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Center for Nonlinear Studies |
Evolutionary events such as hitchhiking and severe bottleneck put their footprint on the dynamics of genetic diversity of a population by inducing homogenization respectively at a single locus and at the genome-wide scale, respectively. Such events have very similar signature at a single locus; as a result, multi-locus DNA sequence data should be used to gain more power for identifying and differentiating of the signatures of such events. The existing methods are based on simulation approaches which gives them flexibility to consider more complex evolutionary scenarios for population dynamics at genome level; however, such methods become computationally infeasible as the number of loci increases. For this problem, I developed an analytical statistical framework for identifying and differentiating the signatures of recent hitchhiking and severe bottleneck effects by using multi-locus DNA sequence data. I applied the framework to human DNA sequence data to explore Out of Africa hypothesis. I used also this framework to relate genetic diversity in HIV DNA sequences to the time of HIV seroconversion in HIV-1-infected patient.
Host: Kipton Barros, T-4 and CNLS