Inferring Continuous and Discrete Population Genetic Structure Across Space

Genetics: A Periodical Record of Investigations Bearing on Heredity and Variation

Graham M. Coop^2¹  Gideon S. Bradburd^1²  Peter L. Ralph^3³ 

[1] Center for Population Biology, Department of Evolution and Ecology, University of California, Davis, California 95616^2;Ecology, Evolutionary Biology, and Behavior Graduate Group, Department of Integrative Biology, Michigan State University, East Lansing, Michigan 48824^1;Institute of Ecology and Evolution, Departments of Mathematics and Biology, University of Oregon, Eugene, Oregon 97403^3

关键词: population genetics;    isolation by distance;    population structure;    model-based clustering;   

DOI  :  10.1534/genetics.118.301333

学科分类：医学（综合）

来源: Genetics Society of America

【 摘 要 】

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 clusters” problem in modeling population genetic variation, and remedies some of the overfitting to which nonspatial models are prone. The method produces useful descriptions of structure in genetic relatedness in situations where separated, geographically distributed populations interact, as after a range expansion or secondary contact. We demonstrate the utility of this approach using simulations and by applying it to empirical datasets of poplars and black bears in North America.

【 授权许可】

CC BY