Genotyping by mass spectrometry takes flight

Genotyping of patients with sporadic and radiation-associated meningiomas

Ionizing radiation is the most established risk factor for meningioma formation. Our aim was to evaluate the main effect of selected candidate genes on the development of meningioma and their possible interaction with ionizing radiation in the causation of this tumor. The total study population included 440 cases and controls: 150 meningioma patients who were irradiated for tinea capitis in childhood, 129 individuals who were similarly irradiated but did not develop meningioma, 69 meningioma patients with no previous history of irradiation, and 92 asymptomatic population controls. DNA from peripheral blood samples was genotyped for single nucleotide polymorphisms (SNP) in 12 genes: NF2, XRCC1, XRCC3, XRCC5, ERCC2, Ki-ras, p16, cyclin D1, PTEN, E-cadherin, TGFB1, and TGFBR2. SNP analysis was done using the MassArray system (Sequenom, San Diego, CA) and computerized analysis by SpectroTYPER. Logistic regressions were applied to evaluate main effect of each gene on meningioma formation and interaction between gene and radiation. Intragenic SNPs in the Ki-ras and ERCC2 genes were associated with meningioma risk (odds ratio, 1.76; 95% confidence interval, 1.07-2.92 and odds ratio, 1.68; 95% confidence interval, 1.00-2.84, respectively). A significant interaction was found between radiation and cyclin D1 and p16 SNPs (P for interaction = 0.005 and 0.057, respectively). Our findings suggest that Ki-ras and ERCC2 SNPs are possible markers for meningioma formation, whereas cyclin D1 and p16 SNPs may be markers of genes that have an inverse effect on the risk to develop meningioma in irradiated and nonirradiated populations.

Diversity Arrays Technology (DArT) for whole-genome profiling of barley

Diversity Arrays Technology (DArT) can detect and type DNA variation at several hundred genomic loci in parallel without relying on sequence information. Here we show that it can be effectively applied to genetic mapping and diversity analyses of barley, a species with a 5,000-Mbp genome. We tested several complexity reduction methods and selected two that generated the most polymorphic genomic representations. Arrays containing individual fragments from these representations generated DArT fingerprints with a genotype call rate of 98.0% and a scoring reproducibility of at least 99.8%. The fingerprints grouped barley lines according to known genetic relationships. To validate the Mendelian behavior of DArT markers, we constructed a genetic map for a cross between cultivars Steptoe and Morex. Nearly all polymorphic array features could be incorporated into one of seven linkage groups (98.8%). The resulting map comprised approximately 385 unique DArT markers and spanned 1,137 centimorgans. A comparison with the restriction fragment length polymorphism-based framework map indicated that the quality of the DArT map was equivalent, if not superior, to that of the framework map. These results highlight the potential of DArT as a generic technique for genome profiling in the context of molecular breeding and genomics.

Pharmacogenomics: unlocking the human genome for better drug therapy

There is great heterogeneity in the way humans respond to medications, often requiring empirical strategies to find the appropriate drug therapy for each patient (the "art" of medicine). Over the past 50 years, there has been great progress in understanding the molecular basis of drug action and in elucidating genetic determinants of disease pathogenesis and drug response. Pharmacogenomics is the burgeoning field of investigation that aims to further elucidate the inherited nature of interindividual differences in drug disposition and effects, with the ultimate goal of providing a stronger scientific basis for selecting the optimal drug therapy and dosages for each patient. These genetic insights should also lead to mechanism-based approaches to the discovery and development of new medications. This review highlights the current status of work in this field and addresses strategies that hold promise for future advances in pharmacogenomics.

Automation in genotyping of single nucleotide polymorphisms

Automation for genotyping of single nucleotide polymorphisms (SNPs) can be split into the automation of the sample preparation and the automation of the analysis technology. SNP genotyping methods are reviewed and solutions for their automation discussed. A panacea for SNP genotyping does not exist. Different scientific questions require adapted solutions. The choice of a technology for SNP genotyping depends on whether few different SNPs are to be genotyped in many individuals, or many different SNPs are to be genotyped in few individuals. The requirements of throughput and the ease of establishing an SNP genotyping operation are important, as well as the degree of integration. The potential and state-of-the-art of different solutions are outlined.