Tissue-specific genetic control of splicing: implications for the study of complex traits.

Idealized Representation of How Overall Expression and Alternative Splicing Events Are Reflected in the Exon Array DataTop panel: In this study, all exon-level data were normalized across all exons and individuals. Transcript-level expression was reported for each transcript interrogated on the array by averaging (PLIER method) exon expression levels for all exons contained in a transcript (annotation details can be found at http://www.affymetrix.com). Subject 1 in this example has a higher overall transcript expression level (indicated by green line representing an average of exons A–G within subject 1) compared to subject 2 (red line). In this example, all exons contained in the transcript were expressed at approximately equal levels, suggesting that this transcript does not have alternative splice variants in either subject. Middle panel: An example of the detection of alternative splicing in which multiple transcripts are produced from a single gene through unique combination of the coding regions. Exon D in subject 2 appears to be expressed at lower quantities when compared to the other exons in the transcript (exon D expression levels lie below the average transcript line), indicating that this exon may be spliced out of the transcript in this subject (i.e., higher expression of transcript isoform II). Bottom panel: A scenario where we cannot definitively establish the combinatorial assembly of exons using these data. In this example, subject 2 has lower expression of both exons B and D. We cannot conclude that this subject has a higher proportion of transcript IV expressed compared to subject 1 or if transcript II and III are expressed at higher levels. Despite this shortcoming in situations of large heterogeneity of transcript isoforms produced with multiple alternative splicing events, these data provide a clear indicator of alternative exon composition within transcripts for a given individual. This study was specifically focused on the cis-acting genetic regulation of overall expression and splicing. Therefore, we were interested in identifying groups of splicing and expression patterns unique to individuals with the same genotype at certain commonly variant loci in and surrounding the transcript or exon. In cases where the expression of multiple exons was under genetic regulation, we declared it a splicing event if <40% of all exons contained in the transcript were associated with high confidence with the genotype. If >40% of exons were implicated, this was considered to be an overall expression change.

Principal Components Analysis of All Exon Expression Level Data for Both Brain and PBMC SamplesThe differentiated pattern of expression suggests the need for tissue specific evaluations of alternative splicing and expression and demonstrates the added benefit of studying genetic regulation of splicing and expression in two unique and important cellular populations. A similar profile was observed for the transcript level expression values in the two tissue types suggesting the same level of tissue specificity for splicing.

Quantitative Real-Time PCR Confirmation of Selected Genetically Regulated Exon-Level Expression Changes in the Two Tissue TypesThree representative scenarios are presented. The top panel shows an sQTL that was present in both brain and PBMCs. The middle panel and bottom panel show sQTLs unique to a particular tissue type, providing unequivocal evidence for tissue specific genetic regulation.

Methodological Details Evaluating the Proximity of a Detected sQTL and Its Region of LD to a Splicing Regulatory RegionRed box represents an exon whose expression is correlated with the SNP indicated by the starred red bar. All SNPs in LD with this sQTL are shown by red bars and the height of the bar indicates the level of correlation (r 2) with the starred SNP. We assessed how often the range of LD for a given sQTL (defined by r 2 > 0.2 with the sQTL) extended into or surpassed the splicing regulatory region. This analysis was performed by evaluating all mRNA transcripts containing the exon regulated by the sQTL. The splicing regulatory region was defined as the genomic region from the start of the exon located upstream of the associated exon through the stop site of the downstream exon interrogated. If the exon was part of multiple transcripts the region including the most distal and proximal neighboring exons was defined the splicing regulatory region. If the affected exon was located at the beginning or end of the transcript then the range was truncated at the start or stop of the transcript, respectively. Finally, if a single SNP associated with more than one exon in a single transcript they were considered as a single entry in this analysis (i.e., sQTL LD needed only come in close proximity of one of the affected exons to be counted as a positive entry).

SNPExpress DatabaseTop panel: Output showing an example of an association between rs10876864 and a splicing change in RPS26. Software permits the input of an SNP, a gene, or a genomic region for comprehensive interrogation of associations between SNPs and exon/transcript expression levels in the regions surrounding the SNP. The blue frame indicates the SNPs genotyped on the chip, the two lighter blue frames correspond to the −log p-values for the brain and PBMC samples, the turquoise panel contains all Ensembl transcripts, and the bottom green panel shows all of the exons/transcripts screened for on the array.Bottom panel: This database can be applied in a SNP-centric or gene-centric approach for determining the functional and phenotypic consequences of genetic variation on the transcriptome.