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By Wade Shafer, Ph.D., ASA Executive Vice President     |     

Editor’s Note: This article was originally published in March 2008 issue of the SimTalk
written by Wade Shafer, Ph.D. Drs. Lauren Hyde and Jackie Atkins provided updates for reprint.     |     

A beef cow’s job is not an easy one. She is expected to conceive at slightly over one year of age, to calve by the time she is two, and rebreed shortly after that while weaning a healthy, viable calf. Furthermore, we demand that she consistently repeats this cycle for the rest of her life — one stumble and, hasta la vista, baby!

To be sure, producers are best served when the cow successfully performs her task for many years, as the longer her productive life, the more profitable she is to the enterprise. Is there anything that can be done to help her out? Certainly, there are environmental factors we can manage that will give her a leg up. For example, by providing adequate nutrition and a proper vaccination regimen and mating her to easy-calving sires (particularly when she is young), we increase the odds of her success. While a cow’s environment has a substantial impact on her reproductive performance, her genetic makeup can too. This article explores the genetics of female reproduction and offers suggestions on how to improve the reproductive performance of your cow herd via genetics.


The obvious place to start a discussion about the genetics of female reproduction is the factor that far and away has the greatest affect on it — crossbreeding. It has long been recognized that crossbreeding enhances virtually all aspects of reproductive performance. Studies too numerous to list here have established the reproductive superiority of crossbred over straightbred cows.

In one of an abundance of studies with similar findings, scientists at the Meat Animal Research Center (MARC) concluded that two-breed rotational cross cows produced 20% more calves over their lifetime than straightbreds due to the favorable impact of heterosis on dam fertility/longevity and calf survivability brought about by the improved calving and mothering ability of the dam (Cundiff et al., 1992). Furthermore, they estimated that when mated to a bull of another breed, the two-breed cross cows would wean 36% more weight over their lifespan than straightbred cows raising straightbred calves. The dramatic increase is attributable to the positive influence of heterosis on reproduction and production in the dam and well as increased growth and survivability in their calves.

Given the overwhelming evidence of the crossbred cow’s reproductive supremacy and the fact that reproduction is a major piece of the profitability puzzle (by most accounts exceeding all other functions by a wide margin of relative importance), it is difficult to conceive of a situation where a commercial enterprise would not benefit financially from a crossbred cow herd.

Are we implying that selecting animals within a breed for reproductive performance is not a worthwhile endeavor? No! Reproductive progress can be made via selection (which we will address later); however, it would take years of intense selection within a breed to yield the kind of improvement that can be achieved in one fell swoop by simply crossbreeding.

Therefore, crossbreeding makes a logical cornerstone in any effort to enhance cow herd reproductive performance. With crossbreeding as the foundation, the selection of superior animals of multiple breeds as inputs to the crossbreeding system can be considered a supplemental means of further boosting reproductive function; however, identifying reproductively superior animals has its challenges, as we will explain.

Indirect Selection

Because the assessment of a cow’s reproductive performance is generally determined later in her life, it seems logical to look for early indicators to hasten the process. For example, it is a commonly held belief that females with a propensity toward fatness will excel reproductively.

Though research has shown that increased fatness, to a point, is strongly and favorably associated with reproductive performance on a phenotypic scale, the few attempts to assess the relationship on a genetic level shows an unfavorable, though weak, relationship. Using data from the Red Angus Association of America (RAAA), researchers at Colorado State University (CSU; Beckman et al., 2006) derived genetic correlations ranging from -.12 to -.22 between body condition at various ages and Stayability (by industry convention, the probability of a cow remaining in the herd through 6 years of age). At the American Simmental Association (ASA), we have found a correlation of -.19 between an animal’s genetic propensity for backfat in the feedlot and their inherent Stayability. We (ASA) have also calculated a -.11 genetic correlation between backfat and heifer pregnancy (the likelihood of a heifer being pregnant at the end of the breeding season) using RAAA data.

Admittedly, these unfavorable correlations between fatness and reproduction may seem illogical. We have all seen a higher proportion of thin cows open at pregnancy test time. Keep in mind, however, that the aforementioned correlations are genetic correlations. The relationships we actually observe, i.e., phenotypic correlations, are influenced by a combination of underlying environmental and genetic relationships. There is little question that females within a herd lucky enough to experience an environment for increased body condition (e.g., extra energy intake) are likely to have better reproductive performance than their herd mates. Furthermore, this strong and positive environmental relationship between fat and reproduction apparently overwhelms what appears to be a slightly negative genetic relationship — yielding the strong, favorable phenotypic relationship we typically observe.

Frankly, there is not enough evidence about the genetic relationship between fatness and reproductive function to make recommendations based on it at this time; however, though it may fly in the face of conventional wisdom, it appears that selecting “easy-fleshing” genotypes will not gain us ground reproductively.

Scrotal circumference has been considered as a predictor of female reproductive performance. Though the preponderance of evidence indicates a strong to a moderately favorable relationship between scrotal circumference and age at puberty in related females, research is less clear on the relationship between scrotal circumference and subsequent measures of reproduction. In a study based on a large population involving several breeds at the MARC, Martinez-Velazquez et al. (2003) found a slightly unfavorable (.15) relationship between scrotal circumference and age at first calving and no relationship between scrotal circumference and first pregnancy, first calving, and first weaning rates. Their conclusion was that selection on scrotal circumference would not be effective in improving female reproduction. These findings are in agreement with some studies and contradicted by others. For those interested, Martinez-Velazquez et al. (2003) provides an excellent literature review on the subject. Given the conflicting evidence, it may not be advisable to base selection decisions on scrotal circumference with the intent of enhancing maternal reproduction.

As for other traits that may be related to reproductive function, Rogers et al. (2004) found that increased levels of milk EPD increased the risk of females being culled. This finding is consistent with ASA data showing an unfavorable (-.15) genetic correlation between milk and Stayability. Other ASA genetic correlations of note are -.26, .40, and -.19 between Stayability and mature weight, maternal calving ease and marbling, respectively. Based on these findings, we would expect females that are inherently lower milking, smaller at maturity, easier calving, and less marbled to stay in the herd longer; however, none of these relationships is strong enough to make a sizable impact on Stayability by selecting for them. Furthermore, other than mature weight, because of its strong relationship to early growth, determining the genetic level of a young heifer for these traits by simply observing them (which is what most commercial producers are limited to) is not possible. Therefore, a different tactic will be required if we wish to improve reproductive performance via selection. Namely, select for it directly — which, as we will point out, is not a trivial task.

Direct Selection

A well-entrenched view of both commercial and seedstock producers is that the “cows left standing” after culling on the components of reproduction (e.g., pregnancy status and calf loss) are genetically superior. By extension, it is presumed that a great deal of progress in reproduction is made through rigorous culling and the retention of heifers out of dams making it to advanced ages. Though this may seem like a reasonable eduction, it is generally not the case.

Unfortunately, little genetic headway is made by simply culling cows that do not achieve reproductive thresholds. This may seem counterintuitive. Why wouldn’t getting rid of the offenders improve your genetics for reproduction? The main reason lies in the fact that measures of reproduction tend to be lowly heritable (estimates typically run between 5-20%). And, with lowly heritable traits, an animal’s own performance is not a good indicator of its genetic level for the trait. Therefore, many open culls may be genetically above average or even superior for reproduction. By the same token, several cows kept because they are bred may be genetically inferior for it — certainly not an outcome that will yield much improvement.

So, how do we directly select for reproduction? Because a cow’s reproductive performance is expressed later in life, and even then it only provides a very cloudy picture of her genetic merit, are we relegated to making little to no selection progress for reproduction? Heck, no! We can clear the clouds with reproductive EPDs.

Though EPDs always provide the best estimate of an animal’s genetic merit, they are especially valuable when applied to low-heritability traits. This is because, when an animal’s own record is a poor indicator of its genetic makeup, gathering information
on its relatives is the only means we currently have of getting a clear picture of the animal.

You may ask yourself, “If an animal’s own performance does not tell us much, what can be gained by records on its relatives?” It is not that a single relative record brings much to the mix (obviously it adds even less than the animal’s own record); it is that there is strength in numbers — an animal can have many relatives with records, but only one record on itself. Through the use of EPDs, we utilize information on all of an animal’s relatives and, in doing so, chip away at the cloud with each record that flows in.

With a low-heritability trait expressed later in life, like reproductive function, the cloud clears slowly — but it will clear. In fact, if an animal has enough progeny records, we can see its genetic merit for reproduction as clear as a bell.

Fortunately, the seedstock industry now has EPDs that are, for the most part, direct measures of reproductive function: Stayability (STAY) and heifer pregnancy (HP). Researchers at CSU developed STAY (Snelling et al., 1995) and HP (Doyle et al., 2000) EPDs, and the RAAA implemented them into the association’s national cattle evaluation a few years later. Since its development, STAY has undergone several revisions. Most recently, the ASA released the industry’s first multi-breed STAY evaluation, which incorporated genomic data in a single-step random regression model.

Though STAY and HP have potential shortcomings (e.g., seedstock breeders’ culling practices are probably not in step with the commercial industry’s, and breed association culling records tend to be sketchy), they are the most effective selection tools available for improving reproductive function. What’s more, based on computer simulation efforts by retired USDA scientist M.D. MacNeil, the economic impact of Stayability when selecting a sire for female replacement is nearly twice that of the next closest trait, while the relative importance of heifer pregnancy is on par with the most important carcass or growth traits (personal communication) — so these reproductive EPDs certainly warrant a great deal of attention in the selection process.

Most commercial producers do not have the luxury of using STAY or HP EPDs to select replacement females; however, if you select sires with superior EPDs in these areas, the reproductive function of your cow herd is likely to improve over time. Given their relationship to Stayability, you may also gain some reproductive ground by selecting sires with lower milk, smaller mature size and better maternal calving ease EPDs. Another option to consider for commercial producers is the commercial option of the American Simmental’s Total Herd Enrollment. The commercial option predicts EPDs on commercial females and coupled with the Cow Herd DNA Roundup provides genomically enhanced EPDs to commercial females.


In closing, we must reiterate that crossbreeding needs to be at the center of any effort to improve the reproductive function of your cow herd. The dramatic impact of heterosis on reproductive performance is crystal clear — no herd should be without it! Though reproductive improvement through selection is possible, it is generally limited to utilizing reproductive EPDs when selecting your herd sires. By combining crossbreeding with the selection of superior sires you will position your enterprise to excel in the most vital area of beef cattle production — cow herd reproduction.

Literature Cited

Beckman, D. W., S. E. Speidel, B. W. Brigham, D. J. Garrick, and R. M. Enns. 2006. Genetic parameters for stayability and body condition score in beef females.

Proc. West. Sect. Am. Soc. An. Sci. 57:93-95. Cundiff, L. V., Nuiiez-Dorniguez, R., Dickerson, G. E., Gregory, K. E., and R.

M. Koch. 1992. Heterosis for lifetime production in Hereford, Angus, Shorthorn, and crossbred cows. Journal of Animal Science. 70:2397-2410.

Doyle, S. P., Golden, B. L., Green, R. D., and J. S. Brinks. 2000. Additive genetic parameter estimates for heifer pregnancy and subsequent reproduction in Angus females. Journal of Animal Science. 78:2091-2098.

Martinez-Velazquez G., K. E. Gregory, G. L. Bennett and L. D.

Van Vleck. 2003. Genetic relationships between scrotal circumference and female reproductive traits. Journal of Animal Science. 81:395-401.

Rogers, P. L., Gaskins, C. T., Johnson, K. A., and M. D. MacNeil. 2004. Evaluating longevity of composite beef females using survival analysis techniques. Journal of Animal Science.

Snelling, W. M, Golden, B. L., and R. M. Bourdon. 1995. Within-herd genetic analyses of stayability of beef females.

Journal of Animal Science. 73:993-1001.

By ASA's Genetic Evaluation Team      |         

Change can be a scary concept to some yet sought after by others. Many ASA members and International Genetic Solution (IGS) partners wonder about the changes on the horizon once BOLT is fully implemented. That change may be nerve racking but in reality, things should change. Why invest in new and improved methods if you get the same answers? Here are key changes to expect with the new genetic evaluation:

1. Movement of EPDs and reranking. EPDs will change especially in younger, lower accuracy cattle. Members should expect movement in lower accuracy cattle, as seen in the existing evaluations, because they may have new progeny data reported. Some cattle will move in a favorable direction while others will do the opposite. Keep in mind even if the EPDs get worse, the prediction of them is more accurate. With enough calves and phenotypes, the current evaluation would eventually arrive at a similar EPD as BOLT, it just would take longer or more information in the current system. With BOLT and the new genetic evaluation methodologies, we will have more accurate EPDs earlier in an animal’s life.

2. More accurate accuracy. This idea takes a little time to sink in. The accuracy reported for each EPD will be a directly calculated and thus closer to the “real” accuracy. The methods to solve accuracy directly are extremely difficult and take a lot of computer power. In the current evaluation, it is not possible to solve for accuracy directly so an approximation method is used to estimate accuracy for each EPD. There are inherent flaws with approximating the accuracy which until BOLT were just part of the evaluation. Now with BOLT, the accuracy reported with the EPD will be more reliable.

3. Reported accuracies will tend to be lower. Again, this is a little confusing at first and sounds like the opposite of what was just explained. The EPDs will be more accurate. The accuracy reported will be more accurate. Both statements are still true. However, one of the inherent flaws in the approximation methods used to find accuracy in the current evaluation, and in all evaluations not produced through BOLT, is they tend to bias the accuracies upward, especially  for younger animals. This was known for a long time, but there was no way to calculate the accuracies directly. With BOLT, having accuracy directly solved results in a more reliable accuracy but that accuracy will often be numerically lower than the current evaluation would predict. However, the new reported accuracies with BOLT should better represent the possible changes for the EPDs.     

4. DNA testing will have a larger impact. With the switch to BOLT, IGS will use Single Step genomic evaluation on all EPDs (currently using Single Step for Stayability EPDs).  Single Step uses the DNA markers, pedigree information, and phenotypic data simultaneously in the prediction of the EPDs.  Previously molecular breeding values (MBVs) were calculated from the genomic information and those MBVs were blended separately into the EPD prediction.  The Single Step method squeezes more information from the DNA markers than the previous approach allowed.  Also, there are biases inherent in the blending process that aren’t a problem with the Single Step approach.  Additionally, with Single Step, the genomic information will not only enhanced EPDs for the genotyped animal but also will be used in the EPD estimates of relatives.     

5. More frequent genetic evaluation runs. With the horse power behind BOLT, IGS can run genetic evaluations much more frequently than the current system allows.  This has many benefits. It allows members to get more immediate feedback after submitting their records.  If members miss a deadline, the next deadline for data won’t be far away.  It allows for more accurate EPDs throughout the year and faster incorporation of the genomics.  The down side is the EPDs put in print will quickly be outdated. 

Genetic evaluation is not stagnant. There will always be improvements as new research in animal breeding, genomics, and statistics advance.  BOLT is revolutionary in the innate flexibility, the computational power, and the statistical methods made possible using this software. Embrace the change to a new and improved genetic evaluation, it’s coming! 

Those of you who have submitted DNA samples for EPD incorporation have been receiving reports with your animals' EPDs before and after incorporation (MBV reports) for the last several years.  We have now discontinued MBV reports. 
The major reason for ceasing the reports is that, as we make our transition to high frequency (e.g., weekly) runs with our new genetic evaluation software (BOLT), these reports will no longer be relevant.  Because we will be adding all the new phenotypes and genotypes that have been submitted since the prior week, the changes between runs will be due to a myriad of reasons (e.g., new phenotypes on an animal or related animals, new DNA on an animal or related animals, etc.), rather than change being limited to DNA results on the animal.  Because of this, it won't be unusual for animals that have not had information submitted directly on them to change.   
For those of you who are interested in comparing the before and after EPDs for animals you submit DNA on, we suggest that you save your animals' EPDs prior to DNA submission.  This can be done by logging onto your Herdbook account and 1) clicking the "Herd Mgmt" tab, 2) selecting the group you would like EPDs on, 3) clicking on the "EPD Report" tab and 4) hitting the "Generate Report" tab.  This procedure will generate a spreadsheet of EPDs that you can download and save for comparing old with new EPDs.  Another option for obtaining animals' EPDs prior to blending is to email ASA's DNA department with the request.      
ASA Board of Trustees' Election.  
Paper Ballots Mailed - Electronic Ballots, email were sent November 15. 

Ballots are sent to adult members who have paid their annual service fee and registered or transferred at least one animal within the last two years. 
  • Paper ballots were mailed on Thursday. Deadline to vote: paper ballots must be received at the Chairman of the Teller's office on or before December 15.
    • Your paper ballot will have instructions for you to vote electronically if so desired. We encourage you to use the electronic option. By voting electronically you will receive a receipt to acknowledge that your vote has been received and there is no worry whether the postal service delivered your ballot on time. 
  • Electronic ballots, a notice from BigPulse will eMail on November 15. Deadline to vote:   midnight on December 15.

Jim Ligon, Cookeville, Tennessee: Click here for campaign letter.
Cliff Orley, Lebanon, Pennsylvania: Click here for campaign letter.
Fred Smith, Clayton, North Carolina: Click here for campaign letter.
Barry Wesner, Chalmers, Indiana: Click here for campaign letter.
North Central RegionClick here for Candidate Profiles.
Tom Hook, Tracy, Minnesota: Click here for campaign letter.
Claye Kaelberer, New Salem, North Dakota
South Central RegionClick here for Candidate Profiles.
John Griswold, Stillwater, Oklahoma: Click here for campaign letter.
Chuck Miller, Olean, Missouri: Click here for campaign letter.
Fred Schuetze, Granbury, Texas: Click here for campaign letter.
Jeff White, Cherokee, Oklahoma: Click here for campaign letter.
Western Region:
Mike Forman by acclamation. No write-in votes qualified.


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