Genome-wide association study for wool production traits in a Chinese Merino sheep population

Application of multi-omics technology in pathogen identification and resistance gene screening of sheep pneumonia

BACKGROUND

Pneumonia constitutes a major health challenge in sheep, severely compromising growth rates and overall productivity, and resulting in considerable economic losses to the sheep industry. To address this issue, the development of disease-resistant breeding programs based on the identification of genetic markers associated with pneumonia susceptibility is of critical importance. This study investigated a sheep population on a farm where pneumonia was endemic. The purpose was to use multi-omics methods to rapidly identify the principal pathogens responsible for pneumonia outbreaks, and to screen for genetic loci and key genes related to pneumonia resistance, thereby providing a scientific basis for the implementation of targeted breeding strategies for pneumonia resistance.

RESULTS

Here, we assessed the impact of pneumonia on sheep growth by evaluating the pneumonia phenotypes of 912 sheep. High-throughput transcriptome sequencing of 40 lungs was conducted to obtain exogenous RNA fragments for microbial sequence alignment. Additionally, 16S rRNA sequencing was performed on lung tissues from 10 healthy and 10 diseased sheep to identify biomarkers associated with phenotypic differences. Mycoplasma ovipneumoniae was identified as the primary pneumonia pathogen, and its presence was further validated by load quantification and immunohistochemical analysis. Integration of genome-wide association study (GWAS) data from 266 lung pathological scores with transcriptome-based differentially expressed genes analysis enabled the identification of five single nucleotide polymorphisms (SNPs) and three potential candidate genes associated with Mycoplasma pneumonia. Subsequent genotyping and phenotype association analyses confirmed the significance of two SNPs and established a strong association between the FOXF1 gene and resistance to Mycoplasma pneumonia.

CONCLUSIONS

High-throughput sequencing technologies have enabled the rapid and accurate identification of the causative pathogen of sheep pneumonia. By integrating multi-omics data, two genomic loci significantly associated with Mycoplasma pneumonia were screened, as well as an anti-Mycoplasma pneumonia key gene, FOXF1.

Exploring the polygenic landscape of wool traits in Turkish Merinos through multi-locus GWAS approaches: middle Anatolian Merino

This study investigates the genetic underpinnings of wool traits, specifically fibre diameter (FD) and staple length (SL), in Middle Anatolian Merino sheep using multi-locus genome-wide association study (GWAS) approaches. Representing the first attempt to examine these polygenic traits with multi-locus methods, the analysis employed four techniques: mrMLM, FASTmrMLM, FASTmrEMMA, and ISIS EM-BLASSO. A total of 18 Quantitative Trait Nucleotides (QTNs) were identified for FD, with 7 co-detected by multiple methods, and 14 QTNs were identified for SL, with 5 co-detected by multiple methods. Post-hoc power analysis revealed high statistical power for both traits (FD: 0.95, SL: 0.91). Notably, three candidate genes-PTPN3, TCF4, and ZBTB8A-were found to be consistent with prior studies. Gene enrichment and pathway analyses reaffirmed the complex and multifactorial molecular mechanisms governing wool traits. These findings enhance our understanding of the polygenic nature of wool traits, shedding light on the intricate genetic regulation and pinpointing genomic regions potentially influencing wool physiology. By identifying specific QTNs associated with FD and SL, this research provides a foundation for elucidating the genetic mechanisms underlying these economically significant traits. Upon validation in diverse populations, these findings hold substantial promise for the application of marker-assisted selection (MAS) to improve wool traits.

TMT-based quantitative proteomics reveals the genetic mechanisms of secondary hair follicle development in fine-wool sheep

The development of secondary hair follicles influences the quality of sheep wool. However, the mechanism by which proteins mediate the fetal development of secondary hair follicles remains unknown. In this study, the histomorphology of secondary hair follicles was analyzed over four stages of fetal development (75, 85, 95, and 105 gestational days). TMT-based quantitative proteomics was used to compare the differential protein profiles of skin tissues between consecutive developmental periods (75 versus 85, 85 versus 95, and 95 versus 105 gestational days). We found that the density of secondary hair follicles and the secondary hair follicles/primary hair follicles ratio increased from 85 to 105 gestational days. Bioinformatic analysis identified 238, 35, and 348 differentially expressed proteins in the respective comparison periods. Focal adhesion, ECM-receptor interaction, and the estrogen signaling pathway all played important roles in secondary hair follicle development. COL1A1, THBS3, ITGA6, COL6A1, and THBS4 were identified as potential candidate proteins in the initiation of secondary hair follicles. This study provides valuable proteomics data on secondary hair follicle development and thus has deepened our understanding of the molecular mechanisms underlying wool quality traits in fine-wool sheep.

Utilization of AI - reshaping the future of food safety, agriculture and food security - a critical review

Artificial intelligence is an emerging technology which harbors a suite of mechanisms that have the potential to be leveraged for reaping value across multiple domains. Lately, there is an increased interest in embracing applications associated with Artificial Intelligence to positively contribute to food safety. These applications such as machine learning, computer vision, predictive analytics algorithms, sensor networks, robotic inspection systems, and supply chain optimization tools have been established to contribute to several domains of food safety such as early warning of outbreaks, risk prediction, detection and identification of food associated pathogens. Simultaneously, the ambition toward establishing a sustainable food system has motivated the adoption of cutting-edge technologies such as Artificial Intelligence to strengthen food security. Given the myriad challenges confronting stakeholders in their endeavors to safeguard food security, Artificial Intelligence emerges as a promising tool capable of crafting holistic management strategies for food security. This entails maximizing crop yields, mitigating losses, and trimming operational expenses. AI models present notable benefits in efficiency, precision, uniformity, automation, pattern identification, accessibility, and scalability for food security endeavors. The escalation in the global trend for adopting alternative protein sources such as edible insects and microalgae as a sustainable food source reflects a growing recognition of the need for sustainable and resilient food systems to address the challenges of population growth, environmental degradation, and food insecurity. Artificial Intelligence offers a range of capabilities to enhance food safety in the production and consumption of alternative proteins like microalgae and edible insects, contributing to a sustainable and secure food system.

Genetics of Wool and Cashmere Fibre: Progress, Challenges, and Future Research

Wool (sheep) and cashmere (goat) fibres have unique biological, physical, and chemical properties and these fibres are becoming more important as the demand for natural products increases. However, these complex protein fibres are at times compromised by natural variability in their properties, and this can impact their use and value. Genetic improvement via selection and breeding can partly overcome this problem, enabling the farming of sheep and goats that produce more desirable fibre. This review explores the challenges in improving wool and cashmere fibre characteristics using genetics, with a focus on improving our understanding of the key protein components of fibres, wool keratins and keratin-associated proteins (KAPs). Despite progress in our knowledge of these proteins, gaining a better understanding of them and how they affect these fibres remains an ongoing challenge. This is not straight-forward, given the large number of similar yet unique genes that produce the proteins and the gaps that remain in their identification and characterisation. More research is required to clarify gene and protein sequence variability and the location and patterns of gene expression, which in turn limits our understanding of fibre growth and variation. Several aspects that currently hinder our progress in this quest include the incomplete identification of all the genes and weaknesses in the approaches used to characterise them, including newer omics technologies. We describe future research directions and challenges, including the need for ongoing gene identification, variation characterisation, and gene expression analysis and association studies to enable further improvement to these valuable natural fibres.

Population structure and selective signature of Kirghiz sheep by Illumina Ovine SNP50 BeadChip

Objective

By assessing the genetic diversity and associated selective traits of Kirghiz sheep (KIR), we aim to uncover the mechanisms that contribute to sheep's adaptability to the Pamir Plateau environment.

Methods

This study utilized Illumina Ovine SNP50 BeadChip data from KIR residing in the Pamir Plateau, Qira Black sheep (QBS) inhabiting the Taklamakan Desert, and commonly introduced breeds including Dorper sheep (DOR), Suffolk sheep (SUF), and Hu sheep (HU). The data was analyzed using principal component analysis, phylogenetic analysis, population admixture analysis, kinship matrix analysis, linkage disequilibrium analysis, and selective signature analysis. We employed four methods for selective signature analysis: fixation index (Fst), cross-population extended homozygosity (XP-EHH), integrated haplotype score (iHS), and nucleotide diversity (Pi). These methods aim to uncover the genetic mechanisms underlying the germplasm resources of Kirghiz sheep, enhance their production traits, and explore their adaptation to challenging environmental conditions.

Results

The test results unveiled potential selective signals associated with adaptive traits and growth characteristics in sheep under harsh environmental conditions, and annotated the corresponding genes accordingly. These genes encompass various functionalities such as adaptations associated with plateau, cold, and arid environment (ETAA1, UBE3D, TLE4, NXPH1, MAT2B, PPARGC1A, VEGFA, TBX15 and PLXNA4), wool traits (LMO3, TRPS1, EPHA5), body size traits (PLXNA2, EFNA5), reproductive traits (PPP3CA, PDHA2, NTRK2), and immunity (GATA3).

Conclusion

Our study identified candidate genes associated with the production traits and adaptation to the harsh environment of the Pamir Plateau in Kirghiz sheep. These findings provide valuable resources for local sheep breeding programs. The objective of this study is to offer valuable insights for the sustainable development of the Kirghiz sheep industry.

Population structure and selection signal analysis of indigenous sheep from the southern edge of the Taklamakan Desert

Analyzing the genetic diversity and selection characteristics of sheep (Ovis aries) holds significant value in understanding their environmental adaptability, enhancing breeding efficiency, and achieving effective conservation and rational utilization of genetic resources. In this study, we utilized Illumina Ovine SNP 50 K BeadChip data from four indigenous sheep breeds from the southern margin of the Taklamakan Desert (Duolang sheep: n = 36, Hetian sheep: n = 74, Kunlun sheep: n = 27, Qira black sheep: n = 178) and three foreign meat sheep breeds (Poll Dorset sheep: n = 105, Suffolk sheep: n = 153, Texel sheep: n = 150) to investigate the population structure, genetic diversity, and genomic signals of positive selection within the indigenous sheep. According to the Principal component analysis (PCA), the Neighbor-Joining tree (NJ tree), and Admixture, we revealed distinct clustering patterns of these seven sheep breeds based on their geographical distribution. Then used Cross Population Extended Haplotype Homozygosity (XP-EHH), Fixation Index (FST), and Integrated Haplotype Score (iHS), we identified a collective set of 32 overlapping genes under positive selection across four indigenous sheep breeds. These genes are associated with wool follicle development and wool traits, desert environmental adaptability, disease resistance, reproduction, and high-altitude adaptability. This study reveals the population structure and genomic selection characteristics in the extreme desert environments of native sheep breeds from the southern edge of the Taklimakan Desert, providing new insights into the conservation and sustainable use of indigenous sheep genetic resources in extreme environments. Additionally, these findings offer valuable genetic resources for sheep and other mammals to adapt to global climate change.

Sheep litter size heredity basis using genome-wide selective analysis

Sheep are important herbivorous domestic animal globally, and the Chinese indigenous sheep breed has a multitude of economically significant variations due to the diverse geographical and ecological conditions. In particular, certain native breeds exhibit a visible high litter size phenotype due to the selection pressure of natural and artificial for thousands of years, offering an ideal animal model for investigating sheep's fecundity. In this study, selective signal analysis was performed on public whole-genome sequencing data from 60 sheep across eight breeds to identify candidate genes related to litter size. Results revealed that a total of 34,065,017 single-nucleotide polymorphisms (SNPs) were identified from all sheep, and 65 candidate genes (CDGs) were pinpointed from the top 1% of interacted windows and SNPs between the pairwise fixation index (FST, >0.149543) and cross-population extended haplotype homozygosity (XP-EHH, >0.701551). A total of 41 CDGs (e.g. VRTN, EYA2 and MCPH1) were annotated to 576 GO terms, of which seven terms were directly linked to follicular and embryonic development (e.g. TBXT, BMPR1B, and BMP2). In addition, 73 KEGG pathways were enriched by 21 CDGs (e.g. ENTPD5, ABCD4 and RXFP2), mainly related to Hippo (TCF4, BMPR1B and BMP2), TGF-β (BMPR1B and BMP2), PI3K-Akt (ITGB4, IL4R and PPP2R5A) and Jak-STAT signalling pathways (IL20RA and IL4R). Notably, a series of CDGs was under strong selection in sheep with high litter size traits. These findings result could improve the comprehension of the genetic underpinnings of sheep litter size. Furthermore, it provides valuable CDGS for future molecular breeding.

Genomic Characterization of Quality Wool Traits in Spanish Merino Sheep

The native Spanish Merino breed was the founder of all the other Merino and Merino-derived breeds worldwide. Despite the fact that this breed was created and improved to produce the highest quality fine wool, the global wool market crisis led to the wholescale crossing of most of the herds with breeds for meat purposes. Nevertheless, there are still some purebred animals with a high potential for producing quality wool. The objective of this study was to characterize the current wool quality of the breed and identify genes associated with these parameters. To achieve this, over 12,800 records from the most representative animals of the breed (registered in the herd book) were analyzed using the Australian OFDA 2000 system, for parameters such as fiber diameter (FD), standard deviation (SD), coefficient of variation (CV), fibers over 15 microns (>15%), staple length (SL), and comfort factor (CRV). Additionally, animals with the most extreme FD values were whole-genome sequenced using NGS. Genome-wide association studies (GWAS) determined the association of 74 variants with the different traits studied, which were located in 70 different genes. Of these genes, EDN2, COL18A1, and LRP1B, associated with fibers over 15%, and FGF12 and ADAM17, associated with SL, play a key role in hair follicle growth and development. Our study reveals the great potential for recovering this breed for fine wool production, and identifies five candidate genes whose understanding may aid in that selection process.

Genome-wide association analysis of fleece traits in Northwest Xizang white cashmere goat

Northwest Xizang White Cashmere Goat (NXWCG) is the first new breed of cashmere goat in the Xizang Autonomous Region. It has significant characteristics of extremely high fineness, gloss, and softness. Genome-wide association analysis is an effective biological method used to measure the consistency and correlation of genotype changes between two molecular markers in the genome. In addition, it can screen out the key genes affecting the complex traits of biological individuals. The aim of this study was to analyze the genetic mechanism of cashmere trait variation in NXWCG and to discover SNP locus and key genes closely related to traits such as superfine cashmere. Additionally, the key genes near the obtained significant SNPs were analyzed by gene function annotation and biological function mining. In this study, the phenotype data of the four traits (cashmere length, fiber length, cashmere diameter, and cashmere production) were collected. GGP_Goat_70K SNP chip was used for genotyping the ear tissue DNA of the experimental group. Subsequently, the association of phenotype data and genotype data was performed using Gemma-0.98.1 software. A linear mixed model was used for the association study. The results showed that four fleece traits were associated with 18 significant SNPs at the genome level and 232 SNPs at the chromosome level, through gene annotated from Capra hircus genome using assembly ARS1. A total of 107 candidate genes related to fleece traits were obtained. Combined with Gene Ontology and Kyoto Encyclopedia of Genes and Genomes enrichment analysis, we can find that CLNS1A, CCSER1, RPS6KC1, PRLR, KCNRG, KCNK9, and CLYBL can be used as important candidate genes for fleece traits of NXWCG. We used Sanger sequencing and suitability chi-square test to further verify the significant loci and candidate genes screened by GWAS, and the results show that the base mutations loci on the five candidate genes, CCSER1 (snp12579, 34,449,796, A → G), RPS6KC1 (snp41503, 69,173,527, A → G), KCNRG (snp41082, 67,134,820, G → A), KCNK9 (14:78472665, 78,472,665, G → A), and CLYBL (12: 9705753, 9,705,753, C → T), significantly affect the fleece traits of NXWCG. The results provide a valuable basis for future research and contribute to a better understanding of the genetic structure variation of the goat.

Whole-Genome Resequencing Reveals Genetic Diversity and Wool Trait-Related Genes in Liangshan Semi-Fine-Wool Sheep

Understanding the genetic makeup of local sheep breeds is essential for their scientific conservation and sustainable utilization. The Liangshan semi-fine-wool sheep (LSS), a Chinese semi-fine-wool breed renowned for its soft wool, was analyzed using whole-genome sequencing data including 35 LSS, 84 sheep from other domestic breeds, and 20 Asiatic mouflons. We investigated the genetic composition of LSS by conducting analyses of the population structure, runs of homozygosity, genomic inbreeding coefficients, and selection signature. Our findings indicated that LSS shares greater genetic similarity with Border Leicester and Romney sheep than with Tibetan (TIB), Yunnan (YNS), and Chinese Merino sheep. Genomic analysis indicated low to moderate inbreeding coefficients, ranging from 0.014 to 0.154. In identifying selection signals across the LSS genome, we pinpointed 195 candidate regions housing 74 annotated genes (e.g., IRF2BP2, BVES, and ALOX5). We also found the overlaps between the candidate regions and several known quantitative trait loci related to wool traits, such as the wool staple length and wool fiber diameter. A selective sweep region, marked by the highest value of cross-population extended haplotype homozygosity, encompassed IRF2BP2-an influential candidate gene affecting fleece fiber traits. Furthermore, notable differences in genotype frequency at a mutation site (c.1051 + 46T > C, Chr25: 6,784,190 bp) within IRF2BP2 were observed between LSS and TIB and YNS sheep (Fisher's exact test, p < 2.2 × 10-16). Taken together, these findings offer insights crucial for the conservation and breeding enhancement of LSS.

Whole-genome resequencing of Dorper and Hu sheep to reveal selection signatures associated with important traits

Dorper and Hu sheep exhibit different characteristics in terms of reproduction, growth, and meat quality. Comparison of the genomes of two breeds help to reveal important genomic information. In this study, whole genome resequencing of 30 individuals (Dorper, DB and Hu sheep, HY) identified 15,108,125 single nucleotide polymorphisms (SNPs). Population differentiation (Fst) and cross population extended haplotype homozygosity (XP-EHH) were performed for selective signal analysis. In total, 106 and 515 overlapped genes were present in both the Fst results and XP-EHH results in HY vs DB and in DB vs HY, respectively. In HY vs DB, 106 genes were enriched in 12 GO terms and 83 KEGG pathways, such as ATP binding (GO:0005524) and PI3K-Akt signaling pathway (oas04151). In DB vs HY, 515 genes were enriched in 109 GO terms and 215 KEGG pathways, such as skeletal muscle cell differentiation (GO:0035914) and MAPK signaling pathway (oas04010). According to the annotation results, we identified a series of candidate genes associated with reproduction (UNC5C, BMPR1B, and GLIS1), meat quality (MECOM, MEF2C, and MYF6), and immunity (GMDS, GALK1, and ITGB4). Our investigation has uncovered genomic information for important traits in sheep and provided a basis for subsequent studies of related traits.

Association between the cashmere production performance, milk production performance, and body size traits and polymorphism of COL6A5 and LOC102181374 genes in Liaoning cashmere goats

The purpose of this study was to analyze the relationship between COL6A5 (collagen type VI alpha 5 chain) and LOC102181374 (alcohol dehydrogenase 1) genes and the production performance of Liaoning cashmere goats by single nucleotide polymorphism (SNP). We have searched for SNP loci of COL6A5 and LOC102181374 genes through sequence alignment and PCR experiments, and have used SPSS and SHEsis software to analyze production data. We obtained five SNP loci in total, including three SNP loci (G50985A, G51140T, G51175A) in COL6A5 gene and two SNP loci (A10067G, T10108C) in LOC102181374 gene. The genotypes G50985A (AG), G51140T (GT), G51175A (AA), A10067G (AA), and T10108C (CC) of these loci have certain advantages in improving the production performance of Liaoning cashmere goats. The haplotype combinations that can improve production performance in COL6A5 gene were H1H5:AGGGAG, H4H4:GGGGAA, and H4H4:GGGGAA. H3H3:GGCC and H2H4:AGTT were the dominant combinations in LOC102181374 gene. At G51175A and A10067G loci, we found that H1H2:AAAG and H1H3:AGAA have dominant effects. These results may provide some support for the molecular breeding of production traits in Liaoning cashmere goats.

Genome-wide association analysis unveils candidate genes and loci associated with aplasia cutis congenita in pigs

BACKGROUND

Aplasia cutis congenita (ACC) is a rare genetic disorder characterized by the localized or widespread absence of skin in humans and animals. Individuals with ACC may experience developmental abnormalities in the skeletal and muscular systems, as well as potential complications. Localized and isolated cases of ACC can be treated through surgical and medical interventions, while extensive cases of ACC may result in neonatal mortality. The presence of ACC in pigs has implications for animal welfare. It contributes to an elevated mortality rate among piglets at birth, leading to substantial economic losses in the pig farming industry. In order to elucidate candidate genetic loci associated with ACC, we performed a Genome-Wide Association Study analysis on 216 Duroc pigs. The primary goal of this study was to identify candidate genes that associated with ACC.

RESULTS

This study identified nine significant SNPs associated with ACC. Further analysis revealed the presence of two quantitative trait loci, 483 kb (5:18,196,971-18,680,098) on SSC 5 and 159 kb (13:20,713,440-207294431 bp) on SSC13. By annotating candidate genes within a 1 Mb region surrounding the significant SNPs, a total of 11 candidate genes were identified on SSC5 and SSC13, including KRT71, KRT1, KRT4, ITGB7, CSAD, RARG, SP7, PFKL, TRPM2, SUMO3, and TSPEAR.

CONCLUSIONS

The results of this study further elucidate the potential mechanisms underlying and genetic architecture of ACC and identify reliable candidate genes. These results lay the foundation for treating and understanding ACC in humans.

Genome-Wide Association Study of Fiber Diameter in Alpacas

The aim of this study was the identification of candidate genomic regions associated with fiber diameter in alpacas. DNA samples were collected from 1011 female Huacaya alpacas from two geographical Andean regions in Peru (Pasco and Puno), and three alpaca farms within each region. The samples were genotyped using an Affymetrix Custom Alpaca genotyping array containing 76,508 SNPs. After the quality controls, 960 samples and 51,742 SNPs were retained. Three association study methodologies were performed. The GWAS based on a linear model allowed us to identify 11 and 35 SNPs (-log10(p-values) > 4) using information on all alpacas and alpacas with extreme values of fiber diameter, respectively. The haplotype and marker analysis method allowed us to identify nine haplotypes with standardized haplotype heritability higher than six standard deviations. The selection signatures based on cross-population extended haplotype homozygosity (XP-EHH) allowed us to identify 180 SNPs with XP-EHH values greater than |3|. Four candidate regions with adjacent SNPs identified via two association methods of analysis are located on VPA6, VPA9, VPA29 and one chromosomally unassigned scaffold. This study represents the first analysis of alpaca whole genome association with fiber diameter, using a recently assembled alpaca SNP microarray.

A computational framework for improving genetic variants identification from 5,061 sheep sequencing data

BACKGROUND

Pan-genomics is a recently emerging strategy that can be utilized to provide a more comprehensive characterization of genetic variation. Joint calling is routinely used to combine identified variants across multiple related samples. However, the improvement of variants identification using the mutual support information from multiple samples remains quite limited for population-scale genotyping.

RESULTS

In this study, we developed a computational framework for joint calling genetic variants from 5,061 sheep by incorporating the sequencing error and optimizing mutual support information from multiple samples' data. The variants were accurately identified from multiple samples by using four steps: (1) Probabilities of variants from two widely used algorithms, GATK and Freebayes, were calculated by Poisson model incorporating base sequencing error potential; (2) The variants with high mapping quality or consistently identified from at least two samples by GATK and Freebayes were used to construct the raw high-confidence identification (rHID) variants database; (3) The high confidence variants identified in single sample were ordered by probability value and controlled by false discovery rate (FDR) using rHID database; (4) To avoid the elimination of potentially true variants from rHID database, the variants that failed FDR were reexamined to rescued potential true variants and ensured high accurate identification variants. The results indicated that the percent of concordant SNPs and Indels from Freebayes and GATK after our new method were significantly improved 12%-32% compared with raw variants and advantageously found low frequency variants of individual sheep involved several traits including nipples number (GPC5), scrapie pathology (PAPSS2), seasonal reproduction and litter size (GRM1), coat color (RAB27A), and lentivirus susceptibility (TMEM154).

CONCLUSION

The new method used the computational strategy to reduce the number of false positives, and simultaneously improve the identification of genetic variants. This strategy did not incur any extra cost by using any additional samples or sequencing data information and advantageously identified rare variants which can be important for practical applications of animal breeding.

Whole-Genome Resequencing Reveals Selection Signal Related to Sheep Wool Fineness

Wool fineness affects the quality of wool, and some studies have identified about forty candidate genes that affect sheep wool fineness, but these genes often reveal only a certain proportion of the variation in wool thickness. We further explore additional genes associated with the fineness of sheep wool. Whole-genome resequencing of eight sheep breeds was performed to reveal selection signals associated with wool fineness, including four coarse wool and four fine/semi-fine wool sheep breeds. Multiple methods to reveal selection signals (Fst and θπ Ratio and XP-EHH) were applied for sheep wool fineness traits. In total, 269 and 319 genes were annotated in the fine wool (F vs. C) group and the coarse wool (C vs. F) group, such as LGR4, PIK3CA, and SEMA3C and NFIB, OPHN1, and THADA. In F vs. C, 269 genes were enriched in 15 significant GO Terms (p < 0.05) and 38 significant KEGG Pathways (p < 0.05), such as protein localization to plasma membrane (GO: 0072659) and Inositol phosphate metabolism (oas 00562). In C vs. F, 319 genes were enriched in 21 GO Terms (p < 0.05) and 16 KEGG Pathways (p < 0.05), such as negative regulation of focal adhesion assembly (GO: 0051895) and Axon guidance (oas 04360). Our study has uncovered genomic information pertaining to significant traits in sheep and has identified valuable candidate genes. This will pave the way for subsequent investigations into related traits.

Transcriptome analysis reveals genes associated with wool fineness in merinos

Hair/wool usually plays an important role in maintaining animal physiological activities, and the economic value of wool cannot be ignored. At present, people set higher demands on wool fineness. Hence, improving wool fineness is the concern of fine wool sheep breeding. Using RNA-Seq to screen the potential candidate genes that associate with wool fineness can provide theoretical references for fine-wool sheep breeding, and also provide us new ideas for further understand the molecular regulation mechanism of hair growth. In this study, we compared the expression pattern difference of genome-wide genes between the skin transcriptomes of Subo and Chinese Merinos. The results showed that, 16 candidate differentially expressed genes (DEGs) (Included: CACNA1S, GP5, LOC101102392, HSF5, SLITRK2, LOC101104661, CREB3L4, COL1A1, PTPRR, SFRP4, LOC443220, COL6A6, COL6A5, LAMA1, LOC114115342 and LOC101116863 genes) that may associate with wool fineness were screened, and these genes were located in signaling pathways that regulate hair follicle development, cycle or hair growth. It is worth noting that, among the 16 DEGs, COL1A1 gene has the highest expression level in Merino skins, and the fold change of LOC101116863 gene is the highest, and the structures of these two genes are both highly conserved in different species. In conclusion, we speculate that these two genes may play a key role in regulating wool fineness and respectively have similar and conserved functions in different species.

Genome-Wide Scan of Wool Production Traits in Akkaraman Sheep

The objective of this study was to uncover the genetic background of wool quality, a production trait, by estimating genomic heritability and implementing GWAS in Akkaraman sheep. The wool characteristics measured included fibre diameter (FD) and staple length (SL) at the age of 8 months and yearling fibre diameter (YFD), yearling staple length (YSL) and yearling greasy fleece weight (YGFW) at 18 months of age. Animals were genotyped using the Axiom 50 K Ovine Genotyping Array. Maximum likelihood estimations of a linear mixed model (LMM) were used to estimate genomic heritability, where GWAS was conducted following a score test of each trait. Genomic heritability estimates for the traits ranged between 0.22 and 0.63, indicating that phenotypes have a moderate range of heritability. One genome- and six chromosome-wide significant SNPs were associated with the wool traits in Akkaraman lambs. Accordingly, TRIM2, MND1, TLR2, RNF175, CEP290, TMTC3, RERE, SLC45A1, SOX2, MORN1, SKI, FAAP20, PRKCZ, GABRD, CFAP74, CALML6 and TMEM52 genes as well as nine uncharacterized regions (LOC101118971, LOC105609137, LOC105603067, LOC101122892, LOC106991694, LOC106991467, LOC106991455, LOC105616534 and LOC105609719) were defined as plausible candidates. The findings of this study shed light on the genetics of wool quality and yield for the Akkaraman breed and suggests targets for breeders during systematic breeding programmes.

Hair Follicle Transcriptome Analysis Reveals Differentially Expressed Genes That Regulate Wool Fiber Diameter in Angora Rabbits

Wool fiber diameter (WFD) is an important index of wool traits and the main determinant of wool quality and value. However, the genetic determinants of fiber diameter have not yet been fully elucidated. Here, coarse and fine wool of Wan strain Angora rabbits and their hair follicle traits were characterized. The results indicated significant differences in the diameters of wool fibers and their hair follicles. The RNA sequencing (RNA-Seq) technique was used to identify differences in gene expression in hair follicles between coarse and fine wool. In total, 2574 differentially expressed genes (DEGs) were found between the two hair follicle groups. Transcription factors, keratin-associated protein (KAP) and keratin (KRT) families, and ECM-related genes may control the structure of fine fibers in rabbits. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) analyses revealed that skin development, epidermal cell and keratinocyte differentiation, epithelium development, and Notch and ribosome signaling pathways were significantly enriched, respectively. GSEA further filtered six important pathways and related core genes. PPI analysis also mined functional DEGs associated with hair structure, including LEF1, FZD3, SMAD3, ITGB6, and BMP4. Our findings provide valuable information for researching the molecular mechanisms regulating wool fiber and could facilitate enhanced selection of super-fine wool rabbits through gene-assisted selection in the future.

Genetic association of wool quality characteristics in United States Rambouillet sheep

Introduction: Fine wool production is an important source of revenue, accounting for up to 13% of total revenue in extensively managed wool sheep production systems of the United States. The Rambouillet are a predominant breed that excels in wool quality characteristics. Understanding the genetic basis of wool quality characteristics would aid in the development of genomic breeding strategies to facilitate genetic improvement. Methods: Wool characteristics and DNA were collected for rams enrolled in the North Dakota State University and University of Wyoming annual central performance ram tests over a three-year period (2019-2021, N = 313). The relationships of wool quality characteristics including grease fleece weight adjusted 365 days (wt. 365 adj.), clean fleece wt. 365 adj., staple length 365 adj., average fiber diameter, face wool cover, amount of skin wrinkles and belly wool were evaluated through genome-wide association studies (GWAS), Pearson correlation and ANOVA. Results: The GWAS identified four genome-wide significant genetic markers (p-value <1.19e-06) and five chromosome-wide significant markers (p-value <1.13e-05) on chromosomes 1, 2, 4, 15, and 19. Significant markers were associated with genes notable for relevant wool biological functions, including the gene ABCC8 which codes for SUR1, an ATP-sensitive potassium channel known to affect hair growth and 60S ribosomal protein L17-like, previously found to be expressed during follicle formation. The strongest Pearson correlation coefficients were identified between clean fleece wt. 365 adj. and grease fleece wt. 365 adj. (r = 0.83) and between clean fleece wt. 365 adj. and staple length 365 adj. (r = 0.53). Additionally, clean fleece wt. 365 adj. was correlated with final body weight (r = 0.35) and scrotal circumference (r = 0.16). Staple length 365 adj. (p-value = 5e-04), average fiber diameter (p-value = .0053) and clean fleece wt. 365 adj. (p-value = .014) were significantly associated with belly wool score. Discussion: The results of this study provide important insight into the relationships between wool quality characteristics and report specific markers that Rambouillet sheep producers may use to help inform selection and breeding decisions for improved wool quality.

Genomic Regions Associated with Wool, Growth and Reproduction Traits in Uruguayan Merino Sheep

The aim of this study was to identify genomic regions and genes associated with the fiber diameter (FD), clean fleece weight (CFW), live weight (LW), body condition score (BCS), pregnancy rate (PR) and lambing potential (LP) of Uruguayan Merino sheep. Phenotypic records of approximately 2000 mixed-age ewes were obtained from a Merino nucleus flock. Genome-wide association studies were performed utilizing single-step Bayesian analysis. For wool traits, a total of 35 genomic windows surpassed the significance threshold (PVE ≥ 0.25%). The proportion of the total additive genetic variance explained by those windows was 4.85 and 9.06% for FD and CFW, respectively. There were 42 windows significantly associated with LWM, which collectively explained 43.2% of the additive genetic variance. For BCS, 22 relevant windows accounted for more than 40% of the additive genetic variance, whereas for the reproduction traits, 53 genomic windows (24 and 29 for PR and LP, respectively) reached the suggestive threshold of 0.25% of the PVE. Within the top 10 windows for each trait, we identified several genes showing potential associations with the wool (e.g., IGF-1, TGFB2R, PRKCA), live weight (e.g., CAST, LAP3, MED28, HERC6), body condition score (e.g., CDH10, TMC2, SIRPA, CPXM1) or reproduction traits (e.g., ADCY1, LEPR, GHR, LPAR2) of the mixed-age ewes.

Whole-genome selective scans detect genes associated with important phenotypic traits in goat (Capra hircus)

Goats with diverse economic phenotypic traits play an important role in animal husbandry. However, the genetic mechanisms underlying complex phenotypic traits are unclear in goats. Genomic studies of variations provided a lens to identify functional genes. In this study, we focused on the worldwide goat breeds with outstanding traits and used whole-genome resequencing data in 361 samples from 68 breeds to detect genomic selection sweep regions. We identified 210-531 genomic regions with six phenotypic traits, respectively. Further gene annotation analysis revealed 332, 203, 164, 300, 205, and 145 candidate genes corresponding with dairy, wool, high prolificacy, poll, big ear, and white coat color traits. Some of these genes have been reported previously (e.g., KIT, KITLG, NBEA, RELL1, AHCY, and EDNRA), while we also discovered novel genes, such as STIM1, NRXN1, LEP, that may be associated with agronomic traits like poll and big ear morphology. Our study found a set of new genetic markers for genetic improvement in goats and provided novel insights into the genetic mechanisms of complex traits.

An insight into the runs of homozygosity distribution and breed differentiation in Mangalitsa pigs

Mangalitsa pigs exhibit three distinct coat color patterns based on which they are described as Red, Blond, and Swallow-bellied. The current study investigated genome-wide diversity and selection signatures in the three breeds using fixation index, runs of homozygosity and population structure analyses. The analyses were originally based on quality-controlled data on 77 Mangalitsa animals from Germany, including 23 Blond, 30 Swallow-bellied and 24 Red Mangalitsa genotyped with a customized version of the ProcineSNP60 v2 Genotyping Bead Chip. Also, 20 Hungarian Mangalitsa genotypes were included as outgroup data for comparison. Estimates of observed heterozygosity were 0.27, 0.28, and 0.29, and inbreeding coefficients estimated based on runs of homozygosity were 24.11%, 20.82%, and 16.34% for Blond, Swallow-bellied and Red Mangalitsa, respectively. ROH islands were detected in all breeds, however, none of these were shared amongst them. The KIF16B gene previously reported to play a role in synaptic signaling was found in a ROH island (SSC17: 16–26) in Swallow-bellied Mangalitsa. The same gene was found to harbor a significantly differentiated SNP (MARC0032380) while contrasting either Blond or Red to Swallow-belied Mangalitsa. In the Red Mangalitsa, some ROH islands were associated with genes that play a role in meat quality traits, i.e., ABCA12, VIL1, PLSCR5, and USP37. Our population structure analysis highlighted a separation of the three breeds, but also showed the closest relatedness between Red and Blond Mangalitsa pigs. Findings of this study improve our understanding of the diversity in the three breeds of Mangalitsa pigs.

Keratinocyte-associated protein 3 plays a role in body weight and adiposity with differential effects in males and females

Despite the obesity crisis in the United States, the underlying genetics are poorly understood. Our lab previously identified Keratinocyte-associated protein 3, Krtcap3, as a candidate gene for adiposity through a genome-wide association study in outbred rats, where increased liver expression of Krtcap3 correlated with decreased fat mass. Here we seek to confirm that Krtcap3 expression affects adiposity traits. To do so, we developed an in vivo whole-body Krtcap3 knock-out (KO) rat model. Wild-type (WT) and KO rats were placed onto a high-fat (HFD) or low-fat diet (LFD) at 6 weeks of age and were maintained on diet for 13 weeks, followed by assessments of metabolic health. We hypothesized that Krtcap3-KO rats will have increased adiposity and a worsened metabolic phenotype relative to WT. We found that KO male and female rats have significantly increased body weight versus WT, with the largest effect in females on a HFD. KO females also ate more and had greater adiposity, but were more insulin sensitive than WT regardless of diet condition. Although KO males weighed more than WT under both diet conditions, there were no differences in eating behavior or fat mass. Interestingly, KO males on a HFD were more insulin resistant than WT. This study confirms that Krtcap3 plays a role in body weight regulation and demonstrates genotype- and sex-specific effects on food intake, adiposity, and insulin sensitivity. Future studies will seek to better understand these sex differences, the role of diet, and establish a mechanism for Krtcap3 in obesity.

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.

A high-density genome-wide association with absolute blood monocyte count in domestic sheep identifies novel loci

Monocytes are a core component of the immune system that arise from bone marrow and differentiate into cells responsible for phagocytosis and antigen presentation. Their derivatives are often responsible for the initiation of the adaptive immune response. Monocytes and macrophages are central in both controlling and propagating infectious diseases such as infection by Coxiella burnetii and small ruminant lentivirus in sheep. Genotypes from 513 Rambouillet, Polypay, and Columbia sheep (Ovis aries) were generated using the Ovine SNP50 BeadChip. Of these sheep, 222 animals were subsequently genotyped with the Ovine Infinium^® HD SNP BeadChip to increase SNP coverage. Data from the 222 HD genotyped sheep were combined with the data from an additional 258 unique sheep to form a 480-sheep reference panel; this panel was used to impute the low-density genotypes to the HD genotyping density. Then, a genome-wide association analysis was conducted to identify loci associated with absolute monocyte counts from blood. The analysis used a single-locus mixed linear model implementing EMMAX with age and ten principal components as fixed effects. Two genome-wide significant peaks (p < 5x10^-7) were identified on chromosomes 9 and 1, and ten genome-wide suggestive peaks (p < 1x10^-5) were identified on chromosomes 1, 2, 3, 4, 9, 10, 15, and 16. The identified loci were within or near genes including KCNK9, involved into cytokine production, LY6D, a member of a superfamily of genes, some of which subset monocyte lineages, and HMGN1, which encodes a chromatin regulator associated with myeloid cell differentiation. Further investigation of these loci is being conducted to understand their contributions to monocyte counts. Investigating the genetic basis of monocyte lineages and numbers may in turn provide information about pathogens of veterinary importance and elucidate fundamental immunology.

Association of SNPs within PTPN3 gene with wool production and growth traits in a dual-purpose sheep population

Protein tyrosine phosphatase non-receptor type 3 (PTPN3), a member of the membrane-associated non-receptor protein tyrosine phosphatase (PTP) family, plays significant roles in the cytoplasm and affects the development and growth of skin and hair. A recent study identified the PTPN3 as the potential gene related to sheep wool quality. To detect single-nucleotide polymorphisms (SNPs) of PTPN3 and elucidate its association with wool production and growth traits in fine wool sheep a total of 644 healthy SG (South African mutton merino♂ × Gansu alpine fine-wool sheep♀, SG) and SSG (South African mutton merino♂ × SG♀, SSG) hybrid sheep were selected. Pooled-DNA sequencing and SNPscan methods were used to scan and genotype SNPs within PTPN3. Association analyses between SNPs and wool production and growth traits were implemented. Consequently, the results revealed that PTPN3 has six SNPs (two missense mutations, one synonymous mutation, and three intron mutations), of which four loci (SNP2, SNP3, SNP4, and SNP5) were significantly positively correlated with growth and wool traits (p < 0.05). SNP4 was significantly (p < 0.05) linked with thigh wool length, and SNP6 was significantly (p < 0.05) associated with abdomen wool length. Moreover, one strongly linked SNP block was identified to be correlated with wool production and growth traits (body weight and body size). The significant SNPs founded by this study could serve as useful genetic markers for breeding fine-wool sheep.^®.

Signature selection analysis reveals candidate genes associated with production traits in Iranian sheep breeds

BACKGROUND

Sheep were among the first animals to be domesticated. They are raised all over the world and produce a major scale of animal-based protein for human consumption and play an important role in agricultural economy. Iran is one of the important locations for sheep genetic resources in the world. Here, we compared the Illumina Ovine SNP50 BeadChip data of three Iranian local breeds (Moghani, Afshari and Gezel), as a population that does not undergone artificial breeding programs as yet, and five other sheep breeds namely East Friesian white, East Friesian brown, Lacaune, DorsetHorn and Texel to detect genetic mechanisms underlying economical traits and daptation to harsh environments in sheep.

RESULTS

To identify genomic regions that have been targeted by positive selection, we used fixation index (Fst) and nucleotide diversity (Pi) statistics. Further analysis indicated candidate genes involved in different important traits such as; wool production included crimp of wool (PTPN3, NBEA and KRTAP20-2 genes), fiber diameter (PIK3R4 gene), hair follicle development (LHX2 gene), the growth and development of fiber (COL17A1 gene)), adaptation to hot arid environments (CORIN gene), adaptive in deficit water status (CPQ gene), heat stress (PLCB4, FAM107B, NBEA, PIK3C2B and USP43 genes) in sheep.

CONCLUSIONS

We detected several candidate genes related to wool production traits and adaptation to hot arid environments in sheep that can be applicable for inbreeding goals. Our findings not only include the results of previous researches, but also identify a number of novel candidate genes related to studied traits. However, more works will be essential to acknowledge phenotype- genotype relationships of the identified genes in our study.

Evaluation of Bayesian alphabet and GBLUP based on different marker density for genomic prediction in Alpine Merino sheep

The marker density, the heritability level of trait and the statistical models adopted are critical to the accuracy of genomic prediction (GP) or selection (GS). If the potential of GP is to be fully utilized to optimize the effect of breeding and selection, in addition to incorporating the above factors into simulated data for analysis, it is essential to incorporate these factors into real data for understanding their impact on GP accuracy, more clearly and intuitively. Herein, we studied the GP of six wool traits of sheep by two different models, including Bayesian Alphabet (BayesA, BayesB, BayesCπ, and Bayesian LASSO) and genomic best linear unbiased prediction (GBLUP). We adopted fivefold cross-validation to perform the accuracy evaluation based on the genotyping data of Alpine Merino sheep (n = 821). The main aim was to study the influence and interaction of different models and marker densities on GP accuracy. The GP accuracy of the six traits was found to be between 0.28 and 0.60, as demonstrated by the cross-validation results. We showed that the accuracy of GP could be improved by increasing the marker density, which is closely related to the model adopted and the heritability level of the trait. Moreover, based on two different marker densities, it was derived that the prediction effect of GBLUP model for traits with low heritability was better; while with the increase of heritability level, the advantage of Bayesian Alphabet would be more obvious, therefore, different models of GP are appropriate in different traits. These findings indicated the significance of applying appropriate models for GP which would assist in further exploring the optimization of GP.

The Quest for Genes Involved in Adaptation to Climate Change in Ruminant Livestock

Livestock radiated out from domestication centres to most regions of the world, gradually adapting to diverse environments, from very hot to sub-zero temperatures and from wet and humid conditions to deserts. The climate is changing; generally global temperature is increasing, although there are also more extreme cold periods, storms, and higher solar radiation. These changes impact livestock welfare and productivity. This review describes advances in the methodology for studying livestock genomes and the impact of the environment on animal production, giving examples of discoveries made. Sequencing livestock genomes has facilitated genome-wide association studies to localize genes controlling many traits, and population genetics has identified genomic regions under selection or introgressed from one breed into another to improve production or facilitate adaptation. Landscape genomics, which combines global positioning and genomics, has identified genomic features that enable animals to adapt to local environments. Combining the advances in genomics and methods for predicting changes in climate is generating an explosion of data which calls for innovations in the way big data sets are treated. Artificial intelligence and machine learning are now being used to study the interactions between the genome and the environment to identify historic effects on the genome and to model future scenarios.

Whole-genome re-sequencing association study on yearling wool traits in Chinese fine-wool sheep

To investigate single nucleotide polymorphism (SNP) loci associated with yearling wool traits of fine-wool sheep for optimizing marker-assisted selection and dissection of the genetic architecture of wool traits, we conducted a genome-wide association study (GWAS) based on the fixed and random model circulating probability unification (FarmCPU) for yearling staple length (YSL), yearling mean fiber diameter (YFD), yearling greasy fleece weight (YGFW), and yearling clean fleece rate (YCFR) by using the whole-genome re-sequenced data (totaling 577 sheep) from the following four fine-wool sheep breeds in China: Alpine Merino sheep (AMS), Chinese Merino sheep (CMS), Qinghai fine-wool sheep (QHS), and Aohan fine-wool sheep (AHS). A total of 16 SNPs were detected above the genome-wise significant threshold (P = 5.45E-09), and 79 SNPs were located above the suggestive significance threshold (P = 5.00E-07) from the GWAS results. For YFD and YGFW traits, 7 and 9 SNPs reached the genome-wise significance thresholds, whereas 10 and 12 SNPs reached the suggestive significance threshold, respectively. For YSL and YCFR traits, none of the SNPs reached the genome-wise significance thresholds, whereas 57 SNPs exceeded the suggestive significance threshold. We recorded 14 genes located at the region of ±50-kb near the genome-wise significant SNPs and 59 genes located at the region of ±50-kb near the suggestive significant SNPs. Meanwhile, we used the Average Information Restricted Maximum likelihood algorithm (AI-REML) in the “HIBLUP” package to estimate the heritability and variance components of the four desired yearling wool traits. The estimated heritability values (h²) of YSL, YFD, YGFW, and YCFR were 0.6208, 0.7460, 0.6758, and 0.5559, respectively. We noted that the genetic parameters in this study can be used for fine-wool sheep breeding. The newly detected significant SNPs and the newly identified candidate genes in this study would enhance our understanding of yearling wool formation, and significant SNPs can be applied to genome selection in fine-wool sheep breeding.

A conditional multi-trait sequence GWAS discovers pleiotropic candidate genes and variants for sheep wool, skin wrinkle and breech cover traits

Background

Imputation to whole-genome sequence is now possible in large sheep populations. It is therefore of interest to use this data in genome-wide association studies (GWAS) to investigate putative causal variants and genes that underpin economically important traits. Merino wool is globally sought after for luxury fabrics, but some key wool quality attributes are unfavourably correlated with the characteristic skin wrinkle of Merinos. In turn, skin wrinkle is strongly linked to susceptibility to “fly strike” (Cutaneous myiasis), which is a major welfare issue. Here, we use whole-genome sequence data in a multi-trait GWAS to identify pleiotropic putative causal variants and genes associated with changes in key wool traits and skin wrinkle.

Results

A stepwise conditional multi-trait GWAS (CM-GWAS) identified putative causal variants and related genes from 178 independent quantitative trait loci (QTL) of 16 wool and skin wrinkle traits, measured on up to 7218 Merino sheep with 31 million imputed whole-genome sequence (WGS) genotypes. Novel candidate gene findings included the MAT1A gene that encodes an enzyme involved in the sulphur metabolism pathway critical to production of wool proteins, and the ESRP1 gene. We also discovered a significant wrinkle variant upstream of the HAS2 gene, which in dogs is associated with the exaggerated skin folds in the Shar-Pei breed.

Conclusions

The wool and skin wrinkle traits studied here appear to be highly polygenic with many putative candidate variants showing considerable pleiotropy. Our CM-GWAS identified many highly plausible candidate genes for wool traits as well as breech wrinkle and breech area wool cover.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-021-00651-0.

Integration of a single-step genome-wide association study with a multi-tissue transcriptome analysis provides novel insights into the genetic basis of wool and weight traits in sheep

BACKGROUND

Genetic improvement of wool and growth traits is a major goal in the sheep industry, but their underlying genetic architecture remains elusive. To improve our understanding of these mechanisms, we conducted a weighted single-step genome-wide association study (WssGWAS) and then integrated the results with large-scale transcriptome data for five wool traits and one growth trait in Merino sheep: mean fibre diameter (MFD), coefficient of variation of the fibre diameter (CVFD), crimp number (CN), mean staple length (MSL), greasy fleece weight (GFW), and live weight (LW).

RESULTS

Our dataset comprised 7135 individuals with phenotype data, among which 1217 had high-density (HD) genotype data (n = 372,534). The genotypes of 707 of these animals were imputed from the Illumina Ovine single nucleotide polymorphism (SNP) 54 BeadChip to the HD Array. The heritability of these traits ranged from 0.05 (CVFD) to 0.36 (MFD), and between-trait genetic correlations ranged from - 0.44 (CN vs. LW) to 0.77 (GFW vs. LW). By integrating the GWAS signals with RNA-seq data from 500 samples (representing 87 tissue types from 16 animals), we detected tissues that were relevant to each of the six traits, e.g. liver, muscle and the gastrointestinal (GI) tract were the most relevant tissues for LW, and leukocytes and macrophages were the most relevant cells for CN. For the six traits, 54 quantitative trait loci (QTL) were identified covering 81 candidate genes on 21 ovine autosomes. Multiple candidate genes showed strong tissue-specific expression, e.g. BNC1 (associated with MFD) and CHRNB1 (LW) were specifically expressed in skin and muscle, respectively. By conducting phenome-wide association studies (PheWAS) in humans, we found that orthologues of several of these candidate genes were significantly (FDR < 0.05) associated with similar traits in humans, e.g. BNC1 was significantly associated with MFD in sheep and with hair colour in humans, and CHRNB1 was significantly associated with LW in sheep and with body mass index in humans.

CONCLUSIONS

Our findings provide novel insights into the biological and genetic mechanisms underlying wool and growth traits, and thus will contribute to the genetic improvement and gene mapping of complex traits in sheep.

Effects of Nano-copper on Antioxidant Function in Copper-Deprived Guizhou Black Goats

Guizhou black goats are essential to the production system in the Wumeng prairie in the Western China. This study aimed to determine the influence of nano-copper on antioxidant system in copper-deprived Guizhou black goats. We analyzed mineral contents in soil, forage, and goats' tissues. Blood parameters were also determined. The results showed that copper concentrations in soil and forage were significantly lower, and the iron content was significantly higher in affected compared with healthy area (P < 0.01). Copper concentrations in animal tissues (blood, liver, and hair) were significantly lower and iron content was significantly higher in affected compared with healthy goats (P < 0.01). After supplementation of nano-copper or copper sulfate, copper concentration in blood was significantly increased and iron content was significantly lower (P < 0.01). Compared with nano-copper group, the effect of copper sulfate was slower. Hemoglobin levels, erythrocyte count, and packed cell volume from nano-copper and copper sulfate groups were significantly higher than those in copper-deprived goats (P < 0.01). Compared with the copper-deprived Guizhou black goats, serum ceruloplasmin levels in nano-copper and copper sulfate groups were significantly increased, while serum lactate dehydrogenase, aspartate aminotransferase, alanine aminotransferase, alkaline phosphatase, and creatinine were significantly decreased (P < 0.01). Compared with the copper-deprived animals, serum superoxide dismutase, glutathione peroxidase, catalase, and total antioxidant capacity in nano-copper and copper sulfate groups were significantly higher, while serum malondialdehyde content was significantly lower (P < 0.01). The effect of copper sulfate group was significantly lower than that in nano-copper group (P < 0.01). Consequently, nano-copper could not only markedly increase the copper content in blood in copper-deprived Guizhou black goats but also much improves the antioxidant capacity.

The climatic and genetic heritage of Italian goat breeds with genomic SNP data

Local adaptation of animals to the environment can abruptly become a burden when faced with rapid climatic changes such as those foreseen for the Italian peninsula over the next 70 years. Our study investigates the genetic structure of the Italian goat populations and links it with the environment and how genetics might evolve over the next 50 years. We used one of the largest national datasets including > 1000 goats from 33 populations across the Italian peninsula collected by the Italian Goat Consortium and genotyped with over 50 k markers. Our results showed that Italian goats can be discriminated in three groups reflective of the Italian geography and its geo-political situation preceding the country unification around two centuries ago. We leveraged the remarkable genetic and geographical diversity of the Italian goat populations and performed landscape genomics analysis to disentangle the relationship between genotype and environment, finding 64 SNPs intercepting genomic regions linked to growth, circadian rhythm, fertility, and inflammatory response. Lastly, we calculated the hypothetical future genotypic frequencies of the most relevant SNPs identified through landscape genomics to evaluate their long-term effect on the genetic structure of the Italian goat populations. Our results provide an insight into the past and the future of the Italian local goat populations, helping the institutions in defining new conservation strategy plans that could preserve their diversity and their link to local realities challenged by climate change.

Identification of genes associated with litter size combining genomic approaches in Luzhong mutton sheep

Litter size is one of the most important reproductive traits of sheep, which has pronounced effects on the profit of husbandry enterprises and enthusiasm of breeders. Despite the importance of litter size, the underlying genetic mechanisms have not been entirely elucidated. Therefore, based on a high-density SNP chip, genome-wide comparative analysis was performed between two groups with different fecundity to reveal candidate genes linked to litter size via detection of homozygosity and selection signatures in Luzhong mutton sheep. Consequently, nine promising genes were identified from six runs of homozygosity islands, and functionally linked to reproduction (ACTL7A, ACTL7B, and ELP1), embryonic development (KLF5 and PIBF1), and cell cycle (DACH1, BORA, DIS3, and MZT1). A total of 128 genes were observed under selection, of which HECW1 and HTR1E were related to total lambs born, GABRG3, LRP1B, and MACROD2 to teat number, and AGBL1 to reproductive seasonality. Additionally, the presence of inbreeding depression implies the urgency of reasonable mating system to increase litter size in the present herd. These findings provide a comprehensive insight to the genetic makeup of litter size, and also contribute to implementation of marker-assisted selection in sheep.

Genome-Wide Association Study Identifies New Candidate Markers for Somatic Cells Score in a Local Dairy Sheep

In the Mediterranean basin countries, the dairy sheep production is usually based on local breeds, which are very well-adapted to their production systems and environments and can indeed guarantee income, employment, and economic viability in areas where production alternatives are scarce or non-existent. Mastitis is still one of the greatest problems affecting commercial milk production. However, genetic evaluation of mastitis is particularly difficult because of its low heritability and the categorical nature of the trait. The aim of this study was to identify genomic regions putatively associated with somatic cells count (SCC) in the local economically important Valle del Belice sheep breed using of deregressed breeding values (DEBV) as response variables. All the samples were genotyped using the Illumina OvineSNP50K BeadChip. Genome-wide association analysis was carried out based on regression of DEBV. A total of eight markers were found to be significantly associated with log-transformed SCC. Several candidate genes associated with SCC were identified related to immunity system and udder conformation. The results can help improving the competitiveness of the local Valle del Belìce breed. Further studies considering a higher sample size or independent population will be needed to confirm our results.

Genome-wide association studies detects candidate genes for wool traits by re-sequencing in Chinese fine-wool sheep

BACKGROUND

The quality and yield of wool determine the economic value of the fine-wool sheep. Therefore, discovering markers or genes relevant to wool traits is the cornerstone for the breeding of fine-wool sheep. In this study, we used the Illumina HiSeq X Ten platform to re-sequence 460 sheep belonging to four different fine-wool sheep breeds, namely, Alpine Merino sheep (AMS), Chinese Merino sheep (CMS), Aohan fine-wool sheep (AHS) and Qinghai fine-wool sheep (QHS). Eight wool traits, including fiber diameter (FD), fiber diameter coefficient of variance (FDCV), fiber diameter standard deviation (FDSD), staple length (SL), greasy fleece weight (GFW), clean wool rate (CWR), staple strength (SS) and staple elongation (SE) were examined. A genome-wide association study (GWAS) was performed to detect the candidate genes for the eight wool traits.

RESULTS

A total of 8.222 Tb of raw data was generated, with an average of approximately 8.59X sequencing depth. After quality control, 12,561,225 SNPs were available for analysis. And a total of 57 genome-wide significant SNPs and 30 candidate genes were detected for the desired wool traits. Among them, 7 SNPs and 6 genes are related to wool fineness indicators (FD, FDCV and FDSD), 10 SNPs and 7 genes are related to staple length, 13 SNPs and 7 genes are related to wool production indicators (GFW and CWR), 27 SNPs and 10 genes associated with staple elongation. Among these candidate genes, UBE2E3 and RHPN2 associated with fiber diameter, were found to play an important role in keratinocyte differentiation and cell proliferation. Gene ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment results, revealed that multitude significant pathways are related to keratin and cell proliferation and differentiation, such as positive regulation of canonical Wnt signaling pathway (GO:0090263).

CONCLUSION

This is the first GWAS on the wool traits by using re-sequencing data in Chinese fine-wool sheep. The newly detected significant SNPs in this study can be used in genome-selective breeding for the fine-wool sheep. And the new candidate genes would provide a good theoretical basis for the fine-wool sheep breeding.

A global analysis of CNVs in Chinese indigenous fine-wool sheep populations using whole-genome resequencing

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.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12864-021-07387-7.

Candidate genes for productivity identified by genome-wide association study with indicators of class in the Russian meat merino sheep breed

Genome-wide association studies allow identification of loci and polymorphisms associated with the formation of relevant phenotypes. When conducting a full genome analysis of sheep, particularly promising is the study of individuals with outstanding productivity indicators – exhibition animals, representatives of the super-elite class. The aim of this study was to identify new candidate genes for economically valuable traits based on the search for single nucleotide polymorphisms (SNPs) associated with belonging to different evaluation classes in rams of the Russian meat merino breed. Animal genotyping was performed using Ovine Infinium HD BeadChip 600K DNA, association search was performed using PLINK v. 1.07 software. Highly reliable associations were found between animals belonging to different evaluation classes and the frequency of occurrence of individual SNPs on chromosomes 2, 6, 10, 13, and 20. Most of the substitutions with high association reliability are concentrated on chromosome 10 in the region 10: 30859297–31873769. To search for candidate genes, 15 polymorphisms with the highest association reliability were selected (–log10(р) > 9). Determining the location of the analyzed SNPs relative to the latest annotation Oar_rambouillet_v1.0 allowed to identify 11 candidate genes presumably associated with the formation of a complex of phenotypic traits of animals in the exhibition group: RXFP2, ALOX5AP, MEDAG, OPN5, PRDM5, PTPRT, TRNAS-GGA, EEF1A1, FRY, ZBTB21-like, and B3GLCT-like. The listed genes encode proteins involved in the control of the cell cycle and DNA replication, regulation of cell proliferation and apoptosis, lipid and carbohydrate metabolism, the development of the inflammatory process and the work of circadian rhythms. Thus, the candidate genes under consideration can influence the formation of exterior features and productive qualities of sheep. However, further research is needed to confirm the influence of genes and determine the exact mechanisms for implementing this influence on the phenotype.

Genome-Wide Association Study Using Individual Single-Nucleotide Polymorphisms and Haplotypes for Erythrocyte Traits in Alpine Merino Sheep

Adaptation to high-altitude hypoxia is essential for domestic animals, such as yak, Tibetan chicken, and Tibetan sheep, living on high plateaus, as it ensures efficient oxygen absorption and utilization. Red blood cells are the primary medium for transporting oxygen in the blood. However, little is known about the genetic mechanism of erythrocyte traits. Genome-wide association studies (GWASs) based on single markers or haplotypes have identified potential mechanisms for genetic variation and quantitative traits. To identify loci associated with erythrocyte traits, we performed a GWAS based on the method of the single marker and haplotype in 498 Alpine Merino sheep for six erythrocyte traits: red blood cell count (RBC), hemoglobin (HGB), hematocrit (HCT), mean corpuscular hemoglobin (MCH), mean corpuscular hemoglobin concentration (MCHC), and RBC volume distribution width coefficient of variation (RWD_CV). Forty-two significant single-nucleotide polymorphisms (SNPs) associated with the six erythrocyte traits were detected by means of a single-marker GWAS, and 34 significant haplotypes associated with five erythrocyte traits were detected by means of haplotype analysis. We identified six genes (DHCR24, SPATA9, FLI1, PLCB1, EFNB2, and SH2B3) as potential genes of interest via gene function annotations, location, and expression variation. In particular, FLI1 and PLCB1 were associated with hematopoiesis and erythropoiesis, respectively. These results provide a theoretical basis for analyzing erythrocyte traits and high-altitude hypoxia adaptation in Alpine Merino sheep and will be a useful reference for future studies of plateau-dwelling livestock.

Whole-genome resequencing of wild and domestic sheep identifies genes associated with morphological and agronomic traits

Understanding the genetic changes underlying phenotypic variation in sheep (Ovis aries) may facilitate our efforts towards further improvement. Here, we report the deep resequencing of 248 sheep including the wild ancestor (O. orientalis), landraces, and improved breeds. We explored the sheep variome and selection signatures. We detected genomic regions harboring genes associated with distinct morphological and agronomic traits, which may be past and potential future targets of domestication, breeding, and selection. Furthermore, we found non-synonymous mutations in a set of plausible candidate genes and significant differences in their allele frequency distributions across breeds. We identified PDGFD as a likely causal gene for fat deposition in the tails of sheep through transcriptome, RT-PCR, qPCR, and Western blot analyses. Our results provide insights into the demographic history of sheep and a valuable genomic resource for future genetic studies and improved genome-assisted breeding of sheep and other domestic animals.

The functions of ocu-miR-205 in regulating hair follicle development in Rex rabbits

BACKGROUND

Hair follicles are an appendage of the vertebrate epithelium in the skin that arise from the embryonic ectoderm and regenerate cyclically during adulthood. Dermal papilla cells (DPCs) are the key dermal component of the hair follicle that directly regulate hair follicle development, growth and regeneration. According to recent studies, miRNAs play an important role in regulating hair follicle morphogenesis and the proliferation, differentiation and apoptosis of hair follicle stem cells.

RESULTS

The miRNA expression profile of the DPCs from Rex rabbits with different hair densities revealed 240 differentially expressed miRNAs (|log2(HD/LD)| > 1.00 and Q-value≤0.001). Among them, ocu-miR-205-5p was expressed at higher levels in DPCs from rabbits with low hair densities (LD) than in rabbits with high hair densities (HD), and it was expressed at high levels in the skin tissue from Rex rabbits (P < 0.05). Notably, ocu-miR-205 increased cell proliferation and the cell apoptosis rate, altered the progression of the cell cycle (P < 0.05), and modulated the expression of genes involved in the PI3K/Akt, Wnt, Notch and BMP signalling pathways in DPCs and skin tissue from Rex rabbits. It also inhibited the phosphorylation of the CTNNB1 and GSK-3β proteins, decreased the level of the noggin (NOG) protein, and increased the level of phosphorylated Akt (P < 0.05). A significant change in the primary follicle density was not observed (P > 0.05), but the secondary follicle density and total follicle density (P < 0.05) were altered upon interference with ocu-miR-205-5p expression, and the secondary/primary ratio (S/P) in the ocu-miR-205-5p interfered expression group increased 14 days after the injection (P < 0.05).

CONCLUSIONS

In the present study, ocu-miR-205 promoted the apoptosis of DPCs, altered the expression of genes and proteins involved in the PI3K/Akt, Wnt, Notch and BMP signalling pathways in DPCs and skin from Rex rabbits, promoted the transition of hair follicles from the growth phase to the regression and resting phase, and altered the hair density of Rex rabbits.

The Effect of Integrating Genomic Information into Genetic Evaluations of Chinese Merino Sheep

Simple Summary

Genetic improvement of wool production and quality traits in fine-wool sheep is an appealing option for enhancing the market value of wool products. We estimated genetic parameters and the accuracies of estimated breeding values for various wool production and quality traits in fine-wool sheep using pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) strategies. ssGBLUP performed slightly better than PBLUP for the studied traits. Therefore, the single-step genetic evaluation method could be successfully implemented in genomic evaluations of fine-wool sheep and the prediction of future breeding values in young Merino sheep as part of an early preselection strategy in the near future.

Abstract

Genomic evaluations are a method for improving the accuracy of breeding value estimation. This study aimed to compare estimates of genetic parameters and the accuracy of breeding values for wool traits in Merino sheep between pedigree-based best linear unbiased prediction (PBLUP) and single-step genomic best linear unbiased prediction (ssGBLUP) using Bayesian inference. Data were collected from 28,391 yearlings of Chinese Merino sheep (classified in 1992–2018) at the Xinjiang Gonaisi Fine Wool Sheep-Breeding Farm, China. Subjectively-assessed wool traits, namely, spinning count (SC), crimp definition (CRIM), oil (OIL), and body size (BS), and objectively-measured traits, namely, fleece length (FL), greasy fleece weight (GFW), mean fiber diameter (MFD), crimp number (CN), and body weight pre-shearing (BWPS), were analyzed. The estimates of heritability for wool traits were low to moderate. The largest h² values were observed for FL (0.277) and MFD (0.290) with ssGBLUP. The heritabilities estimated for wool traits with ssGBLUP were slightly higher than those obtained with PBLUP. The accuracies of breeding values were low to moderate, ranging from 0.362 to 0.573 for the whole population and from 0.318 to 0.676 for the genotyped subpopulation. The correlation between the estimated breeding values (EBVs) and genomic EBVs (GEBVs) ranged from 0.717 to 0.862 for the whole population, and the relative increase in accuracy when comparing EBVs with GEBVs ranged from 0.372% to 7.486% for these traits. However, in the genotyped population, the rank correlation between the estimates obtained with PBLUP and ssGBLUP was reduced to 0.525 to 0.769, with increases in average accuracy of 3.016% to 11.736% for the GEBVs in relation to the EBVs. Thus, genomic information could allow us to more accurately estimate the relationships between animals and improve estimates of heritability and the accuracy of breeding values by ssGBLUP.

Review on Genomic Regions and Candidate Genes Associated with Economically Important Production and Reproduction Traits in Sheep (Ovies aries)

Sheep (Ovis aries) is one of the most economically, culturally, and socially important domestic animals. They are reared primarily for meat, milk, wool, and fur production. Sheep were reared using natural selection for a long period of time to offer these traits. In fact, this production system has been slowing the productivity and production potential of the sheep. To improve production efficiency and productivity of this animal through genetic improvement technologies, understanding the genetic background of traits such as body growth, weight, carcass quality, fat percent, fertility, milk yield, wool quality, horn type, and coat color is essential. With the development and utilization of animal genotyping technologies and gene identification methods, many functional genes and genetic variants associated with economically important phenotypic traits have been identified and annotated. This is useful and presented an opportunity to increase the pace of animal genetic gain. Quantitative trait loci and genome wide association study have been playing an important role in identifying candidate genes and animal characterization. This review provides comprehensive information on the identified genomic regions and candidate genes associated with production and reproduction traits, and gene function in sheep.

A Combined Multi-Cohort Approach Reveals Novel and Known Genome-Wide Selection Signatures for Wool Traits in Merino and Merino-Derived Sheep Breeds

Merino sheep represents a valuable genetic resource worldwide. In this study, we investigated selection signatures in Merino (and Merino-derived) sheep breeds using genome-wide SNP data and two different approaches: a classical FST-outlier method and an approach based on the analysis of local ancestry in admixed populations. In order to capture the most reliable signals, we adopted a combined, multi-cohort approach. In particular, scenarios involving four Merino breeds (Spanish Merino, Australian Merino, Chinese Merino, and Sopravissana) were tested via the local ancestry approach, while nine pair-wise breed comparisons contrasting the above breeds, as well as the Gentile di Puglia breed, with non-Merino breeds from the same geographic area were tested via the FST-outlier method. Signals observed using both methods were compared with genome-wide patterns of distribution of runs of homozygosity (ROH) islands. Novel and known selection signatures were detected. The most reliable signals were observed on OAR 3 (MSRB3 and LEMD3), OAR10 (FRY and RXFP2), OAR 13 (RALY), OAR17 (FAM101A), and OAR18 (NFKBIA, SEC23A, and PAX9). All the above overlapped with known QTLs for wool traits, and evidences from the literature of their involvement in skin/hair/wool biology, as well as gene network analysis, further corroborated these results. The signal on OAR10 also contains well known evidence for association with horn morphology and polledness. More elusive biological evidences of association with the Merino phenotype were observed for a number of other genes, notably LOC101120019 and TMEM132B (OAR17), LOC105609948 (OAR3), LOC101110773 (OAR10), and EIF2S2 (OAR17). Taken together, the above results further contribute to decipher the genetic basis underlying the Merino phenotype.

Genomic approaches to identify hybrids and estimate admixture times in European wildcat populations

The survival of indigenous European wildcat (Felis silvestris silvestris) populations can be locally threatened by introgressive hybridization with free-ranging domestic cats. Identifying pure wildcats and investigating the ancestry of admixed individuals becomes thus a conservation priority. We analyzed 63k cat Single Nucleotide Polymorphisms (SNPs) with multivariate, Bayesian and gene-search tools to better evaluate admixture levels between domestic and wild cats collected in Europe, timing and ancestry proportions of their hybrids and backcrosses, and track the origin (wild or domestic) of the genomic blocks carried by admixed cats, also looking for possible deviations from neutrality in their inheritance patterns. Small domestic ancestry blocks were detected in the genomes of most admixed cats, which likely originated from hybridization events occurring from 6 to 22 generations in the past. We identified about 1,900 outlier coding genes with excess of wild or domestic ancestry compared to random expectations in the admixed individuals. More than 600 outlier genes were significantly enriched for Gene Ontology (GO) categories mainly related to social behavior, functional and metabolic adaptive processes (wild-like genes), involved in cognition and neural crest development (domestic-like genes), or associated with immune system functions and lipid metabolism (parental-like genes). These kinds of genomic ancestry analyses could be reliably applied to unravel the admixture dynamics in European wildcats, as well as in other hybridizing populations, in order to design more efficient conservation plans.

High-density genotyping reveals signatures of selection related to acclimation and economically important traits in 15 local sheep breeds from Russia

Background

Domestication and centuries of selective breeding have changed genomes of sheep breeds to respond to environmental challenges and human needs. The genomes of local breeds, therefore, are valuable sources of genomic variants to be used to understand mechanisms of response to adaptation and artificial selection. As a step toward this we performed a high-density genotyping and comprehensive scans for signatures of selection in the genomes from 15 local sheep breeds reared across Russia.

Results

Results demonstrated that the genomes of Russian sheep breeds contain multiple regions under putative selection. More than 50% of these regions matched with intervals identified in previous scans for selective sweeps in sheep genomes. These regions contain well-known candidate genes related to morphology, adaptation, and domestication (e.g., KITLG, KIT, MITF, and MC1R), wool quality and quantity (e.g., DSG@, DSC@, and KRT@), growth and feed intake (e.g., HOXA@, HOXC@, LCORL, NCAPG, LAP3, and CCSER1), reproduction (e.g., CMTM6, HTRA1, GNAQ, UBQLN1, and IFT88), and milk-related traits (e.g., ABCG2, SPP1, ACSS1, and ACSS2). In addition, multiple genes that are putatively related to environmental adaptations were top-ranked in selected intervals (e.g., EGFR, HSPH1, NMUR1, EDNRB, PRL, TSHR, and ADAMTS5). Moreover, we observed that multiple key genes involved in human hereditary sensory and autonomic neuropathies, and genetic disorders accompanied with an inability to feel pain and environmental temperatures, were top-ranked in multiple or individual sheep breeds from Russia pointing to a possible mechanism of adaptation to harsh climatic conditions.

Conclusions

Our work represents the first comprehensive scan for signatures of selection in genomes of local sheep breeds from the Russian Federation of both European and Asian origins. We confirmed that the genomes of Russian sheep contain previously identified signatures of selection, demonstrating the robustness of our integrative approach. Multiple novel signatures of selection were found near genes which could be related to adaptation to the harsh environments of Russia. Our study forms a basis for future work on using Russian sheep genomes to spot specific genetic variants or haplotypes to be used in efforts on developing next-generation highly productive breeds, better suited to diverse Eurasian environments.

Electronic supplementary material

The online version of this article (10.1186/s12864-019-5537-0) contains supplementary material, which is available to authorized users.