Using Genomics to Improve Dairy CattleTuesday, April 10, 2012
The British Society of Animal Science looks at how genetics can help producers improve their herd, not just for production traits, but also for traits such as greenhouse gas emissions and welfare.
Genomics is the process of identifying the genetic potential of an animal so they can be
selected for breeding on the basis of traits they are expected to show.
It can identify the potential of young animals quickly, helping target specific traits - such as feed efficiency and disease resistance - and help achieve selection goals much quicker than conventional breeding. It will therefore facilitate the improvement of dairy cattle for traits of interest to society at large, such as greenhouse gas emissions and welfare.
Farm animals have historically been selected for breeding on the basis of visual observation by farmers. More recently, farmers have used statistics to select animals which have the traits they consider most important. Artificial insemination (AI) in some species has allowed superior animals to sire many more offspring then they would do naturally, leading to faster rates of improvement. Selecting valuable traits this way does not modify an animal’s genetic make-up - it is simply an enhanced version of natural selection. The process should not be confused with genetic modification.
How genomics work
Genomes are the DNA which contain all genetic or hereditary information of an animal. The genetic difference between animals results mainly from variations in the sequence of nucleotides - four molecules that make up the structure of DNA. The locations of nucleotides along genomes are what makes one animal have better, or worse, traits than another. If the location of nucleotides belonging to an animal can be matched to another, it can be predicted how that animal will perform. That means that a farmer does not need to wait for an animal to mature to know what traits it will have.
The formula to predict an animals traits through its DNA is referred to as SNP (pronounced ‘SNIP’) Keys. Each SNP Key can be used to predict the breeding value of young animals that have not yet demonstrated any performance characteristics for a particular trait. SNP Keys can also be produced for any trait a farmer might be interested in. These predictions are called genomic estimated breeding values (gEBVs) and are highly accurate and dependable because they are based on a national database of more than 11,000 animals.
Conventional selection takes much longer as it relies on young bulls being tested through the performance of their progeny. This takes 5.5 years from the birth of a dairy bull, as the bull has to wait three years for their offspring to be born, have their own calves and start lactating. As a result, bull testing is expensive, needs many progeny to be accurate and is at risk from disease outbreaks.
Genomics allows farmers to benefit from a more widespread evaluation of breeding males for valuable traits - such as feed efficiency, TB-resistance and lameness - as well as better identification of elite females. There are also benefits of applying specific management practices to animals whose genotypes are now accurately known.
Are there any problems with genomics
Predictions for production traits are more accurate than for fitness, as they are more likely to be inherited and more information is available on them. Unless current recording practices change, there is a risk that less easily-inherited traits such as fitness and disease resistance will progress slower than production traits.
There has been some complaint over the consistency of genetic records collected onfarm for evaluation, particularly in the recording of health traits. A national model for recording traits could be considered to tackle the problem.
How will the industry react
Breeding companies invest heavily to ensure a supply of improved breeding stock to farmers through AI bulls, creating as a barrier to smaller companies and individual farmers entering the market.
Already the cost of contracts on bull dams has risen substantially, as has the cost to breeding companies of buying superior young bulls. This implies that although benefits are returning to farmers, these benefits are currently only being realised by a few pedigree breeders.
Ultimately, genomics will advantage individual farmers as they will have more superior AI bulls available for a wider range of traits. As genomic selection becomes more developed, the possibility of providing a service for a particular animal trait such as feed efficiency, or milk quality, may arise. This encourages entry into the market by industry sectors with particular commercial goals, but may lead to segmentation in recording and evaluation. Islands of farm data could arise, which a fail to produce the added value of a large single national dataset.