Searching for similar sequences in a database via BLAST or a similar tool is one of the most common bioinformatics tasks applied in general, and to non-coding RNAs in particular. However, the results of the search might be difficult to interpret due to the presence of partial matches to the database subject sequences. Here, we present rboAnalyzer - a tool that helps with interpreting sequence search result by (1) extending partial matches into plausible full-length subject sequences, (2) predicting homology of RNAs represented by full-length subject sequences to the query RNA, (3) pooling information across homologous RNAs found in the search results and public databases such as Rfam to predict more reliable secondary structures for all matches, and (4) contextualizing the matches by providing the prediction results and other relevant information in a rich graphical output. Using predicted full-length matches improves secondary structure prediction and makes rboAnalyzer robust with regards to identification of homology. The output of the tool should help the user to reliably characterize non-coding RNAs in BLAST output. The usefulness of the rboAnalyzer and its ability to correctly extend partial matches to full-length is demonstrated on known homologous RNAs. To allow the user to use custom databases and search options, rboAnalyzer accepts any search results as a text file in the BLAST format. The main output is an interactive HTML page displaying the computed characteristics and other context of the matches. The output can also be exported in an appropriate sequence and/or secondary structure formats.

• Keywords
• RNA, RNA homology, database, search, secondary structure, sequence,
• Publication type
• Journal Article MeSH

BACKGROUND: The first systematic study of small non-coding RNAs (sRNA, ncRNA) in Streptomyces is presented. Except for a few exceptions, the Streptomyces sRNAs, as well as the sRNAs in other genera of the Actinomyces group, have remained unstudied. This study was based on sequence conservation in intergenic regions of Streptomyces, localization of transcription termination factors, and genomic arrangement of genes flanking the predicted sRNAs. RESULTS: Thirty-two potential sRNAs in Streptomyces were predicted. Of these, expression of 20 was detected by microarrays and RT-PCR. The prediction was validated by a structure based computational approach. Two predicted sRNAs were found to be terminated by transcription termination factors different from the Rho-independent terminators. One predicted sRNA was identified computationally with high probability as a Streptomyces 6S RNA. Out of the 32 predicted sRNAs, 24 were found to be structurally dissimilar from known sRNAs. CONCLUSION: Streptomyces is the largest genus of Actinomyces, whose sRNAs have not been studied. The Actinomyces is a group of bacterial species with unique genomes and phenotypes. Therefore, in Actinomyces, new unique bacterial sRNAs may be identified. The sequence and structural dissimilarity of the predicted Streptomyces sRNAs demonstrated by this study serve as the first evidence of the uniqueness of Actinomyces sRNAs.

• MeSH
• Algorithms MeSH
• RNA, Bacterial chemistry   genetics   MeSH
• Species Specificity MeSH
• Genome, Bacterial MeSH
• DNA, Intergenic MeSH
• Nucleic Acid Conformation MeSH
• Models, Molecular MeSH
• RNA, Untranslated chemistry   genetics   MeSH
• Reverse Transcriptase Polymerase Chain Reaction MeSH
• Base Sequence MeSH
• Oligonucleotide Array Sequence Analysis MeSH
• Streptomyces coelicolor genetics   MeSH
• Streptomyces genetics   MeSH
• Terminator Regions, Genetic MeSH
• Computational Biology MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Validation Study MeSH
• Names of Substances
• RNA, Bacterial MeSH
• DNA, Intergenic MeSH
• RNA, Untranslated MeSH

In this review I focus on the role of splicing in long non-coding RNA (lncRNA) life. First, I summarize differences between the splicing efficiency of protein-coding genes and lncRNAs and discuss why non-coding RNAs are spliced less efficiently. In the second half of the review, I speculate why splice sites are the most conserved sequences in lncRNAs and what additional roles could splicing play in lncRNA metabolism. I discuss the hypothesis that the splicing machinery can, besides its dominant role in intron removal and exon joining, protect cells from undesired transcripts.

• Keywords
• SR proteins, large intervening non-coding RNA, snRNP, spliceosomes, splicing,
• MeSH
• RNA, Long Noncoding * genetics   MeSH
• RNA Splicing MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• RNA, Long Noncoding * MeSH

Coat protein (CP) coding regions of six Potato mop-top virus (PMTV) isolates from the Czech Republic and Denmark (54-10, 54-11, 54-15, 54-19, Korneta and Pacov) were sequenced. Comparison of the obtained nucleotide sequences as well as alignment of the deduced amino acid sequences were performed. The obtained results showed that the isolates from different parts of Europe seem to have highly conserved coding regions which is unexpected for a viral RNA genome known for its high mutation rate. Thus considerable differences in virulence and significant variation in biological properties of these isolates should not be attributed to CP but to some other part of the genome.

• MeSH
• Cloning, Molecular MeSH
• Molecular Sequence Data MeSH
• Plant Diseases virology   MeSH
• Open Reading Frames genetics   MeSH
• Reverse Transcriptase Polymerase Chain Reaction MeSH
• Plant Viruses genetics   isolation & purification   MeSH
• Amino Acid Sequence MeSH
• Base Sequence MeSH
• Sequence Alignment MeSH
• Solanum tuberosum virology   MeSH
• Capsid Proteins genetics   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Capsid Proteins MeSH

Non-coding RNAs (ncRNAs) are regulatory molecules encoded in the intergenic or intragenic regions of the genome. In prokaryotes, biocomputational identification of homologs of known ncRNAs in other species often fails due to weakly evolutionarily conserved sequences, structures, synteny and genome localization, except in the case of evolutionarily closely related species. To eliminate results from weak conservation, we focused on RNA structure, which is the most conserved ncRNA property. Analysis of the structure of one of the few well-studied bacterial ncRNAs, 6S RNA, demonstrated that unlike optimal and consensus structures, suboptimal structures are capable of capturing RNA homology even in divergent bacterial species. A computational procedure for the identification of homologous ncRNAs using suboptimal structures was created. The suggested procedure was applied to strongly divergent bacterial species and was capable of identifying homologous ncRNAs.

• MeSH
• RNA, Bacterial chemistry   MeSH
• Nucleic Acid Conformation MeSH
• Molecular Sequence Data MeSH
• Mycobacterium genetics   MeSH
• RNA, Untranslated chemistry   MeSH
• Base Sequence MeSH
• Sequence Homology, Nucleic Acid MeSH
• Streptomyces genetics   MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• 6S RNA MeSH Browser
• RNA, Bacterial MeSH
• RNA, Untranslated MeSH

The oocyte-to-embryo transition (OET) transforms a differentiated gamete into pluripotent blastomeres. The accompanying maternal-zygotic RNA exchange involves remodeling of the long non-coding RNA (lncRNA) pool. Here, we used next generation sequencing and de novo transcript assembly to define the core population of 1,600 lncRNAs expressed during the OET (lncRNAs). Relative to mRNAs, OET lncRNAs were less expressed and had shorter transcripts, mainly due to fewer exons and shorter 5' terminal exons. Approximately half of OET lncRNA promoters originated in retrotransposons suggesting their recent emergence. Except for a small group of ubiquitous lncRNAs, maternal and zygotic lncRNAs formed two distinct populations. The bulk of maternal lncRNAs was degraded before the zygotic genome activation. Interestingly, maternal lncRNAs seemed to undergo cytoplasmic polyadenylation observed for dormant mRNAs. We also identified lncRNAs giving rise to trans-acting short interfering RNAs, which represent a novel lncRNA category. Altogether, we defined the core OET lncRNA transcriptome and characterized its remodeling during early development. Our results are consistent with the notion that rapidly evolving lncRNAs constitute signatures of cells-of-origin while a minority plays an active role in control of gene expression across OET. Our data presented here provide an excellent source for further OET lncRNA studies.

• Keywords
• endo-siRNA, lncRNA, oocyte, polyadenylation, zygote,
• MeSH
• Blastomeres metabolism   MeSH
• Embryo, Mammalian metabolism   MeSH
• Mice MeSH
• Oocytes metabolism   MeSH
• RNA, Long Noncoding genetics   metabolism   MeSH
• Sequence Analysis, RNA MeSH
• Gene Expression Profiling MeSH
• High-Throughput Nucleotide Sequencing MeSH
• Gene Expression Regulation, Developmental * MeSH
• Animals MeSH
• Check Tag
• Mice MeSH
• Animals MeSH
• Publication type
• Journal Article MeSH
• Names of Substances
• RNA, Long Noncoding MeSH

For the many years, the central dogma of molecular biology has been that RNA functions mainly as an informational intermediate between a DNA sequence and its encoded protein. But one of the great surprises of modern biology was the discovery that protein-coding genes represent less than 2% of the total genome sequence, and subsequently the fact that at least 90% of the human genome is actively transcribed. Thus, the human transcriptome was found to be more complex than a collection of protein-coding genes and their splice variants. Although initially argued to be spurious transcriptional noise or accumulated evolutionary debris arising from the early assembly of genes and/or the insertion of mobile genetic elements, recent evidence suggests that the non-coding RNAs (ncRNAs) may play major biological roles in cellular development, physiology and pathologies. NcRNAs could be grouped into two major classes based on the transcript size; small ncRNAs and long ncRNAs. Each of these classes can be further divided, whereas novel subclasses are still being discovered and characterized. Although, in the last years, small ncRNAs called microRNAs were studied most frequently with more than ten thousand hits at PubMed database, recently, evidence has begun to accumulate describing the molecular mechanisms by which a wide range of novel RNA species function, providing insight into their functional roles in cellular biology and in human disease. In this review, we summarize newly discovered classes of ncRNAs, and highlight their functioning in cancer biology and potential usage as biomarkers or therapeutic targets.

• MeSH
• Humans MeSH
• Neoplasms genetics   MeSH
• RNA, Untranslated genetics   MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• RNA, Untranslated MeSH

Non-coding RNAs (ncRNAs) are nucleotide sequences that are known to assume regulatory roles previously thought to be reserved for proteins. Their functions include the regulation of protein activity and localization and the organization of subcellular structures. Sequencing studies have now identified thousands of ncRNAs encoded within the prokaryotic and eukaryotic genomes, leading to advances in several fields including parasitology. ncRNAs play major roles in several aspects of vector-host-pathogen interactions. Arthropod vector ncRNAs are secreted through extracellular vesicles into vertebrate hosts to counteract host defense systems and ensure arthropod survival. Conversely, hosts can use specific ncRNAs as one of several strategies to overcome arthropod vector invasion. In addition, pathogens transmitted through vector saliva into vertebrate hosts also possess ncRNAs thought to contribute to their pathogenicity. Recent studies have addressed ncRNAs in vectors or vertebrate hosts, with relatively few studies investigating the role of ncRNAs derived from pathogens and their involvement in establishing infections, especially in the context of vector-borne diseases. This Review summarizes recent data focusing on pathogen-derived ncRNAs and their role in modulating the cellular responses that favor pathogen survival in the vertebrate host and the arthropod vector, as well as host ncRNAs that interact with vector-borne pathogens.

• Keywords
• Host–pathogen interactions, Non-coding RNAs, Vector-borne infection,
• MeSH
• Arthropod Vectors MeSH
• Eukaryotic Cells MeSH
• Disease Vectors * MeSH
• Host-Pathogen Interactions genetics   MeSH
• RNA, Untranslated * genetics   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Review MeSH
• Names of Substances
• RNA, Untranslated * MeSH

The short stature homeobox-containing (SHOX) is the most frequently analysed gene in patients classified as short stature patients (ISS) or diagnosed with Leri-Weill dyschondrosteosis (LWD), Langer mesomelic dysplasia (LMD), or Madelung deformity (MD). However, clinical testing of this gene focuses primarily on single nucleotide variants (SNV) in its coding sequences and copy number variants (CNV) overlapping SHOX gene. This review summarizes the clinical impact of variants in noncoding regions of SHOX. RECENT FINDINGS: CNV extending exclusively into the regulatory elements (i.e., not interrupting the coding sequence) are found more frequently in downstream regulatory elements of SHOX. Further, duplications are more frequent than deletions. Interestingly, downstream duplications are more common than deletions in patients with ISS or LWD but no such differences exist for upstream CNV. Moreover, the presence of specific CNVs in the patient population suggests the involvement of additional unknown factors. Some of its intronic variants, notably NM_000451.3(SHOX):c.-9delG and c.-65C>A in the 5'UTR, have unclear clinical roles. However, these intronic SNV may increase the probability that other CNV will arise de novo in the SHOX gene based on homologous recombination or incorrect splicing of mRNA. SUMMARY: This review highlights the clinical impact of noncoding changes in the SHOX gene and the need to apply new technologies and genotype-phenotype correlation in their analysis.

• Keywords
• CNV, ISS, LWD, Non-coding region, SHOX, SNV,
• MeSH
• Phenotype MeSH
• Genetic Variation * MeSH
• Haploinsufficiency genetics   MeSH
• DNA, Intergenic genetics   MeSH
• Humans MeSH
• Short Stature Homeobox Protein genetics   MeSH
• Gene Expression Regulation MeSH
• Check Tag
• Humans MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• DNA, Intergenic MeSH
• Short Stature Homeobox Protein MeSH

The interactions between mitochondria and nucleus substantially influence plant development, stress response and morphological features. The prominent example of a mitochondrial-nuclear interaction is cytoplasmic male sterility (CMS), when plants produce aborted anthers or inviable pollen. The genes responsible for CMS are located in mitochondrial genome, but their expression is controlled by nuclear genes, called fertility restorers. Recent explosion of high-throughput sequencing methods enabled to study transcriptomic alterations in the level of non-coding RNAs under CMS biogenesis. We summarize current knowledge of the role of nucleus encoded regulatory non-coding RNAs (long non-coding RNA, microRNA as well as small interfering RNA) in CMS. We also focus on the emerging data of non-coding RNAs encoded by mitochondrial genome and their possible involvement in mitochondrial-nuclear interactions and CMS development.

• Keywords
• cytoplasmic male sterility, gene expression, global transcriptome, non-coding RNA, pollen development,
• MeSH
• Self-Incompatibility in Flowering Plants genetics   MeSH
• Magnoliopsida physiology   MeSH
• Genes, Mitochondrial MeSH
• RNA, Untranslated genetics   metabolism   MeSH
• Plant Infertility genetics   MeSH
• Pollen genetics   physiology   MeSH
• Genes, Plant MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• RNA, Untranslated MeSH