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Growing recognition of the numerous, diverse and important roles played by non-coding RNA in all organisms motivates better elucidation of these cellular components. Comparative genomics is a powerful tool for this task and is arguably preferable to any high-throughput experimental technology currently available, because evolutionary conservation highlights functionally important regions. Conserved secondary structure, rather than primary sequence, is the hallmark of many functionally important RNAs, because compensatory substitutions in base-paired regions preserve structure. Unfortunately, such substitutions also obscure sequence identity and confound alignment algorithms, which complicates analysis greatly. This paper surveys recent computational advances in this difficult arena, which have enabled genome-scale prediction of cross-species conserved RNA elements. These predictions suggest that a wealth of these elements indeed exist.

Background: An essential driving component in the co-evolution of plants and insects is the ability to produce and handle bioactive compounds. Plants produce bioactive natural products for defense, but some insects detoxify and/or sequester the compounds, opening up for new niches with fewer competitors. To study the molecular mechanism behind the co-adaption in plant-insect interactions, we have investigated the interactions between Lotus corniculatus and Zygaena filipendulae. They both contain cyanogenic glucosides which liberate toxic hydrogen cyanide upon breakdown. Moths belonging to the Zygaena family are the only insects known, able to carry out both de novo biosynthesis and sequestration of the same cyanogenic glucosides as those from their feed plants. The biosynthetic pathway for cyanogenic glucoside biosynthesis in Z. filipendulae proceeds using the same intermediates as in the well known pathway from plants, but none of the enzymes responsible have been identified. A genomics strategy founded on 454 pyrosequencing of the Z. filipendulae transcriptome was undertaken to identify some of these enzymes in Z. filipendulae., Results: Comparisons of the Z. filipendulae transcriptome with the sequenced genomes of Bombyx mori, Drosophila melanogaster, Tribolium castaneum, Apis mellifera and Anopheles gambiae indicate a high coverage of the Z. filipendulae transcriptome. 11% of the Z. filipendulae transcriptome sequences were assigned to Gene Ontology categories. Candidate genes for enzymes functioning in the biosynthesis of cyanogenic glucosides (cytochrome P450 and family 1 glycosyltransferases) were identified based on sequence length, number of copies and presence/absence of close homologs in D. melanogaster, B. mori and the cyanogenic butterfly Heliconius. Examination of biased codon usage, GC content and selection on gene candidates support the notion of cyanogenesis as an "old" trait within Ditrysia, as well as its origins being convergent between plants and insects., Conclusion: Pyrosequencing is an attractive approach to gain access to genes in the biosynthesis of bio-active natural products from insects and other organisms, for which the genome sequence is not known. Based on analysis of the Z. filipendulae transcriptome, promising gene candidates for biosynthesis of cyanogenic glucosides was identified, and the suitability of Z. filipendulae as a model system for cyanogenesis in insects is evident.

User-driven in silico RNA homology search is still a nontrivial task. In part, this is the consequence of a limited precision of the computational tools in spite of recent exciting progress in this area, and to a certain extent, computational costs are still problematic in practice. An important, and as we argue here, dominating issue is the dependence on good curated (secondary) structural alignments of the RNAs. These are often hard to obtain, not so much because of an inherent limitation in the available data, but because they require substantial manual curation, an effort that is rarely acknowledged. Here, we qualitatively describe a realistic scenario for what a "regular user" (i.e., a nonexpert in a particular RNA family) can do in practice, and what kind of results are likely to be achieved. Despite the indisputable advances in computational RNA biology, the conclusion is discouraging: BLAST still works better or equally good as other methods unless extensive expert knowledge on the RNA family is included. However, when good curated data are available the recent development yields further improvements in finding remote homologs. Homology search beyond the reach of BLAST hence is not at all a routine task.

Unlabelled: MicroRNAs (miRNAs) are a group of small, approximately 21 nt long, riboregulators inhibiting gene expression at a post-transcriptional level. Their most distinctive structural feature is the foldback hairpin of their precursor pre-miRNAs. Even though each pre-miRNA deposited in miRBase has its secondary structure already predicted, little is known about the patterns of structural conservation among pre-miRNAs. We address this issue by clustering the human pre-miRNA sequences based on pairwise, sequence and secondary structure alignment using FOLDALIGN, followed by global multiple alignment of obtained clusters by WAR. As a result, the common secondary structure was successfully determined for four FOLDALIGN clusters: the RF00027 structural family of the Rfam database and three clusters with previously undescribed consensus structures., Availability: http://genome.ku.dk/resources/mirclust

Computational methods for determining the secondary structure of RNA sequences from given alignments are currently either based on thermodynamic folding, compensatory base pair substitutions or both. However, there is currently no approach that combines both sources of information in a single optimization problem. Here, we present a model that formally integrates both the energy-based and evolution-based approaches to predict the folding of multiple aligned RNA sequences. We have implemented an extended version of Pfold that identifies base pairs that have high probabilities of being conserved and of being energetically favorable. The consensus structure is predicted using a maximum expected accuracy scoring scheme to smoothen the effect of incorrectly predicted base pairs. Parameter tuning revealed that the probability of base pairing has a higher impact on the RNA structure prediction than the corresponding probability of being single stranded. Furthermore, we found that structurally conserved RNA motifs are mostly supported by folding energies. Other problems (e.g. RNA-folding kinetics) may also benefit from employing the principles of the model we introduce. Our implementation, PETfold, was tested on a set of 46 well-curated Rfam families and its performance compared favorably to that of Pfold and RNAalifold.

Recent computational scans for non-coding RNAs (ncRNAs) in multiple organisms have relied on existing multiple sequence alignments. However, as sequence similarity drops, a key signal of RNA structure--frequent compensating base changes--is increasingly likely to cause sequence-based alignment methods to misalign, or even refuse to align, homologous ncRNAs, consequently obscuring that structural signal. We have used CMfinder, a structure-oriented local alignment tool, to search the ENCODE regions of vertebrate multiple alignments. In agreement with other studies, we find a large number of potential RNA structures in the ENCODE regions. We report 6587 candidate regions with an estimated false-positive rate of 50%. More intriguingly, many of these candidates may be better represented by alignments taking the RNA secondary structure into account than those based on primary sequence alone, often quite dramatically. For example, approximately one-quarter of our predicted motifs show revisions in >50% of their aligned positions. Furthermore, our results are strongly complementary to those discovered by sequence-alignment-based approaches--84% of our candidates are not covered by Washietl et al., increasing the number of ncRNA candidates in the ENCODE region by 32%. In a group of 11 ncRNA candidates that were tested by RT-PCR, 10 were confirmed to be present as RNA transcripts in human tissue, and most show evidence of significant differential expression across tissues. Our results broadly suggest caution in any analysis relying on multiple sequence alignments in less well-conserved regions, clearly support growing appreciation for the biological significance of ncRNAs, and strongly support the argument for considering RNA structure directly in any searches for these elements.

We have developed a semiautomated RNA sequence editor (SARSE) that integrates tools for analyzing RNA alignments. The editor highlights different properties of the alignment by color, and its integrated analysis tools prevent the introduction of errors when doing alignment editing. SARSE readily connects to external tools to provide a flexible semiautomatic editing environment. A new method, Pcluster, is introduced for dividing the sequences of an RNA alignment into subgroups with secondary structure differences. Pcluster was used to evaluate 574 seed alignments obtained from the Rfam database and we identified 71 alignments with significant prediction of inconsistent base pairs and 102 alignments with significant prediction of novel base pairs. Four RNA families were used to illustrate how SARSE can be used to manually or automatically correct the inconsistent base pairs detected by Pcluster: the mir-399 RNA, vertebrate telomase RNA (vert-TR), bacterial transfer-messenger RNA (tmRNA), and the signal recognition particle (SRP) RNA. The general use of the method is illustrated by the ability to accommodate pseudoknots and handle even large and divergent RNA families. The open architecture of the SARSE editor makes it a flexible tool to improve all RNA alignments with relatively little human intervention. Online documentation and software are available at (http://sarse.ku.dk).

Background: The mitochondria are involved in many basic functions in cells of vertebrates, and can be considered the power generator of the cell. Though the mitochondria have been extensively studied there appear to be only few expression studies of mitochondrial genes involving a large number of tissues and developmental stages. Here, we conduct an analysis using the PigEST resource 1 which contains expression information from 35 tissues distributed on one normalized and 97 non-normalized cDNA libraries of which 24 are from developmental stages. The mitochondrial PigEST resource contains 41,499 mitochondrial sequences., Results: The mitochondrial EST (Expressed Sequence Tag) sequences were assembled into contigs which covers more than 94 percent of the porcine mitochondrial genome, with an average of 976 EST sequences per nucleotide. This data was converted into expression values for the individual genes in each cDNA library revealing differential expression between genes expressed in cDNA libraries from developmental and adult stages. For the 13 protein coding genes (and several RNA genes), we find one set of six genes, containing all cytochrome oxidases, that are upregulated in developmental tissues, whereas the remaining set of seven genes, containing all ATPases, that are upregulated in adult muscle and brain tissues. Further, the COX I (Cytochrome oxidase subunit one) expression profile differs from that of the remaining genes, which could be explained by a tissue specific cleavage event or degradation pattern, and is especially pronounced in developmental tissues. Finally, as expected cDNA libraries from muscle tissues contain by far the largest amount (up to 20%) of expressed mitochondrial genes., Conclusion: Our results present novel insight into differences in mitochondrial gene expression, emphasizing differences between adult and developmental tissues. Our work indicates that there are presently unknown mechanisms which work to customize mitochondrial processes to the specific needs of the cell, illustrated by the different patterns between adult and developmental tissues. Furthermore, our results also provide novel insight into how in-depth sequencing can provide significant information about expression patterns.

It has become clear that noncoding RNAs (ncRNA) play important roles in cells, and emerging studies indicate that there might be a large number of unknown ncRNAs in mammalian genomes. There exist computational methods that can be used to search for ncRNAs by comparing sequences from different genomes. One main problem with these methods is their computational complexity, and heuristics are therefore employed. Two heuristics are currently very popular: pre-folding and pre-aligning. However, these heuristics are not ideal, as pre-aligning is dependent on sequence similarity that may not be present and pre-folding ignores the comparative information. Here, pruning of the dynamical programming matrix is presented as an alternative novel heuristic constraint. All subalignments that do not exceed a length-dependent minimum score are discarded as the matrix is filled out, thus giving the advantage of providing the constraints dynamically. This has been included in a new implementation of the FOLDALIGN algorithm for pairwise local or global structural alignment of RNA sequences. It is shown that time and memory requirements are dramatically lowered while overall performance is maintained. Furthermore, a new divide and conquer method is introduced to limit the memory requirement during global alignment and backtrack of local alignment. All branch points in the computed RNA structure are found and used to divide the structure into smaller unbranched segments. Each segment is then realigned and backtracked in a normal fashion. Finally, the FOLDALIGN algorithm has also been updated with a better memory implementation and an improved energy model. With these improvements in the algorithm, the FOLDALIGN software package provides the molecular biologist with an efficient and user-friendly tool for searching for new ncRNAs. The software package is available for download at http://foldalign.ku.dk.

Background: Non-coding RNAs (ncRNAs) are involved in a wide spectrum of regulatory functions. Within recent years, there have been increasing reports of observed polyadenylated ncRNAs and mRNA like ncRNAs in eukaryotes. To investigate this further, we examined the large data set in the Sino-Danish PigEST resource http://pigest.ku.dk which also contains expression information distributed on 97 non-normalized cDNA libraries., Results: We constructed a pipeline, EST2ncRNA, to search for known and novel ncRNAs. The pipeline utilises sequence similarity to ncRNA databases (blast), structure similarity to Rfam (RaveNnA) as well as multiple alignments to predict conserved novel putative RNA structures (RNAz). EST2ncRNA was fed with 48,000 contigs and 73,000 singletons available from the PigEST resource. Using the pipeline we identified known RNA structures in 137 contigs and single reads (conreads), and predicted high confidence RNA structures in non-protein coding regions of additional 1,262 conreads. Of these, structures in 270 conreads overlap with existing predictions in human. To sum up, the PigEST resource comprises trans-acting elements (ncRNAs) in 715 contigs and 340 singletons as well as cis-acting elements (inside UTRs) in 311 contigs and 51 singletons, of which 18 conreads contain both predictions of trans- and cis-acting elements. The predicted RNAz candidates were compared with the PigEST expression information and we identify 114 contigs with an RNAz prediction and expression in at least ten of the non-normalised cDNA libraries. We conclude that the contigs with RNAz and known predictions are in general expressed at a much lower level than protein coding transcripts. In addition, we also observe that our ncRNA candidates constitute about one to two percent of the genes expressed in the cDNA libraries. Intriguingly, the cDNA libraries from developmental (brain) tissues contain the highest amount of ncRNA candidates, about two percent. These observations are related to existing knowledge and hypotheses about the role of ncRNAs in higher organisms. Furthermore, about 80% porcine coding transcripts (of 18,600 identified) as well as less than one-third ORF-free transcripts are conserved at least in the closely related bovine genome. Approximately one percent of the coding and 10% of the remaining matches are unique between the PigEST data and cow genome. Based on the pig-cow alignments, we searched for similarities to 16 other organisms by UCSC available alignments, which resulted in a 87% coverage by the human genome for instance., Conclusion: Besides recovering several of the already annotated functional RNA structures, we predicted a large number of high confidence conserved secondary structures in polyadenylated porcine transcripts. Our observations of relatively low expression levels of predicted ncRNA candidates together with the observations of higher relative amount in cDNA libraries from developmental stages are in agreement with the current paradigm of ncRNA roles in higher organisms and supports the idea of polyadenylated ncRNAs.

Motivation: Single nucleotide polymorphisms (SNPs) analysis is an important means to study genetic variation. A fast and cost-efficient approach to identify large numbers of novel candidates is the SNP mining of large scale sequencing projects. The increasing availability of sequence trace data in public repositories makes it feasible to evaluate SNP predictions on the DNA chromatogram level. MAVIANT, a platform-independent Multipurpose Alignment VIewing and Annotation Tool, provides DNA chromatogram and alignment views and facilitates evaluation of predictions. In addition, it supports direct manual annotation, which is immediately accessible and can be easily shared with external collaborators., Results: Large-scale SNP mining of polymorphisms bases on porcine EST sequences yielded more than 7900 candidate SNPs in coding regions (cSNPs), which were annotated relative to the human genome. Non-synonymous SNPs were analyzed for their potential effect on the protein structure/function using the PolyPhen and SIFT prediction programs. Predicted SNPs and annotations are stored in a web-based database. Using MAVIANT SNPs can visually be verified based on the DNA sequencing traces. A subset of candidate SNPs was selected for experimental validation by resequencing and genotyping. This study provides a web-based DNA chromatogram and contig browser that facilitates the evaluation and selection of candidate SNPs, which can be applied as genetic markers for genome wide genetic studies., Availability: The stand-alone version of MAVIANT program for local use is freely available under GPL license terms at http://snp.agrsci.dk/maviant., Supplementary Information: Supplementary data are available at Bioinformatics online.

In 2001 there were four PubMed entries matching the word "microRNA" (miRNA). Interestingly, this number has now far exceeded 1300 and is still rapidly increasing. This more than anything demonstrates the extreme attention this field has had within a short period of time. With the large amounts of sequence data being generated, the need for analysis by computational approaches is obvious. Here, we review the general principles used in computational gene and target finding, and discuss the strengths and weaknesses of the methods. Several methods rely on detection of evolutionary conserved candidates, but recent methods have challenged this paradigm by simultaneously searching for the gene and the corresponding target(s). Whereas the early methods made predictions based on sets of hand-derived rules from precursor-miRNA structure or observed target-miRNA interactions, recent methods apply machine learning techniques. Even though these methods are already powerful, the amount of data they rely on is still limited. Since it is evident that data are continuously being generated, it must be anticipated that these methods will further improve their performance.

Motivation: An apparent paradox in computational RNA structure prediction is that many methods, in advance, require a multiple alignment of a set of related sequences, when searching for a common structure between them. However, such a multiple alignment is hard to obtain even for few sequences with low sequence similarity without simultaneously folding and aligning them. Furthermore, it is of interest to conduct a multiple alignment of RNA sequence candidates found from searching as few as two genomic sequences., Results: Here, based on the PMcomp program, we present a global multiple alignment program, foldalignM, which performs especially well on few sequences with low sequence similarity, and is comparable in performance with state of the art programs in general. In addition, it can cluster sequences based on sequence and structure similarity and output a multiple alignment for each cluster. Furthermore, preliminary results with local datasets indicate that the program is useful for post processing foldalign pairwise scans., Availability: The program foldalignM is implemented in JAVA and is, along with some accompanying PERL scripts, available at http://foldalign.ku.dk/

Background: Knowledge of the structure of gene expression is essential for mammalian transcriptomics research. We analyzed a collection of more than one million porcine expressed sequence tags (ESTs), of which two-thirds were generated in the Sino-Danish Pig Genome Project and one-third are from public databases. The Sino-Danish ESTs were generated from one normalized and 97 non-normalized cDNA libraries representing 35 different tissues and three developmental stages., Results: Using the Distiller package, the ESTs were assembled to roughly 48,000 contigs and 73,000 singletons, of which approximately 25% have a high confidence match to UniProt. Approximately 6,000 new porcine gene clusters were identified. Expression analysis based on the non-normalized libraries resulted in the following findings. The distribution of cluster sizes is scaling invariant. Brain and testes are among the tissues with the greatest number of different expressed genes, whereas tissues with more specialized function, such as developing liver, have fewer expressed genes. There are at least 65 high confidence housekeeping gene candidates and 876 cDNA library-specific gene candidates. We identified differential expression of genes between different tissues, in particular brain/spinal cord, and found patterns of correlation between genes that share expression in pairs of libraries. Finally, there was remarkable agreement in expression between specialized tissues according to Gene Ontology categories., Conclusion: This EST collection, the largest to date in pig, represents an essential resource for annotation, comparative genomics, assembly of the pig genome sequence, and further porcine transcription studies.

Human and mouse genome sequences contain roughly 100,000 regions that are unalignable in primary sequence and neighbor corresponding alignable regions between both organisms. These pairs are generally assumed to be nonconserved, although the level of structural conservation between these has never been investigated. Owing to the limitations in computational methods, comparative genomics has been lacking the ability to compare such nonconserved sequence regions for conserved structural RNA elements. We have investigated the presence of structural RNA elements by conducting a local structural alignment, using FOLDALIGN, on a subset of these 100,000 corresponding regions and estimate that 1800 contain common RNA structures. Comparing our results with the recent mapping of transcribed fragments (transfrags) in human, we find that high-scoring candidates are twice as likely to be found in regions overlapped by transfrags than regions that are not overlapped by transfrags. To verify the coexpression between predicted candidates in human and mouse, we conducted expression studies by RT-PCR and Northern blotting on mouse candidates, which overlap with transfrags on human chromosome 20. RT-PCR results confirmed expression of 32 out of 36 candidates, whereas Northern blots confirmed four out of 12 candidates. Furthermore, many RT-PCR results indicate differential expression in different tissues. Hence, our findings suggest that there are corresponding regions between human and mouse, which contain expressed non-coding RNA sequences not alignable in primary sequence.

Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http://www.ag.auburn.edu/mirror/tmRDB/) and the Royal Veterinary and Agricultural University, Denmark (http://tmrdb.kvl.dk/). The signal recognition particle database (SRPDB) at http://psyche.uthct.edu/dbs/SRPDB/SRPDB.html is mirrored at http://srpdb.kvl.dk/ and the University of Goteborg (http://bio.lundberg.gu.se/dbs/SRPDB/SRPDB.html). The databases assist in investigations of the tmRNP (a ribonucleoprotein complex which liberates stalled bacterial ribosomes) and the SRP (a particle which recognizes signal sequences and directs secretory proteins to cell membranes). The curated tmRNA and SRP RNA alignments consider base pairs supported by comparative sequence analysis. Also shown are alignments of the tmRNA-associated proteins SmpB, ribosomal protein S1, alanyl-tRNA synthetase and Elongation Factor Tu, as well as the SRP proteins SRP9, SRP14, SRP19, SRP21, SRP54 (Ffh), SRP68, SRP72, cpSRP43, Flhf, SRP receptor (alpha) and SRP receptor (beta). All alignments can be easily examined using a new exploratory browser. The databases provide links to high-resolution structures and serve as depositories for structures obtained by molecular modeling.

We report on the construction of a high-resolution comparative map of porcine chromosome 17 (SSC17) focusing on evolutionary breakpoints with human chromosomes. The comparative map shows high homology with human chromosome 20 but suggests more limited homologies with other human chromosomes. SSC17 is of particular interest in studies of chromosomal organization due to the presence of QTLs that affect meat quality and carcass composition. A total of 158 pig ESTs available in databases or developed by the Sino-Danish Pig Genome Sequencing Consortium were mapped using the INRA-University of Minnesota porcine radiation hybrid panel. The high-resolution map was further anchored by fluorescence in situ hybridization. This study confirmed the extensive conservation between SSC17 and HSA20 and enabled the gene order to be determined. The homology of the SSC17 pericentromeric region was extended to other human chromosomes (HSA4, HSA8) and the chromosomal breakpoint boundaries were accurately defined. In total 15 breakpoints were identified.

We have identified the first porcine microRNA (miRNA) cluster (the mir17-92 cluster) and localized it to the q-arm of pig Chromosome 11. The miRNA cluster was found by sequence similarity search with human miRNA sequences against the pig genomic data generated within the Sino-Danish pig genome project. The resulting data contained three complete and two incomplete miRNA precursors of seven miRNAs from the human mir17-92 cluster. Because there is a 100% sequence identity between the four pig miRNAs and the corresponding human miRNAs, the sequences of three unavailable pig miRNAs were derived from the human data. The expression profiles of seven studied miRNAs were analyzed by hybridization to Northern blots containing five porcine tissues: cerebellum, cortex, hippocampus, kidney, and liver. In order to determine the localization of the mir17-92 cluster in the pig genome, we mapped it by PCR in the porcine somatic cell hybrid (SCH) panel and in the INRA-University of Minnesota (INRA-UMN) porcine radiation hybrid (IMpRH) panel. The PCR results enabled us to localize this cluster to the q-arm of pig Chromosome 11 and map it in relation to two microsatellites. Our study presents the first expression analyses of miRNAs in pig and adds information for further functional studies in this species.

Background: Comparative whole genome analysis of Mammalia can benefit from the addition of more species. The pig is an obvious choice due to its economic and medical importance as well as its evolutionary position in the artiodactyls., Results: We have generated approximately 3.84 million shotgun sequences (0.66X coverage) from the pig genome. The data are hereby released (NCBI Trace repository with center name "SDJVP", and project name "Sino-Danish Pig Genome Project") together with an initial evolutionary analysis. The non-repetitive fraction of the sequences was aligned to the UCSC human-mouse alignment and the resulting three-species alignments were annotated using the human genome annotation. Ultra-conserved elements and miRNAs were identified. The results show that for each of these types of orthologous data, pig is much closer to human than mouse is. Purifying selection has been more efficient in pig compared to human, but not as efficient as in mouse, and pig seems to have an isochore structure most similar to the structure in human., Conclusion: The addition of the pig to the set of species sequenced at low coverage adds to the understanding of selective pressures that have acted on the human genome by bisecting the evolutionary branch between human and mouse with the mouse branch being approximately 3 times as long as the human branch. Additionally, the joint alignment of the shot-gun sequences to the human-mouse alignment offers the investigator a rapid way to defining specific regions for analysis and resequencing.

The untranslated leader of the dimeric HIV-1 RNA genome is folded into a complex structure that plays multiple and essential roles in the viral replication cycle. Here, we have investigated secondary and tertiary structural elements within the 5' 744 nucleotides of the HIV-1 genome using a combination of bioinformatics, enzymatic probing, native gel electrophoresis, and UV-crosslinking experiments. We used a recently developed RNA folding algorithm (Pfold) to predict the common secondary structure of an alignment of 20 divergent HIV-1 sequences. Combining this analysis with biochemical data, we present a secondary structure model for the entire 744 nucleotide fragment, which incorporates previously recognized and novel structural elements. In particular, our data provided strong evidence for a long-distance interaction between the region encompassing the AUG Gag initiation codon and an upstream region and we demonstrate that this feature is highly conserved in distantly related human and animal retroviruses. To obtain information about tertiary interactions we applied an intramolecular UV-crosslinking strategy and identified a novel tertiary interaction within the PBS hairpin structure.

The Signal Recognition Particle Database (SRPDB) at http://psyche.uthct.edu/dbs/SRPDB/SRPDB.html and http://bio.lundberg.gu.se/dbs/SRPDB/SRPDB.html assists in the better understanding of the structure and function of the signal recognition particle (SRP), a ribonucleoprotein complex that recognizes signal sequences as they emerge from the ribosome. SRPDB provides alphabetically and phylogenetically ordered lists of SRP RNA and SRP protein sequences. The SRP RNA alignment emphasizes base pairs supported by comparative sequence analysis to derive accurate SRP RNA secondary structures for each species. This release includes a total of 181 SRP RNA sequences, 7 protein SRP9, 11 SRP14, 31 SRP19, 113 SRP54 (Ffh), 9 SRP68 and 12 SRP72 sequences. There are 44 new sequences of the SRP receptor alpha subunit and its FtsY homolog (a total of 99 entries). Additional data are provided for polypeptides with established or potential roles in SRP-mediated protein targeting, such as the beta subunit of SRP receptor, Flhf, Hbsu and cpSRP43. Also available are motifs for the identification of new SRP RNA sequences, 2D representations, three-dimensional models in PDB format, and links to the high-resolution structures of several SRP components. New to this version of SRPDB is the introduction of a relational database system and a SRP RNA prediction server (SRP-Scan) which allows the identification of SRP RNAs within genome sequences and also generates secondary structure diagrams.

Maintained at the University of Texas Health Science Center at Tyler, Texas, the tmRNA database (tmRDB) is accessible at the URL http://psyche.uthct.edu/dbs/tmRDB/tmRDB.html with mirror sites located at Auburn University, Auburn, Alabama (http://www.ag.auburn.edu/mirror/tmRDB/) and the Bioinformatics Research Center, Aarhus, Denmark (http://www.bioinf.au.dk/tmRDB/). The tmRDB collects and distributes information relevant to the study of tmRNA. In trans-translation, this molecule combines properties of tRNA and mRNA and binds several proteins to form the tmRNP. Related RNPs are likely to be functional in all bacteria. In this release of tmRDB, 186 new entries from 10 bacterial groups for a total of 274 tmRNA sequences have been added. Lists of the tmRNAs and the corresponding tmRNA-encoded tag-peptides are presented in alphabetical and phylogenetic order. The tmRNA sequences are aligned manually, assisted by computational tools, to determine base pairs supported by comparative sequence analysis. The tmRNA alignment, available in a variety of formats, provides the basis for the secondary and tertiary structure of each tmRNA molecule. Three-dimensional models of the tmRNAs and their associated proteins in PDB format give evidence for the recent progress that has been made in the understanding of tmRNP structure and function.

When a set of coregulated genes share a common structural RNA motif, e.g. a hairpin, most motif search approaches fail to locate the covarying but structurally conserved motif. There do exist methods that can locate structural RNA motifs, like FOLDALIGN, but the main problem with these methods is that they are computationally expensive. In FOLDALIGN, a major contribution to this is the use of a greedy algorithm to construct the multiple alignment. To ensure good quality many redundant computations must be made. However, by applying the greedy algorithm on a carefully selected subset of sequences, near full greedy quality can be obtained. The basic idea is to estimate the order in which the sequences entered a good greedy alignment. If such a ranking, found from all pairwise alignments, is in good agreement with the order of appearance in the multiple alignment, the core structural motif can be found by performing the greedy algorithm on just the top sequences in the ranking. The ranking used in this mini-greedy algorithm is found by using two complementing approaches: 1) When interpreting the FOLDALIGN score as an inner product (kernel), the sequences can be ranked according to their distance to their center of mass; 2) We construct an algorithm that attempts to find the K closest sequences in the vector space associated with the inner product, and the remaining sequences can be ranked by their minimum distance to any of the sequences, or to the center of mass in this set. The two approaches arecompared and merged, and the results discussed. We also show that structural alignments of near full greedy quality can found in significantly reduced time, using these methods. The algorithm is being included in the SLASH (Stem-Loop Align SearcH) server available at http://www.bioinf.au.dk/slash.

Correlations between sequence separation (in residues) and distance (in Angstrom) of any pair of amino acids in polypeptide chains are investigated. For each sequence separation we define a distance threshold. For pairs of amino acids where the distance between C alpha atoms is smaller than the threshold, a characteristic sequence (logo) motif, is found. The motifs change as the sequence separation increases: for small separations they consist of one peak located in between the two residues, then additional peaks at these residues appear, and finally the center peak smears out for very large separations. We also find correlations between the residues in the center of the motif. This and other statistical analysis are used to design neural networks with enhanced performance compared to earlier work. Importantly, the statistical analysis explains why neural networks perform better than simple statistical data-driven approaches such as pair probability density functions. The statistical results also explain characteristics of the network performance for increasing sequence separation. The improvement of the new network design is significant in the sequence separation range 10-30 residues. Finally, we find that the performance curve for increasing sequence separation is directly correlated to the corresponding information content. A WWW server, distanceP, is available at http://www.cbs.dtu.dk/services/distanceP/.

We study from a computational standpoint several different physical scales associated with structural features of DNA sequences, including dinucleotide scales such as base stacking energy and propeller twist, and trinucleotide scales such as bendability and nucleosome positioning. We show that these scales provide an alternative or complementary compact representation of DNA sequences. As an example we construct a strand invariant representation of DNA sequences. The scales can also be used to analyze and discover new DNA structural patterns, especially in combinations with hidden Markov models (HMMs). The scales are applied to HMMs of human promoter sequences revealing a number of significant differences between regions upstream and downstream of the transcriptional start point. Finally we show, with some qualifications, that such scales are by and large independent, and therefore complement each other.

Motivation: We extend the standard 'Sequence Logo' method of Schneider and Stevens (Nucleic Acids Res., 18, 6097-6100, 1990) to incorporate prior frequencies on the bases, allow for gaps in the alignments, and indicate the mutual information of base-paired regions in RNA., Results: Given an alignment of RNA sequences with the base pairings indicated, the program will calculate the information at each position, including the mutual information of the base pairs, and display the results in a 'Structure Logo'. Alignments without base pairing can also be displayed in a 'Sequence Logo', but still allowing gaps and incorporating prior frequencies if desired., Availability: The code is available from, and an Internet server can be used to run the program at, http://www.cbs.dtu.dk/gorodkin/appl/slogo. html.

We present a computational scheme to search for the most common motif, composed of a combination of sequence and structure constraints, among a collection of RNA sequences. The method uses a simplified version of the Sankoff algorithm for simultaneous folding and alignment of RNA sequences, but maintains tractability by constructing multi-sequence alignments from pairwise comparisons. The overall method has similarities to both CLUSTAL and CONSENSUS, but the core algorithm assures that the pairwise alignments are optimized for both sequence and structure conservation. Example solutions, and comparisons with other approaches, are provided. The solutions include finding consensus structures identical to published ones.