Differential changes of fat-soluble vitamins and pollutants during lactation in northern elephant seal mother-pup pairs

We investigated the changes of vitamins A and E as well as PCBs and DDTs during lactation in northern elephant seal (Mirounga angustirostris) mother-pup pairs. On average, milk vitamin A concentrations were 6 times higher during late lactation than during early lactation, a pattern that differs dramatically from terrestrial mammals. Vitamin A concentrations also significantly increased in the inner blubber throughout lactation, whereas they remained constant in the outer blubber. Similar dynamics were observed for PCBs and DDTs in maternal blubber and milk. Blubber appears to be an important storage site for vitamin A and organochlorines in seals and a direct transfer of those molecules to the mammary gland may occur. The dynamics of vitamin A, PCBs and DDTs differed from those of vitamin E. There was a significant drop in milk vitamin E concentrations between early and late lactation, which is the usual pattern observed in terrestrial mammals. The dynamics of vitamin E in the blubber layers also differed from those of vitamin A, suggesting different mechanisms of mobilization and transfer into the milk.     

Hormone and metabolite changes associated with extended breeding fasts in male northern elephant seals (Mirounga angustirostris)

We measured metabolic hormones and several key metabolites in breeding adult male northern elephant seals to examine the regulation of fuel metabolism during extended natural fasts of over 3 months associated with high levels of energy expenditure. Males were sampled twice, early and late in the fast, losing an average of 23% of body mass and 47% of adipose stores between measurements. Males exhibited metabolic homeostasis over the breeding fast with no changes in glucose, non-esterified fatty acids, or blood urea nitrogen. Ketoacids increased over the fast but were very low when compared to other fasting species. Changes within individuals in total triiodothyronine (tT₃) were positively related to daily energy expenditure (DEE) and protein catabolism. Differences in levels of thyroid hormones relative to that observed in weaned pups and females suggest a greater deiodination of T₄ to support the high DEE of breeding males. Relative levels of leptin and ghrelin were consistent with the suppression of appetite but a significant reduction in growth hormone across the fast was contrary to expectation in fasting mammals. The lack of the increase in cortisol during fasting found in conspecific weaned pups and lactating females may contribute to the ability of breeding males to spare protein despite high levels of energy expenditure. Together these findings reveal significant differences with conspecifics under varying nutrient demands, suggesting metabolic adaptation to extended high energy fasts.     

A Fast EM Algorithm for BayesA-Like Prediction of Genomic Breeding Values

Prediction accuracies of estimated breeding values for economically important traits are expected to benefit from genomic information. Single nucleotide polymorphism (SNP) panels used in genomic prediction are increasing in density, but the Markov Chain Monte Carlo (MCMC) estimation of SNP effects can be quite time consuming or slow to converge when a large number of SNPs are fitted simultaneously in a linear mixed model. Here we present an EM algorithm (termed “fastBayesA”) without MCMC. This fastBayesA approach treats the variances of SNP effects as missing data and uses a joint posterior mode of effects compared to the commonly used BayesA which bases predictions on posterior means of effects. In each EM iteration, SNP effects are predicted as a linear combination of best linear unbiased predictions of breeding values from a mixed linear animal model that incorporates a weighted marker-based realized relationship matrix. Method fastBayesA converges after a few iterations to a joint posterior mode of SNP effects under the BayesA model. When applied to simulated quantitative traits with a range of genetic architectures, fastBayesA is shown to predict GEBV as accurately as BayesA but with less computing effort per SNP than BayesA. Method fastBayesA can be used as a computationally efficient substitute for BayesA, especially when an increasing number of markers bring unreasonable computational burden or slow convergence to MCMC approaches.     

Accuracy of direct genomic breeding values for nationally evaluated traits in US Limousin and Simmental beef cattle

Background

In national evaluations, direct genomic breeding values can be considered as correlated traits to those for which phenotypes are available for traditional estimation of breeding values. For this purpose, estimates of the accuracy of direct genomic breeding values expressed as genetic correlations between traits and their respective direct genomic breeding values are required.

Methods

We derived direct genomic breeding values for 2239 registered Limousin and 2703 registered Simmental beef cattle genotyped with either the Illumina BovineSNP50 BeadChip or the Illumina BovineHD BeadChip. For the 264 Simmental animals that were genotyped with the BovineHD BeadChip, genotypes for markers present on the BovineSNP50 BeadChip were extracted. Deregressed estimated breeding values were used as observations in weighted analyses that estimated marker effects to derive direct genomic breeding values for each breed. For each breed, genotyped individuals were clustered into five groups using K-means clustering, with the aim of increasing within-group and decreasing between-group pedigree relationships. Cross-validation was performed five times for each breed, using four groups for training and the fifth group for validation. For each trait, we then applied a weighted bivariate analysis of the direct genomic breeding values of genotyped animals from all five validation sets and their corresponding deregressed estimated breeding values to estimate variance and covariance components.

Results

After minimizing relationships between training and validation groups, estimated genetic correlations between each trait and its direct genomic breeding values ranged from 0.39 to 0.76 in Limousin and from 0.29 to 0.65 in Simmental. The efficiency of selection based on direct genomic breeding values relative to selection based on parent average information ranged from 0.68 to 1.28 in genotyped Limousin and from 0.51 to 1.44 in genotyped Simmental animals. The efficiencies were higher for 323 non-genotyped young Simmental animals, born after January 2012, and ranged from 0.60 to 2.04.

Conclusions

Direct genomic breeding values show promise for routine use by Limousin and Simmental breeders to improve the accuracy of predicted genetic merit of their animals at a young age and increase response to selection. Benefits from selecting on direct genomic breeding values are greater for breeders who use natural mating sires in their herds than for those who use artificial insemination sires. Producers with unregistered commercial Limousin and Simmental cattle could also benefit from being able to identify genetically superior animals in their herds, an opportunity that has in the past been limited to seed stock animals.     

Lipoprotein-dependent synthesis of prostacyclin in smooth muscle cells

Low (LDL) and high density lipoproteins (HDL) stimulated prostacycline (PGI2) synthesis in rabbit and human aorta smooth muscle cells growing in culture. The lipoproteins were added to the cells in concentrations equal to that of cholesterol. It was shown that HDL exerted a stronger stimulating effect as compared to LDL. The maximal effect was observed with HDL3. HDL3 isolated from blood serum of healthy volunteers appeared to be more active in PGI2 synthesis promotion than those of CDH patients with documented coronary atherosclerosis. Purified Apo A-1 stimulated the transformation of [14C]arachidonic acid into the products of its metabolism with increased accumulation of 6-keto-PGF1 alpha among labeled metabolites. Estradiol (1.10(-7) M) showed a stimulating effect; norepinephrine (1.10(-6) M) and progesterone (1.10(-7) M) showed an inhibiting effect, whereas corticosterone (1.10(-6) M) and deoxycorticosterone (1.10(-6) M) did not influence the rate of LDL-dependent PGI2 synthesis.