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Open Access Methodology article

TAMGeS: a Three-Array Method for Genotyping of SNPs by a dual-colour approach

Arianna Cozza1, Francesco Morandin2, Silvia Giulia Galfrè13, Veronica Mariotti1, Roberto Marangoni3 and Silvia Pellegrini1*

Author Affiliations

1 Department of Experimental Pathology, Medical Biotechnology, Infectivology and Epidemiology, University of Pisa, Via Roma 55, 56126 Pisa, Italy

2 Department of Mathematics, University of Parma, Parco Area delle Scienze 53/A, 43100 Parma, Italy

3 Department of Informatics, University of Pisa, Largo Bruno Pontecorvo 3, 56127 Pisa, Italy

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BMC Genomics 2007, 8:10  doi:10.1186/1471-2164-8-10

Published: 9 January 2007

Abstract

Background

Many of the most effective high-throughput protocols for SNP genotyping employ microarrays. Genotypes are assessed by comparing the signal intensities that derive from the hybridization of different allele-specific probes labelled either by using four fluorescent dyes, one for each base, or by using only two dyes and investigating the polymorphic alleles two by two on separate arrays. The employment of only two dyes makes it possible to use a dual-laser scanner, which has the advantage of being present in every microarray laboratory. However, this protocol may present some drawbacks. To infer all the six possible genotypes it is necessary to compare signals from two arrays, but this comparison not always is successful. A number of systematic errors in the experimental protocol, in fact, may differently affect signal intensities on separate arrays. Here we present TAMGeS (Three-Array Method for Genotyping of SNPs), an exhaustive method for SNP genotyping through SBE (Single Base Extension) and dual-colour microarrays, which makes the comparison of signals on distinct arrays reliable by using a third array and a data handling method for signal normalization based on bilinear regression theory.

Results

We tested the effectiveness of the proposed method by evaluating the results obtained from the direct comparison of the two arrays or by applying TAMGeS, both on experimental and synthetic data. With synthetic data, TAMGeS reduced the frequency of errors by an order of magnitude, when the incidence of systematic errors was not negligible. With the experimental data, produced by genotyping 25 SNPs in 437 subjects, TAMGeS reduced the percentage of missing genotypes from 54% (Two-Array Method) to 14.5%. Allelic and genotypic call rates were 99.3% and 99.5%, respectively. The normalization procedure takes into account also systematic errors, which can be generated by a time-delayed assay, thus making the protocol more flexible.

Conclusion

TAMGeS represents an innovative method, which proved to be very effective in producing reliable SNP genotyping data by dual-colour microarrays. The requirement of a third array is well balanced by the strong enhancement in data quality and by the greater flexibility of the experimental protocol.