Whole-genome association mapping of gene expression in the human prefrontal cortex

Variations in gene expression among individuals may have multiple downstream implications, including an effect on disease risk. “Genetical genomics” (or expression genetics) uses linkage and association methods to map gene expression phenotypes, connecting genetic variants to expression quantitative trait loci (eQTLs). It represents a promising approach to identifying novel expression regulatory elements in the genome. Studies of human lymphoblastoid cell lines1, liver2 and brain3 have also been reported. Meyers et al.3 studied 193 neuropathologically normal human brain samples from three cortical regions using the Affymetrix 500K Array for genotyping and the Illumina HumanRefseq-8 Expression Array for gene expression measurements. They assessed association between 366,140 SNPs and the expression of 14,078 transcripts, and identified 433 SNP-transcript pairs (99 transcripts) that showed significant cis-association (transcript-specific empirical P value ≤ 0.05); but only 25 of them (involving two genes, KIF1B and IPP) are significant after correcting for all the SNPs and phenotypes (transcripts) tested (Sidak multitranscript-corrected empirical P values ≤ 0.05). We would consider only the two genes truly significant cis- associations as they were the ones surviving correction for all the statistical tests.