Wednesday December 4, 2002
Jean-Marc Lalouel, M.D., D.Sc.
Department of Human Genetics, University of Utah
Abstract: A central issue in genetics is to measure the degree of genetic determination of a trait and to identify underlying sources of its genetic variation. Mathematical methods in genetics have developed along two contrasted conceptual frameworks: Mendelian inheritance of discrete traits, and polygenic inheritance of continuous traits. The former is based on simple binomial proportions, while the latter develops around the Normal distribution. Mendelian genetics proved most powerful for the analysis of rare inherited disorders with simple clinical manifestation, whereas quantitative genetics was most successful in its applications to animal and plant breeding.
The advent of computers removed the practical necessity of this dichotomy. Parallel advances of molecular technologies have introduced new investigative tools that converted genetic modeling from a largely theoretical field into a practical method to identify genes underlying individual variation in health and disease. The first revolution saw the combination of genetic markers and pedigree analysis as a rational approach to genetic discovery, affording the identification of genes and mutations accounting for a host of inherited diseases. The second revolution is in progress and results from the full determination of the entire sequence of complex organisms and the ability to examine the levels of expression of all genes in cells, tissues, organs or whole organisms. The massive investigative power afforded by large-scale gene expression profiling will enable comprehensive analyses of entire biological systems and gene networks. Such breakthrough will require an integration of both mathematics and biology. We will present an overview of these two revolutions, using actual research in progress and pending proposals that should foster interactions between these two academic fields.
For more information contact J. Keener, 1-6089