Author
Huggins, Trevis | |
Edwards, Jeremy | |
Chen, Ming Hsuan | |
Jackson, Aaron | |
McClung, Anna |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 1/16/2018 Publication Date: 2/16/2018 Citation: Huggins, T.D., Edwards, J., Chen, M., Jackson, A.K., McClung, A.M. 2018. Association analysis for loci regulating grain quality traits and marker development in the USDA rice collection. Meeting Abstract. Phenome 2018 Conference, Tucson Arizona. Poster Number 46. Interpretive Summary: Technical Abstract: Uncovering underlying genetics associated with grain quality is important to world food security. Rice is consumed as a whole grain, therefore cooked rice texture, stickiness, chewiness, grain dimensions and grain appearance can affect palatability and marketability. Amylose and protein content play significant roles in determining eating and cooking quality and affect the translucency of milled kernels. Kernel translucency is influenced by the presence of chalk, an opaque area in the grain, which occurs when starch granules are loosely packed in the endosperm. The minicore (MC) panel is a representative germplasm subset of the USDA Rice Core Collection, specifically designed to capture maximum diversity in a manageable size and is ideally suited for genome-wide association (GWA) experiments that have a high phenotyping cost. The publically available re-sequencing dataset of the 203 MC accessions by next generation sequencing (NGS) produced ~3.3 million SNPs. The SNPs were used to conduct GWA analysis on the grain traits, apparent amylose content (AAC), alkali spreading value (ASV), percent grain chalk (Chk) and percent grain protein (Prot). Major known starch related genes, such as soluble starch synthase IIa (SSIIa) and Waxy, were identified, as well as 11 novel grain quality loci, seven novel chalk loci and seven novel protein loci. Further analysis of regions surrounding significant SNPs with Perl scripts identified several overlapping chromosomal regions associated with multiple traits. These results will be instrumental in determining molecular markers useful in marker assisted selection for grain quality and may provide insights into the biological processes that influence it. |