Feed efficiency in dairy sheep: An insight from the milk transcriptome.

Introduction: As higher feed efficiency in dairy ruminants means a higher capability to transform feed nutrients into milk and milk components, differences in feed efficiency are expected to be partly linked to changes in the physiology of the mammary glands. Therefore, this study aimed to determine the biological functions and key regulatory genes associated with feed efficiency in dairy sheep using the milk somatic cell transcriptome. Material and methods: RNA-Seq data from high (H-FE, n = 8) and low (L-FE, n = 8) feed efficiency ewes were compared through differential expression analysis (DEA) and sparse Partial Least Square-Discriminant analysis (sPLS-DA). Results: In the DEA, 79 genes were identified as differentially expressed between both conditions, while the sPLS-DA identified 261 predictive genes [variable importance in projection (VIP) > 2] that discriminated H-FE and L-FE sheep. Discussion: The DEA between sheep with divergent feed efficiency allowed the identification of genes associated with the immune system and stress in L-FE animals. In addition, the sPLS-DA approach revealed the importance of genes involved in cell division (e.g., KIF4A and PRC1) and cellular lipid metabolic process (e.g., LPL, SCD, GPAM, and ACOX3) for the H-FE sheep in the lactating mammary gland transcriptome. A set of discriminant genes, commonly identified by the two statistical approaches, was also detected, including some involved in cell proliferation (e.g., SESN2, KIF20A, or TOP2A) or encoding heat-shock proteins (HSPB1). These results provide novel insights into the biological basis of feed efficiency in dairy sheep, highlighting the informative potential of the mammary gland transcriptome as a target tissue and revealing the usefulness of combining univariate and multivariate analysis approaches to elucidate the molecular mechanisms controlling complex traits.

Influence of a temporary restriction of dietary protein in prepubertal ewe lambs on first lactation milk traits and response to a mammary gland inflammatory challenge.

This study evaluated the influence of a temporary nutritional protein restriction (NPR) performed, under commercial conditions, in prepubertal female lambs on first lactation milk production traits and the inflammatory response triggered by an inflammatory challenge of the. From 40 Assaf female lambs, we defined a control group (Cn = 20), which received a standard diet for replacement lambs and the NPR group (n = 20), which received the same diet but without soybean meal between 3 and 5 months of age. About 150 days after lambing, 24 of these ewes (13 NPR, 11C) were subjected to an intramammary infusion of E. coli lipopolysaccharide (LPS). Our dynamic study identified indicator traits of local (SCC) and systemic (rectal Ta, IL-6, CXCL8, IL-10, IL-36RA, VEGF-A) response to the LPS challenge. The NPR did not show significant effects on milk production traits and did not affect the SCC and rectal Ta after the LPS challenge. However, the NPR had a significant influence on 8 of the 14 plasma biomarkers analysed, in all the cases with higher relative values in the C group. The effects observed on VEGF-A (involved in vasculogenesis during mammary gland development and vascular permeability) and IL-10 (a regulatory cytokine classically known by its anti-inflammatory action) are the most remarkable to explain the differences found between groups. Whereas further studies should be undertaken to confirm these results, our findings are of interest considering the current concern about the future world's demand for protein and the need for animal production systems to evolve toward sustainability.

Integrated analyses of the methylome and transcriptome to unravel sex differences in the perirenal fat from suckling lambs.

In sheep, differences were observed regarding fat accumulation and fatty acid (FA) composition between males and females, which may impact the quality and organoleptic characteristics of the meat. The integration of different omics technologies is a relevant approach for investigating biological and genetic mechanisms associated with complex traits. Here, the perirenal tissue of six male and six female Assaf suckling lambs was evaluated using RNA sequencing and whole-genome bisulfite sequencing (WGBS). A multiomic discriminant analysis using multiblock (s)PLS-DA allowed the identification of 314 genes and 627 differentially methylated regions (within these genes), which perfectly discriminate between males and females. These candidate genes overlapped with previously reported QTLs for carcass fat volume and percentage of different FAs in milk and meat from sheep. Additionally, differentially coexpressed (DcoExp) modules of genes between males (nine) and females (three) were identified that harbour 22 of these selected genes. Interestingly, these DcoExp were significantly correlated with fat percentage in different deposits (renal, pelvic, subcutaneous and intramuscular) and were associated with relevant biological processes for adipogenesis, adipocyte differentiation, fat volume and FA composition. Consequently, these genes may potentially impact adiposity and meat quality traits in a sex-specific manner, such as juiciness, tenderness and flavour.

Microbial community in resistant and susceptible Churra sheep infected by Teladorsagia circumcincta.

Gastrointestinal nematodes (GIN) are a major threat to health and welfare in small ruminants worldwide. Teladorsagia circumcincta is a nematode that inhabits the abomasum of sheep, especially in temperate regions, causing important economic losses. Given that T. circumcincta and microbiome share the same niche, interactions between them and the host are expected. Although it is known that within a sheep breed there are animals that are more resistant than others to infection by GIN, it is not known if the microbiome influences the phenotype of these animals. Under this condition, 12 sheep were classified according to their cumulative faecal egg count (cFEC) at the end of a first experimental infection, 6 as resistant group (RG) and 6 as susceptible group (SG) to T. circumcincta infection. Then, all sheep were experimentally infected with 70,000 L3 of T. circumcincta and at day 7 days post-infection were euthanized. At necropsy, gastric mucosa and gastric content from abomasum were collected to extract bacterial DNA and sequence V3-V4 region from 16S rRNA gene using Ilumina technology. After bioanalysis performed, results showed that α-diversity and ß-diversity remained similar in both groups. However, resistant phenotype sheep showed a higher number of bacteria butyrate-fermenting species as Clostridium sensu stricto 1 (abundance in RG: 1.29% and in SG: 0.069%; p = 0.05), and Turicibacter (abundance in RG: 0.31% and in SG: 0.027%; p = 0.07) in gastric content but also Serratia spp in gastric mucosa (abundance in RG: 0.12% and in SG: 0.041%; p = 0.07). A trend towards a significant negative correlation between cFEC and Clostridium sensu stricto 1 abundance in gastric content was detected (r = - 0.537; p = 0.08). These data suggest that microbiome composition could be another factor associated with the development of the resistant phenotype modifying the interaction with the host and the in last instance affecting the individual risk of infection.

Accuracy of Imputation of Microsatellite Markers from a 50K SNP Chip in Spanish Assaf Sheep.

Transitioning from traditional to new genotyping technologies requires the development of bridging methodologies to avoid extra genotyping costs. This study aims to identify the optimum number of single nucleotide polymorphisms (SNPs) necessary to accurately impute microsatellite markers to develop a low-density SNP chip for parentage verification in the Assaf sheep breed. The accuracy of microsatellite marker imputation was assessed with three metrics: genotype concordance (C), genotype dosage (length r2), and allelic dosage (allelic r2), for all imputation scenarios tested (0.5-10 Mb microsatellite flanking SNP windows). The imputation accuracy for the three metrics analyzed for all haplotype lengths tested was higher than 0.90 (C), 0.80 (length r2), and 0.75 (allelic r2), indicating strong genotype concordance. The window with 2 Mb length provides the best accuracy for the imputation procedure and the design of an affordable low-density SNP chip for parentage testing. We additionally evaluated imputation performance under two null models, naive (imputing the most common allele) and random (imputing by randomly selecting the allele), which in comparison showed weak genotype concordances (0.41 and 0.15, respectively). Therefore, we describe a precise methodology in the present article to impute multiallelic microsatellite genotypes from a low-density SNP chip in sheep and solve the problem of parentage verification when different genotyping platforms have been used across generations.

A multiple-phenotype imputation procedure as a method for prediction of cheese-making efficiency in Spanish Assaf sheep.

Sheep milk is mainly intended to manufacture a wide variety of high-quality cheeses. The ovine cheese industry would benefit from an improvement, through genetic selection, of traits related to the milk coagulation properties (MCPs) and cheese yield-related traits, broadly denoted as "cheese-making traits." Considering that routine measurements of these traits needed for genetic selection are expensive and time-consuming, this study aimed to evaluate the accuracy of a cheese-making phenotype imputation method based on the information from official milk control records combined with the pH of the milk. For this study, we analyzed records of milk production traits, milk composition traits, and measurements of cheese-making traits available from a total of 1,145 dairy ewes of the Spanish Assaf sheep breed. Cheese-making traits included five related to the MCPs and two cheese yield-related traits. The milk and cheese-making phenotypes were adjusted for significant effects based on a general linear model. The adjusted phenotypes were used to define a multiple-phenotype imputation procedure for the cheese-making traits based on multivariate normality and Markov chain Monte Carlo sampling. Five of the seven cheese-making traits considered in this study achieved a prediction accuracy of 0.60 computed as the correlation between the adjusted phenotypes and the imputed phenotypes. Particularly the logarithm of curd-firming time since rennet addition (logK20) (0.68), which has been previously suggested as a potential candidate trait to improve the cheese ability in this breed, and the logarithm of the ratio between the rennet clotting time and the curd firmness at 60 min (logRCT/A60) (0.65), which has been defined by other studies as an indicator trait of milk coagulation efficiency. This study represents a first step toward the possible use of the phenotype imputation of cheese-making traits to develop a practical methodology for the dairy sheep industry to impute cheese-making traits only based on the analysis of a milk sample without the need of pedigree information. This information could be also used in future planning of specific breeding programs considering the importance of the cheese-making efficiency in dairy sheep and highlights the potential of phenotype imputation to leverage sample size on expensive, hard-to-measure phenotypes.

Analysis of Whole Genome Resequencing Datasets from a Worldwide Sample of Sheep Breeds to Identify Potential Causal Mutations Influencing Milk Composition Traits.

Different studies have shown that polymorphisms in the sequence of genes coding for the milk proteins and milk fatty acids are associated with milk composition traits as well as with cheese-making traits. However, the lack of coincident results across sheep populations has prevented the use of this information in sheep breeding programs. The main objective of this study was to exploit the information derived from a total of 175 whole genome resequencing (WGR) datasets from 43 domestic sheep breeds and three wild sheep to evaluate the genetic diversity of 24 candidate genes for milk composition and identify genetic variants with a potential phenotypic effect. The functional annotation of the identified variants highlighted five single nucleotide polymorphisms (SNPs) predicted to have a high impact on the protein function and 42 missense SNPs with a putative deleterious effect. When comparing the allelic frequencies at these 47 polymorphisms with relevant functional effects between the genomes of Assaf and Churra sheep breeds, two missense deleterious variants were identified as potential markers associated to the milk composition differences found between the Churra and Assaf: XDH:92215727C>T and LALBA:137390760T>C. Future research is required to confirm the effect of the potential functionally relevant variants identified in the present study on milk composition and cheese-making traits.

The Milk Microbiota of the Spanish Churra Sheep Breed: New Insights into the Complexity of the Milk Microbiome of Dairy Species.

Milk from healthy animals has classically been considered a sterile fluid. With the development of massively parallel sequencing and its application to the study of the microbiome of different body fluids, milk microbiota has been documented in several animal species. In this study, the main objective of this work was to access bacterial profiles of healthy milk samples using the next-generation sequencing of amplicons from the 16S rRNA gene to characterise the milk microbiome of the Churra breed. A total of 212 samples were collected from two Churra dairy farms with a different management system. The core milk microbiota in Churra ewes includes lesser genera (only two taxa: Staphylococcus and Escherichia/Shigella) than studies reported in other dairy species or even in a previous study in Assaf sheep milk. We found that diversity values in the two flocks of Churra breed were lower than the diversity of the milk microbiota in Assaf. The non-metric multidimensional scaling (NMDS) ordination using Bray-Curtis distance separates samples based on their microbiota composition. The information reported here might be used to understand the complex issue of milk microbiota composition.

Gene Networks Driving Genetic Variation in Milk and Cheese-Making Traits of Spanish Assaf Sheep.

Most of the milk produced by sheep is used for the production of high-quality cheese. Consequently, traits related to milk coagulation properties and cheese yield are economically important to the Spanish dairy industry. The present study aims to identify candidate genes and their regulators related to 14 milk and cheese-making traits and to develop a low-density panel of markers that could be used to predict an individual's genetic potential for cheese-making efficiency. In this study, we performed a combination of the classical genome-wide association study (GWAS) with a stepwise regression method and a pleiotropy analysis to determine the best combination of the variants located within the confidence intervals of the potential candidate genes that may explain the greatest genetic variance for milk and cheese-making traits. Two gene networks related to milk and cheese-making traits were created using the genomic relationship matrices built through a stepwise multiple regression approach. Several co-associated genes in these networks are involved in biological processes previously found to be associated with milk synthesis and cheese-making efficiency. The methodology applied in this study enabled the selection of a co-association network comprised of 374 variants located in the surrounding of genes showing a potential influence on milk synthesis and cheese-making efficiency.

Microbiota characterization of sheep milk and its association with somatic cell count using 16s rRNA gene sequencing.

This work aimed to use 16S ribosomal RNA sequencing with the Illumina MiSeq platform to describe the milk microbiota from 50 healthy Assaf ewes. The global observed microbial community for clinically healthy milk samples analysed was complex and showed a vast diversity. The core microbiota of the sheep milk includes five genera: Staphylococcus, Lactobacillus, Corynebacterium, Streptococcus and Escherichia/Shigella. Although there are some differences, some of these genera are common with the microbiota core pattern of milk from other species, especially with dairy cows. The microbial composition of the studied samples, based on the definition of amplicon sequence variants, was analysed through a correlation network. A preliminary analysis by grouping the milk samples based on their somatic cell count (SCC), which is considered an indicator of subclinical mastitis (SM), showed certain differences for the core of the samples identified as SM. The differences in the microbiota diversity pattern among samples might also suggest that subclinical mastitis would be associated with the significant increase in some genera that are inhabitants of the mammary gland and a remarkable concomitant reduction in the microbial diversity. Additionally, we have also presented here a preliminary analysis to assess the impact of the sheep milk microbiome on SCC, as an indicator of subclinical mastitis. The results here reported provide a first characterization of the sheep milk microbiota and settle the basis for future studies in this field.

High-resolution analysis of selection sweeps identified between fine-wool Merino and coarse-wool Churra sheep breeds.

BACKGROUND: With the aim of identifying selection signals in three Merino sheep lines that are highly specialized for fine wool production (Australian Industry Merino, Australian Merino and Australian Poll Merino) and considering that these lines have been subjected to selection not only for wool traits but also for growth and carcass traits and parasite resistance, we contrasted the OvineSNP50 BeadChip (50 K-chip) pooled genotypes of these Merino lines with the genotypes of a coarse-wool breed, phylogenetically related breed, Spanish Churra dairy sheep. Genome re-sequencing datasets of the two breeds were analyzed to further explore the genetic variation of the regions initially identified as putative selection signals. RESULTS: Based on the 50 K-chip genotypes, we used the overlapping selection signals (SS) identified by four selection sweep mapping analyses (that detect genetic differentiation, reduced heterozygosity and patterns of haplotype diversity) to define 18 convergence candidate regions (CCR), five associated with positive selection in Australian Merino and the remainder indicating positive selection in Churra. Subsequent analysis of whole-genome sequences from 15 Churra and 13 Merino samples identified 142,400 genetic variants (139,745 bi-allelic SNPs and 2655 indels) within the 18 defined CCR. Annotation of 1291 variants that were significantly associated with breed identity between Churra and Merino samples identified 257 intragenic variants that caused 296 functional annotation variants, 275 of which were located across 31 coding genes. Among these, four synonymous and four missense variants (NPR2_His847Arg, NCAPG_Ser585Phe, LCORL_Asp1214Glu and LCORL_Ile1441Leu) were included. CONCLUSIONS: Here, we report the mapping and genetic variation of 18 selection signatures that were identified between Australian Merino and Spanish Churra sheep breeds, which were validated by an additional contrast between Spanish Merino and Churra genotypes. Analysis of whole-genome sequencing datasets allowed us to identify divergent variants that may be viewed as candidates involved in the phenotypic differences for wool, growth and meat production/quality traits between the breeds analyzed. The four missense variants located in the NPR2, NCAPG and LCORL genes may be related to selection sweep regions previously identified and various QTL reported in sheep in relation to growth traits and carcass composition.