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1.  Identification of cyanobacterial non-coding RNAs by comparative genome analysis 
Genome Biology  2005;6(9):R73.
The first genome-wide and systematic screen for non-coding RNAs (ncRNAs) in cyanobacteria. Several ncRNAs were computationally predicted and their presence was biochemically verified. These ncRNAs may have regulatory functions, and each shows a distinct phylogenetic distribution.
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.
Based on a computational prediction we show the presence of several ncRNAs (cyanobacterial functional RNA or Yfr) in several different cyanobacteria of the Prochlorococcus-Synechococcus lineage. Some ncRNA genes are present only in two or three of the four strains investigated, whereas the RNAs Yfr2 through Yfr5 are structurally highly related and are encoded by a rapidly evolving gene family as their genes exist in different copy numbers and at different sites in the four investigated genomes. One ncRNA, Yfr7, is present in at least seven other cyanobacteria. In addition, control elements for several ribosomal operons were predicted as well as riboswitches for thiamine pyrophosphate and cobalamin.
This is the first genome-wide and systematic screen for ncRNAs in cyanobacteria. Several ncRNAs were both computationally predicted and their presence was biochemically verified. These RNAs may have regulatory functions and each shows a distinct phylogenetic distribution. Our approach can be applied to any group of microorganisms for which more than one total genome sequence is available for comparative analysis.
PMCID: PMC1242208  PMID: 16168080
2.  Biocomputational prediction of non-coding RNAs in model cyanobacteria 
BMC Genomics  2009;10:123.
In bacteria, non-coding RNAs (ncRNA) are crucial regulators of gene expression, controlling various stress responses, virulence, and motility. Previous work revealed a relatively high number of ncRNAs in some marine cyanobacteria. However, for efficient genetic and biochemical analysis it would be desirable to identify a set of ncRNA candidate genes in model cyanobacteria that are easy to manipulate and for which extended mutant, transcriptomic and proteomic data sets are available.
Here we have used comparative genome analysis for the biocomputational prediction of ncRNA genes and other sequence/structure-conserved elements in intergenic regions of the three unicellular model cyanobacteria Synechocystis PCC6803, Synechococcus elongatus PCC6301 and Thermosynechococcus elongatus BP1 plus the toxic Microcystis aeruginosa NIES843. The unfiltered numbers of predicted elements in these strains is 383, 168, 168, and 809, respectively, combined into 443 sequence clusters, whereas the numbers of individual elements with high support are 94, 56, 64, and 406, respectively. Removing also transposon-associated repeats, finally 78, 53, 42 and 168 sequences, respectively, are left belonging to 109 different clusters in the data set. Experimental analysis of selected ncRNA candidates in Synechocystis PCC6803 validated new ncRNAs originating from the fabF-hoxH and apcC-prmA intergenic spacers and three highly expressed ncRNAs belonging to the Yfr2 family of ncRNAs. Yfr2a promoter-luxAB fusions confirmed a very strong activity of this promoter and indicated a stimulation of expression if the cultures were exposed to elevated light intensities.
Comparison to entries in Rfam and experimental testing of selected ncRNA candidates in Synechocystis PCC6803 indicate a high reliability of the current prediction, despite some contamination by the high number of repetitive sequences in some of these species. In particular, we identified in the four species altogether 8 new ncRNA homologs belonging to the Yfr2 family of ncRNAs. Modelling of RNA secondary structures indicated two conserved single-stranded sequence motifs that might be involved in RNA-protein interactions or in the recognition of target RNAs. Since our analysis has been restricted to find ncRNA candidates with a reasonable high degree of conservation among these four cyanobacteria, there might be many more, requiring direct experimental approaches for their identification.
PMCID: PMC2662882  PMID: 19309518
3.  Seed-based IntaRNA prediction combined with GFP-reporter system identifies mRNA targets of the small RNA Yfr1 
Bioinformatics  2009;26(1):1-5.
Motivation: Prochlorococcus possesses the smallest genome of all sequenced photoautotrophs. Although the number of regulatory proteins in the genome is very small, the relative number of small regulatory RNAs is comparable with that of other bacteria. The compact genome size of Prochlorococcus offers an ideal system to search for targets of small RNAs (sRNAs) and to refine existing target prediction algorithms.
Results: Target predictions for the cyanobacterial sRNA Yfr1 were carried out with INTARNA in Prochlorococcus MED4. The ultraconserved Yfr1 sequence motif was defined as the putative interaction seed. To study the impact of Yfr1 on its predicted mRNA targets, a reporter system based on green fluorescent protein (GFP) was applied. We show that Yfr1 inhibits the translation of two predicted targets. We used mutation analysis to confirm that Yfr1 directly regulates its targets by an antisense interaction sequestering the ribosome binding site, and to assess the importance of interaction site accessibility.
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC2796815  PMID: 19850757
4.  A comparative genome-wide study of ncRNAs in trypanosomatids 
BMC Genomics  2010;11:615.
Recent studies have provided extensive evidence for multitudes of non-coding RNA (ncRNA) transcripts in a wide range of eukaryotic genomes. ncRNAs are emerging as key players in multiple layers of cellular regulation. With the availability of many whole genome sequences, comparative analysis has become a powerful tool to identify ncRNA molecules. In this study, we performed a systematic genome-wide in silico screen to search for novel small ncRNAs in the genome of Trypanosoma brucei using techniques of comparative genomics.
In this study, we identified by comparative genomics, and validated by experimental analysis several novel ncRNAs that are conserved across multiple trypanosomatid genomes. When tested on known ncRNAs, our procedure was capable of finding almost half of the known repertoire through homology over six genomes, and about two-thirds of the known sequences were found in at least four genomes. After filtering, 72 conserved unannotated sequences in at least four genomes were found, 29 of which, ranging in size from 30 to 392 nts, were conserved in all six genomes. Fifty of the 72 candidates in the final set were chosen for experimental validation. Eighteen of the 50 (36%) were shown to be expressed, and for 11 of them a distinct expression product was detected, suggesting that they are short ncRNAs. Using functional experimental assays, five of the candidates were shown to be novel H/ACA and C/D snoRNAs; these included three sequences that appear as singletons in the genome, unlike previously identified snoRNA molecules that are found in clusters. The other candidates appear to be novel ncRNA molecules, and their function is, as yet, unknown.
Using comparative genomic techniques, we predicted 72 sequences as ncRNA candidates in T. brucei. The expression of 50 candidates was tested in laboratory experiments. This resulted in the discovery of 11 novel short ncRNAs in procyclic stage T. brucei, which have homologues in the other trypansomatids. A few of these molecules are snoRNAs, but most of them are novel ncRNA molecules. Based on this study, our analysis suggests that the total number of ncRNAs in trypanosomatids is in the range of several hundred.
PMCID: PMC3091756  PMID: 21050447
5.  Computational prediction of novel non-coding RNAs in Arabidopsis thaliana 
BMC Bioinformatics  2009;10(Suppl 1):S36.
Non-coding RNA (ncRNA) genes do not encode proteins but produce functional RNA molecules that play crucial roles in many key biological processes. Recent genome-wide transcriptional profiling studies using tiling arrays in organisms such as human and Arabidopsis have revealed a great number of transcripts, a large portion of which have little or no capability to encode proteins. This unexpected finding suggests that the currently known repertoire of ncRNAs may only represent a small fraction of ncRNAs of the organisms. Thus, efficient and effective prediction of ncRNAs has become an important task in bioinformatics in recent years. Among the available computational methods, the comparative genomic approach seems to be the most powerful to detect ncRNAs. The recent completion of the sequencing of several major plant genomes has made the approach possible for plants.
We have developed a pipeline to predict novel ncRNAs in the Arabidopsis (Arabidopsis thaliana) genome. It starts by comparing the expressed intergenic regions of Arabidopsis as provided in two whole-genome high-density oligo-probe arrays from the literature with the intergenic nucleotide sequences of all completely sequenced plant genomes including rice (Oryza sativa), poplar (Populus trichocarpa), grape (Vitis vinifera), and papaya (Carica papaya). By using multiple sequence alignment, a popular ncRNA prediction program (RNAz), wet-bench experimental validation, protein-coding potential analysis, and stringent screening against various ncRNA databases, the pipeline resulted in 16 families of novel ncRNAs (with a total of 21 ncRNAs).
In this paper, we undertake a genome-wide search for novel ncRNAs in the genome of Arabidopsis by a comparative genomics approach. The identified novel ncRNAs are evolutionarily conserved between Arabidopsis and other recently sequenced plants, and may conduct interesting novel biological functions.
PMCID: PMC2648795  PMID: 19208137
6.  Identification and characterisation of non-coding small RNAs in the pathogenic filamentous fungus Trichophyton rubrum 
BMC Genomics  2013;14:931.
Accumulating evidence demonstrates that non-coding RNAs (ncRNAs) are indispensable components of many organisms and play important roles in cellular events, regulation, and development.
Here, we analysed the small non-coding RNA (ncRNA) transcriptome of Trichophyton rubrum by constructing and sequencing a cDNA library from conidia and mycelia. We identified 352 ncRNAs and their corresponding genomic loci. These ncRNA candidates included 198 entirely novel ncRNAs and 154 known ncRNAs classified as snRNAs, snoRNAs and other known ncRNAs. Further bioinformatic analysis detected 96 snoRNAs, including 56 snoRNAs that had been annotated in other organisms and 40 novel snoRNAs. All snoRNAs belonged to two major classes—C/D box snoRNAs and H/ACA snoRNAs—and their potential target sites in rRNAs and snRNAs were predicted. To analyse the evolutionary conservation of the ncRNAs in T. rubrum, we aligned all 352 ncRNAs to the genomes of six dermatophytes and to the NCBI non-redundant nucleotide database (NT). The results showed that most of the identified snRNAs were conserved in dermatophytes. Of the 352 ncRNAs, 102 also had genomic loci in other dermatophytes, and 27 were dermatophyte-specific.
Our systematic analysis may provide important clues to the function and evolution of ncRNAs in T. rubrum. These results also provide important information to complement the current annotation of the T. rubrum genome, which primarily comprises protein-coding genes.
PMCID: PMC3890542  PMID: 24377353
7.  Systematic identification and characterization of chicken (Gallus gallus) ncRNAs 
Nucleic Acids Research  2009;37(19):6562-6574.
Recent studies have demonstrated that non-coding RNAs (ncRNAs) play important roles during development and evolution. Chicken, the first genome-sequenced non-mammalian amniote, possesses unique features for developmental and evolutionary studies. However, apart from microRNAs, information on chicken ncRNAs has mainly been obtained from computational predictions without experimental validation. In the present study, we performed a systematic identification of intermediate size ncRNAs (50–500 nt) by ncRNA library construction and identified 125 chicken ncRNAs. Importantly, through the bioinformatics and expression analysis, we found the chicken ncRNAs has several novel features: (i) comparative genomic analysis against 18 sequenced vertebrate genomes revealed that the majority of the newly identified ncRNA candidates is not conserved and most are potentially bird/chicken specific, suggesting that ncRNAs play roles in lineage/species specification during evolution. (ii) The expression pattern analysis of intronic snoRNAs and their host genes suggested the coordinated expression between snoRNAs and their host genes. (iii) Several spatio-temporal specific expression patterns suggest involvement of ncRNAs in tissue development. Together, these findings provide new clues for future functional study of ncRNAs during development and evolution.
PMCID: PMC2770669  PMID: 19720738
8.  Genomic and Transcriptional Co-Localization of Protein-Coding and Long Non-Coding RNA Pairs in the Developing Brain 
PLoS Genetics  2009;5(8):e1000617.
Besides protein-coding mRNAs, eukaryotic transcriptomes include many long non-protein-coding RNAs (ncRNAs) of unknown function that are transcribed away from protein-coding loci. Here, we have identified 659 intergenic long ncRNAs whose genomic sequences individually exhibit evolutionary constraint, a hallmark of functionality. Of this set, those expressed in the brain are more frequently conserved and are significantly enriched with predicted RNA secondary structures. Furthermore, brain-expressed long ncRNAs are preferentially located adjacent to protein-coding genes that are (1) also expressed in the brain and (2) involved in transcriptional regulation or in nervous system development. This led us to the hypothesis that spatiotemporal co-expression of ncRNAs and nearby protein-coding genes represents a general phenomenon, a prediction that was confirmed subsequently by in situ hybridisation in developing and adult mouse brain. We provide the full set of constrained long ncRNAs as an important experimental resource and present, for the first time, substantive and predictive criteria for prioritising long ncRNA and mRNA transcript pairs when investigating their biological functions and contributions to development and disease.
Author Summary
Virtually all of the eukaryotic genome is transcribed, yet far from all transcripts encode protein. Very little is known about the functions of most non-coding transcripts or, indeed, whether they convey functions at all. Among all such transcripts, we have chosen to consider long non-coding RNAs (ncRNAs) that are transcribed outside of known protein-coding gene loci. Our approach has focused on mouse long ncRNAs whose genomic sequences are conserved in humans, and also on ncRNAs that are expressed in the brain. This conservation might reflect the functionality of the underlying DNA, rather than the ncRNA, sequence. However, this cannot fully explain the concentration of predicted RNA structures in these ncRNAs. These long ncRNAs also tend to be transcribed in the genomic neighbourhood of protein-coding genes whose functions relate to transcription or to nervous system development. These observations are consistent with the positive transcriptional regulation in cis of these genes with nearby transcription of ncRNAs. This model implies co-expression of protein-coding and noncoding transcripts, a hypothesis that we validated experimentally. These findings are particularly important because they provide a rationale for prioritising specific ncRNAs when experimentally investigating regulation of protein-coding gene expression.
PMCID: PMC2722021  PMID: 19696892
9.  Signature proteins for the major clades of Cyanobacteria 
The phylogeny and taxonomy of cyanobacteria is currently poorly understood due to paucity of reliable markers for identification and circumscription of its major clades.
A combination of phylogenomic and protein signature based approaches was used to characterize the major clades of cyanobacteria. Phylogenetic trees were constructed for 44 cyanobacteria based on 44 conserved proteins. In parallel, Blastp searches were carried out on each ORF in the genomes of Synechococcus WH8102, Synechocystis PCC6803, Nostoc PCC7120, Synechococcus JA-3-3Ab, Prochlorococcus MIT9215 and Prochlor. marinus subsp. marinus CCMP1375 to identify proteins that are specific for various main clades of cyanobacteria. These studies have identified 39 proteins that are specific for all (or most) cyanobacteria and large numbers of proteins for other cyanobacterial clades. The identified signature proteins include: (i) 14 proteins for a deep branching clade (Clade A) of Gloebacter violaceus and two diazotrophic Synechococcus strains (JA-3-3Ab and JA2-3-B'a); (ii) 5 proteins that are present in all other cyanobacteria except those from Clade A; (iii) 60 proteins that are specific for a clade (Clade C) consisting of various marine unicellular cyanobacteria (viz. Synechococcus and Prochlorococcus); (iv) 14 and 19 signature proteins that are specific for the Clade C Synechococcus and Prochlorococcus strains, respectively; (v) 67 proteins that are specific for the Low B/A ecotype Prochlorococcus strains, containing lower ratio of chl b/a2 and adapted to growth at high light intensities; (vi) 65 and 8 proteins that are specific for the Nostocales and Chroococcales orders, respectively; and (vii) 22 and 9 proteins that are uniquely shared by various Nostocales and Oscillatoriales orders, or by these two orders and the Chroococcales, respectively. We also describe 3 conserved indels in flavoprotein, heme oxygenase and protochlorophyllide oxidoreductase proteins that are specific for either Clade C cyanobacteria or for various subclades of Prochlorococcus. Many other conserved indels for cyanobacterial clades have been described recently.
These signature proteins and indels provide novel means for circumscription of various cyanobacterial clades in clear molecular terms. Their functional studies should lead to discovery of novel properties that are unique to these groups of cyanobacteria.
PMCID: PMC2823733  PMID: 20100331
10.  Structured RNAs and synteny regions in the pig genome 
BMC Genomics  2014;15(1):459.
Annotating mammalian genomes for noncoding RNAs (ncRNAs) is nontrivial since far from all ncRNAs are known and the computational models are resource demanding. Currently, the human genome holds the best mammalian ncRNA annotation, a result of numerous efforts by several groups. However, a more direct strategy is desired for the increasing number of sequenced mammalian genomes of which some, such as the pig, are relevant as disease models and production animals.
We present a comprehensive annotation of structured RNAs in the pig genome. Combining sequence and structure similarity search as well as class specific methods, we obtained a conservative set with a total of 3,391 structured RNA loci of which 1,011 and 2,314, respectively, hold strong sequence and structure similarity to structured RNAs in existing databases. The RNA loci cover 139 cis-regulatory element loci, 58 lncRNA loci, 11 conflicts of annotation, and 3,183 ncRNA genes. The ncRNA genes comprise 359 miRNAs, 8 ribozymes, 185 rRNAs, 638 snoRNAs, 1,030 snRNAs, 810 tRNAs and 153 ncRNA genes not belonging to the here fore mentioned classes. When running the pipeline on a local shuffled version of the genome, we obtained no matches at the highest confidence level. Additional analysis of RNA-seq data from a pooled library from 10 different pig tissues added another 165 miRNA loci, yielding an overall annotation of 3,556 structured RNA loci. This annotation represents our best effort at making an automated annotation. To further enhance the reliability, 571 of the 3,556 structured RNAs were manually curated by methods depending on the RNA class while 1,581 were declared as pseudogenes. We further created a multiple alignment of pig against 20 representative vertebrates, from which RNAz predicted 83,859 de novo RNA loci with conserved RNA structures. 528 of the RNAz predictions overlapped with the homology based annotation or novel miRNAs. We further present a substantial synteny analysis which includes 1,004 lineage specific de novo RNA loci and 4 ncRNA loci in the known annotation specific for Laurasiatheria (pig, cow, dolphin, horse, cat, dog, hedgehog).
We have obtained one of the most comprehensive annotations for structured ncRNAs of a mammalian genome, which is likely to play central roles in both health modelling and production. The core annotation is available in Ensembl 70 and the complete annotation is available at
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-459) contains supplementary material, which is available to authorized users.
PMCID: PMC4124155  PMID: 24917120
11.  Classification of ncRNAs using position and size information in deep sequencing data 
Bioinformatics  2010;26(18):i426-i432.
Motivation: Small non-coding RNAs (ncRNAs) play important roles in various cellular functions in all clades of life. With next-generation sequencing techniques, it has become possible to study ncRNAs in a high-throughput manner and by using specialized algorithms ncRNA classes such as miRNAs can be detected in deep sequencing data. Typically, such methods are targeted to a certain class of ncRNA. Many methods rely on RNA secondary structure prediction, which is not always accurate and not all ncRNA classes are characterized by a common secondary structure. Unbiased classification methods for ncRNAs could be important to improve accuracy and to detect new ncRNA classes in sequencing data.
Results: Here, we present a scoring system called ALPS (alignment of pattern matrices score) that only uses primary information from a deep sequencing experiment, i.e. the relative positions and lengths of reads, to classify ncRNAs. ALPS makes no further assumptions, e.g. about common structural properties in the ncRNA class and is nevertheless able to identify ncRNA classes with high accuracy. Since ALPS is not designed to recognize a certain class of ncRNA, it can be used to detect novel ncRNA classes, as long as these unknown ncRNAs have a characteristic pattern of deep sequencing read lengths and positions. We evaluate our scoring system on publicly available deep sequencing data and show that it is able to classify known ncRNAs with high sensitivity and specificity.
Availability: Calculated pattern matrices of the datasets hESC and EB are available at the project web site An implementation of the described method is available upon request from the authors.
PMCID: PMC2935403  PMID: 20823303
12.  nocoRNAc: Characterization of non-coding RNAs in prokaryotes 
BMC Bioinformatics  2011;12:40.
The interest in non-coding RNAs (ncRNAs) constantly rose during the past few years because of the wide spectrum of biological processes in which they are involved. This led to the discovery of numerous ncRNA genes across many species. However, for most organisms the non-coding transcriptome still remains unexplored to a great extent. Various experimental techniques for the identification of ncRNA transcripts are available, but as these methods are costly and time-consuming, there is a need for computational methods that allow the detection of functional RNAs in complete genomes in order to suggest elements for further experiments. Several programs for the genome-wide prediction of functional RNAs have been developed but most of them predict a genomic locus with no indication whether the element is transcribed or not.
We present NOCORNAc, a program for the genome-wide prediction of ncRNA transcripts in bacteria. NOCORNAc incorporates various procedures for the detection of transcriptional features which are then integrated with functional ncRNA loci to determine the transcript coordinates. We applied RNAz and NOCORNAc to the genome of Streptomyces coelicolor and detected more than 800 putative ncRNA transcripts most of them located antisense to protein-coding regions. Using a custom design microarray we profiled the expression of about 400 of these elements and found more than 300 to be transcribed, 38 of them are predicted novel ncRNA genes in intergenic regions. The expression patterns of many ncRNAs are similarly complex as those of the protein-coding genes, in particular many antisense ncRNAs show a high expression correlation with their protein-coding partner.
We have developed NOCORNAc, a framework that facilitates the automated characterization of functional ncRNAs. NOCORNAc increases the confidence of predicted ncRNA loci, especially if they contain transcribed ncRNAs. NOCORNAc is not restricted to intergenic regions, but it is applicable to the prediction of ncRNA transcripts in whole microbial genomes. The software as well as a user guide and example data is available at
PMCID: PMC3230914  PMID: 21281482
13.  Bovine ncRNAs Are Abundant, Primarily Intergenic, Conserved and Associated with Regulatory Genes 
PLoS ONE  2012;7(8):e42638.
It is apparent that non-coding transcripts are a common feature of higher organisms and encode uncharacterized layers of genetic regulation and information. We used public bovine EST data from many developmental stages and tissues, and developed a pipeline for the genome wide identification and annotation of non-coding RNAs (ncRNAs). We have predicted 23,060 bovine ncRNAs, 99% of which are un-annotated, based on known ncRNA databases. Intergenic transcripts accounted for the majority (57%) of the predicted ncRNAs and the occurrence of ncRNAs and genes were only moderately correlated (r = 0.55, p-value<2.2e-16). Many of these intergenic non-coding RNAs mapped close to the 3′ or 5′ end of thousands of genes and many of these were transcribed from the opposite strand with respect to the closest gene, particularly regulatory-related genes. Conservation analyses showed that these ncRNAs were evolutionarily conserved, and many intergenic ncRNAs proximate to genes contained sequence-specific motifs. Correlation analysis of expression between these intergenic ncRNAs and protein-coding genes using RNA-seq data from a variety of tissues showed significant correlations with many transcripts. These results support the hypothesis that ncRNAs are common, transcribed in a regulated fashion and have regulatory functions.
PMCID: PMC3412814  PMID: 22880061
14.  Detection of non-coding RNAs on the basis of predicted secondary structure formation free energy change 
BMC Bioinformatics  2006;7:173.
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.
Here, Dynalign, a program for predicting secondary structures common to two RNA sequences on the basis of minimizing folding free energy change, is utilized as a computational ncRNA detection tool. The Dynalign-computed optimal total free energy change, which scores the structural alignment and the free energy change of folding into a common structure for two RNA sequences, is shown to be an effective measure for distinguishing ncRNA from randomized sequences. To make the classification as a ncRNA, the total free energy change of an input sequence pair can either be compared with the total free energy changes of a set of control sequence pairs, or be used in combination with sequence length and nucleotide frequencies as input to a classification support vector machine. The latter method is much faster, but slightly less sensitive at a given specificity. Additionally, the classification support vector machine method is shown to be sensitive and specific on genomic ncRNA screens of two different Escherichia coli and Salmonella typhi genome alignments, in which many ncRNAs are known. The Dynalign computational experiments are also compared with two other ncRNA detection programs, RNAz and QRNA.
The Dynalign-based support vector machine method is more sensitive for known ncRNAs in the test genomic screens than RNAz and QRNA. Additionally, both Dynalign-based methods are more sensitive than RNAz and QRNA at low sequence pair identities. Dynalign can be used as a comparable or more accurate tool than RNAz or QRNA in genomic screens, especially for low-identity regions. Dynalign provides a method for discovering ncRNAs in sequenced genomes that other methods may not identify. Significant improvements in Dynalign runtime have also been achieved.
PMCID: PMC1570369  PMID: 16566836
15.  Evolutionarily divergent spliceosomal snRNAs and a conserved non-coding RNA processing motif in Giardia lamblia 
Nucleic Acids Research  2012;40(21):10995-11008.
Non-coding RNAs (ncRNAs) have diverse essential biological functions in all organisms, and in eukaryotes, two such classes of ncRNAs are the small nucleolar (sno) and small nuclear (sn) RNAs. In this study, we have identified and characterized a collection of sno and snRNAs in Giardia lamblia, by exploiting our discovery of a conserved 12 nt RNA processing sequence motif found in the 3′ end regions of a large number of G. lamblia ncRNA genes. RNA end mapping and other experiments indicate the motif serves to mediate ncRNA 3′ end formation from mono- and di-cistronic RNA precursor transcripts. Remarkably, we find the motif is also utilized in the processing pathway of all four previously identified trans-spliced G. lamblia introns, revealing a common RNA processing pathway for ncRNAs and trans-spliced introns in this organism. Motif sequence conservation then allowed for the bioinformatic and experimental identification of additional G. lamblia ncRNAs, including new U1 and U6 spliceosomal snRNA candidates. The U6 snRNA candidate was then used as a tool to identity novel U2 and U4 snRNAs, based on predicted phylogenetically conserved snRNA–snRNA base-pairing interactions, from a set of previously identified G. lamblia ncRNAs without assigned function. The Giardia snRNAs retain the core features of spliceosomal snRNAs but are sufficiently evolutionarily divergent to explain the difficulties in their identification. Most intriguingly, all of these snRNAs show structural features diagnostic of U2-dependent/major and U12-dependent/minor spliceosomal snRNAs.
PMCID: PMC3510501  PMID: 23019220
16.  Identification of novel non-coding RNAs using profiles of short sequence reads from next generation sequencing data 
BMC Genomics  2010;11:77.
The increasing interest in small non-coding RNAs (ncRNAs) such as microRNAs (miRNAs), small interfering RNAs (siRNAs) and Piwi-interacting RNAs (piRNAs) and recent advances in sequencing technology have yielded large numbers of short (18-32 nt) RNA sequences from different organisms, some of which are derived from small nucleolar RNAs (snoRNAs) and transfer RNAs (tRNAs). We observed that these short ncRNAs frequently cover the entire length of annotated snoRNAs or tRNAs, which suggests that other loci specifying similar ncRNAs can be identified by clusters of short RNA sequences.
We combined publicly available datasets of tens of millions of short RNA sequence tags from Drosophila melanogaster, and mapped them to the Drosophila genome. Approximately 6 million perfectly mapping sequence tags were then assembled into 521,302 tag-contigs (TCs) based on tag overlap. Most transposon-derived sequences, exons and annotated miRNAs, tRNAs and snoRNAs are detected by TCs, which show distinct patterns of length and tag-depth for different categories. The typical length and tag-depth of snoRNA-derived TCs was used to predict 7 previously unrecognized box H/ACA and 26 box C/D snoRNA candidates. We also identified one snRNA candidate and 86 loci with a high number of tags that are yet to be annotated, 7 of which have a particular 18mer motif and are located in introns of genes involved in development. A subset of new snoRNA candidates and putative ncRNA candidates was verified by Northern blot.
In this study, we have introduced a new approach to identify new members of known classes of ncRNAs based on the features of TCs corresponding to known ncRNAs. A large number of the identified TCs are yet to be examined experimentally suggesting that many more novel ncRNAs remain to be discovered.
PMCID: PMC2825236  PMID: 20113528
17.  Genome-wide analysis of putative peroxiredoxin in unicellular and filamentous cyanobacteria 
Cyanobacteria are photoautotrophic prokaryotes with wide variations in genome sizes and ecological habitats. Peroxiredoxin (PRX) is an important protein that plays essential roles in protecting own cells against reactive oxygen species (ROS). PRXs have been identified from mammals, fungi and higher plants. However, knowledge on cyanobacterial PRXs still remains obscure. With the availability of 37 sequenced cyanobacterial genomes, we performed a comprehensive comparative analysis of PRXs and explored their diversity, distribution, domain structure and evolution.
Overall 244 putative prx genes were identified, which were abundant in filamentous diazotrophic cyanobacteria, Acaryochloris marina MBIC 11017, and unicellular cyanobacteria inhabiting freshwater and hot-springs, while poor in all Prochlorococcus and marine Synechococcus strains. Among these putative genes, 25 open reading frames (ORFs) encoding hypothetical proteins were identified as prx gene family members and the others were already annotated as prx genes. All 244 putative PRXs were classified into five major subfamilies (1-Cys, 2-Cys, BCP, PRX5_like, and PRX-like) according to their domain structures. The catalytic motifs of the cyanobacterial PRXs were similar to those of eukaryotic PRXs and highly conserved in all but the PRX-like subfamily. Classical motif (CXXC) of thioredoxin was detected in protein sequences from the PRX-like subfamily. Phylogenetic tree constructed of catalytic domains coincided well with the domain structures of PRXs and the phylogenies based on 16s rRNA.
The distribution of genes encoding PRXs in different unicellular and filamentous cyanobacteria especially those sub-families like PRX-like or 1-Cys PRX correlate with the genome size, eco-physiology, and physiological properties of the organisms. Cyanobacterial and eukaryotic PRXs share similar conserved motifs, indicating that cyanobacteria adopt similar catalytic mechanisms as eukaryotes. All cyanobacterial PRX proteins share highly similar structures, implying that these genes may originate from a common ancestor. In this study, a general framework of the sequence-structure-function connections of the PRXs was revealed, which may facilitate functional investigations of PRXs in various organisms.
PMCID: PMC3514251  PMID: 23157370
Peroxiredoxin; Structure; Phylogeny and evolution; Comparative genomics; Cyanobacteria
18.  The Challenge of Regulation in a Minimal Photoautotroph: Non-Coding RNAs in Prochlorococcus 
PLoS Genetics  2008;4(8):e1000173.
Prochlorococcus, an extremely small cyanobacterium that is very abundant in the world's oceans, has a very streamlined genome. On average, these cells have about 2,000 genes and very few regulatory proteins. The limited capability of regulation is thought to be a result of selection imposed by a relatively stable environment in combination with a very small genome. Furthermore, only ten non-coding RNAs (ncRNAs), which play crucial regulatory roles in all forms of life, have been described in Prochlorococcus. Most strains also lack the RNA chaperone Hfq, raising the question of how important this mode of regulation is for these cells. To explore this question, we examined the transcription of intergenic regions of Prochlorococcus MED4 cells subjected to a number of different stress conditions: changes in light qualities and quantities, phage infection, or phosphorus starvation. Analysis of Affymetrix microarray expression data from intergenic regions revealed 276 novel transcriptional units. Among these were 12 new ncRNAs, 24 antisense RNAs (asRNAs), as well as 113 short mRNAs. Two additional ncRNAs were identified by homology, and all 14 new ncRNAs were independently verified by Northern hybridization and 5′RACE. Unlike its reduced suite of regulatory proteins, the number of ncRNAs relative to genome size in Prochlorococcus is comparable to that found in other bacteria, suggesting that RNA regulators likely play a major role in regulation in this group. Moreover, the ncRNAs are concentrated in previously identified genomic islands, which carry genes of significance to the ecology of this organism, many of which are not of cyanobacterial origin. Expression profiles of some of these ncRNAs suggest involvement in light stress adaptation and/or the response to phage infection consistent with their location in the hypervariable genomic islands.
Author Summary
Prochlorococcus is the most abundant phototroph in the vast, nutrient-poor areas of the ocean. It plays an important role in the ocean carbon cycle, and is a key component of the base of the food web. All cells share a core set of about 1,200 genes, augmented with a variable number of “flexible” genes. Many of the latter are located in genomic islands—hypervariable regions of the genome that encode functions important in differentiating the niches of “ecotypes.” Of major interest is how cells with such a small genome regulate cellular processes, as they lack many of the regulatory proteins commonly found in bacteria. We show here that contrary to the regulatory proteins, ncRNAs are present at levels typical of bacteria, revealing that they might have a disproportional regulatory role in Prochlorococcus—likely an adaptation to the extremely low-nutrient conditions of the open oceans, combined with the constraints of a small genome. Some of the ncRNAs were differentially expressed under stress conditions, and a high number of them were found to be associated with genomic islands, suggesting functional links between these RNAs and the response of Prochlorococcus to particular environmental challenges.
PMCID: PMC2518516  PMID: 18769676
19.  Systematic identification of non-coding RNA 2,2,7-trimethylguanosine cap structures in Caenorhabditis elegans 
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 two anti-TMG antibodies precipitated a similar group of the C. elegans ncRNAs. All snRNAs known to have a TMG cap structure were found in the precipitate, indicating that our identification system was efficient. Other ncRNA families related to splicing, such as SL RNAs and Sm Y RNAs, were also found in the precipitate, as were 7 C/D box snoRNAs. Further analysis showed that the SL RNAs and the Sm Y RNAs shared a very similar Sm binding site element (AAU4–5GGA), which sequence composition differed somewhat from those of other U snRNAs. There were also 16 ncRNAs without an Sm binding site element in the precipitate, suggesting that for these ncRNAs, TMG formation may occur independently of Sm proteins.
Our results showed that most ncRNAs predicted to be transcribed by RNA polymerase II had a TMG cap, while those predicted to be transcribed by RNA plymerase III or located in introns did not have a TMG cap structure. Compared to ncRNAs without a TMG cap, TMG-capped ncRNAs tended to have higher expression levels. Five functionally non-annotated ncRNAs also have a TMG cap structure, which might be helpful for identifying the cellular roles of these ncRNAs.
PMCID: PMC2200864  PMID: 17903271
20.  De novo computational prediction of non-coding RNA genes in prokaryotic genomes 
Bioinformatics  2009;25(22):2897-2905.
Motivation: The computational identification of non-coding RNA (ncRNA) genes represents one of the most important and challenging problems in computational biology. Existing methods for ncRNA gene prediction rely mostly on homology information, thus limiting their applications to ncRNA genes with known homologues.
Results: We present a novel de novo prediction algorithm for ncRNA genes using features derived from the sequences and structures of known ncRNA genes in comparison to decoys. Using these features, we have trained a neural network-based classifier and have applied it to Escherichia coli and Sulfolobus solfataricus for genome-wide prediction of ncRNAs. Our method has an average prediction sensitivity and specificity of 68% and 70%, respectively, for identifying windows with potential for ncRNA genes in E.coli. By combining windows of different sizes and using positional filtering strategies, we predicted 601 candidate ncRNAs and recovered 41% of known ncRNAs in E.coli. We experimentally investigated six novel candidates using Northern blot analysis and found expression of three candidates: one represents a potential new ncRNA, one is associated with stable mRNA decay intermediates and one is a case of either a potential riboswitch or transcription attenuator involved in the regulation of cell division. In general, our approach enables the identification of both cis- and trans-acting ncRNAs in partially or completely sequenced microbial genomes without requiring homology or structural conservation.
Availability: The source code and results are available at
Supplementary information: Supplementary data are available at Bioinformatics online.
PMCID: PMC2773258  PMID: 19744996
21.  Identification of CRISPR and riboswitch related RNAs among novel noncoding RNAs of the euryarchaeon Pyrococcus abyssi 
BMC Genomics  2011;12:312.
Noncoding RNA (ncRNA) has been recognized as an important regulator of gene expression networks in Bacteria and Eucaryota. Little is known about ncRNA in thermococcal archaea except for the eukaryotic-like C/D and H/ACA modification guide RNAs.
Using a combination of in silico and experimental approaches, we identified and characterized novel P. abyssi ncRNAs transcribed from 12 intergenic regions, ten of which are conserved throughout the Thermococcales. Several of them accumulate in the late-exponential phase of growth. Analysis of the genomic context and sequence conservation amongst related thermococcal species revealed two novel P. abyssi ncRNA families. The CRISPR family is comprised of crRNAs expressed from two of the four P. abyssi CRISPR cassettes. The 5'UTR derived family includes four conserved ncRNAs, two of which have features similar to known bacterial riboswitches. Several of the novel ncRNAs have sequence similarities to orphan OrfB transposase elements. Based on RNA secondary structure predictions and experimental results, we show that three of the twelve ncRNAs include Kink-turn RNA motifs, arguing for a biological role of these ncRNAs in the cell. Furthermore, our results show that several of the ncRNAs are subjected to processing events by enzymes that remain to be identified and characterized.
This work proposes a revised annotation of CRISPR loci in P. abyssi and expands our knowledge of ncRNAs in the Thermococcales, thus providing a starting point for studies needed to elucidate their biological function.
PMCID: PMC3124441  PMID: 21668986
22.  Small non-coding RNA profiling and the role of piRNA pathway genes in the protection of chicken primordial germ cells 
BMC Genomics  2014;15(1):757.
Genes, RNAs, and proteins play important roles during germline development. However, the functions of non-coding RNAs (ncRNAs) on germline development remain unclear in avian species. Recent high-throughput techniques have identified several classes of ncRNAs, including micro RNAs (miRNAs), small-interfering RNAs (siRNAs), and PIWI-interacting RNAs (piRNAs). These ncRNAs are functionally important in the genome, however, the identification and annotation of ncRNAs in a genome is challenging. The aim of this study was to identify different types of small ncRNAs particularly piRNAs, and the role of piRNA pathway genes in the protection of chicken primordial germ cells (PGCs).
At first, we performed next-generation sequencing to identify ncRNAs in chicken PGCs, and we performed ab initio predictive analysis to identify putative piRNAs in PGCs. Then, we examined the expression of three repetitive sequence-linked piRNAs and 14 genic-transcript-linked piRNAs along with their linked genes using real-time PCR. All piRNAs and their linked genes were highly expressed in PGCs. Subsequently, we knocked down two known piRNA pathway genes of chicken, PIWI-like protein 1 (CIWI) and 2 (CILI), in PGCs using siRNAs. After knockdown of CIWI and CILI, we examined their effects on the expression of six putative piRNA-linked genes and DNA double-strand breakage in PGCs. The knockdown of CIWI and CILI upregulated chicken repetitive 1 (CR1) element and RAP2B, a member of RAS oncogene family, and increased DNA double-strand breakage in PGCs.
Our results increase the understanding of PGC-expressed piRNAs and the role of piRNA pathway genes in the protection of germ cells.
Electronic supplementary material
The online version of this article (doi:10.1186/1471-2164-15-757) contains supplementary material, which is available to authorized users.
PMCID: PMC4286946  PMID: 25185950
Aves; Non-coding RNA; piRNA; Primordial Germ Cells
23.  Stable stem enabled Shannon entropies distinguish non-coding RNAs from random backgrounds 
BMC Bioinformatics  2012;13(Suppl 5):S1.
The computational identification of RNAs in genomic sequences requires the identification of signals of RNA sequences. Shannon base pairing entropy is an indicator for RNA secondary structure fold certainty in detection of structural, non-coding RNAs (ncRNAs). Under the Boltzmann ensemble of secondary structures, the probability of a base pair is estimated from its frequency across all the alternative equilibrium structures. However, such an entropy has yet to deliver the desired performance for distinguishing ncRNAs from random sequences. Developing novel methods to improve the entropy measure performance may result in more effective ncRNA gene finding based on structure detection.
This paper shows that the measuring performance of base pairing entropy can be significantly improved with a constrained secondary structure ensemble in which only canonical base pairs are assumed to occur in energetically stable stems in a fold. This constraint actually reduces the space of the secondary structure and may lower the probabilities of base pairs unfavorable to the native fold. Indeed, base pairing entropies computed with this constrained model demonstrate substantially narrowed gaps of Z-scores between ncRNAs, as well as drastic increases in the Z-score for all 13 tested ncRNA sets, compared to shuffled sequences.
These results suggest the viability of developing effective structure-based ncRNA gene finding methods by investigating secondary structure ensembles of ncRNAs.
PMCID: PMC3358654  PMID: 22537005
24.  Clusters of Internally Primed Transcripts Reveal Novel Long Noncoding RNAs 
PLoS Genetics  2006;2(4):e37.
Non-protein-coding RNAs (ncRNAs) are increasingly being recognized as having important regulatory roles. Although much recent attention has focused on tiny 22- to 25-nucleotide microRNAs, several functional ncRNAs are orders of magnitude larger in size. Examples of such macro ncRNAs include Xist and Air, which in mouse are 18 and 108 kilobases (Kb), respectively. We surveyed the 102,801 FANTOM3 mouse cDNA clones and found that Air and Xist were present not as single, full-length transcripts but as a cluster of multiple, shorter cDNAs, which were unspliced, had little coding potential, and were most likely primed from internal adenine-rich regions within longer parental transcripts. We therefore conducted a genome-wide search for regional clusters of such cDNAs to find novel macro ncRNA candidates. Sixty-six regions were identified, each of which mapped outside known protein-coding loci and which had a mean length of 92 Kb. We detected several known long ncRNAs within these regions, supporting the basic rationale of our approach. In silico analysis showed that many regions had evidence of imprinting and/or antisense transcription. These regions were significantly associated with microRNAs and transcripts from the central nervous system. We selected eight novel regions for experimental validation by northern blot and RT-PCR and found that the majority represent previously unrecognized noncoding transcripts that are at least 10 Kb in size and predominantly localized in the nucleus. Taken together, the data not only identify multiple new ncRNAs but also suggest the existence of many more macro ncRNAs like Xist and Air.
The human genome has been sequenced, and, intriguingly, less than 2% specifies the information for the basic protein building blocks of our bodies. So, what does the other 98% do? It now appears that the mammalian genome also specifies the instructions for many previously undiscovered “non protein-coding RNA” (ncRNA) genes. However, what these ncRNAs do is largely unknown. In recent years, strategies have been designed that have successfully identified hundreds of short ncRNAs—termed microRNAs—many of which have since been shown to act as genetic regulators. Also known to be functionally important are a handful of ncRNAs orders of magnitude larger in size than microRNAs. The availability of complete genome and comprehensive transcript sequences allows for the systematic discovery of more large ncRNAs. The authors developed a computational strategy to screen the mouse genome and identify large ncRNAs. They detected existing large ncRNAs, thus validating their approach, but, more importantly, discovered more than 60 other candidates, some of which were subsequently confirmed experimentally. This work opens the door to a virtually unexplored world of large ncRNAs and beckons future experimental work to define the cellular functions of these molecules.
PMCID: PMC1449886  PMID: 16683026
25.  Genome-scale NCRNA homology search using a Hamming distance-based filtration strategy 
BMC Bioinformatics  2012;13(Suppl 3):S12.
NCRNAs (noncoding RNAs) play important roles in many biological processes. Existing genome-scale ncRNA search tools identify ncRNAs in local sequence alignments generated by conventional sequence comparison methods. However, some types of ncRNA lack strong sequence conservation and tend to be missed or mis-aligned by conventional sequence comparison.
In this paper, we propose an ncRNA identification framework that is complementary to existing sequence comparison tools. By integrating a filtration step based on Hamming distance and ncRNA alignment programs such as FOLDALIGN or PLAST-ncRNA, the proposed ncRNA search framework can identify ncRNAs that lack strong sequence conservation. In addition, as the ratio of transition and transversion mutation is often used as a discriminative feature for functional ncRNA identification, we incorporate this feature into the filtration step using a coding strategy. We apply Hamming distance seeds to ncRNA search in the intergenic regions of human and mouse genomes and between the Burkholderia cenocepacia J2315 genome and the Ralstonia solanacearum genome. The experimental results demonstrate that a carefully designed Hamming distance seed can achieve better sensitivity in searching for poorly conserved ncRNAs than conventional sequence comparison tools.
Hamming distance seeds provide better sensitivity as a filtration strategy for genome-wide ncRNA homology search than the existing seeding strategies used in BLAST-like tools. By combining Hamming distance seeds matching and ncRNA alignment, we are able to find ncRNAs with sequence similarities below 60%.
PMCID: PMC3311100  PMID: 22536896

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