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G ST ′ , Jost's D , and F ST are similarly constrained by allele frequencies: A mathematical, simulation, and empirical study
Author(s) -
Alcala Nicolas,
Rosenberg Noah A.
Publication year - 2019
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/mec.15000
Subject(s) - biology , allele frequency , allele , coalescent theory , loss of heterozygosity , statistics , genetics , range (aeronautics) , function (biology) , independence (probability theory) , evolutionary biology , gene , mathematics , phylogenetic tree , materials science , composite material
Statistics G ST ′ and Jost's D have been proposed for replacing F ST as measures of genetic differentiation. A principal argument in favour of these statistics is the independence of their maximal values with respect to the subpopulation heterozygosity H S , a property not shared by F ST . Nevertheless, it has been unclear if these alternative differentiation measures are constrained by other aspects of the allele frequencies. Here, for biallelic markers, we study the mathematical properties of the maximal values of G ST ′ and D , comparing them to those of F ST . We show that G ST ′ and D exhibit the same peculiar frequency‐dependence phenomena as F ST , including a maximal value as a function of the frequency of the most frequent allele that lies well below one. Although the functions describing G ST ′ , D , and F ST in terms of the frequency of the most frequent allele are different, the allele frequencies that maximize them are identical. Moreover, we show using coalescent simulations that when taking into account the specific maximal values of the three statistics, their behaviours become similar across a large range of migration rates. We use our results to explain two empirical patterns: the similar values of the three statistics among North American wolves, and the low D values compared to G ST ′ and F ST in Atlantic salmon. The results suggest that the three statistics are often predictably similar, so that they can make quite similar contributions to data analysis. When they are not similar, the difference can be understood in relation to features of genetic diversity.