Friday, August 25
7:30 Breakfast Technology workshop (Sponsorship Available)
8:00 Morning Coffee
SNP Genotyping
8:15 Chair's Remarks
Featured Presentation
8:20 Genome-Wide Association for a Quantitative Trait: QT Interval and NOS1AP
Dan E. Arking, Ph.D., Instructor in Genetic Medicine, McKusick-Nathans Institute of Genetic Medicine, Johns Hopkins University School of Medicine
Performing a genome-wide association study on 200 subjects at the extremes of a population-based QT interval distribution of 3,966 subjects from Germany, followed by genotyping potential positive results in the remainder of the cohort, we identified a common genetic polymorphism influencing this quantitative trait. Statistically significant findings were validated in two independent samples of 2,646 subjects from Germany and 1,805 subjects from the US Framingham Heart Study. This genome-wide study identified NOS1AP a regulator of neuronal
NOS, as a new target that modulates cardiac repolarization. Approximately 60% of subjects of European ancestry carry at least one minor allele of the CAPON genetic variant, likely non-coding, which explains up to 1.5% of QT interval variation.
Case Study One
9:00 SNP Arrays: Looking Beyond Familial Haplotypes
Jean C. Zenklusen, M.S., Ph.D, Staff Scientist, Neuro-Oncology Branch, NIH/NCI
Single Nucleotide Polymorphisms (SNPs) have been used in recent years in epidemiological studies to produce predictive haplotypes for affected individuals based in pedigree studies with affected families, and to identify regions where putative disease genes can be located. With the production of large-scale SNP arrays, this type of work has been greatly facilitated. These types of arrays have also opened new applications for the use of SNPs that are independent of the availability of large, well characterized, familial sample collections. If one considers each individual SNP as an independent, location specific marker along the genome, then these large-scale SNP arrays transform into a very powerful genotyping tool that allows for gene hunting, definition of common areas of copy number alterations, modeling of disease onset, progression and classification based on genomic changes. The challenge faced today by most researchers using these large-scale arrays is the lack of bioinformatics tools to mine the wealth of information being produced. In this seminar we will give an overview of the technology along with some bioinformatics solutions to solve the analysis problems posed by the system.
Case Study Two
9:30 Integrated Genomic Studies in Human Cancer
Levi A. Garraway, M.D., Ph.D., Instructor, Medical Oncology, Dana-Farber Cancer Institute
Systematic characterization of somatic genetic alterations may pave the way for increased deployment of rational therapeutics targeting molecularly-defined cancer subtypes. To this end, our group has applied high-density (100K) single nucleotide polymorphism
(SNP) arrays for genome-wide copy number and loss-of-heterozygosity analysis to a large collection of human tumors and cell lines. Integrating this genetic data with other large-scale data sets, such as gene expression or exon microarray data, has provided new insights into the genes targeted and the associated biology of molecularly-defined tumor subtypes.
10:00 Coffee Break, Poster and Exhibit Viewing
Case Study Three
10:30 Allele-Specific Copy Number Abnormalities Detected in Cancer Samples Using SNP Array Data
Thomas LaFramboise, Ph.D., Assistant Professor, Department of Genetics, Case Western Reserve University School of Medicine
We describe a generalization of the three applications - genotyping, LOH detection, and copy number inference - of SNP arrays. For example, we are able to assign sample SNPs a genotype, regardless of copy number. Thus, normal (diploid) regions are simply the usual AA, AB, or BB. However, a SNP in an amplified region may have genotype
AAAAB; a SNP in a heterozygously deleted region may have genotype B. We also present results and extensions of our approach.
Data Analysis
11:00 SNP500Cancer: A Public Resource for Sequence Validation, Assay Development, and Frequency Analysis for Genetic Variation in Candidate Genes
Dr. Meredith Yeager-Jeffery, Scientific Director, Core Genotyping Facility, NIH
The SNP500Cancer database provides sequence and genotype assay information for candidate SNPs useful in mapping complex diseases, such as cancer. The database is an integral component of the NCI Cancer Genome Anatomy Project
(http://cgap.nci.nih.gov). SNP500Cancer reports sequence analysis of anonymized control DNA samples (n = 102 Coriell samples representing four self-described ethnic groups: African/African-American, Caucasian, Hispanic and Pacific Rim). The website is searchable by gene, chromosome, gene ontology pathway, dbSNP ID and SNP500Cancer SNP ID. As of May 2006, the database includes over 1350 genes and almost 21,000
SNPs.
11:30 Panel Discussion SNP Genotyping - Are We Making Biological Sense?
12:00 Lunch on Your Own or (Technology Workshop Sponsorships Available)
Copy Number Analysis
1:30 Chair's Remarks
Featured Presentation
1:35
Clinical Interpretation of Genomic Aberrations Detected by Array CGH Genome Scanning of Patients with Congenital Abnormalities
Shelly Gunn, M.D., Ph.D., Instructor, Department of Pathology, University of Texas Health Science Center at San Antonio
Genome scanning by array CGH of prenatal and postnatal samples for the detection of congenital chromosomal abnormalities is becoming a routinely ordered test in several institutions. Advantages of the test include its sensitivity and specificity for many common and recurrent chromosomal rearrangements. However, the ability of array CGH to detect a wide variety of sometimes unexpected genomic abnormalities often results in situations where the clinical implications of the findings are misinterpreted or not understood. Genome scanning by array CGH is thus most useful clinically when patient data can be interpreted, understood and explained within a bigger biological picture.
Case Study One
2:05 High Resolution CGH of the Breast Cancer Genome
Paul Meltzer, M.D., Ph.D., Senior Investigator, Cancer Genetics Branch, NHGRI/NIH
Copy number aberrations occur in the vast majority of cancers. Oligonucleotide CGH technologies now permit the accurate determination of copy number at extremely high resolution. Analyzing this data and integrating it with other genomic data, particularly across multiple samples, presents new challenges which will be the subject of this talk.
Case Study Two
2:35
High-resolution Genomic Profiling with Infinium™ Whole Genome Genotyping (WGG)
BeadChips
Dr. Daniel A. Peiffer, Scientist, Molecular Biology Research, Illumina, Inc.
High-density SNP genotyping technology offers numerous advantages over array-CGH using spotted BAC clones or oligonucleotides. Simultaneous measurement of signal intensity variations and changes in allelic ratios makes it possible to detect both copy number changes and copy-neutral loss of heterozygosity events at a chromosomal resolution of a few tens of kilobases. Here we demonstrate the utility of multiple BeadChip formats, assaying up to 550K SNPs to detect chromosomal aberrations in various types of genomic DNA samples. These include homozygous and heterozygous deletions, copy-neutral LOH, and amplifications. We will present data demonstrating how WGG can detect various aberrations in a set of congenital samples previously characterized by BAC array-CGH, FISH, and karyotyping. Applications of utilizing WGG in analyzing large tumor sets will also be presented. Overall, analysis is facilitated by using a genome browser linked to plots of both log ratios of normalized intensities and allelic ratios. The two modes of quantitative analysis will be introduced; one for single samples and the other for paired normal and tumor samples from the same individual. The single-sample mode uses comparison to averaged genotype data from 120 reference samples.
3:05 Refreshment Break, Last Chance for Poster and Exhibit Viewing
Case Study Three
3:30 CGH Data Analysis for Clinical Applications
Mansoor S. Mohammed, Ph.D, President & Chief Operating Officer, CombiMatrix Molecular Diagnostics
Data Analysis
4:00 Combined Genetic-, Expression, and CGH Analysis Reveals New Insights into Complex Disease
Maryam Farzad, Ph.D., Informatics Application Scientist, IBS Informatics, Agilent Technologies
4:30 Panel Discussion Copy Number Analysis - Are We Making Biological Sense?
5:00 Close of Conference
