Of this population-specific variation, 75.5% is due to expression rather than splicing variability, and we find few genes with strong evidence for differential splicing across populations.
To get an insight into the functional role of dystrophin throughout brain development, we assessed genes with strong co-expression to the three different dystrophin isoform groups for enrichment in gene ontology (GO) terms (Fig. 6, Supplementary Table 6).
In particular, of the 46 genes with strong association signals in CAD GWASs that were studied in mouse models, all but one exhibited consistent effects on atherosclerosis-related phenotypes.
We then compared the gene lists ascertained here to four lists from academic research projects that identify genes with strong association to ASD Simons Foundation Autism Risk Initiativee (SFARI),11 Simons Foundation Powering Autism Research for Knowledge (SPARK),12 Autism Speaks – MSSNG,8 and Autism Sequencing Consortium (ASC 13 (Supplementary Table S2).
A possible explanation is the absence of MS susceptibility genes with strong individual effects.
Thus 33,867 of the 41,000 genes with strong reliable signals were sorted and then analysed with TM4 software [19].
In particular they identified (i) 400 genes with strong evidence of positive selection across species, (ii) 144 genes with strong evidence of positive selection in one or more branches, (iii) 3705 genes with weak evidence of positive selection on one or more branches, and (iv) 12280 (orthologs) genes with no significant evidence of positive selection.
This apparently was due to the fact that a few genes with strong prognostic power were not available on all microarray platforms and thus were not retained in the merged data sets.
An ANOVA analysis, including Benjamini and Hochberg correction, corrected P<0.02, and fold change of at least three, gave 531 genes with strong expression differences in the four compartments.
Several genes with strong eQTLs were related to ribosomal function.
Figure 2D displays the resulting list of genes with strong between-dataset expression correlations.
