Genomic Evaluation Guidelines

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DNA technology has developed rapidly in the past nearly two decades and now has a variety of applications. For beef cattle genetic improvement, the primary areas of application are pedigree validation, parentage determination, and gene-based (genotypic) selection. Individual and parentage verifications are now routine practices, and genomic data are now routinely used in EPD production. This chapter describes the current uses of DNA technology and provides an overview of applications currently under development.

DNA Markers

Analytical techniques to differentiate DNA of individuals or populations require genetic markers, which are defined as identifiable DNA segments that differ in nucleotide sequence from one individual to the next. The current standard for identifying genomic markers is single nucleotide polymorphisms (SNPs). Beadarray based "chips" create uniquely identifiable DNA patterns that may be used to follow the transmission of specific chromosomal regions from parents to progeny.

As the name implies, SNPs are a change (mutation) from the specific nucleotide originally present in a particular location in an individual to a different nucleotide at that same site and are transmitted from parent to offspring, just like a gene. Across evolutionary time, thousands of SNPs have been created by mutation. They now can be found every 100 to 300 bases throughout the 3-billion base pairs in the genome. Because SNPs are widely distributed, it is likely that any gene of economic importance is located closely adjacent to several SNPs that can be used to mark its presence. SNP markers promise to be increasingly useful in the future for developing high-resolution maps because of their high throughput capability and potentially low cost in generating data. With the availability of whole-genome sequences, SNPs that are dispersed across all chromosomes present important advantages as markers for genomic analysis.

Some SNPs are located within the coding region of a gene and can affect the structure and function of a protein. This type of variation may be directly responsible for differences among individuals in phenotypic merit for economically important traits. Other SNPs occur either “upstream” or “downstream” of the coding region of a gene and may influence the regulation of gene expression. Others occur in locations that do not interfere with the structure or production of a protein.

DNA Collection

DNA is found in every nucleated cell in the body. It can be extracted from semen, muscle, fat, white blood cells found in blood and milk, skin, and epithelial cells collected from saliva. Minute amounts of tissue, such as a single drop of blood or several mucosal cells, are all that are required for routine DNA analysis. Common collection methods include a drop of blood blotted on a paper that is dried, covered, and stored at room temperature, ear tag systems that deposit a tissue sample in an enclosed container with bar code identification, and hair follicles. Techniques have been developed that allow for rapid release of DNA from cells and immediate analysis of the samples.

Combining Molecular and Quantitative Approaches in Genetic Evaluation

Performance testing and genetic evaluation are being conducted on an increasing number of traits. Types of information available (i.e., available from a practical and economical view) vary among traits. Types of information include pedigree relationships, performance measurements (i.e., phenotypes), and DNA test results. Phenotypes may include direct and indirect measurements on the same trait.

Some traits are difficult to measure for which there are currently no DNA tests available. These traits will likely be the focus of future research. In a second category are traits for which phenotypes are regularly measured in the field, systematically data-based, and for which EPDs are computed. The emergence of DNA tests now permits estimation of BV on animals for which little or no phenotypic information is available (a third category). A current example would be tenderness. Tenderness phenotypes are difficult and expensive to measure, but DNA tests are available. In a fourth category are traits where both phenotypes and DNA tests are available. A current example would be carcass marbling.

Guiding Philosophy

BIF believes that information from DNA tests only has value in selection when incorporated with all other available forms of performance information for economically important traits in NCE, and when communicated in the form of an EPD with corresponding BIF accuracy. For some economically important traits information other than DNA tests may not be available. Selection tools based on these tests should still be expressed as EPD within the normal parameters of NCE.


DNA tests are developed based on associations between variations in base-pair sequences at one or more loci with variations in phenotypes. The animal populations used to develop the test may or may not be representative of beef industry populations. Validation generally involves the confirmation or rejection of these associations in populations that are representative of the beef industry and different from those in which the tests were developed. Validation studies are considered to be more reliable if conducted by scientists who have no vested interest in the tests (e.g., development, commercialization, or marketing). To date, components of commercially available DNA tests have been validated by the National Beef Cattle Evaluation Consortium (NBCEC) serving as an independent third party. Validation serves to reduce risk for breeders using DNA tests for selection.

BIF recommends that breeders who use DNA tests should, whenever possible, choose DNA tests that have been validated in populations that are representative of the beef cattle industry by scientists independent of the organization that developed or will market the test.


Assessment involves determining how specific DNA tests are associated with each other and with non-target phenotypes. Assessment seeks to determine how competing DNA tests overlap and how non-target traits will be influenced by selection based on these tests. For example, it is important to know if selection based on a DNA test for tenderness has any desirable or adverse effects on other economically important traits (growth, feed intake, fertility, etc.). As with validation, assessment studies are considered to be more reliable if conducted by scientists who have no vested interest in the tests.

BIF recommends that assessment studies should be conducted in populations that are representative of the beef cattle industry by scientists independent of the organization that developed or will market the test.

Inclusion of DNA Test Information in NCE Programs

Statistical procedures for incorporating DNA test information into NCE and the computation of EPD and associated accuracies are described in Single-step Hybrid Marker Effects Models and Single-step Genomic BLUP. Results of the evaluation of a DNA test will also provide estimated genetic correlations among competing DNA tests, genetic correlations between DNA tests and non-target traits, and the fraction of the additive genetic variance of the target trait accounted for by the DNA test.

Results of the evaluation phase (described above) will provide all the statistical parameters needed for NCE. The decision to include a DNA test in a NCE system should be made by the organization responsible for computing the EPD. Consideration should be given to heritability of the trait, availability of producer-collected phenotypes, and increase in accuracy provided by the addition of the DNA test information. BIF recommends that a DNA test should be considered for inclusion in the NCE system when, after estimating the covariances and running the NCE system, use of the DNA test results in more accurate EPD at a young age.

Reporting of DNA Test Results by Genomic Companies It is important the DNA test results be reported to the beef industry in a consistent, understandable format. Further, the format should be compatible with NCE methods. It’s possible that a single DNA test (i.e., genotypes from a single panel of markers) may yield information useful for both management and selection. Predictors based on these tests should be clearly identified with respect to their uses – i.e., future phenotypes versus breeding value.

BIF recommends that DNA test results be reported in the form of an EPD, in units of the trait, on a continuous scale, and with a corresponding BIF accuracy. It is likely that research will develop new DNA tests for traits that have no industry-collected phenotypes. If the target trait is measured in the reference populations, evaluation of the DNA test as a selection tool should be as described above.

Novel Traits

It’s conceivable that the target traits for some new DNA tests may not be measured in reference populations. In such cases precise definition of the target trait will be important.

An independent organization such as NBCEC should conduct or coordinate the validation studies of DNA tests for novel traits. Validation may be approximated by review and (or) re-analysis of data used to develop the test. Such data should include DNA test results, phenotypes, and pedigree relationships. Data used to develop such new tests should be of sufficient quality and quantity to allow the estimation of the additive genetic variance of the target trait and the covariance between the DNA test score and the target trait.

BIF recommends that, for DNA tests targeting traits that have no industry-collected phenotypes and for which no phenotypes are collected in reference populations, results should be reported in the form of an EPD, in the units of the trait, on a continuous scale, and with a corresponding BIF accuracy.


Information in this article was derived from Chapter 4 of the 9th edition of the BIF Guidelines, with substantial modification for updating to current technology and methods. The attribution in that chapter was to: M. W. Tess and the BIF Commission on DNA Markers. Commission members: Bill Bowman, Ronnie Green, Ronnie Silcox, Darrell Wilkes, and Jim Wilton. Please view the history link for this article for more information on these modifications.