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

Genome-wide identification of SABATH gene family in soybean relate to salt, aluminum, chromium toxicity

SABATH gene family in plants participates in metabolic processes such as methylation of various hormones and plays an essential role in plant response to abiotic stress. In this study, we identified and sequenced 28 SABATH genes in soybean and divided them into three groups. Genome mapping annotation suggested that tandem repeat was the cause of SABATH gene amplification in soybean. Phylogenetic and homology analyses show that the three groups may have originated from different ancestors. Transcriptome analysis was performed in six soybean tissues using data from public transcriptome. In addition, transcriptome and gene expression analyses revealed their expression patterns under different soybean varieties and various abiotic stresses. These results reveal the differential expression of GmSABATHs gene under these stresses, indicating their potential role in the mechanism of soybean adapting to environmental challenges. These results provide reference information for the evolutionary study of the SABATH family and the potential role of GmSABATHs in soybean resistance to abiotic stress.

Network analysis combined with genome-wide association study helps identification of genes related to amino acid contents in soybean

BACKGROUND

Additional to total protein content, the amino acid (AA) profile is important to the nutritional value of soybean seed. The AA profile in soybean seed is a complex quantitative trait controlled by multiple interconnected genes and pathways controlling the accumulation of each AA. With a total of 621 soybean germplasm, we used three genome-wide association study (GWAS)-based approaches to investigate the genomic regions controlling the AA content and profile in soybean. Among those approaches, the GWAS network analysis we implemented takes advantage of the relationships between specific AAs to identify the genetic control of AA profile.

RESULTS

For Approach I, GWAS were performed for the content of 24 single AAs under all environments combined. Significant SNPs grouping into 16 linkage disequilibrium (LD) blocks from 18 traits were identified. For Approach II, the individual AAs were grouped by five families according to their metabolic pathways and were examined based on the sum, ratios, and interactions of AAs within the same biochemical family. Significant SNPs grouping into 35 LD blocks were identified, with SNPs associated with traits from the same biochemical family often positioned on the same LD blocks. Approach III, a correlation-based network analysis, was performed to assess the empirical relationships among AAs. Two groups were described by the network topology, Group 1: Ala, Gly, Lys, available Lys (Alys), and Thr and Group 2: Ile and Tyr. Significant SNPs associated with a ratio of connected AAs or a ratio of a single AA to its fully or partially connected metabolic groups were identified within 9 LD blocks for Group 1 and 2 LD blocks for Group 2. Among 40 identified QTL for AA or AA-derived traits, three genomic regions were novel in terms of seed composition traits (oil, protein, and AA content). An additional 24 regions had previously not been specifically associated with the AA content.

CONCLUSIONS

Our results confirmed loci identified from previous studies but also suggested that network approaches for studying AA contents in soybean seed are valuable. Three genomic regions (Chr 5: 41,754,397-41,893,109 bp, Chr 9: 1,537,829-1,806,586 bp, and Chr 20: 31,554,795-33,678,257 bp) were significantly identified by all three approaches. Yet, the majority of associations between a genomic region and an AA trait were approach- and/or environment-specific. Using a combination of approaches provides insights into the genetic control and pleiotropy among AA contents, which can be applied to mechanistic understanding of variation in AA content as well as tailored nutrition in cultivars developed from soybean breeding programs.

Unveiling the microbiota-mediated impact of different dietary proteins on post-digestive processes: A simulated in vitro approach

Protein digestion and microbial metabolism play crucial roles in overall health. However, the mechanisms that differentiate the digestion and metabolism of dietary proteins from different sources in the organism remain poorly understood. This study investigated the digestive properties and microbial fermentation of various animal proteins (chicken, pork, beef, and casein) and plant proteins (soy bean, mung bean, kidney bean, rice, and wheat) in an in vitro simulation. The results indicated that animal-derived proteins had higher essential amino acid content (33.97-37.12 g/100 g) and digestibility levels (49.15-60.94 %), and provided more small molecule peptides upon digestion. Nevertheless, soy bean and wheat proteins also exhibited higher digestibility (54.70 % and 60.94 %), probably due to the extraction process. The fermentation results showed that distinct metabolic profiles that emerged for different protein sources. Plant-derived proteins (especially kidney bean, rice and wheat) promoted the proliferation of beneficial bacteria and microbial diversification and stimulated short-chain fatty acids (SCFA) production. Conversely, meat proteins (pork, chicken, beef) had significantly lower microbial diversity and SCFA than these plant proteins. These findings provide valuable insights into the effects of dietary protein sources on digestion and gut microbiome, and offer scientific guidance for optimizing dietary choices to improve health.

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.