2016
Accleration of soybean yield and composition improvement through genomic selection
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Contributor/Checkoff:
North Central Soybean Research Program
Category:
Sustainable Production
Keywords:
GeneticsGenomics
Parent Project:
Accelerating soybean yield and composition improvement through genomic selection
Lead Principal Investigator:
Brian Diers, University of Illinois at Urbana-Champaign
Co-Principal Investigators:
William Beavis, Iowa State University
Asheesh Singh, Iowa State University
Katy M Rainey, Purdue University
Patrick Brown, University of Illinois at Urbana-Champaign
Matthew Hudson, University of Illinois at Urbana-Champaign
Randall Nelson, University of Illinois at Urbana-Champaign
George Graef, University of Nebraska
Aaron Lorenz, University of Nebraska
+7 More
Project Code:
2015-06857-00-00
Contributing Organization (Checkoff):
North Central Soybean Research Program
(n/a)
Institution Funded:
University of Illinois-Carbondale
(n/a)
Brief Project Summary:

Both growers and breeders are frustrated that soybean yields are not increasing as rapidly as yields in maize. Recent evidence also shows that soybean seed protein is drifting lower, but attempts to stabilize or increase protein concentration using current breeding methods will likely slow yield increases further. We propose to increase the rate of genetic improvement for yield and protein by developing a new breeding strategy for soybean called Genomic Selection (GS). GS allows breeders to predict high yield-potential crosses and predict the performance of potential varieties by using thousands of genetic markers weighted based on associations with yield or other economically valuable traits....

Unique Keywords:
#breeding, #breeding & genetics, #genetic markers , #genomic selection, #yield
Information And Results
Project Deliverables

The key deliverables for this project will be methods that breeders can use to speed their progress in developing higher yielding varieties with better protein concentration. This will be the result of the following specific deliverables: (1) Optimized GS methods in soybean breeding programs by leveraging the existing SoyNAM data; (2) Validation of GS compared to traditional breeding methods through field testing; (3) Methods for selecting high yielding breeding lines; (4) Methods for predicting the best parental combinations in breeding programs; and (5) High yielding experimental lines developed through GS released as new varieties or germplasm. The methods developed in this project will be made available to breeders in the public and private sectors and used to improve genetic gains in their breeding programs.

Final Project Results

Update:
see above (October 3rd) for final report

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.