Аграрная наука Евро-Северо-Востока (Apr 2020)

Comparison of methods for evaluating genetic differentiation of populations by microsatellite markers

  • V. M. Kuznetsov

DOI
https://doi.org/10.30766/2072-9081.2020.21.2.169-182
Journal volume & issue
Vol. 21, no. 2
pp. 169 – 182

Abstract

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Comparative studies of eight methods for evaluation of genetic differences by microsatellite (STR) markers (11 loci) DNA were carried out using the example of seven breed samples (N = 84) of dairy cattle. The range of indicators of genetic diversity of samples was as follows: the number of alleles per locus 3.5-6.2, the number of effective alleles per locus – 2.4-4.3, the Shannon index – 0.95-1.56, the observed and expected heterozygosity – 0.56-0.97 and 0.53-0.75. Evaluation summary of genetic differentiation by group A methods (FST, GST, and GST(NEI)) were 13.4, 10.3, and 11.8% (pperm < 0.001); the differences between the estimates were statistically insignificant. Estimates by group B methods (G'ST(HED), G''ST(HED), DEST) were 36.4, 37.5 and 29.2% (pperm < 0.001); differences between the estimates were also statistically insignificant. Estimates obtained by group B methods were statistically significantly higher than those obtained by group A methods by almost 3 times. Methods of groups A, B, and C (GDN and uGDN) were used to calculate paired genetic distances in the samples. Despite significant dif-ferences in estimates, the Mantel test showed a high degree of correspondence of the genetic distance matrices (RM≥0.97; pperm < 0.001), which was manifested in the projections of genetic relations of breed samples on plane 1 and 2 of the principal coordinates. The first two principal coordinates explained 97-99% of STR variation in the genetic distance matrices. It can be assumed that when assessing the actual differentiation of populations by STR-markers, the methods of group B should be used and among them the statistics of DEST as independent of the level of mean within-subpopulation heterozygosity. In the study of spatial ordination of gene pools of populations, in all probability, it is reasonably to use any method.

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