Genome-wide prediction, display and refinement of binding sites with information theory-based models

BACKGROUND: We present Delila-genome, a software system for identification, visualization and analysis of protein binding sites in complete genome sequences. Binding sites are predicted by scanning genomic sequences with information theory-based (or user-defined) weight matrices. Matrices are refined by adding experimentally-defined binding sites to published binding sites. Delila-Genome was used to examine the accuracy of individual information contents of binding sites detected with refined matrices as a measure of the strengths of the corresponding protein-nucleic acid interactions. The software can then be used to predict novel sites by rescanning the genome with the refined matrices. RESULTS: Parameters for genome scans are entered using a Java-based GUI interface and backend scripts in Perl. Multi-processor CPU load-sharing minimized the average response time for scans of different chromosomes. Scans of human genome assemblies required 4–6 hours for transcription factor binding sites and 10–19 hours for splice sites, respectively, on 24- and 3-node Mosix and Beowulf clusters. Individual binding sites are displayed either as high-resolution sequence walkers or in low-resolution custom tracks in the UCSC genome browser. For large datasets, we applied a data reduction strategy that limited displays of binding sites exceeding a threshold information content to specific chromosomal regions within or adjacent to genes. An HTML document is produced listing binding sites ranked by binding site strength or chromosomal location hyperlinked to the UCSC custom track, other annotation databases and binding site sequences. Post-genome scan tools parse binding site annotations of selected chromosome intervals and compare the results of genome scans using different weight matrices. Comparisons of multiple genome scans can display binding sites that are unique to each scan and identify sites with significantly altered binding strengths. CONCLUSIONS: Delila-Genome was used to scan the human genome sequence with information weight matrices of transcription factor binding sites, including PXR/RXRα, AHR and NF-κB p50/p65, and matrices for RNA binding sites including splice donor, acceptor, and SC35 recognition sites. Comparisons of genome scans with the original and refined PXR/RXRα information weight matrices indicate that the refined model more accurately predicts the strengths of known binding sites and is more sensitive for detection of novel binding sites

POIMs: positional oligomer importance matrices—understanding support vector machine-based signal detectors

Motivation: At the heart of many important bioinformatics problems, such as gene finding and function prediction, is the classification of biological sequences. Frequently the most accurate classifiers are obtained by training support vector machines (SVMs) with complex sequence kernels. However, a cumbersome shortcoming of SVMs is that their learned decision rules are very hard to understand for humans and cannot easily be related to biological facts

Method of predicting Splice Sites based on signal interactions

BACKGROUND: Predicting and proper ranking of canonical splice sites (SSs) is a challenging problem in bioinformatics and machine learning communities. Any progress in SSs recognition will lead to better understanding of splicing mechanism. We introduce several new approaches of combining a priori knowledge for improved SS detection. First, we design our new Bayesian SS sensor based on oligonucleotide counting. To further enhance prediction quality, we applied our new de novo motif detection tool MHMMotif to intronic ends and exons. We combine elements found with sensor information using Naive Bayesian Network, as implemented in our new tool SpliceScan. RESULTS: According to our tests, the Bayesian sensor outperforms the contemporary Maximum Entropy sensor for 5' SS detection. We report a number of putative Exonic (ESE) and Intronic (ISE) Splicing Enhancers found by MHMMotif tool. T-test statistics on mouse/rat intronic alignments indicates, that detected elements are on average more conserved as compared to other oligos, which supports our assumption of their functional importance. The tool has been shown to outperform the SpliceView, GeneSplicer, NNSplice, Genio and NetUTR tools for the test set of human genes. SpliceScan outperforms all contemporary ab initio gene structural prediction tools on the set of 5' UTR gene fragments. CONCLUSION: Designed methods have many attractive properties, compared to existing approaches. Bayesian sensor, MHMMotif program and SpliceScan tools are freely available on our web site. REVIEWERS: This article was reviewed by Manyuan Long, Arcady Mushegian and Mikhail Gelfand

MetWAMer: eukaryotic translation initiation site prediction

<p>Abstract</p> <p>Background</p> <p>Translation initiation site (TIS) identification is an important aspect of the gene annotation process, requisite for the accurate delineation of protein sequences from transcript data. We have developed the MetWAMer package for TIS prediction in eukaryotic open reading frames of non-viral origin. MetWAMer can be used as a stand-alone, third-party tool for post-processing gene structure annotations generated by external computational programs and/or pipelines, or directly integrated into gene structure prediction software implementations.</p> <p>Results</p> <p>MetWAMer currently implements five distinct methods for TIS prediction, the most accurate of which is a routine that combines weighted, signal-based translation initiation site scores and the contrast in coding potential of sequences flanking TISs using a perceptron. Also, our program implements clustering capabilities through use of the <it>k</it>-medoids algorithm, thereby enabling cluster-specific TIS parameter utilization. In practice, our static weight array matrix-based indexing method for parameter set lookup can be used with good results in data sets exhibiting moderate levels of 5'-complete coverage.</p> <p>Conclusion</p> <p>We demonstrate that improvements in statistically-based models for TIS prediction can be achieved by taking the class of each potential start-methionine into account pending certain testing conditions, and that our perceptron-based model is suitable for the TIS identification task. MetWAMer represents a well-documented, extensible, and freely available software system that can be readily re-trained for differing target applications and/or extended with existing and novel TIS prediction methods, to support further research efforts in this area.</p

Genome-Wide Identification of Functionally Distinct Subsets of Cellular mRNAs Associated with Two Nucleocytoplasmic-Shuttling Mammalian Splicing Factors

Background: Pre-mRNA splicing is an essential step in gene expression that occurs co-transcriptionally in the cell nucleus, involving a large number of RNA binding protein splicing factors, in addition to core spliceosome components. Several of these proteins are required for the recognition of intronic sequence elements, transiently associating with the primary transcript during splicing. Some protein splicing factors, such as the U2 small nuclear RNP auxiliary factor (U2AF), are known to be exported to the cytoplasm, despite being implicated solely in nuclear functions. This observation raises the question of whether U2AF associates with mature mRNA-ribonucleoprotein particles in transit to the cytoplasm, participating in additional cellular functions. Results: Here we report the identification of RNAs immunoprecipitated by a monoclonal antibody specific for the U2AF 65 kDa subunit (U2AF$^{65}$) and demonstrate its association with spliced mRNAs. For comparison, we analyzed mRNAs associated with the polypyrimidine tract binding protein (PTB), a splicing factor that also binds to intronic pyrimidine-rich sequences but additionally participates in mRNA localization, stability, and translation. Our results show that 10% of cellular mRNAs expressed in HeLa cells associate differentially with U2AF$^{65}$ and PTB. Among U2AF$^{65}$ -associated mRNAs there is a predominance of transcription factors and cell cycle regulators, whereas PTB-associated transcripts are enriched in mRNA species that encode proteins implicated in intracellular transport, vesicle trafficking, and apoptosis. Conclusion: Our results show that U2AF$^{65}$ associates with specific subsets of spliced mRNAs, strongly suggesting that it is involved in novel cellular functions in addition to splicing

The Musashi 1 Controls the Splicing of Photoreceptor-Specific Exons in the Vertebrate Retina

Alternative pre-mRNA splicing expands the coding capacity of eukaryotic genomes, potentially enabling a limited number of genes to govern the development of complex anatomical structures. Alternative splicing is particularly prevalent in the vertebrate nervous system, where it is required for neuronal development and function. Here, we show that photoreceptor cells, a type of sensory neuron, express a characteristic splicing program that affects a broad set of transcripts and is initiated prior to the development of the light sensing outer segments. Surprisingly, photoreceptors lack prototypical neuronal splicing factors and their splicing profile is driven to a significant degree by the Musashi 1 (MSI1) protein. A striking feature of the photoreceptor splicing program are exons that display a switch-like pattern of high inclusion levels in photoreceptors and near complete exclusion outside of the retina. Several ubiquitously expressed genes that are involved in the biogenesis and function of primary cilia produce highly photoreceptor specific isoforms through use of such “switchlike” exons. Our results suggest a potential role for alternative splicing in the development of photoreceptors and the conversion of their primary cilia to the light sensing outer segments