Soybean seeds contain phytochemicals such as polyamines and isoflavones, which have been identified as functional components mediating health benefits in association with the consumption of soy foods. While a clear picture of the spatial distribution of these components within the seed is lacking, such information would be important to enhance or reduce their concentration in respective foods through processing. Thus, the objective of the present study was to visualize the most relevant components with respect to their distribution in soybean seeds. Mature soybean seeds were subject to atmospheric-pressure scanning-microprobe matrix-assisted laser desorption/ionization (AP-SMALDI) combined with a Fourier-transform orbital trapping mass spectrometer to generate high-resolution chemical images of phytochemical distribution. Based on seed cross sections, differential distributions of functional components were found between soybean cotyledon and germ (shoot, hypocotyl, root) regions. Spermidine and spermine were present in higher concentrations in the germ rather than in cotyledons with highest concentrations in root and shoot meristem tissues. Differential concentrations of spermidine and other components between the germ and cotyledon regions were confirmed by seed fractioning. In contrast to polyamines spermidine and spermine, the different types of daidzein, glycitein, and genistein isoflavones were all visualized in root parenchyma tissue exclusively. Overall, mass spectrometry imaging of soybean seeds revealed clear insights into the differential distribution of functional phytochemicals. Based on their distribution and depending on specific needs, spermidine and isoflavones can either be enriched or reduced during food processing by separating cotyledon and germ fractions.

The research work was carried out with the progeny of two soybean cultivars, Richy and Izidor, from the years 2019 and 2020. Plants were grown from seeds pretreated with low temperature (2–5 °C) before sowing for two periods of treatment: 12 days marked as “treated control” (tr. K) and 22 days marked as “treated” (tr.); and “non-treated” (K0) used as a control. Transcriptional profiles of the gene encoding a stress protein kinase were evaluated after the application of abiotic stresses caused by the following: 150 mM NaCl solution/salinity stress/for 24 h; 350 mM mannitol solution/drought stress/for 24 h; and low temperature (4 °C) for 72 h. Transcript levels were established by real-time quantitative reverse transcription polymerase chain reaction (qRT-PCR) in leaf tissue collected from seedlings of the 2019 and 2020 progeny of “tr. K”, “tr.”, and “K0” samples. Analyses determining the quantity of malondialdehyde (MDA) and total antioxidant capacity (TAC) were performed. The expression of investigated stress kinase was highly upregulated after the application of abiotic stress caused by 150 mM solution of NaCl and to a lesser extent by 350 mM solution of mannitol. Detected transcript levels depend on the type of sample out of “tr. K”, “tr.”, and “K0”; the progeny; and the genotype.

Crop breeding advancement is hindered by the imperfection of methods to reveal genes underlying key traits. Genome-wide Association Study (GWAS) is one such method, identifying genomic regions linked to phenotypes. Post-GWAS analyses predict candidate genes and assist in causative mutation (CM) recognition. Here, we assess post-GWAS approaches, address limitations in omics data integration and stress the importance of evaluating associated variants within a broader context of publicly available datasets. Recent advances in bioinformatics tools and genomic strategies for CM identification and allelic variation exploration are reviewed. We discuss the role of markers and marker panel development for more precise breeding. Finally, we highlight the perspectives and challenges of GWAS-based CM prediction for complex quantitative traits.