Identification of Novel Genomic Loci Associated with Soybean Shoot Tissue Macro and Micronutrient Concentrations

Abstract

The mineral composition of crop shoot tissues is important for yield formation and nutrient remobilization to seeds. The natural diversity that exists within crop species can be used to investigate mechanisms that define plant mineral composition and to identify important genomic loci for these processes. The objective of this study was to determine shoot mineral nutrient concentrations in genetically diverse soybean [ (L.) Merr.] genotypes and to identify genomic regions associated with concentrations of different nutrients in shoot tissue. The genotypes were grown at two locations in 2 yr and characterized for macronutrient (Ca, Mg, P, K, and S) and micronutrient (B, Cu, Fe, Mn, and Zn) concentrations in shoot tissues. Genome-wide association studies were conducted with 31,748 single nucleotide polymorphisms (SNPs) via a unified mixed model to identify SNPs associated with macro- and micronutrient concentrations. The number of putative loci identified for the macronutrients ranged from 11 for Ca to 20 for K. For the micronutrients, the number ranged from 10 for Mn to 24 for Fe. In addition to colocated loci for multiple nutrients, 22 individual SNPs were associated with more than one nutrient such that 11 different nutrient combinations were encompassed by these SNPs. Ultimately, the putative loci identified in this study will need to be confirmed and are expected to aid in the identification of new sources of variation for use in soybean breeding programs as well as for mechanistic studies aimed at understanding the regulation of mineral nutrient uptake, translocation, and shoot tissue concentrations.

Identification of Loci Controlling Mineral Element Concentration in Soybean Seeds

“…Such relatively high broad-sense heritability suggested that the phenotype was largely determined by the genotypic effect [20]. Similar heritabilities for these traits have been reported in previous studies (H 2 = 0.48 to 0.93) [14,16]. In addition, a signi cant and positive correlation between the concentrations of K and P was observed (0.65, Table S1).…”

“…Similarly, [16] also reported a QTL associated with the content in these two elements. Such correlations could be due to shared physiological mechanisms and metabolic pathways [4,21].…”

“…Two paralogs of our candidate gene (Glyma.02g154100 and Glyma.07g042500) were functionally characterized as being involved in the root uptake of K + in soybean [23,24]. Interestingly, in the work of Dhanapal et al [16], QTLs for K content do overlap with the genomic positions of these HAK5 paralogs. The fact that we did not detect any association between these paralogs and K content in our study suggests that it is variation in the HAK5 paralog on chromosome 10 (Glyma.10G020000) that contributes to differential accumulation of K in Canadian early-maturing soybean lines.…”

“…An A thaliana cDNA encoding ASA1 successfully complemented a Saccharomyces cerevisiae ATP sulfurylase mutant (met3), thereby restoring both methionine heterotrophy and sulfate transport [26]. Intriguingly, a paralog of our candidate gene was found on Gm10 by [16] (Glyma.10g242600). This again suggests that the same enzymatic activity is contributing to S accumulation, but that different copies of the gene control S content in different sets of germplasm.…”

“…Zhang et al [15] Germplasm Collection to identify 9 QTLs (on chromosomes 1, 2, 5, 9, 10 and 13) associated with Ca, K, P and S content in soybean seeds. Finally, Dhanapal et al [16] reported a total of 65 QTLs across the 20 chromosomes associated with soybean shoot Ca, K, P and S content using 31,748 SNPs and 104 soybean genotypes. Overall, little overlap in the QTLs identi ed in these studies is observed.…”