Working Group

Measuring evolutionary change in modern human populations using cohort data

PI(s): Diddahally Govindaraju (Boston University)
Andrew Clark (Cornell University)
Trudy Mackay (North Carolina State Univerisity)
Stephen Stearns (Yale University)
Start Date: 1-Sep-2007
End Date: 31-Aug-2009
Keywords: genomics, disease, human evolution, population genetics, quantitative genetics

This working group will assemble a team of investigators from population, quantitative, demographic and human genetics, and evolutionary biology to analyze the three generation longitudinal Framingham Heart Study cohort data to document microevolutionary changes in a contemporary human population. The team will utilize the rich and diverse morphological, physiological and genomic data collected for nearly sixty years to primarily understand the manifestation of cardiovascular disease in a healthy white North American population. The investigators will use analytical approaches proven in evolutionary biology and if necessary develop novel approaches for the purpose. This concerted effort will yield an evolutionary framework to understand the distribution of human genetic variation and the role of evolution in human health and disease. The specific aims of this working group are to: 1) measure microevolutionary changes at the phenotype level in a white North American human population, using evolutionary quantitative genetic models, and 2) apply a battery of population genetic tests to identify regions of the genome that deviate from normal segregation patterns or show transmission distortions, utilizing the pedigree, microsatellite and single nucleotide polymorphism data. Analysis of phenotypic data will provide insights on the modular relationship among morphological and physiological traits, reaction norms, selection gradients, levels and strength of natural selection among individuals and families, across age groups and generations. Transmission distortions that may reflect evolutionary change at the molecular level may also have phenotypic and clinical consequences. The results will enrich both evolutionary biology and human health.

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