Non-EST based prediction of exon skipping and intron retention events using Pfam information

Most of the known alternative splice events have been detected by the comparison of expressed sequence tags (ESTs) and cDNAs. However, not all splice events are represented in EST databases since ESTs have several biases. Therefore, non-EST based approaches are needed to extend our view of a transcriptome. Here, we describe a novel method for the ab initio prediction of alternative splice events that is solely based on the annotation of Pfam domains. Furthermore, we applied this approach in a genome-wide manner to all human RefSeq transcripts and predicted a total of 321 exon skipping and intron retention events. We show that this method is very reliable as 78% (250 of 321) of our predictions are confirmed by ESTs or cDNAs. Subsequent analyses of splice events within Pfam domains revealed a significant preference of alternative exon junctions to be located at the protein surface and to avoid secondary structure elements. Thus, splice events within Pfams are probable to alter the structure and function of a domain which makes them highly interesting for detailed biological investigation. As Pfam domains are annotated in many other species, our strategy to predict exon skipping and intron retention events might be important for species with a lower number of ESTs

BioBayesNet: a web server for feature extraction and Bayesian network modeling of biological sequence data

BioBayesNet is a new web application that allows the easy modeling and classification of biological data using Bayesian networks. To learn Bayesian networks the user can either upload a set of annotated FASTA sequences or a set of pre-computed feature vectors. In case of FASTA sequences, the server is able to generate a wide range of sequence and structural features from the sequences. These features are used to learn Bayesian networks. An automatic feature selection procedure assists in selecting discriminative features, providing an (locally) optimal set of features. The output includes several quality measures of the overall network and individual features as well as a graphical representation of the network structure, which allows to explore dependencies between features. Finally, the learned Bayesian network or another uploaded network can be used to classify new data. BioBayesNet facilitates the use of Bayesian networks in biological sequences analysis and is flexible to support modeling and classification applications in various scientific fields. The BioBayesNet server is available at http://biwww3.informatik.uni-freiburg.de:8080/BioBayesNet/

Improved identification of conserved cassette exons using Bayesian networks

<p>Abstract</p> <p>Background</p> <p>Alternative splicing is a major contributor to the diversity of eukaryotic transcriptomes and proteomes. Currently, large scale detection of alternative splicing using expressed sequence tags (ESTs) or microarrays does not capture all alternative splicing events. Moreover, for many species genomic data is being produced at a far greater rate than corresponding transcript data, hence <it>in silico </it>methods of predicting alternative splicing have to be improved.</p> <p>Results</p> <p>Here, we show that the use of Bayesian networks (BNs) allows accurate prediction of evolutionary conserved exon skipping events. At a stringent false positive rate of 0.5%, our BN achieves an improved true positive rate of 61%, compared to a previously reported 50% on the same dataset using support vector machines (SVMs). Incorporating several novel discriminative features such as intronic splicing regulatory elements leads to the improvement. Features related to mRNA secondary structure increase the prediction performance, corroborating previous findings that secondary structures are important for exon recognition. Random labelling tests rule out overfitting. Cross-validation on another dataset confirms the increased performance. When using the same dataset and the same set of features, the BN matches the performance of an SVM in earlier literature. Remarkably, we could show that about half of the exons which are labelled constitutive but receive a high probability of being alternative by the BN, are in fact alternative exons according to the latest EST data. Finally, we predict exon skipping without using conservation-based features, and achieve a true positive rate of 29% at a false positive rate of 0.5%.</p> <p>Conclusion</p> <p>BNs can be used to achieve accurate identification of alternative exons and provide clues about possible dependencies between relevant features. The near-identical performance of the BN and SVM when using the same features shows that good classification depends more on features than on the choice of classifier. Conservation based features continue to be the most informative, and hence distinguishing alternative exons from constitutive ones without using conservation based features remains a challenging problem.</p

Comparative transcription map of the wobbler critical region on mouse chromosome 11 and the homologous region on human chromosome 2p13-14

BACKGROUND: To support the positional cloning of the mouse mutation wobbler (wr) the corresponding regions on human Chr2p13-14 and mouse Chr11 were analyzed in detail and compared with respect to gene content, order, and orientation. RESULTS: The gene content of the investigated regions was highly conserved between the two species: 20 orthologous genes were identified on our BAC/YAC contig comprising 4.5 Mb between REL/Rel and RAB1A/Rab1a. Exceptions were pseudogenes ELP and PX19 whose mouse counterparts were not located within the analyzed region. Two independently isolated genomic clones indicate an inversion between man and mouse with the inverted segment being identical to the wobbler critical interval. We investigated the wobbler critical region by extensive STS/EST mapping and genomic sequencing. Additionally, the full-length cDNA sequences of four newly mapped genes as well as the previously mapped gene Otx1 were established and subjected to mutation analysis. Our data indicate that all genes in the wr critical region have been identified. CONCLUSION: Unexpectedly, neither mutation analysis of cDNAs nor levels of mRNAs indicated which of the candidate genes might be affected by the wr mutation. The possibility arises that there might be hitherto unknown effects of mutations, in addition to structural changes of the mRNA or regulatory abnormalities

TassDB: a database of alternative tandem splice sites

Subtle alternative splice events at tandem splice sites are frequent in eukaryotes and substantially increase the complexity of transcriptomes and proteomes. We have developed a relational database, TassDB (TAndem Splice Site DataBase), which stores extensive data about alternative splice events at GYNGYN donors and NAGNAG acceptors. These splice events are of subtle nature since they mostly result in the insertion/deletion of a single amino acid or the substitution of one amino acid by two others. Currently, TassDB contains 114 554 tandem splice sites of eight species, 5209 of which have EST/mRNA evidence for alternative splicing. In addition, human SNPs that affect NAGNAG acceptors are annotated. The database provides a user-friendly interface to search for specific genes or for genes containing tandem splice sites with specific features as well as the possibility to download large datasets. This database should facilitate further experimental studies and large-scale bioinformatics analyses of tandem splice sites. The database is available at

Adaptation of Mongolian students in the study of the discipline "Engineering graphics"

How is the study of the subject "Engineering Graphics" at the preparatory department Mongolian students. Motivating students and their perception of the subject. Which is typical of adaptation of students from Mongolia

Violating the splicing rules: TG dinucleotides function as alternative 3' splice sites in U2-dependent introns

TG dinucleotides functioning as alternative 3' splice sites were identified and experimentally verified in 36 human genes