Sense overlapping transcripts in IS1341-type transposase genes are functional non-coding RNAs in archaea.
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ABSTRACT:
SUBMITTER: Gomes-Filho JV
PROVIDER: S-EPMC4615843 | biostudies-literature |
REPOSITORIES: biostudies-literature
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Project description:Prokaryotic genomes show a high level of information compaction often with different molecules transcribed from the same locus. Although antisense RNAs have been relatively well studied, RNAs in the same strand, internal RNAs (intraRNAs), are still poorly understood. The question of how common is the translation of overlapping reading frames remains open. We address this question in the model archaeon Halobacterium salinarum. In the present work we used differential RNA-seq (dRNA-seq) in H. salinarum NRC-1 to locate intraRNA signals in subsets of internal transcription start sites (iTSS) and establish the open reading frames associated to them (intraORFs). Using C-terminally flagged proteins, we experimentally observed isoforms accurately predicted by intraRNA translation for kef1, acs3 and orc4 genes. We also recovered from the literature and mass spectrometry databases several instances of protein isoforms consistent with intraRNA translation such as the gas vesicle protein gene gvpC1. We found evidence for intraRNAs in horizontally transferred genes such as the chaperone dnaK and the aerobic respiration related cydA in both H. salinarum and Escherichia coli. Also, intraRNA translation evidence in H. salinarum, E. coli and yeast of a universal elongation factor (aEF-2, fusA and eEF-2) suggests that this is an ancient phenomenon present in all domains of life.
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Project description:Despite hundreds of RNA modifications described to date, only RNA editing results in a change in the nucleotide sequence of RNA molecules compared to the genome. In mammals, two kinds of RNA editing have been described so far, adenosine to inosine (A-to-I) and cytidine to uridine (C-to-U) editing. Recent improvements in RNA sequencing technologies have led to the discovery of a continuously growing number of editing sites. These methods are powerful but not error-free, making routine validation of newly-described editing sites necessary. During one of these validations on DDX58 mRNA, along with A-to-I RNA editing sites, we encountered putative U-to-C editing. These U-to-C edits were present in several cell lines and appeared regulated in response to specific environmental stimuli. The same findings were also observed for the human long intergenic non-coding RNA p21 (hLincRNA-p21). A more in-depth analysis revealed that putative U-to-C edits result from A-to-I editing on overlapping antisense RNAs that are transcribed from the same loci. Such editing events, occurring on overlapping genes transcribed in opposite directions, have recently been demonstrated to be immunogenic and have been linked with autoimmune and immune-related diseases. Our findings, also confirmed by deep transcriptome data, demonstrate that such loci can be recognized simply through the presence of A-to-I and U-to-C mismatches within the same locus, reflective A-to-I editing both in the sense-oriented transcript and in the cis-natural antisense transcript (cis-NAT), implying that such clusters could be a mark of functionally relevant ADAR1 editing events.
| S-EPMC9852825 | biostudies-literature
Project description:Antisense transcription is widespread in bacteria. By base pairing with overlapping sense RNAs, antisense RNAs (asRNA) can form double-stranded RNAs (dsRNA), which are cleaved by RNase III, a dsRNA endoribonuclease. The ectopic expression of plant Tombusvirus p19 in Escherichia coli stabilizes ?21-nucleotide (nt) dsRNA RNase III decay intermediates, which enabled us to characterize otherwise highly unstable asRNA by deep sequencing of p19-captured dsRNA. RNase III-produced small dsRNA were formed at most bacterial genes in the bacterial genome and in a plasmid. We classified the types of asRNA in genomic clusters producing the most abundant p19-captured dsRNA and confirmed RNase III regulation of asRNA and sense RNA decay at three type I toxin-antitoxin loci and at a coding gene, rsd Furthermore, we provide potential evidence for the RNase III-dependent regulation of CspD protein by asRNA. The analysis of p19-captured dsRNA revealed an RNase III sequence preference for AU-rich sequences 3 nucleotides on either side of the cleavage sites and for GC-rich sequences in the 2-nt overhangs. Unexpectedly, GC-rich sequences were enriched in the middle section of p19-captured dsRNA, suggesting some unexpected sequence bias in p19 protein binding. Nonetheless, the ectopic expression of p19 is a sensitive method for identifying antisense transcripts and RNase III cleavage sites in dsRNA formed by overlapping sense and antisense transcripts in bacteria.
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Project description:BackgroundThere is increasing realization that regulation of genes is done partly at the RNA level by sense-antisense binding. Studies typically concentrate on the role of non-coding RNAs in regulating coding RNA. But the majority of transcripts in a cell are likely to be coding. Is it possible that coding RNA might regulate other coding RNA by short perfect sense-antisense binding? Here we compare all well-described human protein coding mRNAs against all others to identify sites 15-25 bp long that could potentially perfectly match sense-antisense.ResultsFrom 24,968 protein coding mRNA RefSeq sequences, none failed to find at least one match in the transcriptome. By randomizations generating artificial transcripts matched for G+C content and length, we found that there are more such trans short sense-antisense pairs than expected. Several further features are consistent with functionality of some of the putative matches. First, transcripts with more potential partners have lower expression levels, and the pair density of tissue specific genes is significantly higher than that of housekeeping genes. Further, the single nucleotide polymorphism density is lower in short pairing regions than it is in flanking regions. We found no evidence that the sense-antisense pairing regions are associated with small RNAs derived from the protein coding genes.ConclusionsOur results are consistent with the possibility of common short perfect sense-antisense pairing between transcripts of protein coding genes.
| S-EPMC2646273 | biostudies-literature
Project description: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.
| S-EPMC6156199 | biostudies-literature
Project description:Non-coding RNAs (ncRNAs) are versatile regulators in cellular networks. While most trans-acting ncRNAs possess well-defined mechanisms that can regulate transcription or translation, they generally lack the ability to directly sense cellular signals. In this work, we describe a set of design principles for fusing ncRNAs to RNA aptamers to engineer allosteric RNA fusion molecules that modulate the activity of ncRNAs in a ligand-inducible way in Escherichia coli. We apply these principles to ncRNA regulators that can regulate translation (IS10 ncRNA) and transcription (pT181 ncRNA), and demonstrate that our design strategy exhibits high modularity between the aptamer ligand-sensing motif and the ncRNA target-recognition motif, which allows us to reconfigure these two motifs to engineer orthogonally acting fusion molecules that respond to different ligands and regulate different targets in the same cell. Finally, we show that the same ncRNA fused with different sensing domains results in a sensory-level NOR gate that integrates multiple input signals to perform genetic logic. These ligand-sensing ncRNA regulators provide useful tools to modulate the activity of structurally related families of ncRNAs, and building upon the growing body of RNA synthetic biology, our ability to design aptamer-ncRNA fusion molecules offers new ways to engineer ligand-sensing regulatory circuits.
| S-EPMC3384300 | biostudies-literature
Project description:The human genome encodes a multitude of different noncoding transcripts that have been tra-ditionally separated on the basis of their lengths into long (>200 nt) or small (<200 nt) noncoding RNAs. The functions, mechanisms of action, and biological relevance of the vast majority of both long and short noncoding transcripts remain unknown. However, according to the functional understanding of the known classes of long and small noncoding RNAs (sncRNAs) that have been shown to play crucial roles in multiple biological processes, it is generally assumed that many unannotated long and small transcripts participate in important cellular functions as well. Nevertheless, direct evidence of functionality is lacking for most noncoding transcripts, especially for sncRNAs that are often dismissed as stable degradation products of longer RNAs. Here, we developed a high-throughput assay to test the functionality of sncRNAs by overexpressing them in human cells. Surprisingly, we found that a significant fraction (>40%) of unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small noncoding transcriptome can harbor multiple func-tional transcripts that warrant future studies.
2023-02-20 | GSE221958 | GEO
Project description:BackgroundIn recent years, a rapidly increasing number of RNA transcripts has been generated by thousands of sequencing projects around the world, creating enormous volumes of transcript data to be analyzed. An important problem to be addressed when analyzing this data is distinguishing between long non-coding RNAs (lncRNAs) and protein coding transcripts (PCTs). Thus, we present a Support Vector Machine (SVM) based method to distinguish lncRNAs from PCTs, using features based on frequencies of nucleotide patterns and ORF lengths, in transcripts.MethodsThe proposed method is based on SVM and uses the first ORF relative length and frequencies of nucleotide patterns selected by PCA as features. FASTA files were used as input to calculate all possible features. These features were divided in two sets: (i) 336 frequencies of nucleotide patterns; and (ii) 4 features derived from ORFs. PCA were applied to the first set to identify 6 groups of frequencies that could most contribute to the distinction. Twenty-four experiments using the 6 groups from the first set and the features from the second set where built to create the best model to distinguish lncRNAs from PCTs.ResultsThis method was trained and tested with human (Homo sapiens), mouse (Mus musculus) and zebrafish (Danio rerio) data, achieving 98.21%, 98.03% and 96.09%, accuracy, respectively. Our method was compared to other tools available in the literature (CPAT, CPC, iSeeRNA, lncRNApred, lncRScan-SVM and FEELnc), and showed an improvement in accuracy by ≈3.00%. In addition, to validate our model, the mouse data was classified with the human model, and vice-versa, achieving ≈97.80% accuracy in both cases, showing that the model is not overfit. The SVM models were validated with data from rat (Rattus norvegicus), pig (Sus scrofa) and fruit fly (Drosophila melanogaster), and obtained more than 84.00% accuracy in all these organisms. Our results also showed that 81.2% of human pseudogenes and 91.7% of mouse pseudogenes were classified as non-coding. Moreover, our method was capable of re-annotating two uncharacterized sequences of Swiss-Prot database with high probability of being lncRNAs. Finally, in order to use the method to annotate transcripts derived from RNA-seq, previously identified lncRNAs of human, gorilla (Gorilla gorilla) and rhesus macaque (Macaca mulatta) were analyzed, having successfully classified 98.62%, 80.8% and 91.9%, respectively.ConclusionsThe SVM method proposed in this work presents high performance to distinguish lncRNAs from PCTs, as shown in the results. To build the model, besides using features known in the literature regarding ORFs, we used PCA to identify features among nucleotide pattern frequencies that contribute the most in distinguishing lncRNAs from PCTs, in reference data sets. Interestingly, models created with two evolutionary distant species could distinguish lncRNAs of even more distant species.
| S-EPMC5648457 | biostudies-literature
Project description:Human genome encodes a multitude of different non-coding transcripts that have been traditionally separated based on their lengths into long or small non-coding RNAs. The vast majority of both long and short non-coding transcripts are not annotated and their functions, mechanisms of action and biological relevance remain unknown. However, based on the functional understanding of the known classes of long and small non-coding RNAs (sncRNAs) that have been shown to play crucial roles in multiple biological processes, it is generally assumed that many unannotated long and small transcripts participate in important cellular functions as well. Still, direct evidence of functionality is lacking for most non-coding transcripts, especially for sncRNAs that are often dismissed as stable degradation products of longer RNAs. Here, we have developed a high-throughput assay to test functionality of sncRNAs based on overexpressing them in human cells. Surprisingly, we found that a significant fraction (> 40%) unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small non-coding transcriptome can harbor multiple functional transcripts that warrant future studies.
2023-02-20 | GSE221954 | GEO
Project description:Human genome encodes a multitude of different non-coding transcripts that have been traditionally separated based on their lengths into long or small non-coding RNAs. The vast majority of both long and short non-coding transcripts are not annotated and their functions, mechanisms of action and biological relevance remain unknown. However, based on the functional understanding of the known classes of long and small non-coding RNAs (sncRNAs) that have been shown to play crucial roles in multiple biological processes, it is generally assumed that many unannotated long and small transcripts participate in important cellular functions as well. Still, direct evidence of functionality is lacking for most non-coding transcripts, especially for sncRNAs that are often dismissed as stable degradation products of longer RNAs. Here, we have developed a high-throughput assay to test functionality of sncRNAs based on overexpressing them in human cells. Surprisingly, we found that a significant fraction (> 40%) unannotated sncRNAs appear to have biological relevance. Furthermore, contrary to the expectation, the potentially functional transcripts are not highly abundant and can be derived from protein-coding mRNAs. These results strongly suggest that the small non-coding transcriptome can harbor multiple functional transcripts that warrant future studies.
2023-02-20 | GSE221956 | GEO