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Abstract 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 β-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.

IntroductionAs 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 methodsRNA-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).ResultsIn 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.DiscussionThe 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.

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.

Abstract 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.

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.

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.

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.