Genomic selection using beef commercial carcass phenotypes.

In this study, an industry terminal breeding goal was used in a deterministic simulation, using selection index methodology, to predict genetic gain in a beef population modelled on the UK pedigree Limousin, when using genomic selection (GS) and incorporating phenotype information from novel commercial carcass traits. The effect of genotype-environment interaction was investigated by including the model variations of the genetic correlation between purebred and commercial cross-bred performance (ρX). Three genomic scenarios were considered: (1) genomic breeding values (GBV)+estimated breeding values (EBV) for existing selection traits; (2) GBV for three novel commercial carcass traits+EBV in existing traits; and (3) GBV for novel and existing traits plus EBV for existing traits. Each of the three scenarios was simulated for a range of training population (TP) sizes and with three values of ρX. Scenarios 2 and 3 predicted substantially higher percentage increases over current selection than Scenario 1. A TP of 2000 sires, each with 20 commercial progeny with carcass phenotypes, and assuming a ρX of 0.7, is predicted to increase gain by 40% over current selection in Scenario 3. The percentage increase in gain over current selection increased with decreasing ρX; however, the effect of varying ρX was reduced at high TP sizes for Scenarios 2 and 3. A further non-genomic scenario (4) was considered simulating a conventional population-wide progeny test using EBV only. With 20 commercial cross-bred progenies per sire, similar gain was predicted to Scenario 3 with TP=5000 and ρX=1.0. The range of increases in genetic gain predicted for terminal traits when using GS are of similar magnitude to those observed after the implementation of BLUP technology in the United Kingdom. It is concluded that implementation of GS in a terminal sire breeding goal, using purebred phenotypes alone, will be sub-optimal compared with the inclusion of novel commercial carcass phenotypes in genomic evaluations.

Implications of host genetic variation on the risk and prevalence of infectious diseases transmitted through the environment.

Previous studies have shown that host genetic heterogeneity in the response to infectious challenge can affect the emergence risk and the severity of diseases transmitted through direct contact between individuals. However, there is substantial uncertainty about the degree and direction of influence owing to different definitions of genetic variation, most of which are not in line with the current understanding of the genetic architecture of disease traits. Also, the relevance of previous results for diseases transmitted through environmental sources is unclear. In this article a compartmental genetic-epidemiological model was developed to quantify the impact of host genetic diversity on epidemiological characteristics of diseases transmitted through a contaminated environment. The model was parameterized for footrot in sheep. Genetic variation was defined through continuous distributions with varying shape and degree of dispersion for different disease traits. The model predicts a strong impact of genetic heterogeneity on the disease risk and its progression and severity, as well as on observable host phenotypes, when dispersion in key epidemiological parameters is high. The impact of host variation depends on the disease trait for which variation occurs and on environmental conditions affecting pathogen survival. In particular, compared to homogeneous populations with the same average susceptibility, disease risk and severity are substantially higher in populations containing a large proportion of highly susceptible individuals, and the differences are strongest when environmental contamination is low. The implications of our results for the recording and analysis of disease data and for predicting response to selection are discussed.

Gene flow in a national cross-breeding beef population.

Future progress in genetic improvement and the monitoring of genetic resources in beef cattle requires a detailed understanding of the population under selection. This study examines the gene flow in the UK beef population with an uncommon breeding structure involving interaction between the beef and dairy populations. British Cattle Movement Service records were used as the primary source of information, and these data were triangulated with UK government statistics, other industry information sources and existing literature to build up a profile of the UK beef industry. Estimates were made of the breed composition of suckler cows, breeding bulls and the prime slaughter population. Cross-bred animals made up 85% and 94%, respectively, of the commercial beef breeding cow and prime slaughter populations. Holstein/Friesian (through cross-breeding) made up the largest proportion of genes in both these populations with 33% and 28%, respectively. The next five most popular breeds were specialist beef breeds: Limousin (22% and 18%), Charolais (11% and 6%), Simmental (9% and 11%), Angus (7% and 8%) and Belgian Blue (6% and 6%). Combined, the top seven beef breeds accounted for 94% of beef genetics in the prime slaughter population, and 80% of this came from non-native breeds. The influence of dairy breeds in the commercial beef breeding population was highlighted by the fact that 44% of replacement commercial beef breeding females were sourced from beef-sired crosses in the dairy herd, and in total 74% of all maternal grand dams of prime slaughter animals were Holstein/Friesian. The use of selection index technology was also investigated by analysing breeding bull sale results, with the correlation between the terminal sire index and sale price of young breeding bulls being generally moderate but significant, ranging from 0.21 to 0.38 across the major beef breeds. The most influential source of genetics in the commercial suckler beef herd was natural service breeding bulls. These were mostly sourced from pedigree breeders, and accounted for 47.8% of the genetics in the prime beef population. Artificial insemination sires were responsible for 16.6% of prime beef genetics, with the remaining 35.6% coming from dairy breeds, 95% of which was Holstein/Friesian.

Restricting coancestry and inbreeding at a specific position on the genome by using optimized selection.

Over recent years, selection methodologies have been developed to allow the maximization of genetic gain whilst constraining the rate of inbreeding. The desired rate of inbreeding is achieved by constraining the group coancestry using the numerator relationship matrix computed from pedigree. It is shown that when the method is applied to mixed inheritance models, where a QTL is segregating together with polygenes, the rate of inbreeding achieved in the region around a QTL is greater than the desired level. The constraint on group coancestry at specific positions around the QTL is achieved by using a relationship matrix computed from pedigree and genetic markers. However, the rate of inbreeding realized at the position of constraint is lower than that expected given the assumed relationship between group coancestry and the subsequent rate of inbreeding. The use of markers in the calculation of the relationship matrix allows the selection of candidates with very low or zero relationships because they are homozygous for alternative alleles, which results in a heterozygosity amongst their offspring higher than would be expected given their allele frequencies. A generation of random selection restored the expected relationship between group coancestry and inbreeding.

Industry benefits from recent genetic progress in sheep and beef populations.

An analytical model that evaluates the benefits from 10 years of genetic improvement over a 20-year time frame was specified. Estimates of recent genetic trends in recorded traits, industry statistics and published estimates of the economic values of trait changes were used to parameterise the model for the UK sheep and beef industries. Despite rates of genetic change in the relevant performance-recorded breeding populations being substantially less than theoretical predictions, the financial benefits of genetic change were substantial. Over 20 years, the benefits from 10 years of genetic progress at recently achieved rates in recorded hill sheep, sheep crossing sire and sheep terminal sire breeding programmes was estimated to be £5.3, £1.0 and £11.5 million, respectively. If dissemination of genetic material is such that these rates of change are also realised across the entire ram breeding industry, the combined benefits would be £110.8 million. For beef cattle, genetic evaluation systems have been operating within all the major breeds for some years with quite widespread use of performance recording, and so genetic trends within the beef breeds were used as predictors of industry genetic change. Benefits from 10 years of genetic progress at recent rates of change, considering a 20-year time frame, in terminal sire beef breeds are expected to be £4.9 million. Benefits from genetic progress for growth and carcass characters in dual-purpose beef breeds were £18.2 million after subtraction of costs associated with a deterioration in calving traits. These benefits may be further offset by unfavourable associated changes in maternal traits. Additional benefits from identification and use of the best animals available from the breeding sector for commercial matings through performance recording and genetic evaluation could not be quantified. When benefits of genetic improvement were expressed on an annual present value basis and compared with lagged annual investment costs to achieve it, the internal rate of return (IRR) on the combined investment in sheep and beef cattle was 32%. Despite a much higher rate of participation in performance recording, the present value of benefits and the IRR were lower for beef cattle than for sheep. The implications of these results for future national and industry investment in genetic improvement infrastructure were discussed.

Genetic parameters for a maternal breeding goal in beef production.

New maternal breeding values have been developed for use in UK beef evaluations. To undertake multitrait BLUP evaluations, it is necessary to have a full covariance matrix. This study outlines the approach taken to construct the full covariance matrices for the four beef breeds that most widely contribute to suckler beef cows in the United Kingdom. The maternal traits investigated were age at first calving, calving interval, lifespan, mature cow weight, 200-d weight, and calving difficulty. Three terminal sire traits (weight at 400 d, ultrasonic fat depth, and muscle score) were included to estimate covariances between the new and existing traits. A sire-maternal-grandsire model was used for the estimation procedure in a series of bivariate and multivariate models. A weighted bending procedure was employed to construct positive definite covariance matrices. Parameter estimates broadly agreed with literature values, although for some traits, literature information was very scarce. Some differences between parameters for different breeds were evident.

Synthesis of direct and maternal genetic components of economically important traits from beef breed-cross evaluations.

Published information on relative performance of beef breed crosses was used to derive combined estimates of purebred breed values for predominant temperate beef breeds. The sources of information were largely from the United States, Canada, and New Zealand, although some European estimates were also included. Emphasis was on maternal traits of potential economic importance to the suckler beef production system, but some postweaning traits were also considered. The estimates were taken from comparison studies undertaken in the 1970s, 1980s and 1990s, each with representative samples of beef breeds used in temperate agriculture. Weighting factors for breed-cross estimates were derived using the number of sires and offspring that contributed to that estimate. These weights were then used in a weighted multiple regression analysis to obtain single purebred breed effects. Both direct additive and maternal additive genetic effects were estimated for preweaning traits. Important genetic differences between the breeds were shown for many of the traits. Significant regression coefficients were estimated for the effect of mature weight on calving ease, both maternal and direct additive genetic, survival to weaning direct, and birth weight direct. The breeds with greater mature weight were found to have greater maternal genetic effects for calving ease but negative direct genetic effects on calving ease. A negative effect of mature weight on the direct genetic effect of survival to weaning was observed. A cluster analysis was done using 17 breeds for which information existed on nine maternal traits. Regression was used to predict breed-cross-specific heterosis using genetic distance. Only five traits, birth weight, survival to weaning, cow fertility, and preweaning and postweaning growth rate had enough breed-cross-specific heterosis estimates to develop a prediction model. The breed biological values estimated provide a basis to predict the biological value of crossbred suckler cows and their offspring.

Bias and power in the estimation of a maternal family variance component in the presence of incomplete and incorrect pedigree information.

Several studies over the last 15 yr have estimated the magnitude of cytoplasmic inheritance of production and type traits in dairy cattle. Pedigree information can be used to assign maternal lineages, and the between-maternal lineage variance is then assumed to be an estimate of cytoplasmic inheritance. Two potential sources of bias and reduction of the power of estimation of cytoplasmic inheritance using such a method are 1) incomplete and 2) incorrect pedigree information being used in the assignment of maternal lineages. The theoretical bias introduced by these two sources of error is investigated and the results of a simulation study varying the number of families, the percentage of pedigree errors, and the level of incomplete lineage assignment are presented. Pedigree errors were found to have the biggest impact. A pedigree error rate of 8% per generation would result in a 75% reduction in the estimable magnitude of a 5% true component of variance after nine generations. The effect that these mechanisms have on the power of estimation are discussed and investigated by simulation. It was concluded that using historical pedigree, with incomplete and incorrect maternal family information, to assign maternal lineage would cause a downward bias in the magnitude of the cytoplasmic effect estimated. In the future, it will be possible to overcome pedigree problems by using molecular information to directly assign cytoplasmic lineage groups.