Identification and Mapping of QTLs for Sulfur-Containing Amino Acids in Soybean (Glycine max L.)

Comparison of grain traits and genetic diversity between Chinese and Uruguayan soybeans (Glycine max L.)

Soybeans (Glycine max L.), originating in China, were introduced to South America in the late 19th century after passing through North America. South America is now a major soybean-producing region, accounting for approximately 40% of the global soybean production. Crops like soybeans gradually adapt to the local climate and human-selected conditions, resulting in beneficial variations during cultivation in different regions. Comparing the phenotypic and genetic variations in soybeans across different regions is crucial to determining the variations that may enhance soybean productivity. This study identified seed-related traits and conducted a genetic diversity analysis using 46 breeding soybean varieties from China and Uruguay. Compared to the Chinese soybean germplasm, the Uruguayan equivalent had a lower 100-grain weight, higher oil content, lower protein content, and higher soluble sugar content. Using ZDX1 gene chips, genetic typing was performed on the 46 breeding varieties. Cluster analysis based on SNP sites revealed significant differences in the genetic basis of Sino-Uruguayan soybean germplasm. Selection analysis, including nucleotide polymorphism (π) and fixation indexes (Fst), identified several genomic regions under selection between Sino-Uruguayan soybean germplasm. The selected intervals significantly enriched gene ontology (GO) terms related to protein metabolism. Additionally, differentiation occurred in genes associated with the oil content, seed weight, and cyst nematodes between Sino-Uruguayan soybean germplasm, such as GmbZIP123 and GmSSS1. These findings highlight the differences in seed-related phenotypes between Sino-Uruguay soybean germplasm and provide genomic-level insights into the mechanisms behind phenotypic differences, offering valuable references for understanding soybean evolution and molecular breeding.

Bioaccessibility and Digestibility of Proteins in Plant-Based Drinks and Cow's Milk: Antioxidant Potential of the Bioaccessible Fraction

During the last years, a strong increase in the sales volume and consumption of plant-based drinks was observed, which were partly used as an alternative to cow's milk. As milk is a relevant protein source in many countries, we have investigated the protein bioaccessibility and digestibility of soy, almond, and oat drinks in comparison to milk using the tiny-TIMsg gastrointestinal model. The relative protein digestibility of all products was between 81% (soy drink) and 90% (milk). The digestible indispensable amino acid score (DIAAS) in vitro method was used to estimate the protein nutritional quality. The highest DIAAS values were obtained for milk in tryptophan (117%) and soy drink in sulfur containing amino acids (100%). Oat drink was limited in lysine (73%), almond drink in lysine (34%) and the sulfur containing amino acids (56%). Additionally, the antioxidant activity of the bioaccessible fractions was analyzed using Trolox equivalent antioxidative capacity and oxygen radical absorbance capacity assays, revealing a higher antioxidative potential of milk and soy drink compared to oat and almond drink.

Natural variation of GmFATA1B regulates seed oil content and composition in soybean

Soybean (Glycine max) produces seeds that are rich in unsaturated fatty acids and is an important oilseed crop worldwide. Seed oil content and composition largely determine the economic value of soybean. Due to natural genetic variation, seed oil content varies substantially across soybean cultivars. Although much progress has been made in elucidating the genetic trajectory underlying fatty acid metabolism and oil biosynthesis in plants, the causal genes for many quantitative trait loci (QTLs) regulating seed oil content in soybean remain to be revealed. In this study, we identified GmFATA1B as the gene underlying a QTL that regulates seed oil content and composition, as well as seed size in soybean. Nine extra amino acids in the conserved region of GmFATA1B impair its function as a fatty acyl-acyl carrier protein thioesterase, thereby affecting seed oil content and composition. Heterogeneously overexpressing the functional GmFATA1B allele in Arabidopsis thaliana increased both the total oil content and the oleic acid and linoleic acid contents of seeds. Our findings uncover a previously unknown locus underlying variation in seed oil content in soybean and lay the foundation for improving seed oil content and composition in soybean.

Rapid and reliable detection and quantification of organophosphorus pesticides using SERS combined with dispersive liquid-liquid microextraction

Rapid and reliable detection and quantification of pesticide residues in complex matrices by surface enhanced Raman spectroscopy (SERS) remain challenging due to the low level of target molecules and the interference of nontarget components. In this study, SERS was combined with dispersive liquid-liquid microextraction (DLLME) to develop a rapid and reliable method for the detection of organophosphorus pesticides (OPPs). In this method, DLLME was used to extract and enrich two representative OPPs (triazophos and parathion-methyl) from a liquid sample, and a portable Raman spectrometer was used to analyze the separated sediment using homemade gold nanoparticles colloids as enhancing substrates. The results showed that the developed method displayed good sensitivity and stability for the detection and quantification of triazophos and parathion-methyl with R² ≥ 0.98. The calculated limits of detection (LODs) in the simultaneous detection of triazophos and parathion-methyl were 2.17 × 10^-9 M (0.679 ppb) and 2.28 × 10^-8 M (5.998 ppb), and the calculated limits of quantification (LOQs) were 7.23 × 10^-9 M (2.26 ppb) and 7.62 × 10^-8 M (19.098 ppb), respectively. Furthermore, the developed SERS method was successfully applied to the detection of triazophos and parathion-methyl in apple juice with recoveries between 78.07% and 110.87% and relative standard deviations (RSDs) ≤ 2.06%. Therefore, the developed DLLME facilitated liquid SERS method exhibited good sensitivity and stability for the rapid detection and quantification of OPPs and had the potential to be applied to the rapid detection of OPPs in complex matrices.