Dataset Information

A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana.

ABSTRACT: Algorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.We have developed a new computational technique to identify significantly conserved motifs involved in splice site regulation. First, 84 putative exonic splicing enhancer hexamers are identified in Arabidopsis thaliana. Then a Gibbs sampling program called ELPH was used to locate conserved motifs represented by these hexamers in exonic regions near splice sites in confirmed genes. Oligomers containing 35 of these motifs have been shown experimentally to induce significant inclusion of A. thaliana exons. Second, integration of our regulatory motifs into two different splice site recognition programs significantly improved the ability of the software to correctly predict splice sites in a large database of confirmed genes. We have released GeneSplicerESE, the improved splice site recognition code, as open source software.Our results show that the use of the ESE motifs consistently improves splice site prediction accuracy.

SUBMITTER: Pertea M

PROVIDER: S-EPMC1892810 | biostudies-literature | 2007 May

REPOSITORIES: biostudies-literature

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A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana.

Pertea Mihaela M Mount Stephen M SM Salzberg Steven L SL

BMC bioinformatics 20070521

<h4>Background</h4>Algorithmic approaches to splice site prediction have relied mainly on the consensus patterns found at the boundaries between protein coding and non-coding regions. However exonic splicing enhancers have been shown to enhance the utilization of nearby splice sites.<h4>Results</h4>We have developed a new computational technique to identify significantly conserved motifs involved in splice site regulation. First, 84 putative exonic splicing enhancer hexamers are identified in Ar ...[more]

PMID: 17517127

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Project description:Nitric oxide (NO) is an important signaling molecule that regulates many physiological processes in plants. One of the most important regulatory mechanisms of NO is S-nitrosylation-the covalent attachment of NO to cysteine residues. Although the involvement of cysteine S-nitrosylation in the regulation of protein functions is well established, its substrate specificity remains unknown. Identification of candidates for S-nitrosylation and their target cysteine residues is fundamental for studying the molecular mechanisms and regulatory roles of S-nitrosylation in plants. Several experimental methods that are based on the biotin switch have been developed to identify target proteins for S-nitrosylation. However, these methods have their limits. Thus, computational methods are attracting considerable attention for the identification of modification sites in proteins. Using GPS-SNO version 1.0, a recently developed S-nitrosylation site-prediction program, a set of 16,610 candidate proteins for S-nitrosylation containing 31,900 S-nitrosylation sites was isolated from the entire Arabidopsis proteome using the medium threshold. In the compartments "chloroplast," "CUL4-RING ubiquitin ligase complex," and "membrane" more than 70% of the proteins were identified as candidates for S-nitrosylation. The high number of identified candidates in the proteome reflects the importance of redox signaling in these compartments. An analysis of the functional distribution of the predicted candidates showed that proteins involved in signaling processes exhibited the highest prediction rate. In a set of 46 proteins, where 53 putative S-nitrosylation sites were already experimentally determined, the GPS-SNO program predicted 60 S-nitrosylation sites, but only 11 overlap with the results of the experimental approach. In general, a computer-assisted method for the prediction of targets for S-nitrosylation is a very good tool; however, further development, such as including the three dimensional structure of proteins in such analyses, would improve the identification of S-nitrosylation sites.

Dataset Information

A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana.

Publications

A computational survey of candidate exonic splicing enhancer motifs in the model plant Arabidopsis thaliana.

Similar Datasets

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