HIGH-IMPACT RESEARCH FOR SOYBEAN IMPROVEMENT USING GENETICS AND GENOMICS
Location: Corn, Soybean and Wheat Quality Research Unit
Project Number: 3607-21000-012-15
Start Date: Sep 01, 2011
End Date: Sep 30, 2014
Map new genes (QTL) for soybean yield by nested association mapping
We will use the nested association mapping (NAM) experimental design to map quantitative trait loci (QTL) that control yield, agronomic traits, and protein and oil content to a high level of precision. With the NAM design, a single parent (the maturity group (MG) variety IA3023) was crossed to 50 MG II-V parents, including high yielding parents derived from exotic germplasm, creating a series of populations that will be used in genetic mapping studies. In the final experiment, we plan to test 40 populations each of which has 140 lines giving a total of 5,600 MG III experimental lines. The 5,600 lines in the populations will be genotyped with 1,536 SNP markers but the parents will be genotyped with over 50,000 SNP markers. Because of the design and the large size of the experiment, we will be able to project the information from the 50,000 markers onto the 5,600 lines in the experiment, thus allowing for an unprecedented accuracy in mapping QTL controlling agronomic and quality traits.
Conventional QTL mapping studies can only map a QTL to a relatively large chromosomal region that contains thousands of genes. It is predicted that the highly accurate mapping in the NAM populations will allow us to map QTL to small genetic intervals that contain only a few genes. This means that we should be able identify genetic marker patterns that are so tightly linked to the QTL that these markers will be diagnostic for the presence of the different QTL alleles in any soybean germplasm that we test. This will make it possible to predict what alleles are present in each potential parent and use that information to select the best parents to cross including exotic germplasm not currently being used. We can also use the same markers to select for the progeny that have the best combination of alleles to increase yield.