Genome-wide Association Mapping of Qualitatively Inherited Traits in a Germplasm Collection

Authors

Nonoy B. Bandillo, University of Nebraska-Lincoln
Aaron J. Lorenz, University of Nebraska-LincolnFollow
George L. Graef, University of Nebraska-LincolnFollow
Diego Jarquin, University of Nebraska-LincolnFollow
David L. Hyten, University of Nebraska-LincolnFollow
Randall L. Nelson, USDA, Agricultural Research ServiceFollow
James E. Specht, University of Nebraska-LincolnFollow

Document Type

Article

Date of this Version

2016

Citation

the plant genome | july 2017 | vol. 10, no. 2

Comments

© Crop Science Society of America

Open access

doi: 10.3835/plantgenome2016.06.0054

Abstract

Genome-wide association (GWA) has been used as a tool for dissecting the genetic architecture of quantitatively inherited traits. We demonstrate here that GWA can also be highly useful for detecting many major genes governing categorically defined phenotype variants that exist for qualitatively inherited traits in a germplasm collection. Genome-wide association mapping was applied to categorical phenotypic data available for 10 descriptive traits in a collection of ~13,000 soybean [Glycine max (L.) Merr.] accessions that had been genotyped with a 50,000 single nucleotide polymorphism (SNP) chip. A GWA on a panel of accessions of this magnitude can offer substantial statistical power and mapping resolution, and we found that GWA mapping resulted in the identification of strong SNP signals for 24 classical genes as well as several heretofore unknown genes controlling the phenotypic variants in those traits. Because some of these genes had been cloned, we were able to show that the narrow GWA mapping SNP signal regions that we detected for the phenotypic variants had chromosomal bp spans that, with just one exception, overlapped the bp region of the cloned genes, despite local variation in SNP number and nonuniform SNP distribution in the chip set.