Assessment of milk metabolites as biomarkers for predicting feed efficiency in dairy sheep.

Estimating feed efficiency (FE) in dairy sheep is challenging due to the high cost of systems that measure individual feed intake. Identifying proxies that can serve as effective predictors of FE could make it possible to introduce FE into breeding programs. Here, 39 Assaf ewes in first lactation were evaluated regarding their FE by 2 metrics, residual feed intake (RFI) and feed conversion ratio (FCR). The ewes were classified into high, medium and low groups for each metric. Milk samples of the 39 ewes were subjected to untargeted metabolomics analysis. The complete milk metabolomic signature was used to discriminate the FE groups using partial least squares discriminant analysis. A total of 41 and 26 features were selected as the most relevant features for the discrimination of RFI and FCR groups, respectively. The predictive ability when utilizing the complete milk metabolomic signature and the reduced data sets were investigated using 4 machine learning (ML) algorithms and a multivariate regression method. The orthogonal partial least squares algorithm outperformed other ML algorithms for FCR prediction in the scenarios using the complete milk metabolite signature (R2 = 0.62 ± 0.06) and the 26 selected features (R2 = 0.62 ± 0.15). Regarding RFI predictions, the scenarios using the 41 selected features outperformed the scenario with the complete milk metabolite signature, where the multilayer feedforward artificial neural network (R2 = 0.18 ± 0.14) and extreme gradient boosting (R2 = 0.17 ± 0.15) outperformed other algorithms. The functionality of the selected metabolites implied that the metabolism of glucose, galactose, fructose, sphingolipids, amino acids, insulin, and thyroid hormones was at play. Compared with the use of traditional methods, practical applications of these biomarkers might simplify and reduce costs in selecting feed-efficient ewes.

Genetic parameters of milk mid-infrared spectra and their genetic relationships with milk production and feed efficiency traits in French Lacaune dairy sheep.

In French dairy sheep, Fourier transform infrared (FTIR) milk spectral data routinely predict the major milk components used in national genetic evaluations. The direct influence of genetic and environmental factors on milk FTIR spectra has been widely studied in dairy cattle, and relatively little in dairy ewes. In this study, 36,873 milk test-day records were available for 4,712 French Lacaune ewes farmed on 8 commercial farms. Our main goals were to provide the first description of spectral data and estimate the genetic parameters of French Lacaune dairy sheep during lactation. Principal component analysis (PCA) results demonstrated the impact of the lactation period on specific wavenumbers, allowing the identification of FTIR spectra collected at early (mo 2-4) and late (mo 5-7) lactation stages. The average estimated heritability (±mean SE) of the FTIR milk spectra from 2,971 to 926 cm-1 (446 wavenumbers) was 0.29 ± 0.02, ranging from 0.13 ± 0.01 to 0.42 ± 0.02. Furthermore, the heritabilities of spectra collected at the beginning or end of lactation changed at each point of the spectrum. However, at each wavenumber, the genomic correlation of transmittance values between these 2 lactation periods was high (>0.77), indicating the absence of a genotype-environment interaction. The genomic correlations between spectral regions and milk production traits (i.e., daily milk yield, fat and protein content, somatic cell score) varied from moderate to high. The results suggested that the most heritable areas of the spectrum were also genetically associated with dairy traits. Finally, the genomic correlations observed between the ewes' feed efficiency traits and the FTIR spectrum were moderate to high, while the genomic correlations between the change in body condition score and spectral data were rather low to moderate. This study confirmed that spectral data from Lacaune ewe milk were heritable, evolved phenotypically and genetically during lactation and were genetically correlated with traits included in breeding goals or traits of interest to the dairy industry.

First report of eprinomectin-resistant isolates of Haemonchus contortus in 5 dairy sheep farms from the Pyrénées Atlantiques département in France.

Infection of sheep by gastrointestinal nematodes (GIN) in pastoral systems such as those found in the South Western area of France, the Pyrénées Atlantiques, is one of the main reasons for economic loss and degradation of their welfare. In the present study, the efficacy of eprinomectin (EPN) was monitored on farms from this area following suspicion of lack of anthelmintic efficacy. Suspicions were raised by veterinarians, based on clinical signs ranging from milk and body condition loss, to anaemia, and mortality. Resistance was evaluated according to the World Association for the Advancement for Veterinary Parasitology (WAAVP) guidelines using fecal egg count reduction tests reinforced by individual analysis of drug concentration in the serum of all treated ewes by high-performance liquid chromatography (HPLC). EPN was administered by subcutaneous (SC) and topical (T) route according to manufacturer's requirements, as well as by the oral route (O) with the topical solution according to off-labelled practices in the field. For the first time in France, the presence of resistant isolates of Haemonchus contortus to EPN was observed in 5 dairy sheep farms. The HPLC dosages showed exposure of worms to concentrations compatible with anthelmintic activity for animals treated by the SC and O routes. By contrast, they showed under exposure to the drug of most individuals treated by the T route. EPN is the only null milk withdrawal anthelmintic molecule currently available. The presence of resistant isolates of the pathogenic H. contortus to EPN in this important dairy region requires an urgent change in grazing, and sometimes production, systems.

Alternative hormone-free reproduction management of a dairy sheep flock disrupts the farm's annual feeding system calendar and its associated strategies.

Hormone-free (HF) reproduction in dairy sheep is a way to meet current societal demands, but it requires being prepared for collateral impacts on related system components. The efficiency of HF practices (e.g., using the male effect for estrus induction and synchronization) is uncertain compared with hormonal treatment (HT). For example, these practices can lead to higher variability in the flock physiological stage patterns throughout the year, which has direct consequences for feeding regimens. The objective of this work was to simulate the impacts of HF reproduction management, including artificial insemination (AI), on the temporal distribution of productive performance and nutritional requirements of a conventional dairy sheep flock. Using the REPROsheep2.0 model, 6 scenarios were compared over one typical production season for the same flock (n = 597 Lacaune ewes) intensively reared in the Roquefort region of France. These scenarios depicted reproduction with HT and AI in mid-May (Early); HT and AI in July (Summer Late); HT and AI in November (Autumn Late); and their HF versions (HF-Early; HF-Summer Late, and HF-Autumn Late, respectively). In all HF scenarios, a reduction in the number of ewes lambing and consequently in the annual milk production of the farm was observed (-1 to -7%). This affected annual performance with a subsequent decrease of total annual nutritional requirements (-2 to -6%). The HF scenarios resulted in a staggering of lambing events with a 7- to 14-d shift in the appearance of milk production peaks and related nutritional requirements compared with the HT scenarios. Transitioning from conventional to HF reproduction management, while preserving AI, would increase farm workload, lengthen milking period operations, and necessitate a readjustment of feeding management strategies with regard to available feed resources. Depending on the production season, the observed delay in the distribution of nutritional requirements could be either an attractive or an unfavorable outcome for farmers. The delay may be concordant, for example, with the recently observed impacts of climate change on seasonal forage availability in Mediterranean regions (less spring herbage production and warmer temperatures) that are affecting farmers' decision-making about the most efficient use of forage and feed resources.

Microbiability of milk composition and genetic control of microbiota effects in sheep.

Recently, high-dimensional omics data are becoming available in larger quantities, and models have been developed that integrate them with genomics to understand in finer detail the relationship between genotype and phenotype, and thus improve the performance of genetic evaluations. Our objectives are to quantify the effect of the inclusion of microbiome data in the genetic evaluation for dairy traits in sheep, through the estimation of the heritability, microbiability, and how the microbiome effect on dairy traits decomposes into genetic and nongenetic parts. In this study we analyzed milk and rumen samples of 795 Lacaune dairy ewes. We included, as phenotype, dairy traits and milk fatty acids and proteins composition; as omics measurements, 16S rRNA rumen bacterial abundances; and as genotyping, 54K SNP chip for all ewes. Two nested genomic models were used: a first model to predict the individual contributions of the genetic and microbial abundances to phenotypes, and a second model to predict the additive genetic effect of the microbial community. In addition, microbiome-wide association studies for all dairy traits were applied using the 2,059 rumen bacterial abundances, and the genetic correlations between microbiome principal components and dairy traits were estimated. Results showed that in general the inclusion of both genetic and microbiome effect did not improve the fit of the model compared with the model with the genetic effect only. In addition, for all dairy traits the total heritability was equal to the direct heritability after fitting microbiota effects, due to a microbiability being almost zero for most dairy traits and heritability of the microbial community was very close to zero. Microbiome-wide association studies did not show operational taxonomic units with major effect for any of the dairy traits evaluated, and the genetic correlations between the first 5 principal components and dairy traits were low to moderate. So far, we can conclude that, using a substantial data set of 795 Lacaune dairy ewes, rumen bacterial abundances do not provide improved genetic evaluation for dairy traits in sheep.

Evaluation of Streptococcus species isolated from subclinical sheep mastitis by molecular methods and determination of virulence factors and antimicrobial resistance genes.

Streptococcus (S.) species are important pathogens that cause mastitis in sheep. The study aimed to examine Streptococcus species in sheep milk with subclinical mastitis, assessing their prevalence, antimicrobial resistance, and virulence genes. A total of 200 milk samples were collected from sheep farms in Izmir's five districts. Out of 32 (28.6%) Streptococcus isolates identified by phenotypic methods, 25 were genotypically identified as S. uberis, 5 as S. agalactiae, and 2 as S. dysgalactiae. Disk diffusion was used to determine the antimicrobial resistance of the isolates. PCR was employed to identify antimicrobial resistance and virulence genes in the isolates. The highest resistance was found for cloxacillin (100%), and the highest sensitivity was found for florfenicol (84%). The most common resistance gene combination was tetM+tetS (3/32) for S. uberis in 9.4%. A total of five virulence genes were detected. GapC+sua (56.2%) constituted the most common gene pattern. The highest virulence gene gapC was detected in 78.1% (25/32) of the isolates. The cylE gene was not detected (0%) in the isolates. Streptococcus species may play a role in mastitis in sheep, emphasising the need for meticulous hygienic milking practices.

Oar-miR-16b and oar-miR-27a: negatively correlated with milk yield and milk protein in sheep.

The characterization of miRNAs from sheep milk and their effect on milk yield and composition in sheep are remain unclear. Therefore, the aim of this study was to determine the expression pattern of several important miRNAs, which are associated with lactation in the sheep milk between high and low lactating-yield ewe groups. In addition to experimentally obtained miRNA expression results, the miRNA target genes were determined by bioinformatics analysis to identify biological pathways involved. miRNAs found to differ significantly in the expression level between the groups were oar-miR-181a, oar-miR-23a, oar-miR-27a, oar-miR-16b and oar-miR-374. Also, oar-miR-27a was shown negative correlation with milk protein and lactose contents while oar-miR-16b was shown negative correlation with milk yield in the high milk yield group. The highest connected hub genes for miR-27a target genes were determined as MAPK14 and PPARG. Also, six genes (HSPA4L, DNAJA2, ATP6V1B2, PPP2R1A, PPP2R1B, and PRKAR2A) were detected as hub genes for miR-16b. In this study, the relationship between expression profiles of several important miRNAs in sheep milk and milk yield and milk composition were investigated for the first time in high and low lactating yield groups.

Identification and bioactivity evaluation of flavan-3-ols in the milk of dairy sheep fed Cynomorium songaricum.

Cynomorium songaricum is a traditional medicine and also a food material that is eaten raw or processed as tea or beverages. As a featured plant in semi-desert grasslands, C. songaricum is also eaten by the cattle and sheep in the area. This research study fed dairy sheep C. songaricum to determine the flavan-3-ols in sheep milk. Catechin (Cat), epicatechin (Epi), procyanidin A1 (A1), procyanidin A2 (A2), and procyanidin B1 (B1) were detected in sheep milk with the concentration being Epi > A2 > Cat > B1 > A1 at 24 h after the administration of C. songaricum. Neither A1 nor A2 were detected in the methanol extract of C. songaricum. Cysteine degradation of the plant revealed that in addition to Epi, A2 was the extending unit of the polymeric flavan-3-ols in C. songaricum, indicating that A2 is released digestively from the polymers and enters the milk. Procyanidin B-1 was converted to A1 on incubation in raw but not heated milk, indicating that the A1 in milk is the enzymatically transformed product of B1. Accelerated oxidation showed that the flavan-3-ols, B1, Cat, and Epi significantly protects the unsaturated triacyglycerols in the milk from oxidation. The flavan-3-ol could slow down the oxidation of glutathione and the latter may play an important role in preventing the milk triglycerides from oxidation. Flavan-3-ols are polyphenols with many health benefits. The present research revealed the antioxidant activities of flavan-3-ols that could be absorbed to sheep milk, adding new evidences for the values of these flavan-3-ols and for the milk.

Responses to melatonin of 2 breeds of dairy ewes in early lactation under autumn photoperiod conditions.

A total of 72 dairy ewes of 2 breeds (MN, Manchega, 72.4 ± 1.9 kg of body weight, n = 36; LC, Lacaune, 77.7 ± 2.3 kg of body weight; n = 36) were used to evaluate the lactational effects of melatonin implants in early lactation and under the short-day photoperiod conditions of autumn (experiment was centered on the winter solstice). Ewes lambed in autumn and were penned indoors in 12 balanced groups of 6 ewes by breed, body weight, age, and number of lambs, and randomly assigned to a 2 × 2 × 3 factorial design (treatment × breed × replicate). Ewes suckled their lambs for 28 d. Treatments were (1) melatonin (MEL), which received 1 subcutaneous implant of melatonin (18 mg/ewe) in the ear base at 35 ± 1 d (1 wk after lamb weaning), and (2) control, which did not receive any treatment. Ewes were fed ad libitum a total mixed ration (forage:concentrate, 60:40) and machine milked twice daily. Daily milk yield was automatically recorded from d 29 to 105 of lactation and sampled every 2 wk for composition. Jugular blood was sampled for plasma hormone analyses at 30, 50, 80, 110, and 124 d of lactation. Body reserves were assessed every 2 wk. Feed intake was measured by pen during 3 separated periods after the start of the treatments (wk 2 to 3, wk 6 to 7, and wk 10 to 11). Feed intake, and milk yield and composition varied by breed, but no MEL effects were detected on dry matter intake, milk yield, milk composition, or fat and protein standardized milk in either breed. As a result of the unique composition of the implants and the variable body weights of the ewes, the MEL treatment dose (on average, 0.24 mg/kg of body weight) was 6.8% greater in the MN (lighter) than in the LC (heavier) ewes. Plasmatic melatonin markedly increased in the MEL-treated ewes (on average, 111%), but despite the amount of MEL used, the MN responded greatly compared with the LC ewes (150 vs. 63%, respectively). No differences in basal plasmatic melatonin were detected between breeds (6.4 ± 1.1 pg/mL, on average), indicating the greater responsiveness to the implants of the lighter MN ewes. Plasmatic prolactin tended to decrease in the MEL-treated ewes (-35%, on average), but the effect was significant only in the MN ewes (-54%), in agreement with their greater response to MEL. No effects of MEL treatment were detected on plasmatic IGF-I in either breed. Moreover, body reserves did not vary by effect of MEL treatment or breed throughout the experiment. In conclusion, the use of exogenous melatonin as MEL implants, together with the endogenous melatonin naturally produced under short-day photoperiod conditions, had no effects on the early-lactation performances of dairy sheep, despite their breed and level of production.

Low-density SNP panel for efficient imputation and genomic selection of milk production and technological traits in dairy sheep.

The present study aimed to ascertain how different strategies for leveraging genomic information enhance the accuracy of estimated breeding values for milk and cheese-making traits and to evaluate the implementation of a low-density (LowD) SNP chip designed explicitly for that aim. Thus, milk samples from a total of 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra) were collected and analyzed to determine 3 milk production and composition traits and 2 traits related to milk coagulation properties and cheese yield. The 2 studied populations were genotyped with a customized 50K Affymetrix SNP chip (Affymetrix Inc.) containing 55,627 SNP markers. The prediction accuracies were obtained using different multitrait methodologies, such as the BLUP model based on pedigree information, the genomic BLUP (GBLUP), and the BLUP at the SNP level (SNP-BLUP), which are based on genotypic data, and the single-step GBLUP (ssGBLUP), which combines both sources of information. All of these methods were analyzed by cross-validation, comparing predictions of the whole population with the test population sets. Additionally, we describe the design of a LowD SNP chip (3K) and its prediction accuracies through the different methods mentioned previously. Furthermore, the results obtained using the LowD SNP chip were compared with those based on the 50K SNP chip data sets. Finally, we conclude that implementing genomic selection through the ssGBLUP model in the current breeding programs would increase the accuracy of the estimated breeding values compared with the BLUP methodology in the Assaf (from 0.19 to 0.39) and Churra (from 0.27 to 0.44) dairy sheep populations. The LowD SNP chip is cost-effective and has proven to be an accurate tool for estimating genomic breeding values for milk and cheese-making traits, microsatellite imputation, and parentage verification. The results presented here suggest that the routine use of this LowD SNP chip could potentially increase the genetic gains of the breeding selection programs of the 2 Spanish dairy sheep breeds considered here.

Influence of Mediterranean climate and lunar calendar on milk production in Lacaune breed ewes.

Environmental factors affect daily milk production in dairy animals. The aim of this study was to quantify the effects of environmental factors, specifically mean temperature (°C), relative humidity (%), temperature-humidity index (THI), solar radiation (°), pluvial precipitation (mm) and lunar calendar (full moon, waxing quarter, waning quarter, new moon), on milk production (kg/d). The analysis was based on 96,195 morning and evening milking records documented on 109 consecutive days, from 869 Lacaune ewes. Ewes were housed in groups of 174 individuals. The analysis was performed in two independent procedures, a Pearson correlation analysis and a multivariate analysis of the ewe's interrelationships, which was based on the total variance estimate and a Varimax-rotated factorial analysis. Milk yield (kg/d) was significantly (p < 0.05) negatively correlated with mean temperature (-0.24), relative humidity (-0.16), THI (-0.24), and radiation (-0.18), which suggests that the higher these environmental factors, the lower the milk yield. Lunar calendar had a significant (p < 0.01) effect on milk production yield; specifically, yields were higher on the full moon and new moon (2.25 ± 0.05 kg/day) than they were on the crescent or waning moon (2.17 ± 0.05 kg/day). In conclusion, ewes that had been exposed to higher mean temperature, relative humidity, THI and solar radiation had the lowest milk yield, and milk yields are highest on full and new moons. The results of this work may be helpful in making predictions for milk production in Lacaune ewes in the Mediterranean region throughout the year.

Genetic basis of thermotolerance in 2 local dairy sheep populations in the Iberian Peninsula.

Sheep milk production in the Northern Mediterranean countries heavily relies on local breeds subject to selection schemes to improve milk production. Climate change may shift the range of thermal loads on the animals and challenge their adaptation to the new thermal gradient. The objective of this study was to characterize the genetic component of thermal tolerance of 2 local breeds from the Iberian Peninsula, Latxa and Manchega, belonging to different genetic types that have evolved under different climatic environments (Oceanic for Latxa and Continentalized Mediterranean for Manchega). A total of 79,243 and 2,388,853 test day monthly records of milk, fat and protein yields from 12,882 and 277,904 ewes of Latxa and Manchega breeds, respectively, along a 12-yr period, were matched with the value of the average temperature-humidity index (THI) on the day of milk recording of the closest weather station to the flocks. These data were used to fit individual reaction norms (Legendre polynomials) describing changes in yields along the THI gradient. Genetic values for thermal tolerance were obtained from the slopes of those reaction norms under cold or heat stress and variances and covariances between yield and thermal tolerance were derived from the (co)variance matrices of the polynomial random regression coefficients. Results showed differing patterns in the 2 breeds. The Latxa breed showed clearer signs of genotype by environment interaction than did Manchega. Estimated correlations between yields under extremes of cold and heat were always above 0.8 for Manchega and around 0.4 for Latxa for all traits. Estimates of correlations between comfort and thermal stress were again over 0.8 for Manchega and lower for the higher (hot end) values (down to 0.6) than for the lower (cold end) values (down to 0.84) of the THI gradient for Latxa, indicating greater thermal stress expected from high than from low temperatures in this breed. Substantial variability in thermal tolerance under the more extreme THI values was found in both breeds. Estimated genetic correlations between yield and thermal tolerance were close to 0 and 0.2 for Latxa and Manchega in the cold and down to -0.6 and -0.3 in the heat end, although small variation was observed for fat in Latxa. Estimated realized trends from the average estimated breeding value, by year of birth, showed a positive response for yields in both breeds [around 0.1 standard deviation (SD) unit], but a detrimental correlation for thermal tolerance (down to -0.03 SD units for heat tolerance in Latxa). These results can be used to design optimal selection strategies for sustainable improvement of productivity under a rising-temperature scenario associated with climate change.

Genome-wide association studies (GWAS) and post-GWAS analyses for technological traits in Assaf and Churra dairy breeds.

This study aimed to perform a GWAS to identify genomic regions associated with milk and cheese-making traits in Assaf and Churra dairy sheep breeds; second, it aimed to identify possible positional and functional candidate genes and their interactions through post-GWAS studies. For 2,020 dairy ewes from 2 breeds (1,039 Spanish Assaf and 981 Churra), milk samples were collected and analyzed to determine 6 milk production and composition traits and 6 traits related to milk coagulation properties and cheese yield. The genetic profiles of the ewes were obtained using a genotyping chip array that included 50,934 SNP markers. For both milk and cheese-making traits, separate single-breed GWAS were performed using GCTA software. The set of positional candidate genes identified via GWAS was subjected to guilt-by-association-based prioritization analysis with ToppGene software. Totals of 84 and 139 chromosome-wise significant associations for the 6 milk traits and the 6 cheese-making traits were identified in this study. No significant SNPs were found in common between the 2 studied breeds, possibly due to their genetic heterogeneity of the phenotypes under study. Additionally, 63 and 176 positional candidate genes were located in the genomic intervals defined as confidence regions in relation to the significant SNPs identified for the analyzed traits for Assaf and Churra breeds. After the functional prioritization analysis, 71 genes were identified as promising positional and functional candidate genes and proposed as targets of future research to identify putative causative variants in relation to the traits under examination. In addition, this multitrait study allowed us to identify variants that have a pleiotropic effect on both milk production and cheese-related traits. The incorporation of variants among the proposed functional and positional candidate genes into genomic selection strategies represent an interesting approach for achieving rapid genetic gains, specifically for those traits difficult to measure, such as cheese-making traits.

Measuring liveweight changes in lactating dairy ewes with an automated walk-over-weighing system.

Monitoring liveweight (LW) is an important part of sound management practices at the individual and flock level (e.g., controlling for nutritional status based on body condition, reproduction, and health-related issues), but it is time consuming and stressful. To our knowledge, no literature has reported on the evaluation of automated weighing systems in dairy sheep as an alternative to conventional static scales. The objective of this research was to evaluate the practical feasibility of using an automated walk-over-weighing (WoW) prototype to measure daily LW changes in dairy ewes without human intervention. We used adult Lacaune dairy ewes in 2 complementary trials conducted indoors. Trial 1 aimed at evaluating the repeatability, precision, and accuracy of LW measures recorded using WoW scales compared with a static scale (the gold standard). Forty-two adult ewes (LW ± standard deviation = 71.3 ± 10.4 kg) were randomly drafted from the main flock and used in a 1-day session. The trial included 3 passages. In each passage, ewes were weighed first on a static scale; once a static position was achieved and LW recorded, they continued the circuit and immediately traversed the WoW scale for an automated LW record. Trial 2 aimed to demonstrate the feasibility of using the WoW device under real-world conditions in a dairy sheep-farming system. The WoW scale was installed in the exit race of the milking parlor and evaluated over 7 wk with adult ewes in mid lactation (n = 93; LW 78.5 ± 8.1 kg). Once the ewes were acclimated to the WoW system, 1 group of ewes (n = 48) continued to receive the same feeding regimen (controls), and the other group (n = 45) underwent a nutritional challenge [challenged; 2 wk of undernutrition and then back to control regimen (refeeding) for 1 wk]. We evaluated the ability of the WoW to detect small changes in LW. We collected LW data (2 weighings per ewe per day) from the WoW after each of the 2 milking sessions (morning and evening). We also obtained LW values by weighing the ewes using a static scale once a week. The automated WoW system showed substantial agreement with the gold standard when assessed using Lin's concordance correlation coefficient and Bland and Altman's method, largely due to high repeatability. The WoW system was adequate for detecting small daily variations in LW during undernutrition and refeeding periods. Misbehaviors resulted in spurious WoW values in trial 2, requiring us to use filtration methods to exclude outlier weights and allow meaningful assessment of small LW changes. The WoW system evaluated here is an alternative to the static scales conventionally used on dairy sheep farms. If sound filtration of raw data is applied, WoW could contribute to the close (daily) monitoring of individual LW without operator intervention (i.e., voluntary weighing) and taking animal welfare into account (i.e., no stress related to the weighing session on static scales).

Detection of genomic regions underlying milk production traits in Valle del Belice dairy sheep using regional heritability mapping.

The aim of this study was to identify genomic regions underlying milk production traits in the Valle del Belice dairy sheep using regional heritability mapping (RHM). Repeated measurements for milk yield (MY), fat percentage and yield (F% and FY) and protein percentage and yield (P% and PY), collected over a period of 6 years (2006-2012) on 481 Valle del Belice ewes, were used for the analysis. Animals were genotyped with the Illumina 50k SNP chip. Variance components, heritabilities and repeatabilities within and across lactations were estimated, fitting parity, litter size, season of lambing and fortnights in milk, as fixed; and additive genetic, permanent environment within and across lactations, flock by test-day interaction and residual as random effects. For the RHM analysis, the model included the same fixed and random effects as before, plus an additional regional genomic additive effect (specific for the region being tested) as random. While the whole genomic additive effect was estimated using the genomic relationship matrix (GRM) constructed from all SNPs, the regional genomic additive effect was estimated from a GRM matrix constructed from the SNPs within each region. Heritability estimates ranged between 0.06 and 0.15, with repeatabilities being between 0.14 and 0.24 across lactations and between 0.23 and 0.39 within lactation for all milk production traits. A substantial effect of flock-test-day on milk production traits was also estimated. Significant genomic regions at either genome-wide (p < .05) or suggestive (i.e., one false positive per genome scan) level were identified on chromosome (OAR) 2, 3 and 20 for F% and on OAR3 for P%, with the regions on OAR3 in common between the two traits. Our results confirmed the role of LALBA and AQP genes, on OAR3, as candidate genes for milk production traits in sheep.

Genome-wide association study of milk production traits in a crossbred dairy sheep population using three statistical models.

Milk production is one of the most important characteristics of dairy sheep, and the identification of genes affecting milk production traits is critical to understanding the genetics and improve milk production in future generations. Three statistical techniques, namely GWAS, ridge-regression BLUP and BayesC π , were used to identify SNPs in significant association with three milk production traits (milk yield, fat yield and protein yield) in a crossbred dairy sheep population. The results suggested that chromosomes 1, 3, 4, 5, 7 and 11 were likely to harbor genes important to milk production because these chromosomes had the greatest top-100-SNP variance contributions on the three milk production traits. The GWAS analysis identified between 74 and 288 genome-wide significant SNP (P < 0.05) whereas the BayesCπ model revealed between six and 63 SNPs, each with >95% posterior probability of inclusion as having a non-zero association effect on at least one of the three milk production traits. Positional candidate genes for milk production in sheep were searched, based on the sheep genomic assembly OAR version 3.1, such as those which map position coincided with or was located within 0.1 Mbp of a genome-wide suggestive or significant SNP. These identified SNPs and candidate genes supported some previous findings and also added new information about genetic markers for genetic improvement of lactation in dairy sheep, but keeping in mind that the majority of these positional candidate genes are not necessarily true causative loci for these traits and future validations are thus necessary.

Suppression of prolactin and reduction of milk secretion by effect of cabergoline in lactating dairy ewes.

The effects of cabergoline, an ergot derivative and dopamine receptor agonist, were investigated in 30 ewes of 2 dairy breeds (Manchega; MN, n = 15; Lacaune; LC, n = 15). Ewes were in a similar late-lactation stage, but differed in milk yield according to breed (MN vs. LC, 1.02 ± 0.03 vs. 2.27 ± 0.05 kg/d). Treatments consisted of a single intramuscular injection of cabergoline at different doses per ewe. Cabergoline doses (per ewe) were: low (0.56 mg), high (1.12 mg), and control (CON; 0 mg; 1 mL of saline). Milk yield was recorded daily (d -14 to 25), milk and blood were sampled, and udder traits were measured from d -2 to 14 after injection. No local reaction at the injection site, nor behavior and metabolic indicators of the ewes were detected after the cabergoline injection, but milk yield fell rapidly in both breeds (MN vs. LC, -54% vs. -27%) when compared with CON ewes. Cabergoline effects progressively disappeared after d 5, and no milk yield differences between treatments were detected from d 8 to 25 after injection. Milk fat and protein contents increased similarly (22% and 23%; respectively) in both breeds and at both cabergoline doses until d 5, and the effects disappeared thereafter. Plasma prolactin (PRL) decreased dramatically in the low- and high-treated ewes the day after injection when compared with the CON ewes, and reached values below the detection limit of the assay between d 1 and 5, increasing similarly thereafter. On d 14, PRL values were 58% greater in the low- and high-treated than in the CON ewes, showing that PRL concentrations rebounded when the cabergoline effects ceased. Total udder volume correlated with milk accumulated in the udder (r = 0.77) of all groups of ewes throughout the experiment, suggesting its use as a noninvasive method for the estimation of milk stored in the udder. Udder volume was similar for the low and high ewes, but both values were lower than those of the CON ewes from d 1 to 14 after injection. No other effects on udder size were detected. Cabergoline dramatically inhibited PRL secretion and decreased milk yield and udder volume of lactating dairy ewes. The low dose of cabergoline was as effective as the high dose in the 2 breeds of dairy ewes. These results suggest the use of cabergoline to facilitate the decrease of milk production in dairy ewes (e.g., dry-off, illness care), although further research in pregnant dairy ewes and during the following lactation is still needed.

Inbreeding, effective population size, and coancestry in the Latxa dairy sheep breed.

Traditionally, breeding programs have estimated and managed inbreeding based on pedigree information. The availability of genomic marker panels has made possible new alternatives to achieve more precise estimates, for example in case of missing pedigree. The objective of the present study was to assess and compare, different estimation methods (pedigree-based methodologies, single SNP-based approach (homozygosity) and runs of homozygosity-based method) to analyze the evolution of genetic diversity measured as inbreeding or as coancestry of 3 selected populations of Latxa dairy sheep (Latxa Cara Rubia and Latxa Cara Negra from Euskadi and Navarre). Genomic data came from 972 artificial insemination rams genotyped with the Illumina OvineSNP50 BeadChip (Illumina Inc., San Diego, CA) whose genealogy consisted of 4,484 animals. Inbreeding estimates based on molecular data were more similar between them than compared with those based on pedigree information. However, the SNP-based approach estimations of effective population size differed more, reflecting the sensitivity of effective population size to small changes in the evolution of inbreeding. The 2 Latxa Cara Negra populations showed increases of inbreeding rates with time and effective population sizes between 64 and 103 animals, depending on breed and methodology used. The Latxa Cara Rubia population did not show an increase in inbreeding rate, mainly due to semen importation from the related French population of Manech Tête Rousse. The effective size estimates based on coancestry increase show a higher variability and they are more sensitive to the source of information and the data structure considered. Realized effective population size based on individual increase in inbreeding were in agreement with the previous estimates. Coancestry evolution analysis based on DNA information showed an increase on coancestry during the last 10 yr in all breeds, as a consequence of the selection process. Moreover, the increase on coancestry between Latxa Cara Rubia and Manech Tête Rousse was more noticeable between than within each of those breeds.

The effect of parity number on the metabolism, inflammation, and oxidative status of dairy sheep during the transition period.

The objective of this study was to evaluate whether dairy sheep during the transition period are affected by their parity numbers with regard to (1) body weight (BW), body condition score (BCS), and production performance (milk yield and composition) and (2) metabolic, inflammation, and stress biomarkers. For this purpose, 30 Sarda dairy ewes [15 primiparous (PRP) and 15 multiparous (MUP) ewes] were recruited on d 90 of gestation. Each group was homogeneous according to age, BW, and BCS. Sampling was carried out at -60, -30, -7, 0, +30, and +60 d from lambing. The MUP ewes showed a higher BW (46.32 vs. 38.71 kg) and larger litter size (1.45 vs. 1.06 kg) but a lower BCS (2.47 vs. 2.70) than the PRP ewes. Furthermore, the MUP ewes had lower concentrations of glucose (3.49 vs. 4.27 mol/L), cholesterol (1.63 vs. 1.81 mmol/L), free fatty acids (0.47 vs. 0.62 mmol/L), and triglycerides (0.22 vs. 0.25 mmol/L) compared with PRP ewes. With regard to inflammation and oxidative stress parameters, the PRP group had higher haptoglobin (0.48 vs. 0.18 g/L) and paraoxonase (187.90 vs. 152.11 U/L) activity than the MUP group. Overall, the MUP ewes were characterized by greater milk production performance and greater feed intake, resulting in a better energy balance, than the PRP ewes. Interestingly, these findings highlighted a different metabolic and inflammatory response over the transition period between PRP and MUP ewes, with the latter displaying lower concentrations of inflammatory-related biomarkers.

Exploring the inclusion of genomic information and metafounders in Latxa dairy sheep genetic evaluations.

The availability of genomic marker panels has made possible more precise estimates of breeding values. Sheep breeding programs are implementing genomic selection. In Latxa dairy sheep breed, a previous study using pre-corrected data and a small number of genotyped animals did not show a clear advantage of genomic selection. The objective of the present study was to ascertain the possible benefits of GS for the Latxa breed based on more data than before and using better tools, in particular single-step genomic BLUP using metafounders to model missing pedigree. Goodness of prediction of pedigree and genomic evaluations was analyzed by cross-validation comparing predictions of young rams using whole and partial (truncated) data sets. The results showed that with the current available data, genetic and genomic evaluations have the same accuracy. Contrary to the previous study, predictions were nearly unbiased, which shows the advantage of using single-step genomic BLUP. However, genomic information did not yield more precise evaluations. This could be explained by the small number of sibs in the young rams.