Applications of Population Genetics to Animal Breeding, from Wright, Fisher and Lush to Genomic Prediction

Abstract

Although animal breeding was practiced long before the science of genetics and the relevant disciplines of population and quantitative genetics were known, breeding programs have mainly relied on simply selecting and mating the best individuals on their own or relatives' performance. This is based on sound quantitative genetic principles, developed and expounded by Lush, who attributed much of his understanding to Wright, and formalized in Fisher's infinitesimal model. Analysis at the level of individual loci and gene frequency distributions has had relatively little impact. Now with access to genomic data, a revolution in which molecular information is being used to enhance response with "genomic selection" is occurring. The predictions of breeding value still utilize multiple loci throughout the genome and, indeed, are largely compatible with additive and specifically infinitesimal model assumptions. I discuss some of the history and genetic issues as applied to the science of livestock improvement, which has had and continues to have major spin-offs into ideas and applications in other areas.

Genome-based establishment of a high-yielding heterotic pattern for hybrid wheat breeding

“…Accordingly, we observed a higher ratio of the additive versus the dominance genetic variance for the heterotic groups identified based on the simulated annealing algorithm compared with the scenario of random grouping of lines (Table 1). The enhanced relevance of additive genetic variance contributes to an increase in recurrent selection gain (16). Moreover, predictions based on additive effects are more accurate than those based on dominance effects (14).…”

“…Moreover, optimizing hybrid performance focuses on the short-term success of a heterotic pattern. This short-term success arises mainly through high selection intensities (16) and a low number of elite founder individuals in the heterotic groups. In contrast, long-term selection gain benefits from genetic variance, which is associated with a large effective population size of the heterotic pattern.…”

Predicting the future of plant breeding: complementing empirical evaluation with genetic prediction

“…The origins and development of quantitative genetics theory for both plant and animal breeding were strongly motivated by the need to provide a predictive genetic framework to guide the design of breeding methodology (Hill 2014;Walsh 2014). The 'Breeder's Equation' (Lynch and Walsh 1998;Walsh 2005) has been extended into many forms to represent the expected genetic gain from cycle to cycle for alternative breeding methods (e.g.…”

“…Traditional genetic evaluation techniques (Henderson 1984;Hallauer and Miranda Filho 1988;Hill 2014) rely exclusively on the use of phenotypic and pedigree data to estimate datasetspecific genetic parameters that are then used within Henderson's mixed model equations (HMME) to obtain best linear unbiased predictors (BLUP) for the candidates for selection. Both Likelihood and Bayesian statistical methods have been developed to perform this type of genetic evaluation (Sorensen and Gianola 2002).…”

Is Continued Genetic Improvement of Livestock Sustainable?

“…Chickens provide my main source of examples as they have been under very strong selection pressure for many decades in the developed world and there is well-documented evidence of their genetic improvement, but the principles are not species-dependent. Further background on animal breeding history, quantitative genetics theory, results, and references are given elsewhere by me (Hill 2010(Hill , 2014Hill et al 2016) and of course by many others.…”