Use of tiling array data and RNA secondary structure predictions to identify noncoding RNA genes

Weile, Christian; Gardner, Paul P.; Hedegaard, Mads M.; Vinther, Jeppe

doi:10.1186/1471-2164-8-244

Cited by 15 publications

(12 citation statements)

References 35 publications

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“…Covariance is present when the identity of a residue at one position in a sequence is at least partially dependent upon the identity of the residue at another position. Covariance has been widely used to evaluate RNA structure (27,34,36,46,69,73) and less extensively to probe intraprotein interactions (26,42,53). We and others recently applied it to the full amino acid coding potential of the hepatitis C virus (HCV) genome (3,11,41).…”

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confidence: 99%

Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses

Donlin

Szeto

Gohara

et al. 2012

J Virol

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Coordinated variation among positions in amino acid sequence alignments can reveal genetic dependencies at noncontiguous positions, but methods to assess these interactions are incompletely developed. Previously, we found genome-wide networks of covarying residue positions in the hepatitis C virus genome (R. Aurora, M. J. Donlin, N. A. Cannon, and J. E. Tavis, J. Clin. Invest. 119:225-236, 2009). Here, we asked whether such networks are present in a diverse set of viruses and, if so, what they may imply about viral biology. Viral sequences were obtained for 16 viruses in 13 species from 9 families. The entire viral coding potential for each virus was aligned, all possible amino acid covariances were identified using the observed-minus-expectedsquared algorithm at a false-discovery rate of <1%, and networks of covariances were assessed using standard methods. Covariances that spanned the viral coding potential were common in all viruses. In all cases, the covariances formed a single network that contained essentially all of the covariances. The hepatitis C virus networks had hub-and-spoke topologies, but all other networks had random topologies with an unusually large number of highly connected nodes. These results indicate that genomewide networks of genetic associations and the coordinated evolution they imply are very common in viral genomes, that the networks rarely have the hub-and-spoke topology that dominates other biological networks, and that network topologies can vary substantially even within a given viral group. Five examples with hepatitis B virus and poliovirus are presented to illustrate how covariance network analysis can lead to inferences about viral biology. V iral genomes are usually small, and as a group, they are structurally very diverse. This places significant constraints on viral genetic coding patterns and leads to the variety of gene expression strategies and replication mechanisms that are summarized by Baltimore's seminal viral classification system (4). These constraints affect the selection pressures on viral genomes, often in ways not normally encountered by the genomes of cellular organisms. Although the effects of complex selective processes, such as epistasis and pleiotropy, on viral intragenomic interactions are partially understood in theoretical terms (24,33,37), observation of their effects on a genome-wide scale has proven difficult.The multiple-sequence alignments that underlie most genetic analyses assume that each position in an alignment is independent of all others, and hence, the alignments are blind to intragenomic dependencies. Such dependencies are clearly of major biological importance, because folding of proteins and RNAs brings distant residues into close proximity, so there is more information in sequence sets than standard analytical methods reveal. One method to find long-distance genetic interactions is to identify covariances among a collection of related sequences. Covariance is present when the identity of a residue at one position in a sequence is at l...

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confidence: 99%

Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses

Donlin

Szeto

Gohara

et al. 2012

J Virol

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“…It is known that most of the genome is transcribed in complex patterns of interacting and overlapping transcripts from both strands ( 5–9 ), and most mammalian genes also have antisense transcripts ( 7 , 9–11 ). We currently have a great deal of information ( 4 , 5 , 12–14 ) arising from modern technologies, such as tiling arrays, that confirm the genome to be pervasively transcribed, and that the noncoding regions, such as the introns and intergenic regions, play an important role in human genome regulation by cis -acting at the transcriptional level ( 4 , 15 , 16 ). These approaches have resulted in the discovery of many novel transcribed sequences, and provide a new perspective on the number and extent of transcripts.…”

Section: Introductionmentioning

confidence: 99%

No-match ORESTES explored as tumor markers

Mello¹,

Abrantes²,

Torres³

et al. 2009

Nucleic Acids Research

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Sequencing technologies and new bioinformatics tools have led to the complete sequencing of various genomes. However, information regarding the human transcriptome and its annotation is yet to be completed. The Human Cancer Genome Project, using ORESTES (open reading frame EST sequences) methodology, contributed to this objective by generating data from about 1.2 million expressed sequence tags. Approximately 30% of these sequences did not align to ESTs in the public databases and were considered no-match ORESTES. On the basis that a set of these ESTs could represent new transcripts, we constructed a cDNA microarray. This platform was used to hybridize against 12 different normal or tumor tissues. We identified 3421 transcribed regions not associated with annotated transcripts, representing 83.3% of the platform. The total number of differentially expressed sequences was 1007. Also, 28% of analyzed sequences could represent noncoding RNAs. Our data reinforces the knowledge of the human genome being pervasively transcribed, and point out molecular marker candidates for different cancers. To reinforce our data, we confirmed, by real-time PCR, the differential expression of three out of eight potentially tumor markers in prostate tissues. Lists of 1007 differentially expressed sequences, and the 291 potentially noncoding tumor markers were provided.

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“…Recent experimental evidence in mammals has indicated that the portion of the genome that is transcribed, as well as the number of functional RNAs in the genome, is much higher than previously thought [1]–[10]. Functional RNAs include noncoding RNAs as well as cis-acting RNA elements within mRNAs.…”

Section: Introductionmentioning

confidence: 99%

Conserved Secondary Structures in Aspergillus

McGuire

2008

PLoS ONE

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BackgroundRecent evidence suggests that the number and variety of functional RNAs (ncRNAs as well as cis-acting RNA elements within mRNAs ) is much higher than previously thought; thus, the ability to computationally predict and analyze RNAs has taken on new importance. We have computationally studied the secondary structures in an alignment of six Aspergillus genomes. Little is known about the RNAs present in this set of fungi, and this diverse set of genomes has an optimal level of sequence conservation for observing the correlated evolution of base-pairs seen in RNAs.Methodology/Principal FindingsWe report the results of a whole-genome search for evolutionarily conserved secondary structures, as well as the results of clustering these predicted secondary structures by structural similarity. We find a total of 7450 predicted secondary structures, including a new predicted ∼60 bp long hairpin motif found primarily inside introns. We find no evidence for microRNAs. Different types of genomic regions are over-represented in different classes of predicted secondary structures. Exons contain the longest motifs (primarily long, branched hairpins), 5′ UTRs primarily contain groupings of short hairpins located near the start codon, and 3′ UTRs contain very little secondary structure compared to other regions. There is a large concentration of short hairpins just inside the boundaries of exons. The density of predicted intronic RNAs increases with the length of introns, and the density of predicted secondary structures within mRNA coding regions increases with the number of introns in a gene.Conclusions/SigificanceThere are many conserved, high-confidence RNAs of unknown function in these Aspergillus genomes, as well as interesting spatial distributions of predicted secondary structures. This study increases our knowledge of secondary structure in these aspergillus organisms.

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Use of tiling array data and RNA secondary structure predictions to identify noncoding RNA genes

Cited by 15 publications

References 35 publications

Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses

Genome-Wide Networks of Amino Acid Covariances Are Common among Viruses

No-match ORESTES explored as tumor markers

Conserved Secondary Structures in Aspergillus

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