EFFICIENT ANNOTATION OF NON-CODING RNA STRUCTURES INCLUDING PSEUDOKNOTS VIA AUTOMATED FILTERS

The relative prominence of developmental bias versus natural selection is a long standing controversy in evolutionary biology. Here we demonstrate quantitatively that developmental bias is the primary explanation for the occupation of the morphospace of RNA secondary structure (SS) shapes. By using the RNAshapes method to define coarse-grained SS classes, we can directly measure the frequencies that non-coding RNA SS shapes appear in nature. Our main findings are, firstly, that only the most frequent structures appear in nature: The vast majority of possible structures in the morphospace have not yet been explored. Secondly, and perhaps more surprisingly, these frequencies are accurately predicted by the likelihood that structures appear upon uniform random sampling of sequences. The ultimate cause of these patterns is not natural selection, but rather strong phenotype bias in the RNA genotype-phenotype (GP) map, a type of developmental bias that tightly constrains evolutionary dynamics to only act within a reduced subset of structures which are easy to “find”.

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NOVEL INTRONIC NON-CODING RNAS CONTRIBUTE TO MAINTENANCE OF PHENOTYPE IN SACCHAROMYCES CEREVISIAE

10.1101/033076 ◽

2015 ◽

Author(s):

Katarzyna B Hooks ◽

Samina Naseeb ◽

Sam Griffiths-Jones ◽

Daniela Delneri

Keyword(s):

Saccharomyces Cerevisiae ◽

Rna Structure ◽

Structure Prediction ◽

De Novo ◽

Intron Retention ◽

Intron Loss ◽

Common Belief ◽

Rna Structures ◽

Protein Coding ◽

Non Coding Rna

The Saccharomyces cerevisiae genome has undergone extensive intron loss during its evolutionary history. It has been suggested that the few remaining introns (in only 5% of protein-coding genes) are retained because of their impact on function under stress conditions. Here, we explore the possibility that novel non-coding RNA structures (ncRNAs) are embedded within intronic sequences and are contributing to phenotype and intron retention in yeast. We employed de novo RNA structure prediction tools to screen intronic sequences in S. cerevisiae and 36 other fungi. We identified and validated 19 new intronic RNAs via RNAseq and RT-PCR. Contrary to common belief that excised introns are rapidly degraded, we found that, in six cases, the excised introns were maintained intact in the cells. In other two cases we showed that the ncRNAs were further processed from their introns. RNAseq analysis confirmed higher expression of introns in the ribosomial protein genes containing predicted RNA structures. We deleted the novel intronic RNA structure within the GLC7 intron and showed that this predicted ncRNA, rather than the intron itself, is responsible for the cell???s ability to respond to salt stress. We also showed a direct association between the presence of the intronic ncRNA and GLC7 expression. Overall, these data support the notion that some introns may have been maintained in the genome because they harbour functional ncRNAs.

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Rapid Annotation of Non-coding RNA Structures with a Parameterized Filtering Approach

Intelligent Computing Theories and Methodologies - Lecture Notes in Computer Science ◽

10.1007/978-3-319-22186-1_54 ◽

2015 ◽

pp. 542-553

Author(s):

Yinglei Song ◽

Junfeng Qu ◽

Chunmei Liu

Keyword(s):

Rna Structures ◽

Non Coding Rna ◽

Filtering Approach

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LocalSTAR3D: a local stack-based RNA 3D structural alignment tool

Nucleic Acids Research ◽

10.1093/nar/gkaa453 ◽

2020 ◽

Author(s):

Xiaoli Chen ◽

Nabila Shahnaz Khan ◽

Shaojie Zhang

Keyword(s):

Structural Alignment ◽

Data Bank ◽

Local Alignment ◽

Global Alignment ◽

Rna Structures ◽

3D Structures ◽

Rna Molecules ◽

Non Coding Rna ◽

Alignment Tool ◽

Wide Range

Abstract A fast-growing number of non-coding RNA structures have been resolved and deposited in Protein Data Bank (PDB). In contrast to the wide range of global alignment and motif search tools, there is still a lack of local alignment tools. Among all the global alignment tools for RNA 3D structures, STAR3D has become a valuable tool for its unprecedented speed and accuracy. STAR3D compares the 3D structures of RNA molecules using consecutive base-pairs (stacks) as anchors and generates an optimal global alignment. In this article, we developed a local RNA 3D structural alignment tool, named LocalSTAR3D, which was extended from STAR3D and designed to report multiple local alignments between two RNAs. The benchmarking results show that LocalSTAR3D has better accuracy and coverage than other local alignment tools. Furthermore, the utility of this tool has been demonstrated by rediscovering kink-turn motif instances, conserved domains in group II intron RNAs, and the tRNA mimicry of IRES RNAs.

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Discovery of 17 conserved structural RNAs in fungi

10.1101/2021.02.01.429235 ◽

2021 ◽

Author(s):

William Gao ◽

Thomas A. Jones ◽

Elena Rivas

Keyword(s):

Rna Structure ◽

Genomic Region ◽

Homology Search ◽

Rna Structures ◽

Sequence Alignments ◽

Multiple Sequence ◽

Multiple Sequence Alignments ◽

Metabolic Genes ◽

Non Coding Rna ◽

Non Coding Rnas

AbstractMany non-coding RNAs with known functions are structurally conserved: their intramolecular secondary and tertiary interactions are maintained across evolutionary time. Consequently, the presence of conserved structure in multiple sequence alignments can be used to identify candidate functional non-coding RNAs. Here, we present a bioinformatics method that couples iterative homology search with covariation analysis to assess whether a genomic region has evidence of conserved RNA structure. We used this method to examine all unannotated regions of five well-studied fungal genomes (Saccharomyces cerevisiae, Candida albicans, Neurospora crassa, Aspergillus fumigatus, and Schizosaccharomyces pombe). We identified 17 novel structurally conserved non-coding RNA candidates, which include 4 H/ACA box small nucleolar RNAs, 4 intergenic RNAs, and 9 RNA structures located within the introns and untranslated regions (UTRs) of mRNAs. For the two structures in the 3′ UTRs of the metabolic genes GLY1 and MET13, we performed experiments that provide evidence against them being eukaryotic riboswitches.

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Genetic impacts on thermostability of onco-lncRNA HOTAIR during the development and progression of endometriosis

PLoS ONE ◽

10.1371/journal.pone.0248168 ◽

2021 ◽

Vol 16 (3) ◽

pp. e0248168

Author(s):

Cherry Yin-Yi Chang ◽

Chung-Chen Tseng ◽

Ming-Tsung Lai ◽

An-Jen Chiang ◽

Lun-Chien Lo ◽

...

Keyword(s):

Statistical Significance ◽

Net Energy ◽

Nucleotide Polymorphisms ◽

Rna Structures ◽

Single Nucleotide ◽

Non Coding Rna ◽

And Migration ◽

Long Non Coding Rna ◽

Lncrna Hotair

HOTAIR is a well-known long non-coding RNA (lncRNA) involved in various cellular signaling, whereas its functional impacts on endometriosis development are still largely unknown. To this end, six potential functional single nucleotide polymorphisms (SNPs) in HOTAIR, with minor allele frequencies more than 10% in Han population and altered net energy of RNA structures larger than 0.5 kcal/mol, were selected for genotyping study. The study included 207 endometriosis patients and 200 healthy women. Genetic substitutions at rs1838169 and rs17720428 were frequently found in endometriosis patients, and rs1838169 showed statistical significance (p = 0.0174). The G-G (rs1838169-rs17720428) haplotype showed the most significant association with endometriosis (p < 0.0001) with enhanced HOTAIR stability, and patients who harbor such haplotype tended to show higher CA125. Data mining further revealed higher mRNA HOTAIR levels in the endometria of patients with severe endometriosis which consistently showed reduced HOXD10 and HOXA5 levels. HOTAIR knockdown with specific shRNAs down-regulated cell proliferation and migration with the induction of HOXD10 and HOXA5 expression in human ovarian clear cancer cells. Our study therefore provided evidence to indicate a prominent role of HOTAIR in promoting endometriosis, which could be used as a potential target for clinical applications.

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R2DT: computational framework for template-based RNA secondary structure visualisation across non-coding RNA types

10.1101/2020.09.10.290924 ◽

2020 ◽

Cited By ~ 2

Author(s):

Blake A. Sweeney ◽

David Hoksza ◽

Eric P. Nawrocki ◽

Carlos Eduardo Ribas ◽

Fábio Madeira ◽

...

Keyword(s):

Large Subunit ◽

3D Structure ◽

Rna Structures ◽

Computational Framework ◽

Link Type ◽

Comprehensive Method ◽

Non Coding Rna ◽

Wide Range ◽

2D Structure ◽

Non Coding Rnas

AbstractNon-coding RNAs (ncRNA) are essential for all life, and the functions of many ncRNAs depend on their secondary (2D) and tertiary (3D) structure. Despite proliferation of 2D visualisation software, there is a lack of methods for automatically generating 2D representations in consistent, reproducible, and recognisable layouts, making them difficult to construct, compare and analyse. Here we present R2DT, a comprehensive method for visualising a wide range of RNA structures in standardised layouts. R2DT is based on a library of 3,632 templates representing the majority of known structured RNAs, from small RNAs to the large subunit ribosomal RNA. R2DT has been applied to ncRNA sequences from the RNAcentral database and produced >13 million diagrams, creating the world’s largest RNA 2D structure dataset. The software is freely available at https://github.com/rnacentral/R2DT and a web server is found at https://rnacentral.org/r2dt.

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