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The genetic scientific community is exploding with new robust tools which explore the connections between genotypes and phenotypes. The falling prices from developing to mature genotyping platforms, result in abundant data to interrogate and analyze. In addition, as more detailed clinical classification of patients is performed, stronger genetic associations of complex diseases are discovered. The new technical developments that enable the association of genes with disease, as well as practical examples of how these techniques are used is the emphasis of Cambridge Healthtech Institute’s Second Annual Genotyping Tools: Sequencing to SNPs . . . Strategies to Success. Learn from savvy, seasoned researchers as they share their scientific strategies and success.

Monday, June 8

7:30 am Registration and Morning Coffee

Copy Number Variation

8:45 Chairperson’s Remarks
Kelly Li, Ph.D., Senior Staff Scientist, Genomic Assays R&D, Applied Biosystems


Mechanisms for CNV in the Human Genome: From Single Exons to Megabases of Genomic Change

LupskiJames R. Lupski, M.D., Ph.D., Cullen Professor and Vice Chairman, Molecular & Human Genetics; Professor, Baylor College of Medicine






9:45 Genomic Profiles of DNA Copy Number Alteration in Human Cancer

Jonathan R. Pollack, M.D., Ph.D., Associate Professor, Department of Pathology, Stanford University School of Medicine

Cancer genomes are characterized by gains and losses of genomic DNA, resulting in the altered expression of cancer genes, and driving cancer development/progression. As such, mapping copy number alterations is a powerful approach to pinpoint novel cancer genes. This presentation will summarize evolving technologies for profiling copy number alterations, and their application to cancer genomics with emphasis on cancer gene/pathway discovery. The integration of genomic profiles with other genome-scale data, including expression profiles, will also be discussed.

10:15 Networking Coffee Break

10:45 Systematic Assessment of Copy Number Variant Detection via Genome-wide SNP Genotyping

Gregory Cooper, Ph.D., Senior Research Fellow, Genome Sciences, University of Washington

11:15 GLI2 Promotes Multiple Tumor Cell Characteristics

Antoine Snijders, Ph.D., Biologist Research Scientist, Life Sciences Division, Lawrence Berkeley National Lab

Genome-wide DNA copy number profiling identified GLI2, a downstream transcription factor in the hedgehog signaling pathway, as a candidate oncogene amplified and overexpressed in oral squamous cell carcinoma. Hedgehog signaling is often activated in tumors, yet it remains unclear how GLI2, a transcription factor activated by this pathway, acts as an oncogene. We show that GLI2 is a pleiotropic oncogene. Overexpression induces genomic instability and blocks differentiation, likely mediated in part by enhanced expression of the stem cell gene SOX2. GLI2 also induces TGFbeta dependent transdifferentiation of foreskin and tongue, but not gingival fibroblasts into myofibroblasts, creating an environment permissive for invasion by keratinocytes, which are in various stages of differentiation having down regulated GLI2. Thus, up-regulated GLI2 expression is sufficient to induce a number of the acquired characteristics of tumor cells; however the stroma, in a tissue specific manner, determines whether certain GLI2 oncogenic traits are expressed.

11:45 Significant Gene Content Variation Characterizes the Genomes of Inbred Mouse Strains

Paul Kassner, Ph.D., Scientific Director, Amgen, Inc.

12:15 pm Close of Morning Session

12:30 Luncheon Presentation Sponsored by Applied bio 
Copy Number Variation Analysis Using Quantitative TaqMan® Copy Number Assays
Kelly Li, Ph.D., Senior Staff Scientist, Genomic Assays R&D, Applied Biosystems
Copy number variation (CNV) is an important polymorphism in the human genome. Whole-genome CNV studies have identified over thousands of CNV regions (CNVRs) that cover more than 10-25% of the human genome. These CNVRs contain hundreds of genes and disease loci. Their copy number changes could impact gene activity and disease susceptibility. Although array-based technologies are powerful for large-scale CNV discoveries, more quantitative technologies with higher sample throughput are required to validate newly identified CNVs, detect deletions/duplications in larger populations, and investigate specific regions/genes in disease association studies. To meet these challenges and demands, Applied Biosystems has developed and launched over 1.6 million genome-wide pre-designed TaqMan® copy number assays. The TaqMan® copy number assay is a duplex reaction with a FAM™-assay targeting the gene of interest and a VIC®-assay targeting the reference gene (two copies per diploid genome) in the same well. Copy number is then determined by relative quantification using a reference sample known to have two copies of the gene of interest. To validate the proprietary assay design pipeline, we tested a collection of selected assays with a genomic DNA set of 92 individuals, aneuploidy samples, HAPMAP DNA collection as well as samples with known deletions/duplications. We will also show several studies in collaboration with our customers to demonstrate the utilities of TaqMan® copy number assays in different applications. These studies show TaqMan® copy number assays are quantitative and robust with high reproducibility, accuracy, specificity, and sample throughput for copy number detections.

Single Nucleotide Polymorphism

2:00 Chairperson’s Remarks

James R. Lupski, M.D., Ph.D., Cullen Professor and Vice Chairman, Molecular & Human Genetics; Professor, Baylor College of Medicine

2:05 Signatures of Evolution in Disease Gene Characterization

Ching Ouyang, Ph.D., Assistant Research Scientist, Department of Molecular Medicine, Beckman Research Institute of the City of Hope

The association of human genetic variation with common, complex diseases has been intensively studied. We have focused on the relationship of SNPs with potential and actual functional variation to evolutionary lineages of human haplotypes and linkage disequilibrium blocks. Our rationale is that such functional variation may have ancient roots in the descent of humans, representing an array of responses to changing environments maintained by balancing selection. Thus far, our analysis supports this hypothesis; and we will present evidence and examples of haplotype frameworks, evolutionarily conserved across all human populations thus far examined and responsible for as much as half of functional differences encoded by human SNP variation.

2:35 Rare Functional SNPs and the Genetic Architecture of Complex Diseases

Ivan Gorlov, Ph.D., Department of Genitourinary Medical Oncology, M.D. Anderson Cancer Center, The University of Texas

Presented will be our study which sought to evaluate the relationship between functional effects of SNPs and minor allele frequency. SNPs were classified according to whether they are synonymous or nonsynonymous. Nonsynonymous SNPs were further classified into conservative - those with a minor effect on protein structure and function, and radical - those with a major effect. Results showed that the more significant the effect on the protein function, the lower the minor allele frequency of the SNP, suggesting a negative selection against SNPs that affect protein function. The implication of our studies is that while the common-disease common variant hypothesis may be valid in some situations, many protein-changing and therefore potentially functional SNPs undergo negative selection pressure. Infrequent SNPs are likely to play an important role in etiology of complex diseases with multiple genes involved in disease development.

3:05 Avoiding Hidden Allelic Drop-out During SNP
Genotyping by Using Robust Multiplex PCR and Arrayed Primer Extension

Scott Tebbutt, Ph.D., Assistant Professor and Principal Investigator, The James Hogg iCAPTURE Centre for Cardiovascular and Pulmonary Research, St. Paul’s Hospital, University of British Columbia

We have developed an accurate medium-throughput genotyping method based on arrayed primer extension (APEX). Our microarray-based design, chemistry and analysis tools have been validated using resources from the International HapMap Project, and deliver highly robust and accurate genotypes (100% call rate and >99.9% genotyping accuracy) from as little as 5ng of genomic DNA (for a 50-plex assay). We use multiple and redundant genetic probes for each SNP site, along with robust statistical analysis algorithms designed to unambiguously capture the data from this genetic probe redundancy and turn these data into a high-quality genotype call. In contrast to other genotyping platforms, this allows us to obtain extremely high call rates whilst maintaining excellent genotype accuracy. In addition, our recent development of a modified PCR design that reduces the probability of genotyping error due to sporadic allelic drop-out, further improves on the accuracy of our method.

Sponsored by
Sequenom small logo
3:35 Genomic Biomarker Validation Using the Sequenom MassARRAY

Marijo Gallina, Marketing Manager, Sequenom

Personalized medicine has the potential to revolutionize the way we practice medicine; this has been universally recognized and accepted by researchers, clinicians and regulatory agencies. For the past decade, researchers have utilized the many excellent tools and technologies available allowing researchers to discover novel biomarkers (SNPs, copy number variants, transcript profiles, etc.) and the scientific literature is filled with preliminary research findings associating these biomarkers with clinical outcomes. Unfortunately, most of these findings have not led to validated, clinically applicable tools to allow the personalized revolution to come to fruition. One of the primary reasons for this bottleneck is the lack of technologies allowing clinical researchers to validate biomarkers in an efficient, cost effective manner. Sequenom now provides specific tools allowing clinical researchers to validate their biomarkers across relevant samples types at a low per sample cost, with highest quality data. Examples from the scientific and clinical literature as well as from internal studies, will be presented demonstrating the ability to validate a variety of biomarker types (including gene expression profiles, genotypes, epigenetic markers) utilizing a flexible format with the sample throughput capabilities required to clinically validate a biomarker set.

3:50 Networking Refreshment Break

4:15 Electrostatic Imaging of DNA Microarrays

Khalid Salaita, Postdoctoral Fellow, Department of Chemistry, University of California Berkeley

I will describe a method for sensitive and label-free electrostatic readout of DNA or RNA hybridization on microarrays. The electrostatic properties of the microarray are measured from the position and motion of charged microspheres randomly dispersed over the surface. We demonstrate nondestructive electrostatic imaging with 10 micron lateral resolution overcentimeter-length scales, which is four-orders of magnitude larger than that achievable with conventional scanning electrostatic force microscopy. Changes in surface charge density as a result of specific hybridization can be detected and quantified with 50-pM sensitivity, single base-pair mismatch selectivity and in the presence of complex background. Because the naked eye is sufficient to read out hybridization, this approach may facilitate broad application of multiplexed assays.

4:45 Pathway-Based Analysis of GWAS

Sergio E Baranzini, Ph.D., Assistant Professor, Department of Neurology, University of California San Francisco
The usefulness of genome-wide association studies (GWAS) to discover common genetic variants associated with susceptibility to complex diseases has been empirically demonstrated. In a typical GWAS, hundreds of thousands of markers are tested simultaneously in cases and controls and the allelic frequencies of each marker are compared between the two groups. However, because of the exceedingly large multiple testing involved in these studies, very few exceed the genome-wide significance threshold and those that do not exceed this stringent statistical requirement are generally neglected. In this presentation, evidence will be presented that while individual modest genetic effects are difficult to ascertain, they can be collectively identified by combining nominally significant proof of genetic association with current knowledge of biochemical pathways.

5:15 Welcoming Reception

6:30 Close of Day