The Assessing the genetic differentiation of Holstein cattle herds in the Leningrad region using Fst statistics

Смарагдов, М. Г.; Kudinov, Andrei A.; Uimari, Pekka

doi:10.23986/afsci.69777

Cited by 8 publications

(10 citation statements)

References 19 publications

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“…The position of forth herd is outstanding on these images. The mean pairwise F st value with other 12 herds for herd 4 is also the greatest 0.0087 compared with those of other 12 herds (0.0038-0.0063) [25]. We assume that this result is caused by the heavy use of bulls from the Netherlands between 2000 and 2007 years in herd 4, while bulls imported mainly from the USA and Canada were more recently used in the other 12 herds.…”

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 84%

“…3. These herds have minimal mean pairwise F stvalues with other 12 herds 0.0038 and 0.0039 [25]. The herd 3 forms many insignificant at P ≤ 0.05 pairwise herds combinations with other herds revealed by PCA 1-20 (Table 5) and at P ≤ 1.26e-12 by PC 1-100 (Table 6).…”

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 89%

“…This indicates a relatively homogeneous genetic structure of the herds due to a big enough gene flow between herds as result of artificial selection. For example the proportions of the cows born from the same bulls in 78 pair of the herds was up to 32% [25]. In fundamental analysis of genetic diversity with PCA, Patterson et al [3] discovered a threshold (as measured, for example, by F st ) below which the population structure was essentially undetectable.…”

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 99%

“…We propose this is a consequence of genetic relatedness of the cows in the herds. Really, the cows from 13 herds had considerable genetic relatedness owing to use high proportion up to 32% the same sires in the herds [25].…”

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 99%

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Assessing the power of principal components and wright’s fixation index analyzes applied to reveal the genome-wide genetic differences between herds of Holstein cows

Смарагдов

Kudinov

2020

BMC Genet

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Background Due to the advent of SNP array technology, a genome-wide analysis of genetic differences between populations and breeds has become possible at a previously unattainable level. The Wright’s fixation index (Fst) and the principal component analysis (PCA) are widely used methods in animal genetics studies. In paper we compared the power of these methods, their complementing each other and which of them is the most powerful. Results Comparative analysis of the power Principal Components Analysis (PCA) and Fst were carried out to reveal genetic differences between herds of Holsteinized cows. Totally, 803 BovineSNP50 genotypes of cows from 13 herds were used in current study. Obtained Fst values were in the range of 0.002–0.012 (mean 0.0049) while for rare SNPs with MAF 0.0001–0.005 they were even smaller in the range of 0.001–0.01 (mean 0.0027). Genetic relatedness of the cows in the herds was the cause of such small Fst values. The contribution of rare alleles with MAF 0.0001–0.01 to the Fst values was much less than common alleles and this effect depends on linkage disequilibrium (LD). Despite of substantial change in the MAF spectrum and the number of SNPs we observed small effect size of LD - based pruning on Fst data. PCA analysis confirmed the mutual admixture and small genetic difference between herds. Moreover, PCA analysis of the herds based on the visualization the results of a single eigenvector cannot be used to significantly differentiate herds. Only summed eigenvectors should be used to realize full power of PCA to differentiate small between herds genetic difference. Finally, we presented evidences that the significance of Fst data far exceeds the significance of PCA data when these methods are used to reveal genetic differences between herds. Conclusions LD - based pruning had a small effect on findings of Fst and PCA analyzes. Therefore, for weakly structured populations the LD - based pruning is not effective. In addition, our results show that the significance of genetic differences between herds obtained by Fst analysis exceeds the values of PCA. Proposed, to differentiate herds or low structured populations we recommend primarily using the Fst approach and only then PCA.

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Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 84%

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 89%

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 99%

Section: Comparing the Power Of F St And Pca Analyzesmentioning

confidence: 99%

See 2 more Smart Citations

Assessing the power of principal components and wright’s fixation index analyzes applied to reveal the genome-wide genetic differences between herds of Holstein cows

Смарагдов

Kudinov

2020

BMC Genet

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show abstract

“…Maintaining genetic diversity and minimizing the inbreeding are important aims of all successful beef cattle breeding programs (Hall & Brandley, 1995). The single nucleotide polymorphism (SNP) is a modern tool to estimate genetic diversity (Smaragdov et al, 2018). The F-statistics (F IS , F IT and F ST ) are usually estimated for the analysis of population structure (Wright, 1965).…”

Section: Introductionmentioning

confidence: 99%