Abstract
Linkage and association analyses were performed to identify loci affecting disease susceptibility by scoring previously characterized sequence variations such as microsatellites and single nucleotide polymorphisms. Lack of markers in regions of interest, as well as difficulty in adapting various methods to high-throughput settings, often limits the effectiveness of the analyses. We have adapted the Escherichia coli mismatch detection system, employing the factors MutS, MutL and MutH, for use in PCR-based, automated, high-throughput genotyping and mutation detection of genomic DNA. Optimal sensitivity and signal-to-noise ratios were obtained in a straightforward fashion because the detection reaction proved to be principally dependent upon monovalent cation concentration and MutL concentration. Quantitative relationships of the optimal values of these parameters with length of the DNA test fragment were demonstrated, in support of the translocation model for the mechanism of action of these enzymes, rather than the molecular switch model. Thus, rapid, sequence-independent optimization was possible for each new genomic target region. Other factors potentially limiting the flexibility of mismatch scanning, such as positioning of dam recognition sites within the target fragment, have also been investigated. We developed several strategies, which can be easily adapted to automation, for limiting the analysis to intersample heteroduplexes. Thus, the principal barriers to the use of this methodology, which we have designated PCR candidate region mismatch scanning, in cost-effective, high-throughput settings have been removed.