Ebook Genetic improvement of farmed animals: Part 2

Part 2 book "Genetic improvement of farmed animals" includes content: Predicting breeding values, dairy cattle breeding, beef cattle breeding; sheep and goat breeding, poultry breeding, pig breeding, aquaculture breeding, future directions.
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Ebook Genetic improvement of farmed animals: Part 2 7 Predicting Breeding Values Introduction In Chapter 4 we concentrated on how to predict responses to selection in simple breeding programmes. This is useful for comparing alternative breeding programmes, and helping to make sensible investment decisions. When it comes to actually implementing selection there are a number of steps that can be taken to improve the chances of achieving the responses predicted. In this chapter, we will outline the steps that are required to obtain the most appropriate breeding values for any species, and discuss the issues involved. This process of predicting breeding values is often termed genetic evaluation. Figure 7.1 shows the typical steps involved in producing breeding values in modern breeding schemes. We discuss each of these steps in the following sections. However, it will be easier to understand how modern schemes work if we first examine some of the principles, and the earlier approaches, on which modern schemes are founded. Of course, the country, species and type of organization involved will all influence how these steps are implemented in practice. In this chapter we focus on the principles and generic approach, and in the later chapters we highlight the particular issues relevant to each species. Fig. 7.1. A flow diagram of a typical pathway to producing predicted breeding values. Performance Data and Pedigrees All genetic evaluation requires performance data of some type. These will either be direct measurements of the traits of interest in the selection programme or correlated, or proxy, traits which can be used as selection criteria. These data will need to be recorded on the animals in the breeding programme and their relatives, along with any appropriate details which will be used later to build the most appropriate model for analysis. For instance, the ages at weighing and the sexes of the lambs are two such factors if we are considering predicting the genetic merit of a population of sheep for body weight. Obviously, performance records should be as accurate as possible since any inaccuracies in data will increase the phenotypic variation of the trait (strictly speaking, the environmental component of this) and make it harder to predict the ‘true’ breeding values. For the various methods of evaluation, it is essential to collect complete and accurate pedigrees. This seems obvious too, but is not always easy, partly due to human error. For instance, the availability of genomic data has identified fairly high levels of incorrect parentage recording (typically 10–12% errors). Hence, it is important to have a proper database for the storage of pedigree data, and their validation at collection. When genomic data are available for a population, these can also be used to validate and correct pedigree records. Genomic data also offer another option for populations where pedigree data are not available, or are difficult to collect. Some genomic methods do not require pedigree data but the relationships among animals is computed from the genomic data. This means that genetic evaluation can be implemented without the requirement for pedigrees. This is discussed later in greater detail. In cattle, sheep and goats, collation and checking of performance and pedigree records tends to be carried by a recording agency. These recording agencies could be commercial companies that offer a charged service to farmers or breed associations. However, for fish, pigs and poultry, the recording operations are carried out mostly within breeding companies. For cattle, sheep and goats, the prediction of breeding values tends to be carried out at a national level, providing estimates of the genetic merit for all animals in the country, or at least those that have their pedigrees recorded. Usually, a national body is responsible for the genetic evaluation and the data are usually transferred from the recording agencies to the evaluation centre. Examples of national evaluation centres for dairy cattle include Edinburgh Genetic Evaluation Services (EGENES) 2019 in the UK, the Canadian Dairy Network (CDN), 2019 in Canada and the Council on Dairy Cattle Breeding in the USA (CDCB), 2019. Examples for sheep and goats include France Génétique Elevage (2019) in France, Sheep Improvement Limited (SIL), 2019 in New Zealand, Sheep Genetics-LambPlan (2019) and KidPlan (2019) in Australia. Evaluations are usually carried out separately for each breed, although across-breed evaluations are becoming more common, especially when records from crossbred animals are available. National systems for genetic evaluations often include a large amount of historical and current performance data and require deep pedigrees, usually spanning many generations. Pig, fish and poultry companies typically perform their genetic evaluations in house. Management of Candidates for Selection In most breeding programmes we attempt to disentangle the effects of genes and the environment, in order to select animals that have high genetic merit, and not those that perform well simply because they are well fed and managed. As far as possible, animals that are going to be compared should be managed to give them equal opportunity to express their genetic merit. For example, comparisons of post-weaning growth of animals will be fairest if they are all weaned at the same age and have equal access to feed. The en ...