Dr. Stephen Miller jumps from the frying pan into the fire, so to speak, with a recent career change from the leading edge of fundamental research in beef cattle genomics to the cutting edge of its implementation.
“It’s exciting to be involved in the decisions on how to put the research into practice,” says Miller of his new position as director of genetic research with Angus Genetics Inc. (AGI), St. Joseph, Missouri.
“Genomics is a transformative technology because it greatly accelerates the rate of genetic change by evaluating more animals for more traits at younger ages.”
Miller became well-known within Canada’s beef industry for genomic research during his 20 years at the University of Guelph, obtaining his doctorate in animal breeding and genetics specializing in beef cattle, and continuing his career in that area with the department of animal and poultry science. Recent projects included the Canadian Cattle Genome Project and the related international 1000 Bull Genomes Project as well as genomic innovations projects investigating prediction tools to improve fertility, feed efficiency and carcass and meat quality led by the Canadian Simmental Association. Most recently, he spent nearly three years with New Zealand’s AgResearch animal genomics team.
Miller joined AGI in September as two major projects were starting to unfold. Both have implications for Canadian Black Angus genetics as well because AGI, a subsidiary of the American Angus Association, runs genomic evaluations for Black Angus cattle in both countries and also provides this service for the American and Canadian Charolais associations. Genomic evaluations for Canadian Red Angus cattle are run with those for the Red Angus Association of America by the American Simmental Association, which also handles Canadian Simmental genomic evaluations.
Single-step genomic evaluation
One project involves rolling over from the current two-step method of generating genomic evaluations to the single-step (creep) method, described in a recent journal article by a University of Georgia research team, and already in use for Holstein cattle, pigs and poultry.
As Miller explains, the single-step method eliminates the need for the periodic calibrations required for the two-step method. Calibrations correlate the genomic information for all genotyped animals in the database with the phenotypic information (pedigree, performance and progeny records) for all animals in the database to determine how well the two relate and adjust the prediction equation for each trait accordingly. Next, the genetic information for every genotyped animal needs to be run through the new prediction equation to establish each animal’s molecular breeding values for each trait and to merge with its phenotypic information for the genomic-enhanced expected progeny differences (EPDs).
The first calibration in 2010 included genotypes for 2,253 animals leading to the breed’s first set of genomic-enhanced EPDs. Including genomic information improves the accuracy of EPDs particularly for young sires because it adds the equivalent of seven to 24 performance records, depending on the trait, even before the bull sires any offspring at all. Calving ease direct, heifer pregnancy rate, weaning weight and yearling weight are among the traits with the highest number of progeny equivalencies, whereas, carcass weight and marbling are at the lower end.
The bottom line is that the progeny equivalencies as well as the correlations for the prediction equations change with each calibration. Through the years since 2010, genotypes have been added by leaps and bounds as DNA testing became more affordable and mainstream among breeders. Calibration five in July 2016 added genomic information for 108,000 animals to total 256,000 genotypes altogether in the database.
“So, our EPDs are getting more accurate and breeders see that as progress, but adding genotypes in big jumps of 50,000 or more all at once causes some abrupt EPD changes and re-ranking of sires,” Miller explains.
Re-ranking is most apparent among younger animals, but not so much the older ones because the genetic information is overwhelmed by the sheer number of progeny records that go into the calculation.
These abrupt changes are also evident when genetic evaluations are run only twice a year. Since 2010, Angus evaluations have been run weekly.
The single-step method handles genomic, phenotypic and pedigree information simultaneously so that new genetic information can be added as it comes in instead of having to wait for a calibration to update the prediction equation. The correlations and progeny equivalencies still change, but the changes are gradual.
Since last May, the single-step method has been in use for some traits to evaluate its ability to process information from a database as large as AGI’s. Starting in November, the one-step and two-step (based on calibration five) methods were running side by side every week to detect any significant issues. The plan is for a complete switch over to the one-step method by this spring for Angus cattle and then for AGI’s other clients.
Structured sire evaluation
Before genomics — not all that long ago considering the first complete bovine genome was sequenced in 2009 — pedigrees and actual performance data of an animal and its offspring were the only tools available to establish its genetic merit. The only way to prove carcass traits for EPDs was to organize trials to follow progeny through to harvest to get the actual carcass data, Miller explains, giving the Charolais breed’s “conception to consumer” program as one example.
Progeny trials have limitations in that the cost restricts the number of sires that can be evaluated each year and, because of the time frame from conception to harvest, some of the test sires may have been culled before the results are in hand.
DNA testing is much more timely and cost-effective than progeny trials now that it is becoming more the norm, Miller says. As a point in fact, genomic test results were submitted with more than one-quarter of the Angus cattle registered with the American association in 2015 alone. As of early November 2016, there were 272,000 genotypes in AGI’s database, up 16,000 from the July calibration.
To use a genomic prediction of carcass traits or any trait with confidence, there has to be a bulk of phenotypic information (reference population) for comparison to underpin the prediction equation.
Although there are 1.8 million yearling ultrasound records in AGI’s database, those only tell part of the story when it comes to actual carcass performance, Miller explains. Ultrasound is a useful predictor of genetic merit because the correlations between ultrasound and carcass measurements are high, for example, over 0.7 in the Angus database between ultrasound per cent intramuscular fat in yearling bulls and marbling in finished steers. Adding actual carcass data strengthens the genomic predictions.
Since AGI’s database holds only 112,000 actual measurements for carcass weight, ribeye, back fat and marbling collected over many years, AGI’s board of directors has decided to be proactive about getting measured carcass data by implementing a structured sire evaluation project.
Participating herds are large commercial operations that have the resources to do artificial insemination, record keeping and finish the calves or retain ownership to get carcass data from packers.
The reference population is being seeded with high-use Angus sires so far including AAR Ten X 7008 SA, Connealy Impression, Connealy Right Answer 746, GAR Prophet, and S Chisum 6175. The 24 test sires are some of their high-use progeny with a lot of ultrasound records on progeny, but lacking carcass data.
The first year, 1,850 cows were AI’d to the test sires from December 2015 through spring 2016. Another 2,000 cows will be AI’d this year with the hope that the program will be ongoing to test additional sires.
Miller says tenderness scoring isn’t part of this project because it is expensive and intensive requiring meat samples from each carcass to be collected at the plant and transported to a lab for testing.
An interesting add-on will involve collecting information on feedlot health traits, primarily the ability of test progeny to resist bovine respiratory disease during the feeding period. A scoring system developed by university and government researchers is being considered for use to record disease characteristics in live animals including the severity of temperature, eye and nasal discharge, cough, and depression. The analysis could tell whether there are sire differences and genomic relationships that might make it possible to get a genomic prediction.
More data from commercial herds
While research and technology have added new traits and increased the accuracy of selection tools, most of the phenotypic information has been collected from seedstock herds. To move ahead, emphasis needs to shift to collecting phenotypes from commercial herds. Those phenotypes, combined with genomics, can contribute to the selection of breeding stock beyond seedstock herds, in turn closing the loop from genetic research to seedstock to commercial producers.
“At the end of the day, all the best science is for naught if it does not show up in an improvement in cattle on the ranch, in the feedlot and the beef on consumers’ plates,” Miller says.