Sep 15, 2017

Inferring Continuous and Discrete Population Genetic Structure Across Space

BioRxiv : the Preprint Server for Biology
Gideon S BradburdPeter L Ralph

Abstract

A classic problem in population genetics is the characterization of discrete population structure in the presence of continuous patterns of genetic differentiation. Especially when sampling is discontinuous, the use of clustering or assignment methods may incorrectly ascribe differentiation due to continuous processes (e.g., geographic isolation by distance) to discrete processes, such as geographic, ecological, or reproductive barriers between populations. This reflects a shortcoming of current methods for inferring and visualizing population structure when applied to genetic data deriving from geographically distributed populations. Here, we present a statistical framework for the simultaneous inference of continuous and discrete patterns of population structure. The method estimates ancestry proportions for each sample from a set of two-dimensional population layers, and, within each layer, estimates a rate at which relatedness decays with distance. This thereby explicitly addresses the “clines versus cluster” problem in modeling population genetic variation. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a r...Continue Reading

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Mentioned in this Paper

Genetic Drift
2-Dimensional
Ursus americanus
Anatomical Space Structure
Cell Differentiation Process
Cell Growth
Populus
Description
Structure
Simulation

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