Implementation of genomic selection in UK beef and sheep breeding
Todd, Darren Lindsay
Genomic selection (GS) has been adopted by the dairy cattle breeding industry and the opportunity exists to implement this technology in UK beef and sheep breeding. However, these sectors do not appear so readily predisposed to GS implementation. Following an introduction to GS in Chapter 1, Chapter 2 investigated the structure of the little-studied UK beef breeding sector. This provided estimates of key commercial and pedigree population parameters, for use in modelling genetic gain from GS. Terminal traits were found to be the dominant selection goals, with 85% of beef-sired commercial matings resulting in progeny being slaughtered at a prime age. Pedigree bulls disseminated the majority of genes in the sector via natural service. The correlation between the terminal selection index (TI) and the sale price of breeding bulls was moderate, suggesting a modest uptake of genetic technology in the sector. Chapter 3 estimated selection intensity for TI, generation interval and the dissemination rate of improved genes in the pedigree Limousin population. In order to predict the genetic gain achievable in using GS in beef and sheep breeding, Chapters 4 to 6 undertook deterministic selection index simulations, incorporating genomic information as correlated traits. In Chapter 4, GS was modelled for terminal beef traits, when incorporating carcass information and accounting for likely genotype by environment interaction. Using a training population of 2000 sires, this concept was predicted to offer 40% greater genetic gain than existing BLUP selection using pedigree phenotypes. Gene flow methodology projected the commercial value of this gain to offer a substantial return net of genotyping costs. Chapter 5 explored GS for maternal beef traits within the concept of a nucleus breeding scheme. Whilst greater genetic gain was predicted with GS than with conventional BLUP, the economic value of this gain was projected to be too low to justify such a scheme in the UK. Chapter 6 proposed a synergy between computer tomography (CT) phenotypes and GS in sheep breeding. Developing a genomic predictor from male selection candidates with CT phenotypes and conventional performance records was predicted to increase genetic gain by 55% over BLUP selection without CT traits. Introducing GBV contributed most of the accuracy in this scenario, suggesting that the existing performance recording structure in UK sheep breeding could in the future be replaced by GS using CT. In the general discussion, the potential for GS in other beef and sheep traits was considered in the light of the outcomes of these simulations. Given the lack of vertical integration in UK beef and sheep sectors, the drivers for implementation of GS are examined. Finally, the options for international cooperation and the possibilities offered by future genotyping technology are considered. It was concluded that implementation of GS incorporating beef carcass phenotypes was merited and could provide a platform for future GS implementation in other novel traits. Sheep GS with CT traits was considered a higher risk strategy, due to the lack of evidence for uptake of existing EBV technology.