Estimation of additive and non-additive genetic effects for fertility and reproduction traits in North American Holstein cattle using genomic information

Non-additive genetic effects are usually ignored in animal breeding programs due to data structure (e.g., incomplete pedigree), computational limitations and over-parameterization of the models. However, non-additive genetic effects may play an important role in the expression of complex traits in livestock species, such as fertility and reproduction traits. In this study, components of genetic variance for additive and non-additive genetic effects were estimated for a variety of fertility and reproduction traits in Holstein cattle using pedigree and genomic relationship matrices. Four linear models were used: (a) an additive genetic model; (b) a model including both additive and epistatic (additive by additive) genetic effects; (c) a model including both additive and dominance effects; and (d) a full model including additive, epistatic and dominance genetic effects. Nine fertility and reproduction traits were analysed, and models were run separately for heifers (N = 5,825) and cows (N = 6,090). For some traits, a larger proportion of phenotypic variance was explained by non-additive genetic effects compared with additive effects, indicating that epistasis, dominance or a combination thereof is of great importance. Epistatic genetic effects contributed more to the total phenotypic variance than dominance genetic effects. Although these models varied considerably in the partitioning of the components of genetic variance, the models including a non-additive genetic effect did not show a clear advantage over the additive model based on the Akaike information criterion. The partitioning of variance components resulted in a re-ranking of cows based solely on the cows’ additive genetic effects between models, indicating that adjusting for non-additive genetic effects could affect selection decisions made in dairy cattle breeding programs. These results suggest that non-additive genetic effects play an important role in some fertility and reproduction traits in Holstein cattle.     

Application of multiple shrinkage methods to genomic predictions

New challenges have arisen with the development of large marker panels for livestock species. Models easily become overparameterized when all available markers are included. Solutions have led to the development of shrinkage or regularization techniques. The objective of this study was the application and comparison of Bayesian LASSO (B-L), thick-tailed (Student-t), and semiparametric multiple shrinkage methods. The B-L and Student-t methods were also each analyzed within a single shrinkage and a multiple shrinkage framework. Simulated and real data were used to evaluate each method's performance. Real data consisted of SNP genotypes of 4,069 Holstein sires. Traits included in analysis of real data were milk, fat, protein yield, and somatic cell score. The performance of each model was compared based on correlations between true and predicted genomic predicted transmitting abilities. Model performance was also compared with the performance of routinely used methods such as Bayes-A and GBLUP through cross-validation techniques. When using simulated data regardless of shrinkage framework, shrinkage models outperformed genomic BLUP (GBLUP). The average advantage of shrinkage models ranged from 1% to approximately 8% depending on the prior specification. When analyzing real data, shrinkage models slightly outperformed GBLUP for most traits. Shrinkage models were better able to model traits for which 1 or more SNP of large effect have been identified. Overall, results suggested a relatively small advantage in multiple shrinkage models. Multiple shrinkage methods could represent a useful alternative to current methods of prediction; however, their performance in a variety of scenarios needs to be investigated further.     

Interpreting the spatio-temporal patterns of sea turtle strandings: Going with the flow

Knowledge of the spatial and temporal distribution of specific mortality sources is crucial for management of species that are vulnerable to human interactions. Beachcast carcasses represent an unknown fraction of at-sea mortalities. While a variety of physical (e.g., water temperature) and biological (e.g., decomposition) factors as well as the distribution of animals and their mortality sources likely affect the probability of carcass stranding, physical oceanography plays a major role in where and when carcasses strand. Here, we evaluate the influence of nearshore physical oceanographic and wind regimes on sea turtle strandings to decipher seasonal trends and make qualitative predictions about stranding patterns along oceanfront beaches. We use results from oceanic drift-bottle experiments to check our predictions and provide an upper limit on stranding proportions. We compare predicted current regimes from a 3D physical oceanographic model to spatial and temporal locations of both sea turtle carcass strandings and drift bottle landfalls. Drift bottle return rates suggest an upper limit for the proportion of sea turtle carcasses that strand (about 20%). In the South Atlantic Bight, seasonal development of along-shelf flow coincides with increased numbers of strandings of both turtles and drift bottles in late spring and early summer. The model also predicts net offshore flow of surface waters during winter - the season with the fewest relative strandings. The drift bottle data provide a reasonable upper bound on how likely carcasses are to reach land from points offshore and bound the general timeframe for stranding post-mortem (< two weeks). Our findings suggest that marine turtle strandings follow a seasonal regime predictable from physical oceanography and mimicked by drift bottle experiments. Managers can use these findings to reevaluate incidental strandings limits and fishery takes for both nearshore and offshore mortality sources.     

Smoke-derived taint in wine: the release of smoke-derived volatile phenols during fermentation of Merlot juice following grapevine exposure to smoke

The release of smoke-derived volatile phenols during the fermentation of Merlot grapes, following grapevine exposure to smoke, has been investigated. The concentrations of guaiacol, 4-methylguaiacol, 4-ethylguaiacol, 4-ethylphenol, and eugenol were determined by gas chromatography-mass spectrometry and found to increase throughout the winemaking process. Only trace levels (< or = 1 microg/L) of guaiacol and 4-methylguaiacol could be detected in free run juice derived from the fruit of smoked vines; the highest levels, 388 microg/L and 93 microg/L, respectively, were observed in the finished wine. Control wine (derived from fruit of unsmoked vines) contained 4 microg/L guaiacol, with the volatile phenols either not detected or detected at only trace levels (< or = 1 microg/L) throughout fermentation. The role of enzyme and acid catalyzed hydrolysis reactions in releasing smoke-derived volatile compounds was also investigated. The volatile phenols were released from smoked free run juice by strong acid hydrolysis (pH 1.0) and enzyme (beta-glucosidase) hydrolysis, but not mild acid hydrolysis (juice pH 3.2-3.7). Guaiacol was again the most abundant smoke-derived phenol, present at 431 microg/L and 325 microg/L in strong acid and enzyme hydrolysates, respectively. Only trace levels of each phenol could be detected in each control hydrolysate. This study demonstrates the potential for under-estimation of smoke taint in fruit and juice samples; the implications for the assessment of smoke taint and quantification of volatile phenols are discussed.     

Separation of selenium, zinc, and copper compounds in bovine whey using size exclusion chromatography linked to inductively coupled plasma mass spectrometry

To study the role of trace elements for the quality and nutritional value of bovine milk, the distribution of selenium, zinc, and copper in whey was investigated using a method linking size exclusion chromatography to inductively coupled plasma mass spectrometry (SEC-ICP-MS). Three major peaks were detected for selenium, two peaks for zinc, and five peaks for copper. More than 65% of the selenium was found in protein fractions, mainly in fractions coinciding with the major whey proteins beta-lactoglobulin and alpha-lactalbumin. All zinc was associated with low molecular weight compounds (<5 kDa) and one of these compounds was probably citrate. More than 60% of the copper eluted in protein fractions and two of the five major peaks probably contained metallothionein and citrate. This method was used to compare milk and whey produced by organic and conventional feeding procedures. The selenium content in whey and desalted milk produced using organic regimens was significantly lower than that in conventional samples. Moreover, the proportion of selenium in protein fractions of organic whey was significantly smaller than that in conventional whey, but the distributions of zinc and copper did not differ. This study showed that with the SEC-ICP-MS technique the distribution profiles of several trace elements in whey could be studied in the same run and that the selenium profile differed in whey produced by organic and conventional procedures.     

Context-Dependent Viral Transgenerational Immune Priming in Honey Bees (Hymenoptera: Apidae)

Transgenerational immune priming is the process of increased resistance to infection in offspring due to parental pathogen exposure. Honey bees (Apis mellifera L. (Hymenoptera: Apidae)) are hosts to multiple pathogens, and this complex immune function could help protect against overwhelming infection. Honey bees have demonstrated transgenerational immune priming for the bacterial pathogen Paenibacillus larvae; however, evidence for viral transgenerational immune priming is lacking across insects in general. Here we test for the presence of transgenerational immune priming in honey bees with Deformed wing virus (DWV) by injecting pupae from DWV-exposed queens and measuring virus titer and immune gene expression. Our data suggest that there is evidence for viral transgenerational immune priming in honey bees, but it is highly context-dependent based on route of maternal exposure and potentially host genetics or epigenetic factors.     

Antiplatelet effects and pharmacodynamics of clopidogrel in cats

OBJECTIVE: To evaluate antiplatelet effects and pharmacodynamics of clopidogrel in cats. DESIGN: Original study. ANIMALS: 5 purpose-bred domestic cats. PROCEDURE: Clopidogrel was administered at dosages of 75 mg, p.o., every 24 hours for 10 days; 37.5 mg, p.o., every 24 hours for 10 days; and 18.75 mg, p.o., every 24 hours for 7 days. In all cats, treatments were administered in this order, with at least 2 weeks between treatments. Platelet aggregation in response to ADP and collagen and oral mucosal bleeding times (OMBTs) were measured before and 3, 7, and 10 days (75 and 37.5 mg) or 7 days (18.75 mg) after initiation of drug administration. Serotonin concentration in plasma following stimulation of platelets with ADP or collagen was measured before and on the last day of drug administration. Platelet aggregation, OMBT, and serotonin concentration were evaluated at various times after drug administration was discontinued to determine when drug effects were lost. RESULTS: For all 3 dosages, platelet aggregation in response to ADP platelet aggregation in response to collagen, and serotonin concentration were significantly reduced and OMBT was significantly increased at all measurement times during drug administration periods. All values returned to baseline values by 7 days after drug administration was discontinued. No significant differences were identified between doses. None of the cats developed adverse effects associated with drug administration. CONCLUSIONS AND CLINICAL RELEVANCE: Results suggest that administration of clopidogrel at dosages ranging from 18.75 to 75 mg, p.o., every 24 hours, results in significant antiplatelet effects in cats.