2 minute read
Genetic Improvement of Longevity
by Ryan Boldt, Director of Breed Improvement
In terms of genetic improvement, some of the most challenging traits to make rapid genetic progress are fertility and longevity. There are several pre-disposing factors that make these traits diffi cult to improve including heritability of the traits, average age when phenotypes are collected and the sex-limited nature of the phenotypes.
The range of heritability for a trait like Stayability is low. Heritability predictions have generally been estimated to be 0.20 or less, based on diff erent populations and defi nitions of the trait. This adds challenges when selecting for these traits, because a majority of the performance differences that are experienced on the phenotypic level are driven by environment.
Another important factor to consider is that data for these traits can only be collected on females that are retained in the herd. An average rate of female retention is 20% of total females produced or approximately 10% of the total calf crop, assuming a 50/50 split of males and females. In addition to this, females are older when necessary phenotypes are collected so the ability to generate large amounts of data on young animals is more limited.
While each of the above factors presents challenges for making genetic progress in these traits, by using EPDs for selection decisions, genetic progress can still be made. Over time, copious amounts of work have gone into making the genetic evaluations of these diffi cult traits as accurate as possible. Tremendous time has been invested in research and development, statistical model improvement and improvement in data collection protocols with the goal to enhance the accuracy of these EPD predictions.
When the STAY EPD was fi rst introduced, it was a single-trait model and females had to be six years of age before an observation was collected. In 2007, an improvement allowed for observations at younger ages to be included in the model. Since then, another advancement in modeling techniques known as random regression has been employed. Currently this is the model being used in RAAA genetic evaluation conducted through International Genetic Solutions. This approach offers several advantages in terms of including more of the available data, as well as directly incorporating genomic information into the EPD calculations.
The question becomes, “Can we trust the information that we see on potential sires to improve the genetic merit of the herd?” To study this, a group of dams born from 1995 to 2011 were pulled from the RAAA database for analysis. These dams were then sorted into four groups based on the current STAY EPD of their sires. Within each of these groups the average number of single-born calves were calculated. The fi gure illustrates the average number of calves produced from dams in each of the diff erent quartiles from high to low sire STAY EPDs.
As illustrated, the EPD percentile becomes larger (less favorable STAY EPD) as we move across the diff erent groups, and the average number of calves produced per female per lifetime decreases – as we would expect. This is good news that shows if we use sires that have higher STAY EPDs, on average, we would expect the daughters of these sires to remain in the herd longer and produce more calves. This type of analysis provides evidence that when we look across large numbers of animals, we do see the EPD system working as expected, and that selecting for more favorable values will, on average, give more positive results. n