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Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum-likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user-friendly web application called divMigrate-online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs. [ABSTRACT FROM AUTHOR]

Currently, there is a demand for software to analyze polymorphism data such as microsatellite DNA and single nucleotide polymorphism with easily accessible interface in many fields of research. In this article, we would like to make an announcement of POPTREE2, a computer program package, that can perform evolutionary analyses of allele frequency data. The original version (POPTREE) was a command-line program that runs on the Command Prompt of Windows and Unix. In POPTREE2 genetic distances (measures of the extent of genetic differentiation between populations) for constructing phylogenetic trees, average heterozygosities (H) (a measure of genetic variation within populations) and GST (a measure of genetic differentiation of subdivided populations) are computed through a simple and intuitive Windows interface. It will facilitate statistical analyses of polymorphism data for researchers in many different fields. POPTREE2 is available at http://www.med.kagawa-u.ac.jp/∼genomelb/takezaki/poptree2/index.html. [ABSTRACT FROM PUBLISHER]

POPTREE software, including the command line (POPTREE) and the Windows (POPTREE2) versions, is available to perform evolutionary analyses of allele frequency data, computing distance measures for constructing population trees and average heterozygosity (H) (measure of genetic diversity within populations) and GST (measure of genetic differentiation among subdivided populations). We have now developed a web version POPTREEW (http://www.med.kagawa-u.ac.jp/∼genomelb/takezaki/poptreew/) to provide cross-platform access to all POPTREE functions including interactive tree editing. Furthermore, new POPTREE software (POPTREE, POPTREE2, and POPTREEW) computes standardized GST and Jost’s D, which may be appropriate for data with high variability, and accepts genotype data in GENEPOP format as an input. [ABSTRACT FROM PUBLISHER]