Harvest Moon: Some personal thoughts on past and future directions in animal breeding research.

Abstract

It was with great pleasure that I served on the editorial board of this journal for almost twenty years, gaining many insights into the developments of concepts and practices in our scientific field. Now, as I gladly hand over this editorial task to younger colleagues, I take the opportunity to present some thoughts on where we are and where we should go in animal breeding research. The major objective of animal breeding is to generate genetic progress. Note that “progress” has a positive connotation, meaning that breeding aims at changing populations in a desired, positive direction. This is different from “selection response”, which is neutral and also can go in the wrong direction, as we often see in cases of correlated selection responses on fitness traits. An important task of animal breeding research should therefore be to enable genetic progress, although this is certainly not the only reason for research in animal breeding, which can also, for example, provide revealing insights into more general biological mechanisms. In which research areas lies the greatest potential to further promote genetic progress in practical animal breeding? I will discuss this using two important (and rather old) concepts in breeding, namely the selection index and the breeder's equation. The selection index (Hazel,1943, Genetics 28: 467) provides the conceptual framework for the definition of the breeding goal. The value of traits here is defined in economic terms; more specifically, a marginal utility coefficient needs to be specified for each trait. While the overall concept of the selection index has proven to be extremely powerful in practical breeding, it must be doubted that all breeding goals can be fully expressed in economic terms. By and large, nowadays' breeding goals in most livestock species are composed of two parts: roughly one half is attributed to an increase in production value, that is producing more and better milk, meat, eggs etc. and by this improving the source of production-related income of the farmer. The other half is attributed to so-called functional traits, which originally were defined as traits that affect the ability of an animal to be productive in the first place. Initially, these were traits related to health, fertility and production efficiency, but now are extended to traits related to animal welfare (beyond health in the medical sense) and environmental impact. These latter aspects are linked to broader societal expectations towards animal production and thus indirectly to secure markets for animal products in the longer term. The immediate economic impact of functional traits lies in the saving of costs, for example through a reduction of expenses for vets and feed. But can the actual value of the trait “calving performance” of a dairy cow be fully appraised by a detailed account of costs saved for the vet and the drugs, working hours spent (including night-time surcharges), reduced milk performance, increased service period and eventually the costs of the calf and/or the replacement of the cow in the case of a fatal outcome? In all traits that are related to animal health and welfare, there is an additional non-monetary value, which consequently is hardly quantifiable in economic terms. This additional value has two aspects, which are interlinked: the suffering of the affected animals, and the societal impact. The loss of a male Holstein calf due to a difficult calving may be economically marginal, but it obviously has a serious animal welfare aspect, and society in the long term will not accept increased calf losses as a “by-product” of an economic breeding programme, with detrimental long-term effects on the willingness to consume animal products. A purely economic approach never will catch the full value of such traits, causing a too low weight of these traits in complex breeding goals. This in parts explains certain misdevelopments in practical breeding, such as unacceptably high piglet mortality rates in some high-fertility breeds, or the low and frustratingly slowly increasing longevity of dairy cows. Defining breeding goals is one of the key entrepreneurial challenges of a breeding organization, and it always has to take anticipated future production conditions, demand structures and socio-economic context into account. Personally, I expect that in many Western countries breeding objectives will have to respond to a much greater extent to society's expectations in terms of animal welfare, but also to an increasing scepticism towards an excessive industrialization of animal production. International commitments and coordinated actions to limit global heating will also assign much greater importance to trait complexes related to nutrient efficiency, direct greenhouse gas emission and climate adaptation. In the longer term, we even should be prepared for a decline in the consumption of meat and animal products, due to their inherent “climate inefficiency” relative to plant-based diets. A purely economic approach has its limitations here, hence alternative approaches, more in the spirit of “desired gains” indices should be revisited and considered. Such developments certainly would benefit from an intensified exchange of the animal breeding community with experts in economics, business and social sciences. While breeding goals determine where to go, breeding programmes describe, how to get there. The conceptual core of breeding programmes is the breeders' equation, which dates back to Lush's seminal book “Animal Breeding Plans” in 1937. From this simple equation it is apparent, that animal breeding basically has three main levers to accelerate genetic progress: increased selection intensity, more accurate breeding values and shorter generation intervals. The fourth factor in the equation, usable genetic variation, plays a role mainly in maintaining the possibility of genetic progress by avoiding erosion of genetic variance through inbreeding, while the possibilities of effectively increasing genetic variation, and through this genetic progress, are limited in many cases. An additional lever primarily affecting breeding efficiency (i.e. genetic progress over breeding costs) are the economics of performance testing. In reviewing the scientific literature of recent decades, my impression (which admittedly may be subject to a personal bias) is that a disproportionate amount of research has been devoted to a single factor, namely increasing the accuracy of breeding value estimation, while the other levers were considerably under-researched. Since the introduction of the basic BLUP concept through Henderson in the mid 1970s, there were a few significant methodological steps, like establishing animal models, random regression models and—most remarkably—the introduction of genomic breeding value estimation. In addition, we have seen extensive research on countless variations of the established evaluation methods, which often were found to have miniscule effects on the ranking of selection candidates in a practical context. This was especially so in the genomic era, where whole methodological “alphabets” were developed without ever leading to a sustainable advantage over simple and robust basic methods like GBLUP. Other efforts were aimed at identifying single genes or QTL that could eventually help to make better genetic predictions. In the context of complex traits, this approach, originally developed in the era of “marker-assisted selection” in the 1990s and carried over into the era of genomic selection, has not, with few exceptions, significantly improved the accuracy of breeding values that contribute to improved genetic progress. Although there are excellent arguments for conducting research aimed at better understanding the genetic basis of complex traits, directly increasing genetic progress in such traits is not the most convincing among them. While a strong focus has been placed on research aiming at the increase of the accuracy of breeding values, the other two major levers affecting genetic progress, that is selection intensity and generation interval, have received comparatively little research attention. Selection intensity in particular is also directly linked to breeding costs, making it the most crucial factor in the profitability of breeding programmes. Both are major elements of breeding programme design and thus less technical but more organizational. This may be one of the reason why research has much less focused on such topics in the last years or even decades. Another reason for this shortcoming is a lack of suitable methodology to design and optimize modern breeding programmes, which can no longer be represented by the breeder's equation in its simple form, but are complex in nature and therefore need to be adequately designed. In the first article of this issue, we present our ideas for a unifying concept of animal breeding programmes based on a modular approach that allows a comprehensive representation of breeding programmes of any complexity. Based on this, it will be possible to evaluate and ultimately optimize breeding programmes with different objective functions. Using more advanced methods for genetic evaluation may increase the accuracy of breeding values by a few per cent, which directly translates into an increase of the genetic progress by the same margin. I would argue that in many practical breeding programmes it will be relatively simple to achieve a similar or even higher proportional increase in selection intensity or a reduction in generation interval through a more stringent organization of the breeding process. However, we see relatively little research on innovative breeding programmes based on conceptual alternatives, such as a more nucleus type of breeding in dairy cattle, or programmes making much more systematic use of innovative reproductive technologies like semen and embryo sexing or cloning, but also of novel approaches to automated phenotyping. This being said, we should of course do one without leaving the other, that is combine the most accurate genetic evaluation methods with the most efficient design and stringent implementation of breeding programmes to achieve breeding goals that reflect the challenges of our time.