Detecting imbalanced expression of SNP alleles by minisequencing on microarrays

Abstract

BackgroundEach of the human genes or transcriptional units is likely to contain single nucleotide polymorphisms that may give rise to sequence variation between individuals and tissues on the level of RNA. Based on recent studies, differential expression of the two alleles of heterozygous coding single nucleotide polymorphisms (SNPs) may be frequent for human genes. Methods with high accuracy to be used in a high throughput setting are needed for systematic surveys of expressed sequence variation. In this study we evaluated two formats of multiplexed, microarray based minisequencing for quantitative detection of imbalanced expression of SNP alleles. We used a panel of ten SNPs located in five genes known to be expressed in two endothelial cell lines as our model system.ResultsThe accuracy and sensitivity of quantitative detection of allelic imbalance was assessed for each SNP by constructing regression lines using a dilution series of mixed samples from individuals of different genotype. Accurate quantification of SNP alleles by both assay formats was evidenced for by R2 values > 0.95 for the majority of the regression lines. According to a two sample t-test, we were able to distinguish 1–9% of a minority SNP allele from a homozygous genotype, with larger variation between SNPs than between assay formats. Six of the SNPs, heterozygous in either of the two cell lines, were genotyped in RNA extracted from the endothelial cells. The coefficient of variation between the fluorescent signals from five parallel reactions was similar for cDNA and genomic DNA. The fluorescence signal intensity ratios measured in the cDNA samples were compared to those in genomic DNA to determine the relative expression levels of the two alleles of each SNP. Four of the six SNPs tested displayed a higher than 1.4-fold difference in allelic ratios between cDNA and genomic DNA. The results were verified by allele-specific oligonucleotide hybridisation and minisequencing in a microtiter plate format.ConclusionsWe conclude that microarray based minisequencing is an accurate and accessible tool for multiplexed screening for imbalanced allelic expression in multiple samples and tissues in parallel.

Allelic imbalance in gene expression as a guide to cis-acting regulatory single nucleotide polymorphisms in cancer cells

“…The reason for this difference could be the high sensitivity of detecting minority alleles using minisequencing primer extension, which we have previously shown to be 1–5%, depending on the sequence context of the SNP (15,29). Alternatively it is possible that cancer-related genes in cancer cells are more frequently expressed in an allele-specific manner than randomly selected genes in lymphoblastoid cell-lines that have been analyzed for AI in other studies.…”

“…Inspired by a number of studies that have identified putative rSNPs in genes related to cancer (14,17,18) and the response to treatment with anticancer drugs (19–22), we used a panel of cell lines that represent different types of cancers and have been well characterized for their response patterns against anticancer drugs (23) as target cells in our study. For detecting AI in the expression of candidate genes for cancer and anticancer drug response we used our ‘in house’ developed tag-microarray minisequencing system, which we have previously shown to be accurate and sensitive for quantitative detection of AI (15). Genes that displayed AI were then subjected to bioinformatics-assisted identification of rSNPs that alter the strength of transcription factor binding in their upstream regulatory regions.…”

CEBPG Exhibits Allele-Specific Expression in Human Bronchial Epithelial Cells

“…Despite this built-in quality control step, numerous additional known and unknown sources of analytical variation remain uncontrolled by this method alone and can potentially result in inaccurate and low precision of ASE measurement 17,36,38. In this study we implemented multiple additional quality control measures to address some of the potential sources of analytical error encountered in ASE association studies.…”