Data Collection

Data Collection for Seedstock Producers

At the core of genetic improvement is the collection of data. While data quality is critical, quantity of data collected can sometimes overcome the limitations on data quality that inherently occur in farm and ranch operations. Along with weights and scores for economically relevant traits and their indicator traits, accurate identification of animals, parents, contemporary groups, and other important details (e.g., age) are essential.

At the core of genetic improvement is the collection of high quality data. Data quality can be impacted by several clearly identified factors. While completeness, timeliness, accuracy, and conformity are all essential, consistency is often the least understood and most overlooked consideration for quality data. Collecting, recording, manipulating and processing data using consistent procedures at both the farm and association levels is the most important aspect to maintaining quality data.

In order to keep all data collected associated with an individual animal an effective beef cattle identification system is essential. Standards have been developed for identification methods that ensure unique and accurate identification of animals during the transmission and processing of data. Because the number of animals processed in National Cattle Evaluations programs (NCE) is routinely in the millions, it is not practical to routinely use registration number information for on-farm data collection. Standards for ear tagging and on-farm electronic identification have also been implemented. In addition, recording of animal identification is closely associated with the collection of genomic information.

Historically, many beef breed genetic evaluations were based on progeny weaned and/or registered and did not require that data be recorded from females that failed to reproduce or whose progeny were not registered.  By contrast, inventory based Whole Herd Reporting (WHR) requires collection of annual production and performance records on all cattle within a herd.

Data recording on individual cows is essential for the prediction of female fertility. Cow fertility is often the most impactful factor on profitability in the beef herd. Additionally, accurate and complete cow data are essential for prediction of traits with a maternal influence (e.g. weaning weight).

The Female Production Data to be recorded on each cow must be standardized because it is often the most complex data that a producer deals with.

Data collection of complete and accurate data on individual calf performance through slaughter or breeding is critical to making genetic improvement. Using consistent methods for taking animals' weights, measures, and scores is key to accurate data. Additionally, using a commercial or breed association supplied performance recording software helps to improve consistency of data collection and reporting.

Contemporary Groups

content by Jennifer Bormann

Data Collection on Calves

Weights

Yearling Weight

Content by Michael Gonda

Data Collection on Yearling Bulls

Content by Madison Butler/Megan Rolf

Data Collection on Yearling Heifers

Pelvic Measurements

Content by Dave Patterson

Reproductive Tract Scores

Content by Dave Patterson

Data Collection on Mature Cows

Mature Height and Weight

content by Heather Bradford

Body Condition Scores

Content by Dave Lalman

Teat and Udder Scores

Content by David Riley

Foot and Leg Scores

content by Lane Giess

Adaptability-Related Traits

PAP Scores

Content by Mark Enns, Milt Thomas, and Scott Speidel

Hair Shedding

Content by Trent Smith

Genomic Data

Use of genomic data requires quality sample collection. Once samples are acquired and processed according to breed association specifications, the data can be incorporated into reporting systems for breed associations, including reporting schemes for monogenic traits such as horned/polled genotype or genetic abnormality carrier status as well as for quantitative traits, which will be utilized within either single-step genomic BLUP or single-step hybrid marker effects models for genetic prediction. Genotype data can also be utilized for other applications, as detailed below.

Parentage Testing

content by Megan Rolf

Genotype data is often used for parentage testing for embryo transfer calves or in the case of ambiguous birth date. It can also be helpful for producers who utilize multiple-sire pastures. The concept behind using genetic markers for parentage testing is based on the fact that each animal receives one allele from each parent, which makes up the animal's genotype (i.e. for an animal that is Aa, the A comes from one parent, while the a comes from the other). Therefore, an animal's genotypes at many loci can be compared to genotypes of potential parents at those same loci to determine if those markers are consistent with that individual being a parent of the offspring in question.

One common misconception of parentage testing is that the test determines parentage absolutely. Rather, parentage testing excludes animals that cannot be the parents of a particular offspring, rather than proving that an animal is the parent. In the simplest terms, we use the genetic markers to exclude animals as a possible parent, with the goal of having only one animal left as the most likely parent for that offspring after all others have been excluded. This is why all possible parents must be genotyped and included in the comparison to get accurate results, but the inclusion of animals that can be excluded due to location, color, or other factors is discouraged.

The newest type of parentage panels typically utilize 96 SNP (or single nucleotide polymorphism) markers. To account for genotyping errors, one exclusion out of all the markers in the panel is typically allowed and still determine parentage. Two to three exclusions would indicate a need to re-test the sample to rule out contamination, poor DNA quality, or poor genotyping results. More than three exclusions will lead to a complete exclusion of that animal as a potential parent. Research has shown that parentage can be determined with greater specificity with a larger number of SNP markers (around 400), but at a greater cost. A balance between cost effectiveness and having a reasonable ability to eliminate animals that could not have been the parents must be achieved.

Older parentage panels utilized Microsatelllite markers, and these panels typically had a smaller number of markers. Parentage cannot be determined if animals are not genotyped on the same type of panel, as the markers at the same loci cannot be compared between these panels.

References:

International Society for Animal Genetics. (2012). Guidelines for cattle parentage verification based on SNP markers. http://www.isag.us/Docs/Guideline-for-cattle-SNP-use-for-parentage-2012.pdf.

More detailed infomration on parentage testing along with relevant examples can be found here.

Data Collection for Commercial Producers

Content by Jackie Atkins (and Chip Kemp?)

Data Collection at Feedlots

Content by Larry Kuehn