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DNA + EPDs = Marker-Assisted "Optimum" Selection

The past 50 years has been a phenomenal learning experience for beef cattle breeders around the world. With the general foundation of population and quantitative genetics built by many prominent thinkers during the first half of the 20th century, and the advent of the computer-based information age of the past 20 years, we now have some very good tools available.With the past decades' developments

The past 50 years has been a phenomenal learning experience for beef cattle breeders around the world. With the general foundation of population and quantitative genetics built by many prominent thinkers during the first half of the 20th century, and the advent of the computer-based information age of the past 20 years, we now have some very good tools available.

With the past decades' developments in understanding the genetic code of animal and plant species, some of our traditional problems appear to have solutions. DNA technology may allow us to become much more accurate and comprehensive in our genetic evaluation of all species of livestock.

And, while they will be helpful for livestock and dairy industries worldwide, emerging DNA-based technologies will likely impact beef cattle production more heavily because the beef cattle industry has more to gain.

Unraveling The Genetic Code Our understanding of the genome of plants and animals was launched 20 years ago when methods of visualizing differences at the DNA level began to evolve. Much of this development resulted from several governments around the world attempting to "map" the human genome to allow development of better methods of fighting disease and aging.

This technology allowed the first genes to be identified and mapped during the 1980s. Yet progress was slow because the techniques were difficult and expensive.

Some rather dramatic molecular biology advancements occurred in the late 1980s. These allowed our DNA knowledge base to explode in the last 10 years.

In order to use this technology, we must identify the underlying genes contributing to the genetic variation between animals for performance traits. Given that we really know little about those genes, the first step had to be the development of a map of the bovine genome.

You might think of this map as an information highway for finding locations in DNA that play a role in interesting performance characteristics. Think of this map in terms of mile markers. Since the total cattle genome is organized into three billion individual nucleotides, we can conceptually divide it into "mile" units. A mile in our context is what is referred to as a centimorgan (cM). One centimorgan covers one million nucleotides, making a total of 3,000 "miles" of genetic highway in the bovine genome to be "mapped."

In short, a mile marker is defined as a location on the DNA highway where we are able to detect the genetic makeup of the individual (called genotyping). These locations are called DNA markers. The newer technologies produced in the late 1980s allowed us to identify a rather large number of these markers spread throughout the entire cattle genetic highway.

A huge aid in the development of the cattle gene map has been the discovery that most species in the world share over 80% sameness in base sequence in the genetic code. This knowledge is useful because as individual genes (and markers) are mapped in one species, they become useful information for mapping in another species.

As a result of a combination of new technologies and comparative mapping, several bovine gene maps have rapidly become well-marked in the past several years. As early as 1990, less than 150 locations were mapped with any degree of certainty in the bovine genome. Today, the number of marked locations in the public domain is considered to be between 1,800 to 2,000.

If we assume these marker locations are evenly spaced across the genome, then with 2,000 markers that means that there is a marker approximately every 1.3 "miles" of chromosomal distance. This type of gene map is very useful because we expect markers and genes within 50 "miles" of each other to be inherited together. This concept, called genetic linkage, allows us to use these markers to help us find unknown genes affecting economically important traits we are interested in improving. These genes are what we call quantitative trait loci (QTL).

The Search For Economically Important Trait Loci In 1994, the era of scanning of the bovine genetic map to search for markers associated with performance differences really got underway. One of the best examples in beef cattle is the set of resource families developed by Drs. Jeremy Taylor, Jim Sanders, Bill Turner and Scott Davis at Texas A&M University.

For the past 10 years, the beef cattle industry in the U.S. has been attempting to improve consumer demand for beef products by improving carcass merit. A beef checkoff-funded project was initiated at Texas A&M's Angleton research station to identify genes affecting variation in marbling ability.

The project, started in 1990, required the development of resource cattle families that would be expected to be highly heterozygous for genes affecting this trait and other measures of carcass merit. Through a series of controlled crossbreeding of Brahman and Angus, a total of 42 full-sib families were produced representing 16 sires and 19 dams. Life history data on 613 head of progeny were collected.

In this project, several important gene locations for a number of traits were identified, including five genes that appear to affect marbling and seven more that influence tenderness, measured either by Warner Bratzler Shear Force (WBS) or by taste panel evaluation. Additionally, the project identified five QTL effects on ribeye area, eight QTL effects on hot carcass weight, and five QTLs affecting dressing percentage.

Several things are evident from the experience and results of this project.

* It's clear that developing these resource families is a slow, expensive and laborious process.

* The approach used in this project will likely only uncover linked markers in chromosomal regions containing large QTL effects. Researchers still have to identify the exact genes causing these effects.

* Because this reverse genetics approach hopes to identify markers to be used in selection programs, the genetic relationships identified within a particular set of families may not hold up in other populations. In other words, the markers linked to QTL effects identified in this particular project may not be useful in families or breed populations beyond those of Angus or Brahman.

* Further, making the technology usable to industry is a major challenge. Given that we don't know how useful the markers identified in the project described above will be across other families and breeds, there must be a second step.

That step is currently underway as a portion of another large project funded by a partnership between the beef checkoff, an agricultural genetics company and 15 beef cattle breed associations. The project, commonly referred to as the National Carcass Merit Project, will evaluate 11,000 sire-identified progeny from 16 breeds over the next three years.

The project will validate 11 of the DNA markers identified by the Texas A&M project across the major U.S. beef breeds. Through this effort, we will quickly answer whether these markers will be widely useful.

Benefits Of Marker-Assisted Selection QTLs identified through ongoing searches of the developing bovine gene map are likely to be most beneficial for those traits that are difficult and expensive to measure. In order of greatest to least degree of benefit, we can expect the following categories of traits to benefit the most from marker-assisted selection (MAS):

* disease resistance and immunocompetence,

* carcass quality and palatability attributes,

* fertility and reproductive efficiency,

* maintenance requirements (i.e., energetic efficiency),

* carcass quantity and yield,

* milk production and maternal ability, and

* growth performance.

This ranking is due to a combination of considerations including: 1) relative difficulty in collecting performance data, 2) relative magnitude of the heritability and phenotypic variation observed in the traits, 3) current existing amount of performance information available, and 4) when performance data becomes available in the life cycle of the cow herd. Most of the rankings above then become self-explanatory.

To be realistic, however, we must realize that QTLs will not serve as silver bullets. As long as we rely on markers rather than the QTLs themselves we are still only crudely defining the genotypes across the larger beef cattle population.

Once the QTLs are finely mapped and direct tests are available, then the accuracy of selection will be markedly improved. Until then, however, the marginal gains that MAS make over selection on polygenic breeding values (i.e., EPDs) is not as high as you might think.

In the late 1970s, the late Charles Smith, a highly respected geneticist, predicted that gene level information would only provide substantial gains for traits in which genetic evaluation information is lacking. Thus, for traits that national cattle evaluation programs evaluate widely (i.e., growth rate) MAS will not help a great deal.

Results from a number of simulation studies now show quite clearly that he was correct. The overall conclusion is that markers combined with EPD information w ill enhance the accuracy of genetic evaluation.

Lastly, in the current climate of the beef cattle industry, where everyone is looking for a magical solution, it's imperative we don't overestimate this technology. Performance in economically important quantitative traits is due to many genes. While it is likely true that some genes play a bigger role, there still are many in the picture.

Have We Overlooked An Application Of DNA Markers? In our zest to search for individual gene effects, we may have overlooked an immediately usable application of DNA marker technology. Genetic improvement programs worldwide face an inability to trace back information on animals to the genetic level.

For example, in the U.S. a particular commercial animal may change ownership as many as 10 times during its production. Because of this industry structure, if a steak in a restaurant does not provide a satisfactory eating experience, the owner of that steak has no way to feed that information back to the producer to improve genetic programs.

Because every piece of the animal, or its products, contains a copy of the genetic code, DNA provides a unique mechanism for traceback. Furthermore, DNA identification of parentage from calves sired in multiple sire pasture situations would significantly enhance the accuracy of breeding value estimates as well as potentially give us new ways to evaluate genetic differences in male fertility.

Summary Tremendous progress has been made in the past decade toward understanding the bovine genome. We're in the beginning stages of providing producers with DNA information to improve the accuracy of our MAS decisions. This application of DNA technology will likely prove most beneficial for traits that are difficult to measure.

It's important to understand, however, that the MAS approach will only improve our current genetic evaluation procedures by incrementally adding to breeding value accuracy in some traits. In a concerted effort, powerful genetic prediction programs coupled with MAS will ultimately move us forward by allowing us to make genetic decisions on traits that are difficult, or costly, to measure. There's little doubt we will experience huge changes in the way we think about genetic evaluation in the future. As Lord Kelvin said many years ago, knowledge and information create the power to continually improve our world. In the end, that is our mission in life.

To begin reviewing those technologies that may have the greatest impact on the beef industry, you must first understand the organization of the genetic material in a beef animal.

Most cells of the cow, whether it is muscle, hair, white blood cell or any other form of cell, has a nucleus containing an exact copy of the total genome of the animal. The genome consists of all deoxyribonucleic acid (DNA), the major chemical component of chromosome pairs, in each cell nucleus.

In cattle, there are 30 pairs of chromosomes. At conception, one of the chromosomes in each pair is inherited from the sire, the other from the dam. These chromosomes are made up of two DNA strands wound around a core of protein.

DNA can be broken down into individual sub-units called genes, which contain the instructions, or genetic code, for a particular protein needed by an animal's body.

Genes are located at a particular location, or locus, on one of the 30 chromosome pairs. Genes are made up of a series of grouped, linked building blocks, called bases. Genes vary in size, with most ranging between 500 bases and 5,000 bases.

If the series of bases making up a gene has more than one possible form or allele, we say that the gene is polymorphic. A very small change, involving only one base in the gene, can cause a functional effect on performance.

A simple analogy to think about how genetic material is organized can be made by comparing the genome to a book. The book is divided into chapters (chromosomes) which have paragraphs(genes) composed of words (codons) made up of letters (bases or nucleotides).

As cattle breeders, we learn of genes and alleles through such simply inherited qualitative traits as color (black or red) and polled vs. horned. For example, we have known for a long time that there are two alleles at the black/red gene locus. The black allele is dominant.

That means when present, the black allele dominates the other allele (known as the recessive allele). In our example, this results in the animal being black if it carries the dominant allele either on one or both of the chromosomes where that gene locus resides.

If the animal carries one dominant allele and one recessive allele, the animal is called heterozygous. If the animal carries two of the same alleles (either dominant or recessive), the animal is known as homozygous.

An animal can be red only if it carries the recessive allele, which codes for red coat color, on both chromosomes of the pair (if it is a recessive homozygote). As a result, we all know that a heterozygote carrier black bull still can produce red calves if mated to a red cow, because that bull can still contribute one recessive allele to a mating.

This may sound straight-forward, but unfortunately the total genome is much more complex than our example. From the size of all of the chromosomal material combined, we estimate that there are over three billion individual nucleotides making up some 100,000 genes in the DNA code.

Furthermore, we have believed for a long time that most economically important traits are not coded through just one gene, but instead are controlled by many genes, a condition we call polygenic. What really complicates the picture is that it is likely that these genes interact with one another in ways we don't yet fully understand.

CyberGenetics CAB Genetics of Cattle US MARC INRA-France http://w3/ U.S. Livestock Genome Mapping Human Genome Links Rockefeller Institute Jackson Lab Roslin Institute Chicken Gene Map National Biotech. Center Waningen Ag. Chicken Canadian Beef Cattle Reference Herd Perkin Elmer AgGen ABS Global Inc. Texas A&M Gene Mapping