Methods in Genetics and Clinical Interpretation Analysis of Complex Disease Association and Linkage Studies Using the University of California Santa Cruz Genome Browser

The sequencing of the human genome, the identification of common single-nucleotide polymorphisms (SNPs) and haplotype blocks, and advances in microarray technology have enabled the study of complex diseases at a level of detail not previously imaginable. These have aided in the design and analyses of association and linkage studies of many complex diseases including cardiovascular disease. Recent technological advances have enabled the undertaking of large-scale genome-wide association studies (GWAS) that can assay hundreds of thousands of polymorphic sites on hundreds to thousands of individuals to find genomic regions associated with disease. Although results from these experiments enable the identification of smaller regions of association compared with previous studies, as with all linkage and association studies, there is the need for the further investigation of regions of interest for the causal genes or variants. The purpose of this review is to present a detailed demonstration as to how publicly available resources can be used to easily guide more detailed research into genomic regions of interest identified in linkage and association study data. Large-scale projects, such as the Human Genome Sequencing project,1,2 have generated large volumes and varieties of annotated genomic data necessitating the development of Internet-based tools to organize and make practically available these public data. One important tool in human disease research is the web-based graphical genome browsers that use the human genome sequence as the framework on which to organize genomic annotations, providing various ways for researchers to view and extract important information. Currently, there are 3 human genome browsers that have been developed for public use: (1) the National Center for Biotechnology Information (NCBI) Map Viewer3; (2) the University of California Santa Cruz (UCSC) Genome Browser4; and (3) the European Bioinformatics Institute’s Ensembl system.5 Although these genome browsers share common features and genomic information, each being built on top of the same reference genome sequence, they each have a different look and feel and provide unique capabilities.6 In particular, the UCSC Genome Browser has a tool called Genome Graphs that is especially suited for linkage and association study analyses. The following sections will demonstrate the capabilities of this tool focusing on a recently published GWAS result from the Wellcome Trust Case Control Consortium. As with all studies of this type, regions of disease association were identified encompassing large numbers of genes that are candidates for further studies. To prioritize future research, genes in each region need to be investigated for a possible role in a particular disease. The following step-by-step instructions demonstrate a straightforward and efficient method using the Genome Graphs tool within the UCSC Genome Browser that can help to prioritize a small number of meaningful candidates from a large-scale association study. The Figure provides an illustrated outline of this method, with a more detailed description of each step below (note that each of the panels in the Figure is also available as a larger figure in the Data Supplement).