Bio | Virginia State University

Education

Research in the Harris lab utilizes bioinformatics and comparative genomics strategies to search for the genetic factors underlying susceptibility to inherited diseases such as obesity, non-insulin dependent diabetes mellitus (NIDDM, aka Type 2 Diabetes), and parasite resistance and improved production traits in agricultural species. These are examples of multifactorial traits that are often the result of a combined influence of multiple genes and their interaction with the environment. These factors make conclusive identification of causative genes difficult. My research uses an integrative systems approach to taking on this problem. There is a rapidly increasing wealth of genomic information available online; including annotated genomic information for many species and experimental data including QTL, GWAS and model organism studies. We perform metagenomic analyses by reviewing the accumulated data for a disease or trait at a particular genomic locus and using state-of-the-art bioinformatic tools and resources to identify the most likely genetic candidates for future study.

Non-insulin dependent diabetes mellitus (Type 2 Diabetes) is one of the most significant chronic human diseases, affecting over 20 million people in the United States (7% of the population). NIDDM is associated with obesity and characterized primarily by insulin resistance and impaired insulin production. In the Harris lab we gather evidence from multiple sources to search for genetic factors responsible for susceptibility to this disease. Fig 1 shows a comparative genomic map with human (Hs) chromosome 01 and syntenic regions (highlighted with black lines) in mouse (Mm) and rat (Rn). Mapping out areas of synteny between human and animal model species allows us to narrow the otherwise enormous amounts of data to be analyzed. We can then add genetic and physiological data from the animal studies to the human studies and look for common elements. Potential candidate genes for the disease are then analyzed for functional significance using a mouse model and methodology uniquely developed here at Virginia State University.

As one of the initial members of the International Goat Genomics Consortium (founded by fellow VSU colleague Dr. Brian Sayre), we work with researchers around the world to characterize, annotate, and store the goat genome. This effort involves developing databases and bioinformatic tools to store and analyze the massive amounts of genomic data being generated around the world for several populations of the goat species. The Goat Research Improvement Project (GRIP) is a collection of ongoing projects to assist in this effort.

Infections resulting from gastrointestinal (GI) parasites are a primary limitation to livestock production for ruminants such as goats. As nematode resistance to anthelmintics broadens, discovering factors that confer genetic resistance becomes increasingly important. In the Harris lab we use a mouse model as a framework for comparative genomics analysis to find genetic factors associated with phenotypes that are resistant to GI parasite infections. We use methods including a cross-validation analysis to prioritize the genes found in the regions as potential candidate genes. Results are compared with gene expression studies in mouse, cow and sheep to provide further evidence for genes that are upregulated in resistant animals. Current results confirm that GI parasite response is multifactorial, potentially involving many gene-gene and gene-environment interactions, and demonstrate QTL studies as an integral part of a comprehensive systems biology analysis to identify candidate causative genes for complex phenotypes.

Please contact me if you're interested in doing research in my lab. We have opportunities available from the freshman to the graduate student level. This is an exciting time to be doing bioinformatics research at Virginia State University!

Twigger SN, Shimoyama N, et al 2007 The Rat Genome Database, update 2007--easing the path from disease to data and back again. Nucleic Acids Res. Jan;35(Database issue):D658-62
Twigger SN, Harris G, et al 2005 Tools and Strategies for Physiological Genomics - The Rat Genome Database. Physiol Genomics. 2005 Oct 17;23(2):246-56.
de la Cruz N, Harris G, et al 2005 The Rat Genome Database (RGD): developments towards a phenome database. Nucleic Acids Res. 2005 Jan 1;33(Database issue):D485-91.
Harris GC and Levine JE 2003 An acceleration of the GnRH pulse generator is correlated with initiation of puberty in male rats. Endocrinology 144:163-171.

2007 Graduate Student Seminar, Virginia State University, Petersburg, VA. Seminar title: "Bioinformatics: Opportunities for graduate research at VSU"

2006 Seminar Series, University of Richmond, Richmond, VA. Seminar title: "Comparative Genomics: Finding genes involved in Type II Diabetes Mellitus"
2006 Invited Lecture, Biology Club, Virginia State University, Petersburg, VA. Seminar title: "Comparative Genomics: Finding genes involved in Type II Diabetes Mellitus"
2004 34 ^th Meeting of the Society for Neuroscience. Seminar title: "Rat Genome Database Free Workshop