PSII-7 Genome-wide characterization of SNPs and Indels in Royal White and White Dorper sheep using whole-genome sequencing.

Abstract Whole-genome sequencing (WGS) provides a comprehensive approach to understanding genetic variation and selection in livestock breeds. Royal White (RW) and White Dorper (WD) sheep are composite breeds developed for improved growth, reproduction, and environmental adaptability, yet their values and potential remain largely unexplored at the genomic level. The objectives of this study were to (1) characterize genome-wide single nucleotide polymorphisms (SNPs) and insertions/deletions (indels), (2) identify genetic variations differentiating breeds, and (3) investigate selection signatures associated with economically important traits. Whole-genome sequencing was performed on RW (n = 11) and WD (n = 9), with reads aligned to the Ovis aries Rambouillet reference genome (ARS-UI_Ramb_v2.0), followed by variant calling to detect SNPs and indels. Identified variants were annotated using the Ensembl variation database (Ovis_aries_rambouillet; version 113; file date: 2024-08-29). Selective sweep analysis, integrating Fixation Index (Fst) and nucleotide diversity (π) statistics with the top 5% highest Fst and π ratios, was conducted to identify genomic regions under selection. Additionally, detected variants differentiating breeds were cross-referenced with the SheepQTLdb to associate them with known quantitative trait loci (QTLs; release 55; file date: 2024-12-23) linked to economically important traits. The results showed that a total of 21,957,139 SNPs and 2,866,600 indels were detected in RW, while WD had 18,641,789 SNPs and 2,397,368 indels, with 13,982,112 SNPs and 1,393,966 indels shared between both breeds. Comparing all the detected variants with the Ensembl database, 70.83% of RW and 71.22% of WD SNPs and indels were previously reported, while the remaining were novel. Selective sweep analysis identified potential selective genes associated with key phenotypic traits. In RW, selection signals were observed for immunity-related traits, including Maedi-Visna virus susceptibility (e.g., TMPRSS12). For growth, differentiation was identified in body weight (e.g., BCKDHB, CDH6, RFTN1) and average daily gain (e.g., MYO15B). Reproductive traits under selection included offspring number (e.g., DYNC2H1, AZIN2). Additionally, milk production traits such as milk yield (e.g., ZNF366), milk fat percentage (e.g., ADD2), and milk protein percentage (e.g., RNase_MRP-AEBP2) were enriched. In WD, selection signals were detected for morphological traits, including ear size (e.g., SCN11A), and immunity, with gastrointestinal nematode resistance (e.g., ATP6V0A1, IKZF4) and Maedi-Visna virus susceptibility (e.g., PAX8). Growth-related differentiation was found in body weight (e.g., PCBD2). Reproductive traits, including reproductive seasonality (e.g., FAT3), were also under selection. Milk production traits, such as milk yield (e.g., MTCL1), showed differentiation. These findings enhance our understanding of the genomic landscape of RW and WD, providing insights into their selection patterns and genetic basis for key phenotypic and production traits. This knowledge can support future breeding strategies, genomic selection, and genetic improvement programs.