Differentiation measures for conservation genetics
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We compare the two main classes of measures of population structure in genetics: (1) fixation measures such as FST, GST, and θ, and (2) allelic differentiation measures such as Jost’s D and entropy differentiation. These two groups of measures quantify complementary aspects of population structure, which have no necessary relationship with each other. We focus especially on empirical aspects of population structure relevant to conservation analyses. At the empirical level, the first set of measures quantify nearness to fixation, while the second set of measures quantify relative degree of allelic differentiation. The two sets of measures do not compete with each other. Fixation measures are often misinterpreted as measures of allelic differentiation in conservation applications; we give examples and theoretical explanations showing why this interpretation can mislead. This misinterpretation has led to the mistaken belief that the absolute number of migrants determines allelic differentiation between demes when mutation rate is low; we show that in the finite island model the absolute number of migrants determines nearness to fixation, not allelic differentiation. We show that a different quantity, the factor which controls Jost’s D, is a good predictor of the evolution of the actual genetic divergence between demes at equilibrium in this model. We also show that when conservation decisions require judgements about differences in genetic composition between demes, allelic differentiation measures should be used instead of fixation measures. Allelic differentiation of fast-mutating markers can be used to rank pairs or sets of demes according to their differentiation, but the allelic differentiation at coding loci of interest should be directly measured in order to judge its actual magnitude at these loci.
Jost , L , Archer , F , Flanagan , S , Gaggiotti , O , Hoban , S & Latch , E 2018 , ' Differentiation measures for conservation genetics ' Evolutionary Applications , vol In press . DOI: 10.1111/eva.12590
© 2018 The Authors. Evolutionary Applications published by John Wiley & Sons Ltd. This is an open access article under the terms of the Creative Commons Attribution License, which permits use, distribution and reproduction in any medium, provided the original work is properly cited.
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