Timing of transcriptomic and proteomic changes in the bovine placentome after parturition.

Proper post-partum reproductive performance is important for reproductive efficiency in beef cows, and dystocia decreases post-partum fertility. Crossbred beef cows (n = 1676) were evaluated for lifetime performance based on degree of dystocia at presentation of the first calf. Cows that experienced moderate or severe dystocia produced fewer calves during their productive life (P < 0.01). The exact mechanism is unclear, but may be due to the contributions of dystocia to abnormal placental separation. Proteolytic activity is hypothesized to contribute to placental separation in ruminants; however, when ovine placentomes were collected following caesarian section, no proteolytic activity was detected. We hypothesized that stage 2 of parturition was necessary to stimulate proteolysis and initiate placental separation. Serial placentome collections were performed on mature cows (n = 21 initiated; 7 with complete sampling) at hourly intervals for the first 2 h after expulsion of the calf. An intact piece of each placentome was fixed for histological evaluation, and a separate piece of caruncular and cotyledonary tissue from each placentome was frozen for transcriptomic and proteolytic analysis. A full set of placentomes was collected from only 7 of 21 cows at 0, 1, and 2 h, and all cows had expelled fetal membranes by 6 h. Histological, transcriptomic and proteolytic analysis was performed on placentomes from cows from which three placentomes were collected (n = 7). The microscopic distance between maternal and fetal tissues increased at 1 h (P = 0.01). Relative transcript abundance of matrix metalloprotease 14 (MMP14) tended to increase with time (P = 0.06). The relative transcript abundance of plasminogen activator urokinase-type (PLAU) was greater in caruncles than cotyledons (P = 0.01), and tended (P = 0.10) to increase in the caruncle between 0 and 2 h while remaining unchanged in the cotyledon over the same span of time. Greater PLAU and plasminogen activator tissue-type (PLAT) proteolytic activity was detected by zymography in the caruncle than the cotyledon immediately post-partum (P < 0.01). From these findings we conclude that 1) dystocia during the first parity decreases lifetime productivity in beef cattle, 2) the PA system is present at both the transcript and protein level in the bovine plactentome during parturition and 3) proteolytic activity is localized to the caruncular aspect of the placentome.

Comparison of Bayesian models to estimate direct genomic values in multi-breed commercial beef cattle.

BACKGROUND: While several studies have examined the accuracy of direct genomic breeding values (DGV) within and across purebred cattle populations, the accuracy of DGV in crossbred or multi-breed cattle populations has been less well examined. Interest in the use of genomic tools for both selection and management has increased within the hybrid seedstock and commercial cattle sectors and research is needed to determine their efficacy. We predicted DGV for six traits using training populations of various sizes and alternative Bayesian models for a population of 3240 crossbred animals. Our objective was to compare alternate models with different assumptions regarding the distributions of single nucleotide polymorphism (SNP) effects to determine the optimal model for enhancing feasibility of multi-breed DGV prediction for the commercial beef industry. RESULTS: Realized accuracies ranged from 0.40 to 0.78. Randomly assigning 60 to 70% of animals to training (n ≈ 2000 records) yielded DGV accuracies with the smallest coefficients of variation. Mixture models (BayesB95, BayesCπ) and models that allow SNP effects to be sampled from distributions with unequal variances (BayesA, BayesB95) were advantageous for traits that appear or are known to be influenced by large-effect genes. For other traits, models differed little in prediction accuracy (~0.3 to 0.6%), suggesting that they are mainly controlled by small-effect loci. CONCLUSIONS: The proportion (60 to 70%) of data allocated to training that optimized DGV accuracy and minimized the coefficient of variation of accuracy was similar to large dairy populations. Larger effects were estimated for some SNPs using BayesA and BayesB95 models because they allow unequal SNP variances. This substantially increased DGV accuracy for Warner-Bratzler Shear Force, for which large-effect quantitative trait loci (QTL) are known, while no loss in accuracy was observed for traits that appear to follow the infinitesimal model. Large decreases in accuracy (up to 0.07) occurred when SNPs that presumably tag large-effect QTL were over-regressed towards the mean in BayesC0 analyses. The DGV accuracies achieved here indicate that genomic selection has predictive utility in the commercial beef industry and that using models that reflect the genomic architecture of the trait can have predictive advantages in multi-breed populations.