Splice prediction tools

Fruit fly and human splice predictor.
Directly callable from our sequencing software Gensearch.

In order to better understand intronic and exonic mutations leading to splicing defects, we decided to create the Human Splicing Finder website. This tool is aimed to help study of the pre-mRNA splicing. 

To calculate the consensus values of potential splice sites and search for branch points, new algorithms were developed. Furthermore, we have integrated all available matrices to identify exonic and intronic motifs, as well as new matrices to identify hnRNP A1, Tra2-β and 9G8.

Integrated web server, namely RegRNA, to identify the homologs of Regulatory RNA motifs and elements against an input mRNA sequence. Both sequence homologs or structural homologs of regulatory RNA motifs can be identified. The regulatory RNA motifs supported in RegRNA are categorized into several classes:

• Motifs in mRNA 5'-UTR and 3'-UTR. 
• Motifs involved in mRNA splicing.
• Motifs involved in transcriptional regulation. 
• Other motifs in mRNA, such as riboswitches. 
• Prediction of the splice sites, such as splicing donor/acceptor sites.
• RNA structural features, such as inverted repeat.
• miRNA target sites.

Analyzes the exonic sequence to find the presence of Exonic Splicing Enhancer Elements

GENSCAN Web Server at MIT: identification of complete gene structures in genomic DNA. Directly callable from ou sequencing software Gensearch.

A fast, flexible system for detecting splice sites in the genomic DNA of various eukaryotes. The system has been trained and tested successfully on Plasmodium falciparum (malaria), Arabidopsis thaliana, human, Drosophila, and rice . Training data sets for human and Arabidopsis thaliana are included. Use the GeneSplicer Web Interface to run GeneSplicer directly, or see below for instructions on downloading the complete system including source code . 

The NetGene2 server is a service producing neural network predictions of splice sites in human, C. elegans and A. thaliana DNA.

ASSP predicts putative alternative exon isoform, cryptic, and constitutive splice sites of internal (coding) exons. Skipped splice sites are not differentiated from constitutive sites. Non-canonical splice sites are not detected. Alternative splicing is predicted based on the DNA/RNA sequence information only. For splice site prediction within a sequence putative splice sites are preprocessed using position specific score matrices.

SplicePort is a web-based tool for splice-site analysis that allows the user to make splice-site predictions for submitted sequences. In addition, the user can also browse the rich catalog of features that underlies these predictions, and which we (the authors) have found capable of providing high classification accuracy on human splice sites. Feature selection is optimized for human splice sites, but the selected features are likely to be predictive for other mammals as well.

Publication

MaxEntScan is based on the approach for modeling the sequences of short sequence motifs such as those involved in RNA splicing which simultaneously accounts for non-adjacent as well as adjacent dependencies between positions. This method is based on the 'Maximum Entropy Principle' and generalizes most previous probabilistic models of sequence motifs such as weight matrix models and inhomogeneous Markov models.

EX-SKIP is simple utility that compares the ESE/ESS profile of a wild-type and a mutated allele to quickly determine which exonic variant has the highest chance to skip this exon. It calculates the total number of ESSs, ESEs and their ratio. Specifically, it computes the number of RESCUE-ESEs (Fairbrother 2004; Fairbrother 2002), FAS-ESSs (Wang 2004), PESEs/PESSs (Zhang 2004), neighbourhood inference (Stadler 2006) and EIE/IIEs (Zhang 2008) for each segment.

Specific short oligonucleotide sequences that enhance pre-mRNA splicing when present in exons, termed exonic splicing enhancers (ESEs), play important roles in constitutive and alternative splicing (ESE References). A hybrid computational/experimental method, RESCUE-ESE, was recently developed for identifying sequences with ESE activity. In this approach, specific hexanucleotide sequences are identified as candidate ESEs on the basis that they have both significantly higher frequency of occurrence in exons than in introns and also significantly higher frequency in exons with weak (non-consensus) splice sites than in exons with strong (consensus) splice sites. Representative hexamers from ten different classes of candidate ESEs, together with 6 or 7 bases of flanking sequence context on each side, were introduced into a weak (poorly spliced) exon in a splicing reporter construct. These reporter minigenes were then transfected into cultured cells, where they are transcribed and spliced, and the relative level of inclusion of the test exon was assayed by quantitative (radio-labeled) RT-PCR. Point mutants of these sequences were also analyzed to confirm the precise motifs responsible for ESE activity.