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Dr. Jamie Courter is your Mizzou Beef Genetics Extension Specialist

By Jared E. Decker Many of you have probably noticed that things have been a lot less active on the A Steak in Genomics™   blog, but you probably haven't known why. In January 2021, I was named the Wurdack Chair in Animal Genomics at Mizzou, and I now focus on research, with a little bit of teaching. I no longer have an extension appointment. But, with exciting news, the blog is about to become a lot more active! Jamie Courter began as the new MU Extension state beef genetics specialist in the Division of Animal Sciences on September 1, 2023. I have known Jamie for several years, meeting her at BIF when she was a Masters student. I have been impressed by Jamie in my interactions with her since that time.  Dr. Courter and I have been working closely together the last 6 weeks, and I am excited to work together to serve the beef industry for years to come! Jamie holds a bachelor’s degree in animal science from North Carolina State University and earned a master's degree in animal

Three Awesome Things We Learned From Hair Shedding

Figure 1 from Durbin et al. 2020.

We recently posted a preprint (a research publication that has not yet been peer reviewed) to the bioRxiv server. You can read the article here: https://doi.org/10.1101/2020.05.21.109553 

*Update: Peer-reviewed, published paper is available open-access here: https://gsejournal.biomedcentral.com/articles/10.1186/s12711-020-00584-0 "Development of a genetic evaluation for hair shedding in American Angus cattle to improve thermotolerance"

This manuscript describes our work with Angus breeders and Angus Genetics Inc. to create a hair shedding EPD for the American Angus Association.

We learned a lot of cool things about hair shedding in this paper. Including how hair shedding is related to other traits and how hair shedding is related to the environment.

1) Negative Relationship Between Milk and Growth
Something interesting to me was to learn more about the genetic correlation between weaning weight direct and weaning weight maternal. Most producers will know weaning weight maternal as the Milk EPD. Many animal breeders have believed that the negative genetic correlation between weaning weight maternal (milk) and weaning weight direct is a by-product of the procedures used to estimate EPDs. A negative genetic correlation between weaning weight and milk would mean that as the genetic potential for growth goes up the genetic potential for milk goes down, and vice versa. However, there has been some research to demonstrate that this genetic correlation in fact has a biological interpretation. Researchers directly measured the milk production of cattle. When they looked at the genetic relationship between these direct measures of milk production and growth they still observe a negative genetic correlation between milk and growth. C. Lee has hypothesized that this is possibly due to partitioning of energy within the cow. Cattle can either be predisposed to partition energy towards growth and body weight maintenance or they can be predisposed to partition energy towards milk production or other forms of maternal care. In most of our hair shedding and weaning weight analyses for this project we saw the same -0.3 to -0.4 range for genetic correlation between growth and milk as typically reported. However, when we divide the data based on the environment in which it was collected, the genetic correlation between weaning weight direct and milk becomes more negative in the Fescue Belt (-0.6). We believe that this may be due to the stressful environment making the choice to direct energy towards growth or lactation more severe in this challenging environment. IGS recently announced that they were setting the genetic correlation between weaning weight direct and weaning weight maternal to zero. I think this is a mistake. I think the negative genetic correlation between growth and milk is real, and we will have better EPDs if we account for this. However, more research is probably needed in this area.

2) Hair Shedding Grazing Fescue or Not is Similar but not Identical. 
The genetic correlation between hair shedding while grazing fescue versus hair shedding while grazing other forages is 0.93. The genetic correlation is not 1, so they are not identical, but they are very similar. Another way to think about this is if we are selecting for early shedding animals, whether grazing fescue or not, we would select the same animals. 
The repeatability of the trait is the amount of variation that is similar across different time points. In this case, it is how repeatable is hair shedding from one year to the next. For cattle grazing something other than fescue, the repeatability was the same as the heritability. This means we didn't observe any permanent effects other than additive genetics. However, when grazing fescue, the heritability was 0.40 and the repeatability was 0.45. This means that there are permanent effects outside of additive genetics that are affecting the hair shedding from year to year. What this permanent effect is, we don't know. Fescue can cause permanent damage to things like blood vessels. Ultimately, this tells us that the stress from fescue in one year is affecting the hair shedding in a different year.  

3) Hair Shedding Tells Us About the Current Status of the Cow.
About 35 to 40 percent of the variation in hair shedding is due to additive genetic effects. This means about 60 percent of the variation is due to factors outside of genetics. Further, the poorest shedding cows tend to be the youngest cows. 

Figure 3 from Durbin et al. 2020
Figure 3 from Durbin et al. 2020; comparison of hair shedding scores with animal age. The youngest, most stressed cows shed off later.

We all know that these youngest cows tend to be the most nutritionally stressed. Two-year-old cows are still growing, raising their first calf, trying to get re-bred, and are often lowest on the pecking order in a herd. Thus, hair shedding may tell us about the nutritional status of a cow, much like a body condition score. In hind sight, I wish we would have collected body condition scores on all of the cows in the project. Going forward, I'm interested to see how hair shedding can be used as a management tool, in addition to a selection tool.

Bonus Concept) LIGHT!
My senior year at New Mexico State, I got to take a graduate level Environmental Physiology course with Dr. Tim Ross. In that course, we learned that animals sensing light is a main method for them to sense seasonal changes. Interestingly, it appears that some of the largest associations with hair shedding are located near genes involved in light sensing or physiology of the eye. Very cool to see that concept come full circle in my group's research!

We are really excited to get this new genetic evaluation out for Angus producers. We are also excited to follow this first study up with a larger study of 35,000 hair shedding scores across 12,000 cows in 11 different beef breeds. It will be interesting to see which of these observations are supported in the larger data set.


Joe C. Paschal said…
Another great example of merging genomics with applied animal breeding! Thank you!
Jared Decker said…
Question regarding conception rates:

We didn't directly look at conception rates, but we tried to back into it. When we looked at unadjusted weaning weights (so cows get credit for older calves), early shedding cows had heavier calves. For cows grazing fescue, for every 1 point improvement in hair shedding, the calf weaning weight increased 11 pounds. For cows on other forages, for every 1 point improvement in hair shedding, the calf weaning weight increased 7 pounds. When we adjusted for age of calf, these effects went down to 5.5 and 2.5 pounds, respectively.
Jared Decker said…
Question regarding prediction accuracy:

We can predict hair shedding with a prediction accuracy of 0.70. This is quite accurate. The genetic evaluation uses a single-step analysis in which we combine pedigree and genomic information in a single analysis. Further, this is with 14,839 scores from 8,619 cows. Of these cows, 3,898 had genomic test data. The added information from repeated records helps us more precisely predict the animal's genetic merit.

In our follow-up genomic predictions we will use ~35,000 scores from ~12,000 cows.
Unknown said…
Thanks for posting this info! So cool! Great work and I appreciate all your hard work and applied research.🦁🐂🐃🐄🐓🐔🐾🐣🦚🐟🦆🦢🐜🌼🌾🍖🍗🥩🥓🍞🧀🌽🍶☕🍼🍯🍷🍦🥣🍳🥚🧂🥯🥜🥒🥦🍄🥔🥕🍇🍐🍊🍉🍑🍌🍒🍍🍓thanks!
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