Sheep Industry News August 2021

Table 1

The information generated through the SNP chips enable the estimation of more accurate relationship among animals and, therefore, better estimates of inbreeding and genetic diversity in general. Such information also allows the identification of ani mals carrying genetic conditions that might be lethal or unfavor able, such as ovine progressive pneumonia and scrapie suscepti bilities, or with major impact on performance, such as myostatin and fertility genes. Furthermore, it can be used for parentage assignment and correction of pedigree errors. The information from these genetic markers can also be com bined with pedigree and phenotypic records to calculate Genom ic-enhanced Estimated Breeding Values in a process known as genomic prediction. The outcome is that selection response can be increased at an unprecedented rate in sheep and other live stock species (greater than 60 percent for some traits). However, to obtain GEBV we first need to establish a reference population, which are animals both with performance measurements for the traits of interest and genomic data. We then use the animals in this reference population to determine which SNP are favorably or unfavorably associated with a given trait. That information is combined with pedigree and performance records to predict the genetic merit of genotyped – and related non-genotyped – ani mals more accurately. The composition of the reference population impacts the ac curacy of the GEBV. The following factors are key. First, the refer ence population needs to represent the genetic diversity observed in the breed under selection. In other words, it is important to choose key ancestors and animals from multiple farms and genetic backgrounds to fully capture this genetic diversity that is present. Second, when establishing the reference population, all of the genotyped animals should also have performance records – or progeny with performance records – for the most important traits. The animals to be genotyped do not need to be measured for all traits of interest, but at least for some of them. Third, key ancestors – rams and ewes with multiple parities – should be

prioritized since they contribute more to the genetic pool. Lastly, those animals genotyped should not be chosen solely based on their performance. In other words, the reference population needs to contain animals across the range of performance levels. Genomic prediction enables breeders to obtain more ac curate breeding values in young animals that have not yet been measured for the traits of interest (e.g., number lambs born and reared), which then can be used in selection decisions. As an example, in Table 1 (above) we show the increase in accuracy achieved when adding genomic information for a lowly (h2 = 0.10) and moderately (h2 = 0.30) heritable trait, such as number reared and adult body weight, respectively. Particularly for traits that are lowly heritable, and where little performance informa tion is yet available, genomics is most advantageous. Such is also the case for traits that are difficult or expensive to measure (e.g., disease resistance, feed efficiency, meat quality), sex limited (e.g., litter size), or measured late in life (e.g., longev ity). As breeding programs in sheep incorporate this wider set of traits, genomic tools will become ever increasingly important. SUMMING UP Systems for genetic evaluation and selection are indispensable to our sheep industry. Combining new genomic technologies with our well-established and tested approaches provides tremen dous opportunity to improve traditional and more novel traits in our flocks. Importantly, genomics builds on what we already do, and does not replace it. In fact, for those already engaged with NSIP, EBVs will appear the same as now but will be predicted more accurately. Genomic evaluation does entail costs – both in terms of time invested and the expense of performance recording and genomic testing. Yet, the payoff is clear. Beyond more accurate EBVs, ancestry track ing is improved and genetic conditions are identified. By defining clear objectives for our breeding programs, and by utilizing the tools available to genetically improve our flocks, the growth and sustainability of our industry looks bright.

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