Body weight is an important economic trait for sheep and it is vital for their successful production and breeding. Therefore, identifying the genomic regions and biological pathways that contribute to understanding variability in body weight traits is significant for selection purposes. In this study, the genome-wide associations of birth, weaning, yearling, and adult weights of 460 fine-wool sheep were determined using resequencing technology. The results showed that 113 single nucleotide polymorphisms (SNPs) reached the genome-wide significance levels for the four body weight traits and 30 genes were annotated effectively, including AADACL3, VGF, NPC1, and SERPINA12. The genes annotated by these SNPs significantly enriched 78 gene ontology terms and 25 signaling pathways, and were found to mainly participate in skeletal muscle development and lipid metabolism. These genes can be used as candidate genes for body weight in sheep, and provide useful information for the production and genomic selection of Chinese fine-wool sheep.

Background: Copy number variation (CNV) is an important source of genetic variation that has a significant influence on phenotypic diversity, economically important traits and the evolution of livestock species. In this study, the genome-wide CNV distribution characteristics of 32 fine-wool sheep from three breeds were analyzed using resequencing. Results: A total of 1,747,604 CNVs were detected in this study, and 7228 CNV regions (CNVR) were obtained after merging overlapping CNVs; these regions accounted for 2.17% of the sheep reference genome. The average length of the CNVRs was 4307.17 bp. “Deletion” events took place more frequently than “duplication” or “both” events. The CNVRs obtained overlapped with previously reported sheep CNVRs to variable extents (4.39–55.46%). Functional enrichment analysis showed that the CNVR-harboring genes were mainly involved in sensory perception systems, nutrient metabolism processes, and growth and development processes. Furthermore, 1855 of the CNVRs were associated with 166 quantitative trait loci (QTL), including milk QTLs, carcass QTLs, and health-related QTLs, among others. In addition, the 32 fine-wool sheep were divided into horned and polled groups to analyze for the selective sweep of CNVRs, and it was found that the relaxin family peptide receptor 2 (RXFP2) gene was strongly influenced by selection. Conclusions: In summary, we constructed a genomic CNV map for Chinese indigenous fine-wool sheep using resequencing, thereby providing a valuable genetic variation resource for sheep genome research, which will contribute to the study of complex traits in sheep.

Alpine Merino Sheep is a novel breed reared from Australian Merino Sheep as the father and Gansu Alpine Fine-Wool Sheep as the mother, living all year in cold and arid alpine areas with exceptional wool quality and meat performance. Body weight is an important economic trait of the Alpine Merino Sheep, but there is limited research on identifying the genes associated with live weight in the 14th month for improving the accuracy of the genomic prediction of this trait. Therefore, this study’s sample comprised 1310 Alpine Merino Sheep ewes, and the Fine Wool Sheep 50K Panel was used for genome-wide association study (GWAS) analysis to identify candidate genes. Moreover, the trial population (1310 ewes) in this study was randomly divided into two groups. One group was used as the population for GWAS analysis and screened for the most significant top 5%, top 10%, top 15%, and top 20% SNPs to obtain prior marker information. The other group was used to estimate the genetic parameters based on the weight assigned by heritability combined with different prior marker information. The aim of this study was to compare the accuracy of genomic breeding value estimation when combined with prior marker information from GWAS analysis with the optimal linear unbiased prediction method for genome selection (GBLUP) for the breeding value of target traits. Finally, the accuracy was evaluated using the five-fold cross-validation method. This research provides theoretical and technical support to improve the accuracy of sheep genome selection and better guide breeding. The results demonstrated that eight candidate genes were associated with GWAS analysis, and the gene function query and literature search results suggested that FAM184B, NCAPG, MACF1, ANKRD44, DCAF16, FUK, LCORL, and SYN3 were candidate genes affecting live weight in the 14th month (WT), which regulated the growth of muscle and bone in sheep. In genome selection analysis, the heritability of GBLUP to calculate the WT was 0.335–0.374, the accuracy after five-fold cross-verification was 0.154–0.190, and after assigning different weights to the top 5%, top 10%, top 15%, and top 20% of the GWAS results in accordance with previous information to construct the G matrix, the accuracy of the WT in the GBLUP model was improved by 2.59–7.79%.

Hair follicle development and wool shedding in sheep are poorly understood. This study investigated the population structures and genetic differences between sheep with different wool types to identify candidate genes related to these traits. We used Illumina ovine SNP 50K chip genotyping data of 795 sheep populations comprising 27 breeds with two wool types, measuring the population differentiation index (Fst), nucleotide diversity (θπ ratio), and extended haplotype homozygosity among populations (XP-EHH) to detect the selective signatures of hair sheep and fine-wool sheep. The top 5% of the Fst and θπ ratio values, and values of XP-EHH < −2 were considered strongly selected SNP sites. Annotation showed that the PRX, SOX18, TGM3, and TCF3 genes related to hair follicle development and wool shedding were strongly selected. Our results indicated that these methods identified important genes related to hair follicle formation, epidermal differentiation, and hair follicle stem cell development, and provide a meaningful reference for further study on the molecular mechanisms of economically important traits in sheep.

Heat stress is an important environmental factor affecting livestock production worldwide. Primary hepatocytes and preadipocytes derived from Hu sheep were used to establish a heat stress model. Quantitative reverse transcriptase-PCR (qRT-PCR) analysis showed that heat induction significantly increased the expression levels of heat stress protein (HSP) genes and the N⁶-methyladenosine (m6A) methylation modification genes: methyltransferase-like protein 3 (METTL3), methyltransferase-like protein 14 (METTL14), and fat mass and obesity associated protein (FTO). Heat stress simultaneously promoted cell apoptosis. Transcriptome sequencing identified 3980 upregulated genes and 2420 downregulated genes related to heat stress. A pathway enrichment analysis of these genes revealed significant enrichment in fatty acid biosynthesis, degradation, and the PI3K-Akt and peroxisome proliferator-activated receptor (PPAR) signaling pathways. Overexpression of METTL3 in primary hepatocytes led to significant downregulation of HSP60, HSP70, and HSP110, and significantly increased mRNA m6A methylation; FTO interference generated the opposite results. Primary adipocytes showed similar results. Transcriptome analysis of cells under METTL3 (or FTO) inference and overexpression revealed differentially expressed genes enriched in the mitogen-activated protein kinase (MAPK) signaling pathways, as well as the PI3K-Akt and Ras signaling pathways. We speculate that METTL3 may increase the level of m6A methylation to inhibit fat deposition and/or inhibit the expression of HSP genes to enhance the body’s resistance to heat stress, while the FTO gene generated the opposite molecular mechanism. This study provides a scientific basis and theoretical support for sheep feeding and management practices during heat stress.

In recent years, research has gradually uncovered the mechanisms of animal adaptation to hypoxic conditions in different altitude environments, particularly at the genomic level. However, past genomic studies on high-altitude adaptation have often not delved deeply into the differences between varying altitude levels. This study conducted whole-genome sequencing on 60 Tibetan sheep (Medium Altitude Group (MA): 20 Tao sheep (TS) at 2887 m, High Altitude Group (HA): 20 OuLa sheep (OL) at 3501 m, and Ultra-High Altitude Group (UA): 20 AWang sheep (AW) at 4643 m) from different regions of the Tibetan Plateau in China to assess their responses under varying conditions. Population genetic structure analysis revealed that the three groups are genetically independent, but the TS and OL groups have experienced gene flow with other northern Chinese sheep due to geographical factors. Selection signal analysis identified FGF10, MMP14, SLC25A51, NDUFB8, ALAS1, PRMT1, PRMT5, and HIF1AN as genes associated with ultra-high-altitude hypoxia adaptation, while HMOX2, SEMA4G, SLC16A2, SLC22A17, and BCL2L2 were linked to high-altitude hypoxia adaptation. Functional analysis showed that ultra-high-altitude adaptation genes tend to influence physiological mechanisms directly affecting oxygen uptake, such as lung development, angiogenesis, and red blood cell formation. In contrast, high-altitude adaptation genes are more inclined to regulate mitochondrial DNA replication, iron homeostasis, and calcium signaling pathways to maintain cellular function. Additionally, the functions of shared genes further support the adaptive capacity of Tibetan sheep across a broad geographic range, indicating that these genes offer significant selective advantages in coping with oxygen scarcity. In summary, this study not only reveals the genetic basis of Tibetan sheep adaptation to different altitudinal conditions but also highlights the differences in gene regulation between ultra-high- and high-altitude adaptations. These findings offer new insights into the adaptive evolution of animals in extreme environments and provide a reference for exploring adaptation mechanisms in other species under hypoxic conditions.