Genetic data often exhibit patterns broadly consistent with 'isolation by distance'-a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.
%0 Journal Article
%1 petkova2016visualizing
%A Petkova, D
%A Novembre, J
%A Stephens, M
%D 2016
%J Nat Genet
%K effective_resistance methods resistance_distance spatial_coalescent
%N 1
%P 94-100
%R 10.1038/ng.3464
%T Visualizing spatial population structure with estimated effective migration surfaces
%U https://www.ncbi.nlm.nih.gov/pubmed/26642242
%V 48
%X Genetic data often exhibit patterns broadly consistent with 'isolation by distance'-a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.
@article{petkova2016visualizing,
abstract = {Genetic data often exhibit patterns broadly consistent with 'isolation by distance'-a phenomenon where genetic similarity decays with geographic distance. In a heterogeneous habitat, this may occur more quickly in some regions than in others: for example, barriers to gene flow can accelerate differentiation between neighboring groups. We use the concept of 'effective migration' to model the relationship between genetics and geography. In this paradigm, effective migration is low in regions where genetic similarity decays quickly. We present a method to visualize variation in effective migration across a habitat from geographically indexed genetic data. Our approach uses a population genetic model to relate effective migration rates to expected genetic dissimilarities. We illustrate its potential and limitations using simulations and data from elephant, human and Arabidopsis thaliana populations. The resulting visualizations highlight important spatial features of population structure that are difficult to discern using existing methods for summarizing genetic variation.},
added-at = {2016-11-04T07:24:25.000+0100},
author = {Petkova, D and Novembre, J and Stephens, M},
biburl = {https://www.bibsonomy.org/bibtex/204a084a9d4f84c3af1a19c2a14a3c155/peter.ralph},
doi = {10.1038/ng.3464},
interhash = {5f41acb94f516f1a060860960b0828d5},
intrahash = {04a084a9d4f84c3af1a19c2a14a3c155},
journal = {Nat Genet},
keywords = {effective_resistance methods resistance_distance spatial_coalescent},
month = jan,
number = 1,
pages = {94-100},
pmid = {26642242},
timestamp = {2016-11-04T07:24:25.000+0100},
title = {Visualizing spatial population structure with estimated effective migration surfaces},
url = {https://www.ncbi.nlm.nih.gov/pubmed/26642242},
volume = 48,
year = 2016
}