Genomic selection: the option for new robustness traits?

The Resilient Dairy Genome Project-A general overview of methods and objectives related to feed efficiency and methane emissions

The Resilient Dairy Genome Project (RDGP) is an international large-scale applied research project that aims to generate genomic tools to breed more resilient dairy cows. In this context, improving feed efficiency and reducing greenhouse gases from dairy is a high priority. The inclusion of traits related to feed efficiency (e.g., dry matter intake [DMI]) or greenhouse gases (e.g., methane emissions [CH4]) relies on available genotypes as well as high quality phenotypes. Currently, 7 countries (i.e., Australia, Canada, Denmark, Germany, Spain, Switzerland, and United States) contribute with genotypes and phenotypes including DMI and CH4. However, combining data are challenging due to differences in recording protocols, measurement technology, genotyping, and animal management across sources. In this study, we provide an overview of how the RDGP partners address these issues to advance international collaboration to generate genomic tools for resilient dairy. Specifically, we describe the current state of the RDGP database, data collection protocols in each country, and the strategies used for managing the shared data. As of February 2022, the database contains 1,289,593 DMI records from 12,687 cows and 17,403 CH4 records from 3,093 cows and continues to grow as countries upload new data over the coming years. No strong genomic differentiation between the populations was identified in this study, which may be beneficial for eventual across-country genomic predictions. Moreover, our results reinforce the need to account for the heterogeneity in the DMI and CH4 phenotypes in genomic analysis.

Assessment of long-term trends in genetic mean and variance after the introduction of genomic selection in layers: a simulation study

Nucleus-based breeding programs are characterized by intense selection that results in high genetic gain, which inevitably means reduction of genetic variation in the breeding population. Therefore, genetic variation in such breeding systems is typically managed systematically, for example, by avoiding mating the closest relatives to limit progeny inbreeding. However, intense selection requires maximum effort to make such breeding programs sustainable in the long-term. The objective of this study was to use simulation to evaluate the long-term impact of genomic selection on genetic mean and variance in an intense layer chicken breeding program. We developed a large-scale stochastic simulation of an intense layer chicken breeding program to compare conventional truncation selection to genomic truncation selection optimized with either minimization of progeny inbreeding or full-scale optimal contribution selection. We compared the programs in terms of genetic mean, genic variance, conversion efficiency, rate of inbreeding, effective population size, and accuracy of selection. Our results confirmed that genomic truncation selection has immediate benefits compared to conventional truncation selection in all specified metrics. A simple minimization of progeny inbreeding after genomic truncation selection did not provide any significant improvements. Optimal contribution selection was successful in having better conversion efficiency and effective population size compared to genomic truncation selection, but it must be fine-tuned for balance between loss of genetic variance and genetic gain. In our simulation, we measured this balance using trigonometric penalty degrees between truncation selection and a balanced solution and concluded that the best results were between 45° and 65°. This balance is specific to the breeding program and depends on how much immediate genetic gain a breeding program may risk vs. save for the future. Furthermore, our results show that the persistence of accuracy is better with optimal contribution selection compared to truncation selection. In general, our results show that optimal contribution selection can ensure long-term success in intensive breeding programs using genomic selection.

Preferences of European dairy stakeholders in breeding for resilient and efficient cattle: A best-worst scaling approach

Including resilience in the breeding objective of dairy cattle is gaining increasing attention, primarily as anticipated challenges to production systems, such as climate change, may make some perturbations more difficult to moderate at the farm level. Consequently, the underlying biological mechanisms by which resilience is achieved are likely to become an important part of the system itself, increasing value on the animal's ability to be unperturbed by variable production circumstances, or to quickly return to pre-perturbed levels of productivity and health. However, because the value of improving genetic traits to a system is usually based on known profit functions or bioeconomic models linked to current production conditions, it can be difficult to define longer-term value, especially under uncertain future production circumstances and where nonmonetary values may be progressively more important. We present the novel application of a discrete choice experiment, used to investigate potential antagonisms in the values of genetic improvements for 8 traits to dairy cattle system stakeholders in Europe when the production goal was either efficiency or resilience. A latent class model was used to identify heterogeneous preferences within each production goal, and postestimation was used to identify associations between these preferences and sociodemographic characteristics of respondents. Results suggested 3 distinct latent preference classes for each production goal. For the efficiency goal, yield and feed efficiency traits were generally highly valued, whereas for the resilience goal, health and robustness traits were generally highly valued. In both cases, these traits generally carried a low value in the other production scenario. Overall, in both scenarios, longevity was highly valued; however, the value of this trait in terms of resilience will depend on phenotyping across diverse environments to sufficiently capture performance under various anticipated system challenges. Additionally, results showed significant associations between membership of latent preference classes with education level and profession. In conclusion, as resilience becomes increasingly important, it is likely that a continued reliance on the short-term economic value of traits alone will lead decision makers to misrepresent the importance of some traits, including those with substantial contextual values in terms of resilience.

Inter-animal genetic variability exist in organoleptic properties of prime beef meat

The objective of the present study was to estimate genetic parameters for four organoleptic traits in beef meat, namely tenderness, juiciness, flavour and chewiness using data from 5380 young crossbred progeny of 748 different sires. As well as using the mean animal sensory score across all panellists for a given trait, other aggregate functions such as the median and modal values were also investigated. The heritability (SE) of mean tenderness, juiciness, flavour and chewiness was 0.16 (0.04), 0.14 (0.04), 0.11 (0.03) and 0.21 (0.06), respectively; heritability estimates for the other aggregate values of these traits were generally lower. All genetic correlations between tenderness, juiciness and flavour were positive (0.52 to 0.68) while the genetic correlations between these three traits with chewiness were all negative varying from -0.95 to -0.48. Weak genetic correlations (≤|0.16|) were evident between the sensory traits and all of carcass weight, conformation and subcutaneous fat cover.

Grazing Allometry: Anatomy, Movement, and Foraging Behavior of Three Cattle Breeds of Different Productivity

Modern breeding has formed a multitude of cattle breeds ranging from undemanding, low-productive breeds to high-productive, specialized dairy, or beef cattle. The choice of breed has important implications for farm management, but its impact on pasture vegetation is underestimated. We hypothesized (i) that anatomy, movement, and foraging behavior of cattle are allometrically related on the individual level, (ii) that differences among cattle are not explained by individual variation alone but also by breed, and (iii) that anatomy, movement, and foraging behavior of a cattle breed is related to its productivity. In order to test these hypotheses, we conducted a controlled grazing experiment in which three cattle breeds simultaneously grazed three types of heterogenous, alpine pastures: low-productive Highland cattle (average weight: 358 kg); local, dual-purpose Original Braunvieh (582 kg); and high-productive Angus × Holstein crossbreed (679 kg). We measured body weight and claw base of nine cows per breed after 10 weeks of grazing alpine pastures. Over a period of 9 days, we recorded the step frequency and lying time by pedometer and space use by GPS. Moreover, we visually observed foraging behavior on three occasions per cow. Forage selectivity and quality were calculated for every cow's diet. Allometric relationships were analyzed on the individual level by fitting standardized major axes. For most parameters measured, we detected strong allometric relationships and clear differences among breeds that depended on the level of productivity. The claws of Highland cattle were relatively large compared to their body weight and thus they exerted less static pressure than other breeds. Moreover, the more productive a breed was, the higher its selectivity and step frequency were. For example, Highland cattle foraged shrubs and thistles more frequently than high-productive Angus × Holstein. The latter walked longer distances to select higher-quality forage, while Highland cattle used the space more evenly, visited steeper slopes, and moved further away from water points. Irrespective of breed, vegetation composition influenced cattle behavior: On pastures of low forage quality, animals walked more, foraged more selectively, and used space less evenly. In conclusion, the observed breed-specific differences can be used to improve pasture management and grassland conservation.

Allele substitution and dominance effects of CD166/ALCAM gene polymorphisms for endoparasite resistance and test-day traits in a small cattle population using logistic regression analyses

The study investigated the effects of four single-nucleotide polymorphisms (SNPs) in the activated leukocyte cell adhesion molecule (ALCAM) gene on liver fluke (Fasciola hepatica) infections (FH-INF), gastrointestinal nematode infections (GIN-INF) and disease indicator traits [e.g. somatic cell score (SCS), fat-to-protein ratio (FPR)] in German dual-purpose cattle (DSN). A genome-wide association study inferred the chip SNP ALCAMc.73+32791A>G as a candidate for F. hepatica resistance in DSN. Because of the crucial function of ALCAM in immune responses, SNPs in the gene might influence further resistance and performance traits. Causal mutations were identified in exon 9 (ALCAMc.1017T>C) and intron 9 (ALCAMc.1104+10T>A, ALCAMc.1104+85T>C) in a selective subset of 94 DSN cows. We applied logistic regression analyses for the association between SNP genotypes with residuals for endoparasite traits (rINF-FH, rGIN-INF) and estimated breeding values (EBVs) for test-day traits. The probability of the heterozygous genotype was estimated in dependency of the target trait. Allele substitution effects for rFH-INF were significant for all four loci. The T allele of the SNPs ALCAMc.1017T>C and ALCAMc.1104+85T>C was the favourable allele when improving resistance against FH-INF. Significant allele substitution for rGIN-INF was only found for the chip SNP ALCAMc.73+32791A>G. We identified significant associations between the SNPs with EBVs for milk fat%, protein% and FPR. Dominance effects for the EBVs of test-day traits ranged from 0.00 to 0.47 SD and were in the direction of improved resistance for rFH-INF. We estimated favourable dominance effects from same genotypes for rFH-INF and FPR, but dominance effects were antagonistic between rFH-INF and SCS.

Invited review: Phenotyping strategies and quantitative-genetic background of resistance, tolerance and resilience associated traits in dairy cattle

In dairy cattle, resistance, tolerance and resilience refer to the adaptation ability to a broad range of environmental conditions, implying stable performances (e.g. production level, fertility status) independent from disease or infection pressure. All three mechanisms resistance, tolerance and resilience contribute to overall robustness, implying the evaluation of phenotyping and breeding strategies for improved robustness in dairy cattle populations. Classically, breeding approaches on improved robustness rely on simple production traits, in combination with detailed environmental descriptors and enhanced statistical modelling to infer possible genotype by environment interactions. In this regard, innovative environmental descriptors were heat stress indicators, and statistical modelling focussed on random regression or reaction norm methodology. A robust animal has high breeding values over a broad spectra of environmental levels. During the last years, direct health traits were included into selection indices, implying advances in genetic evaluations for traits being linked to resistance or tolerance against infectious and non-infectious diseases. Up to now, genetic evaluation for health traits is primarily based on subjectively measured producer-recorded data, with disease trait heritabilities in a low-to-moderate range. Thus, it is imperative to identify objectively measurable phenotypes as suitable biomarkers. New technologies (e.g. mid-infrared spectrometry) offer possibilities to determine potential biomarkers via laboratory analyses. Novel biomarkers include measurable physiological traits (e.g. serum metabolites, hormone levels) as indicators for a current infection, or the host's reaction to environmental stressors. The rumen microbiome composition is proposed as a biomarker to detect interactions between host genotype and environmental effects. The understanding of host genetic variation in disease resistance and individual expression of robustness encourages analyses on the underlying immune response (IR) system. Recent advances have been made in order to infer the genetic background of IR traits and cows immunological competence in relation to functional and production traits. Thus, a last aspect of this review addresses the genetic background and current state of genetic control for resistance to economically relevant infectious and non-infectious dairy cattle diseases by considering immune-related factors.

Symposium review: Novel strategies to genetically improve mastitis resistance in dairy cattle

Mastitis is a disease of major economic importance to the dairy cattle sector because of the high incidence of clinical mastitis and prevalence of subclinical mastitis and, consequently, the costs associated with treatment, production losses, and reduced animal welfare. Disease-recording systems compiling data from a large number of farms are still not widely implemented around the world; thus, selection for mastitis resistance is often based on genetically correlated indicator traits such as somatic cell count (SCC), udder depth, and fore udder attachment. However, in the past years, several countries have initiated collection systems of clinical mastitis, based on producers recording data in most cases. The large data sets generated have enabled researchers to assess incidence of this disease and to investigate the genetic background of clinical mastitis itself, as well as its relationships with other traits of interest to the dairy industry. The genetic correlations between clinical mastitis and its previous proxies were estimated more accurately and confirmed the strong relationship of clinical mastitis with SCC and udder depth. New traits deriving from SCC were also studied, with the most relevant findings being associated with mean somatic cell score (SCS) in early lactation, standard deviation of SCS, and excessive test-day SCC pattern. Genetic correlations between clinical mastitis and other economically important traits indicated that selection for mastitis resistance would also improve resistance against other diseases and enhance both fertility and longevity. However, milk yield remains negatively correlated with clinical mastitis, emphasizing the importance of including health traits in the breeding objectives to achieve genetic progress for all important traits. These studies enabled the establishment of new genetic and genomic evaluation models, which are more efficient for selection to mastitis resistance. Further studies that are potential keys for future improvement of mastitis resistance are deep investigation of the bacteriology of mastitis, identification of novel indicator traits and tools for selection, and development of a larger female reference population to improve reliability of genomic evaluations. These cutting-edge studies will result in a better understanding of the genetic background of mastitis resistance and enable a more accurate phenotyping and genetic selection to improve mastitis resistance, and consequently, animal welfare and industry profitability.

Review: Deciphering animal robustness. A synthesis to facilitate its use in livestock breeding and management

As the environments in which livestock are reared become more variable, animal robustness becomes an increasingly valuable attribute. Consequently, there is increasing focus on managing and breeding for it. However, robustness is a difficult phenotype to properly characterise because it is a complex trait composed of multiple components, including dynamic elements such as the rates of response to, and recovery from, environmental perturbations. In this review, the following definition of robustness is used: the ability, in the face of environmental constraints, to carry on doing the various things that the animal needs to do to favour its future ability to reproduce. The different elements of this definition are discussed to provide a clearer understanding of the components of robustness. The implications for quantifying robustness are that there is no single measure of robustness but rather that it is the combination of multiple and interacting component mechanisms whose relative value is context dependent. This context encompasses both the prevailing environment and the prevailing selection pressure. One key issue for measuring robustness is to be clear on the use to which the robustness measurements will employed. If the purpose is to identify biomarkers that may be useful for molecular phenotyping or genotyping, the measurements should focus on the physiological mechanisms underlying robustness. However, if the purpose of measuring robustness is to quantify the extent to which animals can adapt to limiting conditions then the measurements should focus on the life functions, the trade-offs between them and the animal's capacity to increase resource acquisition. The time-related aspect of robustness also has important implications. Single time-point measurements are of limited value because they do not permit measurement of responses to (and recovery from) environmental perturbations. The exception being single measurements of the accumulated consequence of a good (or bad) adaptive capacity, such as productive longevity and lifetime efficiency. In contrast, repeated measurements over time have a high potential for quantification of the animal's ability to cope with environmental challenges. Thus, we should be able to quantify differences in adaptive capacity from the data that are increasingly becoming available with the deployment of automated monitoring technology on farm. The challenge for future management and breeding will be how to combine various proxy measures to obtain reliable estimates of robustness components in large populations. A key aspect for achieving this is to define phenotypes from consideration of their biological properties and not just from available measures.

Genetics and genomics of reproductive performance in dairy and beef cattle

Excellent reproductive performance in both males and females is fundamental to profitable dairy and beef production systems. In this review we undertook a meta-analysis of genetic parameters for female reproductive performance across 55 dairy studies or populations and 12 beef studies or populations as well as across 28 different studies or populations for male reproductive performance. A plethora of reproductive phenotypes exist in dairy and beef cattle and a meta-analysis of the literature suggests that most of the female reproductive traits in dairy and beef cattle tend to be lowly heritable (0.02 to 0.04). Reproductive-related phenotypes in male animals (e.g. semen quality) tend to be more heritable than female reproductive phenotypes with mean heritability estimates of between 0.05 and 0.22 for semen-related traits with the exception of scrotal circumference (0.42) and field non-return rate (0.001). The low heritability of reproductive traits, in females in particular, does not however imply that genetic selection cannot alter phenotypic performance as evidenced by the decline until recently in dairy cow reproductive performance attributable in part to aggressive selection for increased milk production. Moreover, the antagonistic genetic correlations among reproductive traits and both milk (dairy cattle) and meat (beef cattle) yield is not unity thereby implying that simultaneous genetic selection for both increased (milk and meat) yield and reproductive performance is indeed possible. The required emphasis on reproductive traits within a breeding goal to halt deterioration will vary based on the underlying assumptions and is discussed using examples for Ireland, the United Kingdom and Australia as well as quantifying the impact on genetic gain for milk production. Advancements in genomic technologies can aid in increasing the accuracy of selection for especially reproductive traits and thus genetic gain. Elucidation of the underlying genomic mechanisms for reproduction could also aid in resolving genetic antagonisms. Past breeding programmes have contributed to the deterioration in reproductive performance of dairy and beef cattle. The tools now exist, however, to reverse the genetic trends in reproductive performance underlying the observed phenotypic trends.