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Genetic Summary Report
 
   

Genetic Summary Report

Purpose
 
With the onset of genomics, the rate at which genetic progress can be achieved has increased very rapidly. The ability to find the highest genetic merit sires and cows has become much easier. Ultimately, the key decisions remain: What semen to buy and which cows to breed to which bulls, while increasing the genetics within your herd. To make good decisions, it is important to understand the genetic makeup within the herd. Because genomics has allowed us to select from the "best of the best", not only in our own herds, but also in the industry, diversity within the genetic pool of available AI sires has shrunk. Knowing the prominence of bloodlines in the herd will allow for more informed breeding decisions, faster genetic progress, and the ability to control inbreeding.

The Genetic Summary Report is designed to give dairy producers and their management team valuable information that will assist in making better breeding decisions. The summary relies heavily on identification of animals with a unique, official ID. The Council on Dairy Cattle Breeding (CDCB) cannot generate a proof on unidentified animals. Proper identification of each cow or heifer's sire, dam, and service sires will allow for more accurate analysis of data. The Genetic Summary Report analyzes both cows and heifers. Reporting heifer information allows for calculation of what genetics will be entering the herd.

Sample Holstein Report         Sample Jersey Report        Sample Mixed Herd Report
Understanding the Genetic Summary Report

      

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Report Explanation - Block A

The cows and heifers (youngstock) PTA (Predict Transmitting Ability) values included in Block A have either been calculated by CDCB/Animal Improvement Programs Laboratory (AIPL) using a simple parent average, a parent average combined with phenotypic data, genomic data, or genomic data combined with production data. If the animal did not receive a proof from CDCB/AIPL and AgSource has sire and dam information, AgSource will calculate a parent average value. The Avg Inbr% and Avg Fut Inbr% are numbers that come from CDCB only.

In Block A, the percentile breakdowns are based on ALL active cows (or heifers) in the AgSource database. In this example, there are 416,123 cows and 395,815 youngstock included in these benchmarks. The number of animals listed for the herd could differ from the amount of animals that are actually in the herd. This report is only analyzing animals that are properly identified and have genetic information. Herds with poor identification will not see complete information.

Top Block A allows producers to see how their herd ranks among other herds of similar type (Holstein, Jersey, or All Other Breeds). Depending on which traits are considered important when selecting AI bulls, the producer can see where their cows and heifers rank relative to all AgSource cows and heifers and decide if the desired progress is actually being achieved. For example, if this herd were selecting for PTA SCS, they would be ranked between the 50th and 80th percentile for both their cows and heifers. Highlights are used to indicate which percentile rankings the herd falls in between.
 
What's the difference between genomic inbreeding and inbreeding?
Inbreeding looks at the dam and sire and expected heritability. There is no analysis of how the genomes actually transmit or line up in the animal. (This acts very similarly to a calculated parent average for heifers on the Genetic Selection Guide)

Genomic inbreeding is the actual measure of what genes are in common. If the genomic inbreeding percentage is higher than the inbreeding percentage, it is telling you that the actual genes in common are higher than the regular pedigree inbreeding was able to calculate.

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Block B shows the active cows' and heifers' inbreeding % (based on pedigree) and genomic inbreeding % by year of birth. The red line is the breed average calculated by CDCB each genetic update. The question, "What is my inbreeding percentage," is perhaps the number one question producers ask their reproduction experts. Because inbreeding calculations require information on pedigrees, these numbers are very hard to get and as of right now, CDCB is the only entity that can provide this information on both registered and grade animals. Breed registry programs could provide the information on animals identified through their programs as well.

The key to understanding inbreeding is that as the inbreeding percentages increase, the number of common good and bad genes also increase. Generally speaking, the common bad genes overtake the common good genes. If they do not, this is what is referred to as line breeding, or bringing desired traits to the forefront.

Top Research done by Dr. Bennet Cassell (see Table 1) shows that for each one percent inbreeding increase, a herd would experience a reduction of 24 NM$ lifetime performance, an increase of .36 days in age-at-first-calving, a loss of 13 days Productive Life, a loss of 790 pounds of lifetime milk production, 25 pounds of lifetime protein production and a .26-month increase in first- calving interval.

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Block C illustrates the herd's NM$ distribution. The distribution is based on where the cow or heifers' NM$ ranks nationally. Each colored section of the bar graph represents the number of cows or heifers in the herd that are ranked in the bottom 50th percentile all the way to the top 90th percentile of cows across the US. In this example, out of the 463 youngstock that have received a NM$, 271 animals rank in the top 10 percent (90th percentile) of all heifers in the AIPL database, while 8 youngstock are in the bottom 50th percentile.

Top This chart will illustrate exactly how the herd has been advancing the genetics of their animals. You would expect to see more youngstock in the 90th percentile than older animals. If not, this could be an area of concern.

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This graph shows active cows' and heifers' NM$ broken out by year of birth. You should see an improvement over time. The red line shows the average NM$ value for active cows and heifers in the AgSource database so you can compare your herd and rate of progress against other AgSource members. Herds will have the option to select either CM$ or NM$.

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Above the Genetic Trend graphs show the averages for various traits calculated on active cows each test date. There is approximately three years worth of data in each graph. Herds that began testing less than three years ago will see data from the point they start testing. The dotted line is the top 80th percentile AgSource herds based on the trait graphed. Analysis shows where the herd is currently at and you can compare the rate of improvement against the 80th percentile herds. Other traits will be added in future updates to this report.

TopThe benchmark numbers are all based on the 80th percentile herd, not the 80th percentile cow. The benchmark line will change based on the breed comparison being used, however the herd value will represent all animals in the herd, regardless of comparison. For this reason, numbers illustrated in Block E are different than the 80th percentile numbers in Block A.

The USDA NM$ value represents the national 80th percentile NM$ value as of the last genetic update. AgSource values are generally very close.

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Block F looks at active cows' genetic values and lifetime production values and breaks out the herd based on the type of semen used, either conventional AI, sexed semen AI or natural/unknown. These values are the averages for the cows in each group, not the sires. Natural or Unk is based on the scenario where there was no sire NAAB code reported. These sires may have a registration number, but it is unknown if they are a herd bull or AI Stud without an NAAB code. AgSource is still given a PTA on animals with unknown sires, but it is based on the dam's contribution. If there are a large number of animals in the Natural/Unk category, you should double check to ensure that sires are being properly recorded. It is important that a NAAB number is recorded for an AI breeding. Simply entering a registration or sire name will not suffice.

It is possible that the genetic value seen with the use of the sexed semen does not match the genetic value of those cows sired by conventional semen. In such a scenario, the herd may be sacrificing genetic progress.

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Top Block G illustrates the values of key traits for cows and youngstock based on the different types of proofs an animal can receive.

Conventional proofs are the animals that have received a proof at USDA based on pedigree and production data. The genomic tested proofs are those recognized at AIPL based on genomic testing of the animal herself. The imputed proof is based on the genomic testing of the animal's ancestry or progeny.

Two values of inbreeding are calculated for animals that have been genomic tested. First is the animal's own genomic inbreeding percent (GIB%), a reflection of the common genes inherited from its parents. The more useful value in making mating decisions and in bull selection is the genomic future inbreeding percent (GFI%), indicating how likely the resulting offspring of a bull is to inherit common genes due to general use as a service sire

The importance of this summary is to identify if the herd is doing any genomic testing and compare the genetic values of the genomically tested animals with those not genomically tested. There could be a significant difference. If the producer uses the AgSource Genetic Selection Guide for cows and heifers, the reliability of the genetic values for the animals genomically tested would be higher and decisions regarding those animals would lead to greater accuracy of the end result.

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Block H breaks up the cows into four quartiles. Quartiles are based on NM$ values. For each quartile, we display genetic and phenotypic values. If the genetic program is working, you would expect the 1st quartile to show better genetics and better all around production levels.

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Block I tells you which genes (sires) are most prevalent throughout the herd. It looks at the sire, maternal grand sire and paternal grand sire. If a producer used a bull quite a bit, you would expect to see many daughters or maternal granddaughters out of him. However, a bull that was never used may also have a very high prevalence of genes in the herd because he was the sire of one of the bulls heavily used.

Top The more prevalent a certain bull is, the greater the risk of inbreeding. Unless a good mating program is used, attention to  bloodlines must be considered when selecting bulls. In the example above, the producer has a lot of Sequoia genes in the herd, both daughters and granddaughters. However maybe unknown to the producer, he has a lot of Boliver, Freddie, and Ramos granddaughters as well, even though he did not use those bulls directly. Analysis of this chart will help a producer control inbreeding he may not have known was taking place. The more thorough a producer is in reporting breeding and sire identification, the more accurate these analyses will be.

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Block J is a supplement to Block I and illustrates the current inbreeding distribution of the herd. If the producer uses a good mating program, it minimizes inbreeding and maximizes genetic progress at the same time. Further information is provided that illustrates the AgSource distribution of inbreeding, based on type of herd being analyzed. Most mating programs used by AI organizations try to keep inbreeding below 6.25%. In some cases, herds allow for a higher percentage of inbreeding in an attempt to capitalize on good genes (line breeding). The top ten inbred animals are also listed.

Animals over 12.5% inbred should be avoided. If a large percentage of animals are in this category, this could be caused by lack of an inbreeding management program, incorrect recording of sires, or mistakes made at the time of breeding.

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Top Block K shows the top 12 ranking bulls, based on number of milking daughters, and averages the genotypic and phenotypic numbers. You can see how some lines are performing in the herd; higher production, component, and lower cell counts. This graph helps answer or prove what many producers are currently thinking about the performance of some bulls in their herd by evaluating the actual performance of the daughters.

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The above graph is similar to Block E graphs; however we're looking at the genetics of the service sires that were used in the herd. This is another analysis in which the AgSource 80th percentile is herd based, not cow based.

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Top Assuming heifer information and pregnancies are reported, Block M shows the heifers broken out by three-month age groups. The genetic values are for the heifers, not the calves carried by the heifers. The purpose of this summary is to see what genetics will be entering the herd over the next two years. Compare these numbers with the graphs in Block E and you will know if the genetics entering the herd are significantly higher. The genetic values used to calculate the averages are parent averages if genomic information is not available. If genetic progress is to be recognized by the herd, you would expect the values in Block M to improve from oldest to youngest, and that all values in Block M are higher than those in Block A and E, which represents the current milking herd genetics.

For further information regarding interpretation or application of the Genetic Summary Report, contact: 

Erin Berger - eberger@agsource.com
Taliah Danzinger - tdanzinger@agsource.com
Char Handschke - chandschke@agsource.com
Paul Jandrin - pjandrin@agsource.com
Bob Ranallo - branallo@agsource.com
or call 800-236-4995

   
 
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