Inseminate without hormonal treatment in dairy sheep farms: exploring the consequences on the sustainability of several contrasted production systems

Alternatives to hormonal treatments (HTs) in dairy sheep reproduction management are being explored in response to increasing societal concerns regarding animal welfare and food safety. However, hormone-free reproduction implies higher variability in flock performances and additional constraints for timely synchronised artificial insemination (AI) in the flock, impacting the diffusion of genetic progress. The use of the male effect, a well-known practice to induce synchronised oestrus, combined with precision tools (e.g., heat detector), is a plausible way to implement AI without HT in dairy sheep farms. To date, the consequences of such alternative reproduction management on the whole farm sustainability remain unknown. To anticipate these potential impacts, a multiagent model (REPRIN'OV) was used to simulate dairy sheep farms' sustainability indicators (biotechnical, economic, environmental and workload). A reproduction management scenario, including the use of the male effect followed by AI on the adult ewes (HFAI), was simulated and compared to the current reproduction management of four case study farms (Early_conv, Late_conv, Early_org and Late_org). They were selected to represent the different agricultural models (Conventional or Organic) and reproduction seasons (Early - during spring, out of ewes' natural reproduction season - or Late -from early summer to the end of autumn) of the Roquefort Basin's farms in Southern France. Simulation results showed that the HFAI scenario had different consequences depending on the farm's production system type. A negative effect on most key sustainability indicators of the Conv farms was observed, as a significant reduction in the fertility rate, in the proportion of young ewes born from AI (-54% in both farms; P < 0.05) and in the flock's milk production were observed; while the workload and greenhouse gas (GHG) emissions were increased compared to the initial scenario. In the Org farms, HFAI had neutral to positive effects on most indicators as the fertility, milk production of the flock, workload during milking and GHG emissions were barely affected by this scenario, while an increase in the proportion of young ewes born from AI was observed (+39% and + 43% in each farm, respectively; P < 0.05), allowing a better farm gross margin. Still, the workload during lambing was increased in Early_org (+18%; P < 0.05), as Early farms, tended to be more negatively impacted by HFAI than Late ones. Overall, our simulation approach provides interesting elements to exchange with stakeholders on how to progress towards a socially acceptable reproduction management system, for the dairy sheep sector.

Exploring the value of genomic predictions to simultaneously improve production potential and resilience of farmed animals

Sustainable livestock production requires that animals have a high production potential but are also highly resilient to environmental challenges. The first step to simultaneously improve these traits through genetic selection is to accurately predict their genetic merit. In this paper, we used simulations of sheep populations to assess the effect of genomic data, different genetic evaluation models and phenotyping strategies on prediction accuracies and bias for production potential and resilience. In addition, we also assessed the effect of different selection strategies on the improvement of these traits. Results show that estimation of both traits greatly benefits from taking repeated measurements and from using genomic information. However, the prediction accuracy for production potential is compromised, and resilience estimates tends to be upwards biased, when families are clustered in groups even when genomic information is used. The prediction accuracy was also found to be lower for both traits, resilience and production potential, when the environment challenge levels are unknown. Nevertheless, we observe that genetic gain in both traits can be achieved even in the case of unknown environmental challenge, when families are distributed across a large range of environments. Simultaneous genetic improvement in both traits however greatly benefits from the use of genomic evaluation, reaction norm models and phenotyping in a wide range of environments. Using models without the reaction norm in scenarios where there is a trade-off between resilience and production potential, and phenotypes are collected from a narrow range of environments may result in a loss for one trait. The study demonstrates that genomic selection coupled with reaction-norm models offers great opportunities to simultaneously improve productivity and resilience of farmed animals even in the case of a trade-off.

Genomic and Phenotypic Udder Evaluation for Dairy Cattle Selection: A Review

The traditional point of view regarding dairy cattle selection has been challenged by recent genomic studies indicating that livestock productivity prediction can be redefined based on the evaluation of genomic and phenotypic data. Several studies that included different genomic-derived traits only indicated that interactions among them or even with conventional phenotypic evaluation criteria require further elucidation. Unfortunately, certain genomic and phenotypic-derived traits have been shown to be secondary factors influencing dairy production. Thus, these factors, as well as evaluation criteria, need to be defined. Owing to the variety of genomic and phenotypic udder-derived traits which may affect the modern dairy cow functionality and conformation, a definition of currently important traits in the broad sense is indicated. This is essential for cattle productivity and dairy sustainability. The main objective of the present review is to elucidate the possible relationships among genomic and phenotypic udder evaluation characteristics to define the most relevant traits related to selection for function and conformation in dairy cattle. This review aims to examine the potential impact of various udder-related evaluation criteria on dairy cattle productivity and explore how to mitigate the adverse effects of compromised udder conformation and functionality. Specifically, we will consider the implications for udder health, welfare, longevity, and production-derived traits. Subsequently, we will address several concerns covering the application of genomic and phenotypic evaluation criteria with emphasis on udder-related traits in dairy cattle selection as well as its evolution from origins to the present and future prospects.

Genetic polymorphism in European and African sheep breeds reared in Hungary based on 48 SNPs associated with resistance to gastrointestinal parasite infection using KASP-PCR technique

This pilot study used an alternative and economically efficient technique, the Kompetitive Allele-Specific Polymerase Chain Reaction (KASP-PCR) to examine 48 SNPs from 11 parasite-resistance genes found on 8 chromosomes in 110 animals from five sheep breeds reared in Hungary; Hungarian Tsigai, White Dorper, Dorper, Ile de France, and Hungarian Merino. Allele and genotype frequencies, fixation index, observed heterozygosity, expected heterozygosity, F statistic, and their relationship with the Hardy-Weinberg equilibrium (WHE) and the polymorphic information content (PIC) were determined, followed by principal component analysis (PCA). As much as 32 SNPs out of the 48 initially studied were successfully genotyped. A total of 9 SNPs, 4 SNPs in TLR5, 1 SNP in TLR8, and 4 SNPs in TLR2 genes, were polymorphic. The variable genotype and allele frequency of the TLRs gene indicated genetic variability among the studied sheep breeds, with the Hungarian Merino exhibiting the most polymorphisms, while Dorper was the population with the most SNPs departing from the HWE. According to the PIC value, the rs430457884-TLR2, rs55631273-TLR2, and rs416833129-TLR5 were found to be informative in detecting polymorphisms among individuals within the populations, whereas the rs429546187-TLR5 and rs424975389-TLR5 were found to have a significant influence in clustering the population studied. This study reported a moderate level of genetic variability and that a low to moderate within-breed diversity was maintained in the studied populations.

Breeding options for nematode resistance in Lacaune dairy sheep

Due to progressing anthelmintic resistance of gastrointestinal nematodes (GIN), supportive measures are needed to control these parasites. In sheep, it has been shown that selection towards an increased nematode resistance is feasible and that faecal egg count (FEC) is the generally acknowledged trait for selection. However, a selection based on FEC would come with certain costs, therefore auxiliary, cheaper resistance traits would be most welcome. FAMACHA©, a colour classification of the eyelid, usually used to determine the manifestation of an infection with Haemonchus contortus, could serve as such. Therefore, we collected FAMACHA©, packed cell volume (PVC) and FEC phenotypes of approx. 1150 naturally infected Lacaune ewes on 15 commercial farms in Switzerland. The Haemonchus-proportion was determined on farm level. Phenotypic correlations of FEC and FAMACHA© as well as FAMACHA© and PCV were 0.25 (SE 0.03) and -0.35 (SE 0.08), respectively, and correspond well with the results of other studies. A multi-trait animal model was applied to estimate genetic parameters with FEC, FAMACHA©, PVC and milk yield as dependent variables. The heritabilities of FEC, FAMACHA©, PCV and milk yield were estimated to be moderate with values of 0.33 (SE 0.08), 0.30 (SE 0.08), 0.36 (SE 0.08) and 0.34 (SE 0.08), respectively. The genetic correlations between FEC and FAMACHA© and between FEC and PCV were estimated to be close to zero with values of 0.03 (SE 0.22) and 0.01 (SE 0.21), respectively. The average Haemonchus-proportion compared to other GIN was found to be 43%. The FAMACHA© classification of the Lacaune ewes seems to indicate a rather high worm challenge, with 38, 14 and 2% of observations classified to scores 3, 4 and 5, respectively. However, the worm challenge according to FEC was moderate. It has been suggested that the genetic correlation between FAMACHA© and FEC is more pronounced when FEC was high. It could therefore be that the lack of genetic correlation was due to an insufficient worm challenge, even though the Lacaune were grazing at least 70 days before phenotyping. The genetic correlation between FEC and milk yield was estimated to be 0.07 (SE 0.22, slightly unfavourable). We conclude that if FEC is used as trait, the Lacaune could be selected for lower susceptibility towards nematode infection. The use of FAMACHA© as an auxiliary trait for FEC is not feasible, due to an inexistent genetic correlation between these two traits.

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.

Genetic Parameters and Genomic Regions Underlying Growth and Linear Type Traits in Akkaraman Sheep

In the current study, the genetic architecture of growth and linear type traits were investigated in Akkaraman sheep. Estimations of genomic heritability, genetic correlations, and phenotypic correlations were implemented for 17 growth and linear type traits of 473 Akkaraman lambs by the univariate and multivariate analysis of animal mixed models. Correspondingly, moderate heritability estimates, as well as high and positive genetic/phenotypic correlations were found between growth and type traits. On the other hand, 2 genome-wide and 19 chromosome-wide significant single nucleotide polymorphisms were found to be associated with the traits as a result of animal mixed model-based genome-wide association analyses. Accordingly, we propose several genes located on different chromosomes (e.g., PRDM2, PTGDR, PTPRG, KCND2, ZNF260, CPE, GRID2, SCD5, SPIDR, ZNF407, HCN3, TMEM50A, FKBP1A, TLE4, SP1, SLC44A1, and MYOM3) as putative quantitative trait loci for the 22 growth and linear type traits studied. In our study, specific genes (e.g., TLE4, PTGDR, and SCD5) were found common between the traits studied, suggesting an interplay between the genetic backgrounds of these traits. The fact that four of the proposed genes (TLE4, MYOM3, SLC44A1, and TMEM50A) are located on sheep chromosome 2 confirms the importance of these genomic regions for growth and morphological structure in sheep. The results of our study are therefore of great importance for the development of efficient selection indices and marker-assisted selection programs, as well as for the understanding of the genetic architecture of growth and linear traits in sheep.

Multivariate and Genome-Wide Analysis of Mid-Infrared Spectra of Non-Coagulating Milk of Sarda Sheep Breed

Milk coagulation ability is crucial for the dairy sheep industry since the whole amount of milk is processed into cheese. Non-coagulating milk (NCM) is defined as milk not forming a curd within the testing time. In sheep milk, it has been reported in literature that up to 20% of milk is NCM. Although the clotting properties of individual milk have been widely studied, little attention has been given to NCM and genomic dissection of this trait. Mid-infrared (MIR) spectra can be exploited both to predict cheese-making aptitude and to discriminate between coagulating milk and NCM. The main goals of this work were (i) to assess the predictivity of MIR spectra for NCM classification and (ii) to conduct a genome-wide association study on coagulation ability. Milk samples from 949 Sarda ewes genotyped and phenotyped for milk coagulation properties (MCPs) served as the training dataset. The validation dataset included 662 ewes. Three classical MCPs were measured: rennet coagulation time (RCT), curd firmness (a30), and curd firming time (k20). Moreover, MIR spectra were acquired and stored in the region between 925.92 and 5,011.54 cm−1. The probability of a sample to be NCM was modeled by step-wise logistic regression on milk spectral information (LR-W), logistic regression on principal component (LR-PC), and canonical discriminant analysis of spectral wave number (DA-W). About 9% of the samples did not coagulate at 30 min. The use of LR-W gave a poorer classification of NCM. The use of LR-PC improved the percentage of correct assignment (45 ± 9%). The DA-W method allows us to reach 75.1 ± 10.3 and 76.5 ± 18.4% of correct assignments of the inner and external validation datasets, respectively. As far as GWA of NCM, 458 SNP associations and 45 candidate genes were detected. The genes retrieved from public databases were mostly linked to mammary gland metabolism, udder health status, and a milk compound also known to affect the ability of milk to coagulate. In particular, the potential involvement of CAPNs deserves further investigation.

Study of the Fatty Acid Profile of Milk in Different Sheep Breeds: Evaluation by Multivariate Factorial Analysis

Simple Summary

The quality of milk is strongly influenced by its lipid profile. The increase in fats with nutraceutical properties at the expense of those negative for human health, has always been a goal to improve the functional properties of milk. To achieve this goal, it is essential to know the metabolism of the mammary gland and the relationship between the various lipid components. Much is known about bovine milk, while the aspect relating to the sheep species has not been developed. The present work aims to investigate the relationships between the various fatty acids in sheep’s milk through a multivariate approach, which can highlight the mammary role of lipid synthesis.

Abstract

A multivariate analysis was used to investigate the fatty acid (FA) profile in three different Italian sheep breeds: Comisana, Massese, and Sarda. A sample of 852 animals was considered: 118 Massese, 303 Comisana, 431 Sarda. Sarda sheep were divided into two groups, based on their breeding origin (298 and 133 reared in Sardinia and Tuscany, respectively). Sarda sheep, bred both in Sardinia and in Tuscany, were considered in different groups, both because in these two regions most of the sheep of this breed are reared, and because they differ in geographical characteristics and in the farming system. The individual milk FA composition of dairy ewes was analyzed with multivariate factor analysis. The extracted factors were representative of the following eight groups of fatty acids or functions: factor 1 (odd branched fatty acids and long-chain fatty acids), factor 2 (sn3_position), factor 3 (alternative biohydrogenation), factor 4 (SCD_1), factor 5 (SCD_2), factor 6 (SCD_3), factor 7 (fat secretion) and factor 8 (omega-3). A factor analysis suggested the presence of different metabolic pathways for de novo short- and medium-chain fatty acids and Δ9-desaturase products. The ANOVA of factor scores highlighted the significant effects of the breed. The results of the present study showed that breed is an important factor in defining the fatty acid profile of milk, combined with the effect of the diet. Breeds reared in the same farming system (Comisana, Massese and Sarda reared in Tuscany) showed significant differences for all the factors extracted. At the same time, we found differences between the Sarda sheep reared in Sardinia and Tuscany, two different regions of Italy.

Animal Board Invited Review: Meta-analysis of genetic parameters for resilience and efficiency traits in goats and sheep

Genetic selection focused purely on production traits has proven very successful in improving the productive performance of livestock. However, heightened environmental and infectious disease challenges have raised the need to also improve the resilience of animals to such external stressors, as well as their efficiency in utilising available resources. A better understanding of the relationship between efficiency and production and health traits is needed to properly account for it in breeding programmes and to produce animals that can maintain high production performance in a range of environmental conditions with minimal environmental footprint. The aim of this study was to perform a meta-analysis of genetic parameters for production, efficiency and health traits in sheep and goats. The dataset comprised 963 estimates of heritability and 572 genetic correlations collated from 162 published studies. A threelevel meta-analysis model was fitted. Pooled heritability estimates for milk production traits ranged between 0.27 ± 0.03 and 0.48 ± 0.13 in dairy goats and between 0.21 ± 0.06 and 0.33 ± 0.07 in dairy sheep. In meat sheep, the heritability of efficiency traits ranged from 0.09 ± 0.02 (prolificacy) up to 0.32 ± 0.14 (residual feed intake). For health traits, pooled heritability was 0.07 ± 0.01 (faecal egg count) and 0.21 ± 0.01 (somatic cell score) in dairy goats and 0.14 ± 0.04 (faecal egg count) and 0.13 ± 0.02 (somatic cell score) in dairy sheep. In meat sheep, the heritability of disease resistance and survival traits ranged between 0.07 ± 0.02 (mastitis) and 0.50 ± 0.10 (breech strike). Pooled estimates of genetic correlations between resilience and efficiency traits in dairy goats were not significantly different from zero with the exception of somatic cell score and fat content (-0.19 ± 0.01). In dairy sheep, only the unfavourable genetic correlation between somatic cell score and protein content (0.12 ± 0.03) was statistically significant. In meat sheep only, the correlations between growth and faecal egg count (-0.28 ± 0.11) as well as between growth and dagginess (-0.33 ± 0.13) were statistically significant and favourable. Results of this meta-analysis provide evidence of genetic antagonism between production and health in dairy sheep and goats. This was not observed in meat sheep where most of the pooled estimates had high standard errors and were non-significant. Based on the obtained results, it seems feasible to simultaneously improve efficiency and health in addition to production by including the different types of traits in the breeding goal. However, a better understanding of potential trade-offs between these traits would be beneficial. Particularly, more studies focused on reproduction and resilience traits linked to the animal's multi-trait response to challenges are required.

Preliminary Assessment of Body Condition Score as a Possible Marker for the Targeted Selective Treatment of Dairy Sheep Against Gastrointestinal Nematodes

Purpose

In the fight against anthelmintic resistance, targeted selective treatments (TSTs), where only a small percentage of a flock receives treatment, have become increasingly popular. Overall, implementation of such treatments can be based on various parameters including Body condition score (BCS). As infection with non-bloodsucking nematodes, frequently encountered on sheep farms in the central Mediterranean basin, commonly causes bodyweight reduction, the aim of this research is to evaluate the effectiveness of BCS as a parameter for the implementation of TSTs in lactating dairy sheep with subclinical gastrointestinal nematode (GIN) infections from the island of Sardinia, Italy.

Methods

Faecal samples from 1012 ewes divided into 2 groups (third and fifth month of lactation) were collected and their BCS recorded. Faecal egg counts and coprocultures were performed for the assessment of the GIN burden and identification of present species.

Results

An overall GIN prevalence of 85.4% with a mean eggs per gram (EPG) of faeces of 210.1 ± 347.3 was found. Teladorsagia spp. and Trichostrongylus spp. were the GIN genera most identified. Overall, animals with the lowest BCS had the highest EPG values and a negative correlation (r = − 0.163) between the EPG values and BCS of the studied animals was found, which was most significant for older sheep.

Conclusion

This research confirmed BCSs and EPG values for GIN in sheep to be negatively correlated, particularly in older ewes. Application of TSTs for lactating sheep with a BCS < 2.25, especially to older ewes, could be beneficial in case of subclinical GIN infections, although further studies are needed to work out precise recommendation.

Unfavorable genetic correlations between fecal egg count and milk production traits in the French blond-faced Manech dairy sheep breed

Background

Genetic selection has proven to be a successful strategy for the sustainable control of gastrointestinal parasitism in sheep. However, little is known on the relationship between resistance to parasites and production traits in dairy breeds. In this study, we estimated the heritabilities and genetic correlations for resistance to parasites and milk production traits in the blond-faced Manech breed. The resistance to parasites of 951 rams from the selection scheme was measured through fecal egg counts (FEC) at 30 days post-infection under experimental conditions. Six milk production traits [milk yield (MY), fat yield (FY), protein yield (PY), fat content (FC), protein content (PC) and somatic cell score (LSCS)], were used in this study and were collected on 140,127 dairy ewes in first lactation, as part of the official milk recording. These ewes were related to the 951 rams (65% of the ewes were daughters of the rams).

Results

Fecal egg counts at the end of the first and second infections were moderately heritable (0.19 and 0.37, respectively) and highly correlated (0.93). Heritabilities were moderate for milk yields (ranging from 0.24 to 0.29 for MY, FY and PY) and high for FC (0.35) and PC (0.48). MY was negatively correlated with FC and PC (− 0.39 and − 0.45, respectively). FEC at the end of the second infection were positively correlated with MY, FY and PY (0.28, 0.29 and 0.24, respectively with standard errors of ~ 0.10). These slightly unfavorable correlations indicate that the animals with a high production potential are genetically more susceptible to gastrointestinal parasite infections. A low negative correlation (− 0.17) was also found between FEC after the second infection and LSCS, which suggests that there is a small genetic antagonism between resistance to gastrointestinal parasites and resistance to mastitis, which is another important health trait in dairy sheep.

Conclusions

Our results indicate an unfavorable but low genetic relationship between resistance to gastrointestinal parasites and milk production traits in the blond-faced Manech breed. These results will help the breeders’ association make decisions about how to include resistance to parasites in the selection objective.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12711-022-00701-1.

Unravelling the effect of environment on the genome of Sarda breed ewes using Runs of Homozygosity

Natural adaptation and artificial selection have shaped the genome of modern livestock breeds. Among SNP-based metrics that are used to detect signatures of selection at genome-wide level, runs of homozygosity (ROH) are getting increasing popularity. In this paper, ROH distribution and features of a sample of 823 Sarda breed ewes farmed at different levels of altitude are analysed to investigate the effect of the environment on the patterns of homozygosity. A total of 46,829 (33,087 unique) ROH were detected. OAR2 exhibited the largest average number of ROH per animal. The most frequent ROH (OAR27, 38.9-44.2 Mb) was shared by 327. ROH length was statistically affected (p < 0.001) by both the altitude and temperature of the place where the flock was located. The highest probability of a SNP falling in a ROH was observed for hill ewes, whereas the smallest one for mountain. A total of 457 SNP exceeded the 99th percentile of the ROH count per SNP distribution and were considered significant. These markers mapped in eight chromosomes and they clustered into 17 ROH islands, where 80 candidate genes were mapped. Results of this study highlighted differences in the ROH distribution and features among sheep farmed in flocks located at different levels of altitude, confirming the role of environmental adaptability in shaping the genome of this breed.

Effect of Body Condition Score, Treatment Period and Month of the Previous Lambing on the Reproductive Resumption of Melatonin-Treated Sarda Breed Sheep during Spring

Simple Summary

Improving reproductive efficiency in sheep farms is a crucial task for researchers. Therefore, the present research considers the conditions commonly found in Sarda sheep farms and evaluates the effects on reproductive activity via the following factors: exogenous melatonin treatment through subcutaneous implants, different periods of melatonin treatment, varying body condition scores (BCS) and the previous lambing of the treated ewes. The results of the present research suggest that melatonin treatment is able to reliably enhance reproductive efficiency. Furthermore, the findings indicate that optimal reproductive efficiency can be achieved by ensuring that melatonin is administered in April to ewes that have a BCS of >2.5 and have passed their third month of lactation.

Abstract

Stakeholders place great emphasis upon rationalizing the management and rearing techniques which are utilized within sheep farms. The present study aimed to investigate factors which may improve the reproductive performance of melatonin-treated Sardinian sheep via a series of three trials. The first trial (n = 100) investigated the effect of melatonin treatment alongside body condition score (BCS), the second trial (n = 150) investigated the effect of treatment alongside the date of treatment (treatment period) and the third trial (n = 150) investigated the effect of treatment alongside the previous lambing of the ewes. The findings indicated that melatonin is an effective tool for anticipating and improving the reproductive activity of in Sarda breed sheep during the springtime. Furthermore, to obtain optional results, melatonin implantation should be conducted in April, in ewes that have a BCS of >2.5 and that have passed their third month of lactation.

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.

Mammary Gland Structures Are Not Affected by an Increased Growth Rate of Yearling Ewes Post-Weaning but Are Associated with Growth Rates of Singletons

The experiment aimed to examine the impacts of an increased growth rate of ewes between three and seven months of age on udder development using ultrasound and to establish whether ultrasonography could be used to identify ewe mammary structures that may be indirect indicators of singleton growth to weaning. Udder dimensions, depths of gland cistern (GC), parenchyma (PAR) and fat pad (FP) were measured in late pregnancy (P107), early lactation (L29), and at weaning (L100) in 59 single-bearing yearling ewes selected from two treatments. The 'heavy' group (n = 31) was preferentially fed prior to breeding achieving an average breeding live-weight of 47.9 ± 0.38 kg at seven months of age. The 'control' group (n = 28) had an average breeding live-weight of 44.9 ± 0.49 kg. Udder dimensions, GC, PAR and FP did not differ between treatments. Lamb growth to L100 was positively associated (p < 0.05) with PAR at P107 and GC at L29. There was no evidence of negative effects of the live-weight gain treatments on udder development of yearling ewes as measured by ultrasonography. The results suggest that this ultrasound method has the potential to identify pregnant yearling ewes which would wean heavier singletons.

Improving dairy performance through molecular characterization of SREBP-1 gene in Sarda sheep breed

This research has two aims: (i) to characterize the coding sequence of the SREBP-1 gene in dairy sheep in order to investigate possible relationships between single nucleotide polymorphisms (SNPs) and milk traits; and (ii) to investigate possible relationship between SREBP-1 gene expression and nucleotide variation. Four hundred adult and multiparous lactating Sarda breed ewes were selected from two farms. Milk samples were collected from Day 30 to Day 150 of lactation to determine the mean yield, somatic cell count, lactose, fat, and protein content of the milk. RNA was extracted from the milk samples, after which the SREBP-1 gene coding regions were amplified and sequenced to scan mutations. Whilst eight SNPs were identified, none had statistically significant association with the analysed milk traits. Moreover, the identified expression patterns were not affected by the SNP or combined genotypes. High SREBP-1 gene expression levels were found to be correlated with high milk fat content (P < 0.01), indicating the crucial role of this gene in the milk fat synthesis. In conclusion, the polymorphisms found within SREBP-1 gene exhibited no significant associations with milk traits or with individual SREBP-1 mRNA expression patterns. The findings thus suggest that this small genetic variability may derive from the selection carried out in Sarda breed to improve milk yield.

Metabolic and hormonal control of energy utilization and partitioning from early to mid lactation in Sarda ewes and Saanen goats

In a recent study, we observed that starch-rich diets used in mid lactation induced lower milk production persistency and higher body fat accumulation in dairy ewes compared with dairy goats. Because these species differences could be linked to hormonal mechanisms that drive energy partitioning, in the same experiment, we explored the evolution of metabolic and hormonal status during lactation to test this hypothesis. Twenty mature Sarda dairy ewes and 20 mature Saanen goats [15-134 ± 11 d in milk (DIM), mean ± SD] were compared simultaneously. In early lactation, each species was allocated to one dietary treatment: high-starch diet [HS: 20.4% starch, on dry matter (DM) basis], whereas from 92 ± 11 DIM, each species was allocated to 1 of 2 dietary treatments: HS (20.0% starch, on DM basis) and low-starch (LS: 7.8% starch, on DM basis) diets. Blood samples were collected in the morning to analyze glucose, nonesterified fatty acids (NEFA), growth hormone (GH), insulin, and insulin-like growth factor I (IGF-I). Data were analyzed using the PROC MIXED procedure of SAS with repeated measurements (SAS Version 9.0). The HS and LS diets applied in mid lactation did not affect metabolic status of the animal within species; thus, only a comparison between species was carried out. From early to mid lactation, plasma glucose concentration was higher in ewes than in goats (54.57 vs. 48.35 ± 1.18 mg/dL), whereas plasma NEFA concentration was greater in goats than in ewes (0.31 vs. 0.25 ± 0.03 mmol/L). Goats had higher plasma GH concentration and lower plasma insulin content than ewes (4.78 vs. 1.31 ng/mL ± 0.47; 0.11 vs. 0.26 μg/L ± 0.02). Plasma IGF-I concentration did not vary between species. The comparison of metabolic and hormonal status of lactating Sarda dairy ewes and Saanen goats, carried out by studying simultaneously the 2 species in the same stage of lactation and experimental conditions, suggests that the higher insulin and glucose concentration observed in Sarda ewes explains why they partitioned more energy toward body reserves than to the mammary gland, especially in mid lactation. This can justify the negative effect of high-starch diets in mid-lactating Sarda ewes. Conversely, the highest GH and NEFA concentration observed in Saanen goats explain why they partitioned more energy of starch diets toward the mammary gland than to body reserves and justify the positive effect of high-starch diet in mid lactation. Together, these different responses contribute to explain why specialized dairy goats, such as the Saanen breed, have a higher milk production persistency than specialized dairy sheep breeds, such as the Sarda.

Estimation of genetic parameters for cheese-making traits in Spanish Churra sheep

The global production of sheep milk is growing, and the main industrial use of sheep milk is cheese making. The Spanish Churra sheep breed is one of the most important native dairy breeds in Spain. The present study aimed to estimate genetic parameters for a wide range of traits influencing the cheese-making ability of Churra sheep milk. Using a total of 1,049 Churra ewes, we studied the following cheese-making traits: 4 traits related to milk coagulation properties (rennet coagulation time, curd-firming time, and curd firmness at 30 and 60 min after addition of rennet), 2 traits related to cheese yield (individual laboratory cheese yield and individual laboratory dried curd yield), and 3 traits measuring curd firmness over time (maximum curd firmness, time to attain maximum curd firmness, and syneresis). In addition, a list of milk traits, including the native pH of the milk and several milk production and composition traits (milk yield; the fat, protein, and dried extract percentages; and the somatic cell count), were also analyzed for the studied animals. After discarding the noncoagulating samples (only 3.7%), data of 1,010 ewes were analyzed with multiple-trait animal models by using the restricted maximum likelihood method to estimate (co)variance components, heritabilities, and genetic correlations. In general, the heritability estimates were low to moderate, ranging from 0.08 (for the individual laboratory dried curd yield trait) to 0.42 (for the fat percentage trait). High genetic correlations were found within pairs of related traits (i.e., 0.93 between fat and dried extract percentages, -0.93 between the log of the curd-firming time and curd firmness at 30 min, 0.70 between individual laboratory cheese yield and individual laboratory dried curd yield, and -0.94 between time to attain maximum curd firmness and syneresis). Considering all the information provided here, we suggest that in addition to the current consideration of the protein percentage trait for improving cheese yield traits, the inclusion of the pH of milk as a measured trait in the Churra dairy breeding program would represent an efficient strategy for improving the cheese-making ability of milk from this breed.

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

Simple Summary

Parentage misassignments directly affect genetic gain in traditional breeding programs. The use of genetic markers facilitates parentage verification. In sheep, microsatellite markers and single nucleotide polymorphism (SNP) markers have been proposed by the International Society of Animal Sciences (ISAG) for parentage testing. Since the implementation of genomic selection, the microsatellite information used for parental testing in previous generations is gradually being replaced by SNPs. However, parentage verifications should all be performed using the same technology. A strategy for transitioning from microsatellites to SNP markers, while avoiding extra genotyping costs, is the imputation of microsatellite alleles from SNP haplotypes. This study aims to identify the optimum approach, using a minimum number of SNPs to accurately impute microsatellite markers and developing a low-density SNP chip for parentage verification in the Assaf sheep breed. The imputation approach described here reached high accuracies using a low number of SNP markers, which supports the development of a low-density SNP chip that could avoid the problems of genotyping with both technologies, being a cost-effective method for parentage testing. This study will help sheep breeders to perform parentage verification when different genotyping platforms have been used across generations.

Abstract

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.

Plasmatic Profile of Pregnancy-Associated Glycoprotein (PAG) during Gestation and Postpartum in Sarda and Lacaune Sheep Determined with Two Radioimmunoassay Systems

Simple Summary

Nowadays the need to optimize and maximize the productivity of dairy sheep leads farmers to plan lambing in specific periods in order to avoid economic loss due to nonproductive animals. The goal is to diagnose pregnancy at early gestation in order to minimize the costs of unproductive animals and to properly formulate rations for the energy requirements of gestating or lactating animals at the same time. Moreover, early pregnancy diagnosis, as well as the possibility of distinguishing between single and multiple gestations, enables farmers to plan the management of lambing well in advance thus minimizing manpower requirements. This study showed, for the first time, the plasmatic profile of PAG (pregnancy-associated glycoproteins) in Sarda and Lacaune ewes during gestation and the postpartum period using two different radioimmune assay (RIA) systems, thus enhancing our knowledge regarding PAG concentrations in domestic ruminants. Moreover, it showed that for both breeds these RIA systems are capable of distinguishing pregnant from nonpregnant ewes starting from day 18 of gestation. Furthermore, the rapid disappearance of PAG concentration following lambing did not require the use of a cut-off limit in postpartum animals as a means for detecting a new pregnancy.

Abstract

This study was carried out to determine ovine pregnancy-associated glycoprotein (oPAG) levels in the plasma of Sarda and Lacaune ewes throughout gestation and in the first month postpartum, using two heterologous radioimmunoassays (RIA-706 and RIA-srPool) and to study the correlations between PAG levels and fetal gender and number. On Day 18 of pregnancy, PAG concentrations were detected in 90.1% and 80.8% of Sarda pregnant ewes with RIA-706 and RIA-srPool, respectively; and in 90% and in 75% of Lacaune pregnant ewes with RIA-706 and RIA-srPool, respectively. From Day 30, PAG concentrations were detected in all pregnant ewes by using both RIA methods. In the postpartum period, the PAG concentrations in Sarda ewes decreased rapidly reaching minimal levels (<1 ng/mL) on day 28 using both RIA-706 and RIA-srPool. In Lacaune ewes, PAG-706 levels were higher than PAG-srPool from parturition until the last day of observation (Day 28 postpartum). It was also observed that mean concentrations were higher in multiple than in single pregnancies in Sarda and Lacaune ewes. Moreover, due to the rapid disappearance of PAG concentration following lambing, a cut-off limit in postpartum animals was not required as a means for detecting a new pregnancy.

Genetic parameters of weeping teats in Italian Saanen and Alpine dairy goats and their relationship with milk production and somatic cell score

This paper reports a quantitative genetics analysis of weeping teats (WT), an abnormality of the mammary gland in goats. Weeping teats are characterized by milk oozing out of the teat or by the presence of multiple cysts near its base. This abnormality has been routinely recorded in Italian Alpine and Saanen goats since 2000 using a score of 0 or 1 (0 = defect not present, 1 = defect present). No information is available on the genetic background of WT or its relationship with production or other udder-related traits. Data obtained by the Italian National Sheep and Goat Breeders Association (Rome, Italy) were used to estimate both heritability of WT and its genetic correlation with milk yield, somatic cell score, and udder traits. The final data set used in the analysis included 2,178 Saanen and 2,309 Alpine primiparous goats kidding from 2009 to 2014. The pedigree data included 7,333 Saanen and 7,421 Alpines, respectively. A threshold-linear multivariate animal model was used to estimate variance and covariance components. A genealogical data analysis was also implemented, including genealogical data completeness, inbreeding, and identification of possible most recent common ancestors. On average, around 4 and 13% of primiparous Saanen and Alpine females kidding from 2009 to 2014 showed mammary gland abnormality, respectively. Weeping teats heritability was 0.27 and 0.26 for Saanen and Alpine, respectively. Genetic correlations between milk production or somatic cell score ranged from -0.16 in Saanen to 0.43 in Alpine, but the standard error of the estimates was very large. Positive genetic correlations were observed among WT and teat characteristics in both Saanen and Alpine. The average inbreeding of abnormality carriers was 2.4 and 5.1 for Saanen and Alpine, respectively. The genealogical data analysis identified 4 common ancestors of affected does in Saanen and 2 in Alpine. These results indicate that WT have a possible genetic background. A genome-wide association study might help in understanding the polygenic or monogenic determination of this abnormality.

Association of UDP-galactose-4-epimerase with milk protein concentration in the Chinese Holstein population

Objective

An initial RNA-Sequencing study revealed that UDP-galactose-4-epimerase (GALE) was one of the most promising candidates for milk protein concentration in Chinese Holstein cattle. This enzyme catalyzes the interconversion of UDP-galactose and UDP-glucose, an important step in galactose catabolism. To further validate the genetic effect of GALE on milk protein traits, genetic variations were identified, and genotypes-phenotypes associations were performed.

Methods

The entire coding region and the 5′-regulatory region (5′-UTR) of GALE were re-sequenced using pooled DNA of 17 unrelated sires. Association studies for five milk production traits were performed using a mixed linear animal model with a population encompassing 1,027 Chinese Holstein cows.

Results

A total of three variants in GALE were identified, including two novel variants (g.2114 A>G and g.2037 G>A) in the 5′-UTR and one previously reported variant (g.3836 G>C) in an intron. All three single nucleotide polymorphisms (SNPs) were associated with milk yield (p<0.0001), fat yield (p = 0.0006 to <0.0001), protein yield (p = 0.0232 to <0.0001) and protein percentage (p<0.0001), while no significant associations were detected between the SNPs and fat percentage. A strong linkage disequilibrium (D’ = 0.96 to 1.00) was observed among all three SNPs, and a 5 Kb haplotype block involving three main haplotypes with GAG, AGC, and AGG was formed. The results of haplotype association analyses were consistent with the results of single locus association analysis (p<0.0001). The phenotypic variance ratio above 3.00% was observed for milk protein yield that was explained by SNP-g.3836G >C.

Conclusion

Overall, our findings provided new insights into the polymorphic variations in bovine GALE gene and their associations with milk protein concentration. The data indicate their potential uses for marker-assisted breeding or genetic selection schemes.

PrP gene polymorphism and its influence on some productive traits of sheepbreeds reared in Bulgaria

The rapiddissemination of scrapie over the past few decades led to development of aspecific eradication programme, based on the polymorphisms within the prionprotein gene (PRNP). Current approach encourages the selection ofanimals carrying the resistant ARR/ARR genotype, while other genotypes areconsidered less preferable. Although the strategy seems to be working quitewell, farmers are concerned whether this will affect sheep productivity andsubsequently decrease net profits. The current study was aimed to elucidatethe linkage between the PrP gene polymorphism (based on codons 136,154 and 171) and some productive traits (live weight, reproduction, milk andfleece yield) of three sheep breeds reared in Bulgaria – Assaf, NortheastBulgarian Merino and Blackhead Pleven. The total number of detectedgenotypes was six – ARR/ARR, ARR/ARQ, ARR/ARH, ARQ/ARQ, AHQ/ARQ and ARR/VRQ,with different prevalence within each breed. The observed lack ofsignificant differences in the studied performance traits between the PRNP genotypes suggests that PRNP polymorphisms did not influencethe sheep productive performance. Therefore, selection of animals on theresistant genotype (ARR/ARR) would not worsen their productivity. Theobtained results should help the better understanding of scrapie selectionand the positive effect that it would have to both health care and industry.

Mapping genomic regions affecting milk traits in Sarda sheep by using the OvineSNP50 Beadchip and principal components to perform combined linkage and linkage disequilibrium analysis

Background

The detection of regions that affect quantitative traits (QTL), to implement selection assisted by molecular information, remains of particular interest in dairy sheep for which genetic gain is constrained by the high costs of large-scale phenotype and pedigree recording. QTL detection based on the combination of linkage disequilibrium and linkage analysis (LDLA) is the most suitable approach in family-structured populations. The main issue in performing LDLA mapping is the handling of the identity-by-descent (IBD) probability matrix. Here, we propose the use of principal component analysis (PCA) to perform LDLA mapping for milk traits in Sarda dairy sheep.

Methods

A resource population of 3731 ewes belonging to 161 sire families and genotyped with the OvineSNP50 Beadchip was used to map genomic regions that affect five milk traits. The paternally and maternally inherited gametes of genotyped individuals were reconstructed and IBD probabilities between them were defined both at each SNP position and at the genome level. A QTL detection model fitting fixed effects of principal components that summarize IBD probabilities was tested at each SNP position. Genome-wide (GW) significance thresholds were determined by within-trait permutations.

Results

PCA resulted in substantial dimensionality reduction, in fact 137 and 32 (on average) principal components were able to capture 99% of the IBD variation at the locus and genome levels, respectively. Overall, 2563 positions exceeded the 0.05 GW significance threshold for at least one trait, which clustered into 75 QTL regions most of which affected more than one trait. The strongest signal was obtained for protein content on Ovis aries (OAR) chromosome 6 and overlapped with the region that harbours the casein gene cluster. Additional interesting positions were identified on OAR4 for fat content and on OAR11 for the three yield traits.

Conclusions

PCA is a good strategy to summarize IBD probabilities. A large number of regions associated to milk traits were identified. The outputs provided by the proposed method are useful for the selection of candidate genes, which need to be further investigated to identify causative mutations or markers in strong LD with them for application in selection programs assisted by molecular information.

Prediction of Milk Coagulation Properties and Individual Cheese Yield in Sheep Using Partial Least Squares Regression

Simple Summary

Considered that all sheep milk in Italy is destined for cheese processing, traits describing rennet coagulation aptitude should be among the most important selection goals for dairy breeds. To reduce the costs and logistics related to the large-scale recording of these traits, mid-infrared (MIR) spectroscopy could be conveniently used to generate reliable predictions without any additional cost. The aims of this research were to predict the milk coagulation properties (MCP) and individual cheese yield (ILCY) in sheep by MIR spectrometry using partial least squares regression (PLS), and to compare different data pre-treatment procedures. The prediction results observed in the present study, although moderate, suggest the possibility of adding novel phenotypes (e.g., MCP and ILCY) in breeding schemes for dairy sheep breeds. Mid-infrared spectroscopy coupled with PLS regression could allow the prediction of phenotypes at the population level without additional costs.

Abstract

The objectives of this study were (i) the prediction of sheep milk coagulation properties (MCP) and individual laboratory cheese yield (ILCY) from mid-infrared (MIR) spectra by using partial least squares (PLS) regression, and (ii) the comparison of different data pre-treatments on prediction accuracy. Individual milk samples of 970 Sarda breed ewes were analyzed for rennet coagulation time (RCT), curd-firming time (k20), and curd firmness (a30) using the Formagraph instrument; ILCY was measured by micro-manufacturing assays. An Furier-transform Infrared (FTIR) milk-analyzer was used for the estimation of the milk gross composition and the recording of MIR spectrum. The dataset (n = 859, after the exclusion of 111 noncoagulating samples) was divided into two sub-datasets: the data of 700 ewes were used to estimate prediction model parameters, and the data of 159 ewes were used to validate the model. Four prediction scenarios were compared in the validation, differing for the use of whole or reduced MIR spectrum and the use of raw or corrected data (locally weighted scatterplot smoothing). PLS prediction statistics were moderate. The use of the reduced MIR spectrum yielded the best results for the considered traits, whereas the data correction improved the prediction ability only when the whole MIR spectrum was used. In conclusion, PLS achieves good accuracy of prediction, in particular for ILCY and RCT, and it may enable increasing the number of traits to be included in breeding programs for dairy sheep without additional costs and logistics.

Coagulation Traits of Sheep and Goat Milk

Milk production from sheep and goat species is continuously growing worldwide, and its main use is for cheesemaking. Given that the final quality of cheese is linked to the traits of raw milk cheese yield at dairy plants, it is often calculated by using predictive formulas based on fat and protein content. Predictive formulas have been studied for bovine milk and are very effective but not appropriate for sheep and goat milk. Several methods, which simulate the actual coagulation processes, are available at the laboratories. This article reviews the available literature about rennet coagulation and cheese yield traits from sheep and goat milk and the methods used at the laboratory level. In general, if compared to cow milk, sheep and goat milk are characterized by shorter rennet coagulation times and a very limited amount of non-coagulating samples. Curd firmness of sheep milk is almost independent from the rennet coagulation time, and some coagulation traits can be predicted by infrared spectra. In addition, coagulation traits are characterized by appropriate values of heritability to be considered in selective breeding plans. With regard to goat milk, rennet coagulation time and cheese yield are strongly influenced by the breed effect.

Association between the GHR, GHRHR and IGF1 gene polymorphisms and milk coagulation properties in Sarda sheep

We investigated whether variation of the sheep Growth Hormone Receptor (GHR), Growth Hormone Releasing Hormone Receptor (GHRHR) and Insulin-Like Growth Factor 1 (IGF1) genes were associated with milk coagulation properties (MCP) in sheep. The GHR, GHRHR and IGF1 genes are part of the GH system, which is known to modulate metabolism, growth and reproduction as well as mammogenesis and galactopoiesis in dairy species. A total of 380 dairy Sarda sheep were genotyped for 36 SNPs mapping to these three genes. Traditional MCP were measured as rennet coagulation time (RCT), curd-firming time (k20) and curd firmness at 30 m (a30). Modeling of curd firming over time (CFt) was based on a 60 m lactodynamographic test, generating a total of 240 records of curd firmness (mm) for each milk sample. The model parameters obtained included: the rennet coagulation time as a result of modeling all data available (RCTeq, min); the asymptotic potential value of curd firmness (CFP, mm) at an infinite time; the CF instant rate constant (kCF, %/min); the syneresis instant rate constant (kSR, %/min); the maximum value of CF (CFmax, mm) and the time at achievement of CFmax (tmax, min). Statistical analysis revealed that variation of the GHR gene was significantly associated with RCT, kSR and CFP (P < 0.05). No other significant associations were detected. These findings may be useful for the dairy industry, as well as for selection programs.

Effect and Interaction of β-Lactoglobulin, Kappa Casein, and Prolactin Genes on Milk Production and Composition of Awassi Sheep

Simple Summary

Beta-lactoglobulin (β-LG), prolactin (PRL), and Kappa casein (CSN3) all contribute to the determination of milk production and composition, but have not been assessed in local Awassi sheep. Therefore, our aim was to analyze the contribution of these genes in milk production and composition traits in commercial Awassi ewe population by genotyping and sequencing these genes. Our results showed the prevalence of the different variations (alleles) of the tested genes in the Awassi population, and no association among β-LG and CSN3 polymorphic genotypes and milk production, or PRL and fat%. Also, all 3 genes help determine the milk production potential of Awassi ewes and help assess milk components, and thus can be used in breeding programs to select for milk potential.

Abstract

A participatory animal-breeding program was applied to 9 commercial Awassi sheep flocks in Jordan. This study aimed to assess the influence of Beta-lactoglobulin (β-LG), Prolactin (PRL), and Kappa casein (CSN3) genes, genotypes and their interaction on milk production and composition traits of 167 genotyped Awassi ewes via Polymerase Chain Reaction (PCR) followed by sequencing. Allele frequencies for the two variants were 0.42 and 0.58 for β-LG, 0.82 and 0.18 for PRL, and 0.92 and 0.08 for CSN3. No association was found among β-LG and CSN3 polymorphic genotypes with milk production traits. However, ewes with PRL AA genotype showed higher milk production, β-LG AB was associated with lowest fat%, high solid not fat (SNF)%, protein%, and lactose%. β-LG BB was associated with highest milk density. PRL, β-LG, and CSN3 polymorphic genotypes were differentially associated with milk production and component traits. Furthermore, β-LG × PRL interaction showed the highest milk production and fat%; β-LG × PRL recorded the highest SNF%, protein%, lactose%, and milk density, while the PRL × CSN3 had the highest fat% and SNF%. The enhancing effects of these gene interactions can be incorporated in Awassi breeding programs to improve milk production and composition.

Evaluation of reference lactation length in Chios dairy sheep

Definition and establishment of a fixed reference lactation length could provide useful tools for on-farm comparison of ewes and flock management as well as genetic evaluations for the breeding programme. The objectives of this study were to (i) evaluate different reference lactation lengths for the Chios dairy sheep and (ii) define the most suitable reference length for the breed. A total of 260 042 test-day milk records from 24 474 ewes in 130 flocks collected between 2003 and 2014 were used; 15 different lactation lengths were evaluated ranging from 120 to 260 days, defined at 10-day intervals as reference for the Chios sheep. The evaluation criteria included: (a) heritability and repeatability of milk yield in each reference lactation, (b) genetic correlation of reference lactation milk yield with actual lactation milk yield and yield at first test-day record and (c) correlated response in reference lactation milk yield from selection based on first test-day milk yield. The latter emulates genetic gains achieved for milk yield based on early lactation selection. Heritability and repeatability estimates of reference lactation milk yield and genetic correlation with actual lactation yield favoured long reference lactations (180 to 230 days). On the contrary, correlation with first test-day record milk yield was higher for short lactations (120 to 170 days). Moreover, selection on first test-day record milk yield would lead to a correlated response in reference yield in 220 days equal to 85% of the highest estimate achieved in the maximum reference length of 260 days (190 days when only considering first lactation milk yield). Based on the results of the present study, an overall reference lactation length for the Chios breed of 220 days post-lambing and a first lactation reference length of 190 days post-lambing are recommended.

Estimates of genetic parameters, genetic trends, and inbreeding in a crossbred dairy sheep research flock in the United States

For the past 2 decades, the Spooner Agriculture Research Station (ARS) of the University of Wisconsin-Madison operated the only dairy sheep research flock in North America. The objectives of the present study were to 1) obtain estimates of genetic parameters for lactation and reproductive traits in dairy ewes, 2) estimate the amount of genetic change in these traits over time, and 3) quantify the level of inbreeding in this flock over the last 20 yr. Multiple-trait repeatability models (MTRM) were used to analyze ewe traits through their first 6 parities. The first MTRM jointly analyzed milk (180-d-adjusted milk yield [180d MY]), fat (180-d-adjusted fat yield [180d FY]), and protein (180-d-adjusted protein yield [180d PY]) yields adjusted to 180 d of lactation; number of lambs born per ewe lambing (NLB); and lactation average test-day somatic cell score (LSCS). A second MTRM analyzed 180d MY, NLB, LSCS, and percentage milk fat (%F) and percentage milk protein (%P). The 3 yield traits were moderately heritable (0.26 to 0.32) and strongly genetically correlated (0.91 to 0.96). Percentage milk fat and %P were highly heritable (0.53 and 0.61, respectively) and moderately genetically correlated (0.61). Milk yield adjusted to 180 d was negatively genetically correlated with %F and %P (-0.31 and -0.34, respectively). Ewe prolificacy was not significantly ( > 0.67) genetically correlated with yield traits, %P, or LSCS but lowly negatively correlated with %F (-0.26). Lactation somatic cell score was unfavorably genetically correlated with yield traits (0.28 to 0.39) but not significantly ( > 0.09) correlated with %F, %P, and NLB. Within-trait multiple-trait models through the first 4 parities revealed that 180d MY, 180d FY, 180d PY, %F, and %P were strongly genetically correlated across parity (0.67 to 1.00). However, the genetic correlations across parity for NLB and LSCS were somewhat lower (0.51 to 0.96). Regressing predicted breeding values for 180d MY, without and with the addition of breed effects, on ewe year of birth revealed a positive genetic gain of 2.30 and 6.24 kg/yr, respectively, over the past 20 yr in this flock. Inbreeding coefficients of ewes with an extended pedigree ranged from 0.0 to 0.29, with an average of 0.07. To optimize genetic gains and avoid excessive inbreeding, the development of a national genetic improvement program should be a top priority for the growing dairy sheep industry.

Phenotypic and genetic relationships between indicators of the mammary gland health status and milk composition, coagulation, and curd firming in dairy sheep

The present study investigated the effect of somatic cell count, lactose, and pH on sheep milk composition, coagulation properties (MCP), and curd firming (CF) parameters. Individual milk samples were collected from 1,114 Sarda ewes reared in 23 farms. Milk composition, somatic cell count, single point MCP (rennet coagulation time, RCT; curd firming time, k₂₀; and curd firmness, a₃₀, a₄₅, and a₆₀), and CF model parameters were achieved. Phenotypic traits were statistically analyzed using a mixed model to estimate the effects of the different levels of milk somatic cell score (SCS), lactose, and pH, respectively. Additive genetic, herd, and residual correlations among these 3 traits, and with milk composition, MCP and CF parameters, were inferred using a Bayesian approach. From a phenotypic point of view, higher SCS levels caused a delayed gelification of milk. Lactose concentration and pH were significant for many milk quality traits, with a very intense effect on both coagulation times and curd firming. These traits (RCT, RCT estimated using the curd firming over time equation, and k₂₀) showed an unfavorable increase of about 20% from the highest to the lowest level of lactose. Milk samples with pH values lower than 6.56 versus higher than 6.78 were characterized by an increase of RCT (from 6.00 to 14.3 min) and k₂₀ (from 1.65 to 2.65 min) and a decrease of all the 3 curd firmness traits. From a genetic point of view, the marginal posterior distribution of heritability estimates evidenced a large and exploitable variability for all 3 phenotypes. The mean intra-farm heritability estimates were 0.173 for SCS, 0.418 for lactose content, and 0.206 for pH. Lactose (favorably), and SCS and pH (unfavorably), at phenotypic and genetic levels, were correlated mainly with RCT and RCT estimated using the curd firming over time equation and scarcely with the other curd firming traits. The SCS, lactose, and pH were significantly correlated with each other's. In conclusion, results reported in the present study suggest that SCS, pH, and lactose affect, contemporarily and independently, milk quality and MCP. These phenotypes, easily available during milk recording schemes measured by infrared spectra prediction, could be used as potential indicators traits for improving cheese-making ability of ovine milk.

The comparison of the lactation and milk yield and composition of selected breeds of sheep and goats

The objective of this study was to characterize the milk yield (MY) and milk composition of relevant sheep and goat breeds raised around the world to be used with nutrition models for diet formulation and nutrient balancing. A 2-step approach was used. First, a database developed by the Food and Agriculture Organization was used to identify relevant breeds (i.e., frequently raised) by comparing the occurrence of transboundary breed names across countries. We selected transboundary breeds that occurred more than 3 times and other relevant breeds obtained from the specialized literature that had milk production information (e.g., MY, days in milk, and milk fat, protein, and lactose). The majority of sheep breeds were classified as nondairy (76%) because they lacked milk production information. Karakul and Merino accounted for up to 2.4% of sheep breeds raised around the world, whereas the other individual breeds accounted for less than 1%. In contrast, nondairy breeds of goats accounted for 46.3% and of the remaining 53.7%, Saanen, Boer, Anglo-Nubian, Toggenburg, and Alpine accounted for 6.5, 5, 4.4, 4, and 3%, respectively, of the transboundary breeds. Second, a database compiled from published studies for the selected sheep (n = 65) and goats (n = 78) breeds were analyzed using a random coefficients model (studies and treatments within studies as random effects). For sheep breeds, the average and SD were 1.1 ± 0.3 kg/d for MY, 6.9 ± 1% for milk fat, 5.4 ± 0.4% for milk protein, 5 ± 0.3% for milk lactose, 17.7 ± 1.4% for milk total solids, and 1,073 ± 91 kcal/kg of milk energy. Lacaune had the greatest MY compared to Comisana and Tsigai (1.65 versus 0.83 and 0.62 kg/d; respectively, P < 0.05), but milk components were not different among breeds. For goats breeds, the average and SD across breeds were 1.7 ± 0.6 kg/d for MY, 4.2 ± 0.9% for milk fat, 3.3 ± 0.4% for milk protein, 4.4 ± 0.4% for milk lactose, 12.7 ± 1.1% for milk total solids, and 750 ± 75 kcal/kg of milk energy. Alpine had similar MY to Saanen (2.66 versus 2.55 kg/d, respectively; P > 0.05), but greater (P < 0.05) than other breeds. The Boer breed had the greatest milk fat, protein, lactose, and total solids than several other breeds, leading to the greatest milk energy content (907 kcal/kg). Because there are many factors that can alter MY and milk composition, averages provided in this study serve as guidelines, and nutritionists must obtain observed values when using nutrition models.

Factors affecting ewe performance in a crossbred dairy sheep research flock in the United States

The Spooner Agricultural Research Station operated the only dairy sheep research flock in North America through 2016. The original nondairy ewe flock was "bred up" to a crossbred dairy flock through the use of rams and semen of the East Friesian (EF) and Lacaune (LA) dairy breeds. The objective of this study was to determine the environmental and nonadditive genetic effects that influence performance of dairy ewes. The traits analyzed were 180 d adjusted milk (180d MY), fat (180d FY), and protein (180d PY) yields, percentage fat (%F) and protein (%P) in milk, lactation average somatic cell score (LSCS), and number of lambs born per ewe lambing (NLB). The univariate repeatability models included the fixed effects of year of lambing, age, weaning system (except for the trait of NLB), individual breed composition, and individual retained heterosis along with the random additive genetic, permanent environmental, and residual effects. Estimates of heritability were moderate for 180d MY (0.32 ± 0.04), 180d FY (0.26 ± 0.04), and 180d PY (0.29 ± 0.04), high for %F (0.54 ± 0.04) and %P (0.61 ± 0.04), and low for LSCS (0.12 ± 0.03) and NLB (0.08 ± 0.02). Ewes that reared their lambs had lower ( < 0.01) 180d MY, 180d FY, 180d PY, %F, and %P and higher ( < 0.001) LSCS than ewes that had their lambs removed shortly after parturition. Relative to nondairy breeding, EF and LA breeding had positive ( < 0.001) effects on 180d MY, 180d FY, and 180d PY, but a negative ( < 0.03) effect on %P. Purebred EF ewes were predicted to have lower ( < 0.001) %F than purebred LA or nondairy ewes. Purebred LA ewes were predicted to have a higher ( < 0.001) LSCS than purebred EF or nondairy ewes. Purebred EF ewes were expected to be more ( < 0.001) prolific than purebred LA or nondairy ewes. Individual retained heterosis had a favorable ( < 0.01) effect on 180d MY, 180d FY, 180d PY, and NLB. Knowledge of the factors affecting dairy ewe performance are important for dairy sheep producers to make more informed husbandry and breeding decisions.

Variants in the 3' untranslated region of the ovine acetyl-coenzyme A acyltransferase 2 gene are associated with dairy traits and exhibit differential allelic expression

The acetyl-CoA acyltransferase 2 (ACAA2) gene encodes an enzyme of the thiolase family that is involved in mitochondrial fatty acid elongation and degradation by catalyzing the last step of the respective β-oxidation pathway. The increased energy needs for gluconeogenesis and triglyceride synthesis during lactation are met primarily by increased fatty acid oxidation. Therefore, the ACAA2 enzyme plays an important role in the supply of energy and carbon substrates for lactation and may thus affect milk production traits. This study investigated the association of the ACAA2 gene with important sheep traits and the putative functional involvement of this gene in dairy traits. A single nucleotide substitution, a T to C transition located in the 3' untranslated region of the ACAA2 gene, was used in mixed model association analysis with milk yield, milk protein yield and percentage, milk fat yield and percentage, and litter size at birth. The single nucleotide polymorphism was significantly associated with total lactation production and milk protein percentage, with respective additive effects of 6.81 ± 2.95 kg and -0.05 ± 0.02%. Additionally, a significant dominance effect of 0.46 ± 0.21 kg was detected for milk fat yield. Homozygous TT and heterozygous CT animals exhibited higher milk yield compared with homozygous CC animals, whereas the latter exhibited increased milk protein percentage. Expression analysis from age-, lactation-, and parity-matched female sheep showed that mRNA expression of the ACAA2 gene from TT animals was 2.8- and 11.8-fold higher in liver and mammary gland, respectively. In addition, by developing an allelic expression imbalance assay, it was estimated that the T allele was expressed at an average of 18% more compared with the C allele in the udder of randomly selected ewes. We demonstrated for the first time that the variants in the 3' untranslated region of the ovine ACAA2 gene are differentially expressed in homozygous ewes of each allele and exhibit allelic expression imbalance within heterozygotes in a tissue-specific manner, supporting the existence of cis-regulatory DNA variation in the ovine ACAA2 gene. This is the first study reporting differential allelic imbalance expression of a candidate gene associated with milk production traits in dairy sheep.

Estimates of heritability and genetic correlations for milk coagulation properties and individual laboratory cheese yield in Sarda ewes

Objective of this study was to estimate genetic parameters of milk coagulation properties (MCPs) and individual laboratory cheese yield (ILCY) in a sample of 1018 Sarda breed ewes farmed in 47 flocks. Rennet coagulation time (RCT), curd-firming time (k 20) and curd firmness (a 30) were measured using Formagraph instrument, whereas ILCY were determined by a micromanufacturing protocol. About 10% of the milk samples did not coagulate within 30 min and 13% had zero value for k 20. The average ILCY was 36%. (Co)variance components of considered traits were estimated by fitting both single- and multiple-trait animal models. Flock-test date explained from 13% to 28% of the phenotypic variance for MCPs and 26% for ILCY, respectively. The largest value of heritability was estimated for RCT (0.23±0.10), whereas it was about 0.15 for the other traits. Negative genetic correlations between RCT and a 30 (-0.80±0.12), a 30 and k 20 (-0.91±0.09), and a 30 and ILCY (-0.67±0.08) were observed. Interesting genetic correlations between MCPs and milk composition (r G>0.40) were estimated for pH, NaCl and casein. Results of the present study suggest to use only one out of three MCPs to measure milk renneting ability, due to high genetic correlations among them. Moreover, negative correlations between ILCY and MCPs suggest that great care should be taken when using these methods to estimate cheese yield from small milk samples.