Editors’ note: During the April board meeting, the Board of Trustees passed a directive to add possible change to the main animal page in Herdbook.

Wade Shafer, Ph.D.

This tenet certainly holds true when it comes to genetic evaluation. By now, all of us are well aware that EPD inevitably change over time. Curiously, change, particularly more than moderate change, is often cited as a reason to discount the utility of our genetic evaluation system or to question breeder integrity. For the most part, these are unwarranted deductions. The fact of the matter is, EPD should change over time — in some cases dramatically.

There are two sources of change in EPD over time. First, change can be due to differences in the methodology of calculation. As the technology for calculating EPD improves, an upgrading of the system is warranted from time to time. Upgrades and resulting changes are justified because they improve the validity of our genetic evaluation system. We certainly saw this with the movement to the IGS Multi-breed Genetic Evaluation powered by BOLT. This upgrade caused changes in EPDs, in some cases substantial change; however, it greatly improved our system — certainly justifying the changes.

The second type of change, which represents the vast majority of change over time, is due to additional data being incorporated into the data set. To illustrate this change, it is helpful to consider the relationship between estimates and “true” values. Because we aren’t privy to animals’ true genetic values, we are required to estimate them through the use of phenotypic observations. As additional observations are collected from one evaluation to the next, EPD, on average, move closer to the true values they estimate. Change resulting from this “zeroing in” on true values results in more accurate EPD —certainly a good thing.

Though clearly beneficial, this change can be sizable as EPD move toward their true values. To demonstrate this fact, let’s look at the possible change (PC) statistic associated with each EPD. Possible change is the range ± an animal’s EPD that, 67 percent of the time, we expect the animal’s true genetic value to fall within. If we extend the range to 2 and 3 PC units ± an animal’s EPD, its true value is expected to fall within the range 95 and 99 percent of the time, respectively. With these percentages in mind, we can make some assumptions; first, in a group of 100 bulls, it is expected that 33 (100 - 67), 5 (100 – 95) and 1 (100 – 99) of them have true genetic values outside a 1, 2 and 3 PC unit range, respectively, from their EPD for a particular trait; second, when considering multiple traits, the number of instances in which true values fall outside PC ranges increases by a multiple of the number of traits. For example, if we consider 15 traits on our sample of 100 bulls, we expect 495 (15 x 33), 75 (15 x 5) and 15 (15 x 1) instances where sires have true values more than 1, 2 and 3 PC units, respectively, from their current EPD.   

To add further perspective, let’s take a bull calf with a 60 YW EPD and a corresponding 0.30 accuracy.  The PC range for this calf’s EPD is ± 18.  If he turns into an AI sire, eventually developing a YW accuracy of 0.99 (i.e., his EPD is essentially his true genetic value), there is a 67, 95 and 99 percent chance that his 0.99 accuracy EPD will fall between 78-42 (± 1 PC unit), 96-24 (± 2 PC units) and 114-6 (± 3 PC units), respectively. As you can see, it would be fairly common (33 percent of the time) for the calf to end up with an EPD over 78 or under 42, a result that would fairly categorize him as either a high- or low-growth bull.  Furthermore, it wouldn’t be that extraordinary (1 percent of the time) for this middle-of-the-road YW calf to end up being on the very extreme ends of the spectrum (over 114 or under 6).  If we expand the array of traits to 15 for this calf, it would hardly be remarkable for one of his 0.99 accuracy EPDs to end up 3 PC units from where he started; it should happen 15 percent of the time.     

What does all this mean?  From my vantage point, this puts into perspective the fact estimates are going to change — in some cases, dramatically (e.g., beyond 3 PC units). Furthermore, through PC, we are told “upfront” about the range of change to anticipate. Therefore, when a sire moves dramatically, rather than discount our genetic evaluation system or assume there were faulty data submitted on him, we should be more accepting of it — knowing that it is expected to occur at a predicted frequency. 

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