Akito Taneda

Accumulation of Potato spindle tuber viroid-specific small RNAs is accompanied by specific changes in gene expression in two tomato cultivars

To better understand the biogenesis of viroid-specific small RNAs and their possible role in disease induction, we have examined the accumulation of these small RNAs in potato spindle tuber viroid (PSTVd)-infected tomato plants. Large-scale sequence analysis of viroid-specific small RNAs revealed active production from the upper portion of the pathogenicity and central domains, two regions previously thought to be underrepresented. Profiles of small RNA populations derived from PSTVd antigenomic RNA were more variable, with differences between infected Rutgers (severe symptoms) and Moneymaker (mild symptoms) plants pointing to possible cultivar-specific differences in small RNA synthesis and/or stability. Using microarray analysis, we monitored the effects of PSTVd infection on the expression levels of >100 tomato genes containing potential binding sites for PSTVd small RNAs. Of 18 such genes down-regulated early in infection, two genes involved in gibberellin or jasmonic acid biosynthesis contain binding sites for PSTVd small RNAs in their respective ORFs.

MODenA: a multi-objective rnA inverse folding

Artificially synthesized RNA molecules have recently come under study since such molecules have a potential for creating a variety of novel functional molecules. When designing artificial RNA sequences, secondary structure should be taken into account since functions of noncoding RNAs strongly depend on their structure. RNA inverse folding is a methodology for computationally exploring the RNA sequences folding into a user-given target structure. In the present study, we developed a multi-objective genetic algorithm, MODENA (Multi-Objective DEsign of Nucleic Acids), for RNA inverse folding. MODENA explores the approximate set of weak Pareto optimal solutions in the objective function space of 2 objective functions, a structure stability score and structure similarity score. MODENA can simultaneously design multiple different RNA sequences at 1 run, whose lowest free energies range from a very stable value to a higher value near those of natural counterparts. MODENA and previous RNA inverse folding programs were benchmarked with 29 target structures taken from the Rfam database, and we found that MODENA can successfully design 23 RNA sequences folding into the target structures; this result is better than those of the other benchmarked RNA inverse folding programs. The multi-objective genetic algorithm gives a useful framework for a functional biomolecular design. Executable files of MODENA can be obtained at http://rna.eit.hirosaki-u.ac.jp/modena/.

Multi-objective pairwise RNA sequence alignment

MOTIVATION With an increase in the number of known biological functions of non-coding RNAs, the importance of RNA sequence alignment has risen. RNA sequence alignment problem has been investigated by many researchers as a mono-objective optimization problem where contributions from sequence similarity and secondary structure are taken into account through a single objective function. Since there is a trade-off between these two objective functions, usually we cannot obtain a single solution that has both the best sequence similarity score and the best structure score simultaneously. Multi-objective optimization is a widely used framework for the optimization problems with conflicting objective functions. So far, no one has examined how good alignments we can obtain by applying multi-objective optimization to structural RNA sequence alignment problem. RESULTS We developed a pairwise RNA sequence alignment program, Cofolga2mo, based on multi-objective genetic algorithm (MOGA). We tested Cofolga2mo with a benchmark dataset which includes sequence pairs with a wide range of sequence identity, and we obtained at most 100 alignments for each inputted RNA sequence pair as an approximate set of weak Pareto optimal solutions. We found that the alignments in the approximate set give benchmark results comparable to those obtained by the state-of-the-art mono-objective RNA alignment algorithms. Moreover, we found that our algorithm is efficient in both time and memory usage compared to the other methods. AVAILABILITY Our MOGA programs for structural RNA sequence alignment can be downloaded at http://rna.eit.hirosaki-u.ac.jp/cofolga2mo/.

Multi-objective genetic algorithm for pseudoknotted RNA sequence design.

RNA inverse folding is a computational technology for designing RNA sequences which fold into a user-specified secondary structure. Although pseudoknots are functionally important motifs in RNA structures, less reports concerning the inverse folding of pseudoknotted RNAs have been done compared to those for pseudoknot-free RNA design. In this paper, we present a new version of our multi-objective genetic algorithm (MOGA), MODENA, which we have previously proposed for pseudoknot-free RNA inverse folding. In the new version of MODENA, (i) a new crossover operator is implemented and (ii) pseudoknot prediction methods, IPknot and HotKnots, are used to evaluate the designed RNA sequences, allowing us to perform the inverse folding of pseudoknotted RNAs. The new version of MODENA with the new crossover operator was benchmarked with a dataset composed of natural pseudoknotted RNA secondary structures, and we found that MODENA can successfully design more pseudoknotted RNAs compared to the other pseudoknot design algorithm. In addition, a sequence constraint function newly implemented in the new version of MODENA was tested by designing RNA sequences which fold into the pseudoknotted structure of a hepatitis delta virus ribozyme; as a result, we successfully designed eight RNA sequences. The new version of MODENA is downloadable from http://rna.eit.hirosaki-u.ac.jp/modena/.

Deep sequencing uncovers commonality in small RNA profiles between transgene-induced and naturally occurring RNA silencing of chalcone synthase-A gene in petunia

BackgroundIntroduction of a transgene that transcribes RNA homologous to an endogenous gene in the plant genome can induce silencing of both genes, a phenomenon termed cosuppression. Cosuppression was first discovered in transgenic petunia plants transformed with the CHS-A gene encoding chalcone synthase, in which nonpigmented sectors in flowers or completely white flowers are produced. Some of the flower-color patterns observed in transgenic petunias having CHS-A cosuppression resemble those in existing nontransgenic varieties. Although the mechanism by which white sectors are generated in nontransgenic petunia is known to be due to RNA silencing of the CHS-A gene as in cosuppression, whether the same trigger(s) and/or pattern of RNA degradation are involved in these phenomena has not been known. Here, we addressed this question using deep-sequencing and bioinformatic analyses of small RNAs.ResultsWe analyzed short interfering RNAs (siRNAs) produced in nonpigmented sectors of petal tissues in transgenic petunia plants that have CHS-A cosuppression and a nontransgenic petunia variety Red Star, that has naturally occurring CHS-A RNA silencing. In both silencing systems, 21-nt and 22-nt siRNAs were the most and the second-most abundant size classes, respectively. CHS-A siRNA production was confined to exon 2, indicating that RNA degradation through the RNA silencing pathway occurred in this exon. Common siRNAs were detected in cosuppression and naturally occurring RNA silencing, and their ranks based on the number of siRNAs in these plants were correlated with each other. Noticeably, highly abundant siRNAs were common in these systems. Phased siRNAs were detected in multiple phases at multiple sites, and some of the ends of the regions that produced phased siRNAs were conserved.ConclusionsThe features of siRNA production found to be common to cosuppression and naturally occurring silencing of the CHS-A gene indicate mechanistic similarities between these silencing systems especially in the biosynthetic processes of siRNAs including cleavage of CHS-A transcripts and subsequent production of secondary siRNAs in exon 2. The data also suggest that these events occurred at multiple sites, which can be a feature of these silencing phenomena.

Adplot: detection and visualization of repetitive patterns in complete genomes

MOTIVATION Repetitive DNA sequences are abundant in genomes and efficient mining of significant repeats is important as the first step of repetitive sequence research. Although many computational tools for the purpose, either automatic or visualization ones, have been developed, detection and analysis of approximate repeats are still non-trivial task. RESULTS Auto Dot PLOT (Adplot), a dotplot-like repetitive pattern visualization program with a window filtering based on iid Bernoulli trials, is developed and applied to yeast chromosomes and human T cell receptor locus sequence. Typical examples found in yeast chromosomes 1 and 10 and a tandem repeat of periods longer than 10,000 bp in human T cell receptor locus are presented. A complex structure composed of both direct and palindromic repeats found in yeast chromosome 10 is also visualized as specific dot pattern. Computational time measured by a Pentium 3 PC for each yeast auto chromosome with a standard parameter setting is linearly scaled and below 10 s per one chromosome, indicating efficiency of the program. From the examples, it is shown that Adplot can visualize approximate local repeat structures and give us a diagnosis power for inferring a duplicational history of repeats. AVAILABILITY Adplot can be obtained by an e-mail request.

Multi-objective optimization for RNA design with multiple target secondary structures

BackgroundRNAs are attractive molecules as the biological parts for synthetic biology. In particular, the ability of conformational changes, which can be encoded in designer RNAs, enables us to create multistable molecular switches that function in biological circuits. Although various algorithms for designing such RNA switches have been proposed, the previous algorithms optimize the RNA sequences against the weighted sum of objective functions, where empirical weights among objective functions are used. In addition, an RNA design algorithm for multiple pseudoknot targets is currently not available.ResultsWe developed a novel computational tool for automatically designing RNA sequences which fold into multiple target secondary structures. Our algorithm designs RNA sequences based on multi-objective genetic algorithm, by which we can explore the RNA sequences having good objective function values without empirical weight parameters among the objective functions. Our algorithm has great flexibility by virtue of this weight-free nature. We benchmarked our multi-target RNA design algorithm with the datasets of two, three, and four target structures and found that our algorithm shows better or comparable design performances compared with the previous algorithms, RNAdesign and Frnakenstein. In addition to the benchmarks with pseudoknot-free datasets, we benchmarked MODENA with two-target pseudoknot datasets and found that MODENA can design the RNAs which have the target pseudoknotted secondary structures whose free energies are close to the lowest free energy. Moreover, we applied our algorithm to a ribozyme-based ON-switch which takes a ribozyme-inactive secondary structure when the theophylline aptamer structure is assumed.ConclusionsCurrently, MODENA is the only RNA design software which can be applied to multiple pseudoknot targets. Successful design results for the multiple targets and an RNA device indicate usefulness of our multi-objective RNA design algorithm.

An efficient genetic algorithm for structural RNA pairwise alignment and its application to non-coding RNA discovery in yeast

BackgroundAligning RNA sequences with low sequence identity has been a challenging problem since such a computation essentially needs an algorithm with high complexities for taking structural conservation into account. Although many sophisticated algorithms for the purpose have been proposed to date, further improvement in efficiency is necessary to accelerate its large-scale applications including non-coding RNA (ncRNA) discovery.ResultsWe developed a new genetic algorithm, Cofolga2, for simultaneously computing pairwise RNA sequence alignment and consensus folding, and benchmarked it using BRAliBase 2.1. The benchmark results showed that our new algorithm is accurate and efficient in both time and memory usage. Then, combining with the originally trained SVM, we applied the new algorithm to novel ncRNA discovery where we compared S. cerevisiae genome with six related genomes in a pairwise manner. By focusing our search to the relatively short regions (50 bp to 2,000 bp) sandwiched by conserved sequences, we successfully predict 714 intergenic and 1,311 sense or antisense ncRNA candidates, which were found in the pairwise alignments with stable consensus secondary structure and low sequence identity (≤ 50%). By comparing with the previous predictions, we found that > 92% of the candidates is novel candidates. The estimated rate of false positives in the predicted candidates is 51%. Twenty-five percent of the intergenic candidates has supports for expression in cell, i.e. their genomic positions overlap those of the experimentally determined transcripts in literature. By manual inspection of the results, moreover, we obtained four multiple alignments with low sequence identity which reveal consensus structures shared by three species/sequences.ConclusionThe present method gives an efficient tool complementary to sequence-alignment-based ncRNA finders.

Cofolga: a genetic algorithm for finding the common folding of two RNAs

In order to predict non-coding RNA genes and functions on the basis of genome sequences, accurate secondary structure prediction is useful. Although single-sequence folding programs such as mfold have been successful, it is of great importance to develop a novel approach for further improvement of the prediction performance. In the present paper, a secondary structure prediction method based on genetic algorithm, Cofolga, is proposed. The program developed performs folding and alignment of two homologous RNAs simultaneously. Cofolga was tested with a dataset composed of 13 tRNAs, seven 5S rRNAs, five RNase P RNAs, and five SRP RNAs; as a result, it turned out that the average prediction accuracies for the tRNAs, 5S rRNAs, RNase P RNAs, and SRP RNAs obtained by Cofolga with an optimal weight factor and default parameters were 83.6, 81.8, 73.5, and 67.7%, respectively. These results were superior to those obtained by a single-sequence folding based on free-energy minimization in which corresponding average prediction accuracies were 52.4, 47.4, 57.7, and 52.3%, respectively. Cofolga has a post-processing in which a single-sequence folding is performed after fixation of a predicted common structure; this post-processing enables Cofolga to predict a structure that is present in one of two RNAs alone. The executable files of Cofolga (for Windows/Unix/Mac) can be obtained by an e-mail request.

A small nucleolar RNA functions in rRNA processing in Caenorhabditis elegans.

CeR-2 RNA is one of the newly identified Caenorhabditis elegans noncoding RNAs (ncRNAs). The characterization of CeR-2 by RNomic studies has failed to classify it into any known ncRNA family. In this study, we examined the spatiotemporal expression patterns of CeR-2 to gain insight into its function. CeR-2 is expressed in most cells from the early embryo to adult stages. The subcellular localization of this RNA is analogous to that of fibrillarin, a major protein of the nucleolus. It was observed that knockdown of C/D small nucleolar ribonucleoproteins (snoRNPs), but not of H/ACA snoRNPs, resulted in the aberrant nucleolar localization of CeR-2 RNA. A mutant worm with a reduced amount of cellular CeR-2 RNA showed changes in its pre-rRNA processing pattern compared with that of the wild-type strain N2. These results suggest that CeR-2 RNA is a C/D snoRNA involved in the processing of rRNAs.