High-density single-nucleotide polymorphism maps of the human genome.

Here we report a large, extensively characterized set of single-nucleotide polymorphisms (SNPs) covering the human genome. We determined the allele frequencies of 55,018 SNPs in African Americans, Asians (Japanese-Chinese), and European Americans as part of The SNP Consortium's Allele Frequency Project. A subset of 8333 SNPs was also characterized in Koreans. Because these SNPs were ascertained in the same way, the data set is particularly useful for modeling. Our results document that much genetic variation is shared among populations. For autosomes, some 44% of these SNPs have a minor allele frequency > or =10% in each population, and the average allele frequency differences between populations with different continental origins are less than 19%. However, the several percentage point allele frequency differences among the closely related Korean, Japanese, and Chinese populations suggest caution in using mixtures of well-established populations for case-control genetic studies of complex traits. We estimate that approximately 7% of these SNPs are private SNPs with minor allele frequencies <1%. A useful set of characterized SNPs with large allele frequency differences between populations (>60%) can be used for admixture studies. High-density maps of high-quality, characterized SNPs produced by this project are freely available.

Primer design and marker clustering for multiplex SNP-IT primer extension genotyping assay using statistical modeling.

MOTIVATION: The optimization of the primer design is critical for the development of high-throughput SNP genotyping methods. Recently developed statistical models of the SNP-IT primer extension genotyping reaction allow further improvement of primer quality for the assay. RESULTS: Here we describe how the statistical models can be used to improve primer design for the assay. We also show how to optimize clustering of the SNP markers into multiplex panels using statistical model for multiplex SNP-IT. The primer set failure probability calculated by a model is used as a minimization function for both primer selection and primers clustering. Three clustering algorithms for the multiplex genotyping SNP-IT assay are described and their relative performance is evaluated. We also describe the approaches to improve the speed of primer design and clustering calculations when using the statistical models. Our clustering decreases the average failure probability of the marker set by 7-25%. The experimental marker failure rate in the multiplex reaction was reduced dramatically and success rate can be achieved as high as 96%. AVAILABILITY: The primer design using statistical models is freely available from www.autoprimer.com.

Auto-validation of fluorescent primer extension genotyping assay using signal clustering and neural networks.

BACKGROUND: SNP genotyping typically incorporates a review step to ensure that the genotype calls for a particular SNP are correct. For high-throughput genotyping, such as that provided by the GenomeLab SNPstream instrument from Beckman Coulter, Inc., the manual review used for low-volume genotyping becomes a major bottleneck. The work reported here describes the application of a neural network to automate the review of results. RESULTS: We describe an approach to reviewing the quality of primer extension 2-color fluorescent reactions by clustering optical signals obtained from multiple samples and a single reaction set-up. The method evaluates the quality of the signal clusters from the genotyping results. We developed 64 scores to measure the geometry and position of the signal clusters. The expected signal distribution was represented by a distribution of a 64-component parametric vector obtained by training the two-layer neural network onto a set of 10,968 manually reviewed 2D plots containing the signal clusters. CONCLUSION: The neural network approach described in this paper may be used with results from the GenomeLab SNPstream instrument for high-throughput SNP genotyping. The overall correlation with manual revision was 0.844. The approach can be applied to a quality review of results from other high-throughput fluorescent-based biochemical assays in a high-throughput mode.

Chloride transport across lipid bilayers and transmembrane potential induction by an oligophenoxyacetamide.

This contribution describes the discovery and properties of a synthetic, low-molecular weight compound that transports Cl- across bilayer membranes. Such compounds have potential as therapeutics for cystic fibrosis and cancer. The H+/Cl- co-transport activities of acyclic tetrabutylamides 1-6 were compared by using a pH-stat assay with synthetic EYPC liposomes. The ion transport activity of the most active compound, trimer 3, was an order of magnitude greater than that of calix[4]arene tetrabutylamide C1 a macrocycle known to function as a synthetic ion channel. Trimer 3 has an unprecedented function for a synthetic compound, as it induces a stable potential in liposomes experiencing a transmembrane Cl-/SO42- gradient. Data from both pH-stat and 35Cl NMR experiments indicate that 3 co-transports H+/Cl-. Although 3 transports both Cl- and H+ the overall process is not electrically silent. Thus, trimer 3 induces a stable potential in LUVs due to a transmembrane anionic gradient. The ability of trimer 3 to transport Cl-, to maintain a transmembrane potential, along with its high activity at uM concentrations, its low molecular weight, and its simple preparation, make this compound a valuable lead in drug development for diseases caused by Cl- transport malfunction.