Illustration of Study Design.

The main resource for identifying alternatively spliced exons was compiled using two data sources produced by high-throughput genome-wide techniques: sequence-derived computed data and expression-derived experimental data. (A) Sequence-derived computed data: putative alternatively spliced exons were predicted using a sequence data-driven alternative splicing model and the genomic locations of ISEs which were identified by scanning the intronic regions near intronic SNPs for putative ISE motifs (6-mer in length, see Materials and Methods). (B) Expression-derived experimental data: exon-level microarrays and cis-expression quantitative trait loci data (cis-eQTL, p<0.01, Materials and Methods) were obtained from our previous work with HapMap LCLs (87 Utah residents with Northern and Western European ancestry (CEU) and 89 Yoruba from Ibadan, Nigeria (YRI)). (C) Experimental data (panel B) was integrated in order to not only verify predicted exon skipping events from AS modeling data (panel A) but also to identify regulatory relationships between ISE SNPs and putative exon skipping events. (D) We investigated SNP associations with SI using an additive model and the allele associated with an increase in exon skipping. (E) Potential functionality of genetic variations was computationally evaluated by investigating the protein domains encoded by skipped exons and thus the impact on the protein function.