A progeny test was designed to test whether genetic superiority for lean growth in terminal sires is expressed in their crossbred progeny when reared in a different environment. In each of 1986, 1987 and 1988, 22 Suffolk rams were chosen at the conclusion of an indoor, intensive performance testing regime on an index score that rated their propensity for lean growth, while constraining fat growth, at 150 days of age. Half of these rams had high index scores and half had low index scores. In each year, around 400 crossbred ewes were mated and the resulting lambs were finished on grass to one of three target live weights (35·5, 41·5, and 47·0 kg). Shoulder joints were dissected on 1505 lambs whilst half carcasses were dissected on 372 lambs. Double sampling techniques were then used to combine the data from the shoulder and half carcass more precisely to predict the lean, fat and bone weight and content in the carcass.

With each increment in target live weight, the carcasses were heavier and had proportionally more fat. The progeny of high index rams consistently had 144 (s.e.d. 32) g more lean, 66 (s.e.d. 12) g more bone, and 186 (s.e.d. 32) g less fat in a 19·7 (s.e. 0·5) kg carcass than progeny of low index rams, from the double sampling procedure. This improved composition reflected a correlated response to ram selection on the index. One standard deviation increase in ram index score corresponded to 51 g more lean and 64 g less fat in the 20 kg carcass of their crossbred offspring. These results show that the use of rams with high lean index scores in a crossbreeding system will produce lambs with leaner carcasses. Visual appraisals of fat and conformation both increased as the weight and, consequently, the fatness of the carcass increased. Offspring of high index rams were consistently scored as less fat than offspring of low index rams. But, at the lighter weights (35·5 and 41·5 kg), they were also scored lower in conformation — in effect, a penalty for their higher genetic merit for lean growth.

A dispersed hybrid MOET nucleus project was implemented in the Canadian dairy industry. Embryo yield, pregnancy rate, and effects of management and selection practices are reported. Repeatability of viable embryo yield was 0.31. Average viable embryo yield was 6.85 (s.e. 5.35) embryos per collection, with average pregnancy rates of 0.58, 0.46 and 0.51 for grade 1 fresh, frozen, and split embryos, respectively. Of the donors selected, 80% produced enough embryos to form a family of at least 15 offspring. Based on observed results, expectations of family size and structure and generation intervals were calculated. Only 10% of completed families are expected to result in less than three milking daughters. Generation interval for sib-tested sires was 58 months of age under practical field conditions, which was shorter by a factor of 0.19 than a traditional progeny test but longer than original theoretical estimates by a factor of 0.32. Realized selection intensities for a total merit index were 2.22 for sires and 3.77 for dams of embryos. Accuracies of selection for sires and dams were 0.93 and 0.73 respectively. To improve the scheme, use of more fresh embryos, embryo splitting and less delay in transferring frozen embryos are recommended.

Open and closed nucleus and conventional and modern progeny testing schemes were compared for expectation and variance of genetic gain. Generation intervals were optimized, with minimum values of 2 and 6 years (progeny test results available) for males in nucleus and progeny testing schemes, respectively. Females had a minimum generation interval of 2 years, except in the conventional progeny testing schemes, which had a minimum of 4 years (one individual record available). Apart from the generation intervals and the progeny test, open nucleus and progeny testing schemes were identical, since ‘nucleus females’ are also born in progeny testing schemes, being full-sibs of the young bulls and dispersed over commercial herds. The number of nucleus sires (bull sires) selected was varied between four and 32. Selection was for milk production.

A deterministic model was used, that accounted for variance reduction due to selection and the effects of finite size and family structure on the selection differentials. Prediction of the variance of the selection response accounted for selection of full- and paternal half-sibs.

Closed nucleus schemes gave a factor 0·03, 0·13 and 0·19 larger response rates than open nucleus and modern and conventional progeny testing schemes, respectively. Reduction of genetic variance of open nucleus schemes was larger than that of closed nucleus schemes, which caused the slightly higher response rates of closed nucleus schemes. Standard deviations of selection responses of closed nucleus schemes were a factor 0·46, 0·79 and 0·86 larger, respectively.

Preference for the schemes was assessed using a quadratic utility function expressing risk and inbreeding aversion. The increase in genetic gain due to shortening of generation intervals more than compensated for its increased variance. Whether the increased genetic gain due to closing the nucleus compensated for its increased variance depended on the amount of risk aversion. Selection of four sires and eight to 16 sires had the highest utility in progeny testing and nucleus schemes, respectively.

The effect of increased female reproductive rates on selection response, on efficiency of progeny testing and on the openness of the nucleus was investigated in open nucleus breeding plans. Conventional progeny testing plans and closed nucleus plans are special classes of open nucleus plans. In the open nucleus plans, generation intervals and selection across tiers were optimized. The number of offspring per elite dam was varied from 1 to 41, progeny testing of young bulls in the female base population was varied from 0 to 100 test records and the size of the nucleus was varied from 250 to 2000 young bulls born per year. Also efficiency of selection was varied: efficient selection in T(heoretical)-schemes and less efficient selection in P(ractical)-schemes. Especially, selection of base parents was less efficient i n P-schemes.

The deterministic prediction model took account of variance reduction due to selection and reduction of selection differentials due to correlations between estimated breeding values of relatives (order statistics). For closed nucleus plans, the results of the model were verified with Monte Carlo simulation results.

By increasing female reproductive rates, genetic gain increased by a factor 0·08 and 0·16 for the T- and P-schemes respectively. The nuclei in P-schemes were less open, due to the less efficient selection in the female base population. Schemes that were less open benefited more from increased female reproductive rates because selection differentials in small nuclei increased more than those in large base populations. The optimal open nucleus plan became less open with increasing female reproduction. Generally, progeny testing of bulls reduced genetic gain (by up to a factor 0·1) but it also reduced inbreeding rates. Progeny testing was more efficient in schemes that were less open: in P-schemes with 41 offspring per dam, progeny testing increased genetic gain. With many offspring per dam there were fewer full-sib families, causing lower selection differentials due to order statistics effects. This effect could be prevented by increasing the size of the nucleus.

Central test data of two pig breeding companies were analysed to estimate sire × testing regime (S × T) interaction for ultrasonic backfat thickness (BT), life-time growth rate (GL) and growth rate during test (GT). Testing regime consisted of a combination of sex, test period and housing system (individual v. group housing). Data were analysed within five lines, with 5417, 8331, 3427, 2413 and 1263 records of progeny of 97, 162, 64, 69 and 33 sires, respectively. The data were collected from May 1983 until May 1987 (lines 1, 2 and 3) and from June 1985 until May 1987 (lines 4 and 5). Testing regime had a significant effect on BT (in three lines) and on GL and GT (in five lines). S × T interaction was significant only for BT in three lines and for GT in one line. Genetic correlations between identical traits, measured under the two testing regimes, varied from 0·64 to 1·00 for BT, from 0·65 to 1·00 for GL and from 0·62 to 1·00 for GT. Conclusively, within central test S × T interactions were relatively unimportant for BT, GT and GL.

A theoretical analysis of the potential benefits of marker-assisted selection (MAS) of candidate bulls prior to entry into a young sire progeny testing programme was carried out. It is assumed that quantitative trait loci (QTL) affecting milk production have been mapped with respect to known genetic markers, and MAS is based on evaluation of elite sires in order to identify marker alleles in coupling to favourable or unfavourable QTL alleles. Candidate bulls, descendants of the elite sire will then be selected, prior to conventional progeny testing, on the basis of the marker alleles derived from the elite-sire ancestor.

The analysis considers recombination between marker and QTL, the difficulty of tracing specific marker alleles from sire to progeny, and the expectation that MAS, in practice, will be implemented in the grandsons, rather than in the sons of elite sires. It is shown that MAS of candidate bulls, based on the use of a single diallelic marker in linkage to a QTL will have only a negligible effect on the rate of genetic progress. Increases of 15 to 20% in the rate of genetic gain, however, can be obtained by the use of single polyallelic markers, and increases of 20 to 30% can be obtained by utilizing haplotypes of diallelic or polyallelic markers.

The published theoretical estimates of equilibrium genetic change possible by progeny testing in dairy cattle are too high. Much of the overestimation is because no account has been taken of the temporary reduction in genetic variation due to selection of parents and ancestors. A particular efficient progeny testing scheme was modelled theoretically and simulated on computer using a continuous infinitesimal additive model. To make the simulation feasible an elite breeding herd of females was used, and progeny testing was done outside the herd. The proportional reduction in genetic variance due to previous selection was 0·25, 0·27 and 0·29 for original heritabilities of 0·05, 0·25 and 0·50, with the theoretical and simulated results being very similar. The theoretical and simulated proportional losses in equilibrium selection responses were 0·22 and 0·26, 0·21 and 0·22 and 0·21 and 0·25, respectively, for the three levels of heritability. Thus, most of the loss in response in the simulation results came from the reduction in genetic variance due to selection.