Investigating the persistence of accuracy of genomic predictions over time in broilers

Accuracy of genomic predictions is an important component of the selection response. The objectives of this research were: 1) to investigate trends for prediction accuracies over time in a broiler population of accumulated phenotypes, genotypes, and pedigrees and 2) to test if data from distant generations are useful to maintain prediction accuracies in selection candidates. The data contained 820K phenotypes for a growth trait (GT), 200K for two feed efficiency traits (FE1 and FE2), and 42K for a carcass yield trait (CY). The pedigree included 1,252,619 birds hatched over 7 years, of which 154,318 from the last 4 years were genotyped. Training populations were constructed adding 1 year of data sequentially, persistency of accuracy over time was evaluated using predictions from birds hatched in the three generations following or in the years after the training populations. In the first generation, before genotypes became available for the training populations (first 3 years of data), accuracies remained almost stable with successive additions of phenotypes and pedigree to the accumulated dataset. The inclusion of 1 year of genotypes in addition to 4 years of phenotypes and pedigree in the training population led to increases in accuracy of 54% for GT, 76% for FE1, 110% for CY, and 38% for FE2; on average, 74% of the increase was due to genomics. Prediction accuracies declined faster without than with genomic information in the training populations. When genotypes were unavailable, the average decline in prediction accuracy across traits was 41% from the first to the second generation of validation, and 51% from the second to the third generation of validation. When genotypes were available, the average decline across traits was 14% from the first to the second generation of validation, and 3% from the second to the third generation of validation. Prediction accuracies in the last three generations were the same when the training population included 5 or 2 years of data, and a decrease of ~7% was observed when the training population included only 1 year of data. Training sets including genomic information provided an increase in accuracy and persistence of genomic predictions compared with training sets without genomic data. The two most recent years of pedigree, phenotypic, and genomic data were sufficient to maintain prediction accuracies in selection candidates. Similar conclusions were obtained using validation populations per year.     

Measurements of the equation of state of deuterium at the fluid insulator-metal transition

A high-intensity laser was used to shock-compress liquid deuterium to pressures from 22 to 340 gigapascals. In this regime deuterium is predicted to transform from an insulating molecular fluid to an atomic metallic fluid. Shock densities and pressures, determined by radiography, revealed an increase in compressibility near 100 gigapascals indicative of such a transition. Velocity interferometry measurements, obtained by reflecting a laser probe directly off the shock front in flight, demonstrated that deuterium shocked above 55 gigapascals has an electrical conductivity characteristic of a liquid metal and independently confirmed the radiography.     

Modeling genetic differences of combined broiler chicken populations in single-step GBLUP

The introduction of animals from a different environment or population is a common practice in commercial livestock populations. In this study, we modeled the inclusion of a group of external birds into a local broiler chicken population for the purpose of genomic evaluations. The pedigree was composed of 242,413 birds and genotypes were available for 107,216 birds. A five-trait model that included one growth, two yield, and two efficiency traits was used for the analyses. The strategies to model the introduction of external birds were to include a fixed effect representing the origin of parents and to use unknown parent groups (UPG) or metafounders (MF). Genomic estimated breeding values (GEBV) were obtained with single-step GBLUP using the Algorithm for Proven and Young. Bias, dispersion, and accuracy of GEBV for the validation birds, that is, from the most recent generation, were computed. The bias and dispersion were estimated with the linear regression (LR) method,whereas accuracy was estimated by the LR method and predictive ability. When fixed UPG were fit without estimated inbreeding, the model did not converge. In contrast, models with fixed UPG and estimated inbreeding or random UPG converged and resulted in similar GEBV. The inclusion of an extra fixed effect in the model made the GEBV unbiased and reduced the inflation. Genomic predictions with MF were slightly biased and inflated due to the unbalanced number of observations assigned to each metafounder. When combining local and external populations, the greatest accuracy can be obtained by adding an extra fixed effect to account for the origin of parents plus UPG with estimated inbreeding or random UPG. To estimate the accuracy, the LR method is more consistent among scenarios, whereas the predictive ability greatly depends on the model specification.     

Prevalence of Cysticercus bovis in Australian cattle

Objective The first national abattoir survey of Cysticercus bovis (‘beef measles’) in cattle was conducted in February 2008. Methods During the data collection period, 493,316 cattle were subjected to standard postmortem procedures, including incision of the masseter and heart muscles. On-site veterinarians were asked to record the location of any C. bovis cysts, as well as the National Livestock Identification System ear tag numbers of infected animals. Veterinarians were asked to submit samples for laboratory confirmation by histology and polymerase chain reaction testing. Results Of the 23 samples submitted, none was positive for C. bovis by either diagnostic method. Conclusions Occasional, isolated diagnoses of beef measles are still made in most states of Australia, but since the last regional surveys were conducted 30 years ago, when the estimated prevalence was 50 to 200 per 100,000 cattle slaughtered, the parasite has become extremely rare.