MicroRNAs may predict lifelong cattle health, productivity

9/12/2018

In U.K. dairy herds, up to a third of cows are affected by disease or reproductive failure and need to be removed from the herd before the end of their productive life, according to an announcement from The Roslin Institute. This incurs significant costs to farmers and raises serious animal welfare issues.

Similar scenarios play out in dairy herds in the U.S. as well.

A procedure to identify cows early on that are likely to have problems later in life would be extremely beneficial for the dairy industry and would have the potential to significantly improve animal welfare, the institute said.

A study by scientists at The Roslin Institute and Scotland's Rural College showed that the blood levels of certain microRNAs change dramatically during early life in cows and, importantly, that some microRNAs are closely associated with the incidence of diseases such as lameness and mastitis, as well as with milk production in mature cows, the announcement said.

MicroRNAs are small molecules produced by all body tissues that play important regulatory roles in animals and plants. MicroRNA levels can be readily quantified in blood using standard laboratory procedures and can be used to assess changes in the function of specific body tissues -- a feature that is already being exploited for disease diagnosis in people, Roslin said.

"As we have already shown in previous studies, these results show that microRNAs may be very useful as diagnostic tools in dairy cows and potentially other livestock species. Specifically, we think that microRNAs could allow for selection early on of the most promising animals in a herd in order to maximize productivity and animal well-being," said Dr. Xavier Donadeu, one of the authors of the study at The Roslin Institute.

This work has been supported by Scotland's Rural College funds awarded to professor Georgios Banos and Donadeu. The results were published in the journal Scientific Reports.

Tags: Health, Herd, Productivity