With the continued development of new computational tools for multiple sequence alignment, it is necessary today to develop benchmarks that aid the selection of the most effective tools. Simulation-based benchmarks have been proposed to meet this necessity, especially for non-coding sequences. However, it is not clear if such benchmarks truly represent real sequence data from any given group of species, in terms of the difficulty of alignment tasks.Drosophila group of species, and show that these data sets truly represent the variability observed in genomic data in terms of the difficulty of the alignment task. This allows us to make significant progress towards estimating the alignment accuracy of current tools in an absolute sense, going beyond only a relative assessment of different tools. We evaluate six widely used multiple alignment tools in the context of Drosophila non-coding sequences, and find the accuracy to be significantly different from previously reported values. Interestingly, the performance of most tools degrades more rapidly when there are more insertions than deletions in the data set, suggesting an asymmetric handling of insertions and deletions, even though none of the evaluated tools explicitly distinguishes these two types of events. We also examine the accuracy of two existing tools for annotating insertions versus deletions, and find their performance to be close to optimal in Drosophila non-coding sequences if provided with the true alignments.We find that the conventional simulation approach, which relies on empirically estimated values for various parameters such as substitution rate or insertion/deletion rates, is unable to generate synthetic sequences reflecting the broad genomic variation in conservation levels. We tackle this problem with a new method for simulating non-coding sequence evolution, by relying on genome-wide distributions of evolutionary parameters rather than their averages. We then generate synthetic data sets to mimic orthologous sequences from the Drosophila non-coding sequences, and shown it to be more realistic than traditional benchmarks. Apart from helping to select the most effective tools, these benchmarks will help practitioners of comparative genomics deal with the effects of alignment errors, by providing accurate estimates of the extent of these errors.We have developed a method to generate benchmarks for multiple alignments of  Drosophila species [The availability of genome sequences of closely related species  has pro species -6), offe species -12 in li species , and tha species .Given the availability of multiple tools to perform either of these two tasks, a researcher faces two important questions: "Which of the tools should I use for my task?" and "How accurate will the tool be on my data?" Answers to these come from studies that use data sets ("benchmarks") where the true answers are known, to evaluate and compare different tools. The design of benchmarks therefore directly affects the reliability of bioinformatics analyses that use those tools. The two most widely used benchmarking approaches for alignment tools are (i) to make use of biological sequences and their manually curated alignments from databases such as Homstrad , BAliBAS1) We present a new simulation-based benchmarking method that is based on the entire spectrum of values of its parameters as inferred from real data. This is in contrast to existing approaches that rely on the average observed values of the parameters.2) We quantify the difficulty of aligning a data set by leveraging recent developments  on estimDrosophila non-coding sequences. The specific alignment task we consider is that of global alignment of ~1-10 Kbp long sequences, and our conclusions may not apply to the task of local alignment, which was studied in [Drosophila genomes, and find these to be very different from previously reported values. We also evaluate two schemes for annotating insertions and deletions specifically, and find their accuracy to be comparable, and close to optimal.3) Using our new benchmarks, we evaluate and compare the accuracy of six multiple alignment tools  We find that data sets with an excess of deletions over insertions are more amenable to accurate alignment than those with an excess of insertions, suggesting an implicit bias  with respect to their treatment of indels, even though none of the evaluated tools explicitly makes a distinction between insertions and deletions.expected frequency of those events in the generated data sets. Variation in the frequency of these events, which underlie the difficulty of alignment tasks, results from the inherent randomness of the simulation process, i.e., the differences in random choices made from one "run" of the process to another. It is natural to ask if the resulting variability across data sets in a synthetic benchmark is comparable to the corresponding variability observed in real orthologous sequences. The question is particularly relevant due to the heterogeneity of non-coding sequences with respect to the density of functional elements and also motivated by the known variation in evolutionary rates across loci [Modeling of DNA sequence evolution has been studied extensively in the past, and state-of-the-art simulation programs -20 draw oss loci -36.Drosophila non-coding sequences (see Methods). A key difference in our implementation was that branch lengths  were estimated from non-coding sequences themselves, instead of synonymous substitution rates from coding sequences, as has been done previously. We elaborate on this important issue later in this section.We began by implementing the above-mentioned simulation paradigm, which we call the "traditional" paradigm, by incorporating the "constraint blocks" idea of Pollard et al.  into theDrosophila sequences from eight species (see Methods), computed the sum of branch lengths of the phylogenetic tree estimated from ~1 Kbp segments of alignment, and found the distribution of this statistic to have a large variance across the genome " alignment quality score as the agreement between two alignments, one generated from original sequences and the other from their reversed versions. Hall [Since substitution rates are generally correlated with indel rates, a large variance in the former implies a corresponding variance in indel frequencies, which of course lie at the root of the alignment problem. This suggests that if we could measure the "difficulty of alignment" in any region of the genome , we ought to see a large variability in this measure across the genome. Moreover, if the observed distribution of the alignment difficulty measure is comparable to that in a benchmark, we would be confident in making claims about performance of alignment tools based on that benchmark. The problem is that measuring alignment difficulty on real data requires knowledge of their true alignment, which is unavailable. Recent work by Landan and Graur  showed tns. Hall  later shns. Hall , but othK = 10 phylogenies {ϕ1, ϕ2, ..., ϕK} that are scaled versions of the original phylogeny ϕ0, i.e., every branch length in phylogeny ϕi is a constant factor τi times the corresponding branch length in ϕ0.  We modified the simulator to first sample at random one of the K phylogenies, and simulate according to this setting of branch lengths, with all other parameters being fixed as before. In other words, the distribution of alignment quality scores from the new simulation process is a mixture distribution, with components parameterized by different phylogenies and the probability of sampling any particular phylogeny being the mixture weight. We estimated an upper bound on the agreement between this mixture distribution and the observed distribution of alignment quality scores, by maximum likelihood training of mixture weights, through expectation-maximization algorithm [We hypothesized that the above observation about synthetic data sets was due to the use of a single setting of the branch lengths, and the relatively low variability resulting from the randomness of the process itself Figure . If thislgorithm . This "bThe above results, while encouraging in terms of better reproducing the genomic variability of alignment difficulty, were obtained by fitting parameters of the simulation process so as to best match real data. We next asked if we could achieve the same or better agreement between the synthetic and real data distributions without having seen the real distribution of alignment quality scores. This would then allow us to use the observed agreement as a relatively unbiased assessment of how realistic the benchmark is. Developing the mixture model idea from the previous section, we now computed for each parameter the entire distribution of values observed in real data alignments, just as the traditional approach estimates the average of these values. The simulation process was now made to sample each parameter independently from its empirical distribution, and then generate a data set based on the sampled parameter values. The benchmark thus constructed (comprising 10000 different data sets) was examined for its distribution of alignment quality scores, and as seen in Figure The above analysis was performed using the sum-of-pairs score (SPS), which is the simplest of the scores defined in the HoT approach . We repeK = 3, ..., 8. For each choice of K, 10000 sets of sequences corresponding to K different Drosophila species were simulated and the above alignment tools were run with default parameters or with the best setting recommended by their authors. We then compared the resulting alignments to the "true" alignments reported by the simulation program, using the following three commonly used evaluation measures [alignment agreement, which is the fraction of aligned base pairs  in the predicted alignment that agree with the true alignment, (ii) alignment sensitivity, which is the fraction of aligned base pairs of the true alignment that agree with the predicted alignment, and (iii) alignment specificity, which is the fraction of aligned base pairs of the predicted alignment that agree with the true alignment. Whereas the alignment agreement score considers aligned base pairs as well as bases aligned to gaps, the sensitivity and specificity scores are calculated only from aligned base pairs. The results of our evaluations are shown in Figure K. Its performance degrades more slowly (with increasing K) than the other tools, as a result of which the gap between Pecan and the other tools became larger more species were included in the tests. The average alignment agreement in five species alignments produced by Pecan (the species most divergent from D. melanogaster being D. pseudoobscura) was close to 80%, but degraded to ~67% when aligning all eight species.We used our new benchmark to evaluate and compare six leading multiple alignment tools that are publicly available and can align DNA sequences. These are ClustalW 2.0.5 , Dialignmeasures ,41: (i) K = 8, ClustalW showed an alignment agreement of 36% or 46% depending on whether there was an excess of insertions or deletions (respectively). The same trend was seen in terms of the alignment sensitivity and specificity measures. Noticably, Pecan was largely unaffected by this dichotomy of data sets.  that had an excess of insertions over deletions, and separately to those data sets with an excess of deletions , limiting ourselves to the eight-species data sets. All trends reported above were also seen in this alternative view of the results  also for alignment specificity, and for other species pairs and alignment programs as well  is added. Reasoning that phylogenies for which computed alignments are largely inaccurate would not be suitable for insertion/deletion annotation in any case, we chose to limit our assessment to the following five Drosophila species: D. melanogaster, D. simulans, D. yakuba, D. ananassae, and D. pseudoobscura  Indel Ratio Agreement, which is the agreement of the ratio of the number of insertions to the total number of indels between the two annotations, and (iii) Indel Annotation Coverage, which is the fraction of indel positions on which the two annotations agree (see Methods). Traditional alignment programs mark the predicted locations of insertions and deletions as "gaps", and do not proceed to annotate these gaps as being insertions or deletions. This latter task has received some attention recently with at least two "indel annotation schemes" being published, based on maximum-parsimony ("sbInfer" ) and proD. pseudoobscura, the species with the longest terminal branch in the phylogeny. Indel Ratio Agreement scores of both tools were close to optimal (1) in all five species. While the sensitivity scores of Indel Annotation Coverage of the two tools were above 90% across all five species, the specificity scores were above 90% only for the four species except D. pseudoobscura. The loss of accuracy on the D. pseudoobscura branch is presumably due to the fact that there is no "outgroup" species to aid disambiguation of insertions and deletions on this branch. We further discuss the implications of these observations in the next section. We also repeated our assessment for sequences with an excess of insertions or of deletions, as above, but no significant differences was observed between these two categories (data not shown).As summarized in Table Drosophila species. This new simulation method exploits the spectrum of values of evolutionary statistics  seen across a genome. We take advantage of an objective "alignment quality" measure to show that the synthetic sequences produced agree with real sequences not only in terms of evolutionary statistics, but are also as easy or hard to align as real data sets. In this sense, our evaluation results are more likely to reflect the actual accuracy values of alignment-related tools on data from Drosophila species. We note that our strategy of sampling parameters (used in evolutionary simulations) from their empirical distribution has parallels with traditional Bayesian inference where one integrates over  a prior distribution on parameters, rather than using a single point estimate.Choosing the most suitable tool for aligning orthologous sequences is essential to studies in comparative genomics and in molecular evolution, making it critical to develop accurate benchmarking methodology. In this study, we propose a novel simulation-based approach to generate realistic data sets mimicking orthologous non-coding sequences from multiple A key step in our benchmark construction was the ability to assess the quality of an alignment without access to the corresponding true alignment. This ability has been the result of several recent publications by other authors. Prakash and Tompa ,44 develcis-regulatory architecture, vis-a-vis the density and evolution of binding sites. However, it is not yet clear which, if any, of these different assumed models of regulatory sequence evolution is most suited to represent the variability in constraint patterns across different regions of the genome. Our simplistic "conserved block" model  seems tD. melanogaster - D. pseudoobscura) is widely different from the value observed in real non-coding sequence alignments (~0.4 substitutions/site). One could argue that this gap may be offset if we set an appropriate frequency of conserved positions (with very low rates), resulting in an average substitution rate that is close to the empirically observed value. However, this turned out not be the case for any realistic setting of the frequency of conserved positions (data not shown). We therefore chose to be guided by existing estimates of the frequency and length distribution of conserved blocks, with substitution rates that are some constant β (see Methods) times the "neutral" rate outside of the blocks, and set this neutral rate so that the average rate for the entire sequence matches observed values. Our choice reflects the philosophy that simulated data sets ought to match real data in terms of various evolutionary statistics and net alignment difficulty, and the discordance of the used neutral rate from synonymous substitution rates is ignored for the sake of practicality.Some clarification is in order with respect to our manner of choosing substitution rates for the simulation process, since it marks a significant departure from traditional thinking. The latter, as embodied in the work of Pollard et al. , prescriTo our knowledge, no previous benchmarking study has evaluated the effect of insertions and deletions on the performance of alignment tools. Some studies -25 have Drosophila species. While the accuracy was close to optimal on four of the five terminal branches, we observed that both tools over-estimate insertions as well as deletions on the longest branch (leading to D. pseudoobscura), while accurately predicting the ratio of insertions to deletions. We note that the D. pseudoobscura branch in the phylogenetic tree originates from the root of the tree, and we would expect to have better annotation results for this branch if an appropriate outgroup species was used. For studies that intend to use insertion to deletion ratio profiling to identify loci with unusual evolutionary patterns  it may s  than previously reported, and points to a clear asymmetry in the handling of insertions versus deletions by most alignment tools.We have presented a novel method for generating benchmarks of non-coding sequence alignments, that relies on a spectrum of parameter values reflecting the genome-wide variation of those parameters. We have shown our benchmarks to accurately match the difficulty of aligning real data, by taking advantage of recent developments in measurement of alignment quality. Benchmark evaluations on Drosophila genome sequences (release 5) with 14 insects were downloaded from UCSC Genome Browser Database [D. melanogaster, D. simulans, D. yakuba, D. ananassae, D. pseudoobscura, D. willistoni, D. mojavensis, and D. grimshawi. We extracted fragments of the genome-wide multiple alignments that have sequences for all eight species, whose minimum length is 1 Kbp, and which have less than 50% of their length masked . The extracted alignments were used to estimate simulation parameter values, as described below. The distribution of HoT alignment quality scores [Whole-genome multiple alignments of Database . In casey scores  was compy scores .Drosophila species were estimated from the multiple alignments described above, using Paml [D. melanogaster genome.Median branch lengths of a phylogenetic tree for eight ing Paml . This phing Paml , with thing Paml , substiting Paml  and inseing Paml , with paing Paml . The lening Paml . The lening Paml  and the to be the overall evolutionary rate (the estimated branch length), tn be the unconstrained evolutionary rate , α be the fraction of sequence length that falls into conserved blocks, and β be the ratio of the evolutionary rate of conserved blocks to that outside blocks. Then we have:The estimated median branch lengths mentioned above reflect an average of the rates in conserved and non-conserved regions of real non-coding sequences, whereas the phylogeny input to Dawg by definition represents the substitution rate outside of blocks. Therefore, the branch lengths of the phylogeny were adjusted based on the specified coverage of conserved blocks and their evolutionary rates. Let Drosophila non-coding sequences and marked consecutive columns as a conserved block if the following two conditions hold: (i) they span at least 10 consecutive non-gapped columns and (ii) Phastcons scores of all columns are greater than or equal to 0.9  and the root sequence was sampled from the D. melanogaster non-coding genome  to link their simulations to the pair of species. They later updated this value in a new phylogeny http://www.danielpollard.com/trees.html. We used their divergence estimates from the latter phylogeny and the benchmark they prescribed for this level of divergence, and evaluated the alignment programs ourselves on this benchmark.The benchmark generated by Pollard et al.  parameteNIt and NDt are true numbers of insertions and deletions, and NIe and NDe are predicted numbers of insertions and deletions.Indel Count Agreement is defined by the following formula, where Indel Ratio Agreement is defined by the following formula, with notation as above:Indel Annotation Coverage is the fraction of indel positions on which the two annotations agree.The time complexity of the Indelign program is exponential in the number of "conditionally dependent blocks" and this prohibits fast annotation of certain data sets with relatively large numbers of species . To reduhttp://europa.cs.uiuc.edu/RealisticAlignmentBenchmarks/.Source code for the modified Dawg and Indelign programs, phylogenetic trees, simulated sequences and their alignments, and computed alignments by six alignment tools are available from Indel: insertion and deletion; SPS: sum-of-pair score; CS: column scoreJK and SS conceived of the study, participated in its design, performed the analysis, and drafted the manuscript. JK developed the software and performed experiments. Both authors read and approved the final manuscript.Performance of multiple alignment tools compared by alignment sensitivity. The scores were calculated by using all synthetic data sets (left panel), and by using only data sets where the expected number of insertions is two times more than the number of deletions or vice versa (middle and right panels respectively).Click here for filePerformance of multiple alignment tools compared by alignment specificity. The scores were calculated by using all synthetic data sets (left panel), and by using only data sets where the expected number of insertions is two times more than the number of deletions or vice versa (middle and right panels respectively).Click here for fileAn example data set from the benchmark shown (in part) with true alignment (top panel) and alignments computed by each different programs.Click here for fileDependence of performance (sensitivity (left) and specificity (right)) of each alignment program on various descriptive statistics of the data sets.Click here for filePerformance of multiple alignment tools compared by alignment sensitivity of pairs of species. The scores were calculated by using all synthetic data sets (left panel), and by using only data sets where the expected number of insertions is two times more than the number of deletions or vice versa (middle and right panels respectively).Click here for filePerformance of multiple alignment tools compared by alignment specificity of pairs of species. The scores were calculated by using all synthetic data sets (left panel), and by using only data sets where the expected number of insertions is two times more than the number of deletions or vice versa (middle and right panels respectively).Click here for fileComparison of estimated alignment sensitivity and specificity, using Mlagan or Pecan, as obtained from the Pollard et al.  benchmarClick here for fileComparison of estimated alignment sensitivity and specificity as obtained from the Pollard et al. benchmark.Click here for filePhylogenetic trees and branch lengths in Newick format.Click here for fileDrosophila non-coding sequences obtained from UCSC Genome Browser Database.Genome-wide distribution of the fraction of conserved blocks estimated by using Phastcons conservation scores and multiple alignments of Click here for fileDescriptive statistics of traditional and new benchmarks.Click here for file


In the last decade, sequencing projects have led to the development of a number of annotation systems dedicated to the structural and functional annotation of protein-coding genes. These annotation systems manage the annotation of the non-protein coding genes (ncRNAs) in a very crude way, allowing neither the edition of the secondary structures nor the clustering of ncRNA genes into families which are crucial for appropriate annotation of these molecules.LeARN is a flexible software package which handles the complete process of ncRNA annotation by integrating the layers of automatic detection and human curation.This software provides the infrastructure to deal properly with ncRNAs in the framework of any annotation project. It fills the gap between existing prediction software, that detect independent ncRNA occurrences, and public ncRNA repositories, that do not offer the flexibility and interactivity required for annotation projects. The software is freely available from the download section of the website  Science magazine selected the discovery of small RNA with a regulatory function as a scientific breakthrough of the year [C. elegans [Our knowledge of small non-protein-coding RNAs (ncRNAs) has considerably evolved during the last decade. In 2002, the year . Since,  elegans -5. BecauDetecting novel ncRNAs by experimental RNomics is not an easy task . This haab-initio methods rely on an existing bias in base composition between ncRNA and the rest of the genome in order to provide a segmentation of the genomic sequence into ncRNA regions and others [Computational methods for ncRNA prediction can be classified into four approaches; bias composition analysis, minimization of free energy, searching for homologous RNA in the context of conserved family-specific characteristics, and sequence-based homology searches. The first approach analyzes the intrinsic features of the genomic sequence in order to detect ncRNA candidates. These d others ,14. Theyd others . Candidad others . A thirdd others , or covad others . More fld others ; Milpat d others ). These d others , RNAz [2d others , MSARI [d others , ddbRNA d others  have higComplementary to the development of detection strategies, many user interfaces have been developed to modify and annotate RNA sequences and structures .The aim of LeARN, the annotation platform presented here, is to manage the complete process of annotation of ncRNA genes. It can incrementally integrate the results of arbitrary detection programs and provides life scientists with user friendly interfaces allowing both structural and functional annotations. In order to facilitate later exploitation of annotations, LeARN relies on existing standards such as the Rfam database and the RNAML data exchange format, thus providing full interoperability with existing databases and software.The general architecture of LeARN is shared by most annotation platforms Figure . The firThe package . LeARN handles this redundancy by prioritizing the detection software in the main configuration file. A second type of redundancy is caused by overlaps between sequences, and this is critical in the context of ongoing BAC-to-BAC sequencing projects. In order to manage this source of redundancy, LeARN can rely on an additional file describing pairwise overlaps to avoid artificial over-prediction of redundant ncRNA genes.n-1 before starting the greedy analysis of the release n.The software allows for incremental updates of gene and family annotations which is an essential feature for ongoing sequencing projects. Incremental updating is made possible by using the RNAML files of the release In order to analyze one or several complete genomes, it is often useful to run detection computations in parallel. To accommodate the parallelization and the greedy algorithm previously described, the program offers the possibility to execute all detection programs beforehand. In this case, a command line is generated for each execution of a detection program. Each command line stores the result of its execution in a cache directory using an unambiguous filename based on the program name and version and the MD5 checksum of the analyzed sequence and can be directly executed in parallel. When the pipeline later requires the execution of a prediction program, it may directly use the cache result instead of running the prediction itself.The pipeline can easily be customized to integrate arbitrary detection programs providing results in GFF2 format. In addition to the definition of site specific pipelines, this opens the possibility of using LeARN as a light-weighted visualisation interface for researchers willing to develop new detection software.LeARN relies on a repository of RNAML documents to store the annotations of molecules and ncRNA families. This technical choice is compatible with the limited amount of data generated to annotate ncRNA (less than 10 Mb of RNAML to describe the annotation of 130 Mb of legume genome sequences). Relying on RNAML documents (i) provides a native interoperability with the visualisation software which use this standard format; (ii) takes advantage of XSLT processors which allow both document transformations and efficient (via XPATH queries) searches in XML repositories, and (iii) provides users with a light-weight package that does not require any RDBMS skill.The Web interface of LeARN is structured by the different functionalities it offers: scanning the current database and annotating ncRNA molecules or families.The "browse" tab allows lists of ncRNAs and ncRNA families to be displayed Figure . By clicIn order to correct the unavoidable discrepancies and errors generated by an automatic process, the LeARN package provides the expert user with an annotation interface for editing both structural and functional annotations as well as merging and splitting families. This requires user authentication. After the first login, the user must create his/her own workspace, initially defined by a copy of the public database. At any time, the 'Status' page allows the user to select the database he/she wants to use: it can be either the browsable public database or its own editable private one. Editing rights are made visible by a change in the background colour. The system allows for the parallel annotation by several experts, but prevents the concurrent annotation of the same family by different experts.In LeARN, the annotation of a ncRNA molecule is a three step process Figure . The firThe annotation process for families is similar to the previous one Figure . The firPyrococcus abyssi (Pa), Pyrococcus furiosus (Pf), Pyrococcus horikoshii (Ph) and Thermococcus kodakarensis (Tk). For these genomes, the RFAM genome browser gives 11 sRNA families in Pa, 12 sRNA families in Pf, 10 sRNA in families in Ph and 10 sRNA families in Tk for a total of 13 different families. With LeARN, iteratively built with RFAM covariance models, a classification in 16 families was obtained. From the original RFAM families, only the snoR9 family disappeared in this classification.We illustrate LeARN usage with two case studies on thermoccocales genomes We chose the C/D box sRNA family as the first case study. This family is mainly characterized by the presence of four motifs: C (RUGAUGA), D' (CUGA), C' (UGAUGA) and D boxes (CUGA). The region of 9 nucleotides downstream of D and/or D' boxes generally interacts with the target of the C/D sRNA mostly forming Watson-crick interactions. For a more accurate annotation, it is usual to further classify these ncRNA genes into subfamilies with a common target. In LeARN, four families were built automatically from the RFAM covariance model associated to the C/D box sRNA family (ID: snoPyro_CD). The largest snoPyro_CD family contained 74 candidates while the other ones contained only 1 candidate. From the Family browser, it was possible to select and merge all the four families  into only one (RFL0002) making it possible to analyze all candidates together and to classify them according to the conserved boxes and the sequence similarity at the target interaction site. This was done on the merged family using the Edit family function. Using the incrementally updated alignments provided by LeARN, the clustering of sequences into subfamilies based on their targets was straightforward. At the end of the process, 23 novel families were proposed. We renamed them according to the archaea sRNA database . Three cThe second case study concerns H/ACA sRNA. In RFAM, HgcE, HgcF and HgcG have unknown function but were found to be H/ACA sRNA genes named respectively Pf3, Pf6 and Pf7 . Thanks To summarize, LeARN provides a way to complete the gap between existing databases and gene prediction tools. It offers the user a working environment for editing sequence and structure of individual sRNA, as well as RNA families, by using sRNA dedicated functionalities for automatic and manual annotation operations.The first case study showed that one of the advantages of LeARN is to manage redundancy of candidates. The case of sRNA sR9 is a good example. One of the drawbacks of the automatic process of sRNA identification was the assignment of the sR9 C/D box sRNA to the general snoRNA family instead of the more accurate snoR9 family provided by the covariance model of RFAM. This is certainly a result of the proposed iterative approach which relies in part on the energy heuristic clustering. Despite this wrong assignment and the incomplete sequence for two members of this family, it was possible to group all the sR9 candidates and to extend those for which the H/ACA region was lacking by using the various functionalities of LeARN. In both case studies, it was particularly useful to be able to edit a sequence (extension of some regions) with regard to the literature and available knowledge of known H/ACA sRNA, candidates of the family, and availability of genomic sequences. The availability of an automatic or manual alignment of sRNA of the sequence and the structure, and the graphical representation of the consensus secondary structure considerably facilitated the improvement of the structural annotation.All the annotations were done and saved in the private environment of the annotator which offers a very nice and useful working space for personal annotation. After the annotation, it appears now essential to submit these structural annotations to the administrator to replace less accurate ones. One can also imagine that these annotations could be submitted, in the context of a collaborative annotation process, to any RNA database administrator in order to share the annotations with the scientific community. For example, novel sequence and structural annotations of C/D box and H/ACA archaea sRNA could allow new, more accurate RFAM covariance models to be generated for future archaea genome annotations.The demo section of the LeARN home page provides access both to raw results generated by the automatic process applied on the four thermoccocale genomes ("demo server"), and to the database after the edition of C/D box and H/ACA sRNA families ("annotation of C/D box and H/ACA families").The LeARN package can be used for ncRNA annotation projects for any set of sequences including complete genomes. It integrates tools and web interfaces covering the three layers of the ncRNA annotation process: a flexible detection and clustering pipeline, a RNAML database and a web interface to manage the expert annotation. The software has been designed to manage the complete ncRNA annotation process in the frame of whole genome annotation projects and to fill the gap between existing detection software and public ncRNA repositories. Moreover, LeARN is also an extendible and light-weight package, which can be used as an annotation interface either by life scientists wanting to annotate a single ncRNA family or by bioinformaticists who need a simple interface to visually evaluate their results. It can also be used to build training datasets or for any other activity involving ncRNA annotation.Project name: LeARNProject home page: Operating system: UNIXProgramming language: Perl-OO, XSLTOther requirements: Infernal [Infernal , Vienna Infernal , Mfold [Infernal , Rfam [8Infernal , ClustalInfernal , ncbi-blInfernal . The AdmLicense: Free Software license CECILL2 Any restrictions to use by non-academics: NoneXML: eXtensible Markup LanguageXSLT: eXtensible Stylesheet Language TransformationsCN designed, implemented and tested the software; JG led the design. JG, CG and TS tested the programs and contributed to the preparation of the manuscript. All authors have read and approved the final manuscript.LeARN 1.0.1 tarball. Tarball with LeARN source code. For installation instructions, see .Click here for file


There has been plentiful evidence of kinesthetically induced rapid compensation for unanticipated perturbation in speech articulatory movements. However, the role of auditory information in stabilizing articulation has been little studied except for the control of voice fundamental frequency, voice amplitude and vowel formant frequencies. Although the influence of auditory information on the articulatory control process is evident in unintended speech errors caused by delayed auditory feedback, the direct and immediate effect of auditory alteration on the movements of articulators has not been clarified.This work examined whether temporal changes in the auditory feedback of bilabial plosives immediately affects the subsequent lip movement. We conducted experiments with an auditory feedback alteration system that enabled us to replace or block speech sounds in real time. Participants were asked to produce the syllable /pa/ repeatedly at a constant rate. During the repetition, normal auditory feedback was interrupted, and one of three pre-recorded syllables /pa/, /Φa/, or /pi/, spoken by the same participant, was presented once at a different timing from the anticipated production onset, while no feedback was presented for subsequent repetitions. Comparisons of the labial distance trajectories under altered and normal feedback conditions indicated that the movement quickened during the short period immediately after the alteration onset, when /pa/ was presented 50 ms before the expected timing. Such change was not significant under other feedback conditions we tested.The earlier articulation rapidly induced by the progressive auditory input suggests that a compensatory mechanism helps to maintain a constant speech rate by detecting errors between the internally predicted and actually provided auditory information associated with self movement. The timing- and context-dependent effects of feedback alteration suggest that the sensory error detection works in a temporally asymmetric window where acoustic features of the syllable to be produced may be coded. During the development of speech production, different sorts of sensory feedback help to coordinate the movements of the respiratory, laryngeal, velopharyngeal, and articulatory subsystems. Cutaneous and/or somatosensory information on the status of multiple articulators and auditory information related to produced speech constitute important sources of feedback for speech motor control In this study, we examined the online control mechanism for articulatory lip movement by suddenly shifting the auditory feedback timing in the ahead-of-time or delayed direction, and/or replacing the feedback syllable by other syllables, during the repetition of bilabial plosives /pa/. Labial distance trajectories under altered and normal feedback conditions were compared within a single cycle of lip closing/opening movement subsequent to the auditory alteration. Statistical analysis revealed that a quickened lip closing/opening movement was clearly elicited when the auditory feedback preceded the real production by 50 ms. On the other hand, such change was not significant when the feedback was provided more than 50 ms before the real production or was delayed, and/or when the feedback syllable was replaced by /Φa/ or /pi/. These results suggest (1) an underlying mechanism that detects errors between anticipated and actually provided auditory consequences for the rapid modification of subsequent movements, and (2) a temporally asymmetric window for detecting auditory errors in which acoustic features of the syllable to be produced may be coded.All participants gave their written informed consent to participating in this study, which was approved by the Research Ethics Board of NTT Communication Science Laboratories.Ten adults  aged from 21 to 39 participated in the experiments. All the participants were native speakers of Japanese and exhibited no obvious speech difficulties as judged by the experimenters.In the experiment, the participants sat on a chair and were asked to insert the earphones as deeply as possible in the ear canal. A microphone mounted in a floor stand was located close to the left ears of the participants who were asked to keep their heads in a fixed position throughout the experiments. The participants heard their own unaltered speech picked up by the microphone through the earphones while vocalizing an /a/ sound in their natural way. They were then asked to adjust the gain of the microphone so that they heard their own speech sounds most naturally. The participants were also asked to adjust the sound level of the pink noise they heard through the earphones, which was produced by a noise generator (Bruel & Kjaer Type 1405), while vocalizing an /a/ sound in their natural way, so that, as far as possible, they did not perceive their own bone-conducted auditory feedback, but without experiencing stress. The sound level of the noise chosen by the ten participants in the experiments was 61.5±2.75 dBSPL as measured by a probe microphone (Etymotic Research Probe Microphone ER-7C).We chose an in-the-ear transducer with a view to eliminating the participants' own air-conducted auditory feedback most effectively. However, the occlusion effect caused by the in-ear earphone can influence the bone conduction threshold. The occlusion effect is the result of the acoustic energy created by the vibration of the walls of the external ear canal in response to a bone conducted signal trapped in the ear. When the tip of the earphone is fitted deeper in the ear canal, there is less opportunity for vibrations to occur and the occlusion effect is reduced The three-dimensional motion of the upper and lower lips was measured with an optical motion capture system  at a sampling frequency of 250 Hz. Six low mass, retro-reflective markers with a diameter of 4 mm were placed on the vermilion borders of the upper and lower lips in the midsagittal section, the bridge and the tip of the nose, and the left and right side of the forehead, as shown in In each trial in this experiment, the participants were asked to produce an isolated syllable /pa/ seven times while maintaining a constant speech rate. For each trial, the auditory feedback corresponding to the third repetition of /pa/ was altered by shifting the timing and/or replacing the type of syllable, while the subsequent feedback was blocked. A comparison of the articulatory lip movement under each altered condition with that under a normal condition enabled us to evaluate the effect of auditory feedback alteration on speech motor control more precisely than previous studies based on DAF. As for speech errors produced when employing DAF, their speech rate dependence can also be disputed in the light of certain controversial results The experiment consisted of five test blocks and one control block. Each test block consisted of forty-six trials, where twenty-three different feedback conditions were employed for two different repetition rates (200 and 300 ms per syllable). Of the twenty-three feedback conditions, twenty-one were altered conditions where one of three syllables  was presented at seven different timings , one was a blocked condition (no feedback after the second repetition), and one was unaltered. The control block consisted of twenty trials with unaltered feedback conditions, half of which were conducted at 200 ms per syllable and half at 300 ms per syllable.In the experiment, the control block was introduced first, which took about 5 minutes, followed by five test blocks, each of which took about 10 minutes. There was a short break between each block. During the test blocks, the order of the feedback conditions applied to each participant was shuffled block by block. In the control block, the two syllable rates were alternated trial by trial.When preparing these stimuli, the participants repeated /pa/, /Φa/, and /pi/ in their most natural way. While the participants were producing these syllables, the burst onset timing of one syllable was detected in the same way as in the experiments, and 200 ms of the signals from the detected onset were stored for each of the three syllables, while preserving the amplitude ratio among the syllables. Examples of the stored syllables for a participant are shown in The time varying three-dimensional labial distance (LD) was calculated from the marker position data. For each participant, the LD trajectories of all trials were temporally aligned at the predicted third repetition onset by referring to the simultaneously recorded acoustic signals. The mean LD trajectory of five trials was obtained for each of forty-six different conditions in the five test blocks . The mean trajectory of ten trials from the control  block was also obtained for the two speech rates.n under the control and altered conditions, respectively. Each LD trajectory was unbiased and windowed by a Blackman window to reduce the boundary effects. The lag that provided the maximum cross-correlation was represented as The auditorily induced change in the labial movement was represented by a lag that provided the maximum cross-correlation between the LD trajectories under the altered and control conditions within the post-stimulus period. Note that this method was more stable and consistent than that using the displacement error or the velocity error, maybe because of the inter-participant variability in the time course of lip opening-closing cycle see . In Fig.To adjust for the phase difference between the trajectories of the altered and control conditions before alteration onset, the lag within the pre-stimulus period By comparing the two trajectories in each panel, the mouth opening movement subsequent to the auditory stimulus onset appeared generally to occur sooner for the −50 ms stimulus presentation. While a similar hasty movement was also observed for the −150 and −100 ms conditions, the effect seemed to be weaker. The deviation between the trajectories under each of the delayed feedback  and control conditions was much smaller. Similar results were obtained for all ten participants.In For 22 altered conditions at each speech rate, the statistical significance of the difference from the “normal” condition was evaluated with a two-sided paired t-test . A statistically significant change (p<0.05) was found only when syllable /pa/ was presented 50 ms prior to the onset of syllable production for a rate of 300 ms per syllable. Under this condition, the auditory feedback alteration resulted in an ahead-of-time shift of the articulatory lip movement according to From the experimental results, we concluded that an ahead-of-time shift in the articulatory lip movement emerged rapidly when the auditory feedback preceded the real syllable production by 50 ms. However, too early a manipulation (−150 and −100 ms) of the auditory feedback did not significantly affect the subsequent articulatory lip movement. The delayed feedback also produced no significant change. Syllables that were not identical to those of the speech task (/Φa/ and /pi/) had no significant effect even when they were fed back 50 ms prior to the real syllable production. Finally, the articulatory changes were not significant for the faster speech rate (200 ms per syllable) under any of the alteration conditions tested.The experimental results obtained in the current study showed that the ahead-of-time and delayed auditory feedback affected the articulatory lip movement in a time-asymmetric manner during repetitive syllable production. Significantly hastened articulation at around 120 ms from the auditory alteration onset occurred when the auditory stimulus was presented 50 ms prior to the onset of syllable production. Taken together with the hypothetical feedforward and feedback mechanisms of speech motor control More interestingly, our experimental result revealed that no delayed feedback had a significant effect on the subsequent lip movement. One possible explanation for this result may be an imperfect masking of the air- and bone-conducted auditory feedback. In our experiment, an in-ear earphone was used to realize the effective isolation of the air-conducted feedback of the participants' own speech output. In addition, a masking noise was delivered to their ears to disturb the sensation and/or perception of the air- and bone-conducted feedback to a certain degree. However, even a small amount of natural feedback might still reduce the effect of sensory error on the motor control compared with ahead-of-time feedback alteration. This might result in the insufficient effect of the delayed auditory feedback.Another possible mechanism for the temporally asymmetric effect could be related to the response attenuation in the auditory cortex resulting from self-produced vocalization The experimental results showed that the auditory feedback of /Φa/ and /pi/ did not significantly change the subsequent lip movement, irrespective of the timing of the feedback. Taking this fact together with the hypothetical feedback-feedforward error correction mechanism The results also revealed of the effect of /Φa/ had a larger mean value than that of /pi/ being fed back 50 ms prior to /pa/ production at a rate of 300 ms per syllable, though both were statistically insignificant. One suspected cause is that /pi/ has a smaller relative acoustical power than /Φa/. In the experiment, the auditory feedback amplitude of each syllable was dynamically adjusted so that its syllabic power ratio to the syllable /pa/ to be produced by each participant was matched with that in his/her natural production. (See the Task subsection for details.) Another possible cause of the smaller mean effect of the /pi/ feedback could be related to a larger acoustic deviation of /pi/ from /pa/ compared with that of /Φa/, in the light of the evidence showing that the auditory cortex responded differently to self-produced and externally produced speech sounds during speech production The experimental result showed that none of the altered auditory feedback tested under the faster speech condition (200 ms per syllable) induced significant articulatory changes. So far little has been reported about the dependence of the auditory alteration effect on speech rate. There have been conflicting results regarding the speech-rate dependence of DAF-induced disfluencies, where speech errors were found to decrease A study on the accuracy with which speakers repeat a monosyllable in time with an external rhythm suggested two underlying processes depending on the repetition rate From the viewpoint of rhythmic properties, languages are considered to be classified as stress-, syllable-, or mora-timed, although a quantitative measure of speech rhythm has not been established. While the results of the current study were obtained from Japanese speakers, it would also be interesting to consider whether the same behavior occurs in other language speakers. Language-specific aspects of temporal organization of the kinematics of lower lip-jaw articulation have been compared between English, French, and Japanese, which are assumed to be examples of stress-, syllable-, and mora-timed languages, respectively A rapid auditorily induced change in articulatory lip movement was found when auditory feedback preceded real syllable production by 50 ms when isolated syllables were spoken repeatedly at a rate of 300 ms per syllable. The change was not significantly induced when the feedback occurred earlier than 50 ms or was delayed, and/or the feedback syllable was replaced by other syllables. The results suggested that a compensatory mechanism detected sensory errors between the internally predicted and actually provided auditory information associated with the self-produced speech, by using a temporally asymmetric window in which acoustic features of the syllable to be produced may be coded. This study provides evidence that the temporal dynamics of articulatory lip movement must be correctly maintained not only with somatosensory feedback resulting from peripheral motor activation but also with auditory feedback of self-produced speech.Figure S1Inter-participant variability in the time course of lip opening-closing behaviors. The solid and dotted curves indicate temporal patterns of the labial distance (left panels) and their first time-derivatives (right panels) under altered feedback and control conditions, respectively, during the repetitive production of /pa/ at a rate of 300 ms per syllable for each participant (P1 - 10). In the altered condition, the auditory feedback /pa/ was presented 50 ms prior to the predicted production onset. The thick vertical line indicates the onset timing of the auditory stimulus, and the dotted vertical line indicates the predicted third repetition onset. The pre- and post-stimulus periods used in the cross-correlation analysis are highlighted by the light and dark gray rectangles, respectively. As comparing the graphs of different participants, the displacement and its velocity patterns varied, and the timing of initiation of behavioral changes  by the feedback alteration were also different across the participants. Because of these variability, the kinetic variables such as the displacement and its time derivative were not useful to extract the common behavioral change across participants. In the main analysis, we therefore hired cross-correlation value as a lag-lead index because of robustness to the inter-participant behavioral variability.(0.20 MB TIF)Click here for additional data file.


Individuals involved in rescue, recovery, demolition, and cleanup at the World Trade Center (WTC) site were exposed to a complex mixture of airborne smoke, dust, combustion gases, acid mists, and metal fumes. Such exposures have the potential to impair nasal chemosensory  function.The goal of this study was to evaluate the prevalence of chemosensory dysfunction and nasal inflammation among these individuals.We studied 102 individuals who worked or volunteered at the WTC site in the days and weeks during and after 11 September 2001 (9/11) and a comparison group with no WTC exposure matched to each participant on age, sex, and job title. Participants were comprehensively evaluated for chemosensory function and nasal inflammation in a single session. Individual exposure history was obtained from self-reported questionnaires.The prevalence of olfactory and trigeminal nerve sensitivity loss was significantly greater in the WTC-exposed group relative to the comparison group . Among the WTC responders, however, individuals caught in the dust cloud from the collapse on 9/11 exhibited the most profound trigeminal loss. Analysis of the nasal lavage samples supported the clinical findings of chronic nasal inflammation among the WTC-exposed cohort.The prevalence of significant chemosensory impairment in the WTC-exposed group more than 2 years after their exposure raises concerns for these individuals when the ability to detect airborne odors or irritants is a critical safety factor.This outcome highlights the need for chemosensory evaluations among individuals with exposure to acute high or chronic levels of airborne pollutants. Individuals who were near the World Trade Center (WTC) on 11 September 2001 (9/11) and those involved in rescue, demolition, and cleanup at the WTC site were exposed to a complex mixture of airborne smoke, dust, combustion gases, acid mists, and metal fumes. In the earliest days after the disaster, many may have worked without adequate respiratory protection. Since then, thousands of individuals have developed chronic respiratory symptoms related to their WTC exposure .As the sentinel portal to the respiratory system, the nose and upper respiratory tract subserve a number of critical functions in humans: warming and humidifying incoming air, trapping and desorbing particulates and vapors, and the sensory functions of olfaction (smell) and chemical somatosensation (irritation or chemesthesis) . These fThe potential for acute or chronic exposure to chemical vapors or particles to impair olfactory function has long been recognized  and placed into glass bottles in a 20-step semi-log dilution series, starting with a concentration of 100% vol/vol liquid. Each bottle contained 10 mL of a stimulus . When volunteers inhaled from the nosepieces affixed to each bottle, they sampled from the ~ 250-mL headspace inside each of the two bottles (one sniffing port per nostril). We determined analytical measurements using headspace gas chromatography, and obtained thresholds using a two-alternative, forced-choice, two-up and one-down staircase method with a five-reversal criterion, as has been described previously . On eachIn addition to the ability to detect odor, another significant functional capacity of the nose is to detect irritation or pungency from chemicals that stimulate the free nerve endings of the trigeminal nerve. The lateralization method for measuring irritation is a psychophysical technique that permits an objective assessment of intranasal irritation that is not confounded by negative responses to the perception of an odor . The latOdor identification is the ability to produce or select the correct name/label of an odorant when it is presented at a concentration well above the detection threshold. The odor identification assessment consisted of 20 common odors, each presented twice  and nearly significantly associated with mucociliary transit time (p = 0.07). As shown in Because dust cloud exposure on 9/11 was found to be significantly associated with new-onset asthma , we wereAlthough often overlooked as a locus for toxic exposure effects, the nose represents one of the first sites of impact for airborne pollutants. As such, it not only serves to trap and detoxify numerous forms of potential toxicants but performs many sensory functions equally critical to human health and safety. The impact of exposure to volatile chemicals, particulates, and metal fumes on olfaction can take many forms, ranging from total loss (anosmia) to diminished sensitivity (hyposmia) or distortions in quality (dysosmia). The mechanisms underlying the adverse effects after acute or chronic exposure may also differ, depending on the agent or agents involved in the exposure. Some agents are capable of directly damaging tissue in areas that contain high densities of olfactory receptors. Other nonreactive agents can impair olfaction indirectly through stimulation of inflammatory mediators that possibly interfere with normal signal transduction in the olfactory epithelium or that produce anatomical changes altering the conduction of the chemical molecules to the olfactory epithelium . In the Although we matched the controls to the WTC workers on a case-by-case basis for exact job title, age, sex, and smoking status, the controls were located in the Philadelphia area, whereas most of the WTC workers came from the New York City region. We did not believe this biased the results, however, because air quality data for typical pollutants collected in both regions strongly confirm the similarity of the ambient exposures, with the Philadelphia region having slightly higher levels of volatile organic compounds .Despite observing substantial impairments in olfactory and trigeminal sensitivity among the WTC workers and volunteers relative to the occupationally matched controls, we did not find a significant difference in odor identification ability between the groups. In prior studies evaluating the effects of chemical exposure on olfactory ability, odor identification performance appeared to be inconsistently sensitive to pollutant exposure. For example, Differences in the levels of cytokines/chemokines in the NLF suggest that inflammatory mechanisms may underlie the functional effects we observed. As IL-6 is one of the most important mediators of the acute phase of response to injury, the lower levels found among the WTC workers with chronic inflammatory symptoms would not be considered unusual . IncreasThe robust association we found between the degree of exposure to the dust cloud on 9/11 and the loss of trigeminal sensitivity is particularly noteworthy, given that individuals were tested > 2 years after this exposure. Individuals who were not directly exposed to the dust cloud (either because of distance from the towers or by not being in lower Manhattan on 9/11) had significantly decreased ability to detect irritation relative to the matched controls. However, the thresholds of those individuals who were directly exposed in the dust cloud showed the most dramatic signs of impairment. The relationship between trigeminal function and pollutant exposure has not been evaluated as often as that for olfactory function, but should be considered in future studies.The failure to find a predictive relationship between long-term exposure history at the WTC site and performance on chemosensory function tests was surprising. However, we note that 97% of our test population worked/volunteered in lower Manhattan between 12 September and 18 September, which, after 9/11, was the period during which the potential for pollutant exposure was likely at its highest. If the chemosensory alterations we observed were due primarily to dust exposure on 9/11 and to some degree to other exposures during the first week, then the lack of variance in our exposure data during this week would obscure finding a relationship. We have noted that among the matched controls, sensitivity to the odor of PEA and the irritancy of n-butanol was associated with age. No such relationships were observed among the WTC workers, as the relatively small impact of this variable may have been overshadowed by damage incurred from early exposure at the site.Although the nasal chemosensory system can be remarkably robust to damage from airborne pollutants , its welNotably, the near-absent ability to detect nasal irritation for n-butanol for those individuals who were caught in the dust cloud from the collapse of the towers may be the most significant hazard we documented, as it is this sensory system that is in the first line of defense against many toxicants that could otherwise reach and potentially damage the lower airways. However, the decreased sensitivity to the irritancy of n-butanol may not be predictive of deficits for detecting all nasal irritants. Since the cloning of the capsaicin receptor in 1997, researchers have identified a number of transient receptor potential ion channels on sensory neurons, which appear to confer some level of specificity in the neuronal response to airway irritants . NonetheIt is unknown to what degree, if any, recovery of olfactory or trigeminal function has occurred in the interim for these individuals. Nor is it known how many of the WTC-exposed individuals who were not tested in this study have suffered similar chemosensory impairment but who may be unaware that they have lost an important sensory tool for detecting airborne hazards. For this reason, broader screening of chemosensory function among WTC-exposed individuals seems warranted, with a special focus on reevaluating individuals who participated in this study. The goal of such efforts should be not only to determine the prevalence or degree of chronic impairment for these individuals, but also to inform us of the potential for recovery, the factors that may be associated with recovery, and the time course necessary for recovery of function. Moreover, the lessons learned from studying this cohort can also provide important clues for monitoring and protecting the upper airways and chemosensory function in other populations having potential for acute exposure to airborne toxicants.


MotifCluster finds related motifs in a set of sequences and clusters the sequences into families using the motifs they contain. , lets users test whether proteins are related, cluster sequences by shared conserved motifs, and visualize motifs mapped onto trees, sequences and three-dimensional structures. We demonstrate MotifCluster's accuracy using gold-standard protein superfamilies; using recommended settings, families were assigned to the correct superfamilies with 0.17% false positive and no false negative assignments.MotifCluster finds related motifs in a set of sequences, and clusters the sequences into families using the motifs they contain. MotifCluster, at  Detection of evolutionary relationships between very distantly related protein families is important for efforts to assign functions to newly identified proteins, as well as to understand the evolutionary mechanisms by which new functions have emerged. Pairwise sequence identities between proteins in distantly related families are often statistically insignificant. Algorithms such as COMPASS  that evaIdentification of short, highly conserved sequences, known as motifs, in proteins provides important insights into the regions of proteins that have been conserved within a superfamily or suprafamily, as well as those that have diverged in specific families. Consideration of these motifs in conjunction with mechanistic and structural information can provide a picture of the sequence changes that led to acquisition of new catalytic capabilities. Two motif-finding algorithms, MEME (Multiple EM for motif elicitation)  and the A drawback of these algorithms is that the results depend on the order of sequences provided in the input set in an unpredictable way. Clustering sets of sequences based upon visual analysis of motifs, as in , is bothIn this paper, we present a new online tool, MotifCluster, that clusters input sequences according to the presence or absence of user-supplied motifs. MotifCluster uses any of six different distance metrics. Some of these metrics group sequences that contain the same motifs in the same order, and others look solely at which motifs are shared. The ability to take order into account is critical in some cases, because motifs may need to be in the context of a specific structural context to have biological activity. However, domain shuffling and circular permutation of sequences are not uncommon, so it can also be important to recognize the occurrence of shared motifs in an unusual order. Longer or more highly significant motifs can be given more weight than shorter or less significant motifs, or all motifs can be treated equally. Sequences can also be labeled with user-defined designations, such as family assignment, and the associations between families and motifs can then be used to explore functional relationships. In addition to clustering input sequences according to the motifs they contain, MotifCluster automatically maps motifs onto the structures of all proteins in the set for which structural information is available, providing an immediate visual assessment of the location of each motif. MotifCluster can be used online from the URL provided in the abstract, which also links to documentation and a downloadable version.MotifCluster allows sequences to be clustered according to their shared motifs in several ways, and facilitates identification of relationships between groups of sequences that share specific motifs. MotifCluster provides methods for testing whether different sequence families are related to one another, whether the motifs are meaningful in the context of the structures corresponding to each sequence (when available), and whether the patterns of motifs identified are consistent with standard phylogenetic analysis. The latter feature is particularly important, as standard phylogenetic analysis becomes difficult when sequences are highly diverse because alignments become unreliable below about 30% sequence identity . Brief sSeveral reports are generated after uploading a set of aligned or unaligned sequences, motif information, and, optionally, mappings that relate sequence identifiers (IDs) to known gene families. In these reports, each motif is assigned a unique style  that is used consistently throughout the displays. Each report format can be selected from a drop down list on the search results page.The first four report formats display motifs, either including or excluding the rest of the sequence, on a tree based either on the sequences or the motifs. These reports are important for establishing whether a particular motif fits the overall phylogenetic pattern, or has evolved convergently in different lineages, and can be especially useful for establishing relationships between sequences that are too diverse for construction of phylogenetic trees using standard methods. They are also important for visualizing where the motifs occur in the sequences, which can be important for detecting domain shuffling. These four report formats are described below.This tree is built using a matrix of distances calculated from the motif-based alignment. The metric used to build this tree reflects similarities only among the motifs (and not in the rest of the sequences). The color-coded motifs and location information are displayed, along with links to available Protein Data Bank (PDB) structures. The PDB links allow the user to view the motifs found in a particular sequence on the corresponding structure using PyMol . This foSimilar to the 'Motifs on motif-based tree' format above, except that the full sequences are shown (rather than just the sequences of the motifs). This format is useful for deciding whether there are extended regions of conservation around the motifs in specific groups of sequences, and like the format above, for identifying domain shuffling or circular permutation of motifs.Similar to the 'Sequences on motif-based tree' format above, except that a phylogenetic tree is generated using MUSCLE  based on similarities among the full-length sequences. Motifs are highlighted and displayed as for the 'Motifs on motif-based tree' format. This display is useful for testing whether the pattern of motif conservation follows the overall conservation of the sequences: if motifs have not evolved convergently and the sequences are sufficiently closely related to retain phylogenetic signal, the tree built using the motifs will be approximately the same as the tree built using the sequences, and, in both cases, large clades of sequences containing the motifs should be observed. Alternatively, if the sequences are so highly diverged that phylogenetic reconstruction is unreliable , the moSimilar to 'Sequences on motif-based tree' and 'Motifs on sequence-based tree (full-length)' formats above: displays only the sequences of the motifs on the tree built using the full-length sequences.The next group of reports shows which sequences contain each motif. These reports are useful for evaluating which motifs are meaningful, and which tend to occur together in the same sequences.P-values, grouped by sequence. For each sequence, motifs are displayed in order of decreasing significance . A display underneath the sequence indicates conservation: positions annotated with asterisks match the motif consensus at positions that are not highly conserved ; positions annotated with gray shaded + sighs match the consensus at positions that are highly conserved, and red positions are mismatches at positions that are highly conserved. This format is especially useful for finding systematic differences that may be functionally important within motifs. For example, single amino acid changes in a motif conserved in a superfamily may be related to divergence in function in a particular family.Displays a table of motifs and associated P-values, grouped by motif. For each motif, an alignment of the motif regions is displayed, with the majority consensus of the motif displayed above the alignment. Highly conserved columns (determined by the 'conservation threshold' parameter) in the consensus motif are colored. Positions within individual motifs are highlighted in grey if they match the consensus sequence. Like the 'Statistics by sequence' format, this format is useful for finding sequence changes that are potentially associated with functional changes.Displays a table of motifs and associated The final group of reports provides tools for exploratory analysis.Displays an interactive form allowing the user to select specific motifs to highlight in the alignment. This format is useful for assisting in decisions about which motifs are likely to be real and which are false positives, and reduces the visual complexity in the motif- and sequence-based tree formats by allowing the user to focus on specific motifs of interest.Displays all sequences in a network representation, with each connected component drawn as a separate network. The connected components are determined by the 'edge threshold' parameter. For example, if this parameter is 1, each connected component consists of all the sequences that share at least one motif with any other sequence in the connected component. If the parameter is 2, all sequences in a connected component must share at least two motifs with at least one other sequence in the same connected component. The list of IDs for the sequences in each connected component is displayed, and the actual sequences in each connected component can be downloaded as a FASTA file.We currently support motifs generated using either MEME  or the GThe distance between pairs of sequences based upon the motifs they contain can be calculated using several methods. The following distance measures are currently implemented in MotifCluster Figure .The Common fraction score method Figure  calculatThe Longest common substring (LCS) score method Figure  finds thThe Needleman-Wunsch (NW) score method Figure  uses theThe delta-delta score Figure  measuresThe UPGMA (Unweighted pair group method with arithmetic mean) clustering algorithm  uses a dWe generate a weighted graph showing the relationships between all sequences in terms of the motifs they share. Vertices in the graph represent a sequence in the input set, and each edge in the graph represents a relationship in which two sequences share one or more motifs. Thus, each sequence is connected to every other sequence with which it shares at least one common motif. The weight of each edge in the graph is calculated as the number of motifs shared by each pair of sequences. Once the full weighted graph has been generated, edges whose weight is less than the 'edge threshold' are removed from the graph. For example, if the edge threshold is 2 (the default), the connection is broken between any two sequences that share only a single motif.The display shows a thumbnail of each connected component, suppressing figures for connected components that consist of only one sequence. These thumbnails can be expanded into larger figures, including EPS output for printing or publication. The graphs are visualized using the random layout option in NetworkX , which wMost code described here was written in Python 2.4 and tested on MacOSX and Linux. The exceptions are the NW algorithm , which wWe describe the capabilities of MotifCluster using four cases as examples. First, we use the case of the two convergently evolved families of ribose 5-phosphate isomerases to show that structurally distinct proteins that have the same function can be correctly clustered. Second, we use a set of curated superfamilies that contains 4,887 sequences in 91 families divided among 5 superfamilies . These 'Escherichia coli and RpiB from E. coli [Ribose 5-phosphate isomerases catalyze the interconversion of ribulose 5-phosphate and ribose 5-phosphate. Two structurally distinct families of ribose 5-phosphate isomerases have been identified, exemplified by RpiA from  E. coli ,19. This-10 and an H-value of 10-20 with E. coli ribose 5-phosphate isomerase (gi 16130815) as the seed. A divergent set of 41 sequences was picked from the 465 sequences found by PSI-BLAST using DivergentSet [-10 and an H-value of 10-20 with E. coli ribose 5-phosphate isomerase B (gi 16131916) as the seed. A divergent set of 39 sequences was chosen from the 412 sequences found by PSI-BLAST search using a 55% identity threshold cutoff. The RpiB sequences range from 140-187 residues in length (average 153) and have an average pairwise identity of 46.4%. Motifs in the combined set of sequences were found by MEME using an E-value threshold of 10-20 and a setting of 10 expected motifs. Figure RpiA sequences were found using PSI-BLAST  with an et al. [-175). We tested MotifCluster using different edge threshold settings , and using the Gibbs sampler and MEME to find the underlying motifs, in order to test how well it was able to cluster family members within the same superfamily. Specifically, we expect sequences from the same superfamily to be connected by multiple motifs, but we do not expect members of different superfamilies to be bridged in this manner.We tested MotifCluster on the gold-standard set of mechanistically diverse superfamilies described by Brown et al. , which cFigure Figure et al.  are given in Figure Statistics describing the performance of MotifCluster in analyses of all pairs of the 91 sequence families described by Brown The false negative rate in this analysis was essentially zero (data not shown). No false negatives were found at all except when an edge threshold of three was used for motifs found by MEME. In that case, the algorithm failed to find a link between the deoxy-D-mannose-octulosonate 8-phosphate phosphatase and P-type ATPase families in the haloacid dehalogenase superfamily. Thus, the presence of at least two shared MEME motifs is a strong indicator of shared superfamily membership, whereas absence of at least two shared MEME motifs is a strong indicator of lack of shared superfamily membership. However, failure to assign all sequences to a single cluster (for members of the same superfamily) or to two distinct clusters (for members of different superfamilies) is frequent Figure . The ave2+ in the β-phosphoglucomutases. Figure ++. The comparable residue in the haloacid dehalogenase (Asp176) forms a hydrogen bond with Lys147. In addition, an active site Ser forms a hydrogen bond to the substrate in both cases. Residues in the other motifs that are conserved only in one of the two families are identifiable in the active site, as well; these residues contribute to family-specific functions such as stabilization of the chloride leaving group in the haloacid dehalogenase family. This type of analysis has traditionally been carried out by manual mapping of motifs discovered by MEME or the Gibbs sampler onto structures in a separate structure visualization package. By automating this process, MotifCluster speeds up the analysis and allows rapid analysis of multiple sets of different composition, which can be important because the motifs found by MEME and the Gibbs sampler vary somewhat according to the composition of the input set.Figure The Trx-fold suprafamily encompasses an extremely divergent set of proteins with a wide range of functions. All members of the suprafamily share the canonical Trx-fold structure, but the ancestral function (reduction of disulfide bonds using a pair of active site cysteines) has been modified in some superfamilies. For example, in the peroxiredoxin family, a cysteine corresponding to the more buried cysteine in Trxs is involved in reduction of peroxides, but the other cysteine has been changed to a threonine . In the An analysis of the relationship between thioredoxins (Trxs) and peroxiredoxin (Prxs) was reported in 2004: no significant pairwise identity could be demonstrated between sequences in these two families, but the Shotgun algorithm  identifiFigure Motif identification informs functional, mechanistic and evolutionary analyses in several ways. First, the patterns of motifs observed in subsets of the input set can be used to cluster the proteins into families, a useful tool for prediction of function for unannotated proteins. Second, motifs indicate regions of proteins that have been conserved for reasons of structure and/or function. Changes in a region of a protein family, either resulting in a different motif or in subtle, family-specific changes within a motif, suggest the changes that have led to emergence of new functions in an ancestral scaffold.MotifCluster takes input from motif-finding algorithms such as MEME or the Gibbs sampler, and the results are therefore dependent upon the choice of the input set because the characteristics of the input set have a strong effect upon the motifs that are found. A crucial limitation of existing techniques is that motif-finding algorithms typically assume that each sequence is drawn independently from a background distribution, and thus can be biased by the presence of closely related sequences. We previously addressed this problem with our software DivergentSet , which aAnalysis of the importance of sequence motifs is greatly enhanced when motifs can be mapped onto the structure of representative proteins. Such mapping allows visualization of motifs that are found in the core of the protein and may be responsible for maintaining the overall structural fold, motifs that are on the surface and may be involved in interactions with ligands or other proteins, and motifs that are found in clefts or crevices that may harbor active sites. The automation of the clustering of sequences and the mapping of motifs onto structures substantially reduces the time required to carry out such analyses, and will provide many new insights into the relationships among highly divergent protein families.CMP: cytochrome maturation protein; IDs: identifiers; LCS: Longest common substring; MEME: Multiple EM for motif elicitation; MUSCLE: Multiple sequence comparison by log-expectation; NW: Needleman-Wunsch; PDB: Protein Data Bank; Prx: peroxiredoxin; Trx: thioredoxin; UPGMA: Unweighted pair group method with arithmetic mean.MH and JW developed the software. SDC and RK directed the research. RK and MH wrote the manuscript, with most figures provided by JW.


To study the concentration of stress in class V restoration of four different restorative materials subjected to occlusal load of 100N, 150N, 200N, 250N and to analyse the obtained data with the listed properties of the restorative material.Using FEM analysis the stresses generated in a class V lesion in a mandibular premolar was studied.Within the framework of the aforementioned views, and from the results of the study it can be concluded that microfilled composite is the most suitable restorative material followed by flowable composite, glass ionomer cement and resin modified glass ionomer cement.Restoration of Class V lesions with materials of higher modulus of elasticity will enable better stress distribution. The human tooth is a marvel of nature. However, it has one significant shortcoming; it has only a limited capacity for regeneration. This necessitates the replacement of tooth structure lost as a result of caries, trauma or other reasons, with a suitable restorative material.The restoration of most surfaces of tooth is a fairly successful procedure. This is because of the improved understanding of caries and other disease processes, as well as due to the advancements in restorative materials and techniques. However, restoration of cervical lesions – both carious and noncarious defects – presents a unique clinical situation, because the etiology of such lesions is not always clear. The teeth are subjected to occlusal loads constantly. Besides, other factors like location of the tooth, abnormal occlusal stresses, age of the patient and the restorative material used have a significant influence on the retention rates.Traditionally, restorative treatment of cervical lesions was carried out by preparing Class V cavities and restoring them with various materials like silver amalgam, gold, porcelain, silicates etc. All these materials have some disadvantages and generally require removal of moderate amounts of the remaining tooth structure. With the advent of adhesive restorative materials, the need for preparing a cavity has long been overcome and simple conservative treatments, which utilize bonding for retention, have become more popular. Materials having adhesive potential are composites, polyacid modified glass ionomer, glass ionomer, resin modified glass ionomer and a combination of glass ionomer and composite in a bi-layered technique. Various Finite element analysis (FEA) is one of the more recently used techniques for stress analysis. The basic concept of this technique is the visualization of actual structure as an assemblage of a finite number of elements. Finite element analysis divides the problem domain into a collection of smaller parts (elements). An overall approximated solution to the original problem is determined.Various software such as NASTRAN, Auto FEA, IDEAS, IANA, IBM Finite element modeler, LS Dyna, NISA II are available for FEA.A three-dimensional mathematical finite element analysis model was generated for analysis, using an intact normal extracted human mandibular second premolar. The mandibular second premolar was selected for the study, as the incidence of cervical lesion is most common on the buccal aspect of lower premolars.The first step in a finite element analysis is modeling. The quality of the analysis results depends on the accuracy of the model. The tooth was subjected to a CT (computerized tomography) scan and the cross section of the tooth was obtained at an equal interval of 0.5 mm. In each cross section, the different layers of the tooth were viewed accurately. These sections were obtained in DICOM format and the data was fed to the computer.  Thus a virtual model of the second mandibular premolar was obtained.Bone was created as a rectangular block. The root portion was inserted inside the bone. This bone was constrained for motion in all the directions. The model was exported to NASTRAN.The creation of the Finite Element Model (FEM) was the next step. The Finite Element Model was divided into several Finite Elements. The element chosen for the study was C Tetra, which is a 4-noded element. NASTRAN was used to create the Finite Element Model. Class V cavity measuring 2 mm gingivo-occlusally, 3 mm mesiodistally and 1.5 mm in depth was held constant, with occlusal margin in enamel and gingival margin in dentine. The internal line angles of the cavity were rounded, in order to prevent any stress concentration.Following the meshing of the tooth model and the bone block, the outer element of the bone was fully constrained. The generated model, unrestored and restored with the above mentioned materials, was then subjected to an occlusal load of 100N, 150N, 200N and 250N, at right angles to the buccal cusp at a point 0.4 mm inside the buccal cusp tip, to simulate the effect of tooth contact in a lateral excursive movement.The load was applied and the stress analysis was carried out using the NASTRAN solver. The stress distributions have been plotted using the general post processor of NASTRAN.MODEL I - This model was restored with microfilled composite (Silux plus) .MODEL II - The second model was restored with flowable composite (Tetric Flow) .MODEL III - The third model was restored completely with glass ionomer cement (Ketac Bond) .MODEL IV - The fourth model was restored with resin modified glass ionomer cement (Vitrebond) 3]Cervical lesions are common and they pose a challenge to the dental profession. It is likely that their prevalence will increase, as the world's population ages. The location of these lesions makes it difficult to provide a long-lasting restoration. The prevalence of noncarious Class V lesions has been estimated to be between 31 and 56%. It has also been estimated that 85% of the population shows some loss of tooth structure at the cervical area.Over the last decade or so, a biomechanical theory (tooth flexure theory) has been postulated, suggesting that mechanical overloading of cervical enamel caused by cuspal flexure may contribute to noncarious cervical tooth loss. As the tooth flexes, the cusps are subjected to an axial compression load, resulting in cervical tensile and shear stresses acting at right angles to an axial load in a manner similar to a diametral compression test. This results in breakdown of the bonds between the hydroxyapatite crystals, which leads to crack formation, which eventually results in enamel loss. This mechanism has been termed ‘abfraction’.Abfraction lesions are wedge-shaped defects that are principally found on the buccal and labial aspects of the teeth. There seems to be a strong association between abfraction lesions and parafunctional habits. Previous studies have found that stresses concentrate in the thin cervical enamel area and the magnitude of these stresses exceeds the known failure stresses for enamel.A higher frequency of cervical lesions has been noted in mandibular teeth than in maxillary teeth. In recent studies, retentive failure rates of restorations were also found to be higher in the mandibular arch than the maxillary arch. The higher incidence and increased failure rate of restorations are consistent with the lingual orientation of the mandibular teeth. It renders them more susceptible to the concentration of tensile stresses at the cervical cross section of the mandibular teeth, particularly the bicuspids and may also contribute to the failure of these teeth to withstand tensile stress. The difficulty in moisture control of mandibular teeth during the restorative process and less number of open tubules in mandibular dentin have also been mentioned as possible contributory factors to the increased failure rate.Numerous clinical trials have been undertaken involving Class V restorations, but no consensus currently exists regarding the long-term clinical performance of any restorative material. Many questions regarding material selection and clinical techniques are still unanswered.Treatment of Class V lesions presents a unique challenge. Leakage and lost restoration are a common observation among clinicians. Tooth location, stressful, occlusion, type of restorative material and the age of the patient have significant influence on the retentive failure rates.µm and this gap often remains open, despite swelling of the restoration following water absorption. These gaps between the tooth margin and restoration lead to clinical problems such as post-operative sensitivity, stained margins and recurrent caries.[Resin composites and glass ionomer cements are widely used for restoring cervical lesions, as they are esthetic and mercury free, and they bond to the tooth structure. One of the main problems that clinicians face when restoring Class V or cervical cavities with composite resin is dealing with the problems of polymerization shrinkage. The shrinkage which accompanies the setting of these materials results in marginal gap formation in the order of 10-15t caries.Microfilled resins tend to flex with the tooth rather than debond, as compared to the more rigid macrofilled resin restorations. A thicknVarious methodologies have been used to study the stress concentrations in the cervical regions. These include Articulated study models, Photo elIn this method, solutions for each element are combined to obtain a solution to the body. Among the various methods for assessing deformations produced in different structures, FEA has proven its efficiency in many ways, from the normal situations concerning the nature of tooth movement under orthodontic loads to special situations like alveolar bone loss, use of extra oral forces systems in orthodontics etc. The other experimental methods may indicate the ultimate load for failure of a tooth, but may not provide satisfactory answers regarding the development mechanism of such a failure. However, with FEM, the intermediate levels of a process can easily be understood and it is most suitable for the modeling of an asymmetrical tooth structure.in vitro virtual model study.This study investigated the strength properties of various resin based restorative materials recommended for use in Class V applications. The purpUsing finite element analysis, stresses generated in a Class V lesion unrestored and restored with various groups of materials were evaluated. A mandibular premolar was used in the study, as a higher frequency of cervical lesions has been noted in mandibular teeth. The cavities that destroy the structural integrity of an intact tooth leads to the development of stress concentration near cavity vicinities .In a restored tooth, when the loading angle and the restorations size were kept fixed, increasing the load was found to increase the Von Misses stress in the immediate vicinity of the restored area and it was found to be inversely proportional to the Young's modulus value of the restorative material. As the value of Young's moduli of the enamel and the restoration material do not match, it inevitably disrupts the otherwise continuous structure and gives rise to stress concentrations. If the restoration material has larger Young's modulus, the destruction becomes less prominent. The increase in the load does not cause a change in the overall stress pattern, but only shifts the value to a higher scale. In all the models considered, the Von Misses developed in the unrestored tooth was found to reach higher values than the stresses developed in the restored model.Applying this data to a real model, one can suggest that the loading at which the tooth is being subjected to may not create immediate failure in the tooth, but may create cracks in the tooth structure; over a period of time, it may lead to a complete failure. As the formation of non-carious lesions/cavities are an inevitable part of various etiological factors, their possible negative effects should be foreseen and necessary precautions should be taken. From the mechanical point of view, restoration of these defects is important and the best clinical approach would be to apply restorative materials, which have large Young's moduli.13 This iOne can draw a similar conclusion from the present study, as microfilled composite (9.5GPa) performed best with a stress value of 54.1MPa at a load of 250N, followed by flowable composite (6.2GPa) with a sA virtual model cannot completely mimic a real biological model, i.e. a set of teeth cushioned by periodontal ligament and perpetually being subjected to various types of loading stresses. Therefore, any conclusion drawn by considering a single stress component will not reflect the true behavior of the tooth and hence will be far from accurate. Similarly, as the tooth represents a highly irregular structure, any two-dimensional analysis will fail to represent the actual tooth. In addition, FEA itself has its own limitations such as - solving a large number of complex equations consume a lot of time; the accuracy is limited to the software and hardware capabilities of the computer; and, it is governed by the element inputs. Wrong inputs can lead to design deficiency.In spite of these limitations, FEM is one of the most widely used stress analysis in dentistry today, as it is most suitable for modeling an asymmetrical structure like the tooth. Finite Element Analysis is a method wherein one can visualize and study the stresses generated in a tooth, restoration, restoration-tooth interface etc., simultaneously for different occlusal/incidental forces, thus generating a virtual picture of biomechanical characteristics of any restoration. This helps us in predicting the probable success of a restoration for a given clinical situation. Improved computers and modeling techniques render the FEM a very reliable and accurate estimation approach in biomechanical applications.This study using finite element analysis evaluated stresses generated in a Class V lesion unrestored and restored with glass ionomer, resin-modified glass ionomer, microfilled composite, flowable composite and subjected to load of 100N, 150N, 200N, 250N. A mandibular premolar was used in the study and the principal stresses developed during various occlusal loads were evaluated.The results of the study suggest that –The cavities that destroy the structural integrity of an intact tooth lead to the development of stress concentrations near the cavity vicinities.The loading at which the tooth is being subjected to may not create immediate failure in the tooth, but may create cracks in the tooth structure. The applied load may eventually lead to a complete failure.The following observations were drawn from the analysis:When a tensile load is applied on a tooth with Class V lesion, there is a high stress concentration in the mesio-axial and disto-axial proximities.Restoration of these defects helps in the reduction of stress concentration.The stress concentration is in the immediate vicinity of the restored area and was found to be inversely proportional to the Young's modulus value of the restorative material used.From the biomechanical point of view, it can be said that the best approach is to apply restorative materials which have as large as possible Young's moduli.Within the framework of the aforementioned views, it can be concluded that for Class V application, Microfilled composite performed the best, followed by Flowable composite, Glass Ionomer cement and Resin modified glass ionomer cement.