IGS Around the Web

IGS Around the Web (13)

Staying profitable year in and year out in the farming and ranching business is not easily achieved. Perhaps there is no bigger case of this than with dairy farmers who have struggled with low fluid milk prices for years.

However, dairy farmers are realizing that their approximately 5 million breeding-age heifers and 9 million cows can generate profit from more than just milk. One of the most underdeveloped potential profit centers is the production of specialized dairy crossed steer calves and excess heifers that can be profitably fed and marketed by feedyards. With that in mind, there has been an exponential increase in the use of beef semen in dairy herds to produce more desirable feeder cattle.

Affordable genomic tests that give commercial dairy producers a look at their heifers’ genetic potential has helped make this happen. Dairy farmers can now determine if a heifer entering the herd has the genetics to produce outstanding replacement dairy females or would be better used to breed beef bulls to produce value-added feeder cattle.

Sexed semen is another piece of the puzzle that allows the top dairy heifers and cows to have only heifer calves, decreasing the number of females needed to supply a dairy operation with replacements. Statistics from the National Association of Animal Breeders (NAAB) show how popular it has become to breed the bottom-end dairy cows to beef bulls, with a 59 percent increase in beef semen last year alone. To be sure, the majority of this increased semen in going into dairy cows and not beef cows.

However, the use of beef semen in dairy cows has often involved little thought in terms of selecting the right bulls, so dairy producers need a better strategy to make this system sustainable.

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Wednesday, 20 June 2018 04:52

Management Perspectives: No hype: EPDs work

Written by

Dr. Bob Hough, WLJ correspondent

As EPDs and other breeding tools get more complicated, some ranchers have returned to the “tradition” of just looking at animals to determine their genetic worth. DON’T. EPDs work.            

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 the accuracy of genetic predictions.

The whole goal of 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.


Thursday, 08 March 2018 11:57

The IGS Feeder Profit Calculator (FPC)

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Seedstock and commercial producers share their firsthand experience with ASA’s new and innovative feeder calf value prediction.       |

By Emme Troendle and Lilly Platts        |

What is it?  Historically, the primary limitation of valuing feeder calves has been accurately gauging the profit potential of the largest genetic group within the industry — the crossbred calf. International Genetic Solutions (IGS), a collaborative effort of numerous breed associations, has developed a tool to assist in determining feeder calf value, called the Feeder Profit CalculatorTM (FPC).  

“The FPC offers an objective way of describing the genetic merit on a set of calves,” comments John Irvine of Irvine Ranch, owner and manager of a 225-head operation of registered Simmental located outside of Manhattan, Kansas. “To date, there has not been a more accurate way to quantify calf value. Many producers try to do the right things in terms of management such as weaning and using sound vaccination practices, to prepare calves for the challenges they will face in the feedlot. The FPC offers a common language to bridge communication between those selling and purchasing feeder cattle.”

The FPC incorporates genetic knowledge of mainstream sires, regardless of breed, preconditioning and vaccination information, and weaning management and responsible health programs to evaluate the value on a set of calves. “As this tool gains traction and becomes commonplace for cattle buyers to use, producers will be better rewarded for their efforts, in respect to their investments in better genetics as well as improved efforts in preconditioning calves to offer a better product for the next link in the industry chain,” says Mike Forman, owner and operator of Trinity Farms, a 700-head ranch of registered SimAngusTM cows in Ellensburg, WA.

The finished product is a certificate that highlights the genetic and management predictions on calves along with certain carcass and growth traits. All producer-provided information is highlighted on the official certificate, and an additional page is included, indicating all the genetic information provided. “Our hope is that with a certificate in hand, our customers who are already making investments in quality genetics, making further commitments to provide better health and management of their calves, will be rewarded,” Forman continues.

As seedstock producers, Irvine and Forman share their insight on the FPC:

Q: Why is having this information valuable to those supplying feeder calves?

Forman: FPC is a well-designed third-party validation that helps to provide structured reasoning to establish value relative to the average feeder calf price dependent upon the producer inputs in regard to genetic selection, health and management. It helps to reinforce what our position has been for years – producers have three things to sell – genetics, health and the management the cattle are under. 

 Irvine: The FPC provides a great metric to gauge value for producers that have routinely invested in quality genetics as well as practice good management. Additionally, by scoring their calves, FPC provides the cow-calf producer a benchmark to make measurable progress moving forward, whether it be on the management or genetics side. 


Q: What would you say to someone hesitant about using the Feeder Profit Calculator?

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Tuesday, 24 January 2017 12:04

Upping the Accuracy With Single-step Genetic Evaluation

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Article by Wes Ishmael   |   Beef Magazine

As the art and science of genomics becomes more accurate, cow-calf producers benefit. While cow-calf producers won’t directly participate in genomic evaluation now that single-step evaluation is a reality, they’ll be able to buy bulls with more accurate and reliable EPDs from their seedstock suppliers.


“If you’re a breeder doing a lot of genotyping and phenotyping — you’re measuring all of the data in all of the traits — single-step genomic evaluation lets you leverage the accuracy from that immediately,” says Stephen Miller, director of genetic research for Angus Genetics Inc. (AGI). “I think that’s a strong component of why breeders may become even more active in genotyping than they have been so far.”

Miller is describing what he believes will be one of the results of the single-step beef cattle genetic evaluation currently being refined and tested by organizations with massive databases, including AGI and International Genetic Solutions (IGS), which is a collaboration of 12 breed associations.

For the American Angus Association (AAA), AGI conducts a single-breed genetic evaluation. AAA’s registry grows by about 300,000 annually. The AAA database for genetic evaluation includes weaning weights for 8.3 million animals and birth weights for 7.6 million, among a host of various phenotypes.

Conversely, Mahdi Saatchi, lead genomicist at IGS, explains the organization’s database includes more than 16 million animals — the largest multibreed beef cattle genetic evaluation system in the world — adding more than 400,000 each year.

Single-step genetic evaluation is meant to replace what is currently and usually a multistep process used to incorporate genomic information into the calculation of expected progeny differences (EPDs).

As Alison Van Eenennaam, University of California, Davis, Extension beef geneticist, explains in the report titled “Recent Developments in Genetic Evalua-tions and Genomic Testing” (available at ebeef.org), “Currently, the incorporation of genomic information into genetic evaluations is statistically complex, and often involves a multistep approach that requires 1) traditional genetic evaluation with an animal model, 2) estimation of the marker effects and development of the prediction equation, and 3) a blending of those two pieces of information using a variety of approaches to develop a genome-enhanced EPD [GE-EPD].”

With this multistep approach, GE-EPDs are available only for genotyped animals. Including their information in genetic evaluation requires what’s termed a “training population” used to recalibrate prediction equations periodically. Suffice it to say, this is an added step that requires lots of time.

A shortcoming of the multistep approach is that selection bias can creep into the evaluation, since animals superior in genetic merit are the most likely ones to be genotyped. Saatchi adds that weighting estimates for the information included can be a primary source of biases.

Keep in mind that EPDs were already the gold standard of genetic prediction, even before genomic data was included in genetic evaluation.

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Tuesday, 14 June 2016 15:58

The IGS Implementation of BOLT

Written by

Bruce Golden
Theta Solutions

Over the last 50 years we have had evolution of the statistical methods used to calculate genetic predictions, EPDs, for livestock. What drove the evolution of these methods? Knowledge of statistical models? New methods? Data? Enabling computer technology? Golden states that he believes the drive for better models has been a desire to increase the accuracy of prediction.

Golden and Garrick had written grants to write genetic prediction software in the past. This avenue appears to have dried up, so they decided to start a company, Theta Solutions, in order to fund the development of genetic prediction. The latest genetic prediction runs contained 46,000 animals with genomic data.

Theta Solutions uses graphical processing units, originally built for video gaming, to have a high performance computer at a relatively low cost. The BOLT software focuses on custom turnkey analyses, once the system is set up all one needs to do is feed it data.

Using non-GPU computing, Golden can solve 51 million equations in 1649 seconds. The fastest GPU implementation took 78 seconds.

Why do we use a Bayesian sampler for solving mixed models?

  • No accuracy approximation bias 
  • Can get PE covariance
  • Can apply marker selection methods
  • Can include prior information

With traditional methods, it took 23 seconds per sample, with new implementation can do a sample in 2 seconds. (Gibbs sampling is kind of like turning a statistical crank over and over to solve very complex equations, each sample is one turn of the crank.) They also parallelized the sampling, further speeding up the process. This parallelized processing is like working cattle with 100s of chutes rather than a single cute.

There are three ways to combine genomics with traditional EPDs,

  • blending Genomic BLUP (combine pedigree prediction with genomic prediction, two separate analyses)
  • single-step Genomic BLUP (combine pedigree relationships and genomic relationships, one analysis)
  • hybrid model (single step with marker effects)

Single-step genomic models outperform traditional EPDs. But, the hybrid model outperforms both models, especially for unproven animals. The purpose of the hybrid model is to squeeze more information out of the data.

Currently looking at a data set with 6 million pedigree records, 4.8 million birth weight records, and 1.9 million post weaning gain records, 46,402 genotyped animals and used 44,414 SNP markers.


Read the full article here

Sunday, 17 April 2016 15:52

BOLT software brings more reliability to EPDs

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The accuracy of genetic prediction took a big leap forward when genomically enhanced EPDs became available. Now, with new technology, prediction accuracy may get honed to an even finer edge.

Wes Ishmael | Aug 01, 2016

Less risk in genetic selection via higher-accuracy expected progeny differences (EPDs).

That’s the bottom line promise of BOLT, new software adopted by International Genetic Solutions (IGS) to conduct its National Cattle Evaluation (NCE).

IGS is the unique collaboration of 12 breed associations in the U.S. and Canada to conduct a common, multi-breed NCE with a combined database representing almost 17 million animals.

Many at the recent annual meeting of the Beef Improvement Federation heralded BOLT as a revolutionary step in NCE.

“It's a game-changer,” believes Wade Shafer, executive vice president of the American Simmental Association (ASA).

True accuracy

BOLT is an acronym for Biometric Open Language Tools. Bruce Golden and Dorian Garrick — noted animal breeders familiar to those in the seedstock business — developed the new software and license its use through their company, Theta Solutions LLC.

Increased prediction accuracy with BOLT comes through the software’s ability to directly incorporate genomic data into the EPD calculation.

“Until now, we’ve had to incorporate DNA information through a post-evaluation blending process that combines the independent genomic data and traditional EPD into one published EPD value,” says Larry Keenan, director of breed improvement for the Red Angus Association of America (RAAA). “BOLT gives us the capability to incorporate genomic information directly into EPDs.”

Even though systems before BOLT meant DNA data were blended post-evaluation, its inclusion in recent years significantly increased the EPD accuracy for young animals. “This absolutely will allow us to maximize use of information in the database for pedigree, phenotypic and genotypic data,” Keenan says.

“There is so much information, but because of the limitation of the models and technology that have been available to us previously, we couldn’t squeeze out all of the value from that information. We’ll be able to get more out of it with BOLT,” he says.

Another powerful feature is BOLT’s capacity to calculate actual (true) accuracy, says Shafer.

“Prior to BOLT, the calculation of accuracy in NCE has been limited to what has been dubbed ‘approximation methods,’ ” Shafer says. “These methods take an indirect approach to the calculation of accuracy and routinely result in estimates of accuracy that can be quite different than an animal's actual accuracy.”

Because BOLT can calculate accuracy directly, it is capable of producing true accuracy. “Prior to BOLT, it was thought that the calculation of true accuracy was not feasible on large databases due to the computational requirements being untenable,” Shafer says.

Keep in mind that EPDs are already the gold standard of genetic prediction. Given available technology, they’re as reliable as possible.

Increased precision

The massive size of the IGS database also lends itself to increased prediction accuracy.

“Accuracy is critical to making genetic progress,” Shafer emphasizes. “There are almost 17 million animals in the IGS database. The accuracy of prediction generally increases with the volume of data.”

Depending on your leanings, a multi-breed NCE also offers sturdier predictions than a single-breed analysis.

Think of it like this — a registered Red Angus bull has an EPD within that breed, built upon the pedigree, phenotypic data, and now, genotypic data — submitted to that breed’s database. But the bull may also sire or be a relative to lots of other cattle accounted for in other breed databases. Being able to account for more progeny and relatives across more of the cattle population makes for a more accurate snapshot of the bull's genetic potential.

ASA began working with Cornell University in 1995, funding research and development for multi-breed NCE. Unlike in the traditional model, where universities developed NCE models and performed NCE for breed association clients, ASA shared the development costs and ownership.

At the time, Simmental breeders — like those of other Continental breeds — were primarily focused on breeding up cattle to purebred levels.

“We had lots of halfblood, three-quarter-blood and seven-eighths-blood Simmental, but we were using a single-breed model for genetic evaluation,” Shafer explains. A single-breed model couldn’t fully account for breed differences or heterosis.

These days, of course, another advantage of multi-breed analysis is that hybrid and composite seedstock are commonplace.

What you can expect

“From what we have seen thus far, it appears BOLT has the capacity to improve the accuracy of prediction well beyond any currently existing technology,” Shafer says. “As is typically the case with new genetic evaluation technology, the biggest gains will be on younger, lower-accuracy animals — which, fortuitously, is the vast majority of animals being considered as breeding stock.”

When IGS begins conducting its NCE with BOLT, seedstock producers will likely see some reranking of bulls, which always causes discomfort. The EPD accuracies for some bulls will likely decline, too. Rather than an indication that the new method is less robust, declining accuracy with the initial BOLT NCE would mean that the previous accuracy, calculated via the approximation method, was too high.

Already, EPDs can be compared directly among IGS breeds for growth and carcass traits. Ultimately, plans call for making that possible with heifer pregnancy and stayability, too.

“BOLT is a software package that is very dynamic and flexible, with the ability to accommodate most any type of statistical model,” Shafer explains. “Its flexibility makes upgrading models or developing EPDs for new traits highly feasible.”

BOLT is lightning-fast, too, compared to current NCE models and technology. Running the current IGS NCE without BOLT takes a couple of days. Running the NCE on the same computer with BOLT only takes a few minutes.

“The remarkable increase in speed is due to the software being written in a manner that utilizes the hardware to its fullest capacity — an approach that takes a world-class understanding of the interaction between computer programming and hardware,” Shafer explains. “BOLT’s dramatic speed allows for computational feats that were previously considered untenable, such as the calculation of true accuracy on a massive database.”

IGS is in the process of readying its massive database for BOLT. There is no launch date, but indications are that it should be this year or the first part of next year.

 “Eventually, I believe all genetic evaluation providers, regardless of species, will go to it [BOLT] because of the power it brings to the table,” Keenan says. 

Read the full article here.http://www.beefmagazine.com/cattle-genetics/bolt-software-brings-more-reliability-epds


Tuesday, 17 January 2017 11:25

Recent Developments in Genetic Testing and Genomic Testing

Written by

Alison Van Eenennaam | University of California, Davis

The application of genomics to improve the accuracy of EPDs is a rapidly developing field. There are ongoing improvements in genotyping and sequencing technologies, statistical methods to increase the correlation between genomic predictions and true genetic merit, and the computing systems to handle the large datasets associated with animal breeding. One thing still remains true in the genomic age and that is the need to collect accurate phenotypic records. It is essential to ensure performance data, pedigree, and DNA information are recorded and reported accurately. Genomic predictions will only be as reliable as the data upon which they are based.  Although it might seem like the genomics era could signal the end of performance recording, the opposite is true. Now more than ever, it is important that producers accurately report data, and ensure that animals which are genotyped are correctly identified so that their information can contribute towards improving the accuracy of the genomic predictions of the future.

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Tuesday, 17 January 2017 11:20

Bob Weaber from KState and Larry Kuehn from US MARC

Written by


"Brown Bagger" electronic presentation a couple weeks ago. Bob's focus was on the changing landscape in the area of genetic evaluation and Larry talked about MARC's involvement in multi-breed and across breed comparisons. This is a highly recommended presentation for those interested in genetic evaluation.  Click here.

Tuesday, 17 January 2017 11:14

IGS: We Collaborate You Profit

Written by

BeefMagazine.com    |    Published  September 13, 2016
Chip Kemp, American Simmental Association

Every industry is riddled with examples of supposed experts missing the mark as they neglected to heed the voices of those they serve. Too often, those with the loudest megaphone attempt to explain what we should want as opposed to hearing what is truly desired or needed. Enter the Edsel, the Blimp, AOL, and the overwhelming majority of politicians.

So how do we avoid the pitfalls of leadership hubris? How do we ensure that customer voices are at the core of decision making? How do we balance the need for innovation with the ability to get novel products to gain traction in the marketplace? 

Humility and an intense interest in listening to and understanding the needs of business partners are crucial.  Agriculture at its very core is neighbors teaching neighbors how to make it greener, produce it healthier, grow it faster, or improve the taste. There are countless examples of successful firms engaging their business partners regarding new products, new approaches, and new directions. Your seed salesman, local coop, area veterinarian, regional sale barn are all forced to hear their customers and react accordingly. The feedback loop is quick, impactful, and brutal.

Other parts of our industry have been slower to seek input from commercial clients. One example is the area of Genetic Evaluation of Beef Cattle. The complexity of science, speed of innovation, overly-acronymed jargon are all reasons that well-intentioned folks sometimes isolate themselves and are slow to share findings and ideas with the end user. The historical breed association has been eager to report results, but less enthusiastic about incorporating commercial data or letting folks see behind the magic curtain of genetic analysis. Again, this isn’t necessarily an indication that associations were hiding or avoiding their obligation. Rather, in most cases it was a matter of limited personnel to share the message and limited scientific capability to incorporate commercial data.

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