Cornelius L. Nel

Context: Selection for a composite trait, such as number of lambs weaned per ewe joined (NLWEJ), aims to simultaneously improve the underlying components, such as fertility (ELEJ), litter size (NLBEL) or ewe rearing ability (ERAEL). However, a concern with selection on NLWEJ is the higher risk of mortality as litter sizes increase. Aim: This study estimated genetic parameters, (co)variance components and the long-term genetic changes in the component traits in the Elsenburg Merino flock that has been divergently selected in favour (H-Line) or against (L-Line) performance in NLWEJ. Methods: The dataset included up to 6779 reproduction phenotypes recorded on 1836 ewes linked to a pedigree containing 10,903 identities. The data were analysed with a repeated measures linear mixed model using ASREML V4.2 software. Genetic trends were derived by regressing breeding values on year within each line. Results: Heritability estimates were low, with the highest value observed for NLBEL (0.12 ± 0.02). All traits were affected by an animal permanent environmental effect from 0.05 for ERAEL to 0.12 for ELEJ. All traits diverged between the H- and L-Lines, with an upward rate of annual gain of nearly 1% for the composite trait NLWEJ, and positive but smaller gains of 0.3% for ELEJ, 0.45% for NLBEL and 0.15% for ERAEL. It was reassuring to see that the trend for ERAEL was stable despite the increase in NLBEL for H-Line ewes and the unfavourable genetic correlation (rg = −0.57 ± 0.14) between these two traits. Conclusions: In a well designed breeding program, the use of NLWEJ as selection criteria can be effective to breed ewes with a high output at weaning. Use of a composite trait might not deliver optimal genetic gains for the components ELEJ and ERAEL, however, and could favour NLBEL, which might not be desirable in all environments. Implications: For commercial flocks, favourable results will depend on complete recording and correct processing of information from all ewes mated and lambs born. Otherwise, NLWEJ only reflects NLBEL, where the predicted response in ERAEL is unfavourable.

1. The heritability (h²) of liveweight (LW) in ostriches can be highly variable, depending on age at recording. The objective of this study was to consider random regression (RR) as an alternative to the multi-trait (MT) structure for the analysis of repeated measures of LW.2. The data included 74 683 LW phenotypes recorded from 10 052 birds aged between 20 and 410 days (d) of age. Statistical analysis included single trait (ST), MT and RR analysis in a linear mixed model framework using the ASREML V4.2 software.3. For ST and MT, six traits were defined to represent LW at 28, 77, 150, 230, 300 and 365 d of age. Random variance components included direct genetic and maternal permanent environment (PE) effects. A MT analysis including all six traits converged.4. For RR, the data was transformed (LW + 10)^-0.5 due to difficulty in dealing with large scale effects. The final RR model fitted direct genetic and animal PE components as third degree Legendre polynomials and heterogeneous residuals.5. The h² estimates was in agreement across analysis, ranging from moderate (0.16-0.20) for W28 to high (0.41-0.51) for W230 to W365. Importantly, the genetic relationship between LW recorded as a chick and juvenile was only moderate (~0.35 to 0.55). The correlations between RR and MT EBVs for the six traits were 0.85, 0.54, 0.65, 0.75, 0.83 and 0.91, showing a considerable level of re-ranking.6. This study reaffirmed age dependent genetic variation when determining LW in ostriches. The RR structure was useful for overcoming the dimension problem of MT analysis, but was susceptible to scale effects present in the data, despite transformation. It remains unknown whether the need for cubic terms reflected scale or animal effects.

The adaptability and success of sheep are confirmed by the fact that they are the world’s most diverse mammalian livestock species, contributing some 25% to the global number of farm animal breeds ( Cottle, 2010). The latter author showed that the ovine species is indeed globally successful and present in farming landscapes throughout the world, ranging from arid to high rainfall areas and from sea level to the highest mountains. Sheep are often farmed in resource-poor and otherwise marginal regions, constrained by climate and soil type ( Cloete and Olivier, 2010). There is also consensus that the global climate is highly likely to become more unstable in future ( Rust and Rust, 2013). Droughts are expected to become more intense and persist longer, also leading to periods of prolonged heat stress ( Van Wettere et al., 2021). Challenging environmental conditions are often characterized by further constraints, such as a variety of external and internal parasites ( Karlsson and Greeff, 2012), as well as extremes in terms of climate, soil, and topography ( Cloete and Olivier, 2010). Challenging climatic conditions at lambing also commonly compromise lamb survival ( Pollard, 2006). Fighting and controlling endemic diseases and other stressors represent a considerable cost to livestock production, creating the need for more robust and easy-care animals being able to thrive in particularly challenging environments ( Friggens et al., 2017).

Extensive sheep farming is often associated with small flocks grazing large areas, delivering limited economic returns compared with the revenue of examples such as dairy or intensive beef cattle farming. However, sheep are a popular choice of livestock in challenging environments where few other production systems are viable ( Rust and Rust, 2013). Low input, extensive systems make use of the ability of ruminants to metabolize low-quality, high fiber materials that characterize pastoral grazing. By producing wool, meat, and sometimes dairy, extensive sheep production can deliver high-quality output products from a low-quality input that would otherwise have had little value for sustaining mankind. Furthermore, extensive pastoral systems can arguably be excused from some of the criticisms aimed at factory farming ( Frank, 1979).

Context: Coping with high levels of cold stress should be beneficial to survival of lambs, given the high mortality rate associated with severe winter storms. The Elsenburg Merino selection experiment involved divergent selection for reproduction. Phenotypic results comparing the positively selected H-Lines and negatively selected L-Lines suggested that cold-stress adaption could have contributed to the favourable genetic trends for survival of H-Line lambs. However, observing the genetic merit of better adapted animals depends on the presence of cold stress at the time of recording. A genotype by environment component (G × E) could, thus, be important when assessing survival/mortality phenotypes. Aim: This study proposed the genetic analysis of this possible G × E component and compared the H- and L-Lines in this regard. Methods: The sire model allowed the use of progeny phenotypes for neonatal mortality recorded during different levels of cold stress, and the possible G × E could be investigated through the reaction-norm approach. Genetic parameters were evaluated as random regression components by implementing a Gibbs sampling approach. A data set of 5723 individual lamb records was analysed as the progeny of 213 sires. Results: A modelled G × E component played an important role in mortality outcomes, with the mean estimate (and 95% confidence interval) for the slope (ssb2=0.113[0.0019–0.28]AN22464_IE1.gif) only marginally smaller than the corresponding estimate for the intercept (ssa2=0.124[0.003–0.26]AN22464_IE2.gif). The reaction-norm model showed a higher heritability (h2 ± posterior standard deviation) for mortality at 3 days of age during high cold-stress (0.22 ± 0.16 at ~1100 KJm-2h-1) than during mild (0.13 ± 0.10 at ~960 KJm-2h-1) conditions, suggesting a greater ability to discriminate between sires at increasing stress levels. Conclusions: Failure to account for this G × E component putatively contributes to the low h2 commonly reported for survival traits. The higher h2 at increased levels of cold stress could have played an important part in the higher survival of the H-Line progeny, who were better at coping with cold, wet and windy conditions. Implications: Larger studies representing a wider environmental trajectory are recommended. This should be very feasible since cold stress can be derived from commonly available weather-station data.

The proceedings of the 12th World Congress on Genetics Applied to Livestock Production provide you with 816 papers representing the leading research in livestock genetics around the globe. This boo...

Background: South Africa and Australia shares multiple important sheep breeds. For some of these breeds, genomic breeding values are provided to breeders in Australia, but not yet in South Africa. Combining genomic resources could facilitate development for across country selection, but the influence of population structures could be important to the compatability of genomic data from varying origins. The genetic structure within and across breeds, countries and strains was evaluated in this study by population genomic parameters derived from SNP-marker data. Populations were first analysed by breed and country of origin and then by subpopulations of South African and Australian Merinos. Results: Mean estimated relatedness according to the genomic relationship matrix varied by breed (-0.11 to 0.16) and bloodline (-0.08 to 0.06) groups and depended on co-ancestry as well as recent genetic links. Measures of divergence across bloodlines (F_ST: 0.04–0.12) were sometimes more distant than across some breeds (F_ST: 0.05–0.24), but the divergence of common breeds from their across-country equivalents was weak (F_ST: 0.01–0.04). According to mean relatedness, F_ST, PCA and Admixture, the Australian Ultrafine line was better connected to the SA Cradock Fine Wool flock than with other AUS bloodlines. Levels of linkage disequilibrium (LD) between adjacent markers was generally low, but also varied across breeds (r²: 0.14–0.22) as well as bloodlines (r²: 0.15–0.19). Patterns of LD decay was also unique to breeds, but bloodlines differed only at the absolute level. Estimates of effective population size (N_e) showed genetic diversity to be high for the majority of breeds (N_e: 128–418) but also for bloodlines (N_e: 137–369). Conclusions: This study reinforced the genetic complexity and diversity of important sheep breeds, especially the Merino breed. The results also showed that implications of isolation can be highly variable and extended beyond breed structures. However, knowledge of useful links across these population substructures allows for a fine-tuned approach in the combination of genomic resources. Isolation across country rarely proved restricting compared to other structures considered. Consequently, research into the accuracy of across-country genomic prediction is recommended.

Context: Mortality of new-born lambs is well known to have important implications for both animal production and welfare. Improving survival rates by genetic selection is very desirable, but the low heritability of survival traits challenges the prospect of useful genetic gain. Aim: This study aimed to derive genetic and environmental parameters for lamb survival in the Elsenburg Merino resource flock. It also investigated correlations to possible indicator traits birthweight and birth coat score and reported genetic progress in breeding values for lamb survival following 33 years of divergent selection. Methods: The flock was divergently selected for number of lambs weaned and was separated by the High (positive) and Low (negative) selection groups. The pedigree file identified 8138 lambs as the progeny of 273 sires and 2062 dams. The study considered total survival from birth to weaning (Tsv) that was also partitioned into perinatal survival to 3 days of age, and the remaining period. Variance components were derived by linear mixed models by using the ASREML® program. Genetic trends were derived by predicting mean breeding values for selection groups within each year and evaluated by fitting linear and broken-stick regression models. Results: Predicted Tsv of H-line lambs (0.81 ± 0.01) was higher (P < 0.01) than that of L-line lambs (0.68 ± 0.01). Heritability was significant but low for survival traits (0.03–0.07), moderate for birthweight (0.16) and high for birth coat score (0.54). Genetic trends of the H-line trended divergently (P < 0.01) to the L-line for survival traits, but a changepoint (P < 0.01) in trend suggested that the H-line reached a selection plateau following 19–22 years of selection. Preceding this period, the rate of genetic change equalled ~1% of the mean for Tsv. Conclusions: Despite the low heritability of survival, the genetic trends reported in this study contradicted the premise that genetic selection is not a worthwhile method to reduce incidences of lamb mortality. Implications: It is recommended that lamb survival phenotypes should be recorded and incorporated into indices individually where possible, but composite traits are a viable alternative.