Selection signatures of wool color in Gangba sheep revealed by genome-wide SNP discovery

BACKGROUND

Gangba sheep as a famous breed of Tibetan sheep, its wool color is mainly white and black. Gangba wool is economically important as a high-quality raw material for Tibetan blankets and Tibetan serge. However, relatively few studies have been conducted on the wool color of Tibetan sheep.

RESULTS

To fill this research gap, this study conducted an in-depth analysis of two populations of Gangba sheep (black and white wool color) using whole genome resequencing to identify genetic variation associated with wool color. Utilizing PCA, Genetic Admixture, and N-J Tree analyses, the present study revealed a consistent genetic relationship and structure between black and white wool colored Gangba sheep populations, which is consistent with their breed history. Analysis of selection signatures using multiple methods (FST, π ratio, Tajima's D), 370 candidate genes were screened in the black wool group (GBB vs GBW); among them, MC1R, MLPH, SPIRE2, RAB17, SMARCA4, IRF4, CAV1, USP7, TP53, MYO6, MITF, MC2R, TET2, NF1, JAK1, GABRR1 genes are mainly associated with melanin synthesis, melanin delivery, and distribution. The enrichment results of the candidate genes identified 35 GO entries and 19 KEGG pathways associated with the formation of the black phenotype. 311 candidate genes were screened in the white wool group (GBW vs GBB); among them, REST, POU2F1, ADCY10, CCNB1, EP300, BRD4, GLI3, and SDHA genes were mainly associated with interfering with the differentiation of neural crest cells into melanocytes, affecting the proliferation of melanocytes, and inhibiting melanin synthesis. 31 GO entries and 22 KEGG pathways were associated with the formation of the white phenotype.

CONCLUSIONS

This study provides important information for understanding the genetic mechanism of wool color in Gangba, and provides genetic knowledge for improving and optimizing the wool color of Tibetan sheep. Genetic improvement and selective breeding to produce wool of specific colors can meet the demand for a diversity of wool products in the Tibetan wool textile market.

Whole Genome Resequencing Reveals Selection Signals Related to Wool Color in Sheep

Wool color is controlled by a variety of genes. Although the gene regulation of some wool colors has been studied in relative depth, there may still be unknown genetic variants and control genes for some colors or different breeds of wool that need to be identified and recognized by whole genome resequencing. Therefore, we used whole genome resequencing data to compare and analyze sheep populations of different breeds by population differentiation index and nucleotide diversity ratios (Fst and θπ ratio) as well as extended haplotype purity between populations (XP-EHH) to reveal selection signals related to wool coloration in sheep. Screening in the non-white wool color group (G1 vs. G2) yielded 365 candidate genes, among which PDE4B, GMDS, GATA1, RCOR1, MAPK4, SLC36A1, and PPP3CA were associated with the formation of non-white wool; an enrichment analysis of the candidate genes yielded 21 significant GO terms and 49 significant KEGG pathways (p < 0.05), among which 17 GO terms and 21 KEGG pathways were associated with the formation of non-white wool. Screening in the white wool color group (G2 vs. G1) yielded 214 candidate genes, including ABCD4, VSX2, ITCH, NNT, POLA1, IGF1R, HOXA10, and DAO, which were associated with the formation of white wool; an enrichment analysis of the candidate genes revealed 9 significant GO-enriched pathways and 19 significant KEGG pathways (p < 0.05), including 5 GO terms and 12 KEGG pathways associated with the formation of white wool. In addition to furthering our understanding of wool color genetics, this research is important for breeding purposes.

Modelling Lactation Curves for Dairy Sheep in a New Zealand Flock

Lactation curves were modelled for dairy sheep in a New Zealand flock, providing information on the lactation yields of milk, fat, protein, and lactose, corrected for 130 days of milking. From 169 ewes, a total of 622 test-day records were obtained during the milk production season of 2021-2022 (from October to January). The flock produced an average of 86.1 kg of milk, 5.1 kg of fat, 4.5 kg of protein, and 4.1 kg of lactose, and moderate to large coefficients of variation were observed (27-31%) for these traits. The lactation persistency of milk, fat, protein, and lactose yields ranged from 52.3 to 72.7%. Analyses of variance for total yield and persistency were performed with an animal model that included the fixed effects of age (parity number), litter size, coat colour, and milking frequency (days in twice-a-day milking) and random residuals. Age and milking frequency were the only factors that significantly affected the yields of milk, fat, protein, and lactose. Age significantly affected the lactation persistency of milk and lactose yields, whereas litter size affected the persistency of protein, and milking frequency affected the persistency of fat. This study on this single flock provides valuable experience for a larger-scale animal breeding programme in New Zealand.

Genetics of the phenotypic evolution in sheep: a molecular look at diversity-driving genes

BACKGROUND

After domestication, the evolution of phenotypically-varied sheep breeds has generated rich biodiversity. This wide phenotypic variation arises as a result of hidden genomic changes that range from a single nucleotide to several thousands of nucleotides. Thus, it is of interest and significance to reveal and understand the genomic changes underlying the phenotypic variation of sheep breeds in order to drive selection towards economically important traits.

REVIEW

Various traits contribute to the emergence of variation in sheep phenotypic characteristics, including coat color, horns, tail, wool, ears, udder, vertebrae, among others. The genes that determine most of these phenotypic traits have been investigated, which has generated knowledge regarding the genetic determinism of several agriculturally-relevant traits in sheep. In this review, we discuss the genomic knowledge that has emerged in the past few decades regarding the phenotypic traits in sheep, and our ultimate aim is to encourage its practical application in sheep breeding. In addition, in order to expand the current understanding of the sheep genome, we shed light on research gaps that require further investigation.

CONCLUSIONS

Although significant research efforts have been conducted in the past few decades, several aspects of the sheep genome remain unexplored. For the full utilization of the current knowledge of the sheep genome, a wide practical application is still required in order to boost sheep productive performance and contribute to the generation of improved sheep breeds. The accumulated knowledge on the sheep genome will help advance and strengthen sheep breeding programs to face future challenges in the sector, such as climate change, global human population growth, and the increasing demand for products of animal origin.

Genetics of Base Coat Colour Variations and Coat Colour-Patterns of the South African Nguni Cattle Investigated Using High-Density SNP Genotypes

Nguni cattle are a Sanga type breed with mixed B. taurus and B. indicus ancestry and proven resistance to ticks, diseases and other harsh conditions of the African geographical landscape. The multi-coloured Nguni coats have found a niche market in the leather industry leading to breeding objectives towards the promotion of such diversity. However, there is limited studies on the genomic architecture underlying the coat colour and patterns hampering any potential breeding and improvement of such trait. This study investigated the genetics of base coat colour, colour-sidedness and the white forehead stripe in Nguni cattle using coat colour phenotyped Nguni cattle and Illumina Bovine HD (770K) genotypes. Base coat colour phenotypes were categorised into eumelanin (n = 45) and pheomelanin (n = 19). Animals were categorised into either colour-sided (n = 46) or non-colour-sided (n = 94) and similarly into presence (n = 15) or absence (n = 67) of white forehead stripe. Genome-wide association tests were conducted using 622,103 quality controlled SNPs and the Efficient Mixed Model Association eXpedited method (EMMAX) implemented in Golden Helix SNP Variation Suite. The genome-wide association studies for base coat colour (eumelanin vs. pheomelanin) resulted into four indicative SNPs on BTA18 and a well-known gene, MC1R, was observed within 1 MB from the indicative SNPs (p < 0.00001) and found to play a role in the melanogenesis (core pathway for melanin production) and the MAPK signalling pathway. GWAS for colour-sidedness resulted in four indicative SNPs, none of which were in close proximity to the KIT candidate gene known for colour-sidedness. GWAS for the white forehead stripe resulted in 17 indicative SNPs on BTA6. Four genes MAPK10, EFNA5, PPP2R3C and PAK1 were found to be associated with the white forehead stripe and were part of the MAPK, adrenergic and Wnt signalling pathways that are synergistically associated with the synthesis of melanin. Overall, our results prove prior knowledge of the role of MC1R in base coat colours in cattle and suggested a different genetic mechanism for forehead stripe phenotypes in Nguni cattle.

Genomic mapping identifies two genetic variants in the MC1R gene for coat colour variation in Chinese Tan sheep

Coat colour is one of the most important economic traits of sheep and is mainly used for breed identification and characterization. This trait is determined by the biochemical function, availability and distribution of phaeomelanin and eumelanin pigments. In our study, we conducted a genome-wide association study to identify candidate genes and genetic variants associated with coat colour in 75 Chinese Tan sheep using the ovine 600K SNP BeadChip. Accordingly, we identified two significant SNPs (rs409651063 at 14.232 Mb and rs408511664 at 14.228 Mb) associated with coat colour in the MC1R gene on chromosome 14 with −log10(P) = 2.47E-14 and 1.00E-13, respectively. The consequence of rs409651063 was a missense variant (g.14231948 G>A) that caused an amino acid change (Asp105Asn); however, the second SNP (rs408511664) was a synonymous substitution and is an upstream variant (g.14228343G>A). Moreover, our PCR analysis revealed that the genotype of white sheep was exclusively homozygous (GG), whereas the genotypes of black-head sheep were mainly heterozygous (GA). Interestingly, allele-specific expression analysis (using the missense variant for the skin cDNA samples from black-head sheep) revealed that only the G allele was expressed in the skin covered with white hair, while both the G and A alleles were expressed in the skin covered with black hair. This finding indicated that the missense mutation that we identified is probably responsible for white coat colour in Tan sheep. Furthermore, qPCR analysis of MC1R mRNA level in the skin samples was significantly higher in black-head than white sheep and very significantly higher in GA than GG individuals. Taken together, these results help to elucidate the genetic mechanism underlying coat colour variation in Chinese indigenous sheep.

GBS Data Identify Pigmentation-Specific Genes of Potential Role in Skin-Photosensitization in Two Tunisian Sheep Breeds

The Tunisian Noire de Thibar sheep breed is a composite breed, recently selected to create animals that are uniformly black in order to avoid skin photosensitization after the ingestion of toxic "hypericum perforatum" weeds, which causes a major economic loss to sheep farmers. We assessed genetic differentiation and estimated marker F_ST using genotyping-by-sequencing (GBS) data in black (Noire de Thibar) and related white-coated (Queue fine de l'ouest) sheep breeds to identify signals of artificial selection. The results revealed the selection signatures within candidate genes related to coat color, which are assumed to be indirectly involved in the mechanism of photosensitization in sheep. The identified genes could provide important information for molecular breeding.

Transcriptomic Analysis of Coding Genes and Non-Coding RNAs Reveals Complex Regulatory Networks Underlying the Black Back and White Belly Coat Phenotype in Chinese Wuzhishan Pigs

Coat color is one of the most important characteristics for distinguishing Chinese indigenous pig breeds. In Wuzhishan pigs, the animals have black on the back and white on the abdomen. However, the molecular genetic basis of this phenotype is unclear. In this study, we used high-throughput RNA sequencing to compare expression profiles of coding and non-coding RNAs from white and black skin samples obtained from individual Wuzhishan pigs. The expression profiling revealed that 194 lncRNAs (long non-coding RNAs), 189 mRNAs (messenger RNAs), and 162 miRNAs (microRNAs) had significantly different levels of expression (|log₂ fold change| > 1, p-value < 0.05) in white and black skin. Compared to RNA levels in black skin, white skin had higher levels of expression of 185 lncRNAs, 181 mRNAs, and 23 miRNAs and lower levels of expression of 9 lncRNAs, 8 mRNAs, and 139 miRNAs. Functional analysis suggested that the differentially expressed transcripts are involved in biological processes such as melanin biosynthesis, pigmentation and tyrosine metabolism. Several key genes involved in melanogenesis, including MLANA, PMEL, TYR, TYRP1, DTC, TRPM1 and CAMK2A, had significantly different levels of expression in the two skin tissues. Potential lncRNA–miRNA–gene interactions were also examined. A total of 15 lncRNAs, 11 miRNAs and 7 genes formed 23 lncRNA–miRNA–gene pairs, suggesting that complex regulatory networks of coding and non-coding genes underlie the coat color trait in Wuzhishan pigs. Our study provides a foundation for understanding how lncRNA, miRNA and genes interact to regulate coat color in black-back/white-belly pigs. We also constructed lncRNA–miRNA–gene interaction networks to elucidate the complex molecular mechanisms underlying skin physiology and melanogenesis. The results extend our knowledge about the diversity of coat color among different domestic animals and provide a foundation for studying novel mechanisms that control coat color in Chinese indigenous pigs.