2016
Initiation of a genomic selection pipeline for public soybean breeders in the North Central region
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Contributor/Checkoff:
North Central Soybean Research Program
Category:
Sustainable Production
Keywords:
GeneticsGenomics
Parent Project:
This is the first year of this project.
Lead Principal Investigator:
Aaron Lorenz, University of Minnesota
Co-Principal Investigators:
William Beavis, Iowa State University
Asheesh Singh, Iowa State University
William Schapaugh, Kansas State University
Dechun Wang, Michigan State University
Katy M Rainey, Purdue University
Leah McHale, The Ohio State University
Patrick Brown, University of Illinois at Urbana-Champaign
Brian Diers, University of Illinois at Urbana-Champaign
Matthew Hudson, University of Illinois at Urbana-Champaign
Alex Lipka, University of Illinois at Urbana-Champaign
Randall Nelson, University of Illinois at Urbana-Champaign
Henry Nguyen, University of Missouri
Andrew Scaboo, University of Missouri
Grover Shannon, University of Missouri
George Graef, University of Nebraska
Aaron Lorenz, University of Nebraska
+15 More
Project Code:
CON000000055560
Contributing Organization (Checkoff):
North Central Soybean Research Program
(n/a)
Institution Funded:
University of Minnesota
(n/a)
Brief Project Summary:

Increases in soybean yield through breeding are slower than producers expect. There are several possible reasons for the reduced rate of gain in soybean grain yield, including limited genetic variation in the commercially used gene pool, amount of time required for each breeding cycle, size of the breeding populations, and accuracy of evaluations. Advances in genomics have made whole-genome genotyping less expensive than multi-location yield testing. A powerful approach to make use of this genomic information for selective breeding is through a method called genomic prediction and selection. Large datasets of genomic and phenotypic information are required to maximize the effectiveness of...

Unique Keywords:
#association studies, #breeding, #breeding & genetics, #database, #genome sequencing, #genomic selection, #molecular markers, #pedigrees, #uniform soybean tests, #yield
Information And Results
Project Deliverables

Key deliverables from this project include 1) a community resource for genomic prediction and selection that improves breeders’ ability to exploit current elite as well as exotic germplasm; 2) identification of genes exclusive to exotic germplasm that improve yield and agronomic performance; 3) knowledge of the distribution of these genes among the USDA Soybean Germplasm Collection which will enhance the introgression of these genes into elite North American germplasm, and hence increase yield.

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.