2014
Optimizing genomic selection for a soybean breeding program
Contributor/Checkoff:
Category:
Sustainable Production
Keywords:
GeneticsGenomics
Lead Principal Investigator:
Aaron Lorenz, University of Nebraska
Co-Principal Investigators:
George Graef, University of Nebraska
Project Code:
795
Contributing Organization (Checkoff):
Institution Funded:
Brief Project Summary:

The overall objectives of this project are to test, explore and optimize a novel breeding methodology for soybeans. This methodology termed Genomic selection, most effectively uses the information produced by high-throughput, high-volume DNA marker information.

The research team has explored the optimal use of marker information. They report that a substantial number of markers can be dropped without sacrificing genomic prediction accuracy; relatively small training populations can be used (~100); and computationally predicting missing DNA marker information provides little to no benefit. They are also studying the density and distribution of DNA markers obtained through this novel...

Unique Keywords:
#breeding & genetics, #research methodology, #soybean breeding - methodology, #soybean genetic markers, #soybean genomics
Information And Results
Project Deliverables

Knowledge of the potential of genomic selection to enhance the speed and accuracy of soybean breeding programs.

Final Project Results

The United Soybean Research Retention policy will display final reports with the project once completed but working files will be purged after three years. And financial information after seven years. All pertinent information is in the final report or if you want more information, please contact the project lead at your state soybean organization or principal investigator listed on the project.