Fig 1.
Genetic structure of the Brazilian Gir population.
(a) Eigenvalues of principal component analysis (PCA). (b) PCA scatter-plots of the first two principal components (PC) showing clearly separation between beef population (green color) and dairy population (red-yellow colors). (c) Inference of the number of clusters in Gir cattle based on K-means algorithm. (d) Plots of the first two discriminant functions of discriminant analysis of PC algorithm.
Fig 2.
Average heterozygosity per chromosome in two populations.
Light grey = beef cattle; dark grey = dairy cattle.
Fig 3.
Genomic distribution of Fst values.
SNPs were plotted relative to their physical positions within each autosome. The cutoff to call SNP outliers was defined as three standard deviations above the mean for each autosome. Red dots are SNPs with Fst beyond the cutoff value.
Fig 4.
Scatter plots for population-specific allele frequency (dairy x beef).
The data were displayed as a collection of points; each point represents an SNP having the allele frequency for the dairy population determining the position on the vertical axis and the allele frequency for the beef population determining the position on the horizontal axis. It reveals a positive linear relationship between allele frequencies of two populations.
Fig 5.
Genome-wide distribution of |iHS| values for Gir cattle.
Upper = beef population; bottom = dairy population.
Table 1.
Top ten significant iHS genomic regions harboring signatures of selection in beef and dairy Gir cattle.
Table 2.
Top ten significant XP-EHH genomic regions harboring signatures of selection in beef and dairy Gir cattle.
Table 3.
Gene Ontology terms and KEGG pathways enrichment analysis.