Animal Molecular Breeding, 2025, Vol.15, No.2, 49-59 http://animalscipublisher.com/index.php/amb 50 2 Genomic Selection in Goat Breeding 2.1 Concept and mechanism of genomic selection (GS) Lei et al. (2024) demonstrated that GS uses numerous markers across the entire genome and combines the expression data of animals to estimate their genetic breeding values. The 52K SNP chips specially designed for goats have also been widely used with the development of next-generation sequencing technology, and they can provide a lot of useful genetic information. Rupp et al. (2016) and Zhang et al. (2024) found that GS is more accurate and efficient than traditional methods because it takes into account both phenotypic data and genetic relationships among animals. GS is particularly practical for some goat populations with relatively small breeding scales and immature systems. 2.2 Applications in goat traits of interest Genomic selection (GS) has been used to improve many important traits of goats, such as milk production, wool quality and meat yield. Scientists used SNP data from the whole genome to identify many DNA regions and genes related to these traits. These traits include fur color, adaptation to high altitudes, growth rate, fertility, milk protein content, etc. (Wang et al., 2016; Brito et al., 2017; Guo et al., 2018; Yan et al., 2022). For example, the KITLGand ASIP genes are related to fur color, while the EPAS1 gene is related to the ability to adapt to high altitudes. GS technology has also helped identify the “selection imprints” related to milk production and climate adaptation, which is very helpful for directed breeding (Figure 1) (Wang et al., 2016; Guo et al., 2018; Ghanatsaman et al., 2023). Some simulation studies have also found that if medium-density SNP chips, such as 45K chips, are used in combination with a reference population of approximately 1 500 goats, the genomic breeding values (GEBV) of traits such as fiber thickness and body weight can be predicted relatively accurately (Yan et al., 2022). Figure 1 A: putative sweep area (chr. 10, 55.02~55.04 Mb) is approved by π test (The figure was drawn using VCFtools commands (version 0.1.17) and R software environment). B: The patterns of haplotype distribution for VPS13C loci in all 140 goats. The existence of homozygosity and heterozygosity is colored in brown and intermediate brown, respectively. The absence of the derived allele is shown in white. Missing- genotyped regions or individuals are shown in gray (The figure was drawn using Beagle (version 4.0), R software environment and python scripts (our in-home script was used)) (Adopted from Ghanatsaman et al., 2023)
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