuses on non-coding RNA as specific biomarkers and novel therapeutic targets.

A high-throughput approach to predict A-to-I effects on RNA structure indicates a change of double-stranded content in non-coding RNAs

RNA molecules undergo a number of chemical modifications whose effects can alter their structure and molecular interactions. Previous studies have shown that RNA editing can impact the formation of ribonucleoprotein complexes and influence the assembly of membrane-less organelles such as stress-granules. For instance, N6-methyladenosine (m6A) enhances SG formation and N1-methyladenosine (m1A) prevents their transition to solid-like aggregates. Yet, very little is known about adenosine to inosine (A-to-I) modification that is very abundant in human cells and not only impacts mRNAs but also non-coding RNAs. Here, we built the CROSSalive predictor of A-to-I effects on RNA structure based on high-throughput in-cell experiments. Our method shows an accuracy of 90% in predicting the single and double-stranded content of transcripts and identifies a general enrichment of double-stranded regions caused by A-to-I in long intergenic non-coding RNAs (lincRNAs). For the individual cases of NEAT1, NORAD and XIST, we investigated the relationship between A-to-I editing and interactions with RNA-binding proteins using available CLIP data and catRAPID predictions. We found that A-to-I editing is linked to alteration of interaction sites with proteins involved in phase-separation, which suggests that RNP assembly can be influenced by A-to-I. CROSSalive is available at http://service.tartaglialab.com/new_submission/crossalive. This article is protected by copyright. All rights reserved.

Secondary structure prediction of long noncoding RNA: review and experimental comparison of existing approaches

MOTIVATION

In contrast to messenger RNAs, the function of the wide range of existing long noncoding RNAs (lncRNAs) largely depends on their structure, which determines interactions with partner molecules. Thus, the determination or prediction of the secondary structure of lncRNAs is critical to uncover their function. Classical approaches for predicting RNA secondary structure have been based on dynamic programming and thermodynamic calculations. In the last 4 years, a growing number of machine learning (ML)-based models, including deep learning (DL), have achieved breakthrough performance in structure prediction of biomolecules such as proteins and have outperformed classical methods in short transcripts folding. Nevertheless, the accurate prediction for lncRNA still remains far from being effectively solved. Notably, the myriad of new proposals has not been systematically and experimentally evaluated.

RESULTS

In this work, we compare the performance of the classical methods as well as the most recently proposed approaches for secondary structure prediction of RNA sequences using a unified and consistent experimental setup. We use the publicly available structural profiles for 3023 yeast RNA sequences, and a novel benchmark of well-characterized lncRNA structures from different species. Moreover, we propose a novel metric to assess the predictive performance of methods, exclusively based on the chemical probing data commonly used for profiling RNA structures, avoiding any potential bias incorporated by computational predictions when using dot-bracket references. Our results provide a comprehensive comparative assessment of existing methodologies, and a novel and public benchmark resource to aid in the development and comparison of future approaches.

AVAILABILITY

Full source code and benchmark datasets are available at: https://github.com/sinc-lab/lncRNA-folding.

CONTACT

lbugnon@sinc.unl.edu.ar.

Analysis of miRNAs responsive to long-term calcium deficiency in tef (Eragrostis tef (Zucc.) Trotter)

MicroRNAs (miRNAs) play an important role in growth, development, stress resilience, and epigenetic modifications of plants. However, the effect of calcium (Ca²⁺) deficiency on miRNA expression in the orphan crop tef (Eragrostis tef) remains unknown. In this study, we analyzed expression of miRNAs in roots and shoots of tef in response to Ca²⁺ treatment. miRNA-seq followed by bioinformatic analysis allowed us to identify a large number of small RNAs (sRNAs) ranging from 17 to 35 nt in length. A total of 1380 miRNAs were identified in tef experiencing long-term Ca²⁺ deficiency while 1495 miRNAs were detected in control plants. Among the miRNAs identified in this study, 161 miRNAs were similar with those previously characterized in other plant species and 348 miRNAs were novel, while the remaining miRNAs were uncharacterized. Putative target genes and their functions were predicted for all the known and novel miRNAs that we identified. Based on gene ontology (GO) analysis, the predicted target genes are known to have various biological and molecular functions including calcium uptake and transport. Pairwise comparison of differentially expressed miRNAs revealed that some miRNAs were specifically enriched in roots or shoots of low Ca²⁺-treated plants. Further characterization of the miRNAs and their targets identified in this study may help in understanding Ca²⁺ deficiency responses in tef and related orphan crops.

Chemical and Enzymatic Probing of Viral RNAs: From Infancy to Maturity and Beyond

RNA molecules are key players in a variety of biological events, and this is particularly true for viral RNAs. To better understand the replication of those pathogens and try to block them, special attention has been paid to the structure of their RNAs. Methods to probe RNA structures have been developed since the 1960s; even if they have evolved over the years, they are still in use today and provide useful information on the folding of RNA molecules, including viral RNAs. The aim of this review is to offer a historical perspective on the structural probing methods used to decipher RNA structures before the development of the selective 2'-hydroxyl acylation analyzed by primer extension (SHAPE) methodology and to show how they have influenced the current probing techniques. Actually, these technological breakthroughs, which involved advanced detection methods, were made possible thanks to the development of next-generation sequencing (NGS) but also to the previous works accumulated in the field of structural RNA biology. Finally, we will also discuss how high-throughput SHAPE (hSHAPE) paved the way for the development of sophisticated RNA structural techniques.

Long Non-coding RNAs: Mechanisms, Experimental, and Computational Approaches in Identification, Characterization, and Their Biomarker Potential in Cancer

Long non-coding RNAs are diverse class of non-coding RNA molecules >200 base pairs of length having various functions like gene regulation, dosage compensation, epigenetic regulation. Dysregulation and genomic variations of several lncRNAs have been implicated in several diseases. Their tissue and developmental specific expression are contributing factors for them to be viable indicators of physiological states of the cells. Here we present an comprehensive review the molecular mechanisms and functions, state of the art experimental and computational pipelines and challenges involved in the identification and functional annotation of lncRNAs and their prospects as biomarkers. We also illustrate the application of co-expression networks on the TCGA-LIHC dataset for putative functional predictions of lncRNAs having a therapeutic potential in Hepatocellular carcinoma (HCC).

Profiling of RNA Structure at Single-Nucleotide Resolution Using nextPARS

RNA molecules play important roles in almost every cellular process, and their functions are mediated by their sequence and structure. Determining the secondary structure of RNAs is central to understanding RNA function and evolution. RNA structure probing techniques coupled to high-throughput sequencing allow determining structural features of RNA molecules at transcriptome-wide scales. Our group recently developed a novel Illumina-based implementation of in vitro parallel probing of RNA structures called nextPARS.Here, we describe a protocol for the computation of the nextPARS scores and their use to obtain the structural profile (single- or double-stranded state) of an RNA sequence at single-nucleotide resolution.

Structural characterization of NORAD reveals a stabilizing role of spacers and two new repeat units

Long non-coding RNAs (lncRNAs) can perform a variety of key cellular functions by interacting with proteins and other RNAs. Recent studies have shown that the functions of lncRNAS are largely mediated by their structures. However, our structural knowledge for most lncRNAS is limited to sequence-based computational predictions. Non-coding RNA activated by DNA damage (NORAD) is an atypical lncRNA due to its abundant expression and high sequence conservation. NORAD regulates genomic stability by interacting with proteins and microRNAs. Previous sequence-based characterization has identified a modular organization of NORAD composed of several NORAD repeat units (NRUs). These units comprise the protein-binding elements and are separated by regular spacers. Here, we experimentally determine for the first time the secondary structure of NORAD using the nextPARS approach. Our results suggest that the spacer regions provide structural stability to NRUs. Furthermore, we uncover two previously unreported NRUs, and determine the core structural motifs conserved across NRUs. Overall, these findings will help to elucidate the function and evolution of NORAD.

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.

SMAtool reveals sequences and structural principles of protein-RNA interaction

Protein binding events on RNA are highly related to RNA secondary structure, which affects post-transcriptional regulation and translation. However, it remains challenging to describe the association between RNA secondary structure and protein binding events. Here, we present Structure Motif Analysis tool (SMAtool), a pipeline that integrates RNA secondary structure and protein binding site information to profile the binding structure preference of each protein. As an example of applying SMAtool, we extracted the RNA-structure and binding site information respectively from the DMS-seq and eCLIP-seq data of the K562 cell-line, and used SMAtool to analyze the structure motif of each RNA binding protein (RBP). This new approach provided results consistent with X-ray crystallography data from the protein data bank (PDB) database, demonstrating that it can help researchers investigate the structure preference of RBP, and understand the role of RNA secondary structure in gene expression. Availability and implementation: https://github.com/QuKunLab/SMAtool.

Candida parapsilosis: from Genes to the Bedside

Patients with suppressed immunity are at the highest risk for hospital-acquired infections. Among these, invasive candidiasis is the most prevalent systemic fungal nosocomial infection. Over recent decades, the combined prevalence of non-albicans Candida species outranked Candida albicans infections in several geographical regions worldwide, highlighting the need to understand their pathobiology in order to develop effective treatment and to prevent future outbreaks. Candida parapsilosis is the second or third most frequently isolated Candida species from patients. Besides being highly prevalent, its biology differs markedly from that of C. albicans, which may be associated with C. parapsilosis' increased incidence. Differences in virulence, regulatory and antifungal drug resistance mechanisms, and the patient groups at risk indicate that conclusions drawn from C. albicans pathobiology cannot be simply extrapolated to C. parapsilosis Such species-specific characteristics may also influence their recognition and elimination by the host and the efficacy of antifungal drugs. Due to the availability of high-throughput, state-of-the-art experimental tools and molecular genetic methods adapted to C. parapsilosis, genome and transcriptome studies are now available that greatly contribute to our understanding of what makes this species a threat. In this review, we summarize 10 years of findings on C. parapsilosis pathogenesis, including the species' genetic properties, transcriptome studies, host responses, and molecular mechanisms of virulence. Antifungal susceptibility studies and clinician perspectives are discussed. We also present regional incidence reports in order to provide an updated worldwide epidemiology summary.

Transcriptome Sequencing Approaches to Elucidate Host-Microbe Interactions in Opportunistic Human Fungal Pathogens

Infections caused by opportunistic human fungal pathogens are a source of increasing medical concern, due to their growing incidence, the emergence of novel pathogenic species, and the lack of effective diagnostics tools. Fungal pathogens are phylogenetically diverse, and their virulence mechanisms can differ widely across species. Despite extensive efforts, the molecular bases of virulence in pathogenic fungi and their interactions with the human host remain poorly understood for most species. In this context, next-generation sequencing approaches hold the promise of helping to close this knowledge gap. In particular, high-throughput transcriptome sequencing (RNA-Seq) enables monitoring the transcriptional profile of both host and microbes to elucidate their interactions and discover molecular mechanisms of virulence and host defense. Here, we provide an overview of transcriptome sequencing techniques and approaches, and survey their application in studying the interplay between humans and fungal pathogens. Finally, we discuss novel RNA-Seq approaches in studying host-pathogen interactions and their potential role in advancing the clinical diagnostics of fungal infections.

RNA Structure Elements Conserved between Mouse and 59 Other Vertebrates

In this work, we present a computational screen conducted for functional RNA structures, resulting in over 100,000 conserved RNA structure elements found in alignments of mouse (mm10) against 59 other vertebrates. We explicitly included masked repeat regions to explore the potential of transposable elements and low-complexity regions to give rise to regulatory RNA elements. In our analysis pipeline, we implemented a four-step procedure: (i) we screened genome-wide alignments for potential structure elements using RNAz-2, (ii) realigned and refined candidate loci with LocARNA-P, (iii) scored candidates again with RNAz-2 in structure alignment mode, and (iv) searched for additional homologous loci in mouse genome that were not covered by genome alignments. The 3'-untranslated regions (3'-UTRs) of protein-coding genes and small noncoding RNAs are enriched for structures, while coding sequences are depleted. Repeat-associated loci make up about 95% of the homologous loci identified and are, as expected, predominantly found in intronic and intergenic regions. Nevertheless, we report the structure elements enriched in specific genome elements, such as 3'-UTRs and long noncoding RNAs (lncRNAs). We provide full access to our results via a custom UCSC genome browser trackhub freely available on our website (http://rna.tbi.univie.ac.at/trackhubs/#RNAz).