Study of PRRS in pigs shows the value of breeding for disease resilience
Emerging technologies and new statistical methods offer novel approaches to breed livestock that are resilient to disease, with potential significant cost savings to industry, according to a study published in Genetics Selection Evolution.
Improved statistical methods to quantify how animals respond to infection, and to what extent this is controlled by genes that give rise to these traits, pave the way towards selective breeding for optimum disease resilience, according to scientists from the Roslin Institute and pig breeding company Genus PIC.
The team developed mathematical models to estimate the economic value of disease resilience – how an animal’s productivity is impacted by exposure to infection.
The models take into account resistance to disease (the ability of a host animal to limit within-host pathogen load) as well as tolerance (the ability of an infected host to limit the damage caused by a given pathogen load).
The team used data from a previous study of piglets infected by porcine reproductive and respiratory syndrome virus (PRRSV).
According to their calculations, the value of selective breeding based on resistance and tolerance during infectious conditions was more than three times that of breeding based on production traits in disease-free conditions, demonstrating the high economic value of disease resilience.
Data capture or technologies that determine an animal’s response to infection based on its genes could be used to mitigate trade-offs between traits that contribute to resilience, the team found.
Monitoring the level of infection in an animal over time, in addition to tracking production traits, could be used to estimate the influence of resistance and tolerance on its response to infection.
Knowledge regarding genes that affect resistance and tolerance can be applied in two ways, they suggest.
Selective breeding may be based on groups of genes that in combination have a relatively large positive effect on both resistance or tolerance, or by identifying genes that confer complete resistance or complete tolerance to disease. This may however not be possible without new technologies such as genome editing, researchers add.
An alternative option would be to study automated data capture of livestock to determine how much an animal is affected by infection, and how well and how quickly it recovers based on parameters such as milk yield or feed intake.
The study was funded by Genus PLC, the BBSRC and the EU Horizon 2020 project SMARTER.
Article: Knap, P. W., Doeschl-Wilson, A. (2020). Why breed disease-resilient livestock, and how? Genetics, Selection, Evolution 52, 60, doi: 10.1186/s12711-020-00580-4
[SOURCE: The Roslin Institute]