The doubling of milk production per cow in the U.S. in the last 50 years did not happen by chance. Research data since the use of A.I. in dairy herds enrolled in the Dairy Herd Improvement (DHI) program clearly shows that selection for genetic merit for milk yield and the positive environment for feeding and husbandry are about equally responsible for this improvement in milk production.
The dairy industry is now in a position to take another big genetic step forward, thanks to new genetic technology, which has become available in the last five years. The technology, called genomics, has allowed researchers to identify differences at about 55,000 sites in the genetic material or DNA of dairy bulls. The DNA of over 13,000 dairy bulls has been characterized to identify which basic subunit of DNA or nucleotide base pairs were at these sites.
In dairy cattle DNA, each animal has 29 pairs of chromosomes plus a pair of sex chromosomes. One chromosome of each pair is inherited from their dam and the other from their sire. These nucleotide base pairs at each of the sites investigated can be one of three types. An animal can have a pair of one type from both parents (dominant), a pair of the other type from both parents (recessive) or a pair of one type from one parent and the other type from the other parent (dominant-recessive). The sites where differences have been identified in the dairy population, are known as single nucleotide polymorphisms (SNP’s). Using this information along with data on the traits in the Lifetime Net Merit index (NM$) and multiple generation pedigrees, researchers have been able to estimate associations of these SNP’s with certain traits that are a part of the NM$, as well as the NM$ itself.
Traditionally, in our genetic evaluations we have used parent and ancestor information along with individual and progeny information to predict the transmitting abilities of bulls and cows. With the new SNP data on bulls, we now have more information to use to make these predictions. Having more information to use in making these genetic predictions will increase their reliability. For young bulls with no progeny, we have only data on their parents and ancestors to predict the young bull’s transmitting ability.
A recent study by USDA scientists shows there is a very significant gain in reliability when the genomic data is added to the other data already collected and used in the current genetic evaluations. The data in Table 1, from the USDA study, gives the reliability gain for several yield traits and NM$ for young bulls compared to a reliability of the parent average of about 35 percent.
How this information will be used in the new genetic evaluations
The new genomic evaluations were published for the first time in January 2009. Use of the genomics technology and the enhanced genetic evaluations offers potential to radically change dairy cattle selection. Currently, the primary avenues for genetic improvement in an A.I.-bred dairy population are through the selection of the sires and dams of young bulls and the selection of proven sires from among progeny-tested young bulls.
The use of genomics data in conjunction with the traditional phenotypic data used in national genetic evaluations could permit more accurate identification of superior young sires and the selection, at a much earlier age, of superior bulls as the sires of the next generation of young sires. The latter choice could dramatically reduce the interval between generations and as a result significantly increase the rate of genetic improvement.
—Excerpts from Kentucky Dairy Notes, January 2009
Jack McAllister
Dairy Cattle Genetics
University of Kentucky
amcallis@uky.edu
