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This review article examines the role of selenium (Se) and the effects of Se supplementation especially in the bovine species. Selenium is an important trace element in cattle. Some of its roles include the participation in the antioxidant defense the cattle farms. The nutritional requirements of Se in cattle are estimated at 100 μg/kg DM (dry matter) for beef cattle and at 300 μg/kg DM for dairy cows. The rations high in fermentable carbohydrates, nitrates, sulfates, calcium or hydrogen cyanide negatively influence the organism’s use of the selenium contained in the diet. The Se supplementation may reduce the incidence of metritis and ovarian cysts during the postpartum period. The increase in fertility when adding Se is attributed to the reduction of the embryonic death during the first month of gestation. A use of organic Se in feed would provide a better transfer of Se in calves relative to mineral Se supplementation. The addition of Se yeasts in the foodstuffs of cows significantly increases the Se content and the percentage of polyunsaturated fatty acids (PUFA) in milk compared to the addition of sodium selenite. The enzyme 5-iodothyronine deiodinase is a seleno-dependent selenoprotein. It is one of the last proteins to be affected in the event of Se deficiency. This delay in response could explain the fact that several studies did not show the effect of Se supplementation on growth and weight gain of calves. Enrichment of Se in the diet did not significantly affect the slaughter weight and carcass yield of bulls. The impact and results of Se supplementation in cattle depend on physiological stage, Se status of animals, type and content of Se and types of Se administration. Further studies in Se supplementation should investigate the speciation of Se in food and yeasts, as well as understanding their metabolism and absorption. This constitute a path to exploit in order to explain certain different effects of Se.

The estimation of the inbreeding coefficient (F) is essential for the study of inbreeding depression (ID) or for the management of populations under conservation. Several methods have been proposed to estimate the realized F using genetic markers, but it remains unclear which one should be used. Here we used whole-genome sequence data for 245 individuals from a Holstein cattle pedigree to empirically evaluate which estimators best capture homozygosity at variants causing ID, such as rare deleterious alleles or loci presenting heterozygote advantage and segregating at intermediate frequency. Estimators relying on the correlation between uniting gametes (FUNI) or on the genomic relationships (FGRM) presented the highest correlations with these variants. However, homozygosity at rare alleles remained poorly captured. A second group of estimators relying on excess homozygosity (FHOM), homozygous-by-descent segments (FHBD), runs-of-homozygosity (FROH) or on the known genealogy (FPED) was better at capturing whole-genome homozygosity, reflecting the consequences of inbreeding on all variants, and for young alleles with low to moderate frequencies (0.10 < . < 0.25). The results indicate that FUNI and FGRM might present a stronger association with ID. However, the situation might be different when recessive deleterious alleles reach higher frequencies, such as in populations with a small effective population size. For locus-specific inbreeding measures or at low marker density, the ranking of the methods can also change as FHBD makes better use of the information from neighboring markers. Finally, we confirmed that genomic measures are in general superior to pedigree-based estimates. In particular, FPED was uncorrelated with locus-specific homozygosity.

Background Fitting covariates representing the number of haplotype alleles rather than single nucleotide polymorphism (SNP) alleles may increase genomic prediction accuracy if linkage disequilibrium between quantitative trait loci and SNPs is inadequate. The objectives of this study were to evaluate the accuracy, bias and computation time of Bayesian genomic prediction methods that fit fixed-length haplotypes or SNPs. Genotypes at 37,740 SNPs that were common to Illumina BovineSNP50 and high-density panels were phased for ~58,000 New Zealand dairy cattle. Females born before 1 June 2008 were used for training, and genomic predictions for milk fat yield (n = 24,823), liveweight (n = 13,283) and somatic cell score (n = 24,864) were validated within breed (predominantly Holstein–Friesian, predominantly Jersey, or admixed KiwiCross) in later-born females. Covariates for haplotype alleles of five lengths (125, 250, 500 kb, 1 or 2 Mb) were generated and rare haplotypes were removed at four thresholds (1, 2, 5 or 10%), resulting in 20 scenarios tested. Genomic predictions fitting covariates for either SNPs or haplotypes were calculated by using BayesA, BayesB or BayesN. This is the first study to quantify the accuracy of genomic prediction using haplotypes across the whole genome in an admixed population. Results A correlation of 0.349 ± 0.016 between yield deviation and genomic breeding values was obtained for milk fat yield in Holstein–Friesians using BayesA fitting covariates. Genomic predictions were more accurate with short haplotypes than with SNPs but less accurate with longer haplotypes than with SNPs. Fitting only the most frequent haplotype alleles reduced computation time with little decrease in prediction accuracy for short haplotypes. Trends were similar for all traits and breeds and there was little difference between Bayesian methods. Conclusions Fitting covariates for haplotype alleles rather than SNPs can increase prediction accuracy, although it decreased drastically for long (>500 kb) haplotypes. In this population, fitting 250 kb haplotypes with a 1% frequency threshold resulted in the highest genomic prediction accuracy and fitting 125 kb haplotypes with a 10% frequency threshold improved genomic prediction accuracy with comparable computation time to fitting SNPs. This increased accuracy is likely to increase genetic gain by changing the ranking of selection candidates.

In the present study, records on 115,291 heifers distributed in 113 herds were used to investigate the association between age at the first calving ( AFC ) and lactation performance, lactation curve, the length of the first calving interval ( CI ), calf birth weight ( CBW ), and the incidence of dystocia in Holstein heifers in Iran. Based on the AFC, the heifers were classified into eight classes: AFC of 541 to 690 d, 691 to 720 d, 721 to 750 d, 751 to 780 d, 781 to 810 d, 811 to 840 d, 841 to 900 d, and 901 to 1200 d (AFC1 to AFC8, respectively). Multiple regression mixed models were used to investigate the association between AFC and lactation curve parameters, partial and 305-d lactation performance, 100- and 305-d SCS, and the length of the first calving (CI) interval. The mean (SD) and median AFC across all heifers was 760.2 (74.01) and 750 d, respectively. Of 115,291 heifers included, 28,192 and 7,602 heifers were, respectively, ≤ 720 and > 900 d when calving for the first time. More than 44% of the heifers were at 691 to 750 d (23 to 25 months) of age when calving for the first time. An increased AFC was associated with increased partial and 305-d lactation performance, 100- and 305-d SCS, initial milk yield, milk production at the peak of lactation, upward and downward slopes of the lactation curve. The 305-d fat percentage was associated with AFC; however, there was no association between AFC and 305-d protein percentage. An increased AFC was also associated with decreased milk production persistency, delayed peak time, longer CI, and higher calf birth weight. Compared to heifers calving for the first time between 691 to 780 d (23 to 26 months) of age, both increasing and decreasing AFC were associated with increased risk of dystocia. Controlling AFC is an important management factor in achieving a lower risk of dystocia, higher lactation performance, lower SCS, and shorter length of the calving interval.

Myogenin is a protein in the myogenic regulatory factor family that plays an important role in determining carcass and meat traits and is vital for the growth and development of livestock muscles. The objective of this study was to determine the impact of Origanum majorana leaf (MOL) on the myogenin gene expression of lambs. Twenty-four male Kermani lambs were used in a completely randomized design using two experimental groups (0% Origanum majorana L. = MOL0 and 4% Origanum majorana L. = MOL4). Final weight, average daily gain, hot and cold carcass weight, feed conversion ratio, empty body weight, hot and cold dressing percentage, the weight of the shoulder, loin, leg, and lean meat, and the lean/bone ratio were measured. A standard kit was used for extracting total RNA from the loin, leg, and shoulder muscles of the lambs’ tissues. The cDNA was synthesized, a real-time PCR was performed, and the obtained data were analyzed. The results of this study showed that the effect of MOL4 on dry matter intake is not significant. The MOL4 diet increased final weight by 8.22%, average daily gain by 28.57%, hot carcass weight by 11.38%, cold carcass weight by 13.43%, feed conversion ratio by 31.03%, empty body weight by 9.38%, hot dressing percentage by 2.92%, cold dressing percentage by 3.75%, shoulder weight by 56.70%, loin weight by 8.98%, leg weight by 10.90%, lean meat weight by 14.62%, and the lean/bone ratio by 2.85% (p < 0.05) compared to the MOL0. Along with adding MOL4 in the lambs’ diets, in comparison with MOL0, there was higher expression of myogenin in the loin (3.5 times), leg (3.9 times), and shoulder (3.6 times) muscles of the lambs. Due to the fact that adding Origanum majorana to the diet of the lambs enhanced the expression of the myogenin gene in the loin, leg, and shoulder muscles and increased parameters related to growth, it can be used to improve the parameters related to growth and to increase myogenin gene expression in the muscle of lambs.

Clinical mastitis (CM) is an inflammatory disease occurring in the mammary glands of lactating cows. CM is under genetic control, and a prominent CM resistance QTL located on chromosome 6 was reported in various dairy cattle breeds. Nevertheless, the biological mechanism underpinning this QTL has been lacking. Herein, we mapped, fine-mapped, and discovered the putative causal variant underlying this CM resistance QTL in the Dutch dairy cattle population. We identified a ~12 kb multi-allelic copy number variant (CNV), that is in perfect linkage disequilibrium with a lead SNP, as a promising candidate variant. By implementing a fine-mapping and through expression QTL mapping, we showed that the group-specific component gene ( GC ), a gene encoding a vitamin D binding protein, is an excellent candidate causal gene for the QTL. The multiplicated alleles are associated with increased GC expression and low CM resistance. Ample evidence from functional genomics data supports the presence of an enhancer within this CNV, which would exert cis -regulatory effect on GC . We observed that strong positive selection swept the region near the CNV, and haplotypes associated with the multiplicated allele were strongly selected for. Moreover, the multiplicated allele showed pleiotropic effects for increased milk yield and reduced fertility, hinting that a shared underlying biology for these effects may revolve around the vitamin D pathway. These findings together suggest a putative causal variant of a CM resistance QTL, where a cis -regulatory element located within a CNV can alter gene expression and affect multiple economically important traits.

The inbreeding coefficient (F) of individuals can be estimated from molecular marker data, such as SNPs, using measures of homozygosity of individual markers or runs of homozygosity (ROH) across the genome. These different measures of F can then be used to estimate the rate of inbreeding depression (ID) for quantitative traits. Some recent simulation studies have investigated the accuracy of this estimation with contradictory results. Whereas some studies suggest that estimates of inbreeding from ROH account more accurately for ID, others suggest that inbreeding measures from SNP‐by‐SNP homozygosity giving a large weight to rare alleles are more accurate. Here, we try to give more light on this issue by carrying out a set of computer simulations considering a range of population genetic parameters and population sizes. Our results show that the previous studies are indeed not contradictory. In populations with low effective size, where relationships are more tight and selection is relatively less intense, F measures based on ROH provide very accurate estimates of ID whereas SNP‐by‐SNP‐based F measures with high weight to rare alleles can show substantial upwardly biased estimates of ID. However, in populations of large effective size, with more intense selection and trait allele frequencies expected to be low if they are deleterious for fitness because of purifying selection, average estimates of ID from SNP‐by‐SNP‐based F values become unbiased or slightly downwardly biased and those from ROH‐based F values become slightly downwardly biased. The noise attached to all these estimates, nevertheless, can be very high in large‐sized populations. We also investigate the relationship between the different F measures and the homozygous mutation load, which has been suggested as a proxy of inbreeding depression.

Tannins are secondary metabolites naturally present in various plants as a defense mechanism. In animal nutrition, they play a dual role, acting as both antinutritional factors and bioactive agents, with potential benefits in nutrient metabolism and product quality. This meta-analysis aimed to evaluate the effects of dietary tannin on nutrient intake and digestibility, blood serum metabolite levels, growth performance, carcass characteristics, and meat quality in small ruminants. Ninety-seven studies were included in this meta-analysis. The effects of tannins were analyzed using a random-effects model to determine the weighted mean difference between treatments with tannins and the control (without tannins). Publication bias and heterogeneity between studies were explored, and meta-regression and subgroup analyses were performed. The results indicated that tannin significantly increased the intake of dry matter, crude protein, nitrogen (N), fecal N, and meat fatty acids (FA), such as C18:2 ω6, C18:3 ω3, C20:4 ω6, C20:5 ω3, total ω3 and ω6 FA, and total polyunsaturated FA (PUFA). However, NH3-N, urinary N, blood urea nitrogen, cold carcass weight, subcutaneous fat thickness, drip loss, and nutrient digestibility decreased. In conclusion, tannin in small ruminants did not affect animal productivity and antioxidative status, but mainly modified nitrogen metabolism and improved the fatty acid profile of meat.

In dairy cattle, the widespread use of artificial insemination has resulted in increased selection intensity, which has led to spectacular increase in productivity. However, cow fertility has concomitantly severely declined. It is generally assumed that this reduction is primarily due to the negative energy balance of high-producing cows at the peak of lactation. We herein describe the fine-mapping of a major fertility QTL in Nordic Red cattle, and identify a 660-kb deletion encompassing four genes as the causative variant. We show that the deletion is a recessive embryonically lethal mutation. This probably results from the loss of RNASEH2B, which is known to cause embryonic death in mice. Despite its dramatic effect on fertility, 13%, 23% and 32% of the animals carry the deletion in Danish, Swedish and Finnish Red Cattle, respectively. To explain this, we searched for favorable effects on other traits and found that the deletion has strong positive effects on milk yield. This study demonstrates that embryonic lethal mutations account for a non-negligible fraction of the decline in fertility of domestic cattle, and that associated positive effects on milk yield may account for part of the negative genetic correlation. Our study adds to the evidence that structural variants contribute to animal phenotypic variation, and that balancing selection might be more common in livestock species than previously appreciated.

Mammalian species carry ~100 loss-of-function variants per individual 1 , 2 , where ~1–5 of these impact essential genes and cause embryonic lethality or severe disease when homozygous 3 . The functions of the remainder are more difficult to resolve, although the assumption is that these variants impact fitness in less manifest ways. Here we report one of the largest sequence-resolution screens of cattle to date, targeting discovery and validation of non-additive effects in 130,725 animals. We highlight six novel recessive loci with impacts generally exceeding the largest-effect variants identified from additive genome-wide association studies, presenting analogs of human diseases and hitherto-unrecognized disorders. These loci present compelling missense ( PLCD4 , MTRF1 and DPF2 ), premature stop ( MUS81 ) and splice-disrupting ( GALNT2 and FGD4 ) mutations, together explaining substantial proportions of inbreeding depression. These results demonstrate that the frequency distribution of deleterious alleles segregating in selected species can afford sufficient power to directly map novel disorders, presenting selection opportunities to minimize the incidence of genetic disease. An association model that estimates dominance and additive effects applied to imputed whole-genome data from cattle allows for the mapping of recessive syndromes in the absence of disease classification by using proxy phenotypes such as body weight.