Genome Selection for Fleece Traits in Inner Mongolia Cashmere Goats Based on GWAS Prior Marker Information.

The Inner Mongolia Cashmere goat (IMCG) industry is a major contributor to global cashmere production, with fleece traits serving as key economic indicators that directly impact both income and the long-term sustainability of the industry. When genome-wide SNPs are used to estimate kinship matrices, the traditional animal model implicitly assumes that all SNPs have the same effect-size distribution. However, in practice, there are differences in the genetic mechanisms and complexity of different traits. We conducted a genome-wide association study (GWAS) on 2299 IMCGs genotyped with 67,021 SNPs, which were obtained after imputation. The traits measured included cashmere yield (CY), wool length (WL), cashmere length (CL), and cashmere diameter (CD), with a total of 33,564 records collected. The top 5% to 20% of the significant SNPs from the GWAS were used as biological prior information. We then assigned proportional weights based on their contribution to the overall genetic variance and further integrated them with the remaining loci to construct a kinship relationship matrix for estimating genetic parameters and genomic breeding value. By incorporating prior marker information from the GWAS, it was found that the heritability estimates for CY, WL, CL, and CD were 0.26, 0.37, 0.09, and 0.35, respectively. For CY and CL, integrating the top 5% of prior SNP markers yielded the highest genomic prediction accuracies of 0.742 and 0.673, representing improvements of 16.67% and 19.75% over models that did not utilize prior information. In contrast, for WL and CD, the highest accuracies of 0.851 and 0.780 were achieved by integrating the top 10% of prior SNP markers, reflecting improvements of 9.81% and 10.14%, respectively. Compared with the conventional GBLUP method, this method of integrating GWAS-derived prior markers for genomic genetic evaluation can significantly improve the accuracy of genomic prediction for fleece traits in IMCGs. This approach facilitates accurate selection for fleece traits in IMCGs, enabling accelerated genetic progress through long-term breeding programs.