"Everything should be made as simple as possible, but not simpler." - Albert Einstein

Seminar Announcement

A New Model for Analysis of Spatio-Temporal Genetic Variation, with
Emphasis on Population Substructure

Geof H. Givens, Ph.D, Department of Statistics, Colorado State University

Monday, September 8, 2008

4:00 p.m. 223 Weber

ABSTRACT

We describe a general model for pairwise microsatellite allele matching probabilities.  The model can be used for analysis of population substructure, and is particularly focused on relating genetic correlation to measurable covariates.  The approach is
intended for cases where the existence and number of subpopulations is uncertain and a priori assignment of samples to hypothesized subpopulations is difficult.  Such a situation arises, for example, with western Arctic bowhead whales, where genetic samples are available only from a possibly mixed migratory assemblage.  We estimate genetic structure associated with spatial, temporal, or other variables that may confound the detection of population structure.  In the bowhead case, the model permits detection of genetic patterns associated with a temporally pulsed multi-population assemblage in the annual migration.  Hypothesis tests for population substructure and for covariate effects can be carried out using permutation methods.
Simulated and real examples illustrate the effectiveness and reliability of the approach and enable comparisons with other familiar approaches.  Results from the bowhead data and another example yield important findings for biologists and resource managers.