Invited review: A quarter of a century-International genetic evaluation of dairy sires using MACE methodology.

For the past few decades, the international exchange of genetic materials has accelerated. This acceleration has been more substantial for dairy cattle compared with other species. The industry faced the need to put international genetic evaluation (IGE) systems in place. The Interbull Centre has been conducting IGE for various dairy cattle breeds and traits. This study reviews the past and the current status of IGE for dairy cattle, emphasizing the most prominent and well-established method of IGE, namely multiple across-country evaluation (MACE), and the challenges that should be addressed in the future of IGE. The first IGE methods were simple conversion equations. Only a limited number of common bulls between pairs of countries were considered. These bulls were a biased sample of highly selected animals, with their daughters under preferential treatment in the importing countries. Genetic relationships among animals were not considered either. The MACE method was the first IGE method based on mixed-model theory that could handle genotype by environment interaction (G × E) between countries. The G × E between countries is handled by treating the same trait in different countries as different traits, with genetic correlations less than unity between the traits. The G × E between countries is not solely due to different genetic expressions in different environments (countries), but is also attributable to different units or ways of measuring the trait, data editing, and statistical approaches and models used in different countries. The MACE method also considers different genetic means, genetic groups for unknown parents, heterogeneous genetic and residual variances among countries, and heterogeneous residual variances (precision weights for observations) within countries. Other IGE methods that came after MACE are rooted in MACE. The genomic revolution of the industry created new needs and opportunities. However, an unwanted aspect of it was genomic preselection bias. Genomic preselection causes directional information loss from pre-culled animals (bias) in statistical models for genetic and genomic evaluations, and preselected progeny of a mating are no longer a random sample of possible progeny from that mating. National genetic evaluations without genotypes are input to MACE, and biases in national evaluations are propagated internationally through MACE. Genomic preselection for the Holstein breed is a source of concern for introducing bias to MACE, especially when genomic preselection is practiced intensively in the population. However, MACE continues to be useful for other breeds, among other species, or for non-IGE purposes. Future methods will need to make optimum use of genomic information and be free of genomic preselection bias.

Across-country genetic evaluation of meat sheep from Ireland and the United Kingdom.

Genetic evaluations in sheep have proven to be an effective way of increasing farm profitability. Much research has previously been conducted on producing within-country genetic evaluations; however, to date, no across-country sheep genetic evaluations have been produced between Ireland and the UK. The objective of the present study was to examine the feasibility of an across-country genetic evaluation of live body weight and carcass composition traits for Texel sheep raised in Ireland and the UK. The benefit of genetic selection based on across-country genetic evaluations, in comparison with within-country genetic evaluations, was also quantified. Animal traits included early-life and postweaning live body weights, and muscle and fat depth ultrasound measurements. Irish and UK data were combined, common animals with progeny with records in both countries were identified and a series of bivariate analyses were performed separately for each trait to produce across-country genetic evaluations. Fixed effects included contemporary group, age at first lambing of the dam, parity of the dam (Ireland), dam age at lamb's birth (UK), a gender by age of the lamb interaction, a birth type by rearing type of the lamb interaction and country of birth of the lamb. Random effects included the animal additive genetic, dam maternal, litter common environment and residual effect. The model for postweaning weight, muscle depth and fat depth included only the animal additive genetic and litter common environmental random effects. Genetic correlations between the two countries ranged from 0.82 to 0.88 for the various traits. Across-country breeding values were estimated for all animals and response to selection was predicted using the top 10 and top 20 sires in both within- and across-country analyses for the two countries. Overall, results showed that rates of genetic gain could potentially increase from between 2.59% and 19.63% from selection based on across-country genetic evaluations compared to within-country evaluations alone. Across-country evaluations are feasible and would be of significant benefit to both the Irish and UK sheep industries. In order to realize these potential gains though, there would need to be a switch in emphasis by sheep breeders towards using objective traits as their primary selection criteria.

Effect of synchronized breeding on genetic evaluations of fertility traits in dairy cattle.

Estrus detection has become more difficult over the years due to decreases in the estrus expression of high-producing dairy cows, and increased herd sizes and animal density. Through the use of hormonal synchronization protocols, also known as timed artificial insemination (TAI) protocols, it is possible to alleviate some of the challenges associated with estrus detection. However, TAI masks cows' fertility performance, resulting in an unfair comparison of treated animals and innately fertile animals. Consequently, genetically inferior and superior cows show similar phenotypes, making it difficult to distinguish between them. As genetic programs rely on the collection of accurate phenotypic data, phenotypes collected on treated animals likely add bias to genetic evaluations. In this study, to assess the effect of TAI, the rank correlation of bulls for a given trait using only TAI records were compared with the same trait using only heat detection records. A total of 270,434 records from 192,539 animals split across heifers, first and second parity cows were analyzed for the traits: calving to first service, first service to conception, and days open. Results showed large reranking across all traits and parities between bulls compared based on either having only TAI records or only heat detection records, suggesting that a bias does indeed exist. Large reranking was also observed for both the heat detection and TAI groups among the top 100 bulls in the control group, which included all records. Furthermore, breeding method was added to the model to assess its effect on bull ranking. However, there were only minor changes in the rank correlations between scenario groups. Therefore, more complex methods to account for the apparent bias created by TAI should be investigated; for this, the method by which these data are collected needs to be improved through creating a standardized way of recording breeding codes. Though the results of this study suggest the presence of bias within current fertility evaluations, additional research is required to confirm the findings of this study, including looking at high-reliability bulls specifically, to determine if the levels of reranking remain. Future studies should also aim to understand the potential genetic differences between the fertility traits split via management technology, possibly in a multiple-trait analysis.

Effect of calving age on genetic evaluation of milk yield in Holstein cattle.

The aim of this study was to evaluate the effect of including calving age (CA) on genetic evaluation models for Holstein cattle. The evaluated models included the permanent environment, the sire-herd interactions, and the animals and residual effects as random. The fixed effects included the average production of milk, fat, and protein and the herd-year-season effect. The analyzed data included 603,521 records of milk production (in kg) corresponding to 438,098 animals from 527 herds. Additionally, there were 179,122 records of fat and protein components, corresponding to 148,930 animals from 137 herds. The records were classified by first lactation only (FL) and all available lactations (AL) for validation test (VT). The FL records corresponded to 275,487 milk production records with a mean of 10,874.1 ± 2773.9 kg at a mean CA of 25.6 ± 4.2 months. For FL, the milk components consisted of 78,955 records with a mean fat production of 392.86 ± 89.9 kg, a mean protein production of 362.8 ± 74.9 kg and a mean CA of 25.2 ± 4.1 months. For AL, the number of records was 603,521 for milk production with a mean of 10,802.8 ± 2905.9 kg and a mean CA of 35.6 ± 11.5 months. For the milk components, there were 179,122 records with a mean of 36.1 ± 9.5 months for CA and 388.3 ± 98.4 kg and 356.7 ± 82.6 kg for fat and protein, respectively. Three models were compared: the base model (M0) described above, and two alternative models that included CA in a linear and quadratic form (M1 and M2, respectively). Estimations of the variance components (VC) and breeding value (BV) were obtained using a repeatability animal model, with the same phenotypic and pedigree information used for all models. To select the best fit model for the data, a likelihood ratio test (LRtest) was used. A validation test (VT) was also applied to each model to evaluate the consistency of the genetic trends for females with information on AL and FL. The inclusion of CA in its linear form (M1) was the model that achieved the best results in the LRtest and an acceptable value for the VT. These results show that CA improves the model fit for BV prediction and reliability.

Genetic analysis of live weight of local kids to promote genetic evaluations in the arid areas of Tunisia.

Goat meat production, a widely extended activity in the more arid areas of Tunisia, relies on local breeds. These breeds are well adapted to produce under harsh conditions but have a very small size and low productivity. The aim of this study was to establish the basis for future genetic evaluations to improve growth potential of this local stock. A total of 13,095 body weights and pedigree of 945 kids in the caprine herd of the Arid Areas Institute of Médenine were used. Random regression (RR) and multiple trait (MT) models were analyzed and compared. All models included effects of age and weight of dam, age, sex and type of birth of the kid, and year × month of recording, plus random direct and maternal additive genetic and permanent environmental effects. RR and MT models behave similarly, with RR showing slightly better goodness of fit. Heritability estimates for direct (ranging from 0.15 to 0.4) and maternal (0.05 to 0.3) effects showed that efficient selection for weight is feasible in this population. Estimated correlations between ages were high (> 0.8) for direct effects across all ages and low (down to 0.2) for weights taken at distant ages for maternal effects. Estimated genetic correlations between direct and maternal components revealed an antagonistic relationship, especially at early ages. Recording of at least one weight in the first month of age of the kids to evaluate the maternal capacity and a later weight to evaluate direct effects on weight is recommended for genetic evaluations under field conditions.

An overview of international genetic evaluations of show jumping in sport horses.

The breeding of sport horses to compete in the Olympic disciplines of show jumping, eventing, and dressage is fast becoming a global industry with the increased use of reproductive technologies, including artificial insemination and embryo transfer. Reproductive technologies have facilitated the dissemination of genetics from elite horses across multiple countries and breeds as breeders are no longer limited by location. Due to this increased level of crossbreeding, there is an increased need for estimated breeding values (EBVs) for sport horse performance that can be compared across breeds and countries. However, the implementation of across-breed or across-country genetic evaluations has been limited by the differences in each studbook's individual breeding programs and genetic evaluations. Consequently, the aim of this review was to compare the genetic evaluations for show jumping of sport horse studbooks worldwide. The top sport horse studbooks in the world according to the World Breeding Federation for Sport Horses Studbook Rankings 2019 were contacted by email to request information on their current breeding programs and genetic evaluations. Twenty-six of the 51 studbooks contacted replied to this request but only 18 of these studbooks conducted their own genetic evaluations or were part of a larger genetic evaluation in their country of origin. The other eight studbooks were not involved in genetic evaluations at present but expressed an interest in the implementation of such in the future. Overall, many differences were identified among the genetic evaluations of each studbook or each country. The definition of show jumping performance differed within each evaluation and the methods and models utilized also differed. Despite some stallions and mares being registered in multiple studbooks or having progeny in multiple studbooks, these differences make comparison of EBVs across studbooks difficult. Further transparency and collaboration of sport horse studbooks with organizations such as Interstallion, will be essential to facilitate any future implementation of international genetic evaluations for show jumping performance.

The impact of direct-maternal genetic correlations on international beef cattle evaluations for Limousin weaning weight.

In beef cattle maternally influenced traits, estimates of direct-maternal genetic correlations (rdm) are usually reported to be negative. In international evaluations, rdm can differ both within countries (rdm_WC) and between countries (rdm_BC). The rdm_BC are difficult to estimate and are assumed to be zero in the current model for international beef cattle evaluations (Interbeef). Our objective was to investigate re-ranking of international estimated breeding values (IEBVs) in international beef cattle evaluations between models that either used estimated values for rdm or assumed them to be 0. Age-adjusted weaning weights and pedigree data were available for Limousin beef cattle from ten European countries. International EBVs were obtained using a multi-trait animal model with countries modeled as different traits. We compared IEBVs from a model that uses estimated rdm_BC (ranging between -0.14 and +0.14) and rdm_WC (between -0.33 and +0.40) with IEBVs obtained either from the current model that assumes rdm_BC to be 0, or from an alternative model that assumes both rdm_BC and rdm_WC to be 0. Direct and maternal IEBVs were compared across those three scenarios for different groups of animals. The ratio of population accuracies from the linear regression method was used to further investigate the impact of rdm on international evaluations, for both the whole set of animals in the evaluation and the domestic ones. Ignoring rdm_BC, i.e., replacing estimated values with 0, resulted in no (rank correlations > 0.99) or limited (between 0.98 and 0.99) re-ranking for direct and maternal IEBVs, respectively. Both rdm_BC and rdm_WC had less impact on direct IEBVs than on maternal IEBVs. Re-ranking of maternal IEBVs decreased with increasing reliability. Ignoring rdm_BC resulted in no re-ranking for sires with IEBVs that might be exchanged across countries and limited re-ranking for the top 100 sires. Using estimated rdm_BC values instead of considering them to be 0 resulted in null to limited increases in population accuracy. Ignoring both rdm_BC and rdm_WC resulted in considerable re-ranking of animals' IEBVs in all groups of animals evaluated. This study showed the limited impact of the current practice of ignoring rdm_BC in international evaluations for Limousin weaning weight, most likely because the estimated rdm_BC was close to 0. We expect that these conclusions can be extended to other traits that have reported rdm values in the range of rdm_WC values for weaning weight in Limousin.

Genetic parameters and trends for growth traits in Blanco Orejinegro cattle.

Since 1940, efforts have been made to preserve the Blanco Orejinegro (BON) cattle breed by maintaining gene banks. Nine years ago, a BON genetic improvement program was implemented to increase genetic gain based on control of productivity and the use of performance tests, polygenic and genomic evaluations, and selection indices. The objective of this study was to estimate genetic parameters and trends for growth traits by using polygenic (PM) and genomic-polygenic (GPM) models. Productive information from the years 1980 to 2019 was used. The following data were used: 7,304 birth weight (BW) records, 1,281 records of body weight adjusted to 120 days (W120), 4,791 records of weight adjusted to 240 days (W240), 3,339 records of weight adjusted to 480 days (W480), and 1,364 records of weight adjusted to 720 days (W720). The relationship matrix included 13,612 pure animals belonging to the Colombian Corporation for Agricultural Research - AGROSAVIA and the Producer Network program. A total of 1,224 individuals were genotyped with chips of different densities and all were imputed up to 50,932 SNPs. Polygenic and genomic-polygenic models were used to estimate genetic parameters and correlations between the genetic values estimated by each model. A generalized additive model with smoothing was used to estimate trends of genetic values from 1980 to 2019. Heritabilities between 0.29 and 0.40, genetic correlations between 0.13 and 0.94, and phenotypic correlations between 0.23 and 0.72 were observed. Close-to-zero genetic growth was observed for BW and W120. Genetic trends for the other traits were positive, with higher growth in the last 7 years. The heritabilities observed in this population indicate that the traits measured would respond to selection. Greater genetic progress can be achieved in W240, W480, and W720 by continuing with genetic evaluations and developing performance tests and strategies to make genetic material readily available to producers.