Characterization of biological types of cattle (Cycle VII): influence of postpartum interval and estrous cycle length on fertility

Genetic improvement in reproductive efficiency through selection is difficult because many reproductive traits are binomial and have low heritabilities. Before genetic markers can be generated for fertility in cows, greater characterization of reproductive phenotypes is needed to understand the components of the trait. The current study tested the hypotheses that: 1) breeds vary in postpartum interval to estrus (PPIE) and estrous cycle length, 2) a longer estrous cycle immediately before breeding increased pregnancy rates, and 3) a greater number of cycles before breeding increased conception rates. The postpartum interval to estrus, estrous cycle length, and number of cycles before breeding were examined in F1 cows (n = 519) obtained from mating Hereford, Angus, and MARC III cows to Hereford, Angus, Simmental, Limousin, Charolais, Gelbvieh, and Red Angus sires. Cows were classified as having 0, 1, 2, or 3 observed estrous cycles before breeding. All traits analyzed were adjusted to constant BCS. Sire breed of the cow influenced length of the PPIE and number of cycles before the start of breeding (P <0.001). Simmental-sired cows had the shortest PPIE and greatest number of cycles before breeding, whereas Limousin-sired cows had the longest PPIE and least number of cycles before breeding. Cows with a greater number of cycles before breeding did not have greater conception rates than cows that had not exhibited standing estrus before breeding (P = 0.87). In cows that cycled before breeding, the length of the estrous cycle immediately before breeding was influenced by dam breed and BCS (P <0.01). Cows out of Hereford dams had shorter estrous cycles than cows out of MARC III or Angus dams, and estrous cycle length increased as BCS increased. Conception rate decreased as length of the estrous cycle immediately before breeding increased (P = 0.05, -2.2% per d of cycle length). Therefore, previously anestrous cows were just as likely to conceive as cows that had cycled before breeding, and an increased number of observed estrous cycles before breeding did not increase conception rates. There may be an influence of the length of estrous cycle immediately before breeding on conception rates, possibly because a longer estrous cycle results in a persistent follicle with greater potential for a lower quality oocyte. Breed differences in PPIE and estrous cycle length suggest that there are genetic components to these traits.     

Cattle selected for lower residual feed intake have reduced daily methane production

Seventy-six Angus steers chosen from breeding lines divergently selected for residual feed intake (RFI) were studied to quantify the relationship between RFI and the daily rate of methane production (MPR). A 70-d feeding test using a barley-based ration was conducted in which the voluntary DMI, feeding characteristics, and BW of steers were monitored. The estimated breeding value (EBV) for RFI (RFI(EBV)) for each steer had been calculated from 70-d RFI tests conducted on its parents. Methane production rate (g/d) was measured on each steer using SF(6) as a tracer gas in a series of 10-d measurement periods. Daily DMI of steers was lower during the methane measurement period than when methane was not being measured (11.18 vs. 11.88 kg; P = 0.001). A significant relationship existed between MPR and RFI when RFI (RFI(15d)) was estimated over the 15 d when steers were harnessed for methane collection (MPR = 13.3 x RFI(15d) + 179; r(2) = 0.12; P = 0.01). Animals expressing lower RFI had lower daily MPR. The relationship established between MPR and RFI(15d) was used to calculate a reduction in daily methane emission of 13.38 g accompanied a 1 kg/d reduction in RFI(EBV) in cattle consuming ad libitum a diet of 12.1 MJ of ME/kg. The magnitude of this emission reduction was between that predicted on the basis of intake reduction alone (18 g x d(-1) x kg of DMI(-1)) and that predicted by a model incorporating steer midtest BW and level of intake relative to maintenance (5 g x d(-1) x kg of DMI(-1)). Comparison of data from steers exhibiting the greatest (n = 10) and lowest (n = 10) RFI(15d) showed the low RFI(15d) group to not only have lower MPR (P = 0.017) but also reduced methane cost of growth (by 41.2 g of CH(4)/kg of ADG; P = 0.09). Although the opportunity to abate livestock MPR by selection against RFI seems great, RFI explained only a small proportion of the observed variation in MPR. A genotype x nutrition interaction can be anticipated, and the MPR:RFI(EBV) relationship will need to be defined over a range of diet types to account for this.     

The impact of dietary protein source on observed and predicted metabolizable energy of dry extruded dog foods

Fifty-five observations were used to determine the ME content of 8 foods containing different protein sources. The major protein sources tested included low-oligosaccharide whole soybeans; 2 low-oligosaccharide, low-phytate whole soybeans; 2 conventional soybean meals; low-ash poultry meal; low-oligosaccharide, low-phytate soybean meal; and conventional whole soybeans. The ME content of all foods ranged from 3,463 to 4,233 kcal/kg of DM. The first objective was to utilize the observed ME data and test the accuracy of the modified Atwater equation. In this study, the modified Atwater equation generally underpredicted ME compared with the observed ME (residual mean = 247 kcal/kg). The second objective was to use individual data to develop an equation, based on the chemical composition of the food, to predict the ME content of the foods. A multivariate regression analysis was used to predict ME content based on chemical composition. Five models were fitted to the data. Model 1 included CP, ether extract (EE), and crude fiber (CF). Because the foods varied in protein sources, and the ratio of total AA (TAA) to non-AA (NAA) CP ranged from 3.5:1 to 14.4:1, it was hypothesized that accounting for the proportion of TAA and NAA in CP would improve the fit of the model. Therefore, model 2 included TAA, NAA, EE, and CF. Defining CP in terms of TAA and NAA improved the r2 of the model from 0.46 to 0.79. Subsequently, models 3, 4, and 5 replaced the CF term with ADF, NDF, and hemicellulose (HEM). Model 3 included TAA, NAA, EE, and NDF. Model 4 included TAA, NAA, EE, ADF, and HEM. Model 5 included TAA, NAA, EE, and HEM. Defining dietary fiber in terms of HEM improved the r2 of model 2 from 0.79 to 0.81. Residual analysis suggested that replacing the CF term with HEM (model 5) improved the prediction of ME content. In contrast, defining fiber in terms of NDF (model 3) did not result in an improvement over model 2, whereas the ADF term (model 4) did not (P > 0.34) contribute to the overall model. Fractionating CP into TAA and NAA components further defined the chemical composition of the food. These data suggest that defining protein composition improves the accuracy of predicting the ME content of dog foods.     

Detection of single nucleotide polymorphisms associated with ultrasonic backfat depth in a segregating Meishan x White Composite population

Multiple genomic scans have identified QTL for backfat deposition across the porcine genome. The objective of this study was to detect SNP and genomic regions associated with ultrasonic backfat. A total of 74 SNP across 5 chromosomes (SSC 1, 3, 7, 8, and 10) were selected based on their proximity to backfat QTL or to QTL for other traits of interest in the experimental population. Gilts were also genotyped for a SNP thought to influence backfat in the thyroxine-binding globulin gene (TBG) on SSC X. Genotypic data were collected on 298 gilts, divided between the F8 and F10 generations of the US Meat Animal Research Center Meishan resource population (composition, one-quarter Meishan). Backfat depths were recorded by ultrasound from 3 locations along the back at approximately 210 and 235 d of age in the F8 and F10 generations, respectively. Ultrasound measures were averaged for association analyses. Regressors for additive, dominant, and parent-of-origin effects of each SNP were calculated using genotypic probabilities computed by allelic peeling algorithms in GenoProb. The association model included the fixed effects of scan date and TBG genotype, the covariates of weight and SNP regressors, and random additive polygenic effects to account for genetic similarities between animals not explained by known genotypes. Variance components for polygenic effects and error were estimated using MTDFREML. Initially, each SNP was fitted (once with and once without parent-of-origin effects) separately due to potential multi-collinearity between regressions of closely linked markers. To form a final model, all significant SNP across chromosomes were included in a common model and were individually removed in successive iterations based on their significance. Across all analyses, TBG was significant, with an additive effect of approximately 1.2 to 1.6 mm of backfat. Three SNP on SSC3 remained in the final model even though few studies have identified QTL for backfat on this chromosome. Two of these SNP exhibited irregular parent-of-origin effects and may not have been detected in other genome scans. One significant SNP on SSC7 remained in the final, backward-selected model; the estimated effect of this marker was similar in magnitude and direction to previously identified QTL. This SNP can potentially be used to introgress the leaner Meishan allele into commercial swine populations.     

Weaning weight inheritance in environments classified by maternal body weight change

In good environments, cow intake is sufficient for their own growth and for milk production to support their calf. In poor environments, cows lose BW or may reduce milk supply to maintain themselves. Heritability for direct genetic and maternal components of weaning weight as well as the correlations between these components might be expected to vary according to these circumstances. The purpose of this study was to estimate heritability and genetic correlations for the direct genetic and maternal components of weaning weight classified in 2 environments according to maternal BW gain and to identify whether a single heritability estimate is appropriate for the differing environments experienced by cows from year to year. Data used in this analysis was obtained from the Red Angus Association of America and consisted of 96,064 cow BW observations and 27,534 calf weaning weight observations. A dam's change in BW from one year to the next was used to classify each calf's weaning weight into 1 of 2 environmental groups, those being good or poor. Best linear unbiased estimates of the change in cow BW with age were obtained from analysis of cow BW using a repeatability model. If the phenotypic change in cow BW exceeded this average BW change, the calf's weaning weight associated with the end of this time frame was classified as having been observed in a good environment. If not, the calf's corresponding weaning weight was classified as having occurred in a poorer than average environment. Heritability estimates of 0.24 +/- 0.03, 0.24 +/- 0.03, 0.13 +/- 0.02, and 0.14 +/- 0.02 were obtained for weaning weight good direct, poor direct, good maternal, and poor maternal, respectively. Correlations between direct genetic and maternal weaning weight components in the good and poor environments were -0.47 +/- 0.08 and -0.20 +/- 0.09, respectively. These variance components are not sufficiently distinct to warrant accounting for dam nutritional environment in national cattle evaluation.