Optimization of candidate-gene SNP-genotyping by flexible oligonucleotide microarrays; analyzing variations in immune regulator genes of hay-fever samples
1 Division of Functional Genome Analysis, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
2 Division of Clinical Epidemiology, Deutsches Krebsforschungszentrum, Im Neuenheimer Feld 580, 69120 Heidelberg, Germany
3 Institute of Molecular and Cell Biology, 23 Riia St., 51010 Tartu, Estonia
4 Febit biotech, Im Neuenheimer Feld 517, 69120 Heidelberg, Germany
5 The Estonian Biocentre, 23b Riia St., 51010 Tartu, Estonia
6 Molecular Diagnostics Centre, United Laboratories of the Tartu University Hospital, 1a Puusepa Str., 50406 Tartu, Estonia
7 Estonian Genome Project of University of Tartu, 61b Tiigi Str., 50410 Tartu, Estonia
BMC Genomics 2007, 8:282 doi:10.1186/1471-2164-8-282Published: 17 August 2007
Genetic variants in immune regulator genes have been associated with numerous diseases, including allergies and cancer. Increasing evidence suggests a substantially elevated disease risk in individuals who carry a combination of disease-relevant single nucleotide polymorphisms (SNPs). For the genotyping of immune regulator genes, such as cytokines, chemokines and transcription factors, an oligonucleotide microarray for the analysis of 99 relevant SNPs was established. Since the microarray design was based on a platform that permits flexible in situ oligonucleotide synthesis, a set of optimally performing probes could be defined by a selection approach that combined computational and experimental aspects.
While the in silico process eliminated 9% of the initial probe set, which had been picked purely on the basis of potential association with disease, the subsequent experimental validation excluded more than twice as many. The performance of the optimized microarray was demonstrated in a pilot study. The genotypes of 19 hay-fever patients (aged 40–44) with high IgE levels against inhalant antigens were compared to the results obtained with 19 age- and sex-matched controls. For several variants, allele-frequency differences of more than 10% were identified.
Based on the ability to improve empirically a chip design, the application of candidate-SNP typing represents a viable approach in the context of molecular epidemiological studies.