Clinical application of high throughput molecular screening techniques for pharmacogenomics.

Genetic analysis is one of the fastest-growing areas of clinical diagnostics. Fortunately, as our knowledge of clinically relevant genetic variants rapidly expands, so does our ability to detect these variants in patient samples. Increasing demand for genetic information may necessitate the use of high throughput diagnostic methods as part of clinically validated testing. Here we provide a general overview of our current and near-future abilities to perform large-scale genetic testing in the clinical laboratory. First we review in detail molecular methods used for high throughput mutation detection, including techniques able to monitor thousands of genetic variants for a single patient or to genotype a single genetic variant for thousands of patients simultaneously. These methods are analyzed in the context of pharmacogenomic testing in the clinical laboratories, with a focus on tests that are currently validated as well as those that hold strong promise for widespread clinical application in the near future. We further discuss the unique economic and clinical challenges posed by pharmacogenomic markers. Our ability to detect genetic variants frequently outstrips our ability to accurately interpret them in a clinical context, carrying implications both for test development and introduction into patient management algorithms. These complexities must be taken into account prior to the introduction of any pharmacogenomic biomarker into routine clinical testing

Linkage disequilibrium based genotype calling from low-coverage shotgun sequencing reads

Background Recent technology advances have enabled sequencing of individual genomes, promising to revolutionize biomedical research. However, deep sequencing remains more expensive than microarrays for performing whole-genome SNP genotyping. Results In this paper we introduce a new multi-locus statistical model and computationally efficient genotype calling algorithms that integrate shotgun sequencing data with linkage disequilibrium (LD) information extracted from reference population panels such as Hapmap or the 1000 genomes project. Experiments on publicly available 454, Illumina, and ABI SOLiD sequencing datasets suggest that integration of LD information results in genotype calling accuracy comparable to that of microarray platforms from sequencing data of low-coverage. A software package implementing our algorithm, released under the GNU General Public License, is available at http://dna.engr.uconn.edu/software/GeneSeq/. Conclusions Integration of LD information leads to significant improvements in genotype calling accuracy compared to prior LD-oblivious methods, rendering low-coverage sequencing as a viable alternative to microarrays for conducting large-scale genome-wide association studies

Genotyping pooled DNA using 100K SNP microarrays: a step towards genomewide association scans

The identification of quantitative trait loci (QTLs) of small effect size that underlie complex traits poses a particular challenge for geneticists due to the large sample sizes and large numbers of genetic markers required for genomewide association scans. An efficient solution for screening purposes is to combine single nucleotide polymorphism (SNP) microarrays and DNA pooling (SNP-MaP), an approach that has been shown to be valid, reliable and accurate in deriving relative allele frequency estimates from pooled DNA for groups such as cases and controls for 10K SNP microarrays. However, in order to conduct a genomewide association study many more SNP markers are needed. To this end, we assessed the validity and reliability of the SNP-MaP method using Affymetrix GeneChip(®) Mapping 100K Array set. Interpretable results emerged for 95% of the SNPs (nearly 110 000 SNPs). We found that SNP-MaP allele frequency estimates correlated 0.939 with allele frequencies for 97 605 SNPs that were genotyped individually in an independent population; the correlation was 0.971 for 26 SNPs that were genotyped individually for the 1028 individuals used to construct the DNA pools. We conclude that extending the SNP-MaP method to the Affymetrix GeneChip(®) Mapping 100K Array set provides a useful screen of >100 000 SNP markers for QTL association scans

Validation and extension of an empirical Bayes method for SNP calling on Affymetrix microarrays

Extended and validated CRLMM is shown to be more accurate than the Affymetrix default programs, and datasets and methods for validation are presented that can serve as standard benchmarks by which future SNP chip calling algorithms can be measured

A novel multifunctional oligonucleotide microarray for Toxoplasma gondii

<p>Abstract</p> <p>Background</p> <p>Microarrays are invaluable tools for genome interrogation, SNP detection, and expression analysis, among other applications. Such broad capabilities would be of value to many pathogen research communities, although the development and use of genome-scale microarrays is often a costly undertaking. Therefore, effective methods for reducing unnecessary probes while maintaining or expanding functionality would be relevant to many investigators.</p> <p>Results</p> <p>Taking advantage of available genome sequences and annotation for <it>Toxoplasma gondii </it>(a pathogenic parasite responsible for illness in immunocompromised individuals) and <it>Plasmodium falciparum </it>(a related parasite responsible for severe human malaria), we designed a single oligonucleotide microarray capable of supporting a wide range of applications at relatively low cost, including genome-wide expression profiling for <it>Toxoplasma</it>, and single-nucleotide polymorphism (SNP)-based genotyping of both <it>T. gondii </it>and <it>P. falciparum</it>. Expression profiling of the three clonotypic lineages dominating <it>T. gondii </it>populations in North America and Europe provides a first comprehensive view of the parasite transcriptome, revealing that ~49% of all annotated genes are expressed in parasite tachyzoites (the acutely lytic stage responsible for pathogenesis) and 26% of genes are differentially expressed among strains. A novel design utilizing few probes provided high confidence genotyping, used here to resolve recombination points in the clonal progeny of sexual crosses. Recent sequencing of additional <it>T. gondii </it>isolates identifies >620 K new SNPs, including ~11 K that intersect with expression profiling probes, yielding additional markers for genotyping studies, and further validating the utility of a combined expression profiling/genotyping array design. Additional applications facilitating SNP and transcript discovery, alternative statistical methods for quantifying gene expression, etc. are also pursued at pilot scale to inform future array designs.</p> <p>Conclusions</p> <p>In addition to providing an initial global view of the <it>T. gondii </it>transcriptome across major lineages and permitting detailed resolution of recombination points in a historical sexual cross, the multifunctional nature of this array also allowed opportunities to exploit probes for purposes beyond their intended use, enhancing analyses. This array is in widespread use by the <it>T. gondii </it>research community, and several aspects of the design strategy are likely to be useful for other pathogens.</p

Validation and extension of an empirical Bayes method for SNP calling on Affymetrix microarrays

Extended and validated CRLMM is shown to be more accurate than the Affymetrix default programs, and datasets and methods for validation are presented that can serve as standard benchmarks by which future SNP chip calling algorithms can be measured