Automated MALDI-TOF Mass Spectrometry based SNP Genotyping

Abstract

With the advancement of the human genome project the determination of the general structure of the human genome approaches its completion. A 'working draft' covering 90% of the genomic sequence has already been published. Pharmacogenomic research now has to elucidate the molecular polymorphisms underlying individual phenotypic differences. This knowledge will significantly increase the understanding of individual predispositions to certain diseases, as well as the efficacy and potential adverse effects of certain drugs. The most common genetic variations are single nucleotide polymorphisms (SNPs). A SNP is the occurence of a different nucleotide in different individuals at a given chromosomal position. It is estimated that SNPs account for approximately 90% of the individual genotypic variations. SNP genotyping can be addressed by several different methods and technologies. Matrix-assisted laser desorption/ionization mass spectrometry (MALDI-TOF MS) measures directly a physical property of the analyte - its molecular mass. Accordingly, MALDI-TOF MS SNP genotyping is not susceptible to background problems resulting from hybridization based detection reactions. Here we present our MALDI-TOF MS SNP genotyping system that allows fully automated data acquisition and SNP genotyping (Bruker Daltonik, Bremen, Germany). The MALDI-TOF MS technology enables a throughput of several thousands of DNA samples per day. However, sample throughput may be further increased by the analysis of pooled DNA samples. This is especially useful to screen a high sample number for a DNA containing a rare polymorphism. The DNA pool displaying the desired allele can easily be identified and subsequently splitted into individual DNA samples. This approach will significantly decrease the necessary number of samples to be screened. Moreover, recent advances concerning the calculation of allele-frequencies from the peak intensities of spectra from pooled DNA samples look promising.