Two graduate research projects as recipients of the 2022 Walton-Berry Graduate Student Support Grants. Each will receive a $5,000 grant through the ASA Simmental-Simbrah Foundation. The aim of these grants is to help train future leaders in animal breeding, and advance our knowledge of applied livestock genetics by aiding in the professional development, success, and experiences of young animal scientists at the regional and national level. This grant is available to all agricultural disciplines; however, focus will be on the genetic improvement of livestock. The Walton-Berry Graduate Student Support Grant, initiated by Jim Berry of Wildberry Farms, honors Dr. Bob Walton’s lifelong efforts in animal breeding and raising Simmental cattle.
“Identifying Genomic Biomarkers to Improve Beef Heifer Fertility”
Dr. Diniz, assistant professor of animal genomics, Department of Animal Sciences; and graduate student Nicholas Kertz
Reproductive failure is still a constraint for the sustainability of beef production systems. Since fertility traits are not highly heritable, tracking their progress has been limited using traditional approaches. The focus of Dr. Diniz’s research with graduate student Nicholas Kertz is to identify blood biomarkers that underlie heifer fertility. By combining genomics, bioinformatics, and machine learning methods to identify blood biomarkers, the long-term goal is to identify how to select fertile replacement heifers accurately.
Preliminary work shows that metabolic biomarkers can be used to identify fertile vs infertile heifers from blood samples taken at the time of artificial insemination. Work is underway in their laboratory to link metabolic and genomic biomarkers to improve the power of prediction from tissue samples obtained well before breeding time.
University of Nebraska–Lincoln
“Revisiting Economic Selection Index Construction: Planning Horizons and Benchmarking Progress”
Dr. Matt Spangler, Department of Animal Science; and graduate student Hunter Valasek
The aims of this project are twofold: first, to investigate the impact of planning horizon in the development of selection indexes; and second, to develop indexes in retrospect to benchmark genetic selection for improved commercial level net profit.
Economic selection indexes are arguably one of the most essential tools in the animal breeder’s toolkit. Using iGENDEC software that enables the construction of economically optimized selection indexes, researchers will investigate the impact of a planning horizon. Simply put, planning horizon defines the length of time (in years) that the programmed simulation mimics the annual production of cattle in various breeding scenarios.
Though selection indexes have been available to US beef producers for nearly two decades, their collective impact on the beef industry is unknown. Selection indexes, such as $API and $TI, often compete with their components (the many individual trait EPD) in selection decisions. Consequently, it is possible that the aggregate selection decisions are not economically optimal. One way to investigate this is by using the concept of an index in retrospect. An index in retrospect uses the genetic response in component traits (i.e., traits for which EPD exist) to define how they must have been weighted in decision-making. Such a process could be used to benchmark breeds relative to their genetic advancement of commercial-level net profit, and to quantify the difference between the index in retrospect and economically optimized indexes constructed using iGENDEC.
- Created: 04 June 2022
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