RESCUE-ESE identifies candidate exonic splicing enhancers in vertebrate exons

Abstract

A typical gene contains two levels of information: a sequence that encodes a particular protein and a host of other signals that are necessary for the correct expression of the transcript. While much attention has been focused on the effects of sequence variation on the amino acid sequence, variations that disrupt gene processing signals can dramatically impact gene function. A variation that disrupts an exonic splicing enhancer (ESE), for example, could cause exon skipping which would result in the exclusion of an entire exon from the mRNA transcript. RESCUE-ESE, a computational approach used in conjunction with experimental validation, previously identified 238 candidate ESE hexamers in human genes. The RESCUE-ESE method has recently been implemented in three additional species: mouse, zebrafish and pufferfish. Here we describe an online ESE analysis tool (http://genes.mit.edu/burgelab/rescue-ese/) that annotates RESCUE-ESE hexamers in vertebrate exons and can be used to predict splicing phenotypes by identifying sequence changes that disrupt or alter predicted ESEs.

Engineering of PEDF-Expressing Primary Pigment Epithelial Cells by the SB Transposon System Delivered by pFAR4 Plasmids

“…A set of 238 human ESE motifs was employed from the RESCUE-ESE set 57 . ESE motifs are very rich in the nucleotide A (∼50% of all sites in ESEs), followed by the nucleotide G with about 25% of all sites, whereas the nucleotides C and T each occupying about 12%–13% of all sites.…”

Prediction of single‐nucleotide substitutions that result in exon skipping: identification of a splicing silencer inBRCA1exon 6

“…Each utility perform a local search of the exonic sequence for putative ESEs/PESSs (PESEs/PESSs) [Zhang and Chasin, 2004], FAS-ESSs [Wang et al, 2004], RESCUEESEs [Fairbrother et al, 2002;Fairbrother et al, 2004], neighbourhood inference [Stadler et al, 2006] and exon/intron identity elements (EIE/IIEs) [Zhang et al, 2008] The performance of HOT-SKIP was tested with a set of 37 previously reported mutations that resulted in exon skipping and genetic disease (Supplementary Table 4). …”

“…To determine which of the previously determined ESSs or ESEs correlate best with exon inclusion levels, the number of RESCUE-ESEs [Fairbrother et al, 2002;Fairbrother et al, 2004], FASS-ESSs [Wang et al, 2004], PESEs/PESSs [Zhang and Chasin, 2004], neighbourhood inference elements [Stadler et al, 2006] and EIE/IIEs [Zhang et al, 2008] was calculated for each segment. In addition, we employed the ESEfinder [Cartegni et al, 2003;Smith et al, 2006] to correlate exon inclusion levels with predicted scores of putative ESEs for SR proteins.…”

Splicing Aberrations in Congenital Myasthenic Syndromes

“…Representative tools to predict splicing mutations at the 5' and 3' splice sites and the branch point are Human Splicing Finder [29], SD score [30], MaxEntScan [31], Analyzer Splice Tool (AST) [31,32], DBASS5 [33], DBASS3 [34]. Similarly, representative tools to predict splicing cis-elements and their associated RNAbinding proteins are SpliceAid [35], SpliceAid2 [36], ESEfinder [37,38], Rescue-ESE [39,40], FAS-ESS [41], and SF map [42].The details of these tools as well as the other tools and databases are discussed in detail in our recent review article [43]. Among these tools, we developed the SD score algorithm to predict the splicing effect of mutations affecting three nucleotides at the 3' end of an exon and six nucleotides at the 5' end of an intron [30].…”