CSB Seminar - Dr. Michael Province

Please join us for the upcoming CSB Seminar, Monday, May 14, 2018 at 11 a.m. ‐ noon in ND11.218. A meet-the-speaker lunch will follow each seminar in the ND11 atrium.

Michael Province, Ph.D.
Washington University Medical School in St. Louis
Monday, May 14, 11 a.m.

Searching for the Mountains of the Moon: Challenges in Complex Trait Genetics

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My research focuses on the derivation and application of new computational statistical genetics models to dissect the genetic nature of complex traits, through various paradigms: association, gene expression, linkage. Right now, a key issue in complex trait genetics is how to efficiently find the genetic causes of human traits. We can measure the genome with greater precision and depth every day on larger numbers of subjects. Sequencing costs continue to plummet and the $1,000 genome is right around the corner, but what will all of that massive data mean? For any given trait, by far, most of the genome will be noise and should be ignored. Genome-Wide Association Scan (GWAS) results are showing us that there are few common variants with large effects for complex traits, which means that the "missing heritability" for most traits is diffused among large numbers of small effect common variants and/or rare ones. This presents a statistical challenge to find many small population level signals in a vast sea of noise. My lab has been working on computational methods to deal with this general systems biology problem, by leveraging multiple sources of information, combining statistical (association, linkage) as well as biological (various bioinformatic databases) sources to improve our ability to identify and replicate signal variants. We are currently focusing our efforts on heart disease and healthy aging genetics by serving as the Data Coordinating Center for several large, NIH sponsored multicenter family and genetics studies of complex traits, the NHLBI Family Heart Study (heart disease genetics), the Genetics Of Lipid Lower Drugs and Diet Network (GOLDN) study (lipid pharmacogenetics), and the Long Life Family Study (longevity genetics).