Biometric Open Language Tools Genetic Evaluation Software.
The American Hereford Association (AHA) has and will continue to offer the most robust and progressive genetic evaluation that will help identify Hereford genetics that are the most profitable for the commercial Industry. Over the last two years, the AHA Board of Directors and staff have researched and thoroughly evaluated the necessary steps to implement a single step genomic evaluation using the Biometric Open Language Tools (BOLT) software. Along with this, AHA is introducing two new economically relevant traits that are included in an updated set of economic indexes. This document outlines the major revisions that have been implemented into the AHA genetic evaluation that is planned to be released December 4, 2017.
The main growth model will stay the same with little impact to traits in the model. However, because of the new analysis use of the single step Marker Effects Model some animals’ EPDs will change. These changes will primarily be the result of increased accuracy using the new methods and reduced bias.
Scrotal circumference is correlated with weaning weight, but only scrotal circumference EPDs will be reported out of this model. There is a decrease of correlated data impacting scrotal EPDs but this impact will be very small. Again, because of the change in the way the updated genetic evaluation is handling the genomic component there are changes in some animals’ scrotal circumference EPDs.
Birth weight is used as the correlated trait with the carcass traits to account for selection that may occur. Weaning and yearling weight is no longer included as correlated traits with carcass fat and carcass marbling. Instead scan fat and intra-muscular fat along with birth and carcass weight are used to resolve traits of interest when real carcass data are not collected. This could create some changes in carcass fat and marbling EPDs, the two traits reported out of this model. Also, the variance components used as part of the analysis procedure were re-estimated for all carcass traits and the correlation between scan intramuscular fat and carcass marbling decreased from 0.70 to 0.54. Finally, because of the change in the way the updated genetic evaluation is handling the genomic component there can be changes to some animals’ EPDs.
Weaning weight will be used as the correlated trait as birth weight is not adequate to solve for weight traits. However, yearling weight will no longer be included as a correlated trait with carcass weight and carcass rib-eye area to account for selection that may occur. Instead scan rib-eye area and weaning weight are included with any available carcass data to resolve the traits of interest. Carcass rib-eye area and carcass weight will be the only two traits reported out of this model. Analyses comparing the previous carcass trait EPDs to those coming from the new analyses are very high, but can be different for some animals, especially because of the change in the way the updated genetic evaluation is handling the genomic component.
The updated genetic evaluation uses a random regression statistical procedure to calculate calving ease and maternal calving ease (total maternal calving ease). Birth weight is used as the correlated trait in this model but is not reported. The birth weight EPD that is reported comes from the Growth Traits analysis (2a.) discussed previously. This evaluation moves away from the threshold model previously used, in part because it required that observations that are the same within a contemporary group (e.g., herd) could not be used. This means that the new analysis can use all observations regardless of score as well as use the corresponding birth weight phenotype. Even though this evaluation uses only data from two-year old heifers, more observations will be used resulting in a more comprehensive calving ease evaluation than what is being performed today. Also, because of the change in the way the updated genetic evaluation is handling the genomic component there can be changes to some animals’ EPDs.
Mature cow weight is analyzed with weaning weight but only mature cow weight will be reported out of this model. The weaning weight EPD that is published comes from the previously discussed Growth analysis (2a.). Even though the new MCW EPDs are highly correlated to the old analysis, small changes may be seen in part because yearling weight is no longer used as a correlated trait. Finally, because of the change in the way the updated genetic evaluation is handling the genomic component there could be changes in some animals’ EPDs.
Sustained cow fertility is analyzed by itself, without a correlated trait, using random regression statistical model to predict female fertility/longevity. This trait predicts a female’s ability to stay in the herd through the age of twelve (ten calving’s after calving as a two-year-old heifer). The EPD is reported on a probability scale meaning that a higher EPD for a sire means his daughters are more likely to remain fertile and produce more calves throughout their lifetime. Because of the limited number of phenotypes collected that have a corresponding genotype, the genomic component is not included in this model.
The udder and teat evaluation remains the same basic model as it is today with the exception that it includes the genomic information to increase the accuracy of prediction.
Dry matter intake includes weaning and yearling weight as correlated traits but dry matter intake will be the only trait reported out of this model. This EPD predicts the daily consumption of feed. Because of the limited number of phenotypes collected that have a corresponding genotype, the genomic component is not included in this model.
The AHA would not have been able to complete this genetic evaluation overhaul without the guidance of several key scientists. First include Dr. Bruce Golden, Co-Founder, CEO and President of Theta Solutions, LLC, and Dr. Dorian Garrick, Co-Founder, CSO and CFO of Theta Solutions, LLC, that have developed the BOLT software and engineered the script writing and provided the genomic expertise for the updated genetic evaluation. Next Dr. Brad Crook and Dr. Shalanee Weerasinghe of Agriculture Business Research Institute (ABRI) who have orchestrated the genetic evaluation to run with Canadian Hereford and provided the technical support to ensure the evaluation is performing accurately. Also Dr. Mike MacNeil, Delta G, Dr. Matt Spangler, University of Nebraska, and Dr. Larry Kuehn, Meat Animal Research Center, have provided expertise and technical backing in the update of the new economic indexes. Finally, an advisory committee was assembled to review the revisions made to the updated genetic evaluation. This committee was charged with providing feedback to the proposed changes and ultimately giving the recommendation of approval to the AHA BODs. Advisory committee member are as follows; Joe Ellis, Jack Holden, Paul Bennett, Lee Haygood and Mitch Abrahamsen.