Thursday, June 30, 2016

The Next Generation

The beef industry values sustainability. We value successful operations that are passed on to generation after generation. That is why beef producers support  youth programs.

Those of you who know me personally, know I am way too busy for my own good.  I've learned to say no and am making strides in simplifying. When the beef project leader in my kid's 4-H club came open, I should have kept my mouth shut. Instead, I volunteered to be the leader, because I value educating youth. I wanted to pay it forward and help kids fall in love with cattle the way I did.

On Friday July 8th will be our Sturgeon Beef Show. I hope those of you in mid-Missouri will come out and enjoy the successes of our youth.

If you are interested in sponsoring a breed champion, please let me know. Thanks to those who have already sponsored.

Watch the blog for pictures of my little ones falling in love with cattle. If you time driving by my house just right,  you might even catch a glimpse of a computational geneticist trying to catch a calf out in the pasture. :)


Saturday, June 25, 2016

BIF 2016: Genomics, return on investment - fact or fiction?

Tonya Amen
Consultant for Illumina, Inc.

One dairy operation was making $35 per year progress for net merit. After using genomics in late 2009, they were making $50 per year in progress for net merit. After they started testing females, this rate increased to nearly $80.
This dairy herd is now seeing $340 more in life time production by using genomics.

From 2005 to 2008, $B was increasing by $3.77 per year.
From 2009 to 2015, $B increased by $5.62 per year.

From 2013 to 2015, $B increased by $9.31 per year.
A 146% increase in genetic trend.

We have seen more rapid genetic improvement in Angus, Hereford and Simmental, all of which line up nicely with the deployment of GE-EPDs. Thus, it is possible (likely?) that this improved genetic improvement is due to the benefit of genomics.

In the dairy industry, genomics is equivalent to 25 production records, 25 conformation records, and 140 fertility records.
Genomics is saving the Canadian dairy industry $111 million dollars annually.
Genomics is saving the New Zealand Farming Coop $4.2 million annually. The genetic gain is increasing despite the cost saving.

A genomic test for Angus gives a breeder the same amount of information as 17 progeny with records for dry matter intake. A $47 test is much cheaper than doing a feeding trial on 17 progeny.

Three benefits:
1) Identify future problems
2) Identify current problems
3) Gives representative proxies for genetic merit of steer mates

There is also value in avoiding inbreeding. Inbreeding decreases performance, thus avoiding inbreeding helps us to avoid decreased performance. In dairy cattle, there is a $20 lost revenue per year for a 1% increase in inbreeding.

Selecting cattle for placement in a feedlot can be worth up to $38 per head. If we are just trying to use this information for different management, the value is less than $1 per head.

CLARIFIDE plus now can directly predict disease risk in Holstein cattle. As discussed previously, we see large reductions in feed efficiency due to health problems.

Amen's is pointing out that we see a $204 premium for heifers with genomics tests in the Show-Me-Plus program. This leads to a return on investment of 167% to 700%.

Friday, June 24, 2016

BIF 2016: Using genomic tools in commercial beef cattle: taking heifer selection to the next level

Tom Short

Can genetic information from a simple DNA sample allow us to reasonable accuracy of the females lifetime performance?

We know that our national cow herd inventory decreased to a very low level in 2014.

When we rebuilt the cow herd did we keep low quality heifers that should have never been cows?

What type of genomic prediction should we be using to select commercial heifers?

GeneMax Advantage was produced by a collaboration of Angus Genetics Inc, Certified Angus Beef, and Zoetis. It is applicable to beef females that are at least 75% Black Angus. These predictions are based on the Zoetis HD50K product for Angus. The correlations between the genomic predictions and the breeding value are all quite good, around 75%.

The individual traits are combined into three indexes. These are a Cow Advantage Score, Feeder Advantage Score, and Total Advantage Score. The correlation between Total Advantage and the Cow and Feeder indexes are about 70%, but the correlation between Cow Advantage and Feeder Advantage is about 50%. So, if in doubt about your breeding objective, use the Total Advantage Score.

The Cow Advantage is 13% Cow Cost, 66% number of calves, and 21% weight of calves. Carcass Advantage is a combination of feedlot and carcass traits.

Maximum genetic economic improvement is made by selecting on indexes.

Check out Bob Weaber's fact sheet on for more information about indexes.

By selecting on GeneMax Total Advantage, we see about 0.5 standard deviation improvement in Calving Ease Direct. We see about 0.9 SD improvement in weaning weight, 0.4 for marbling, calving ease maternal abour 0.6 SD. If we selected only on weaning weight, we would see unfavorable changes in mature weight, mature height, and decreased improvement for calving ease and other economically important traits.

In Short's model, value of the test is measured over a 10 year period based on the performance of the cow's progeny, grand progeny, and great grand progeny.

The heifers that you test and retain have to pay for the heifers that you test and cull. By 7 years, we see a net revenue of $300 per tested heifer. Break-even occurs between years 3 and 4. The value of the future generations is about 1.5X that of tested females. Keep in mind, investments in genetics is a long term investment!

146 heifers tested in SD herd.
By visual apprasial, the top 100 heifers averaged a 56 Total Advantage Score
By index rank, the top 100 heifers averaged a 65 Total Advantage Score.

A $39 test cost is approximately only $15 more than recommended health protocols to first calving for a first heifer.

Also consider other value considerations.
Value added marketing programs, the average of the heifers matches the average of the steers. Could use this information in marketing steers through TopDollar Angus or Reputation Feeder Cattle.

Also a great shout out to Missouri's Show-Me-Plus program!

This tool is also a unique value to commercial producers because historically they do not have access to genetics predictions for commercial heifers.

See for more information.

Thursday, June 23, 2016

BIF 2016: Can Beef Seedstock Producers Afford Genomics?

Breeding objectives indicate value of genomics for beef cattle

Dr. Mike MacNeil

Is genomic testing a good value to seedstock producers? The answer to this question requires several different lines of thought. To answer this we need a system based approach.

What makes up a genetic prediction?

  • Information from relatives
  • Molecular breeding value
  • Correlated phenotypes
  • Phenotype
No individual animal in a genetic prediction ever has an accuracy of prediction of zero. The information from the calf's relatives brings in substantial amount of information.

What are the advantageous of genomic prediction?
1) Increase accuracy of evaluation
2) More exciting is the opportunity to incorporate additional traits
  • costly or difficult to measure
  • measured late in life (after the time of selection decisions)
  • sex-limited
3) Avoid prolonged generation intervals. For many selection decisions in beef cattle, we make many selection decisions around a year of age.
4) Reputation. This is hard to quantify in dollars and cents!

What is improvement???
MacNeil's definition is making cattle that are more profitable in the next generation.
This can be boiled down to income minus expense.

MacNeil uses a computer model to estimate the effect of changing one trait by a unit of measure and seeing how that influences profit.
This model:

  • Is an abstraction of any actual beef production system.
  • Captures sources of income and expense
  • Has economic parameters which reflect future expectation
  • May be discount income and expense streams 
  • Has data-driven biological parameters 

For these models, MacNeil simulates many animals.

For feed efficiency simulations, MacNeil used 5 scenarios.
Scenario 1: Phenotypes only (accuracy = 2√h2)
Scenario 2: Phenotypes + low accuracy genomic prediction
Scenario 3: Phenotypes + higher accuracy genomic prediction
Scenario 4: (Phenotypes + siblings) + low accuracy genomic prediction
Scenario 5: (Phenotypes + siblings) + higher accuracy genomic prediction  

Going from phenotype to genomics has a fairy substantial jump. Going from a low accuracy genomic prediction to a high accuracy genomic prediction also has a big jump. When we have pedigree predictions with lots of phenotypes, there is no benefit from adding genomics.

"If you have a bull with 200 progeny records, don't waste your money on genomics," MacNeil said.

How many breeding objectives (economic selection indexes) should we have? MacNeil did an analysis. In South Africa, you receive discounts when the carcass weighs 500 pounds.
The correlation between the South African index and United States index was 0.68. The breeding objective in South Africa would work fairly well in the United States. The differences in breeding objectives across the United States are minuscule across environments in the United States. In other words, use indexes! They work!

Genomics only helps birth weight predictions by 9%. Genomics helps dry matter feed intake by 41%, because there are many fewer feed intake records.

For a maternal objective, fitness drives the bus. The cow needs to stay in the herd. This accounted for 50% of the value in the breeding objective.

For stayability in beef cattle, adding genomics had a 76% improvement in the accuracy of genetic prediction. This is because this trait is measured later in life and there are fewer phenotypic records.

In a terminal objective, we increase accuracy by 27%. 

If we generate 60 harvested progeny per sire, we earn $169 per genomic tests.
If we generate 15 replacement heifers on a bull, we earn $159 per genomic tests.

"You are on the order of 4 times the cost for return, based on the cost of the test." MacNeil said.

What are the take home messages:
Breeding objectives greatly facilitate multiple-trait selection
Genomic predictions for component traits add substaintal accuracy to prediction of breeding objectives
Genomic technology has greatest promise for traits that are infrequently recorded or recorded after the selection decision point
With reasonable transfer of economic benefits from commercial to seedstock sector, it indeed does appear that seedstock producers can afford genomics, provided they use rational breeding objectives.

"I started this exercise believing the answer was no." MacNeil said. "I believed it was a shell game about the perception of the value of the technology." 

MacNeil proved to himself that he was wrong.

Multi-trait breeding objectives keep you from going too far down the wrong path. They put the right amount of emphasis on each trait.
Tandem selection and independent culling levels are both less effective than breeding objectives through economic selection indexes.
 If we chase one trait, then run into a problem, select for a second trait, run into a new problem, so chase a third trait- this is tandem selection.

MacNeil stated, "I am troubled by the Angus $B index, as it is an incomplete objective" (i.e. it only takes part of the production system into account, not from conception to slaughter). But, using $B is MUCH better than using the individual component traits.

See for PowerPoint and Proceedings.

Decker's Take Home Thoughts
While many of the cattle that are on our farm or ranch are selected at a year of age, the ages of AI sires can vary greatly. Thus, AI sires may be a potential opportunity to decrease the generation interval. While commercial producers should likely use proven AI sires, this may not be the case for most seedstock producers. Using younger AI sires may be low hanging fruit for many seedstock herds.
Use genomics and use economic selection indexes so that your breeding decisions are rational.

Wednesday, June 22, 2016

BIF 2016: Growing profit by understanding cow maintenance efficiency and maintenance requirement in an animal and systems context

Dr. Mark Enns
Colorado State University

If we had the ability to improve maintenance feed consumption likely would improve profitiability of beef production.
To make genetic improvement we need genetic variability. Is there variability for maintenance energy? Hotovy et al 1991 measured intake and fasting heat production on twins to estimate heritability of maintenance energy. The heritability was 0.51.

But, putting a large number of cattle through metabolism chambers is not feasible.

What tools are available to change maintenance energy?

  • Mature weight and height
  • Body condition scores
  • Maintenance energy EPD

For two beef breeds, we see an unfavorable trend for mature size. If we go from a 1000 pound cow to a 1500 pound cow, we have increased the maintenance requirement by 35.5%.

But, maintenance energy is a function of both body weight and milk production. $EN index produced by the Angus Association is an economic index weighting both body weight and milk production.
Maintenance energy EPD (Mcal/Month), which accounts for mature weight and milk, is an EPD that allows selection of cows requiring less feed for maintenance.

Both $EN and ME EPD have both had unfavorable genetic trends (although ME EPD has plateaued the last few years).

Body condition score adjustments.
Let's assume an average mature weight of 1,350 pounds. If a cow has a body condition score of 5, there is no adjustment. If a cow has a body condition score of 7, the adjusted mature weight is 1144 pounds.

Red Angus Association: mature weight and body condition scores represent roughly 20% of the numbers of weaning weight records reported.
For American Angus Association, there are over 9.1 million weaning weight records. There are about 120,000 mature weight records.

The genetic relationship between birth weight and yearling weight is 0.55. Despite this strong relationship, we have successful created curve bender bulls with good calving ease and high growth.

The relationship between mature weight and yearling weight is 0.72. Just as we have broken the genetic antagonism between birth weight and yearling weight, we need to do the same thing for yearling weight and mature weight.

There has been encouraging progress on the research side. We have improvements in genomic predictions for feed intake. The correlation between feed intake on forage and grain is favorable (Shike), but we need to look at this from a genetic correlation perspective.

"There is evidence that selection can be successful for reducing maintenance energy requirements while still improving growth." Enns said.

Using an economic index, a cattle herd in Australia held mature size constant but increased slaughter weights.

Selection indexes work! Think what we can do with EPDs if we have the necessary data.

We need more data for mature weight and body condition scores.

See for more information about this talk.

Tuesday, June 21, 2016

BIF 2016: The 2016 and 2036 cow herd, what we do and what we need to do better

Dr. Dave Lalman
Oklahoma State University

Lalman points out that we have made tremendous change for post weaning growth. Right now finished cattle weights are increasing at a rate of 9.4 pounds per year. Carcass weights are increasing by 5.7 pounds per year.

Marbling has also increased over time.

Compared with 1995, we have seen fewer yield grade 1s and 2s, but we have seen more yield grade 4s and 5s. The number of yield grade 3s has increased from 34.2% to 46.7%.

The cow-calf sector and the entire industry have responded for the need for increased post-weaning performance and carcass quality.

The increase in calf prices has increased by $5.25 per hundred weight (cwt) per year. The increase in costs has increase by $5 per year. Profitability appears to not have changed that much.

Lalman discussed analyses by Pendell and coworkers published in 2015, in which they analyzed Kansas Farm Management Association data. The data had information from 79 operations with data from 2010 through 2014. In this data, the high profit 1/3 averaged $415 more net return per cow compared to low profit 1/3.

When comparing high profitability to low profitability, 32.2% of the difference was due to gross income per cow. However, 67.8% of the difference between high profit and low profit operations was due to reduced expenses.

Increasing weaning weight often leads to break even (due to management?).

Weaning rates have not changed over time. In the northern US, we see high pregnancy rates above 95%. In the southern US, we see much lower pregnancy rates around 90%. The national average for weaning rates is around 85%.

In most areas, we see no trend for weaning weight. In the Kansas data, we see a 1 pound increase per year in weaning weight. For purebred Angus, we see about 2 pound increase per year.

Hay production (use?) per cow is increasing about 66 pounds per year.

1.1 lb/day increase in dry matter intake increases milk yield by 1 lb/day.  But, this requires 27 additional pounds of feed per 1 pound of calf gain.

Please see for more information about this presentation.

Decker's Take Home Message
First of all, I think we must be clear that this research does not mean EPDs don't work. It doesn't even insinuate that EPDs don't work. What it may mean is that the environment may be limiting the expression of an animal's full genetic potential. If that is true, emphasis on selecting for increased weaning weight should be decreased, and selection pressure redirected to different traits.

Based on surveys of cattle producers, I am highly suspicious that the majority of cattle producers are using EPDs at all, and if they are using them, if they are using them appropriately. A BEEF Magazine survey indicated that the top criteria to select bulls is actual birth weight- this is not using EPDs or using them correctly. Those producers who embrace technology, whether new or old tech, will be the heroes who lead the beef industry forward.

Our experience at our Thompson Research Center has been much different than the data reported in the SPA, CHAPS, or Minnesota data. The Thompson Research Center is operated as a highly profitable commercial herd. Calves are not creep feed or otherwise pampered. In our data, from 1996 to 2013, weaning weight increased by 1.5 pounds per year. While this is not as rapid as the 2.6 or 2.1 pounds per year seen in the Angus data, it is much larger than zero. In our experience, if producers use AI sires and apply a consistent breeding objective then phenotypic improvement will be seen.

Lastly, we agree that the environment may be limiting the performance of cattle. That is why we have designed a research project in which the ultimate deliverable will be region specific EPDs and indexes that are tailored to specific environments.

Monday, June 20, 2016

BIF 2016: Extension demonstration project outcomes; Industry adoption and translation of project deliverables

Dr. Matt Spangler
University of Nebraska-Lincoln

A seedstock producer's goal should be faster genetic progress (breeders equation). But, we need to balance this by the cost of the genetic progress.

Although some of these traits are interesting to us as biologist (what Spangler termed "biological intrigue"), what really matters at the end of the day is improving cattle.

What is the difference between an indicator trait and economically relevant traits? Economically relevant traits are traits that directly impact profit by either influencing revenues or expenses. Indicator traits are traits that are recorded because they allow us to more reliably predict economically relevant traits. An example of this would be calving ease direct and birth weight. No one gets paid for or has costs associated with birth weights. But, birth weight is a great indicator of calving ease, because calving ease can have economic impacts through labor, dead calves, cows that don't rebreed, etc.

Which is the economically relevant trait? Residual feed intake or dry matter intake? Residual feed intake is an indicator to make selection decisions. When you feed cattle, you are charged for the actual feed intake, NOT the residual feed intake. Thus, dry matter intake is the economically relevant trait. See Improving Feed Efficiency: Feed Efficiency Project Releases Decision Support Tool for more information.

What is a selection index? When we use an index we select on aggregate merit. The index is a combination of the individual economically relevant traits into a single value, most frequently expressed as a dollar figure.

“There is no easily accessible, objective way for breeders, particularly breeders in the beef and sheep industries where ownership is diverse and production environments vary a great deal, to use these predictions [EPDs] intelligently.” 
- Bourdon
What does this quote mean? Does it means EPDs don't work? Does it mean that beef producers are stupid? No, it means that it is nearly impossible for an individual beef producer to identify how to use the entire set of published EPDs. What EPDs should be emphasized? What are appropriate bounds for EPDs?
Luckily there is a very easy solution, economic selection indexes.

What drives profitability?
Hot carcass weight is the main driver of profitability, accounting for 59.5% of the impact on profit. Dry matter intake is also important at 11%.

There are 24 beef operations from 7 states that are part of the weight trait project. This project has been designed as a demonstration project of genomic selection. Through this project came some of the first observations that genomic predictions (at least in their current form) don't work well across multiple breeds. In other words, genomic predictions designed in Angus don't work well in Hereford or even Red Angus. The weight trait project was expanded at the start of the USDA Beef Feed Efficiency project. As part of the demonstration project, they got semen from bulls used by producers in the Weight Trait Project. They produced progeny out of these bulls and put the progeny through a feed intake trial. This data has then been turned over to the breed associations to use in the development of feed intake genetic predictions.

Please visit and for more information.

Thursday, June 16, 2016

BIF 2016: In Search of Beef Production Nirvana, Things a cow-calf producer learns when you own a feedyard, what drives profit?

Chip Ramsay
Rex Ranch

"I'm humbled to be in front of you." Ramsay said, "You all represent the most passionate and educated group of producers."

Nirvana, what does that mean?
In the Buddhist tradition, nirvana is described as the extinguishing of the fires that cause suffering and rebirth. These fires are typically identified as the fires of attachment, aversion, and ignorance.

Rex Ranches and their feed yard face weather volatility. In 2012, calf cost was $635, in 2013 it increased to $876.

They also face price volatility, there were swings in $241 of calf price over five years.

There has to be trust between segments. Weighing conditions, changed to do what is best for the cattle instead of worry about who gets the advantage. Because of the integration of the cow-calf and feed yard, they can streamline vaccination protocol and reduce redundancy. This also requires sharing added value. Is it a zero sum game or can we add value? We need to have an abundance mentality and make the pie bigger. Be can't spend ourselves to oblivion, but there are opportunities to increase value.

"If we can't speak in the same language, we can't accomplish anything." says Ramsay.
Perhaps we need to look at contribution margin, revenue minus variable costs.We need a system-wide analysis to find additive value.

Correct use of EPDs can significantly change cattle performance within a generation interval. By focusing on calving ease and marbling, dystocia moved from 25% to 8%.

Wednesday, June 15, 2016

BIF 2016: Gene set enrichment analysis for feed efficiency in beef cattle

Holly Neibergs
Washington State University

Neibergs lead an effort to identify key genes within the network of genes that influence feed efficiency differences.

In this analysis they analyzed over 700,000 DNA variants in about 800 Hereford steers. For these Hereford steers they calculated the residual feed intake. Residual feed intake is how much the observed feed intake differs from the expected feed intake based on average daily gain and body weight. For over 19,000 genes, they identified the DNA marker within 8,000 base pairs of the gene that had the largest effect. These effects were assigned as the effect for that gene. They could then analyze networks of genes to look for gene networks that were significantly involved in feed efficiency differences.

Gene networks involved in cell division, including cytoskeleton organization, influenced differences in feed efficiency. There were also genes involved in the formation and regulation of peroxisomes found to influence feed efficiency. The peroxisome is involved with cellular transport and catabolism. they work on removing free radicals and maintaining lipid homeostatis.

By, Public Domain,
Components of cytoskeleton are labeled by red and green strains.

BIF 2016: Effects of timing and duration of test period and diet type on intake and feed efficiency

Dan Shike
University of Illinois

The correlation between the growing dry matter intake (DMI) and finishing dry matter intake was 0.56. This means 56% of the variation is shared between the two feeding periods.

Average daily gain is not that repeatable. The correlation between average daily gain in the growing period and the finishing period is only 0.11.

However, residual feed intake (RFI), a measure of efficiency, is  repeatable between feeding periods, with a correlation of 0.63.

Using 35 days on feed accounts for about 95% of the variation in feed intake from a 70 day feeding trial.

Intake seems to be very repeatable across stages of life and on different diets.

The residual feed intake (RFI) repeatability was 0.42 when comparing a forage diet to a grain diet.

Intake is repeatable. Gain is not repeatable between test periods.
Shorter duration intakes are strongly correlated to total feeding period intake.
Intake of forage is correlated to intake of grain, furthermore efficiency is also correlated between forage and grain diets.
This implies that intake and efficiency in the feedlot may have application to a cow-calf scenario.

BIF 2016: Feed Efficiency Genomics and RNA Project Discoveries

Jerry Taylor
University of Missouri

The project assembled DNA samples, individual feed intake, growth and carcass data for 8,000 animals from 8 major beef breeds.The project has various objectives, including identifying genes with different levels of expression between high-efficiency and low-efficiency animals, create genomic predictions for feed efficiency, and identify DNA variants responsible for differences in feed efficiency (causal variants).

The project collected 12 Angus sired steers, 12 Charolais sired heifers and steers, and 12 Hereford sired steers, half of which had poor feed efficiency and good feed efficiency. They collected over 15 tissues per animal.

In the Hereford RNA sequencing data, the team found genes that are involved in metabolism. In the Angus and Charolais data they found many genes involved with immune function. This is likely due to the poor feed efficient animals having subclinical illness which led to them having poorer performance and less efficiently turning feed into gain.

The project showed that feed efficiency and its component traits are highly heritable. There are also many relatively large effect genes (quantitative trait loci) for all traits. Many of these stretches of DNA (quantitative trait loci) affect multiple traits and are shared among breeds.

The project is continuing to search for causal variants (the DNA variants responsible for variation in traits).

In order to continue to use the resources generated by the feed efficiency project, industry must continue to collect intake and growth data, and DNA samples.

GeneSeek Meeting: The Value of Genomics

Slides from my presentation at the GeneSeek meeting prior to the Beef Improvement Federation meetings.

Slides can be downloaded here:

Beef Improvement Federation 2016: Decker's thoughts on Dr. Keith Belk's presentation

Dr. Keith Belk spoke at BIF this morning.

Belk suggested we should select based on the microbiome.

Should we be selecting based on the microbiome?


First, our current understanding of the microbiome is very incomplete. Second, the microbiome is not perfectly inherited. Every calf inherits 50% of its DNA from its sire and its dam. DNA can be used for prediction because it is inherited in a predictable manner. The microbiome is not inherited to the same level of predictability. The highest heritibility for a bacterial family is below 40% (DOI: 10.1126/science.aab3958) in human twin studies. In other words, the microbiome is more influenced by the environment, then by inheritance. The microbiome may be a trait that we want to select, but I do not believe it is the tool to make selection decisions.

Swapping genes between symbionts and their hosts are very rare events. Animals have developed mechanisms to stop this from happening. Animals strive to stop other organisms from high jacking their genomes. Are we going to select for horizontal gene transfers? No. We could use gene editing to move genes between species, but the consumer acceptance of this has not been great.

Larger carcasses are one way that we can produce more beef with fewer cows. Dr. Belk seemed to indicate that larger carcasses were bad, without discussing them in the entire context of beef production.

In summary, Dr. Belk veered in some very strange directions that I don't think were constructive for this audience. Perhaps I misunderstood Dr. Belk's comments- if so he is free to respond to my comments.

Dr. Belk did have some worthwhile things to share.

Marbling is important in determining beef palatability. But, tenderness and flavor are also very important to retailers and consumers. And if we have appropriate tenderness, flavor becomes even more important.

"We need to start thinking about selecting for tenderness, juiciness, and flavor," stated Belk.

How much progress have we made in improving meat quality? Part of that improvement is from going from 45% black hide in 2000 to 60% black hide in 2011. In 1995, 49% of carcasses graded choice or better, and in 2011 61% of the cattle graded choice or better.

Beef Improvement Federation 2016: Beef as a consumer driven food business: Changing perspectives from cattle to food production

Dr. John Stika
Certified Angus Beef

Sometimes we think about beef production from a cow based focused. We think about our brand, the brand on the side of our cattle. Stika states we have seen a shift toward thinking about branded beef programs.

Stika states, "The only sustainable flow of dollars from which to continue to build the beef business comes from the consumer." Sometimes we see a bull sell for high dollars, and we hear questions about if that was "real money." The dollars that come from consumers is absolutely real money.

CAB's pull-through strategy:

  • Exceed consumer expectations
  • Build repeat business
  • create benefit across the entire chain
  • Strengthen demand for beef (increase supply and price at the same time)
When consumers make purchase choices, taste is still king.

The comparative retail price of beef is increasing relative to poultry and pork. To keep consumers happy, we have to provide them with better beef. Would you buy the same truck for a higher price? No. Would you buy a better truck for a higher price? Yes.

Demand for Certified Angus Beef has grown by 98% since 2009. Despite a weak economy and reduced cow numbers, sales of Certified Angus Beef increased over this time.

Branded beef programs continue to grow. 

There has been a $8 to $10 spread in choice vs select. There has been a $7 to $15 spread in choice vs high choice.

A high quality carcass is the most valuable thing we produce, but it is the last thing we get paid for. But, cow-calf producers get paid for cattle that do their job by adapting to the environment, producing a calf, and having that calf grow. But, we can do it both! We can select cows that do their job and produce a calf that does his job on the rail and on the plate. 

Consumers are not ignorant.
For consumers, trust and transparency are tops and the story matters. Buying beef is an economic decision made with emotion. We need to approach consumers from an emotional perspective.

Beef Improvement Federation 2016: What will the North American beef market look like 20 years from now: opportunities for domestic and international growth

Dr. Glynn Tonsor
Dr. Ted Schroeder
Kansas State University

The comparative advantages of North American beef industry is world trust and premium prices. North America is the leader in grain-finished production. North America has a sound and effective infrastructure; feed grain base, processing, safety, transportation, genetics and meat quality expertise, research discovery and education.

Some of the comparative disadvantages of North American beef production is that it is not the lowest price per pound producer. Further, there is limited communication, coordination, and signaling between sectors of beef production. There is fragmented support of traceability systems and focus on future beef demand.

Schroeder stated it is important to remember that the value of beef production comes from supplying demands of beef consumers. We need to make sure that the domestic consumer market accepts what we are doing. The United States population is changing, and we need to make sure we are meeting their wants.

We need to identify areas of population and income growth, as these countries will have growing meat demand.

Trans-Pacific Partnership (TPP) involves 12 countries, 830 million people, largest trade agreement, 7 of 30 richest countries. This agreement would reduce the Japan tariff on US beef from 38.5% to 9% over 15 years.

Immense opportunity exists, BUT internal industry coordination must improve.

Tonsor's predictions for 2036:
Less animals and operations yet more beef
Exports as share of production will be more than 11% (alleviate price pressure at home)
Improved coordination and information flows (may be forced simply by technology, attitude change would further improve)

In additions to current premiums and discounts, there are possible new specifications:

  • Tenderness
  • Technology/Prodcution Practice
  • Source verification
  • Many more?

Tuesday, June 14, 2016

GeneSeek Meeting: Genotyping Embryos

Matt Barten
Founder, EMBRUON

We can now biopsy an embryo to extract a small number of cells. We can then extract DNA from that cell. In order to test that DNA with a SNP chip, it has to be copied (amplified) 2,100 times. This is like taking a bushel of corn and amplifying it to a trailer load of corn.

Biopsying an embryo only decreases embryo pregnancy rates by about 10%.

One of the straight forward applications of embryo biopsy is to look for carrier status of genetic abnormalies. We can now do a full GE-EPD test on these biopsies. This means we can actually decide which embryos to implant based on the embryo's genetic merit!
We can know earlier and earlier what the genetic merit is, allowing us a new way to shrink the generation interval.

Barten's company flushes a day early at 6.5 days, then send embryos back out at 7.5 days. They currently use human IVF tools to ship the embryos the same day. He biopsies the embryo and sends back the frozen embryos.

The biggest key to success is recipient quality and management.

Having both parents genotyped allows GeneSeek to assess the accuracy of the embryos genotype. GeneSeek also assess the quality of the DNA to see if it is suitable for SNP chip genotyping, or if they need to focus only on sex and genetic defects.

Decker's Take Home Message
As this technique and technology continues to develop, it will open up exciting new opportunities for shortening the generation interval and practicing within family selection. Half of the variation in the population is observed between full siblings.

GeneSeek Meeting: GGP-F250 SNP Chip

Jerry Taylor
University of Missouri

Why did we create a new SNP chip?
There have been four large USDA research grants that Taylor has been a part of. From theses grants, there has actually been a synergy, the sum has been greater than the individual parts.

In one grant they planned to genotype 4,000 variants in 10,000 cattle to look for variants causing embryo losses due to broken genes. The feed efficiency project and the bovine respiratory disease complex projects both budgeted to test 1,000 variants in 2,000 cattle. With a fourth project, they won additional funds to create a SNP chip to look at 200,000 DNA variants in over 17,000 cattle, thus tying all four projects together.

If a DNA variant is lethal, meaning it causes an embryo which carries two copies of the variant to be aborted, then we will never see an animal carrying two copies of that DNA variant. We can look at the inheritance of DNA variants through pedigrees and identify DNA variants that we should observe animals with two copies, but we never observe an animal with two copies of the DNA variant. These DNA variants are then strong candidates as lethal variants.

We also need to identify causal variants for quantitative traits. This is very hard to do; in his 30 year career, Jerry Taylor has found one causal variant. Why are we chasing causal variants in beef cattle? Unlike dairy cattle, we have lots of breeds represented in the beef industry and knowing the causal variants should allow us to create genomic predictions across cattle breeds.

There is a process, called imputation, that allows us to use lots of DNA variants in our search for causal variants. The DNA variants on chromosomes are inherited in patterns. We can use these patterns to infer or predict the genotype for DNA variants that we did test in genotyped animals using DNA sequence data from other animals with whole genome sequences. Now, we can look for causal variants in analyses with over 10 million variants.

This imputation process is improved by using the GGP-F250 SNP chip. The 200,000 DNA variants on this chip are located in genes, not evenly spaced like mile markes, and are at lower frequencies in cattle breeds. If we are trying to impute rare variants, having rare DNA variants on our SNP chip should help us do this imputation.

The GGP-F250 chip contains DNA variants that change the make up or length of proteins encoded by genes.

Most of the amino acid substitutions (protein sequence changes) are very rare in the population. They are likely to be under selection because they are harmful not helpful. [Evolution in action!] These rare amino acid substitutions may be responsible for hybrid vigor; when we cross two animals from two different breeds the progeny are never carry two copies of these bad amino acid changes. Thus, these crossbred progeny perform better than expected base on the parental averages.

There are about 2,200 DNA variants that we should have seen has homozygotes (two copies). One reason is that the DNA variant is not genotyping correctly. Even when we correct for lots of statistical tests, we see 1,772 variants that we never see as homozygotes (two copies). For many of these variants that appear to be lethal, the SNPs in the surrounding DNA are also not inherited in patterns that we would expect (deviations from Hardy-Weinberg equilibrium).

"We can now look at the things that are actually changing proteins," Taylor stated.

Decker's Take Home Message
The GGP-F250 chip is going to be a great tool for scientists. The GGP-F250 will allow scientists to create new tools for cattle breeders to use to select better cattle.

Further, it appears there are many more lethal variants causing embryonic loss than we recently expected.

The IGS Implementation of BOLT

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.

Hybrid models allow

  • Marker selection models
  • multiple components i.e. maternal effects
  • Multiple traits different markers for different traits
  • Extral polygenic effects
  • MSRP approach (identifying SNPs with effects across traits and breeds)
IGS analysis enhancements and refinements
  • Superior marker effects model
  • Superior accuracy computation
  • New stayability approach
  • New breed effects model
  • Carcass traits solved together with birth weight
  • New method for external EPDs
Decker's Take Home Message
The use of a hybrid model is simply improving methods for computing EPDs. These new predictions will be looked at and scrutinized by many sets of eyes. The breed associations and their partners know how important accuracy and reliability are. 

You may understand very little about this post. There are no boogie men or tricks with this method. It is simply a better way to estimate accurate EPDs from data. 

Monday, June 6, 2016 Monday: EPD Basics and Definitions

EPDs represent the genetic components of an animal’s phenotype that are expected to be passed on to the next generation. Studies have shown that using EPDs are seven to nine times more effective than selecting based on actual phenotypes. This fact sheet will assist readers in understanding how to interpret EPDs and breed averages, and be able to use percentile ranks in order to identify potential sires that fit the desired breeding objective.

Please see the fact sheet for more information.