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SNP Evaluation Systems (continued)
Genomic Selection and Genetic Progress
There are three practical ways of increasing genetic progress: 1) increase accuracy of selection; 2) increase selection intensity; and 3) decrease generation interval, which also results in more selection steps per unit time. Whole genome selection is one of the few tools that can affect all three of these components affecting genetic progress. Accuracy clearly is increased with genomic selection using SNPs. Generation interval can be lowered easily as SNP evaluations of embryos are equally valid as evaluations for young or old animals. Because the technology can be applied broadly at relatively low cost (screening hundreds of embryos or calves), practical opportunities are provided for increasing selection intensity as well. The combination of these advantages, when added to pedigree and phenotypic information on each respective individual, becomes the most powerful, practical approach available for making genetic changes.
Benefits of Using Embryos
One of the most useful aspects of SNP evaluation systems is that they can be applied to evaluate any animal within the population used to develop a SNP system, even embryos or fetuses. Since genotype is fixed at the time of fertilization, the information from a SNP analysis of an embryo biopsy is just as valid as that from an animal of any age. It also is equally valid for ascertaining the genetic value for each sex. Since most Holstein bulls progeny-tested in North America are produced by embryo transfer, the screening process for selecting breeding bulls can be initiated between embryo recovery and embryo transfer. Because analysis of the SNP chip takes several days, including sending the sample to a laboratory, biopsied embryos ideally would be frozen, and selected embryos thawed and transferred. Because only a few cells would be available from a biopsy, as opposed to millions from a blood sample, a DNA amplification step is needed for this approach, a step that is relatively easy and inexpensive (Le Bourhis et al. 2009). The value of starting the genetic selection process with the embryo cannot be overemphasized (Sonstegard et al. 2008). Not only does one not waste costs of embryo transfer, recipients, and post-birth rearing on inferior genotypes, the generation interval is decreased, increasing the rate of genetic progress. Without biopsy and evaluation of genomic information, there is no way to distinguish differences in genetic value among embryos from a particular mating, but by combining technologies, the embryos that will turn into genetically inferior animals can be culled.
Dairy cattle selection has been emphasized because of the large amount of information available and because the benefits of genome selection using SNPs has been verified empirically for dairy cattle breeding (Hayes et al. 2009). While the same principles apply, it remains to be seen how useful this approach will be for beef cattle. It appears that it will be quite useful but much less than for dairy cattle, at least for traits that can be measured in both sexes like weaning weights. There likely will be special advantages of genomic selection for both beef and dairy cattle in breeding for difficult to measure traits, such as disease resistance (Hayes et al. 2009).
Table 2 provides an overview of the relative advantages of genomic selection of embryos using SNPs for selecting breeding males. The same relationships generally apply to selecting breeding females, but cows rarely have accurate progeny tests, and for some traits, their phenotypic information is an important part of the selection process. Genomic information will greatly increase the accuracy of genetic evaluations of cows compared to previous procedures. One factor not considered in Table 2 is cost; for example, costs of embryo transfer are spread over many more future animals through offspring of selected males compared to females. As most dairy bulls used for AI in North America are the result of embryo transfer, imposing selection at the embryo stage would not greatly affect costs. Another important point is the additional value of genomic information for progeny-tested males. The SNP information will be of considerably greater value in the early stages of accumulating progeny test data than later when reliabilities exceed 90%. Achieving high reliability of progeny-testing, however, usually takes years of accumulating data.
|Method||Stage of selection|
|Embryo||Prior to puberty||After progeny test (adult)|
|Progeny test systems||++||++||++|
|Progeny test & genomic selection using SNPs||+++++||++++||+++|
|Note: Rates depend on heritability of the trait, intensity of selection, and whether the trait can be measured in both sexes. When the trait can be measured prior to puberty, e.g., birth weight, that phenotypic information may alter the relative rates in the table.|
Some aspects of Table 2 will be considered controversial, for example, that selecting pre-pubertally with progeny test systems can be as effective as selecting after a progeny test. Although selection before a progeny test is risky for an individual male, the average of a population of young bulls selected based on their pedigree (plus phenotype for some traits) can result in nearly the same genetic gain relative to waiting for progeny test information. The risk of this approach in an individual herd is mitigated by using five or more bulls rather than fewer; the reason that using young, non-progeny-tested bulls is effective is entirely due to taking advantage of shorter generation intervals.
A third line might have been added to Table 2: genomic testing with SNPs without progeny testing. However, it is difficult to envision how such a system would work because accumulated progeny test information is the basis of using the SNP information, at least as currently carried out with cattle. All of these systems depend on collecting accurate phenotypic information that can be correlated with genomic information or pedigree information. High reliability progeny test information is a “gold standard” measure of phenotype.