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Merit Awards

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MERIT AWARD PROGRAM GUIDELINES

Together, the American Simmental Association and the American Simmental/Simbrah Foundation support this Merit Award Scholarship Program each year. Only one award can be achieved per year per applicant. The Bronze, Silver, and Gold Award Certificates are presented to the winners at the National Classic each year. However, the Silver & Gold scholarship money is not awarded until the recipient has registered and paid tuition to attend a postsecondary institution. At that time, the recipient must send proof of enrollment to the Chief Financial Officer at ASA, Linda Kesler ( This email address is being protected from spambots. You need JavaScript enabled to view it. ). A check will then be forwarded to the recipient

 

Merit Award Guidelines

 

1. BRONZE (Certificate and Bronze Lapel Pin) NEW- Deadline No Later than June 1st.

  • For ASA junior members
  • Recognizes achievement in Association sponsored Simmental/Simbrah activities
  • Application and two (2) letters of recommendation required
  • Selected by American Simmental Association with assistance from State Association.
  • Certificates will be presented at the National Classic each year.
  • Unlimited number of awards/state/year
    One-time award per individual. Completed application and recommendation letters and recent photo (head and shoulders) must be submitted to This email address is being protected from spambots. You need JavaScript enabled to view it. NO LATER THAN JUNE 1 st.

*Bronze award new guidelines will take place starting in 2020

Click to View Bronze Application!

2. SILVER (Certificate and $2,000 Scholarship)

  • For ASA junior members who are at least 16 years of age by January 1 of the year of application
  • Recognizes achievement in Association sponsored Simmental/Simbrah activities
  • Application and two (2) letters of recommendation required
  • Must have participated in at least 2 Regional or National Events (Regional and National Classics, IGS Summit, and SPC).
  • Selected from among previous Bronze Award winners by an ASA appointed committee.
  • Presented at National Classic
  • Maximum of 11 awards per year
  • One-time award per individual Completed application, recommendation letters and recent photo (head and shoulders) must be submitted to This email address is being protected from spambots. You need JavaScript enabled to view it. NO LATER THAN JUNE 1 st.
Click to View Silver Application!

3. GOLD (Certificate and $3,000 Scholarship)

  • For ASA junior members who are at least 16 years of age by January 1 of the year of application
  • Recognizes achievement in Association sponsored Simmental/Simbrah activities
  • Application and 3 letters of recommendation required (including one from a State Senior Association Officer or if no State Association a letter from a Senior State member).
  • Must have participated in at least 3 Regional or National Events (Regional and National Classics, IGS Summit, and SCP).
  • Selected from among previous Silver Award winners by an appointed ASA committee.
  • Presented at National Classic
  • Maximum of five awards per year
  • One-time award per individual Completed application, recommendation letters and recent photo (head and shoulders) must be submitted to This email address is being protected from spambots. You need JavaScript enabled to view it. NO LATER THAN JUNE 1 st.
Click to View Gold Application!
Completed application, recommendation letters and recent photo (head & shoulders) must be submitted (postmarked) to the ASA office NO LATER THAN JUNE 1.
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Press Releases - ASA News

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May 2021

SIMMENTAL AND BISON GENOMES RELEASED

 Bozeman, MT — The first reference-quality genome assemblies for the iconic North American Yellowstone bison and the Simmental cattle breed have been published in the Journal of Heredity. Animal genome assemblies provide genetic “blueprints” for how they develop and pass on information to their offspring.

The bison assembly will be used in conservation efforts to maintain genetic diversity, and to study bison evolution by comparing DNA obtained from fossil specimens sampled from permafrost in the Arctic Circle. The Simmental cattle assembly will contribute to an international effort to survey existing cattle breeds around the world to preserve their genetic diversity and identify variation useful for improving beef and dairy traits in different environments. The two genomes are released together because of the unusual way they were created: a single individual hybrid animal from a bison bull and a Simmental cow. Each cell of the hybrid animal contained one copy of the bison and one copy of the Simmental cattle genome. 

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International Genetic Solutions Broadcast

 

 

 

2021 Golden Book Awards Recipients Recognized

George “Parke” and Nina Vehslage, Kevin and Lynette Thompson, and Tom and Shannon Hook.

Finding Consistency in Simmental

Cooper Ranches, located on the productive rangeland of Throckmorton County, Texas, has found success using Simmental genetics to increase efficiency and add consistency to their cow herd. Cooper Ranch females are expected to perform without coaxing and wean a calf that not only makes a profit for the ranch but also goes on to excel for the feeder. Glenn Cooper, the third generation on the operation, and his son, Wes, the fourth generation, manage the business. Rick Ward came on as ranch manager in 2004, bringing with him the Simmental breed, and has since worked with the family to improve the commercial cow herd through genetic selection, and to create females that work with their environment. Ward’s cow sense combined with the Cooper Ranch management philosophy has made for a successful combination.

Read the article

 


The Benefit of Sound Decisions

You care about soundness in your cow herd, right? Of course, you do; it is a trait many in the beef industry today care deeply about. Whether it is in the form of bull returns and guarantees, early culling of replacement heifers and developing bulls, or using an AI sire sight unseen, soundness plays a critical role in your reputation and the success of your enterprise.

Soundness by itself is a complex trait controlled by many skeletal and environmental factors. Fortunately, we know soundness traits such as the curvature of claws, the angle of the hoof, or even the angularity of the hock and skeleton can be improved through genetic selection and appropriate culling practices. The heritability of these traits range from 0.10 to 0.40, meaning approximately 10% to 40% of the variation for soundness traits in our cattle populations can be directly associated with genetics.

Read more here:  https://bit.ly/3gMBLnk


 

Innovation Meets Application

A lot has changed at the American Simmental Association in the last five years. Five years ago, we moved into our new headquarters. We were gearing up for our 50th anniversary and preparing to write the history book. We were launching the International Genetic Solutions (IGS) Feeder Profit Calculator, and anticipating this new way to encompass management and genetics to estimate the relative value of a set of feeder calves. The genetic evaluation used the previous Cornell software and older models, including a two-step blending process for genomic information, and three times a year a fresh evaluation was released. Now we are settled in the headquarters, the IGS FPC has years of growth and success under its belt, and we are cranking out weekly genetic evaluations using improved methods: single-step genomics and the BOLT software system.  Read more here.

 


 

 

 

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Dr. Wade Shafer addressing the World Simmental Fleckvieh Federation Congress at Ft Worth Texas. Photo credit: Fred Schuetze.  

    View the presentation in two segments:  View part one.           View part two.

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Go to www.simmental.org/book to order your copy.

Excerpt from the Foreword written by Dr. John Pollak.                             

"The reader of this book will gain knowledge of the history of the Simmental breed, the Association and the people behind the breed. Embracing the story of Simmental in the United States beef industry may help create a sense of accomplishment and relevance that current membership can take pride in as they carry the banner of the breed forward. But there is also value in studying history. Generations of cattle and of the ranchers and farmers who produced those cattle have come and gone over the past 50 years. They faced cyclical cattle markets, environmental and social issues, and challenges that come from moving an organization and a diverse membership forward. They made mistakes and at times got off course, yet learning from these miscues prepares today's leaders for making future decisions. Bold decisions were made that created positive change and should instill confidence in future leadership as they seek to be innovative in new endeavors. The constant threat in the past is that they continued to adhere to the core principle of data collection and utilization. Hence, I encourage all who read this book to keep in mind how knowledge of this history will help in addressing current aspirations for producing better cattle while addressing new challenges that face not just Simmental but the entire cattle industry".  

 



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Due to objective genetic predictions such as EPDs (expected progeny differences) and indexes, the cattle industry has made tremendous progress in production and efficiency. However, as the models that produce the predictions become more sophisticated and producers understand less of the mathematics behind them, some people are turning off from the technology.

This is a problem because, although calculation of modern genetic predictions has become complicated, the precision and reliability of the EPDs have likewise improved.

An EPD is defined as the difference in expected performance of future progeny of an individual, compared with expected performance at some base point for the population. EPDs are estimated from phenotypic and genomic merit of an individual and all its relatives. They are generally reported in units of measurement for the trait (e.g., lb., cm., etc.). EPDs are best used for comparing the relative genetic transmission differences to progeny between individuals.

 

What it boils down to is EPDs let a producer sort out genetic differences between animals, eliminating the “noise” of the environment. Some producers think they can do this better with their eyes or just a simple set of scales. This has been soundly proven wrong. The most glaring example of this occurred in Red Angus.

The breed was founded based on performance principles in 1954 with performance reporting as a requirement for registration from the very beginning. Although all Red Angus breeders had weights and measures from the beginning, the breed made no genetic progress for over 20 years. That all changed when it began converting this data into information in the form of EPDs. Since the breed started calculating EPDs, the genetic trend for traits measured has improved linearly.

Red Angus also studied the phenotypes for various traits and how they compared to the genetic predictions of the population. An example is weaning weight EPDs, which have been increasing linearly. This lines up perfectly with the breed’s adjusted weaning weights, which have improved at the same rate as the EPDs. EPDs have also allowed the breed to beat genetic antagonisms like increasing weaning weights without increasing birth weight.

Indexes are an even more powerful tool for genetic improvement. Certified Angus Beef studied when cows were flushed to either low or high $B ($Beef terminal index) bulls and all progeny were fed out and harvested. The progeny out of the high $B bulls were significantly better for all input traits into the index including weight per day of age, age at harvest, carcass weight, quality grade, and yield grade. The progeny of the high $B sires had $48.65 lower feedlot production costs and produced carcasses with $166.82 more value for a total financial benefit of $215.47.

The prediction models have also been proven to be unbiased. Cornell University did a retrospective study of the American Simmental Association’s cattle by going back and adding two years of data at a time. They then observed the differences in how cattle’s genetic predictions changed as they went from pedigree estimates through being proven sires. Animals changed up and down as the possible change chart indicated they would, as more information was added to the genetic predictions. They equally moved either up or down demonstrating no bias in the model producing the genetic predictions. If the model was biased, the predictions would tend to move in only one direction.

The basic input into genetic predictions is contemporary group deviations, and the models assume there is no environment by genotype interaction. Cornell also studied this in the Simmental population, and the assumption was validated as true.

That the models have been improving over time only makes the genetic predictions and indexes even that much more valuable.

Genetic predictions using field data were first introduced to the industry with the 1971 Simmental Sire Summary, but those early models were fraught with problems. The early models were based on sires and all dams were assumed to have equal genetic merit, which of course is not correct.

Early models also didn’t account for mating bias. The most common case of mating bias occurs when high-priced artificial insemination sires are only mated to producers’ top cows, so accounting for this bias is important. Over time, these and many more problems have been eliminated. However, with these improvements, the models have become ever more complicated and more of a challenge for the layperson to understand how they work.

 

This brings us to today’s modern genomic models, which are light years better than the old models, but the complicated statistics that go into the genetic predictions are admittedly hard to understand. The goal of the genetic predictions has always been to sort out what is genetic—thus will be transmitted to progeny—from what is due to environment. Marker-assisted selection is the ultimate way to determine genetic value because, by definition, genomics are not influenced by environment.

Adding genomics to traditional information that goes into genetic predictions—like contemporary group deviations, heritability, and trait correlations—all adds up to predictions that are more precise and reliable. They do a much better job of establishing genetic relationship between animals, as well as identifying markers associated with causative genes, all to improve accuracy of genetic predictions.

The whole goal to animal breeding is to improve cattle genetically. This means different things to different people—some are looking to optimize genetics to their environments while others are looking to maximize the genetic potential for traits.

Whatever a producer’s goal, EPDs and indexes are the best way to achieve it. Today’s prediction models do an unprecedented job of removing all the noise from EPDs and indexes, allowing producers to make the most informed genetic selection decisions possible.

It has been demonstrated time and again that visual evaluation and simple weights and measures are inferior substitutes for modern genetic prediction. Those who ignore objective genetic predictions do so at the long-term peril of their business’ ability to compete.

Performance pioneer Don Vaniman summed it up nicely in 1978 when he wrote, “Is it those who feel cattle that look good must perform, or those who accept that animals that perform look good?” — Dr. Bob Hough, WLJ correspondent

Dr. Bob Hough is the retired executive vice president of the Red Angus Association of America and a freelance writer.

 

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International Genetic Solutions (IGS) is an unprecedented collaboration between progressive breed associations fervently committed to enhancing commercial profitability.  The collaboration has yielded the world’s largest genetic evaluation of beef cattle with over 17 million animals and 120,000+ genotypes.

In keeping with our commitment to the cattle industry, IGS is pleased to announce the IGS Multi-breed Genetic Evaluation powered by BOLT.  The new genetic evaluation provides more predictive EPDs, better use of genomics, more accurate accuracy reported with EPDs, all with weekly evaluations.  The announcement ushers in a new era in genetic evaluation — an era made possible by a genetic evaluation system dubbed BOLT (Biometric Open Language Tools, owned by Theta Solutions, LLC).  

The concept for BOLT started in 2014 as a research endeavor between the American Simmental Association and Drs. Bruce Golden and Dorian Garrick.  BOLT is, quite simply, the most revolutionary and powerful genetic evaluation system in existence. Its power allows IGS to leverage genetic evaluation methodology that was once thought to be untenable on large databases — methodology that significantly improves genetic prediction.

In December 2016, IGS published a multi-breed stayability, the industry’s first EPD using BOLT and the first single-step methodology applied to a large beef cattle database.  Since that time, the IGS genetic evaluation team has worked toward fully implementing BOLT with an automated system that enables weekly evaluations for an entire suite of EPDs.  As of May 5th, 2018, ASA is the first of the IGS partners to publish a full suite of EPDs generated by the IGS Multi-breed Genetic Evaluation powered by BOLT.  Each IGS partner has complete autonomy to determine the release date that best fits their organization.  As such, the release of EPDs by the other IGS partners is likely to be staggered over the next several weeks.  As always, we look forward to your questions and comments about what you see.

Here are the notable changes in the evaluation:

Movement of EPDs and reranking. EPDs and indexes will change. These changes will be more dramatic for younger, lower accuracy cattle.  The IGS team has tested the changes and proven the new EPDs result in superior predictions of genetic merit.

Shrinking of EPD range.  You will notice a reduction in the range of EPDs for most traits.  The IGS evaluation team tested the statistical veracity of the reduction and it has proven to be in line with expectations based on the genetic variation in the population.

Improved use of genomics.  With the switch to the BOLT software, IGS will use single-step genomic evaluation on all EPDs. Single-step uses DNA markers, pedigree information, and phenotypic data simultaneously in the prediction of EPDs. Previously, molecular breeding values (MBVs) were calculated from the genomic information and those MBVs were blended in a separate procedure into the EPD predictions. The single-step method squeezes more information from the DNA markers than the previous approach allowed. Additionally, with single-step, the genomic information will not only enhance each EPD for the genotyped animals but also will be used in the EPD estimates of relatives.

It is well established that DNA markers vary greatly in their effect on traits — ranging from large to virtually no impact. To leverage this biological fact in a statistically advantageous manner, the BOLT single-step method only uses markers that have a meaningful impact on the traits of interest, while ignoring those that have little to no effect. Research has shown that by using this approach, BOLT reduces statistical “noise” and thereby increases the accuracy of the EPD prediction compared to other single-step methods.

It is important to note, continued collection of phenotypic records remains a vital part of genetic predictions.  DNA testing will never replace the need to record and submit phenotypes.

More accurate accuracy.  In the previous IGS evaluation platform and all others in existence other than BOLT, the calculation of the accuracy associated with each EPD is achieved through “approximation” methods. It has long been known these methods are a less than optimal approach to the calculation of accuracy — tending to overestimate accuracy. By employing unique computing strategies that leverage both software and hardware efficiencies, BOLT performs what was previously unthinkable — utilizing a sampling methodology to calculate what is essentially true accuracy. Unlike approximated accuracies, BOLT-derived accuracies will result in predicted movements associated with possible change holding true over time. This is not the case with the previous IGS software or any other system currently in existence.

While the IGS evaluation team and partners are excited to release this new chapter in genetic evaluation, the new genetic evaluation system will only realize its true potential if the selection is made using its EPD and index values.  Hands down, there is no better (more accurate) way to select for quantitative traits than an EPD. Economic indexes predict net profit by weighing the EPD for economically relevant traits coupled with economic estimates. To compete with other protein sources, it is imperative that the beef industry adopts the best science and technology to make better breeding selection decisions.             

Please note, each IGS breed association has the latitude to publish the BOLT generated EPDs when the timing is right for their association.  

 

For more information about the IGS Multi-breed Genetic Evaluation powered by BOLT, go to www.internationalgeneticsolutions.com.   

What to expect with the new IGS Multi-breed Genetic Evaluation powered by BOLT

Frequently Asked Questions

Validation of the new EPDs

Value of DNA tests

The IGS Multi-breed Stayability 

 

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Commercial Programs

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The commercial programs offered by the American Simmental Association (ASA) are an effort to provide genetic tools to the largest sector of the beef industry; the commercial cattlemen.  These efforts are supported through multiple ASA programs and the world’s most comprehensive beef genetic database.  The three pillars to ASA Commercial Programs are the:  Total Herd Enrollment — Commercial option (THE-CM), Cowherd DNA Roundup (CHR), and the IGS Feeder Profit CalculatorTM (FPC). These three programs allow you to maximize the genetic awareness surrounding your program and to make better management and selection decisions. Each of these programs is designed to offer you assistance at three key management moments in your production system; Breeding, Heifer Selection, and Weaning. 
 
Get Commercial Cowherd EPDs & Indexes through the Total Herd Enrollment cow inventory-based program.

ASA's Total Herd Enrollment - Commercial Option is designed specifically for serious commercial beef operations.  Any breed type, free Active Herd management software, and only $500/year - regardless of herd size.

The THE-CM is the foundation for these programs and allows you to fully capitalize on the true genetic awareness of your cowherd.  This is a herd reporting program that helps isolate the known genetic potential of every female you own.  The industry’s best metric for understanding genetic merit on individual animals is through an expected progeny difference (EPD).  Simply put, an EPD informs you of the difference in production value for a given trait compared to the average animal.  These are all calculated through pedigree relationships and performance records — and genomics if desired. Selection indexes take that one step further by combining multiple economically relevant EPDs along with industry costs and thresholds into a prediction model.  Your seedstock provider undoubtedly uses EPDs and selection indexes to make mating decisions, why shouldn’t you have the same technology? 
  
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THE - Commercial

Cow Herd DNA Roundup (CHR)  is a research project with GeneSeek

The CHR is your opportunity to push the accelerator on female genetic awareness.  Every cattleman understands who their best-producing cow is, but do they know right away which replacement heifer will fill that role?  The field of genomics allows us to gain a better understanding of a young heifer’s genetic potential even before she starts producing.  This technology utilizes known regions on the bovine genome that impact specific economically relevant traits.  For example, longevity in cattle is known once they've been in production for almost a generation, but you would hope to know that information before you invested time and money in replacements.  Through genomics, we can use known genetic markers to give us an indication of whether a female may last in the herd longer (or shorter) than others.  The CHR will provide you with years of information before you have to invest years of time. 

Find out more now.

Cow Herd DNA Roundup

 

International Genetic Solutions Feeder Profit Calculator (FPC)
 
Capitalizing on novel technology usually requires a tremendous learning curve and a major outlay of dollars.  Not this time! The IGS Feeder Profit Calculator is unique. It will offer a level of genetic awareness of crossbred feeder calves that have not been previously possible in the beef business.  The IGS science team, the IGS partner associations, and the world’s largest beef genetic evaluation database allow the IGS FPC to be delivered at no cost to producers. That is correct. No Cost!
 
 While the other two programs are focused around your cowherd, the FPC is centered around where you make ends meet.  You’ve invested a lot of time and money into not only your cowherd but also your bull battery because you know role genetics plays in the end product.  You’ve also invested in your management protocols to ensure the feeder calves you raise will stay healthy and perform in the feedlot.  These investments help you stay profitable and build a more valuable feeder calf, but are your buyers aware of your commitment?  The FPC is a third-party view of the profit potential on your calf crop through the understanding of genetics, health and management.  Your buyers want low risk, high potential calves with earning potential.  You want to highlight that your calves fit their need.  As opposed to traditional marketing slogans and empty statements lets provide true awareness.  We can Know or Guess.  Choose Know. Follow 
 
 
 

FPC, What is It?

http://simmental.org/site/index.php/commercial-services/carcass-merit-programs-cmp
Would you like to get paid to use some of the most promising herd sire prospects in the industry?  Consider becoming a Carcass Merit Program(CMP) Cooperator

As a Carcass Merit Program cooperator herd, ASA tests a number of young, unproven, high prospect sires through artificial insemination on the cattle within the cooperator’s herd. The purpose of this is to obtain data on the progeny of the sires in order to improve accuracy on the sires EPD’s and adjust the EPD’s according to how the progeny perform. This allows bull owners and genetic companies to identify the high prospect sires and high-quality genetics early on in the sire’s life. Also, by improving the accuracy of the EPD’s, the sires become more predictable and marketable.

 

Find out more now.

Carcass Merit Program

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The new genetic evaluation, Multi-breed Genetic Evaluation powered by BOLT, offers groundbreaking advances in the prediction of EPDs for the IGS group. Here are some frequently asked questions and answers to help you better understand Multi-breed Single-step.

1. What are the key features of the Multi-breed Genetic Evaluation powered by BOLT?

• Faster and more automated system allowing for frequent genetic evaluations.

• Improved use of genomic data.

• Improved methodology for predictions of all traits.

• More accurate accuracy.

• More flexibility to add additional traits or change methods for future improvements.

 2. How is ASA’s single-step approach different from blending for genomic evaluation?

The blending approach uses separate steps to calculate genomically enhanced EPDs.  This approach requires two steps.  The first step is to estimate the effects of DNA markers through a process called “training” or “calibration”. These effects are then used to calculate molecular breeding values (MBVs) on genotyped animals.  The MBVs are then combined with traditionally calculated EPDs to enhance the accuracy of the traditionally calculated EPDs.  The blending process is only performed on genotyped animals. 

Befitting its name, the single-step approach calculates genomically enhanced EPDs in one step — using DNA, pedigree information, and phenotypes simultaneously. As a result, the DNA information not only improves the accuracy of prediction on genotyped animals, but also on the relatives and contemporaries of the genotyped animals.  In a sense, all animals are genomically enhanced under the single-step approach.

There are also issues inherent in the blending process that are solved with single-step. Similar to the fact that only reporting phenotypes on a selected group of animals in your herd can lead to less informative (and more biased) EPDs with traditional evaluation, problems can exist with blending as it only involves genotyped animals — and genotyped animals tend to be highly selected. However, because single-step includes information from non-genotyped as well as genotyped animals, the issues are corrected.

3. How is the Multi-breed Genetic Evaluation powered by BOLT different than other single-step models used in other genetic evaluations?

It is well established that DNA markers vary greatly in their effect on traits — ranging from a large to no impact. To leverage this biological fact in a statistically advantageous manner, the BOLT single-step method only utilizes markers that have a meaningful impact on the traits of interest, while ignoring those that have little to no effect. By using this approach, BOLT reduces the statistical “noise” and thereby increases the accuracy of prediction. By circumventing the “noise,” BOLT-generated EPDs tend to be more accurate than EPDs generated by organizations that are relegated to using all markers in their single-step evaluation.

4. How many DNA markers are being used?

The Multi-breed Genetic Evaluation powered by BOLT uses a subset of weighted markers based on a research study performed by Drs. Mahdi Saatchi and Dorian Garrick, while they were scientists at Iowa State University. Drs. Saatchi and Garrick first used the 50,000 markers to determine a subset of weighted markers that are highly associated with economically relevant traits in beef cattle with consistent effects across breeds. Because the IGS evaluation is for multiple breeds, it is important to remove markers with inconsistent effects or no effects in different breeds.

The Saatchi and Garrick research also found that utilizing genotypes on animals of multiple breeds consistently increased the accuracy of prediction within a particular breed when compared to limiting DNA utilization to only animals of a particular breed.

 5. Why are some traits influenced by markers and others are not?

The genetic architectures of various traits are different. Some are controlled by few genes with large effects and some are controlled by many small effects genes. In the current DNA profilers, there are some markers with high correlations with corresponding genes for some traits and low correlations with others. That’s why we see the different DNA added values for different traits. It is hard to change the genetic architecture of a trait. But, new DNA profilers or future technologies may help to improve the value of DNA information for such traits.   Furthermore, some maternal traits, like Maternal Calving Ease and Milk, are difficult to predict with genomics because there are so few females genotyped. Increasing the number of cows and heifers genotyped will improve the ability to use genomics to predict maternal traits.
 

6. Will genomic testing replace the need to submit phenotype records?

No, reporting actual records is critical. The value of genomic predictions increases as the amount of phenotypic information increases. Furthermore, at this point, animals cannot achieve high accuracy with genomic data alone. High accuracy EPDs are only achievable by collecting many phenotypic records on offspring.

7. How do we know predictions via BOLT are better than the previous system (Cornell software)?

The IGS evaluation team has conducted a series of validations to compare the BOLT system to the Cornell system. BOLT-derived EPDs had higher correlations to birth, weaning and yearling weights (0.34, 0.29, and 0.26, respectively) than the Cornell derived EPDs (0.27, 0.19, and 0.20, respectively). Furthermore, there was a larger difference in average progeny performance (birth, weaning, and yearling) of the top 1% compared to the bottom 1% animals in the BOLT derived EPDs compared to the Cornell calculated EPDs. Both validations suggest the BOLT EPDs align better with the actual phenotypes than the Cornell EPDs.

8. Why do some animals have substantial changes in their indexes?

Though the correlations between the previous (Cornell derived) EPDs/indexes and the BOLT derived EPDs/indexes are relatively strong, there will be some animals that happen to move in a consistently favorable or unfavorable direction in a number of EPDs. Because indexes are comprised of several EPDs, even though movement in individual EPDs may be considered small, movement in the same direction across EPDs may yield sizable movements in the index value. This is particularly true for animals that have consistent movement in traits that are drivers of a particular index. Though in a large population like ours we would expect to see several animals with substantial index movement, these animals will be the exception to the rule.

9. How does BOLT improve our calculation of accuracy?

“True” accuracy can be thought of as the gold standard of accuracy. It is statistically unbiased, and therefore the ultimate measure of accuracy. True accuracy is the accuracy resulting from direct calculation. Unfortunately, even with the massively powerful computing capacity now in existence, the direct calculation of accuracy is not possible on datasets the size of ours. Because we cannot calculate accuracy directly, other approaches to accuracy calculation have been developed.

In our Cornell evaluation platform and all others in existence other than BOLT, the calculation of the accuracy associated with each EPD is achieved through “approximation” methods. It has long been known these methods are a very crude approach to the calculation of accuracy — tending to overestimate accuracy.

Another approach to the calculation of accuracy is via “sampling” methodology. Sampling is shown to be a more accurate predictor of accuracy. In fact, the results of this method were reported to be virtually identical to true accuracy. Unfortunately, due to its computationally intense nature, sampling has long been thought an infeasible approach to the calculation of accuracy on large databases.

BOLT, however, has changed the landscape in this area. By employing unique computing strategies that leverage both software and hardware efficiencies, BOLT performs what was previously unthinkable — utilizing a sampling methodology to calculate what is essentially true accuracy.

Because BOLT can calculate true accuracy, we can put more confidence in our accuracy metrics. Put another way, unlike with approximation, we can count on the predicted movements associated with possible change holding true over time. This was not the case with our Cornell system nor any other system in existence.

10. Why do the carcass EPDs generally have an increase in accuracy with BOLT while this is not a case for other traits?

You will notice that while the Multi-breed Genetic Evaluation powered by BOLT will generally produce lower accuracies than the Cornell system for growth and calving ease traits, the opposite is true for carcass traits.

One reason behind the differing accuracy outcomes is several years ago ASA staff developed a way to temper inflated accuracies in the Cornell carcass evaluation. Unfortunately, this was not possible for growth traits.

Another reason is that the Cornell system only used the carcass and its corresponding ultrasound trait (e.g., marbling score and IMF) to predict carcass EPDs, while records on several additional correlated traits are leveraged with the BOLT system.

A new feature of the BOLT evaluation is a new approach to the calculation of Carcass Weight EPDs. Due to limitations, our previous Carcass Weight EPDs did not incorporate actual carcass weights. They were predicted through an index of birth, weaning, and yearling weights. Besides using prior growth records (weaning, post weaning), the new approach also includes actual carcass weights. This feature will undoubtedly lead to a more accurate prediction of carcass weight.

11. What can I do to improve the predictions on my herd?

Whole Herd Reporting — If you haven’t already, you should consider enrolling your entire herd with a breed association total herd reporting program as it offers the most complete picture of the genetics involved in your herd.

Proper contemporary groups — It is important for the genetic evaluation that you group, to the best of your ability, animals that were treated uniformly. Proper reporting of contemporary groups ensures better predictions for all.         

Take data collection and reporting seriously — Phenotypes are the fuel that drives the genetic evaluation.  Take pride in collecting accurate data. If possible, try to collect additional phenotypes like mature cow weight, cow body condition score, feed intake, and carcass data.           

Use genomics — DNA testing adds more information to what we know about an animal.  The more genotypes we collect, the better we can predict DNA-tested animals in the future. Also, the more relatives genotyped, the better we can predict their relatives in future generations. Therefore, to ensure your bloodlines are well represented in the predictions, genotype your animals. 

Visit www.internationalgeneticsolutions.com for more information.

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