Using transcriptomic and metabolomic data to investigate the molecular mechanisms that determine protein and oil contents during seed development in soybean

Integrated physiological, transcriptomic and metabolomic analyses reveal the mechanism of peanut kernel weight reduction under waterlogging stress

Waterlogging stress (WS) hinders kernel development and directly reduces peanut yield; however, the mechanism of kernel filling in response to WS remains unknown. The waterlogging-sensitive variety Huayu 39 was subjected to WS for 3 days at 7 days after the gynophores touched the ground (DAG). We found that WS affected kernel filling at 14, 21, and 28 DAG. WS decreased the average filling rate and kernel dry weight, while transcriptome sequencing and widely targeted metabolomic analysis revealed that WS inhibited the gene expression in starch and sucrose metabolism, which reduced sucrose input and transformation ability. Additionally, genes related to ethylene and melatonin synthesis and the accumulation of tryptophan and methionine were upregulated in response to WS. WS upregulated the expression of the gene encoding tryptophan decarboxylase (AhTDC), and overexpression of AhTDC in Arabidopsis significantly reduced the seed length, width, and weight. Therefore, WS reduced the kernel-filling rate, leading to a reduction in the 100-kernel weight. This survey informs the development of measures that alleviate the negative impact of WS on peanut yield and quality and provides a basis for exploring high-yield and high-quality cultivation, molecular-assisted breeding, and waterlogging prevention in peanut farming.

Integrating Genome-Wide Association Study, Transcriptome and Metabolome Reveal Novel QTL and Candidate Genes That Control Protein Content in Soybean

Protein content (PC) is crucial to the nutritional quality of soybean [Glycine max (L.) Merrill]. In this study, a total of 266 accessions were used to perform a genome-wide association study (GWAS) in three tested environments. A total of 23,131 high-quality SNP markers (MAF ≥ 0.02, missing data ≤ 10%) were identified. A total of 40 association signals were significantly associated with PC. Among them, five novel quantitative trait nucleotides (QTNs) were discovered, and another 32 QTNs were found to be overlapping with the genomic regions of known quantitative trait loci (QTL) related to soybean PC. Combined with GWAS, metabolome and transcriptome sequencing, 59 differentially expressed genes (DEGs) that might control the change in protein content were identified. Meantime, four commonly upregulated differentially abundant metabolites (DAMs) and 29 commonly downregulated DAMs were found. Remarkably, the soybean gene Glyma.08G136900, which is homologous with Arabidopsis hydroxyproline-rich glycoproteins (HRGPs), may play an important role in improving the PC. Additionally, Glyma.08G136900 was divided into two main haplotype in the tested accessions. The PC of haplotype 1 was significantly lower than that of haplotype 2. The results of this study provided insights into the genetic mechanisms regulating protein content in soybean.

Widely targeted metabolic profiling provides insights into variations in bioactive compounds and antioxidant activity of sesame, soybean, peanut, and perilla

Oilseeds are important sources of diversified nutraceuticals with marked health attributes. Thus, a better understanding of metabolome differences between common oilseeds will be conducive to the food pharmacy. This study aimed to compare the metabolite profiles and antioxidant activity of sesame, soybean, peanut, and perilla seeds and reveal the variation in bioactive compounds. LC-MS-based widely targeted metabolic profiling identified a total of 975 metabolites, of which 753 were common to the four crops. Multivariate analyses unveiled a crop-specific accumulation of metabolites, with 298-388 DAMs (differentially accumulated metabolites) identified. Amino acid metabolism, phenylpropanoid biosynthesis, flavonoid biosynthesis, and lipid metabolism were the most differentially regulated pathways. Furthermore, we revealed the variation in the relative content of 48, 20, 18, 9, 18, 11, and 6 differentially accumulated bioactive flavonoids, phenolic acids, amino acids, vitamins, terpenoids, alkaloids, and coumarins, respectively. Most of the flavonoids accumulated highly in soybean, followed by perilla. Sesame exhibited a better amino acid profile than other oilseeds. DPPH and FRAP assays showed that the antioxidant activity of perilla seed extracts was the highest, followed by soybean, peanut, and sesame. Our results provide data support for the comprehensive use of sesame, perilla, soybean, and peanut seeds in food, and pharmaceutical industries.

QTLs and Candidate Genes for Seed Protein Content in Two Recombinant Inbred Line Populations of Soybean

This study aimed to discover the quantitative trait loci (QTL) associated with a high seed protein content in soybean and unravel the potential candidate genes. We developed two recombinant inbred line populations: YS and SI, by crossing Saedanbaek (high protein) with YS2035-B-91-1-B-1 (low protein) and Saedanbaek with Ilmi (low protein), respectively, and evaluated the protein content for three consecutive years. Using single-nucleotide polymorphism (SNP)-marker-based linkage maps, four QTLs were located on chromosomes 15, 18, and 20 with high logarithm of odds values (5.9-55.0), contributing 5.5-66.0% phenotypic variance. In all three experimental years, qPSD20-1 and qPSD20-2 were stable and identified in overlapping positions in the YS and SI populations, respectively. Additionally, novel QTLs were identified on chromosomes 15 and 18. Considering the allelic sequence variation between parental lines, 28 annotated genes related to soybean seed protein-including starch, lipid, and fatty acid biosynthesis-related genes-were identified within the QTL regions. These genes could potentially affect protein accumulation during seed development, as well as sucrose and oil metabolism. Overall, this study offers insights into the genetic mechanisms underlying a high soybean protein content. The identified potential candidate genes can aid marker-assisted selection for developing soybean lines with an increased protein content.

Differential gene expression provides leads to environmentally regulated soybean seed protein content

Soybean is an important global source of plant-based protein. A persistent trend has been observed over the past two decades that soybeans grown in western Canada have lower seed protein content than soybeans grown in eastern Canada. In this study, 10 soybean genotypes ranging in average seed protein content were grown in an eastern location (control) and three western locations (experimental) in Canada. Seed protein and oil contents were measured for all lines in each location. RNA-sequencing and differential gene expression analysis were used to identify differentially expressed genes that may account for relatively low protein content in western-grown soybeans. Differentially expressed genes were enriched for ontologies and pathways that included amino acid biosynthesis, circadian rhythm, starch metabolism, and lipid biosynthesis. Gene ontology, pathway mapping, and quantitative trait locus (QTL) mapping collectively provide a close inspection of mechanisms influencing nitrogen assimilation and amino acid biosynthesis between soybeans grown in the East and West. It was found that western-grown soybeans had persistent upregulation of asparaginase (an asparagine hydrolase) and persistent downregulation of asparagine synthetase across 30 individual differential expression datasets. This specific difference in asparagine metabolism between growing environments is almost certainly related to the observed differences in seed protein content because of the positive correlation between seed protein content at maturity and free asparagine in the developing seed. These results provided pointed information on seed protein-related genes influenced by environment. This information is valuable for breeding programs and genetic engineering of geographically optimized soybeans.