scholarly journals RNA Structure Elements Conserved between Mouse and 59 Other Vertebrates

Genes ◽  
2018 ◽  
Vol 9 (8) ◽  
pp. 392 ◽  
Author(s):  
Bernhard Thiel ◽  
Roman Ochsenreiter ◽  
Veerendra Gadekar ◽  
Andrea Tanzer ◽  
Ivo L. Hofacker
Keyword(s):  
Rna Structure ◽  
Noncoding Rnas ◽  
Low Complexity ◽  
Structure Alignment ◽  
Rna Structures ◽  
Protein Coding ◽  
Small Noncoding Rnas ◽  
Potential Structure ◽  
Intergenic Regions ◽  
Candidate Loci

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).

scholarly journals Bacterial Noncoding RNAs Excised from within Protein-Coding Transcripts

mBio ◽  
2018 ◽  
Vol 9 (5) ◽  
Author(s):  
Daniel Dar ◽  
Rotem Sorek
Keyword(s):  
Expression Patterns ◽  
Noncoding Rnas ◽  
Large Set ◽  
Rna Structures ◽  
Protein Coding ◽  
Small Noncoding Rnas ◽  
Coding Regions ◽  
Protein Coding Genes ◽  
Evolutionarily Conserved ◽  
Intergenic Regions

ABSTRACT Prokaryotic genomes encode a plethora of small noncoding RNAs (ncRNAs) that fine-tune the expression of specific genes. The vast majority of known bacterial ncRNAs are encoded from within intergenic regions, where their expression is controlled by promoter and terminator elements, similarly to protein-coding genes. In addition, recent studies have shown that functional ncRNAs can also be derived from gene 3′ untranslated regions (3′UTRs) via an alternative biogenesis pathway, in which the ncRNA segment is separated from the mRNA via RNase cleavage. Here, we report the detection of a large set of decay-generated noncoding RNAs (decRNAs), many of which are completely embedded within protein-coding mRNA regions rather than in the UTRs. We show that these decRNAs are “carved out” of the mRNA through the action of RNase E and that they are predicted to fold into highly stable RNA structures, similar to those of known ncRNAs. A subset of these decRNAs is predicted to interact with Hfq or ProQ or both, which act as ncRNA chaperones, and some decRNAs display evolutionarily conserved sequences and conserved expression patterns between different species. These results suggest that mRNA protein-coding regions may harbor a large set of potentially functional small RNAs. IMPORTANCE Bacteria and archaea utilize regulatory small noncoding RNAs (ncRNAs) to control the expression of specific genetic programs. These ncRNAs are almost exclusively encoded within intergenic regions and are independently transcribed. Here, we report on a large set ncRNAs that are “carved out” from within the protein-coding regions of Escherichia coli mRNAs by cellular RNases. These protected mRNA fragments fold into energetically stable RNA structures, reminiscent of those of intergenic regulatory ncRNAs. In addition, a subset of these ncRNAs coprecipitate with the major ncRNA chaperones Hfq and ProQ and display evolutionarily conserved sequences and conserved expression patterns between different bacterial species. Our data suggest that protein-coding genes can potentially act as a reservoir of regulatory ncRNAs.

scholarly journals Genes for Small, Noncoding RNAs under Sporulation Control in Bacillus subtilis

2006 ◽  
Vol 188 (2) ◽  
pp. 532-541 ◽  
Author(s):  
Jessica M. Silvaggi ◽  
John B. Perkins ◽  
Richard Losick
Keyword(s):  
Bacillus Subtilis ◽  
Sigma Factor ◽  
Transcriptional Profiling ◽  
Noncoding Rnas ◽  
Specific Gene ◽  
Cell Compartment ◽  
Protein Coding ◽  
Small Noncoding Rnas ◽  
Indirect Control ◽  
Intergenic Regions

ABSTRACT The process of sporulation in the bacterium Bacillus subtilis is known to involve the programmed activation of several hundred protein-coding genes. Here we report the discovery of previously unrecognized genes under sporulation control that specify small, non-protein-coding RNAs (sRNAs). Genes for sRNAs were identified by transcriptional profiling with a microarray bearing probes for intergenic regions in the genome and by use of a comparative genomics algorithm that predicts regions of conserved RNA secondary structure. The gene for one such sRNA, SurA, which is located in the region between yndK and yndL, was induced at the start of development under the indirect control of the master regulator for entry into sporulation, Spo0A. The gene for a second sRNA, SurC, located in the region between dnaJ and dnaK, was switched on at a late stage of sporulation by the RNA polymerase sigma factor σK, which directs gene transcription in the mother cell compartment of the developing sporangium. Finally, a third intergenic region, that between polC and ylxS, which specified several sRNAs, including two transcripts produced under the control of the forespore-specific sigma factor σG and a third transcript generated by σK, was identified. Our results indicate that the full repertoire of sporulation-specific gene expression involves the activation of multiple genes for small, noncoding RNAs.

scholarly journals MicroRNomics: a newly emerging approach for disease biology

2008 ◽  
Vol 33 (2) ◽  
pp. 139-147 ◽  
Author(s):  
Chunxiang Zhang
Keyword(s):  
Gene Expression ◽  
Genomic Medicine ◽  
Noncoding Rnas ◽  
Cellular Tissue ◽  
Tissue Type ◽  
Regulation Of Expression ◽  
Protein Coding ◽  
Small Noncoding Rnas ◽  
Disease Biology ◽  
Genomic Scale

Genomic evidence reveals that gene expression in humans is precisely controlled in cellular, tissue-type, temporal, and condition-specific manners. Completely understanding the regulatory mechanisms of gene expression is therefore one of the most important issues in genomic medicine. Surprisingly, recent analyses of the human and animal genomes have demonstrated that the majority of RNA transcripts are relatively small, noncoding RNAs (sncRNAs), rather than large, protein coding message RNAs (mRNAs). Moreover, these sncRNAs may represent a novel important layer of regulation for gene expression. The most important breakthrough in this new area is the discovery of microRNAs (miRNAs). miRNAs comprise a novel class of endogenous, small, noncoding RNAs that negatively regulate gene expression via degradation or translational inhibition of their target mRNAs. As a group, miRNAs may directly regulate ∼30% of the genes in the human genome. In keeping with the nomenclature of RNomics, which is to study sncRNAs on the genomic scale, “microRNomics” is coined here to describe a novel subdiscipline of genomics that studies the identification, expression, biogenesis, structure, regulation of expression, targets, and biological functions of miRNAs on the genomic scale. A growing body of exciting evidence suggests that miRNAs are important regulators of cell differentiation, proliferation/growth, mobility, and apoptosis. These miRNAs therefore play important roles in development and physiology. Consequently, dysregulation of miRNA function may lead to human diseases such as cancer, cardiovascular disease, liver disease, immune dysfunction, and metabolic disorders. microRNomics may be a newly emerging approach for human disease biology.

scholarly journals RMalign: an RNA structural alignment tool based on a size independent scoring function

2018 ◽  
Author(s):  
Jinfang Zheng ◽  
Juan Xie ◽  
Xu Hong ◽  
Shiyong Liu
Keyword(s):  
Phase Transition ◽  
Rna Structure ◽  
State Of The Art ◽  
Structural Alignment ◽  
Complex Structure ◽  
3D Structure ◽  
Scoring Function ◽  
Structure Alignment ◽  
Rna Structures ◽  
Transition Points

ABSTRACTRNA-protein 3D complex structure prediction is still challenging. Recently, a template-based approach PRIME is proposed in our team to build RNA-protein complex 3D structure models with a higher success rate than computational docking software. However, scoring function of RNA alignment algorithm SARA in PRIME is size-dependent, which limits its ability to detect templates in some cases. Herein, we developed a novel RNA 3D structural alignment approach RMalign, which is based on a size-independent scoring function RMscore. The parameter in RMscore is then optimized in randomly selected RNA pairs and phase transition points (from dissimilar to similar) are determined in another randomly selected RNA pairs. In tRNA benchmarking, the precision of RMscore is higher than that of SARAscore (0.8771 and 0.7766, respectively) with phase transition points. In balance-FSCOR benchmarking, RMalign performed as good as ESA-RNA with a non-normalized score measuring RNA structure similarity. In balance-x-FSCOR benchmarking, RMalign achieves much better than a state-of-the-art RNA 3D structural alignment approach SARA due to a size-independent scoring function. Taking the advantage of RMalign, we update our RNA-protein modeling approach PRIME to version 2.0. The PRIME2.0 significantly improves about 10% success rate than PRIME.Author summaryRNA structures are important for RNA functions. With the increasing of RNA structures in PDB, RNA 3D structure alignment approaches have been developed. However, the scoring function which is used for measuring RNA structural similarity is still length dependent. This shortcoming limits its ability to detect RNA structure templates in modeling RNA structure or RNA-protein 3D complex structure. Thus, we developed a length independent scoring function RMscore to enhance the ability to detect RNA structure homologs. The benchmarking data shows that RMscore can distinct the similar and dissimilar RNA structure effectively. RMscore should be a useful scoring function in modeling RNA structures for the biological community. Based on RMscore, we develop an RNA 3D structure alignment RMalign. In both RNA structure and function classification benchmarking, RMalign obtains as good as or even better performance than the state-of-the-art approaches. With a length independent scoring function RMscore, RMalign should be useful for the modeling RNA structures. Based on above results, we update PRIME to PRIME2.0. We provide a more accurate RNA-protein 3D complex structure modeling tool PRIME2.0 which should be useful for the biological community.

scholarly journals RNA secondary structure prediction using an ensemble of two-dimensional deep neural networks and transfer learning

2019 ◽  
Vol 10 (1) ◽  
Author(s):  
Jaswinder Singh ◽  
Jack Hanson ◽  
Kuldip Paliwal ◽  
Yaoqi Zhou
Keyword(s):  
Secondary Structure ◽  
Transfer Learning ◽  
Rna Structure ◽  
Structure Prediction ◽  
Secondary Structure Prediction ◽  
Noncoding Rnas ◽  
Rna Structures ◽  
Base Pairs ◽  
Functional Annotations ◽  
Model Training

AbstractThe majority of our human genome transcribes into noncoding RNAs with unknown structures and functions. Obtaining functional clues for noncoding RNAs requires accurate base-pairing or secondary-structure prediction. However, the performance of such predictions by current folding-based algorithms has been stagnated for more than a decade. Here, we propose the use of deep contextual learning for base-pair prediction including those noncanonical and non-nested (pseudoknot) base pairs stabilized by tertiary interactions. Since only $$<$$<250 nonredundant, high-resolution RNA structures are available for model training, we utilize transfer learning from a model initially trained with a recent high-quality bpRNA dataset of $$> $$>10,000 nonredundant RNAs made available through comparative analysis. The resulting method achieves large, statistically significant improvement in predicting all base pairs, noncanonical and non-nested base pairs in particular. The proposed method (SPOT-RNA), with a freely available server and standalone software, should be useful for improving RNA structure modeling, sequence alignment, and functional annotations.

Long and small noncoding RNAs during oocyte-to-embryo transition in mammals

2017 ◽  
Vol 45 (5) ◽  
pp. 1117-1124 ◽  
Author(s):  
Petr Svoboda
Keyword(s):  
Noncoding Rna ◽  
Transcriptional Control ◽  
Noncoding Rnas ◽  
Rna Degradation ◽  
Early Embryo ◽  
Protein Coding ◽  
Small Noncoding Rnas ◽  
Major Genome ◽  
Silencing Pathways ◽  
And Function

Oocyte-to-embryo transition is a process during which an oocyte ovulates, is fertilized, and becomes a developing embryo. It involves the first major genome reprogramming event in life of an organism where gene expression, which gave rise to a differentiated oocyte, is remodeled in order to establish totipotency in blastomeres of an early embryo. This remodeling involves replacement of maternal RNAs with zygotic RNAs through maternal RNA degradation and zygotic genome activation. This review is focused on expression and function of long noncoding RNAs (lncRNAs) and small RNAs during oocyte-to-embryo transition in mammals. LncRNAs are an assorted rapidly evolving collection of RNAs, which have no apparent protein-coding capacity. Their biogenesis is similar to mRNAs including transcriptional control and post-transcriptional processing. Diverse molecular and biological roles were assigned to lncRNAs although most of them probably did not acquire a detectable biological role. Since some lncRNAs serve as precursors for small noncoding regulatory RNAs in RNA silencing pathways, both types of noncoding RNA are reviewed together.

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

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.

scholarly journals SAFB2 enables the processing of suboptimal stem-loop structures in clustered primary miRNA transcripts

2019 ◽  
Author(s):  
Katharina Hutter ◽  
Michael Lohmüller ◽  
Almina Jukic ◽  
Felix Eichin ◽  
Seymen Avci ◽  
...  
Keyword(s):  
Noncoding Rnas ◽  
General Mechanism ◽  
List Type ◽  
Loop Structure ◽  
Stem Loop ◽  
Protein Coding ◽  
Mirna Processing ◽  
Small Noncoding Rnas ◽  
Stem Loop Structure ◽  
Attachment Factor

SummaryMicroRNAs (miRNAs) are small noncoding RNAs that post-transcriptionally silence most protein-coding genes in mammals. They are generated from primary transcripts containing single or multiple clustered stem-loop structures that are thought to be recognized and cleaved by the DGCR8/DROSHA Microprocessor complex as independent units. Contrasting this view, we here report an unexpected mode of processing of a bicistronic cluster of the miR-15 family, miR-15a-16-1. We find that the primary miR-15a stem-loop is a poor Microprocessor substrate and is consequently not processed on its own, but that the presence of the neighboring primary miR-16-1 stem-loop on the same transcript can compensate for this deficiency in cis. Using a CRISPR/Cas9 screen, we identify SAFB2 (scaffold attachment factor B2) as an essential co-factor in this miR-16-1-assisted pri-miR-15 cleavage, and describe SAFB2 as a novel accessory protein of DROSHA. Notably, SAFB2-mediated cluster assistance expands to other clustered pri-miRNAs including miR-15b, miR-92a and miR-181b, indicating a general mechanism. Together, our study reveals an unrecognized function of SAFB2 in miRNA processing and suggests a scenario in which SAFB2 enables the binding and processing of suboptimal DGCR8/DROSHA substrates in clustered primary miRNA transcripts.Highlightsthe primary miR-15a stem-loop structure per se is a poor Microprocessor substratecleavage of pri-miR-15a requires the processing of an additional miRNA stem-loop on the same RNAsequential pri-miRNA processing or “cluster assistance” is mediated by SAFB proteinsSAFB2 associates with the Microprocessor

scholarly journals Pervasiveness of exoribonuclease-resistant RNAs in plant viruses suggests new roles for these conserved RNA structures

2018 ◽  
Author(s):  
Anna-Lena Steckelberg ◽  
Quentin Vicens ◽  
Jeffrey S. Kieft
Keyword(s):  
Plant Viruses ◽  
Untranslated Regions ◽  
Rna Structures ◽  
Protein Coding ◽  
Subgenomic Rnas ◽  
Biochemical Assays ◽  
Intergenic Regions ◽  
Rna Elements ◽  
Folded Rna ◽  
Coding Potential

ABSTRACTExoribonuclease-resistant RNAs (xrRNAs) are discrete folded RNA elements that block the processive degradation of RNA by exoribonucleases. xrRNAs found in the 3′ untranslated regions (UTRs) of animal-infecting flaviviruses and in all three members of the plant-infecting Dianthovirus adopt a complex ring-like fold that blocks the exoribonuclease; this ability gives rise to viral non-coding subgenomic RNAs. The degree to which these folded RNA elements exist in other viruses and in diverse contexts has been unclear. Using computational tools and biochemical assays, we discovered that xrRNA elements are widely found in viruses belonging to the Tombusviridae and Luteoviridae families of plant-infecting RNA viruses, demonstrating their importance and widespread utility. Unexpectedly, many xrRNAs are located in intergenic regions rather than in the 3’UTR and some are associated with the 5′ ends of subgenomic RNAs with protein-coding potential, suggesting that xrRNAs with similar scaffolds are involved in the maturation or maintenance of diverse subgenomic RNAs, not just the ones generated from the 3′UTR.

scholarly journals Comprehensive Identification of Meningococcal Genes and Small Noncoding RNAs Required for Host Cell Colonization

mBio ◽  
2016 ◽  
Vol 7 (4) ◽  
Author(s):  
Elena Capel ◽  
Aldert L. Zomer ◽  
Thomas Nussbaumer ◽  
Christine Bole ◽  
Brigitte Izac ◽  
...  
Keyword(s):  
Endothelial Cells ◽  
Epithelial Cells ◽  
Neisseria Meningitidis ◽  
Host Cell ◽  
Insertion Site ◽  
Noncoding Rnas ◽  
Small Noncoding Rnas ◽  
Transposon Insertion ◽  
Intergenic Regions ◽  
Cell Colonization

ABSTRACTNeisseria meningitidisis a leading cause of bacterial meningitis and septicemia, affecting infants and adults worldwide.N. meningitidisis also a common inhabitant of the human nasopharynx and, as such, is highly adapted to its niche. During bacteremia,N. meningitidisgains access to the blood compartment, where it adheres to endothelial cells of blood vessels and causes dramatic vascular damage. Colonization of the nasopharyngeal niche and communication with the different human cell types is a major issue of theN. meningitidislife cycle that is poorly understood. Here, highly saturated random transposon insertion libraries ofN. meningitidiswere engineered, and the fitness of mutations during routine growth and that of colonization of endothelial and epithelial cells in a flow device were assessed in a transposon insertion site sequencing (Tn-seq) analysis. This allowed the identification of genes essential for bacterial growth and genes specifically required for host cell colonization. In addition, after having identified the small noncoding RNAs (sRNAs) located in intergenic regions, the phenotypes associated with mutations in those sRNAs were defined. A total of 383 genes and 8 intergenic regions containing sRNA candidates were identified to be essential for growth, while 288 genes and 33 intergenic regions containing sRNA candidates were found to be specifically required for host cell colonization.IMPORTANCEMeningococcal meningitis is a common cause of meningitis in infants and adults.Neisseria meningitidis(meningococcus) is also a commensal bacterium of the nasopharynx and is carried by 3 to 30% of healthy humans. Under some unknown circumstances,N. meningitidisis able to invade the bloodstream and cause either meningitis or a fatal septicemia known as purpura fulminans. The onset of symptoms is sudden, and death can follow within hours. Although many meningococcal virulence factors have been identified, the mechanisms that allow the bacterium to switch from the commensal to pathogen state remain unknown. Therefore, we used a Tn-seq strategy coupled to high-throughput DNA sequencing technologies to find genes for proteins used byN. meningitidisto specifically colonize epithelial cells and primary brain endothelial cells. We identified 383 genes and 8 intergenic regions containing sRNAs essential for growth and 288 genes and 33 intergenic regions containing sRNAs required specifically for host cell colonization.

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