Single nucleotide polymorphism (SNP) data can be obtained using one of the numerous uniplex or multiplex SNP genotyping platforms that combine a variety of chemistries, detection methods, and reaction formats. Kompetitive Allele Specific PCR (KASP) is one of the uniplex SNP genotyping platforms, and has evolved to be a global benchmark technology. However, there are no publications relating either to the technology itself or to its application in crop improvement programs. In this review, we provide an overview of the different aspects of the KASP genotyping platform, discuss its application in crop improvement, and compare it with the chip-based Illumina GoldenGate platform. The International Maize and Wheat Improvement Center routinely uses KASP, generating in excess of a million data points annually for crop improvement purposes. We found that (1) 81 % of the SNPs used in a custom-designed GoldenGate assay were transferable to KASP; (2) using KASP, negative controls (no template) consistently clustered together and rarely produced signals exceeding the threshold values for allele calling, in contrast to the situation observed using GoldenGate assays; (3) KASP’s average genotyping error in positive control DNA samples was 0.7–1.6 %, which is lower than that observed using GoldenGate (2.0–2.4 %); (4) KASP genotyping costs for marker-assisted recurrent selection were 7.9–46.1 % cheaper than those of the BeadXpress and GoldenGate platforms; and (5) KASP offers cost-effective and scalable flexibility in applications that require small to moderate numbers of markers, such as quality control analysis, quantitative trait loci (QTL) mapping in bi-parental populations, marker-assisted recurrent selection, marker-assisted backcrossing, and QTL fine mapping.

Single nucleotide polymorphism genotyping using Kompetitive Allele Specific PCR (KASP): overview of the technology and its application in crop improvement

We have developed a high-throughput method for analyzing the methylation status of hundreds of preselected genes simultaneously and have applied it to the discovery of methylation signatures that distinguish normal from cancer tissue samples. Through an adaptation of the GoldenGate genotyping assay implemented on a BeadArray platform, the methylation state of 1536 specific CpG sites in 371 genes (one to nine CpG sites per gene) was measured in a single reaction by multiplexed genotyping of 200 ng of bisulfite-treated genomic DNA. The assay was used to obtain a quantitative measure of the methylation level at each CpG site. After validating the assay in cell lines and normal tissues, we analyzed a panel of lung cancer biopsy samples (N = 22) and identified a panel of methylation markers that distinguished lung adenocarcinomas from normal lung tissues with high specificity. These markers were validated in a second sample set (N = 24). These results demonstrate the effectiveness of the method for reliably profiling many CpG sites in parallel for the discovery of informative methylation markers. The technology should prove useful for DNA methylation analyses in large populations, with potential application to the classification and diagnosis of a broad range of cancers and other diseases.

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High-throughput DNA methylation profiling using universal bead arrays

Oligonucleotide probe arrays have enabled massively parallel analysis of gene expression levels from a single cDNA sample. Application of microarray technology to analyzing genomic DNA has been stymied by the sequence complexity of the entire human genome. A robust, single base-resolution direct genomic assay would extend the reach of microarray technology. We developed an array-based whole-genome genotyping assay that does not require PCR and enables effectively unlimited multiplexing. The assay achieves a high signal-to-noise ratio by combining specific hybridization of picomolar concentrations of whole genome-amplified DNA to arrayed probes with allele-specific primer extension and signal amplification. As proof of principle, we genotyped several hundred previously characterized SNPs. The conversion rate, call rate and accuracy were comparable to those of high-performance PCR-based genotyping assays.

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A genome-wide scalable SNP genotyping assay using microarray technology.

After the recent discovery that common genetic variation in 8q24 influences inherited risk of prostate cancer, we genotyped 2,973 SNPs in up to 7,518 men with and without prostate cancer from five populations. We identified seven risk variants, five of them previously undescribed, spanning 430 kb and each independently predicting risk for prostate cancer (P = 7.9 x 10(-19) for the strongest association, and P < 1.5 x 10(-4) for five of the variants, after controlling for each of the others). The variants define common genotypes that span a more than fivefold range of susceptibility to cancer in some populations. None of the prostate cancer risk variants aligns to a known gene or alters the coding sequence of an encoded protein.

/pdf/multiple-regions-within-8q24-independently-affect-risk-for-1l9xx6r411.pdf

Multiple regions within 8q24 independently affect risk for prostate cancer.

Background Rare mutations affecting the FOXP2 transcription factor cause a monogenic speech and language disorder. We hypothesized that neural pathways downstream of FOXP2 influence more common phenotypes, such as specific language impairment. Methods We performed genomic screening for regions bound by FOXP2 using chromatin immunoprecipitation, which led us to focus on one particular gene that was a strong candidate for involvement in language impairments. We then tested for associations between single-nucleotide polymorphisms (SNPs) in this gene and language deficits in a well-characterized set of 184 families affected with specific language impairment. Results We found that FOXP2 binds to and dramatically down-regulates CNTNAP2, a gene that encodes a neurexin and is expressed in the developing human cortex. On analyzing CNTNAP2 polymorphisms in children with typical specific language impairment, we detected significant quantitative associations with nonsense-word repetition, a heritable behavioral marke...

/pdf/a-functional-genetic-link-between-distinct-developmental-10hzwzdmpc.pdf

A functional genetic link between distinct developmental language disorders.

genetic factors underlying common disease are largely unknown. Discovery of disease-causing genes will transform our knowledge of the genetic contribution to human disease, lead to new genetic screens, and underpin research into new cures and improved lifestyles. The se-quencing of the human genome has catalyzed efforts to search for disease genes by the strategy of associating sequence variants with measurable phenotypes. In particular , the Human Genome Project and follow-on efforts to characterize genetic variation have resulted in the discovery of millions of single-nucleotide polymorphisms (SNPs) (Patil et al. 2001; Sachidanandam et al. 2001; Reich et al. 2003). This represents a significant fraction of common genetic variation in the human genome and creates an unprecedented opportunity to associate genes with phenotypes via large-scale SNP genotyping studies. To make use of this information, efficient and accurate SNP genotyping technologies are needed. However, most methods were designed to analyze only one or a few SNPs per assay, and are costly to scale up (Kwok 2001; Syvanen 2001). To help enable genome-wide association studies and other large-scale genetic analysis projects, we have developed an integrated SNP genotyping system that combines a highly multiplexed assay with an accurate readout technology based on random arrays of DNA-coated beads (Michael et al. 1998; Oliphant et al. 2002; Gunderson et al. 2004). Our aim was to reduce costs and increase productivity by ~2 orders of magnitude. We chose a multiplexed approach because it is more easily scalable and is intrinsically cost-efficient (Wang et al. 1998). Although existing multiplexed approaches lacked the combination of accuracy, robustness, scalability, and cost-effectiveness needed for truly large-scale endeavors, we hypothesized that some of these limitations could be overcome by designing an assay specifically for multiplexing. To increase throughput and decrease costs by ~2 orders of magnitude, it was necessary to eliminate bottlenecks throughout the genotyping process. It was also desirable to minimize sources of variability and human error in order to ensure data quality and reproducibility. We therefore took a systems-level view to technology design, development , and integration. Although the focus of this paper is on a novel, highly multiplexed genotyping assay, the GoldenGate ™ assay, four other key technologies that were developed in parallel, as part of the complete BeadLab system (Oliphant et al. 2002), are briefly described below. BEADARRAY™ PLATFORM We developed an array technology based on random assembly of beads in micro-wells located at the end of an …

D Campbell

Papers

Highly parallel SNP genotyping.