Genome-Wide Associations Identifying Marker-Trait-Associations for Root Morphology and Photosynthetic Related Traits in a Soybean (Glycine max) Diversity Panel

Abstract

Soybean is a staple crop for the food, feed, and fuel industries because of its unique oil and protein composition. It is the second most produced crop globally, with average acres planted and harvest yield increasing annually. However, the current rate of increase is insufficient to match future supply with projected demand. This imbalance is exacerbated by yield decreases due to abiotic stresses, particularly drought. The aim of this thesis project is to address these intertwined phenomena through a two-pronged approach, examining above and below-ground phenotypes for their implication on stress tolerance and yield improvement. Methodologically, this is pursued through phenotypic measurement and analysis followed by genome-wide association analysis seeking to identify markers associated to traits utilizing a soybean diversity panel grown in field conditions. Chapter one is a review of literature, examining the context of this research, discussing the relationship between drought, yield, photosynthesis, and root characteristics. Chapter two delves into the phenotyping and analysis of above-ground biomass traits (photosynthetic rate, stomatal conductance, water-use efficiency, intracellular CO2, leaf area, leaf mass, and specific leaf area). Results of above-ground analysis suggests the environmental dependency of gas exchange data and identify 31 significant SNP associations with 5 of the 7 measured traits. Chapter three then reviews the methodology and results of the analysis with below-ground root system architecture traits. The outcomes of root analysis determine several (30) significant SNPs associated with 5 of the 12 analyzed traits. Findings of this project provide valuable insight into the breadth of genetic diversity within soybean maturity group V, increased understanding of the complex genetic architecture underpinning physiological and morphological traits related to photosynthetic and root architecture traits, and, finally, determines several compelling SNPs and genes to utilize in future projects.