QTL Mapping for Protein and Sulfur-Containing Amino Acid Contents Using a High-Density Bin-Map in Soybean (Glycine max L. Merr.)

Densification of Genetic Map and Stable Quantitative Trait Locus Analysis for Amino Acid Content of Seed in Soybean (Glycine max L.)

Soybean, a primary vegetable protein source, boasts favorable amino acid profiles; however, its composition still falls short of meeting human nutritional demands. The soybean amino acid content is a quantitative trait controlled by multiple genes. In this study, an F2 population of 186 individual plants derived from the cross between ChangJiangChun2 and JiYu166 served as the mapping population. Based on the previously published genetic map of our lab, we increased the density of the genetic map and constructed a new genetic map containing 518 SSR (simple sequence repeats) markers and 64 InDel (insertion-deletion) markers, with an average distance of 5.27 cm and a total length of 2881.2 cm. The content of eight essential amino acids was evaluated in the F2:5, F2:6, and BLUP (best linear unbiased prediction). A total of 52 QTLs (quantitative trait loci) were identified, and 13 QTL clusters were identified, among which loci02.1 and loci11.1 emerged as stable QTL clusters, exploring candidate genes within these regions. Through GO enrichment and gene annotation, 16 candidate genes associated with soybean essential amino acid content were predicted. This study would lay the foundation for elucidating the regulatory mechanisms of essential amino acid content and contribute to germplasm innovation in soybeans.

PhI(OAc)2-Promoted 1,2-Transfer Reaction between 1,1-Disubstituted Allylic Alcohols and Thiophenols

The PhI(OAc)2-promoted 1,2-transfer reaction between allylic alcohols and thiophenols, conducted in an argon atmosphere, has proven to be effective in producing β-carbonyl sulfides from 1,1-disubstituted allylic alcohols in high yields. This method offers a fast and efficient way to synthesize β-carbonyl sulfides, which are valuable intermediates in organic synthesis. This discussion focuses on the effects of the oxidizer, temperature, and solvent on the reaction. A proposed tentative mechanism for this reaction is also discussed.

Sulfate transport and metabolism: strategies to improve the seed protein quality

Sulfur-containing amino acids (SAA), namely methionine, and cysteine are crucial essential amino acids (EAA) considering the dietary requirements of humans and animals. However, a few crop plants, especially legumes, are characterized with suboptimal levels of these EAA thereby limiting their nutritive value. Hence, improved comprehension of the mechanistic perspective of sulfur transport and assimilation into storage reserve, seed storage protein (SSP), is imperative. Efforts to augment the level of SAA in seed storage protein form an integral component of strategies to balance nutritive quality and quantity. In this review, we highlight the emerging trends in the sulfur biofortification approaches namely transgenics, genetic and molecular breeding, and proteomic rebalancing with sulfur nutrition. The transgenic 'push and pull strategy' could enhance sulfur capture and storage by expressing genes that function as efficient transporters, sulfate assimilatory enzymes, sulfur-rich foreign protein sinks, or by suppressing catabolic enzymes. Modern molecular breeding approaches that adopt high throughput screening strategies and machine learning algorithms are invaluable in identifying candidate genes and alleles associated with SAA content and developing improved crop varieties. Sulfur is an essential plant nutrient and its optimal uptake is crucial for seed sulfur metabolism, thereby affecting seed quality and yields through proteomic rebalance between sulfur-rich and sulfur-poor seed storage proteins.

Soybean sorting based on protein content using X-ray fluorescence spectrometry

The purpose of this research was to evaluate performance of an energy-dispersive X-ray fluorescence (XRF) sensor to classify soybean based on protein content. The hypothesis was that sulfur signals and other XRF spectral features can be used as proxies to infer soybean protein content. Sample preparation and equipment settings to optimize detection of S and other specific emission lines were tested for this application. A logistic regression model for classifying soybean as high- or low-protein was developed based on XRF spectra and protein contents. Additionally, the model was validated with an independent set of samples. Global accuracies of the method were 0.83 (training set) and 0.81 (test set) and the corresponding kappa indices were 0.66 and 0.61, respectively. These numbers indicated satisfactory performance of the sensor, suggesting that XRF spectral features can be applied for screening protein content in soybean.

Transcriptional Profile of Soybean Seeds with Contrasting Seed Coat Color

Soybean is the primary source of vegetable protein and is used for various purposes, mainly to feed animals. This crop can have diverse seed coat colors, varying from yellow, black, brown, and green to bicolor. Black seed coat cultivars have already been assigned as favorable for both seed and grain production. Thus, this work aimed to identify genes associated with soybean seed quality by comparing the transcriptomes of soybean seeds with contrasting seed coat colors. The results from RNA-seq analyses were validated with real-time PCR using the cultivar BRS 715A (black seed coat) and the cultivars BRS 413 RR and DM 6563 IPRO (yellow seed coat). We found 318 genes differentially expressed in all cultivars (freshly harvested seeds and seeds stored in cold chamber). From the in silico analysis of the transcriptomes, the following genes were selected and validated with RT-qPCR: ACS1, ACSF3, CYP90A1, CYP710A1, HCT, CBL, and SAHH. These genes are genes induced in the black seed coat cultivar and are part of pathways responsible for ethylene, lipid, brassinosteroid, lignin, and sulfur amino acid biosynthesis. The BRSMG 715A gene has almost 4times more lignin than the yellow seed coat cultivars. These attributes are related to the BRSMG 715A cultivar's higher seed quality, which translates to more longevity and resistance to moisture and mechanical damage. Future silencing studies may evaluate the knockout of these genes to better understand the biology of soybean seeds with black seed coat.

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

Soybean is a major source of high-quality protein for humans and animals. The content of sulfur-containing amino acids (SAA) in soybean is insufficient, which has become the main factor limiting soybean nutrition. In this study, we used the high-density genetic maps derived from Guizao 1 and Brazil 13 to evaluate the quantitative trait loci of cysteine (Cys), methionine (Met), SAA, glycinin (7S), β-conglycinin (11S), ratio of glycinin to β-conglycinin (RGC), and protein content (PC). In genetic map linkage analysis, the major and stable 44 QTLs were detected, which shared nine bin intervals. Among them, the bin interval (bin157-bin160) on chromosome 5 was detected in multiple environments as a stable QTL, which was linked to 11S, 7S, RGC, and SSA. Based on the analysis of bioinformatics and RNA-sequencing data, 16 differentially expressed genes (DEGs) within these QTLs were selected as candidate genes. These results will help to elucidate the genetic mechanism of soybean SAA-related traits and provide the basis for the gene mining of sulfur-containing amino acids.

Genetic dissection reveals the complex architecture of amino acid composition in soybean seeds

Five loci related to soybean protein and amino acid contents were colocated by performing linkage mapping and GWAS. The haplotype analysis showed that Glyma.08G109100 may be useful to improve the soybean seed composition. Soybean (Glycine max (L.) Merr.) seeds are good protein sources. Although genetic variation is abundant, natural variation in seed amino acids and their derived traits is lacking across soybean accessions. Here, we determined the contents of protein and 17 amino acids, obtained 36 derived traits based on the protein and total amino acid contents, and derived 34 traits based on seven amino acid family groups. Furthermore, we performed a linkage analysis of the contents of 17 amino acids and 73 amino acid-derived traits based on the recombinant inbred line (RIL)-derived Kefeng No. 1 × Nannong 1138-2. Six hundred thirty-nine quantitative trait loci (QTLs) were identified, explaining 6.07-39.00% of the phenotypic variation. Among these loci, five were detected in diverse soybean accessions using a genome-wide association study. A network analysis revealed that some loci that were significantly associated with multiple amino acids were tightly linked on chromosome 8 based on linkage disequilibrium values, which also further confirmed the results of the correlation analysis among amino acid traits. Through a combination of a genome-wide association study, linkage analysis, qRT-PCR, and genomic polymorphism comparison, Glyma.08G109100 on chromosome 8, which may affect amino acid contents, was selected. The haplotype analysis showed that Hap-T of Glyma.08G109100 may be useful to improve the contents of protein and 16 amino acids in soybean. This study provides new insights into the genetic basis of the amino acid composition in soybean seeds and may facilitate marker-based breeding of soybean with improved nutritional value.

Linkage and association study discovered loci and candidate genes for glycinin and β-conglycinin in soybean (Glycine max L. Merr.)

KEY MESSAGE

Linkage mapping and GWAS identified 67 QTLs related to soybean glycinin, β-conglycinin and relevant traits. Polymorphisms of the candidate gene Gy1 promoter were associated with the glycinin content in soybean. The major components of storage proteins in soybean seeds are glycinin and β-conglycinin, which play important roles in determining protein nutrition and soy food processing properties. Increasing the protein content while improving the ratio of glycinin to β-conglycinin is substantially important for soybean protein improvement. To investigate the genetic mechanism of storage protein subunits, 184 recombinant inbred lines (RILs) derived from a cross of Kefeng No. 1 and Nannong 1138-2 and 211 diverse soybean cultivars were used to detect loci related to glycinin (11S), β-conglycinin (7S), the sum of glycinin and β-conglycinin (SGC), and the ratio of glycinin to β-conglycinin (RGC). Sixty-seven QTLs and 11 hot genomic regions were identified as affecting the four traits. One genetic region (q10-1) on chromosome 10 was associated with multiple traits by both linkage and association analysis. Eight genes in 11 hot genomic regions might be related to soybean protein subunit. The candidate gene analysis showed that polymorphisms in Gy1 promoters were significantly correlated with the 11S content. The QTLs and candidate genes identified in the present study allow for further understanding the genetic basis of 11S and 7S regulation and provide useful information for marker-assisted selection (MAS) in soybean quality improvement.

Enhancing the Nutritional Quality of Major Food Crops Through Conventional and Genomics-Assisted Breeding

Nutritional stress is making over two billion world population malnourished. Either our commercially cultivated varieties of cereals, pulses, and oilseed crops are deficient in essential nutrients or the soils in which these crops grow are becoming devoid of minerals. Unfortunately, our major food crops are poor sources of micronutrients required for normal human growth. To overcome the problem of nutritional deficiency, greater emphasis should be laid on the identification of genes/quantitative trait loci (QTLs) pertaining to essential nutrients and their successful deployment in elite breeding lines through marker-assisted breeding. The manuscript deals with information on identified QTLs for protein content, vitamins, macronutrients, micro-nutrients, minerals, oil content, and essential amino acids in major food crops. These QTLs can be utilized in the development of nutrient-rich crop varieties. Genome editing technologies that can rapidly modify genomes in a precise way and will directly enrich the nutritional status of elite varieties could hold a bright future to address the challenge of malnutrition.