Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change

Background  

Non-coding RNAs (ncRNAs) have a multitude of roles in the cell, many of which remain to be discovered. However, it is difficult to detect novel ncRNAs in biochemical screens. To advance biological knowledge, computational methods that can accurately detect ncRNAs in sequenced genomes are therefore desirable. The increasing number of genomic sequences provides a rich dataset for computational comparative sequence analysis and detection of novel ncRNAs.     

Fast prediction of RNA-RNA interaction

Background  

Regulatory antisense RNAs are a class of ncRNAs that regulate gene expression by prohibiting the translation of an mRNA by establishing stable interactions with a target sequence. There is great demand for efficient computational methods to predict the specific interaction between an ncRNA and its target mRNA(s). There are a number of algorithms in the literature which can predict a variety of such interactions - unfortunately at a very high computational cost. Although some existing target prediction approaches are much faster, they are specialized for interactions with a single binding site.     

Directed acyclic graph kernels for structural RNA analysis

Background  

Recent discoveries of a large variety of important roles for non-coding RNAs (ncRNAs) have been reported by numerous researchers. In order to analyze ncRNAs by kernel methods including support vector machines, we propose stem kernels as an extension of string kernels for measuring the similarities between two RNA sequences from the viewpoint of secondary structures. However, applying stem kernels directly to large data sets of ncRNAs is impractical due to their computational complexity.     

Improved accuracy of multiple ncRNA alignment by incorporating structural information into a MAFFT-based framework

Background  

Structural alignment of RNAs is becoming important, since the discovery of functional non-coding RNAs (ncRNAs). Recent studies, mainly based on various approximations of the Sankoff algorithm, have resulted in considerable improvement in the accuracy of pairwise structural alignment. In contrast, for the cases with more than two sequences, the practical merit of structural alignment remains unclear as compared to traditional sequence-based methods, although the importance of multiple structural alignment is widely recognized.     

Identification of cyanobacterial non-coding RNAs by comparative genome analysis

Background  

Whole genome sequencing of marine cyanobacteria has revealed an unprecedented degree of genomic variation and streamlining. With a size of 1.66 megabase-pairs, Prochlorococcus sp. MED4 has the most compact of these genomes and it is enigmatic how the few identified regulatory proteins efficiently sustain the lifestyle of an ecologically successful marine microorganism. Small non-coding RNAs (ncRNAs) control a plethora of processes in eukaryotes as well as in bacteria; however, systematic searches for ncRNAs are still lacking for most eubacterial phyla outside the enterobacteria.     

Systematic identification of non-coding RNA 2,2,7-trimethylguanosine cap structures in <Emphasis Type="Italic">Caenorhabditis elegans</Emphasis>

Background  

The 2,2,7-trimethylguanosine (TMG) cap structure is an important functional characteristic of ncRNAs with critical cellular roles, such as some snRNAs. Here we used immunoprecipitation with both K121 and R1131 anti-TMG antibodies to systematically identify the TMG cap structures for all presently characterized ncRNAs in C. elegans.     

The long noncoding RNA RNCR2 directs mouse retinal cell specification

Background  

Recent work has identified that many long mRNA-like noncoding RNAs (lncRNAs) are expressed in the developing nervous system. Despite their abundance, the function of these ncRNAs has remained largely unexplored. We have investigated the highly abundant lncRNA RNCR2 in regulation of mouse retinal cell differentiation.     

ConStruct: Improved construction of RNA consensus structures

Background  

Aligning homologous non-coding RNAs (ncRNAs) correctly in terms of sequence and structure is an unresolved problem, due to both mathematical complexity and imperfect scoring functions. High quality alignments, however, are a prerequisite for most consensus structure prediction approaches, homology searches, and tools for phylogeny inference. Automatically created ncRNA alignments often need manual corrections, yet this manual refinement is tedious and error-prone.     

A novel representation of RNA secondary structure based on element-contact graphs

Background  

Depending on their specific structures, noncoding RNAs (ncRNAs) play important roles in many biological processes. Interest in developing new topological indices based on RNA graphs has been revived in recent years, as such indices can be used to compare, identify and classify RNAs. Although the topological indices presented before characterize the main topological features of RNA secondary structures, information on RNA structural details is ignored to some degree. Therefore, it is necessity to identify topological features with low degeneracy based on complete and fine-grained RNA graphical representations.     

smyRNA: A Novel Ab Initio ncRNA Gene Finder

Background

Non-coding RNAs (ncRNAs) have important functional roles in the cell: for example, they regulate gene expression by means of establishing stable joint structures with target mRNAs via complementary sequence motifs. Sequence motifs are also important determinants of the structure of ncRNAs. Although ncRNAs are abundant, discovering novel ncRNAs on genome sequences has proven to be a hard task; in particular past attempts for ab initio ncRNA search mostly failed with the exception of tools that can identify micro RNAs.

Methodology/Principal Findings

We present a very general ab initio ncRNA gene finder that exploits differential distributions of sequence motifs between ncRNAs and background genome sequences.

Conclusions/Significance

Our method, once trained on a set of ncRNAs from a given species, can be applied to a genome sequences of other organisms to find not only ncRNAs homologous to those in the training set but also others that potentially belong to novel (and perhaps unknown) ncRNA families. Availability: http://compbio.cs.sfu.ca/taverna/smyrna     

Epstein-Barr Virus-Induced Expression of a Novel Human Vault RNA

Non-protein-coding RNAs (ncRNAs) have recently emerged on the scene of genomic research as prominent players in the regulation of gene expression. Many functionally characterized ncRNAs have been shown to be differentially expressed in various organisms during specific environmental or developmental conditions, thus establishing regulatory networks crucial for shaping cellular life. Here, we show that the expression of vault RNAs (vtRNAs) is specifically up-regulated in human lymphocytes upon infection by γ-herpesviruses, such as the Epstein-Barr virus and Kaposi's sarcoma virus. vtRNAs are ncRNAs that are integral to the vault complex, a gigantic (13 MDa) hollow ribonucleoprotein particle with a thus far elusive biological role. Stimulation of vtRNA expression by the Epstein-Barr virus was evident for all three canonical vtRNAs (hvg1-hvg3) and also for a novel ncRNA candidate, initially termed CBL-3. This ncRNA shares clear primary- and secondary-structure similarities with the three known vtRNAs. Importantly, CBL-3 co-sediments with intact vault particles in density gradients of various human cell lines, thus strongly indicating this ncRNA as a novel, fourth vault-complex-associated RNA.     

The evolution of core proteins involved in microRNA biogenesis

Background  

MicroRNAs (miRNAs) are a recently discovered class of non-coding RNAs (ncRNAs) which play important roles in eukaryotic gene regulation. miRNA biogenesis and activation is a complex process involving multiple protein catalysts and involves the large macromolecular RNAi Silencing Complex or RISC. While phylogenetic analyses of miRNA genes have been previously published, the evolution of miRNA biogenesis itself has been little studied. In order to better understand the origin of miRNA processing in animals and plants, we determined the phyletic occurrences and evolutionary relationships of four major miRNA pathway protein components; Dicer, Argonaute, RISC RNA-binding proteins, and Exportin-5.