Genomic Selection and Genome-Wide Association Analysis (GWAS) Technology in Small Ruminant Breeding Globally
DOI:
https://doi.org/10.64614/vzs-27Keywords:
Genetic progress, genomic selection, GWAS, small ruminant breeding, sheep and goats, ohmic techniqueAbstract
In small ruminant breeding, selection programs were long based on phenotypic data and pedigree-based models. However, these methods led to slow genetic progress, especially for quantitative traits. Rapid advancements in molecular technologies—particularly genomic selection (GS) and genome-wide association studies (GWAS)—have introduced a fundamentally new perspective to livestock breeding, as in all other biological fields. GS enables the estimation of genomic breeding values (GEBVs) using high-density single nucleotide polymorphism (SNP) chips, thereby shortening the generation interval and allowing the early identification of animals with superior economic traits. GWAS technology not only identifies genomic regions associated with economically important performance traits and disease resistance, but also reveals the genetic basis of a wide range of characteristics, including environmental tolerance, behavioral traits, adaptation ability, and the quality of relevant production traits. In the early stages of integrating genomic technologies into breeding programs, classical single-locus GWAS methods were primarily used; however, in recent years, multi-locus GWAS (ML-GWAS) approaches have enabled the simultaneous analysis of multiple loci, providing a more accurate and higher-resolution understanding of polygenic architectures. The aim of this review is to evaluate, in light of recent literature, the transition from traditional phenotypic and pedigree-based breeding approaches to modern genomic selection and various GWAS methodologies, considering that small ruminants play a critical role in human nutrition by contributing high-quality protein and are among the leading species in global red meat production. It also summarizes studies focusing on the genetic improvement of multidimensional traits such as production, reproductive performance, disease resistance, adaptation, and environmental tolerance.
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