Archive for Genetics

Dairy Cattle Genetics: Are we breeding cows for the correct environment?

What does a bull’s daughter profile reveal? A description of how the daughters are expected to perform in an intensive barn-housed environment. That works for temperate climates where there is winter, machinery for harvesting forages and cheap fossil fuels. However, what about areas, where only grasses can be grown? Are today’s dairy genetics suited for heat, new bugs and grazing?

The World is Changing

Our dairy cows, developed in north central Europe, operate best in temperatures -20C to +22C ( -5F to 72F). In the 21st century, there are many new factors at play as we breed cows for a variety of environments. Some of these factors include:

  • Climate Change: Predictions are that North America will be 5F warmer by 2050. Dairy cows, like humans, will need to be able to operate optimally at higher temperatures. It will be a significant added cost to keep cows cool for more than half the year. Heat resistance in cattle will be an important characteristic in the future.
  • Land Use: Around the world land for cities is gobbling up vegetable, grains and fruit lands. In turn those crops will push forages for livestock on to land only suitable for grasses or pasture.
  • Regions of Population Increase: The next 2B people, bringing the world to 9B, will be in Asia. Dairy cows there will need to be able to pasture the hillsides and floodplains.
  • Diseases / Insects Resistance: Hot climate and non-temperate climate diseases and insects will add stress to a cow’s life.
  • Fossil Fuel Usage, Machinery and Technology: All of these will become costlier. This will have a significant effect on farms without high cow/heifer numbers. The current trend to replace the cost of labor with technology will continue. Many producers will have cows harvest the forage instead of machinery doing it.
  • Consumer Opinion / Support: The world is no longer about farmers producing food and consumers accepting what is in the store. Consumers are making their needs and requirements known and, in the future, will put many more stipulations on the food they buy. Sure, the milk will be wholesome, but animal welfare, use of drugs on animals, feeds fed to cows, natural environments and many more items will be dictated by consumer understanding. The customer is always right, and they will only buy products that meet their specifications.

As with all things, it comes down to economics. The need to include and the relative importance of these and other factors in genetic indexing and breeding schemes will take time to become a reality. Cows will need to take care of their needs by themselves as much as possible. That also includes nutrition, health, welfare, … and intelligent robots everywhere.

Breeding Must be Ready

Our one-size-fits-all dairy cows are not ready for coping with and prospering under some of the above and other factors. It will take planning and implementation for dairy cattle breeders to be ready with adapted breeds or blood lines. It is hard to look long term when the current cost of production (COP) is not being exceeded by farm gate price in many dairy countries, but the future COP on dairy farms must be addressed by both progressive breeders and breeding organization. First come the ideas, then the research, then the development and finally the application.

A Breeding Goal – A Cow that Manages to Her Own Needs.

We already are breeding for the cow that, on her own, visits the milking machine. Now can we breed the cow that harvests her forage, resists diseases and infections and does it at optimal levels when the thermometer reads 90+F (32+C). Oh yes and she needs to do all that and get back in calf within 80-100 days after her previous calving.

Currently we do not have farm data to use in developing genomic ratings for sires and cows for their ability to forage and exist in tomorrow’s hotter world. So, it will be some time before we can rate and select animals genetically for the traits associated with grazing and a warmer planet.

Some genetic matters that are being worked on include: Slick hair gene, where animals with that gene cope better in hot climates; Tick resistance has yet to be successfully introduced into dairy cattle; Fertility (cow and heifer) is presently receiving much research study; Calf livability and scour resistance is being worked on but with only very limited farm data it is almost impossible to genetically rank sires for these matters.  Without devices that attach to cows it is not possible to measure intake for pastured animals. Information on feed conversion efficiency genetic indexing for animals consuming harvested forages was covered by the Bullvine (reference) but that is for machine harvested forage not for grazing animals.

Information Currently Available to Breeders

Health and wellness genetic ratings have become available for milk cows in the past 3-4 years and for calves and heifer in the past year. More health and disease will be added in the future.

That still leaves research into which sires are genetically the best in terms of heat resistance and forage intake from pasture.

Regarding the ability to cope with tropical temperatures relatively little new information has been found to help breeders. Some breeders rely on their understanding of added body capacity for lungs, solid red color, crossbreeding (i.e. using the Gyr breed from India) and raising heifers at higher altitudes to develop larger lungs. There are no sire indexes for breeders to use. Research needs to be done and field data captured so that more is known on the genetics of dairy cattle coping with tropical conditions.

On the matter of which sires produce daughters more suited to grazing, there are currently three indexes provided by organizations. These indexes are:

  • GM$ (Grazing Merit is published by CDCB) – it includes the same traits as NM$ (Net Merit) but puts 253% as much emphasis on fertility, 85% as much emphasis on production traits and 59% as much emphasis on PL and LIV as NM$ does. The AIPL-USDA research shows that grazed cows need to calve annually, do not need to produce as much fat and protein volume and have fewer longevity and livability problems as compared to housed cows. As in NM$, higher milk volume, higher SCS and higher body weight all receive a negative weighting in GM$. The trait emphasis for GM$(2018) follows:


GM$ = 38% Yield* + 24.5% Fertility* + 16% Type* + 13.5% PL/LIV/Health* + 3.5% SCS + 4.5% CA*

                (* indicates that a number of traits are combined to create the category.  Calving Ability is 4 traits related to calving.)

Table 1: Top Ranking US Holstein Sires for GM$ (Grazing Merit)

Daughter Proven Sires   Genomic Sires
        GM$ NAAB Code Name           GM$ NAAB Code Name
893 203HO1468 Delta   1016 551HO3529 Charl
880 29HO17553 Josuper   990 11HO12174 AltaExplosion
874 7HO12600 Modesty   975 11HO12157 AltaLawson
827 151HO0681 Rubicon   972 29HO18611 Skywalker
827 151HO1602 Director   947 29HO18682 Colorado
815 1HO10396 Cabriolet   939 29HO18693 Crimson
797 7HO12266 Yoder   935 1HO13404 Samsung
787 7HO12021 Ponder   932 29HO18708 Kenobi
785 1HO11327 Gatekeeper 932 29HO18296 Achiever
783 7HO13250 Jedi   916 29HO18633 Roxbury
  • GrazingPRO(Published by Select Sires Inc.) – SSI designates their sires as GrazingPRO™ based in their GM$ rating and requiring that the DPR is >+3.0, Stature is <+0.5, Fat% is positive and Protein% is positive.
  • GrazingPro™ (Published by Semex) – Semex designates their sires as GrazingPro™ and thereby Pasture Perfect for sires that will maximize component yield and put a focus on health and reproductive traits to ensure highly profitable, long-lasting animals with limited problems. These sires will also produce easier calvings and darker colored calves.
  • Outside of North America both Ireland and New Zealand prove their sires on grass-based feeding systems so their EBI (Ireland) and BW (New Zealand) indexes rank sires with consideration of grazing.

The Bullvine Bottom Line

Dairy cattle being fed on grazing systems and living in warmer and warmer climates will be part of our industry’s future. To date there is only limited genetic information, based on assumed trait emphasis, available for breeders to use if they choose to graze their cattle or farm in regions having heat and humidity. Research and genetic evaluation centers need to address these topics.



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The Genetics of Feed Efficiency in Dairy – Where are we at?

Feeding dairy animals has gone from least cost to balanced rations to now where Income Over Feed Costs is king on a herd basis. Producers are now wanting to know which animals are the more efficient at converting feed to growth or milk. Since feed intake in dairy cattle has been considered to be too costly to measure, progeny testing programs have not provided sire daughter feed efficiency indexes.

Breeders want more for less. More growth and more milk from less feed. In this article, The Bullvine do an overview on where the genetics of feed efficiency is at.

Why is Feed Efficiency Important?

With feed costs being 50-60% of the total cost for the milking herd and an even higher percentage for calves, heifers and dry cows, it means that the managers of tomorrow need answers on the genetic side of feed efficiency to help attain future success. The margins in dairy farming are narrow and are likely to remain so into the future. Genetics, along with other disciplines, need to advance efficiencies.  Of course, this not just a “cow” issue, it is also a crop production, harvest, storage and processing issue.

 In other livestock industries, poultry, swine and beef, the genetics of feed efficiency has become a must-have. Dairy is behind in using genetics to advance feed conversion efficiency.

In dollars, saving $0.25 in feed costs per animal per day without reducing income, amounts to $83,500 per year for a 600-cow herd, that milks 500, has up to 100 dry cows and raises their own heifers as herd replacements. That’s not pocket change and if by genetic selection that $83,500 can be achieved – that’s significant.

Tracking Feed Efficiency

Many ways of tracking feed intake have been tried by researchers and companies to monitor animals. They include dry matter intake (DMI), residual feed intake (RFI), feed saved, time at the feed bunk, head movements during feeding, rumination activity and the use of novel electronic devices. But none, as yet, have been found to be the answer to the question – “Which sires produce the daughters that take less feed to produce the same milk revenue?”

Current State of Public Research Results

Dr. Kent Weigel (University of Wisconsin-Madison) on March 24, 2018 presented a very comprehensive report to the Northeast (Cornell) Dairy Production Medicine Symposium on a three-country dairy feed efficiency project (eleven research institutions with nine from the United States, one from Canada and one from The Netherlands) that analyzed numerous research projects and in each project the cows’ intake and performance.  A synopsis of the facts that he reported include:

  • The RFI data available, on approximately 8,000 cows, is not enough to provide accurate sire proofs. Heritability was found to be 19%, but the reliability of sire indexes is only 20-25%. Many, many more cow feed intake records are needed to go along with production and other data.
  • DMI information is closely associated with level of production and cow size but it is not a good indicator of the genetic ability of a sire’s daughters for saving feed costs without altering yield.
  • The ‘feed saved’ research results from Australia provide an interesting concept but, there again, much more data is needed, in order to provide sire genetic indexes.
  • To get to the point of sire genomic indexes for feed efficiency will take time. First of all, a broad-based reference population is needed. Breeders are accustomed to genomic indexes being 65%-75% REL, so the current 20-25% REL for feed efficiency is not high enough.
  • Currently high and low feed efficient cow families have been identified with some level of confidence. So there is progress being made in arriving at useful information.
  • The three country international project, studying dairy cow feed efficiency, will continue including trying out new measurements and devices but breeders cannot expect answers any time soon.

General Recommendation by A. I. for Selecting Sires for Feed Efficiency

The general recommendation from A.I. for breeders who want to move their herds forward, genetically, for feed efficiency has been that they place emphasis on sires with higher fat and protein yield indexes but that also only have average to below average size/frames proofs. National total merit indexes and A.I. stud composite indexes (TPI, NM$, JPI, LPI, Pro$, ICC$, …) usually only place about 50% of their emphasis on those three traits, so changing a herd genetically for feed efficiency will not occur quickly. And it will only occur if the top-ranked sires for those three traits are used extensively to sire the next generation.

Four Organization are Stepping Out and Publishing Feed Efficiency Sire Ratings

There are four organizations that are publishing sire ratings for feed efficiency. A closer look at their information, currently available to breeders, follows:

Holstein US Predicts Feed Efficiency by Using Other Genetic Indexes

All sires on Holstein US various sire listings contain a ‘FE’ (feed efficiency) column. It is an estimate of the net profit a milk producer can expect to receive. Factors included in ’FE’ are: dollar value of extra milk produced, feed costs of the extra milk and extra maintenance costs for large cows. This is the formula that Holstein US uses:

FE = (-0.0187 x Milk) + (1.28 x Fat) + (1.95 x Protein) – (12.4 x Body Weight Composite)

Table 1 – Top FE Proven Holstein Sires

Bull NAAB Code           FE*          Milk            Fat     Protein Body WC          SCS             PL             FI          PTAT           TPI          NM$
1. Josuper 29HO16553 260 3442 114 98 1 2.83 6.1 -0.1 1.42 2806 998
2. Princeton 1HO11881 252 2669 107 84 -0.16 2.77 3.9 -4.6 1.7 2562 842
3. Denver 151HO0690 240 2365 108 76 0.15 2.99 2.5 -0.3 2.14 2695 787
4. Peterpan 7HO12255 235 2226 108 75 0.62 2.96 2.2 -1.5 1.02 2459 708
5. Cabriolet 1HO10396 234 1064 101 53 -1.73 2.89 6.2 1 -0.03 2562 895
6. Maguire 7HO12256 230 1580 116 61 0.62 2.76 3.9 -1.9 1.39 2553 805
AVG Top 15 FE Sires 228 1972         101** 69 -0.09 2.87 4.6          -0.5** 1.54 2625 826
AVG Top 15 TPI Sires 206 1961          86** 68 -0.01 2.86 4.9          0.9** 1.82 2655 807

* Data Source – Holstein US Official Top 100 TPI List of Proven Sires (April ’18)
** Top 15 sires for FE and TPI differ significantly in averages for fat yield (Fat) and fertility (FI). FE sire are superior for fat yeild but inferior for fertilty. As well TPI sires have somewhat higher type (PTAT).

In Table 1 the only points of difference between the Top 15 FE and TPI sires are in the traits FE, Fat Yield, and FI (fertility index). The FE sires are inferior to the TPI sires for fertility (FI), but superior for FE and Fat Yield.

It is worth noting that a feed efficiency index in this context has no direct measurement of feed intake.

Select Sires Uses Indexes and Designates Sires as FeedPRO®

Select Sires identifies the top 20% of their sire lineups as FeedPRO® Sires. The purpose of this selection tool is to highlight sires for producers who are concerned about feed costs and want to improve overall profitability. FeedPRO® is based on US and UK research that found that production, body traits, body condition score and daughter fertility accounted for 90% of the difference in feed intake between animals. Sires that qualify are designated as FeedPRO® Sires but are not assigned an independent index.

Third party researcher reviews were sought by Select Sires in FeedPRO®’s development. Dr Chad Dechow (Penn State) in his analysis found the “FeedPRO® Sires have an advantage, on average, of $0.13 to $0.18 (USA$) per day in income over feed cost when compared to the average active A.I. sire”.

Table 2 – Top SSI FeedPRO® Holstein & Jersey Sires ranked by NM$

Bull NAAB Code          NM$         Milk          Fat     Protein           PL          DPR        PTAT         TPI Codes
(Holstein Proven Sires Designated FeedPRO® )*
Modesty 7HO12600 927 1012 90 56 6.7 1.3 1.93 2748  
Yoder 7HO12266 863 1243 107 53 5.1 -0.3 1.9 2690    A2A2
Jedi 7HO13250 825 2480 70 82 6.5 1.6 2.02 2716  
Tetris 7HO11985 793 2074 90 64 5.6 -0.7 0.69 2526  
Trenton 7HO13094 782 495 79 48 6.7 0 1.56 2562    A2A2
Montross 7HO12165 781 2910 80 85 4.1 -0.5 1.94 2641    A2A2
All 16 Designated Sires* 740 1542 73 56 5.3 0.7 1.41 2546  
(Jersey Proven Sires Designated FeedPRO® )*           JPI  
Chrome 7JE5004 539 1143 71 43 4 -0.9 2.3 180  
Jammer 7JE1254 493 1232 71 34 3.9 -0.7 0.7 139  
All 4 Designated Sires* 481 956 68 39 3.2 -0.7 1.43 150  

* Only the top 20% of SSI sires according to more income from less feed, high production, moderate size, long-term fitness and productivity are designated FeedPRO® 
** Note: These FeedPRO® sires always high high production and longevity but are variable for fertility and type.

The sires listed in Table 2 are among the current top sires that Select Sires has available based on the TPI and NM$ ranking systems.

Table 3 – Correlation of FeedPRO® and Other Indexes.

    Milk     Fat    Protein       NM$      TPI
0.54 0.7 0.7 0.91 0.9

* Data Source – Select Sires Inc Program Description for FeedPRO®

These correlations are moderately high. They show that FeedPRO® is aggressively selecting for increased production, but still, it identifies a noticeably different group of sires at the very top of the lists.

CRV Uses Genetic Indexes and Feed Intakes to Predict Lifetime Efficiency, and Feed Saved

CRV partnered with Wageningen Livestock Research to develop a large dataset of genotyped cows with individual feed intake measurements and then conducted the genetic analysis. From the results of this work CRV has developed two indexes relating to efficiency:

  1. a) ‘Better Life Efficiency’ – Its main components included the breeding values for fat yield, protein yield, longevity and feed intake. CRV has determined that, across a genotyped cow population of >60,000 cows, the top 25% of cows for life efficiency produced over 13,000 kgs. more milk per lifetime than the poorest 25% of cows. Ratings are published for every bull of every breed.  and
  2. b) ‘Saved Feed for Maintenance’ – Cows with a positive breeding value for Saved Feed for Maintenance need less than an average amount of feed for their body maintenance and therefore convert feed into milk more efficiently. This breeding value indicates how much feed (in kg dry matter per day) is saved because the cow is more efficient than average. It has been added to the Dutch/Flemish total merit index, NVI.

Table 4 – Top BLE (and SFM) Sires

US Sires
Sire Name and Code/ID BLE**    SFM***  F + P (lbs)         NM$           PL         DPR
1. Nash 97HO41910 19 0.64 130 877 7.4 0.8
2. Ligero 97HO61744 19 1.22 145 811 5.3 0.6
3. Dirk 97HO41786 17 0.76 117 763 5.7 2.1
4. Shero 97HO41974 16 -0.33 129 841 7.6 2.4
5. Audible 97HO41830 15 0.48 170 846 4.4 -0.4
6. Exclusive 97HO41855 14 0.89 117 820 6.7 3.1
Netherland Sires
Sire Name    BLE**    SFM***  F+P (kgs) Longevity   Fertiltiy  
1. Monaco NL937658659 25 1.77 167 847 97  
2. Empire NL729539557 18 0.85 123 1195 104  
3. Jethro NL872395552 18 1.07 141 855 101  
4. Locker NL872395552 18 1.05 138 832 102  
5. Treasure NL946221484 17 0.52 103 1248 108  
6. Smiley RC DE0539391976 14 0.82 114 932 102  

* Feed Efficiency has two indexes composing it – Beter Life  Efficiency and Saved Feed for Maintenance
** Better Life Efficiency uses the genetic indexes for fat yield, protein yield, longevity andfeed intake.
*** Saved Feed for Mantenance is the feed saved expressed in kg dry matter pe day
Longevity is expressed in days of productive life
Fertility has average value of 100 and STD Dev of 5.

The CRV sires in Table 4 give breeders a variety of pedigrees to choose from and are high production rated.

STgenetics Conducts Progeny Tests for Feed Intake and Performance to Predict Feed Efficiency

STgenetics has been capturing individual animal feed intake information for the extensive group of heifers and cows they own or control. From that feed intake data, along with all genetic indexes and DNA profiles, they have developed a program called ‘EcoFeed™’.

EcoFeed™ is more than simple feed efficiency for milking cows. It is a continuously growing database that monitors the animal’s growth and productivity throughout its entire lifetime from calves, to heifers, to milking cows. Feed efficient animals are expected to use fewer feed resources and convert feed more efficiently while creating less waste, manure, methane and CO2 per unit of production. All of these outcomes should greatly assist in making future dairying more viable, more sustainable and an environmentally friendly industry.

Some of the key components of EcoFeed™ sire indexing include: 1) it is a multi-factor efficiency index that encompasses the entire lifespan of a cow; 2) it is based on modern technology that measures daily individual animal consumption; 3) it includes a progeny testing program, the gold standard of dairy cattle genetic indexing; and 4) once proven, STgenetics sires reach high levels of reliability for EcoFeed™.

STgenetics reports that “To qualify as an EcoFeed™ sire, a bull’s progeny must be genomically tested and complete feed efficiency testing.  Ecofeed™ rankings are based on a 100 base system where every five points, over 100, equals one pound less feed that a sire’s progeny can be expected to consume each day while producing the same amount of milk as their peers.”

Table 5 –  Top Six ST genetics EcoFeed™ Progeny Tested Holstein Sires

Sire NAAB Code EcoFeed EcoFeed REL Milk Fat Protein BWC SCS PL FI PTAT FE TPI NM$ Codes
1. Charismatic 513HO03092 118 69% 850 81 27 -0.44 2.8 6 0.5 1.6 146 2468 709  
2. Comanche 147HO00500 115 53% 704 85 26 -0.67 2.94 5.7 1.1 0.88 155 2390 689  
3. Author 151HO00628 107 42% 543 35 32 1.25 2.92 1.3 1.3 1.69 82 2180 375  
4. Detour 513HO03091 106 64% 1342 73 51 -0.81 2.77 5.6 1.4 1.61 178 2596 795   A2A2
5. Missouri 147HO02462 106 44% 1888 52 54 -1.15 2.68 5.6 0.3 1.74 151 2487 707  
6. Mador 151HO00664 106 43% 1968 36 40 0 2.91 2.3 -1.1 1.91 87 2177 402  
15 Sires with REL >40% 106 53% 1187 62 40 0.02 2.81 4.9 1.1 1.52 134 2415 630  3 are A2A2

1. EcoFeed™ reliabilities are only moderate compared to other traits but they are double the reliabilities for other FE rating systems. As more research is conducted and more animal data is captured, the reliabilitites will increase.
2. Production and longevity focused dairy breeders want productive, fertile, longer lived and moderate sized cows.  The averages for fat, protein, BWC, SCS , PL and FI of the EcoFeed™ sires all should assist in achieving breeders needs.

In Table 5 full brothers, Charismatic and Comanche, stand out ahead of other STgenetics sires for EcoFeed™. Both have good reliabilities with considerable daughter information included, and neither is yet four years old. It appears that the story has just begun for EcoFeed™ sire indexing given that, every week,  STgenetics captures more feed intake and performance data on milking first lactation cows.

Table 6 ST’s correlations table

         TPI         NM$         CM$        Milk          Fat     Protein          PL         DPR         FE
0.02 -0.01 -0.01 0.06 -0.01 0.06 -0.05 -0.08 0.01

* Data Source – ST Genetics information materials

Table 6 reports no correlations between EcoFeed™ and other traits. We would not have expected that as Table 3 shows moderate to high correlations for FeedPRO® with other traits. But when we consider that EcoFeed™is more than just feed efficiency, it may not be as surprising as it first appears. Definitely, breeders will be following the research that STgenetics is doing on lifetime efficiency. It should be noted that the concept of lifetime efficiency is also what CRV bases its ‘Better Life Efficiency’ index on.

 The Bullvine Bottom Line

It is very encouraging to see that organizations have recognized the need to put weight on feed efficiency in their genetic programs.  The potential for increased profit is thereby using genetic indexes to save on feed costs.

 Now is the time for all dairy breeders to study the matter of feed efficiency sire indexing and decide how they will incorporate it into their breeding program. Dairy cattle breeders must use feed efficiency sire ratings now (2018-2019) for milk producers to be able to benefit tomorrow.





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The proof is in your numbers

Let us show you…

We can show you the proof that genetics are one of the cheapest investments you can make to improve the profitability and efficiency of your herd. Proof sheet numbers may seem unclear or unrealistic. So we break them down to see how they translate within your own herd.

When you use a herd management software program, we can create a genetic assessment of your herd to see if genetics really work on your farm.

Do your 2-year-olds give as many pounds of milk as their sires’ proofs predict? Do these cows become pregnant as quickly as their sires’ DPR numbers suggest? And do daughter stillbirth numbers prove to be accurate indicators of DOAs?

When we do a genetic assessment for your herd, it’s important to realize that we only take into account first-lactation animals in order to minimize environmental effects. Phenotype equals genetics plus environment. So when we eliminate – or at least minimize – environmental influences, the actual performance differences we see are due to genetics.

We want to show you how those proof numbers translate to more pounds of milk, more pregnancies and fewer stillborn calves. So here, we take one of our real DairyComp 305 analyses of a real 1,500-cow herd for answers.

The proof in genetics: PTA Milk (PTAM)

We start with PTAM, which tells us how many more pounds of milk a first-lactation animal will produce compared to herdmates on a 305-day ME basis. We set out to find if higher PTAM values on this farm actually convert to more pounds of milk in the tank.

In this example, we sort all first-lactation animals with a known Holstein sire ID, solely on their sires’ PTAM values. We then compare that to their actual 305-day ME milk records.

As Table 1 shows, based on genetics, we expect the top 25 percent of first-lactation heifers to produce 1,541 more pounds of milk on a 305ME basis than their lower PTAM counterparts. In reality, we see a 2,662-pound difference between the top PTAM animals and the bottom in actual daughter performance.

Table 1: How does selection for PTAM affect actual 305ME performance?      
  # of cows Avg. Sire PTAM Avg. 305ME Production
Top 25% high sire PTAM 178 1508 44080
Bottom 25% low sire PTAM 171 -33 41418
Difference   1541 2662

This means that for every pound of milk this herd selects for, they actually get an additional 1.69 pounds of milk. So these first-lactation animals are producing well beyond their genetic potential.

Why do they get more than expected?

When we do most on-farm genetic assessments, we find that the 305ME values closely match the predicted difference based on sire PTAM. However, in this example, the production exceeds what’s expected by more than 1,100 pounds.

We often attribute that bonus milk top-level management, where genetics are allowed to express themselves. This particular herd provides a comfortable and consistent environment for all cows. All of these 2-year-olds are fed the same ration, housed in the same barn and given the same routine. At more than a 40,000-pound average 305ME, this is certainly a well-managed herd, which allows the top genetic animals to exceed their genetic production potential.

Perhaps even more importantly, the identification in this herd is more than 95 percent accurate. Without accurate identification, this analysis simply won’t work. That’s because some cows whose real sire information puts them in the bottom quartile will actually appear in the top quartile and vice-versa.

The proof in genetics: Daughter Pregnancy Rate (DPR)

Our next example from the same 1,500-cow herd shows the benefits of selecting for DPR as part of a customized genetic plan. In the same way as the previous example, we sorted the first-lactation animals, this time based exclusively on their sires’ DPR values, to compare the top versus bottom quartile of 2-year-old cows.

Table 2. How does selection for DPR affect actual pregnancy rates?      
  # of cows Avg. Sire DPR Actual 21-day preg rate
Top 25% high daughter pregnancy rate 176 2.1 25%
Bottom 25% low daughter pregnancy rate 173 -2.2 19%
Difference   4.3 6%

An increase of one point DPR is equivalent to a one-point jump in pregnancy rate, or in other words, four fewer days open. In this herd, we’d predict the top DPR cows to have a pregnancy rate about four points higher than the low DPR group. This means their top DPR cows, on average, become pregnant about 17 days sooner.

What this well-managed herd actually realizes on their first-lactation animals is once again, beyond expectations. Top DPR cows have a six percent higher pregnancy rate than the low DPR group. That six percent difference equates to 24 fewer days open – more than one full heat cycle!

The proof in genetics: Daughter Stillbirths (DSB)

Calves born dead are an economic loss to a dairy. With this in mind, we set out to determine wanted to find proof in DSB figures in this herd. To clarify, a bull’s DSB value tells us how likely his daughters are to give birth to a stillborn calf. A higher DSB means a higher probability for future stillbirths.

Table 3: How does selection for DSB affect actual DOA rates?      
  # of cows Avg. Sire DSB DOA%
High daughter stillbirth 183 10.4 13%
Low daughter stillbirth 146 5.1 3%
Difference   5.3 10%

We know this farm takes extra care in keeping accurate and thorough records on calving ease and DOAs. Because of that, we know their genetic assessment on DSB’s should be accurate.

Here, we sorted all first-lactation animals based on their sires’ DSB values. In this herd, the females with the lower, more favorable DSB values gave birth to 10 percent more live calves than the first-lactation animals out of high DSB sires!

Genetics are real

In well-managed herds with accurate records, we can analyze additional traits. We can break down the differences to show your own herd’s genetic proof in productive life, protein, fat and sire stillbirths.

The proof in genetics is real, and it’s powerful. But farms cannot see this proof if their animals are not identified correctly. True analysis of how genetics work in your herd cannot be done without accurate and precise identification and records.

The traits we’ve analyzed in this example can make a great financial impact for your farm, with very little investment. Each of these examples clearly demonstrates the following:


  1. The proof in genetics is real.
  2. In well-managed farms with herd management software programs, we can show your own herd’s proof of performance from genetics.
  3. When you provide a consistent, comfortable environment, and maintain accurate identification records, you may see animals produce and perform well beyond their genetic expectations.
  4. Work with your Alta advisor to set your own customized genetic plan with emphasis on the traits that match your current plans and future goals. By doing so, you will maximize the proof in genetics through increased herd profit and efficiency.

Source: Alta Genetics

Breeding for Kappa Casein to Increase Cheese Yield

The Bullvine seldom talks about the processing of milk into product when it comes to writing about the breeding of dairy cattle. We expect it happens even less frequently that dairy cattle breeders consider the yield their processor obtains in products from the milk they ship. The different kappa casein genotypes found in today’s dairy cattle can have a significant effect on the volume and quality of cheese produced from milk. Here are some interesting details that we found from our research on this subject.

The Situation

Dairy cattle are evaluated for their ability to produce the percentage of protein in milk and the total protein yield.  Milk processors find that: 1) some milks clot quickly, its cheese is firm and produces the most cheese per unit of milk; 2) some milks clot, but not quickly, and have varying degrees of firmness and produces 10%-15% less cheese, and 3) some milks do not clot. Cheese makers are not prepared to buy milk that fits into the latter category. Studies from Europe and North America have found a strong association between the kappa casein genotype BB and milk that clots quickly, produces firm cheese and has a high volume of cheese yield.

The situation of poor or non-clotting milk came to international attention in the 1970’s when Italian cheese makers were no longer able to make their cheeses from the milk from certain farms. After studying the situation, it was determined that some daughters from North American Holstein sires produced milk that was not desirable for cheese making.  In-depth study identified the problem to be with the kappa casein produced by these non-Italian sires’ daughters.

Kappa Casein Alleles

At least nine alleles have been identified for kappa casein. Specifically, three alleles, A, B, and E, dominate in global dairy cattle populations. Initially, it was thought that two alleles, A and B, were the main ones present in dairy cattle. However, a third allele, E, was found to exist approximately 10% of the time. E is the allele associated with the milk that does not clot to make cheese.

Cheese Yield by Genotype

A synopsis of the published findings on kappa casein genotypes follows:

  • Cheese from the milk of BB cows’ clots 25% faster and is twice as firm as cheese made from AA cow’s milk.
  • Milk from BB cows produces 1.0- 1.5 lbs (about 10%) more cheese per cwt of milk than milk from AA cows.
  • Milk from AB cows is about midway between BB and AA cows for clotting speed, firmness, and yield.
  • Milk from EE cows does not clot and is not suitable for cheese making
  • Milk from AE cows is also considered by most cheese makers to be unsuitable.
  • The literature is not informative on the properties of milk from BE cows. There are suggestions that it may be similar to milk from AA cows when it comes to cheese making.
  • A 1985 study by Okigbo, Richardson, Brown and Ernstrom found that milk with impaired clotting properties was not improved by mixing it with an equal amount of well-clotting milk.

General Stat’s with respect to Kappa Casein

Initially, our focus was on kappa casein relative to North American dairy cows. However, we found interesting information from published studies in Italy, France, Estonia, The Netherlands, Scandinavia, and Turkey.  Milk for cheesemaking is important in these countries because from 40% to 75% (Italy) of the national milk is used to make cheese. Some additional facts include:

  • About 10% of North American Holsteins are BB.
  • North American Jerseys have a significantly higher percent BB than do Holsteins. Likely the result heavy use of two BB Jersey sires from twenty years ago.
  • Globally Brown Swiss are reported to be 35% BB.
  • Holsteins in Europe have between 15% and 23% BB
  • Water Buffalo are almost 100% BB. India, the world’s largest milk producing country, gets half its milk from Water Buffalo.

What About Current Holstein Sires?

Table 1 is the frequency of occurrence for the kappa casein genotypes for the top North American proven or most used Holstein sires.

Table 1 – Kappa Casein Genotype Profiles for North American Holstein Sires

Grouping Total Sires BB AB AA BE AE EE
Most Registered Daughters – USA* 20 2 6 4 4 4 0
Most Registered Daughters – Canada** 20 2 8 5 0 5 0
Top Proven TPI Sires *** 20 4 8 6 1 1 0
Top Proven NM$ Sires *** 20 2 7 6 2 3 0
Top Proven CM$ Sires *** 20 2 6 6 2 4 0
Top Proven LPI Sires *** 20 6 6 5 0 3 0
Top Proven Pro$ Sires *** 20 6 6 6 1 1 0
Average (%)   17% 34% 26% 7% 16% 0%

* For time period two weeks prior to April 03, 2017
** Based on registrations in 2016
*** April 2017 Proofs

Some points that should be noted from this table include:

  • The sires in Table 1 have a higher occurrence of BB (17%) than in the general cow population (10%).
  • There are no EE sires but the 16% level of AE should concern breeders and A.I studs when it comes to cheese firmness and lost potential yield in the future.
  • The frequency of BB & AB is higher in the Canadian sire proof groupings than in other groupings.
  • The overall 38% gene frequency of the B allele gives hope that genetic progress to eliminating E and reducing the A allele should be possible in the not too distant future.

Some BB daughter proven sires that topped or were near the top of the groupings in Table 1 are listed in Table 2.

Table 2 –  Leading BB Daughter Proven Sires

Sire NAAB Code Sire Stack Rank
Aikman 250HO01043 Snowman x Baxter x Goldwyn #2 LPI, #20 Pro$
Aikosnow 200HO03914 Snowman x Baxter x Goldwyn #4 Pro$, #14 LPI
Balisto 29HO16714 Bookem x Watson x Oman #20 TPI
Bob 7HO11752 Bookem x Oman x Manat #8 TPI
Camaro 250HO01109 Epic x Freddie x Lucky Star #9 LPI, #19 Pro$
Donatello 7HO11525 Robust x Planet x Elegant #14 US Registered, #14 CM$, #17 NM$
Dragonheart 7HO12111 Epic x Planet x Elegant #1 Pro$, #4 LPI
Facebook 200HO03753 MOM x Airraid x Shottle #20 CAN Registered
Impression 200HO00560 Socrates x Potter x Durham #1 CAN Registered
Living 200HO06573 Epic x MOM x Shottle #12 Pro$, #19 LPI
Punch 7HO11207 Boxer x Oman x Manat #13 Pro$, #18 LPI
Rookie 7HO11708 Bookem x Bronco x Shottle #9 TPI
Trenton 7HO13094 Sterling x Robust x Planet #9 CM$, #12 NM$

One BB genomically evaluated sire is in the top registered USA sire grouping in Table 1:

  • Jedi                       (7HO13250)                             (Montross x Supersire x Bookem)                #8 US Registered

What About Genomic Sires?

With over half of the semen being used coming from genomically evaluated sires it is important to consider this category. In some herds, only genomic sires are used. However, to summarize the kappa casein genotype frequency for this group is not reasonable as many of the top sires on the April 2017 listings are too young to have semen available yet. As well the usual cautions that The Bullvine gives apply do not overuse any one genomically evaluated sire as their indexes range from 55% to 75% REL. Moreover, take into consideration the future inbreeding coefficient of these sires as a breeder may already have those sires close up in their animals’ sire stacks.

Some genomically evaluated Holstein and Jersey sires that are BB for kappa casein that are worthy of breeder consideration include:

Table 3 – High Ranking BB Genomic Evaluated Sires

Sire NAAB Code Sire Stack          CM$          NM$      TPI/JPI          LPI         Pro$
Achiever 29HO18296 Yoder x Altafrido x Robust 1062 1023 2788 3332 2902
AltaCraig 11HO11749 Stoic x Supersire x Massey 842 806 2643 3188 2498
AltaForever 11HO11821 Silver x Freddie x Obrian 774 746 2642 3313 2767
Baylor 551HO03419 Delta x Bob x Uno 874 846 2735 3379 2722
Cam 7HO13592 Jedi x Moonray x Bookem 893 876 2727 3263 2709
Cardinals 200HO10668 Yoder x McCutchen x Robust 804 785 2682 3108 2155
Galahad 200HO10755 Penmanship x Jacey x McCutchen 732 678 2636 3377 2695
McGuffey 551HO03350 Montross x Robust x Mac 834 820 2683 3199 2657
Medley 29HO18343 Yoder x Balisto x O-Style 986 966 2779 3447 2962
Powerfull-PP 224HO04510 Powerball-P x Supersire x Colt-P 670 635 2462 2962 2225
Selfie 224HO04273 Supershot x Aikman x Larson 749 734 2561 3231 2561
Yale 7HO13328 Yoder x Altafrido x Robust 836 824 2683 3286 2654
AltaBlitz 11JE01320 Axis x Kilowatt x Karbala 619 593 173 1803 1701
Charmer 29JE04009 Chili x Dividend x T-Bone 630 588 178 2010 1824
Halt 29JE03989 Harris x Hendrix x Redhot 664 628 187 1911 1744
Joyride 200JE10011 Rufus x Paramunt x First Prize 152 139 48 2014 1712
Torpedo 250JE01456 Santana-P x Fastrack x Nathan 408 390 118 1823 1514
Tyrion 203JE01632 Hulk x Action 782 736 231 1755 1587

Take Home Ideas

The Bullvine offers the following ideas for breeders and breeding industry people to consider:

  • Cheese Making: In the future, it is entirely possible that cheese processors will not buy milk from Holstein herds that cannot guarantee that their cows are at least a high percentage are BB. Jersey herds and totally BB Holstein herds are likely to be paid a premium for this milk.
  • Niche or Mainstream: In the next five years breeding to increase the percent of BB females will be niche. However, as more and more milk is used to make cheese selection for the B allele and away from the E allele is likely to be mainstream. Selecting sires on total protein without regards to the kappa casein profile of those sires should become a practice from the past.
  • Breeding Animals: Breeders and breeding organizations would be well advised to commence selecting for the B allele when it comes to sire and ET donor selection. An achievable objective would be for A.I. studs to only enter BB and AB bulls into stud starting in 2019. Breeders are advised not to flush any females that are EE, AE and perhaps even BE starting in 2019 or before. Breeders need to ask their semen sales reps for a sire’s kappa casein profile before buying semen. Bull kappa casein profiles are not included in CDCB or CDN files but are most often included in A.I. stud electronic bull files or hard copy catalogs.
  • Research: More research is taking place in many countries of the impact of kappa casein genotype on cheese production. At the University of California (Davis) there are major projects underway on how to use genetic engineering to eliminate the E allele and to fast track changing Holsteins into being BB.

The Bullvine Bottom Line

One characteristic, like kappa casein, cannot rule the breeding, milk production and milk processing industries. However, with a higher and higher percentage of dairy cows’ milk being used to make cheese, breeding for animals with the BB kappa casein genotype can no longer be ignored or thought not to be important. Breeders are advised to ask their semen suppliers for the kappa casein profiles of sires before they purchase semen. Starting immediately sires with EE and AE profiles should be avoided and if the semen is already in the tank then even throwing it out may make good business sense. Because producing females that are EE or AE will delay when premiums may be possible for milk sold for making cheese.



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Recovering lost genetic diversity in Holsteins is focus of professors’ research

Intense genetic selection can have an unintended side effect — the loss of genetic diversity.

There is one cattle breed, in particular — Holstein — that Chad Dechow and Wansheng Liu, researchers in Penn State’s College of Agricultural Sciences, believe needs a bit of help on the genetic diversity front. Thanks to their research, calves recently born at Penn State may help to reintroduce valuable genetic variance.

“If all cows were genetically identical to each other, then there would be no opportunity to select for cows with improved performance,” said Dechow, associate professor of dairy cattle genetics in the college’s Department of Animal Science. “Little to no genetic diversity makes cattle more susceptible to disease and vulnerable to environmental changes.”

And, because Holsteins — known for their distinctive black-and-white markings — produce more milk than any other dairy breed, their health and well-being is important to humans’ health and well-being.

“Milk is important for good health,” said Liu, associate professor of animal genomics. “The efficient production of milk from healthy and fertile cows improves society because we can obtain milk at a reasonable cost and still be confident that farmers are maintaining high levels of animal welfare.” 

Though the Holstein breed dates back 2,000 years to the Netherlands, these cattle are relatively new to America — the first Holsteins were brought to the country in the mid-1850s by a Massachusetts breeder named Winthrop Chenery. He bought a cow from a Dutch ship owner who had used it to provide milk for his crew. It wasn’t long before Chenery was importing Holsteins from Holland because of their exceptional milk production. 

Dechow and Liu wanted to know more about the breed’s history, so in 2014, they teamed with graduate student Xiang-Peng Yue to trace the ancestry of Holsteins in America. Through this research, they learned that nearly all male Holsteins alive today can be traced back to two bulls from the 1960s: Pawnee Farm Arlinda Chief and Round-Oak Rag Apple Elevation. 

“Artificial insemination was really beginning to take off in the 1960s,” Dechow said. “Today, three-quarters of Holsteins result from artificial insemination. Even those born from a ‘natural mating’ usually have a grandfather that was an artificial insemination bull. The widespread use of artificial insemination is what allowed these two bulls to have such a large impact.” 

There is one additional bull from the 1960s that still appears in the male lineage of a handful of sires — a bull born at Penn State named Penstate Ivanhoe Star. He and Pawnee Farm Arlinda Chief share a common male ancestor born in 1890 called Paul De Kol.

While these bulls were responsible for many offspring in the country, they were not the only bulls used for breeding during that era. In fact, thousands of sires from that era have descendants through female lineages. However, over the course of time, the other sires’ lines failed to thrive for several reasons. Penstate Ivanhoe Star is an example.

“He carried two lethal genetic recessives. Once those defects were discovered, many of his male descendants were removed from the population so that the defects would not be propagated so widely,” said Liu, a leading authority on bovine Y-chromosome variations.

This narrowing of the genetic base is not a good thing for Holsteins because it leads to inbreeding, which has the potential to cause genetic defects, poor health and poor milk production.

The researchers then set out on what they thought would be a difficult task — finding descendants of other lineages that existed in the 1960s. Their first call was to the National Animal Germplasm Program in Fort Collins, Colorado, a repository under the United States Department of Agriculture that collects reproductive samples from agriculturally important species. Dechow, who serves as the dairy species chair for the program, thought it would be a good place to start. 

And, he was right — as luck would have it, the repository recently had procured semen from two lost Holstein lineages from the University of Minnesota and ABS Global. The samples were used to fertilize eggs to create a dozen embryos from genetically elite Holstein females owned by one of the nation’s largest dairy genetics companies — Select Sires Inc. Embryos from the first lineage were implanted in surrogate heifers at Penn State’s dairy farm last summer. 

The first group of bouncing baby bovines — three males and three females — were born in April, all healthy and full of spunk. Their growth and health is being tracked by animal science doctoral student Han Longfei to determine how they compare to calves from other lineages. An additional 10 calves from the second lost lineage are expected to make their appearance later this year.   

With the calves are, from left, Chad Dechow, associate professor of dairy cattle genetics; Lydia Hardie, postdoctoral scholar; and Han Longfei, doctoral student. 

“After several years of planning, seeing those first calves was exciting,” Dechow said. “The team really didn’t know what they would look like, and the first calf’s white face with white eyelashes was the first thing that we noticed. Of course, how they look is the least important aspect of the project, and what we really hope is that the lost genetic diversity they represent eventually will be reintroduced to the Holstein population.”

Liu agreed, adding, “We are very happy to see the calves and bring back these lost lines. These calves will further advance our research in cattle genetics, and with that knowledge we can continue to improve genetic diversity, the health of Holsteins and milk production.” 

Dechow and Liu thanked partners on the project, including Penn State’s College of Agricultural Sciences, the National Animal Germplasm Program, Trans Ova (which produced the embryos), Select Sires Inc., the University of Minnesota and ABS Global. Perhaps the most important partners, Dechow noted, are the management team and employees at the Penn State dairy farm who care for the calves every day.

“Many people and companies have provided resources to help resurrect these lineages, so it really has been a broad-based industry effort that we believe will enhance the breed’s diversity and make dairy breeders better stewards of our genetic resources,” Dechow said.

Source: Penn State

More, better bulls for Australian dairy farmers

This week’s release of Australian Breeding Values (ABVs) by DataGene has highlighted a trend that has seen more, young Holstein bulls of high quality coming through the ranks over the past year.

The April ABV release will be the first published by DataGene, having taken on the genetic evaluation roles performed by the Australian Dairy Herd Improvement Scheme (ADHIS) over the past 30 years.

DataGene Genetic Evaluation manager, Michelle Axford, said there were notable increases in the genetic merit of the top Holstein young bulls (see table).

This time last year there were no young, genomic Holstein bulls with a Balanced Performance Index – BPI – above 300 in the Good Bulls Guide. Now there are more than 25. In fact, the average BPI of the top 50 young bulls is now over 300, representing a more than 20% increase over the past year. Also, there is a wider range of bull companies represented by the top 10 Holstein bulls, going up from two last April to five in this release. 

“That’s great news for Australian dairy farmers. Having access to more, better, young bulls means more choice. And by always choosing bulls that carry the Good Bulls logo, dairy farmers can be confident their breeding choices will contribute to an overall improvement in their herd’s genetic merit for profit,” she said.

The past three years has also seen a steady increase in the number of Holstein bulls genomically tested (see graph).

Mrs Axford said that while DataGene had taken on the role of genetic evaluation and broader herd improvement roles, ABV releases were very much a case of ‘business as usual’.

“DataGene has some major projects on the go, including the development of the much-awaited centralised data repository, but the industry can be assured that the routine ABV releases continue as normal,” she said.

DataGene is an initiative of Dairy Australia and the herd improvement industry.


Source: DataGene

Kenya to use embryo transfer technology to improve dairy cattle breeds

Kenya plans to use embryo transfer technology in order to improve its dairy cattle breeds, the government agricultural agency said on Thursday.

Agricultural Development Corporation (ADC) Managing Director Richard Aiyabei told Xinhua in Nairobi that a significant proportion of the country’s dairy population consists of local breeds which have low milk production.

“Embryo transfer technology will be used to increase the average daily milk production from the current 15 liters per cattle to 30 liters per cattle,” Aiyabei said on the sidelines of the Kenya Alliance of Resident Associations Bi Monthly talk series on Kenya’s Food Insecurity.

“Using Embryo transfer technology, we could easily upgrade dairy cattle breeds within a short time,” he added. ADC plans to roll out the embryo transfer technology in order to produce 50,000 heifers annually.

“Embryo transfer is a better way to improve cattle breeds as opposed to use of conventional breeding methods,” Aiyabei added. He noted that improved heifer breeds will be sold to small scale farmers at subsidized rates.

He noted that Kenya’s milk production is unable to meet growing demand. “The majority of the milk produced is from small scale farmers and hence we need to focus on them in order to enhance production,” the government official said.

ADC currently has over 1.6 million acres of land for both crop and livestock production.


Source: African News

Researchers Tap Into Power of Genomics to Breed Feed-efficient Dairy Cattle

At the University of Guelph, researchers are tapping into the power of genomics to breed dairy cattle that are more feed-efficient and produce less methane, while still maintaining the high productivity, health and fertility of dairy cows, thereby getting their wish in the form of a huge database to support the project.

“An ongoing challenge for us in doing these studies on novel traits is the time and money required to collect all the data we need,” said Luiz Brito, a post-doctoral researcher, who holds a PhD Degree in Animal Genetics and Genomics from The University of Guelph.

“One option is to combine data from various research groups around the world who are working on the same traits, as we all have similar goals.”

According to GenomeAlberta, the main purpose of such a database is to increase the reliability of genomic prediction of breeding values for feed efficiency and methane emission in Canada and international partners. In addition, a larger dataset will increase the likelihood of scientific discoveries, such as a better understanding of the genetic architecture and other factors that influence these novel traits.

Churning up data

As difficult as it is for researchers to gather large amounts of data, developing a database to house and make sense of it all is no small feat either.

“We’ve been working with the Canadian Dairy Network (CDN) to set up a secure database and a computationally efficient data exchange to make it all possible. The database will be housed at the CDN which already hosts the national database containing all dairy performance data in Canada, so they have the infrastructure in place to collect large data sets.”

Brito is thrilled to receive data from partners all over the world including Australia, the United States, the UK, Switzerland, and Denmark, with negotiations underway for more countries to join in. At the same time, it presents some unique challenges.

“Because each partner collects and stores data in a different format, I’m working right now on standardizing the process to convert all data to a common format that we can use and redistribute to participants. It’s important to be comparing apples to apples.”

“We’re gathering information on genotypes, pedigrees and phenotypes. As part of the Efficient Dairy Genome Project, in addition to the two main traits, we’re also looking at ones that help measure or can be biological indicators of those two such as milk production and composition and rumen microbiome.”

The more the merrier

They say “more isn’t always better”; in this case, however, Brito would disagree.

“The more data we collect, the more accurate the genomic selection becomes. And as we generate more precise breeding values, it means the producer can make greater genetic progress, boosting the bottom line through greater feed efficiency while reducing the environmental footprint of dairy production in Canada and worldwide.”

As someone from a farming background, Brito is excited both by that prospect and the fact that the database he’s working on is vital to the project’s success.

He’s also encouraged by the long-term prospects for the database.

“It will ensure a continuous and secure flow of information that remains functional long after this project ends. We want something in place that will continue receiving data and re-distributing it to our partners for years to come.”

So nothing against ties and socks, but for a memorable researcher gift, you can’t top a fully stocked database. And if they try returning it for a refund, good luck with that.


Source: The Cattle Site

Epigenetics will be a Driver for Future Successful Dairying

Dairy breeders spend considerable time choosing the next round of bulls to use. That’s important because improvements in genetics has a significant influence on the generations that follow.  Nevertheless, future performance will depend on how epigenetics regulates the DNA acquired through breeding.  When epigenetics enters the picture,  breeders will need to re-consider how they breed and manage their dairy cattle.

What’s Epigenetics?

Epigenetics underlies processes that affect health, ­ fertility, longevity and many traits of dairy cattle. Epigenetic effects differ from direct genetic effects because the animal’s DNA sequence is not changed by epigenetic processes. Rather, epigenetic processes act by regulating whether genes within DNA sequences are “turned on” or “turned off” without any change in the DNA sequence. (Read more: FORGET GENOMICS – EPIGENOMICS & NUTRIGENOMICS ARE THE FUTURE)

Genetic and Epigenetic Differences

Traits such as milk yield, milk protein, conception rate, somatic cell count and udder conformation are heritable, meaning that differences among animals in these traits can be accounted for by family relationships among sires, dams and ancestors. Heritability ranges from around 3% to over 50% for various traits, therefore 3 to 50% of differences among animals are accounted for by differences in their DNA sequences.

The non-genetic variation in traits is included in what we refer to as environmental effects. Weather, feed, facilities, management practices and everything else that cattle are affected by in a herd fits into environmental effects.  Many responses of cattle to environmental effects are regulated by epigenetic or closely-related processes at the cellular level in animals.

Epigenetic effects do not change an animal’s DNA sequence (genome). Instead, epigenetic effects alter how individual genes or groups of genes are controlled or as geneticists say “silenced or differentially regulated” throughout an animal’s life. Originally, epigenetic effects were thought to represent only alterations that could be passed to the next generation without changing in the animal’s genetic code. More recently it seems that epigenetic effects may impact various tissues and organs during certain periods in the animal’s life, without being passed to the next generation.

Epigenetic Triggers

Animal scientists are using the term “developmental programming” to define practices that may trigger epigenetic effects. Developmental programming may act through epigenetic or similar pathways to influence almost any trait of interest in dairy cattle. For dairy farmers, it matters little whether the action occurs through one mechanism or another, as long as responses are predictable and repeatable.

Repeatability means that there is a fairly predictable pattern of an action causing a specific or response separated by weeks, months, years or generations. That makes it challenging to determine cause and effect, without careful observations, good records and repeated verification.

Epigenetic effects may be triggered by conditions associated with natural biological process or by adverse conditions such as negative energy balance, heat stress, exposure to toxins or other disturbances. Epigenetic effects can be either positive or negative, so as we learn more it will be useful to incorporate management practices that stimulate positive effects and limit negative ones.

Epigenetic Effect #1        Calf Feeding and Future Performance

One epigenetic or epigenetic-like effect is the latent response to feeding higher levels of milk or replacer to heifer calves. Calves fed at higher levels produce more milk in first lactation about 2 years later, so the response occurs beginning about 700 days after the action. Preliminary data suggest that heifers fed more milk develop more mammary epithelial cells that become milk-secreting cells when first lactation begins. This is the kind of epigenetic effect that one would see for stem cells that are dividing rapidly when the milk is being fed. The exact regulatory mechanism for this effect is yet to be determined.

Epigenetic Effect #2        Milking Frequency Immediately After Calving

Similar to the situation in calves fed more milk, it has been demonstrated that cows milked 4X daily during the first 3 weeks of lactation and then 2X daily thereafter produce considerably more milk than cows milked 2X from freshening. The 4X milking early in lactation apparently stimulates development of more milk-secreting cells and these then remain throughout lactation, even when milking frequency drops to 2X.

Epigenetic Effect #3        Embryo Survival

It is highly probable that negative epigenetic effects occur when eggs (oocytes) are developing within the ovary when a cow is under stressful conditions. Such can be the case for the egg ovulated by an energy and/or health stressed cow that comes into heat 80 days post calving. The egg ovulated at day eighty actually started growing as an oocyte within her ovary about 3 weeks before calving.

 Oocytes that develop under these stressful conditions have low survivability as embryos. Their fertilization rate is normal, but they degenerate and die at a higher rate in the first week after fertilization. This is a classical example of an adverse epigenetic effect. Our North Carolina State research team published the first report of this effect in 1992. It is referred to as the Britt Hypothesis and it has taken about 25 years for scientists to begin to understand this phenomenon at the DNA level.

Stay Tuned As We Learn More

There is a strong interest in understanding how epigenetics affect the developing fetus and how management of the pregnant cow influences the future long-term responses of the calf she is carrying. During fetal stages, tissues that will form muscles, mammary tissue, the immune system and all other systems undergo development.  We will see a lot of new discoveries about epigenetics in these areas in the years ahead and this will give us tools to support development of better calves during pregnancy.

Husbandry practices trigger many of the epigenetic effects, both good and bad.  Understanding how such effects are mediated will give us husbandry tools to improve both DNA-based genetics and ways to regulate the DNA in a beneficial manner.

The Bullvine Bottom Line

The Bullvine found that this information shared by Jack Britt assisted us in better understanding the topic of epigenetics.  Yes, epigenetics is yet one more piece of the puzzle that progressive breeders are likely to use in the future to both breed and manage their dairy herds.



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