Nucleic Acids Research Advance Access originally published online on January 31, 2007
Nucleic Acids Research 2007 35(5):e34; doi:10.1093/nar/gkl1152
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Nucleic Acids Research, 2007, Vol. 35, No. 5 e34
© 2007 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/2.0/uk/) which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.
Methods Online |
Allelic imbalance in gene expression as a guide to cis-acting regulatory single nucleotide polymorphisms in cancer cells
1Molecular Medicine, 2Clinical Pharmacology, Department of Medical Sciences, Uppsala University, Uppsala, Sweden and 3Department of Biotechnology, AlbaNova University Center, Royal Institute of Technology (KTH), Stockholm, Sweden
*To whom correspondence should be addressed. Tel: +46 18 6112959; Fax: +46 18 553601; E-mail: Ann-Christine.Syvanen{at}medsci.uu.se
Received November 3, 2006. Revised December 6, 2006. Accepted December 6, 2006.
Using the relative expression levels of two SNP alleles of a gene in the same sample is an effective approach for identifying cis-acting regulatory SNPs (rSNPs). In the current study, we established a process for systematic screening for cis-acting rSNPs using experimental detection of AI as an initial approach. We selected 160 expressed 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. Of these genes, 60 contained heterozygous SNPs in their coding regions, and 41 of the genes displayed imbalanced expression of the two cSNP alleles. 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 assay, and in eight of these genes (APC, BCL2, CCND2, MLH1, PARP1, SLIT2, YES1, XRCC1) we identified differential protein binding from a nuclear extract between the SNP alleles. The screening process allowed us to zoom in from 160 candidate genes to eight genes that may contain functional rSNPs in their promoter regions.
Present addresses: Manu Gupta, Cancer Research UK Medical Oncology Laboratory, Barts and the Royal London School of Medicine, Queen Mary College, London, UK
Sumeer Dhar, Department of Pharmacogenomics and Experimental Therapeutics, UNC School of Pharmacy, Chapel Hill, NC, USA
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