Assessment of genetic differentiation of populations by analysis of molecular variance (analytical review)

Abstract

Different approaches to using the analysis of molecular variance (AMOVA) to assess the genetic differentiation of populations have been compared in the research. Data on 11 microsatellite loci of 84 bulls of seven breeds were used. The results were compared for three options of the AMOVA module of the GenAlEx 6.502 program: the allele distance matrix (calculated FST(W&C)(=θ) statistics – variant AMOVA1); the genotype distance matrix (ΦPT– AMOVA2); and the allele size difference matrix (RST– AMOVA3). Similar summary estimates of the genetic differentiation of breeds were obtained: FST(W&C)= 0.108, ΦPT= 0.115, RST= 0.110 (all with pperm≤ 0.001). Between the estimates of FST(W&C)and ΦPTfor each locus, the correlation coefficient was 0.99 (pvalue<0.0001); no statistically significant correlations with RSTwere found. A high correlation of FST(W&C)and ΦPTwith the estimates of differentiation according to Nei’s (0.96) was found. Programs other than GenAlEx (Arlequin v.3.5, GenePop v.4.7.3, RST22) gave similar AMOVA estimates. The negative linear dependence of FST(W&C)and ΦPTon the level of the average heterozygosity of the breed samples was established (R2= 0.6, rS= -0.75 for pvalue < 0.02) and the absence of such dependence for RST(R2= 0.04, rS= -0.23 for pvalue= 0.47). The standardization of the FST(W&C)and ΦPTestimates according to Hedrick’s eliminated this dependence and raised the initial estimates to 0.35 and 0.37, respectively. The latter were comparable to the estimates obtained by the Nei-Hedrick’s (0.364-0.375), Jost’s (0.292), and Morisit-Horn’s (0.308) methods. The Mantel correlations between the matrices of paired genetic distances (GD) calculated by different measures were >0.9 in most cases. The projections of the GD matrices in the principal coordinate analysis (PCoA) on the 2D plane were generally similar. The PCoA identified a cluster of Holstein «ecotypes», a cluster of «Red» breeds, and a branch of the Jersey breed. In the two-factor AMOVA of data on clusters (as two «regions»), the interregional GD was 0.357; the differentiation of breeds within the «regions» did not exceed 0.027. Modeling the association of breeds with close to zero GD resulted in an increase in the number of alleles per locus in the «new» breeds by 29 %, and an increase in the combined estimate of genetic differentiation by 29-46 %. The results obtained can be used in the development of measures for the conservation of endangered breeds.