Browse
Submit Data
Databases
API
Help

Dataset Information

21 Views

0 Connections

0 Citations

0 Reanalyses

0 Downloads

Omics score: 0

Rapid structure-function insights via hairpin-centric analysis of big RNA structure probing datasets.

ABSTRACT: The functions of RNA are often tied to its structure, hence analyzing structure is of significant interest when studying cellular processes. Recently, large-scale structure probing (SP) studies have enabled assessment of global structure-function relationships via standard data summarizations or local folding. Here, we approach structure quantification from a hairpin-centric perspective where putative hairpins are identified in SP datasets and used as a means to capture local structural effects. This has the advantage of rapid processing of big (e.g. transcriptome-wide) data as RNA folding is circumvented, yet it captures more information than simple data summarizations. We reformulate a statistical learning algorithm we previously developed to significantly improve precision of hairpin detection, then introduce a novel nucleotide-wise measure, termed the hairpin-derived structure level (HDSL), which captures local structuredness by accounting for the presence of likely hairpin elements. Applying HDSL to data from recent studies recapitulates, strengthens and expands on their findings which were obtained by more comprehensive folding algorithms, yet our analyses are orders of magnitude faster. These results demonstrate that hairpin detection is a promising avenue for global and rapid structure-function analysis, furthering our understanding of RNA biology and the principal features which drive biological insights from SP data.

SUBMITTER: Radecki P

PROVIDER: S-EPMC8384053 | biostudies-literature |

REPOSITORIES: biostudies-literature

ACCESS DATA

Json Xml

Similar Datasets

Metrics for rapid quality control in RNA structure probing experiments.

Project description:MotivationThe diverse functionalities of RNA can be attributed to its capacity to form complex and varied structures. The recent proliferation of new structure probing techniques coupled with high-throughput sequencing has helped RNA studies expand in both scope and depth. Despite differences in techniques, most experiments face similar challenges in reproducibility due to the stochastic nature of chemical probing and sequencing. As these protocols expand to transcriptome-wide studies, quality control becomes a more daunting task. General and efficient methodologies are needed to quantify variability and quality in the wide range of current and emerging structure probing experiments.ResultsWe develop metrics to rapidly and quantitatively evaluate data quality from structure probing experiments, demonstrating their efficacy on both small synthetic libraries and transcriptome-wide datasets. We use a signal-to-noise ratio concept to evaluate replicate agreement, which has the capacity to identify high-quality data. We also consider and compare two methods to assess variability inherent in probing experiments, which we then utilize to evaluate the coverage adjustments needed to meet desired quality. The developed metrics and tools will be useful in summarizing large-scale datasets and will help standardize quality control in the field.Availability and implementationThe data and methods used in this article are freely available at: http://bme.ucdavis.edu/aviranlab/SPEQC_software CONTACT: saviran@ucdavis.eduSupplementary information: Supplementary data are available at Bioinformatics online.

| S-EPMC5181532 | biostudies-literature

RNAvigate: Efficient exploration of RNA chemical probing datasets.

Project description:Chemical probing technologies enable high-throughput examination of diverse structural features of RNA including local nucleotide flexibility, RNA secondary structure, protein- and ligand-binding, through-space interaction networks, and multi-state structural ensembles. Performing these experiments, by themselves, does not directly lead to biological insight. Instead, deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multi-layered relationships. Current platforms lack the broad accessibility, flexibility, and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library. RNAvigate currently automatically parses twenty-one standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs eighteen plot types. These features enable efficient exploration of nuanced relationships between chemical probing data, RNA structure, and motif annotations across multiple experimental samples. Compatibility with Jupyter Notebooks enables non-burdensome, reproducible, transparent and organized sharing of multi-step analyses and data visualization strategies. RNAvigate simplifies examination of multi-layered RNA structure information and accelerates discovery and characterization of RNA-centric functions in biology.

| S-EPMC10168276 | biostudies-literature

RNAvigate: efficient exploration of RNA chemical probing datasets.

Project description:Chemical probing technologies enable high-throughput examination of diverse structural features of RNA, including local nucleotide flexibility, RNA secondary structure, protein and ligand binding, through-space interaction networks, and multistate structural ensembles. Deep understanding of RNA structure-function relationships typically requires evaluating a system under structure- and function-altering conditions, linking these data with additional information, and visualizing multilayered relationships. Current platforms lack the broad accessibility, flexibility and efficiency needed to iterate on integrative analyses of these diverse, complex data. Here, we share the RNA visualization and graphical analysis toolset RNAvigate, a straightforward and flexible Python library that automatically parses 21 standard file formats (primary sequence annotations, per- and internucleotide data, and secondary and tertiary structures) and outputs 18 plot types. RNAvigate enables efficient exploration of nuanced relationships between multiple layers of RNA structure information and across multiple experimental conditions. Compatibility with Jupyter notebooks enables nonburdensome, reproducible, transparent and organized sharing of multistep analyses and data visualization strategies. RNAvigate simplifies and accelerates discovery and characterization of RNA-centric functions in biology.

| S-EPMC10954457 | biostudies-literature

Probing metagenomics by rapid cluster analysis of very large datasets.

Project description:BACKGROUND: The scale and diversity of metagenomic sequencing projects challenge both our technical and conceptual approaches in gene and genome annotations. The recent Sorcerer II Global Ocean Sampling (GOS) expedition yielded millions of predicted protein sequences, which significantly altered the landscape of known protein space by more than doubling its size and adding thousands of new families (Yooseph et al., 2007 PLoS Biol 5, e16). Such datasets, not only by their sheer size, but also by many other features, defy conventional analysis and annotation methods. METHODOLOGY/PRINCIPAL FINDINGS: In this study, we describe an approach for rapid analysis of the sequence diversity and the internal structure of such very large datasets by advanced clustering strategies using the newly modified CD-HIT algorithm. We performed a hierarchical clustering analysis on the 17.4 million Open Reading Frames (ORFs) identified from the GOS study and found over 33 thousand large predicted protein clusters comprising nearly 6 million sequences. Twenty percent of these clusters did not match known protein families by sequence similarity search and might represent novel protein families. Distributions of the large clusters were illustrated on organism composition, functional class, and sample locations. CONCLUSION/SIGNIFICANCE: Our clustering took about two orders of magnitude less computational effort than the similar protein family analysis of original GOS study. This approach will help to analyze other large metagenomic datasets in the future. A Web server with our clustering results and annotations of predicted protein clusters is available online at http://tools.camera.calit2.net/gos under the CAMERA project.

| S-EPMC2557142 | biostudies-literature

Insights Into Human Intrahepatic NK Cell Function From Single Cell RNA Sequencing Datasets.

Project description:Diverse populations of natural killer (NK) cells have been identified in circulating peripheral blood and a wide variety of different tissues and organs. These tissue-resident NK cell populations are phenotypically distinct from circulating NK cells, however, functional descriptions of their roles within tissues are lacking. Recent advances in single cell RNA sequencing (scRNA-seq) have enabled detailed transcriptional profiling of tissues at the level of single cells and provide the opportunity to explore NK cell diversity within tissues. This review explores potential novel functions of human liver-resident (lr)NK cells identified in human liver scRNA-seq studies. By comparing these datasets we identified up-regulated and down-regulated genes associated with lrNK cells clusters. These genes encode a number of activating and inhibiting receptors, as well as signal transduction molecules, which highlight potential unique pathways that lrNK cells utilize to respond to stimuli within the human liver. This unique receptor repertoire of lrNK cells may confer the ability to regulate a number of immune cell populations, such as circulating monocytes and T cells, while avoiding activation by liver hepatocytes and Kupffer cells. Validating the expression of these receptors on lrNK cells and the proposed cellular interactions within the human liver will expand our understanding of the liver-specific homeostatic roles of this tissue-resident immune cell population.

| S-EPMC8019706 | biostudies-literature

RNA Dependent RNA Polymerases: Insights from Structure, Function and Evolution.

Project description:RNA dependent RNA polymerase (RdRp) is one of the most versatile enzymes of RNA viruses that is indispensable for replicating the genome as well as for carrying out transcription. The core structural features of RdRps are conserved, despite the divergence in their sequences. The structure of RdRp resembles that of a cupped right hand and consists of fingers, palm and thumb subdomains. The catalysis involves the participation of conserved aspartates and divalent metal ions. Complexes of RdRps with substrates, inhibitors and metal ions provide a comprehensive view of their functional mechanism and offer valuable insights regarding the development of antivirals. In this article, we provide an overview of the structural aspects of RdRps and their complexes from the Group III, IV and V viruses and their structure-based phylogeny.

| S-EPMC5850383 | biostudies-literature

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

Project description: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.

2023-06-27 | GSE229536 | GEO

A guanosine-centric mechanism for RNA chaperone function.

Project description:RNA chaperones are ubiquitous, heterogeneous proteins essential for RNA structural biogenesis and function. We investigated the mechanism of chaperone-mediated RNA folding by following the time-resolved dimerization of the packaging domain of a retroviral RNA at nucleotide resolution. In the absence of the nucleocapsid (NC) chaperone, dimerization proceeded through multiple, slow-folding intermediates. In the presence of NC, dimerization occurred rapidly through a single structural intermediate. The RNA binding domain of heterogeneous nuclear ribonucleoprotein A1 protein, a structurally unrelated chaperone, also accelerated dimerization. Both chaperones interacted primarily with guanosine residues. Replacing guanosine with more weakly pairing inosine yielded an RNA that folded rapidly without a facilitating chaperone. These results show that RNA chaperones can simplify RNA folding landscapes by weakening intramolecular interactions involving guanosine and explain many RNA chaperone activities.

| S-EPMC4338410 | biostudies-literature

Probing Xist RNA structure in cells using Targeted Structure-Seq

Project description:The long non-coding RNA (lncRNA) Xist is a master regulator of X-chromosome inactivation in mammalian cells. Models for how Xist and other lncRNAs function depend on thermodynamically stable secondary and higher-order structures that RNAs can form in the context of a cell. Probing accessible RNA bases can provide data to build models of RNA conformation that provide insight into RNA function, molecular evolution, and modularity. To study the structure of Xist in cells, we built upon recent advances in RNA secondary structure mapping and modeling to develop Targeted Structure-Seq, which combines chemical probing of RNA structure in cells with target-specific massively parallel sequencing. By enriching for signals from the RNA of interest, Targeted Structure-Seq achieves high coverage of the target RNA with relatively few sequencing reads, thus providing a targeted and scalable approach to analyze RNA conformation in cells. We use this approach to probe the full-length Xist lncRNA to develop new models for functional elements within Xist, including the repeat A element in the 5'-end of Xist. This analysis also identified new structural elements in Xist that are evolutionarily conserved, including a new element proximal to the C repeats that is important for Xist function. Examination of dimethylsufate reactivity of Xist lncRNA and 18S rRNA in cells using targeted reverse transcription to determine reactivity, and comparisons with untreated control samples.

2016-02-09 | E-GEOD-67667 | biostudies-arrayexpress

Probing the structural hierarchy and energy landscape of an RNA T-loop hairpin.

Project description:The T-loop motif is an important recurrent RNA structural building block consisting of a U-turn sub-motif and a UA trans Watson-Crick/Hoogsteen base pair. In the presence of a hairpin stem, the UA non-canonical base pair becomes part of the UA-handle motif. To probe the hierarchical organization and energy landscape of the T-loop, we performed replica exchange molecular dynamics (REMD) simulations of the T-loop in isolation and as part of a hairpin. Our simulations reveal that the isolated T-loop adopts coil conformers stabilized by base stacking. The T-loop hairpin shows a highly rugged energy landscape featuring multiple local minima with a transition state for folding consisting of partially zipped states. The U-turn displays a high conformational flexibility both when the T-loop is in isolation and as part of a hairpin. On the other hand, the stability of the UA non-canonical base pair is enhanced in the presence of the UA-handle. This motif is apparently a key component for stabilizing the T-loop, while the U-turn is mostly involved in long-range interaction. Our results suggest that the stability and folding of small RNA motifs are highly dependent on local context.

| S-EPMC2175325 | biostudies-literature

OmicsDI is part of the ELIXIR infrastructure

OmicsDI is an Elixir interoperability service. Learn more ›

Tweets

OmicsDI Databases

PRIDE
PeptideAtlas
MassIVE
JPOST Repository
Physiome Model Repository

EGA
EVA
ENA
LINCS
PAXDB
Cell Collective

MetaboLights
Metabolomics Workbench
MetabolomeExpress
GNPS
BioModels
FAIRDOMHub

ArrayExpress
dbGaP
ExpressionAtlas
GEO
NODE

Information

Databases
Help
API
Contact us
Code on GitHub
Terms of use
Submit Data