Allelic imbalance in gene expression as a guide to cis-acting regulatory single nucleotide polymorphisms
1Lili Milani, 1Manu Gupta, 2Sumeer Dhar, 2Marten Fryknas, 2Anders Isaksson, 2Rolf Larsson, 1Ann-Christine Syvanen
1Molecular Medicine, Dept. of Medical Sciences, Uppsala Unviersity, 75185 Uppsala, Sweden, 2Clinical Pharmacology, Dept. of Medical Sciences, Uppsala Unviersity, 75185 Uppsala, Sweden
Single nucleotide polymorphisms (SNPs) in genomic regions that regulate gene expression are major causes of human diversity and may also be important susceptibility factors for complex diseases and traits. To use the relative expression levels of two SNP alleles of a gene in the same sample as the quantitative phenotype is a promising approach for identifying cis-acting regulatory SNPs (rSNPs) or haplotypes. We have established a process for systematic screening for cis-acting rSNPs using experimental detection of allelic imbalance (AI) as the initial approach. We selected 160 candidate genes that are involved in cancer and anticancer drug resistance for analysis of AI in a panel of cell lines that represent different types of cancers and have been well characterized for their response patterns against anticancer drugs. For detecting AI we used our "in house" developed four-colour tag-microarray minisequencing system, which we have previously shown to be accurate for quantitative genotyping of SNPs.
Of the selected genes, 60 contained heterozygous SNPs in their coding regions (cSNPs), and 41 of the genes displayed imbalanced expression of the two cSNP alleles according to the analysis by minisequencing (Milani et al, Nucleic Acids Res 2007). Genes that displayed AI were subjected to bioinformatics-assisted identification of rSNPs that alter the strength of transcription factor binding. rSNPs in 15 genes were subjected to electrophoretic mobility shift assays, and in 8 of these genes we identified differential protein binding between the SNP alleles. The screening process devised here allowed us to zoom in from 160 originally selected candidate genes to eight genes that may contain functional regulatory SNPs in their promoter regions. We are now scaling up this approach using the Illumina iSelect assay to detect SNPs in several thousand genes in a study on 1000 well-characterized cell samples from children with acute lymphoblastic leukemia.