A statistical test for detecting geographic subdivision.

TLDR

The power of the test to detect genetic differentiation in a selectively neutral Wright‑Fisher island model depends on sample size and the rates of migration, mutation, and recombination. The study introduces a statistical test that detects genetic differentiation among subpopulations using molecular variation from DNA sequences sampled across two or more localities. Statistical significance is assessed via Monte Carlo simulations. The test achieves substantial power with sample sizes of 50 when 4Nm < 10, and performs better with genes that recombine than with non‑recombining genes.

Abstract

A statistical test for detecting genetic differentiation of subpopulations is described that uses molecular variation in samples of DNA sequences from two or more localities. The statistical significance of the test is determined with Monte Carlo simulations. The power of the test to detect genetic differentiation in a selectively neutral Wright-Fisher island model depends on both sample size and the rates of migration, mutation, and recombination. It is found that the power of the test is substantial with samples of size 50, when 4Nm less than 10, where N is the subpopulation size and m is the fraction of migrants in each subpopulation each generation. More powerful tests are obtained with genes with recombination than with genes without recombination.