Computational protocol: Identification of Common Genetic Variation That Modulates Alternative Splicing

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Protocol publication

[…] Splice donor and acceptor sequences were scored using a position specific score matrix (PSSM) method []. Alignments of mRNA and EST sequences to the reference human genomic assembly (version: hg17) were taken from the University of California Santa Cruz genome database (http://genome.ucsc.edu) and used to define a population of well-supported (appearing in more than nine transcripts) constitutive splice sites. These were used to train the PSSMs, considering three exonic, six intronic nucleotides at the splice donor, and three exonic, 18 intronic nucleotides for the splice acceptor PSSM []. We compared the splice site scores of the 250 exons predicted by EBI-ASD to show exon skipping (subdivided into those that showed exon skipping in our experimental model and those that did not) with the splice site scores of 7,431 exons that were always found in mRNA transcripts (constitutively present) randomly selected from the genome. We sought to determine if splice site strength could predict those exons that were likely to be skipped. We also sought to determine if the SNP density near to the intron–exon boundaries differed in those exons that showed alternative splicing compared to those that did not. Finally, the sequence context of SNPs correlated with specific splice patterns was analysed to determine whether they affected know splice enhancer or silencer elements, using four published algorithms: http://ast.bioinfo.tau.ac.il/ESR.htm [], http://genes.mit.edu/burgelab/rescue-ese [], http://cubweb.biology.columbia.edu/pesx [], and http://rulai.cshl.edu/tools/ESE []. […]

Pipeline specifications

Software tools RESCUE-ESE, PESX
Application WGS analysis