Thursday, April 18, 2024

Genomic prediction routine in US beef cattle

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Predicting the merit of newborn calves based on SNP genotypes is now a commercial reality for many US beef cattle breeds. The American Angus Association was the first to offer its breeders access to genomic-enhanced Expected Progeny Differences (EPD) through one or both of their partnerships with two competing companies, Igenity (now owned by Neogen), and Zoetis (formally Pfizer Animal Genetics). Since that time, the American Simmental Association, American Hereford Association and North American Limousin Foundation have released genomic-enhanced EPDs. The Red Angus Association of America, the American Gelbvieh Association, and the International Brangus Breeders Association all have prototype genomic predictions and are likely to commercialise those services soon.
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There is no reason why New Zealand breeders could not have access to the same technology, validated in their own animals.

Genomic prediction requires access to a training population of animals with SNP genotypes as well as proven breeding information, that information ideally being based on progeny test performance.

Generally speaking, the training population should comprise at least 1000 animals, but the more animals available the better. The training population in the US dairy industry now exceeds 100,000 genotyped animals.

The training population is used to estimate the breeding values (EBV) of all the genomic fragments that can be identified across the genome using the SNP panel. Summing up the EBV of the inherited genomic fragments identified in newly genotyped animals not yet in the training population gives their EBV. Comparing such predictions to individual and progeny test records for animals not in the training population provides validation of the results.

The square of the correlation between predicted and actual performance indicates the proportion of variation explained by the test.

Training can be repeated as the population of genotyped animals increases, and this has doubled the proportion of variation that could be explained from the genomic tests applied to Hereford cattle from 14% (1081 animals) to 27% (2980 animals).

Results are a little better for American Simmental Association (at 30%) due to their larger (6150) training population, despite the fact their data includes animals from several breeds and breed crosses (e.g. SimAngus, SimBra). Distantly related animals, such as those in breeds not represented in training, cannot be reliably predicted.

Historically, the SNP genotypes have usually comprised information at about 50,000 (50K) loci or genomic positions spread over all the 30 chromosome pairs. Two higher density genotyping panels of about 700K have also been available, but have not improved predictive ability enough to warrant their more than double price tag.

More recently, new panels have become available that comprise custom content along with some of the SNP genotypes that were featured on the 50K or 700K panels. Custom content allows the panels to be used for parentage testing, and for testing for genetic defects and other major gene effects such as coat colour.

GeneSeek, an agri-genomics and veterinary diagnostics company in Nebraska, is the major genotyping company that extracts DNA and determines genotypes for many livestock improvement programmes around the world across a range of species. GeneSeek has recently released its own GeneSeek Genomic Profiler in low-density (GGP-LD 10K) and high-density (GGP-HD 77K) configurations, marketed to collaborating breed associations for US$45 and US$75 respectively.

In both cases, the genotypes from these panels are first transformed to 50K equivalent by a process known as imputation, and the resulting genotypes are then used to sum up the genomic effects to obtain a genomic EBV or EPD. The cost includes DNA extraction, parentage and genomic predictions, but additional royalties are required for some of the genetic defects whose rights are owned by other companies.

Not all traits are equally well predicted. Maternal weaning weight and calving ease are more difficult to predict, whereas birthweight and some carcase traits are more easily predicted (see table). We believe this is due to differences in genomic architecture of these different traits, reflecting the number and location of genes of large effects, among other factors.

Somewhat surprisingly, there are several genomic regions that are major determinants of performance, and these same regions seem to be involved in many breeds, and some of the regions also influence some traits within any particular breed.

The three largest regions in Hereford cattle alone account for more than 30% genetic variance for birthweight and 25% genetic variance in calving ease. These same regions also influence other traits including feedlot performance.

Another region that has some influence in Hereford, and major effects in Simmental and Gelbvieh, also has major effects in Bos indicus and Brangus cattle. That region was discovered in research done in NZ by Livestock Improvement Corporation as being an important determinant of the size and weight differences between Holstein-Friesian and Jersey cattle. The causal mutation was subsequently discovered and alternate homozygotes were shown to have birthweights of 36 vs 43 kg, and 180 vs 200kg liveweights around puberty.

The causal mutation has not been confirmed in these other beef breeds, and it may yet prove that there are several mutations that influence that same gene, known as PLAG1, in much the same way that double muscling in beef cattle, sheep, and humans is due to a variety of different mutations influencing the myostatin gene.

Knowledge of these major gene effects, and the availability of whole genome predictions of EBV, provide new tools for bull breeders and bull buyers. It is hard to believe that such technology wouldn’t have a place in NZ agriculture. 

  • Dorian Garrick is a geneticist at Iowa State University and is executive director of the National Beef Cattle Evaluation Consortium, www.nbcec.org. He is a former associate professor at Massey University.
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