Original Article
Heredity (2009) 102, 506–513; doi:10.1038/hdy.2008.136; published online 28 January 2009
How well do evolutionary trees describe genetic relationships among populations?
S T Kalinowski1
1Department of Ecology, Montana State University, Lewis Hall, Bozeman, MT, USA
Correspondence: Dr ST Kalinowski, Department of Ecology, Montana State University, 310 Lewis Hall, Bozeman, MT 59717, USA. E-mail: skalinowski@montana.edu
Received 2 September 2008; Revised 10 November 2008; Accepted 23 December 2008; Published online 28 January 2009.
Abstract
Bifurcating evolutionary trees are commonly used to describe genetic relationships between populations, but may not be appropriate for populations that did not evolve in a hierarchical manner. The degree to which bifurcating trees distort genetic relationships between populations can be quantified with R2, the proportion the variation in a matrix of genetic distances between populations that is explained by a tree. Computer simulations were used to measure how well the unweighted pair group method with arithmetic mean (UPGMA) and neighbor-joining (NJ) trees depicted population structure for three evolutionary models: a hierarchical model of population fragmentation, a linear stepping-stone model of gene flow and a two-dimensional stepping-stone model of gene flow. These simulations showed that the UPGMA did an excellent job of describing population structure when populations had a bifurcating history of fragmentation, but severely distorted genetic relationships for the linear and two-dimensional stepping-stone models. The NJ algorithm worked well in a broader range of evolutionary histories, including the linear stepping-stone model. A computer program for performing the calculations described in this study is available for download at www.montana.edu/kalinowski.
Keywords:
tree, population, UPGMA, neighbor joining, cophenetic correlation
MORE ARTICLES LIKE THIS
These links to content published by NPG are automatically generated
REVIEWS
Phylogeny estimation: traditional and Bayesian approaches
Nature Reviews Genetics Review (01 Apr 2003)
RESEARCH
Heredity Original Article
Heredity Original Article
Heredity Original Article
Heredity Original Article

