Challenges and strategies for genetic selection of sheep better adapted to harsh environments

Abstract

Sheep production enterprises are a common choice for farming in extensive conditions, leaving sheep exposed to environmental elements such as harsh climates or low-quality forage. It is important for animal breeding to consider adaptability to challenging environments in the genetic selection of sheep, especially given the expected effects anticipated from climate change. Breeding animals for unpredictable environments requires attention to the issue of genotype by environment interaction. Research into these issues for sheep has not matched that seen for intensive species such as pigs or dairy, but opportunities exist both within existing breeding structures as well as from the development of new, novel phenotypes. Health and fitness traits are likely to remain difficult to measure, but current methods and new protocols should be combined with other developments in animal breeding such as genomic selection for worth-while genetic gain. Sheep breeding structures and economics are very different from intensive species such as dairy and thus require particular approaches to promote cooperation and investment from individual breeders and industry. 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). Assuming sustainable stocking rates, extensive sheep farming may be favored in terms of the social and environmental concerns around animal production. However, low input systems are also associated with specific challenges. Outside the support of intensive systems, livestock are expected to survive, produce, and reproduce with little assistance from human intervention or shelter. In addition to requiring a high level of independence, they are also more exposed to the environmental elements such as harsh climates, disease, and parasite challenge. These environmental stressors directly affect production, but the implications for health and welfare should also be considered (Dwyer, 2009). Environmental intervention can be effective (Masters et al., 2023) and should aim to ensure the best outcome for animals wherever possible. In the majority of extensive systems, however, opportunities are limited for being either impractical or too expensive. Animals kept in extensive systems should thus possess an ability to adapt and cope with environmental challenges—a concern of animal breeding and genetics. The issue of adaptability has been previously reviewed according to different definitions such as the genetic selection for animal “robustness” (Rauw and Gomez-Raya, 2015) or “resilience” (Colditz and Hine, 2016; Berghof et al., 2019). The underlying concept is to achieve genetic selection of candidates most capable of withstanding or coping with environmental changes or challenges, with a desirable outcome for both performance and welfare (Rauw et al., 2021). A conceptual framework for genetic robustness was outlined by Knap (2005), and the reader interested in a wider treatment of “adaption and fitness” applied to both animal and plant species should also see the topics compiled by van der Werf et al. (2009). In extensive sheep flocks, climatic stress is a key focus of environmental adaption, and will likely become a greater concern with the effects expected from climate change (Rust and Rust, 2013). Heat stress, for example, has important implications for the well-being of ruminants (Silanikove, 2000). Accordingly, opportunities for genetic improvement of heat stress resistance has received considerable attention in the last two decades, but with the majority of studies aimed at intensive species such as dairy cattle (Pryce et al., 2022). Despite the very high level of exposure to heat stress for sheep, information on the genetic components of heat stress resistance is scarce . In turn, certain stages of the sheep reproduction cycle can also be particularly susceptible to cold stress, which has severe implications for mortality rate when lambs are born into cold, wet, and windy conditions (Donnelly, 1984). Premature death is not only a major contributor to overall reproductive wastage but also an important social concern (Dwyer, 2008). In addition to other stressors such as parasite and disease challenge, this review will address the challenges and opportunities in considering important environmental factors in genetic selection of sheep. This paper aims to (1) provide a short overview of the issues for genetic selection across variable environments; (2) consider the challenges in adapting these concepts to sheep breeding; and (3) suggest strategies promoting research and implementation, both through opportunities within existing datasets as well as in development of novel breeding objectives. Genetic gain is achieved through selection of breeding candidates according to estimated breeding value (EBV) derived from the well-known method of best linear unbiased prediction (BLUP) analysis of performance records. An important characteristic of EBVs is that they present the expected performance of the animal or genotype in the “average” environment (i.e., genetic merit is determined after environmental influences have been accounted for). In the two-tier system common in sheep breeding; however, there may be problems with this assumption. Stud breeders form the top-tier, where performance and pedigree recording is used to identify and market superior males as breeding stock. Producers, who form the lower (commercial) tier, purchase the sires for improving the genetics of their flocks. Producers often make use of the low input, extensive systems described as the target environment of this review, but here performance is not usually recorded on an individual level. In turn, stud animals in the top tier are more likely to be maintained under more intensive management with access to supplementary feeding, shelter, and supervision. Evidence of special treatment of stud animals is not formally recorded, but a well-known occurrence in commercial sheep breeding. The issue is important, because the more challenging circumstances of the progeny born in the lower tier are not accounted for in the “average” environment according to BLUP analysis. This leads not only to a biased EBV but also brings the issue of genotype by environment interaction (G×E), the contention that the genetic merit of an animal is dependent on the environment in which it is recorded. In a G×E scenario, the highest-ranking genotype (e.g., sire) in a given environment (e.g., intensive) is not necessarily the preferred candidate in a different environment. This issue of re-ranking is outlined in Figure 1, an exaggerated example where performance is directly linked to a continuous gradient between either warm or very cold climates. The effects of genotype by environment interaction on performance (y-axis) according to different windows of environmental change (x-axis). Roughly adapted from Fig(s) 3 and 4 of Falconer (1990). If genotype B is well adapted to cope with heat stress, and genotype A with the cold, selecting the best genotype depends on the “environmental window” within which they are measured (e.g., I or III). The extent of re-ranking between A and B will depend on 1) how sensitive genetic performance is to environmental change and 2) the extent of environmental variation, or “width of the window", within which they were recorded. Genetic selection for genotype B in environment I (or vice versa for A in III) should result in genetic progress because in this environment it is likely the preferred candidate more often than not (see Falconer, 1990 for discussion). However, if both heat and cold stress are present, such as in environment II (Figure 1), genetic selection could be ineffective since both A and B could be the preferred choice depending on the climate at a particular time. This describes the general issue of G×E, which can slow genetic progress if the environment is not considered (Mulder and Bijma, 2005). The effect of temperature is an important example, but the environmental stressor could also be the plane of nutrition, disease, or parasite challenge. These are common stressors in extensive systems, and considering adaptability to these factors should be a priority in sheep breeding (Figures 2–4). The dual purpose Dohne Merino sheep breed navigating the hot and arid landscape of the Karoo region, South Africa (Source: Koenas van der Westhuizen). In addition to hot and dry climates, extensive landscapes can also be mountainous, requiring healthy, capable sheep to best make use of the available grazing (Source: Kobus Delport). Here, the same Dohne Merino sheep breed is found in the cold and snowy regions of Patagonia, Chile (Source: Kobus Delport). The most desirable characteristic of production animals is the ability to express good performance or fitness independent of the environment, i.e., a genotype “robust” to external stressors (Knap, 2005). A robust genotype is not necessarily the best performing in either environment I or III, for example, but rather the animal with the best average performance across all environments. The review by Knap (2008) discusses two approaches to testing genetic robustness and resilience. The first involves “reaction norm” analysis (see De Jong and Bijma, 2002), where genetic performance of production or “output” traits are tested for sensitivity to environmental change. The second is to phenotypethe animal’s response to a particular stressor explicitly, for example, the ability to cope with a harsh climate or resistance to a parasitic challenge. The reaction norm approach could be possible with existing datasets recorded to measure production, while the method of directly measuring health or fitness will most likely require the development of new, novel phenotypes to be recorded additionally. In reaction norm analysis, robustness of a genotype can be tested by deriving the random regression of genetic performance on an environmental covariate (e.g., heat or cold stress in Figure 1). In the simplest case of a linear reaction norm, the EBV consists of two components: the intercept or the predicted merit for the average environment and the slope or the predicted sensitivity to environmental change. 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The ability to identify candidates on the information from a few important would be a desirable but the of have been outlined in the Despite a considerable of a small of very important not deliver prediction of genetic to fitness or are often on a but the underlying genetic components are (i.e., outcome is determined by of small to Accordingly, the best approach for genetic gain for these traits is most likely by genomic the method of considering all the information available by as an of genetic (see et al., for an have applied genomic selection in sheep to target difficult to measure or fitness traits such as of et al., parasite resistance et al., and et al., 2021). can also be into G×E studies to genomic reaction norm genetic between different of the environmental (see et al., for an example applied to heat variable effects to it is also possible to effects according to the estimated slope of reaction norm et al., 2022). The method of genomic genomic is in continuous development et al., but has become in breeding for sheep et al., et al., The use of genomic selection methods is likely to a key in the of traits into sheep breeding der Werf et al., By that are to recording difficult to measure could prediction of these traits in flocks where the traits are not recorded. However, the a has been in the in that a level of continuous and be In other difficult to measure traits have to be which could be challenging within certain of commercial sheep breeding. A key in breeding sheep for or fitness will be the of recording and to deliver breeding to commercial to approach this is to an the as a breeding to the and et al., 2022). 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These issues well with the of improving animal since the genetic selection of welfare 2016; et al., with the of animal robustness or (Rauw and Gomez-Raya, and Hine, This paper reviewed the challenges and opportunities for animal breeding to to the high exposure of sheep to harsh conditions, a that be given the expected effects associated with climate change. of the specific being adaption, or it is that animal approach of selecting animals with the production output is not the for these research into these issues should especially for sheep, which have not been to the same level of and development as the more are opportunities within existing structures and but the new developments in novel are the most for progress these in The majority of these new phenotypes are very likely to remain to however, and genetic gain will depend on being combined with other and methods such as genomic This will require and but has been in breeding It is also likely that will be effective in sheep production with the of the This review has not the of the of small to an important but also challenging for sheep breeding and genetics et al., 2022). It also not developments that could deliver more environmental such as where a dual use of as or for sheep as well as production of and 2022). Genetic selection for more robust or sheep should with these climate and intervention However, genetic gain and it can thus be that both the research and commercial should be in opportunities and the challenges such as outlined in this is a within the of of the of South and in at the of and in research in genetics of sheep. has been the of the first studies into genetic prediction of South Merino sheep but has also on and cold stress resilience. are in the genetic prediction of health and welfare and the use of genomic information to such breeding objectives. van der Werf a from and also at was an in from to and a at the for and Health between and In to where is in Breeding and at the of in research into genetic breeding breeding and genomic more than and the Sheep genetics from to which genomic selection was to the sheep industry. has been a of and was in the of of the Research was of in animal breeding such as and is of of Environmental and at has an from and Research in The and a from the of in has been a research at the of in between and and an at the of of in the between and is a research at of Breeding and in and at the Genetic and of in research animal in a climate change and animal and animal and from a at the of in as an at and and and and all from a in Breeding and from the of the was by the of and from to the in was to the of in where in in Breeding and with specific in and of is on sheep and

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