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Measuring population differentiation using G ST or D ? A simulation study with microsatellite DNA markers under a finite island model and nonequilibrium conditions
Author(s) -
LENG LIANG,
ZHANG DEXING
Publication year - 2011
Publication title -
molecular ecology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.619
H-Index - 225
eISSN - 1365-294X
pISSN - 0962-1083
DOI - 10.1111/j.1365-294x.2011.05108.x
Subject(s) - biology , microsatellite , population , dna , non equilibrium thermodynamics , evolutionary biology , genetics , astrophysics , gene , physics , thermodynamics , allele , demography , sociology
The genetic differentiation of populations is a key parameter in population genetic investigations. Wright’s F ST (and its relatives such as G ST ) has been a standard measure of differentiation. However, the deficiencies of these indexes have been increasingly realized in recent years, leading to some new measures being proposed, such as Jost’s D ( Molecular Ecology , 2008; 17 , 4015). The existence of these new metrics has stimulated considerable debate and induced some confusion on which statistics should be used for estimating population differentiation. Here, we report a simulation study with neutral microsatellite DNA loci under a finite island model to compare the performance of G ST and D , particularly under nonequilibrium conditions. Our results suggest that there exist fundamental differences between the two statistics, and neither G ST nor D operates satisfactorily in all situations for quantifying differentiation. D is very sensitive to mutation models but G ST noticeably less so, which limits D ’s utility in population parameter estimation and comparisons across genetic markers. Also, the initial heterozygosity of the starting populations has some important effects on both the individual behaviours of G ST and D and their relative behaviours in early differentiation, and this effect is much greater for D than G ST . In the early stages of differentiation, when initial heterozygosity is relatively low (<0.5, if the number of subpopulations is large), G ST increases faster than D ; the opposite is true when initial heterozygosity is high. Therefore, the state of the ancestral population appears to have some lasting impacts on population differentiation. In general, G ST can measure differentiation fairly well when heterozygosity is low whatever the causes; however, when heterozygosity is high (e.g. as a result of either high mutation rate or high initial heterozygosity) and gene flow is moderate to strong, G ST fails to measure differentiation. Interestingly, when population size is not very small (e.g. N ≥ 1000), G ST measures differentiation quite linearly with time over a long duration when gene flow is absent or very weak even if mutation rate is not low (e.g. μ = 0.001). In contrast, D, as a differentiation measure, performs rather robustly in all these situations. In practice, both indexes should be calculated and the relative levels of heterozygosities (especially H S ) and gene flow taken into account. We suggest that a comparison of the two indexes can generate useful insights into the evolutionary processes that influence population differentiation.