Genetic Diversity and Selection Signal Analysis of Hu Sheep Based on SNP50K BeadChip.

Simple Summary: This study focused on 50 Hu sheep from Gansu to analyze the genetic diversity and kinship relationships within the population and to construct family pedigrees. Candidate genes related to growth development and high reproductive performance in Hu sheep were identified. These findings provide a reference for future Hu sheep breeding, genetic evaluation, and population utilization. This research is designed to examine the genetic diversity and kinship among Hu sheep, as well as to discover genes associated with crucial economic traits. A selection of 50 unrelated adult male Hu sheep underwent genotyping with the SNP50K BeadChip. Seven indicators of genetic diversity were assessed based on high-quality SNP data: effective population size (Ne), polymorphic information content (PIC), polymorphic marker ratio (PN), expected heterozygosity (He), observed heterozygosity (Ho), effective number of alleles, and minor allele frequency (MAF). Plink software was employed to compute the IBS genetic distance matrix and detect runs of homozygosity (ROHs), while the G matrix and principal component analysis were performed using GCTA software. Selective sweep analysis was carried out using ROH, Pi, and Tajima's D methodologies. This study identified a total of 64,734 SNPs, of which 56,522 SNPs remained for downstream analysis after quality control. The population displayed relatively high genetic diversity. The 50 Hu sheep were ultimately grouped into 12 distinct families, with families 6, 8, and 10 having the highest numbers of individuals, each consisting of 6 sheep. Furthermore, a total of 294 ROHs were detected, with the majority having lengths between 1 and 5 Mb, and the inbreeding coefficient FROH was 0.01. In addition, 41, 440, and 994 candidate genes were identified by ROH, Pi, and Tajima's D methods, respectively, with 3 genes overlapping (BMPR1B, KCNIP4, and FAM13A). These results offer valuable insights for future Hu sheep breeding, genetic assessment, and population management. [ABSTRACT FROM AUTHOR]