The author is an associate professor of dairy cattle genetics at Penn State University.

Chad Dechow

he CDCB (Council on Dairy Cattle Breeding) announced during this year’s World Dairy Expo that they will conduct genetic evaluations for six disease resistance traits. The traits that will be evaluated include mastitis resistance, hypocalcemia resistance, displaced abomasum resistance, ketosis resistance, metritis resistance, and retained placenta resistance.

These six traits were selected after initial studies demonstrated they are heritable, represent a significant economic cost to the dairy industry, and are consistently recorded across many farms. Initially, evaluations will be released for Holsteins, but the expectation is that other breeds will be added once the CDCB database grows and includes sufficient data from other breeds.

Farm data driven

Analyses for these traits are facilitated by farmer-recorded health records. When a health event is recorded into farm computer software such as PCDart or Dairy Comp 305 for herds that participate in DHI testing, the information flows through DRPCs (Dairy Records Processing Centers) to CDCB.

Prior to sending health information from the DRPC to CDCB, the data is reformatted so that there is no conducted data on any treatments, if any was given. This is done to protect the farm’s data as some dairy farmers may have concerns about sharing treatment data.

Producers will also have the option of opting out of sending health data to CDCB should they have privacy concerns. This data pipeline has been completed for some DRPCs but is still under development for others. Data for the initial research was conducted with data from Dairy Records Management Systems (DRMS).

Models already exist

Momentum for a national cow health evaluation has been building for some time. We’ve recognized that selection for yield traits could raise susceptibility to disease if not balanced with selection for health.

Nordic countries have a national disease treatment database that has facilitated cow health evaluations since the 1990s, but we do not have an equivalent system in the United States. In the early 2000s, research from the University of Wisconsin-Madison demonstrated that farmer record health data could be used to facilitate genetic evaluations. That research provided a path forward for health evaluations, but it took some time to build the interest across all necessary industry segments and infrastructure required for data to flow from farm to CDCB.

Genetic evaluations for these traits will be presented as disease resistance, with a PTA (Predicted Transmitting Ability) greater than zero indicating that a bull’s daughters are more resistant to that particular disease than a bull with a PTA less than zero.

For instance, consider a herd where 15 percent of cows have at least one episode of clinical mastitis during their lactation. This means that 85 percent of their cows were resistant to clinical mastitis.

We would expect 87 percent of daughters from a bull with a PTA for mastitis resistance of +2 percent to resist mastitis on that farm. On the other hand, 83 percent of daughters would be expected to resist mastitis from a bull with a PTA of -2 percent.

I realize that we think of disease on an incidence rate basis rather than a resistance basis. This makes it extremely important to understand that a higher number is preferred for these traits.

There has been an effort over the last decade to scale any newly released trait in a manner where a higher value is preferred. There are a few traits (SCS, calving ease, and stillbirths) where a smaller value is preferred. This made sense when those traits were developed because there were fewer traits to keep track of and the trait reporting was consistent with how that data was used for management.

As the number of traits available grows, keeping track of which traits should be higher or lower becomes more onerous. Having a common interpretation across traits minimizes the chance that misinterpretation will result in disastrous consequences. Type traits will remain an exception because they represent a biological range — for instance short to tall — that may or may not correspond to what is considered favorable.

A ramp-up period

The CDCB released preliminary health evaluations in December. This preliminary release allows key genetic industry partners to refine how they will handle the data and be prepared for the official release in April of 2018. Not all of the DRPCs had their procedures to send data to CDCB in place for the December evaluation, so the preliminary release will be based on a smaller database than the official evaluations in April.

The preliminary evaluation included a release of results files to each DRPC, to bull studs for their own bulls, breed associations, and those who nominate animals for genotyping. The preliminary release will allow various partners to provide examples of how that data will be presented and used in April. It is not, however, intended to be used for marketing or selection purposes. Because of this, genetic evaluations will not be available for individual animals to inform semen purchase decisions until the official April release.

The heritability of these health traits are all fairly low — less than 5 percent. Because of this, reliability of health trait evaluations will be lower than what we are accustomed to for most traits. For young bulls with no daughters, we can expect reliabilities of 50 percent or less. The reliability will be somewhat higher for mastitis resistance because that trait is recorded by the largest number of herds and because it has higher heritability than the others based on initial research.

Lower heritability and reliability does not mean that genetic progress can’t be made. We’ve made a lot of genetic change — both favorable and unfavorable — for low heritability fertility traits. What the lower reliabilities mean is that it will be important to not place all of our selection pressure on health traits at the expense of other economically important traits.

Updating Net Merit

Scientists at USDA who derive NM$ (Net Merit $) have calculated the economic value of these traits, and it is expected that they will be added to NM$ in April. Their combined weight is expected to be about 3 percent of NM$. This may be somewhat less than one might guess, but there are good reasons why this is so.

Health traits are correlated with other traits included in the index. Productive life, livability, somatic cell score, and fertility generally have favorable correlations with these traits, so we’re already selecting for improved cow health indirectly.

These new traits are an important addition to what we already select for and will improve our selection precision but will not result in dramatic reranking of sires. There is an additional factor that reduces their economic impact to some degree.

When we calculate the economic cost of disease, one of the primary costs is lost milk production for diseased cows. However, this cost is largely accounted for by PTA for milk, fat, and protein yield. If a bull’s daughters are frequently sick and have lower milk yield from being sick, his PTA for yield will reflect this.

While April will represent the beginning of national genetic evaluations for cow health, they are not the first or only genetic evaluations or indicators of cow health that are available to producers. How strongly will CDCB genetic evaluations and other sources and indicators of genetic merit correlate? How do we manage and sort through similar information from multiple sources? I’ll provide some thoughts on that topic next month.