By Bob Weaber, Ph.D., Associate Professor/ Cow-calf Extension Specialist at Kansas State University. Through a series of collaborative data, DNA sample and genotyping agreements between the Canadian Limousin Association, the North American Limousin Foundation (NALF), the University of Missouri, faculty at Kansas State University and the Igenity business unit of GeneSeek, a Neogen Company, Limousin breeders are uniquely positioned to benefit from genomics technology. Work completed in the last several months including a large training exercise consisting of genotypes and EPD data on more than 5,000 animals yielded a robust prediction equation for estimating the genetic merit of a range of traditional traits like growth, calving ease and carcass merit for animals of Limousin and Angus origin recorded in the CLA/ NALF herd books. The results of this research and the necessary computations for blending the genomic predictions with traditional EPDs have already been programmed into the new association software from DigitalBeef being deployed at CLA and NALF. The new set of prediction equations used to compute molecular breeding values (MBV) for genotyped animals works for both Limousin and LimFlex animals. Animals need to be genotyped on either the GGP-LD (low density, 30,000 marker panel) or the GGP-HD panel which contains approximately 150,000 markers. Either density are imputed to a standard profile of 50,000 for use in computing MBV. The new genomic predictions will soon be available to Canadian Limousin breeders through DNA genotyping services provided by Delta Genomics, a Canadian business partnering with GeneSeek to provide services to Canadian producers. Once an animal is genotyped, an animal’s MBV will be produced through the GeneSeek bioinformatics pipeline and integrated into the DigitalBeef software where blending the MBV with EPD will occur. New genomics tools offer Limousin breeders industry leading predictive power and improvement in accuracy. The strength of a DNA marker panel to explain additive genetic variation (the kind explained by EPDs) is reported as %GV or the percentage of genetic variation explained. The closer this value gets to 1, the greater the relative improvement in accuracy as a result of explaining large amounts of genetic variation. The %GV for the newest training is reported in table 1. Progeny equivalents and expected increases in accuracy due to addition of genomic data is present in table 2. Inclusion of performance data in a valid contemporary group and genomic data yields EPDs with accuracies ranging from roughly .40 to .60 without collection of a single progeny phenotype. Progeny equivalents relate the improvement in accuracy due to genomics to the number of progeny records from valid contemporary groups that would be needed to achieve the same level of accuracy. These progeny equivalents range from 10 to 38 across traits.
The most effective way to utilize MBVs computed from animal genotypes is through the inclusion of the MBV in the calculation of an EPD. Convergence of legacy datasets and pedigrees with MBV data has several key benefits for seedstock and commercial beef producers. First, since the MBV represents an estimate of the net genetic merit for a subset of the genes it doesn’t provide a complete picture of animal’s complete genetic merit. For that reason, MBVs are not substitutes for EPDs but can add information useful for the prediction of EPD. Second, continued use of EPD values as the genetic ‘currency’ eliminates retraining and education of members and commercial customers on the use of new tool. Finally, and most importantly, inclusion of MBV data offers a reliable method to increase the accuracy of prediction for EPD, especially for young selection candidates. Substantial improvements in EPD accuracy for non-parent animals for conventional growth and carcass traits is valuable. Improvements in the accuracy of EPDs for traits like heifer pregnancy, stayability, and calving ease and maternal traits, where non-parents won’t have a performance record, may prove to be of even higher value. After all, the decisions that seedstock producers make that result in yearling bulls available for purchase by commercial producers creates all the genetic change in the entire beef value chain. Improving the accuracy of that decision point is expected to have significant impact and value. As producers consider investment in genomic technologies, it is important to consider which animals to genotype. Undoubtedly, producers should seek to capture the value or return on investment from their genotyping investment. There are several ways to seek out the return. One method is the idea of ‘adding value’ to yearling bulls for sale through increased EPD accuracy and buyer confidence. Additionally, the genotyping of a significant percentage of your bulls that are selection candidates for development and sale, should help weed out some of the problem bulls and identify the superstars and bulls that are genetically superior. Another reasonable place to consider investment, maybe even preferential to genotyping young bulls, is the genotyping of replacement heifer candidates. The accuracy improvements reported in table 2 and the associate progeny equivalents suggests that for a number of economically important traits, the genomic information will likely generate more accuracy for a dam’s EPDs than her entire lifetime production of natural calves. Practically, this means you can set much of a herd’s maternal genetic trajectory through the use of genotyping and well before a female even enters in production. Genomics are now a powerful tool for producers to chart and plot their genetic improvement destiny.
Limousin Voice The Bull Issue 2016 44