Identification of a candidate gene associated with isoflavone content in soybean seeds using genome-wide association and linkage mapping

Integrative omics analysis elucidates the genetic basis underlying seed weight and oil content in soybean

Synergistic optimization of key agronomic traits by traditional breeding has dramatically enhanced crop productivity in the past decades. However, the genetic basis underlying coordinated regulation of yield- and quality-related traits remains poorly understood. Here, we dissected the genetic architectures of seed weight and oil content by combining genome-wide association studies (GWAS) and transcriptome-wide association studies (TWAS) using 421 soybean (Glycine max) accessions. We identified 26 and 33 genetic loci significantly associated with seed weight and oil content by GWAS, respectively, and detected 5,276 expression quantitative trait loci (eQTLs) regulating expression of 3,347 genes based on population transcriptomes. Interestingly, a gene module (IC79), regulated by two eQTL hotspots, exhibited significant correlation with both seed weigh and oil content. Twenty-two candidate causal genes for seed traits were further prioritized by TWAS, including Regulator of Weight and Oil of Seed 1 (GmRWOS1), which encodes a sodium pump protein. GmRWOS1 was verified to pleiotropically regulate seed weight and oil content by gene knockout and overexpression. Notably, allelic variations of GmRWOS1 were strongly selected during domestication of soybean. This study uncovers the genetic basis and network underlying regulation of seed weight and oil content in soybean and provides a valuable resource for improving soybean yield and quality by molecular breeding.

Cytochrome GmGLY1 is Involved in the Biosynthesis of Glycitein in Soybean

Isoflavones, the major secondary metabolites of interest due to their benefits to both human and plant health, are exclusively produced by legumes. In this study, we profiled the isoflavone content in dry seeds from 211 soybean [Glycine max (L.) Merr.] accessions grown across five environments. Broad and discernible phenotypic variations were observed among accessions, regions, and years of growth. Twenty-six single-nucleotide polymorphisms (SNPs) associated with the sum of glycitein (GLE), glycitin (GL), 6″-O-acetylglycitin (AGL), and 6″-O-malonylglycitin (MGL) contents were detected in multiple environments via a genome-wide association study (GWAS). These SNPs were located on chromosome 11 (8,148,438 bp to 8,296,956 bp, renamed qGly11-01). Glyma.11g108300 (GmGLY1), a gene that encodes a P450 family protein, was identified via sequence variation analysis, functional annotation, weighted gene coexpression network analysis (WGCNA), and expression profile analysis of candidate gene, and hairy roots transformation in soybean. Overexpression of GmGLY1 increased the glycitein content (GLC) in soybean hairy roots and transgenic seeds, while CRISPR/Cas9-generated mutants exhibited decreased GLC and increased daidzein content (DAC). Haplotype analysis revealed that GmGLY1 allelic variations significantly affect the GLC accumulation. These findings enhance our understanding of genes influencing GLC in soybean and may guide breeding for lines with high and stable GLC.

Multi-omics identification of a key glycosyl hydrolase gene FtGH1 involved in rutin hydrolysis in Tartary buckwheat (Fagopyrum tataricum)

Rutin, a flavonoid rich in buckwheat, is important for human health and plant resistance to external stresses. The hydrolysis of rutin to quercetin underlies the bitter taste of Tartary buckwheat. In order to identify rutin hydrolysis genes, a 200 genotypes mini-core Tartary buckwheat germplasm resource was re-sequenced with 30-fold coverage depth. By combining the content of the intermediate metabolites of rutin metabolism with genome resequencing data, metabolite genome-wide association analyses (GWAS) eventually identified a glycosyl hydrolase gene FtGH1, which could hydrolyse rutin to quercetin. This function was validated both in Tartary buckwheat overexpression hairy roots and in vitro enzyme activity assays. Mutation of the two key active sites, which were determined by molecular docking and experimentally verified via overexpression in hairy roots and transient expression in tobacco leaves, exhibited abnormal subcellular localization, suggesting functional changes. Sequence analysis revealed that mutation of the FtGH1 promoter in accessions of two haplotypes might be necessary for enzymatic activity. Co-expression analysis and GWAS revealed that FtbHLH165 not only repressed FtGH1 expression, but also increased seed length. This work reveals a potential mechanism behind rutin metabolism, which should provide both theoretical support in the study of flavonoid metabolism and in the molecular breeding of Tartary buckwheat.

The GmSTF1/2-GmBBX4 negative feedback loop acts downstream of blue-light photoreceptors to regulate isoflavonoid biosynthesis in soybean

Isoflavonoids, secondary metabolites derived from the phenylalanine pathway, are predominantly biosynthesized in legumes, especially soybean (Glycine max). They are not only essential for plant responses to biotic and abiotic stresses but also beneficial to human health. In this study, we report that light signaling controls isoflavonoid biosynthesis in soybean. Blue-light photoreceptors (GmCRY1s, GmCRY2s, GmPHOT1s, and GmPHOT2s) and the transcription factors GmSTF1 and GmSTF2 promote isoflavonoid accumulation, whereas the E3 ubiquitin ligase GmCOP1b negatively regulates isoflavonoid biosynthesis. GmPHOT1s and GmPHOT2s stabilize GmSTF1/2, whereas GmCOP1b promotes the degradation of these two proteins in soybean. GmSTF1/2 regulate the expression of approximately 27.9% of the genes involved in soybean isoflavonoid biosynthesis, including GmPAL2.1, GmPAL2.3, and GmUGT2. They also repress the expression of GmBBX4, a negative regulator of isoflavonoid biosynthesis in soybean. In addition, GmBBX4 physically interacts with GmSTF1 and GmSTF2 to inhibit their transcriptional activation activity toward target genes related to isoflavonoid biosynthesis. Thus, GmSTF1/2 and GmBBX4 form a negative feedback loop that acts downstream of photoreceptors in the regulation of isoflavonoid biosynthesis. Our study provides novel insights into the control of isoflavonoid biosynthesis by light signaling in soybean and will contribute to the breeding of soybean cultivars with high isoflavonoid content through genetic and metabolic engineering.

Isoflavonoid metabolism in leguminous plants: an update and perspectives

Isoflavonoids constitute a well-investigated category of phenylpropanoid-derived specialized metabolites primarily found in leguminous plants. They play a crucial role in legume development and interactions with the environment. Isoflavonoids usually function as phytoalexins, acting against pathogenic microbes in nature. Additionally, they serve as signaling molecules in rhizobial symbiosis. Notably, owing to their molecular structure resembling human estrogen, they are recognized as phytoestrogens, imparting positive effects on human health. This review comprehensively outlines recent advancements in research pertaining to isoflavonoid biosynthesis, transcriptional regulation, transport, and physiological functions, with a particular emphasis on soybean plants. Additionally, we pose several questions to encourage exploration into novel contributors to isoflavonoid metabolism and their potential roles in plant-microbe interactions.

QTL mapping reveals key factors related to the isoflavone contents and agronomic traits of soybean (Glycine max)

BACKGROUND

Soybean is a valuable source of edible protein and oil, as well as secondary metabolites that can be used in food products, cosmetics, and medicines. However, because soybean isoflavone content is a quantitative trait influenced by polygenes and environmental interactions, its genetic basis remains unclear.

RESULTS

This study was conducted to identify causal quantitative trait loci (QTLs) associated with soybean isoflavone contents. A mutant-based F2 population (190 individuals) was created by crossing the Korean cultivar Hwanggeum with low isoflavone contents (1,558 µg g-1) and the soybean mutant DB-088 with high isoflavone contents (6,393 µg g-1). A linkage map (3,049 cM) with an average chromosome length of 152 cM was constructed using the 180K AXIOM® SoyaSNP array. Thirteen QTLs related to agronomic traits were mapped to chromosomes 2, 3, 11, 13, 19, and 20, whereas 29 QTLs associated with isoflavone contents were mapped to chromosomes 1, 3, 8, 11, 14, 15, and 17. Notably, the qMGLI11, qMGNI11, qADZI11, and qTI11, which located Gm11_9877690 to Gm11_9955924 interval on chromosome 11, contributed to the high isoflavone contents and explained 11.9% to 20.1% of the phenotypic variation. This QTL region included four candidate genes, encoding β-glucosidases 13, 14, 17-1, and 17-2. We observed significant differences in the expression levels of these genes at various seed developmental stages. Candidate genes within the causal QTLs were functionally characterized based on enriched GO terms and KEGG pathways, as well as the results of a co-expression network analysis. A correlation analysis indicated that certain agronomic traits (e.g., days to flowering, days to maturity, and plant height) are positively correlated with isoflavone content.

CONCLUSIONS

Herein, we reported that the major QTL associated with isoflavone contents was located in the interval from Gm11_9877690 to Gm11_9955924 (78 kb) on chromosome 11. Four β-glucosidase genes were identified that may be involved in high isoflavone contents of soybean DB-088. Thus, the mutant alleles from soybean DB-088 may be useful for marker-assisted selection in developing soybean lines with high isoflavone contents and superior agronomic traits.

Construction of a genetic map and QTL mapping of seed size traits in soybean

Soybean seed size and seed shape traits are closely related to plant yield and appearance quality. In this study, 186 individual plants of the F2 generation derived from crosses between Changjiang Chun 2 and JiYu 166 were selected as the mapping population to construct a molecular genetic linkage map, and the phenotypic data of hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean under three generations of F2 single plants and F2:3 and F2:4 lines were combined to detect the QTL (quantitative trait loci) for the corresponding traits by ICIM mapping. A soybean genetic map containing 455 markers with an average distance of 6.15 cM and a total length of 2799.2 cM was obtained. Forty-nine QTLs related to the hundred-grain weight, seed length, seed width, and seed length-to-width ratio of soybean were obtained under three environmental conditions. A total of 10 QTLs were detected in more than two environments with a phenotypic variation of over 10%. Twelve QTL clusters were identified on chromosomes 1, 2, 5, 6, 8, 13, 18, and 19, with the majority of the overlapping intervals for hundred-grain weight and seed width. These results will lay the theoretical and technical foundation for molecularly assisted breeding in soybean seed weight and seed shape. Eighteen candidate genes that may be involved in the regulation of soybean seed size were screened by gene functional annotation and GO enrichment analysis.

Identification of candidate genes for soybean seed coat-related traits using QTL mapping and GWAS

Seed coat color is a typical morphological trait that can be used to reveal the evolution of soybean. The study of seed coat color-related traits in soybeans is of great significance for both evolutionary theory and breeding practices. In this study, 180 F₁₀ recombinant inbred lines (RILs) derived from the cross between the yellow-seed coat cultivar Jidou12 (ZDD23040, JD12) and the wild black-seed coat accession Y9 (ZYD02739) were used as materials. Three methods, single-marker analysis (SMA), interval mapping (IM), and inclusive composite interval mapping (ICIM), were used to identify quantitative trait loci (QTLs) controlling seed coat color and seed hilum color. Simultaneously, two genome-wide association study (GWAS) models, the generalized linear model (GLM) and mixed linear model (MLM), were used to jointly identify seed coat color and seed hilum color QTLs in 250 natural populations. By integrating the results from QTL mapping and GWAS analysis, we identified two stable QTLs (qSCC02 and qSCC08) associated with seed coat color and one stable QTL (qSHC08) related to seed hilum color. By combining the results of linkage analysis and association analysis, two stable QTLs (qSCC02, qSCC08) for seed coat color and one stable QTL (qSHC08) for seed hilum color were identified. Upon further investigation using Kyoto Encyclopedia of Genes and Genomes (KEGG) analysis, we validated the previous findings that two candidate genes (CHS3C and CHS4A) reside within the qSCC08 region and identified a new QTL, qSCC02. There were a total of 28 candidate genes in the interval, among which Glyma.02G024600, Glyma.02G024700, and Glyma.02G024800 were mapped to the glutathione metabolic pathway, which is related to the transport or accumulation of anthocyanin. We considered the three genes as potential candidate genes for soybean seed coat-related traits. The QTLs and candidate genes detected in this study provide a foundation for further understanding the genetic mechanisms underlying soybean seed coat color and seed hilum color and are of significant value in marker-assisted breeding.

Combined analysis of the metabolome and transcriptome provides insight into seed oil accumulation in soybean

BACKGROUND

Soybean (Glycine max (L.) Merr) is an important source of human food, animal feed, and bio-energy. Although the genetic network of lipid metabolism is clear in Arabidopsis, the understanding of lipid metabolism in soybean is limited.

RESULTS

In this study, 30 soybean varieties were subjected to transcriptome and metabolome analysis. In total, 98 lipid-related metabolites were identified, including glycerophospholipid, alpha-linolenic acid, linoleic acid, glycolysis, pyruvate, and the sphingolipid pathway. Of these, glycerophospholipid pathway metabolites accounted for the majority of total lipids. Combining the transcriptomic and metabolomic analyses, we found that 33 lipid-related metabolites and 83 lipid-related genes, 14 lipid-related metabolites and 17 lipid-related genes, and 12 lipid-related metabolites and 25 lipid-related genes were significantly correlated in FHO (five high-oil varieties) vs. FLO (five low-oil varieties), THO (10 high-oil varieties) vs. TLO (10 low-oil varieties), and HO (15 high-oil varieties) vs. LO (15 low-oil varieties), respectively.

CONCLUSIONS

The GmGAPDH and GmGPAT genes were significantly correlated with lipid metabolism genes, and the result revealed the regulatory relationship between glycolysis and oil synthesis. These results improve our understanding of the regulatory mechanism of soybean seed oil improvement.

GmFtsH25 overexpression increases soybean seed yield by enhancing photosynthesis and photosynthates

Increasing plant photosynthetic capacity is a promising approach to boost yields, but it is particularly challenging in C₃ crops, such as soybean (Glycine max (L.) Merr.). Here, we identified GmFtsH25, encoding a member of the filamentation temperature-sensitive protein H protease family, as a major gene involved in soybean photosynthesis, using linkage mapping and a genome-wide association study. Overexpressing GmFtsH25 resulted in more grana thylakoid stacks in chloroplasts and increased photosynthetic efficiency and starch content, while knocking out GmFtsH25 produced the opposite phenotypes. GmFtsH25 interacted with photosystem I light harvesting complex 2 (GmLHCa2), and this interaction may contribute to the observed enhanced photosynthesis. GmFtsH25 overexpression lines had superior yield traits, such as yield per plant, compared to the wild type and knockout lines. Additionally, we identified an elite haplotype of GmFtsH25, generated by natural mutations, which appears to have been selected during soybean domestication. Our study sheds light on the molecular mechanism by which GmFtsH25 modulates photosynthesis and provides a promising strategy for improving the yields of soybean and other crops.

Dual-function C2H2-type zinc-finger transcription factor GmZFP7 contributes to isoflavone accumulation in soybean

Isoflavones are a class of secondary metabolites produced by legumes and play important roles in human health and plant stress tolerance. The C2H2 zinc-finger transcription factor (TF) functions in plant stress tolerance, but little is known about its function in isoflavone regulation in soybean (Glycine max). Here, we report a C2H2 zinc-finger TF gene, GmZFP7, which regulates isoflavone accumulation in soybean. Overexpressing GmZFP7 increased the isoflavone concentration in both transgenic hairy roots and plants. By contrast, silencing GmZFP7 expression significantly reduced isoflavone levels. Metabolomic and qRT-PCR analysis revealed that GmZFP7 can increase the flux of the phenylpropanoid pathway. Furthermore, dual-luciferase and electrophoretic mobility shift assays showed that GmZFP7 regulates isoflavone accumulation by influencing the expression of Isoflavone synthase 2 (GmIFS2) and Flavanone 3 β-hydroxylase 1 (GmF3H1). In this study, we demonstrate that GmZFP7 contributes to isoflavone accumulation by regulating the expression of the gateway enzymes (GmIFS2 and GmF3H1) of competing phenylpropanoid pathway branches to direct the metabolic flux into isoflavone. A haplotype analysis indicated that important natural variations were present in GmZFP7 promoters, with P-Hap1 and P-Hap3 being the elite haplotypes. Our findings provide insight into how GmZFP7 regulates the phenylpropanoid pathway and enhances soybean isoflavone content.

Identification of hub genes regulating isoflavone accumulation in soybean seeds via GWAS and WGCNA approaches

INTRODUCTION

Isoflavones are the secondary metabolites synthesized by the phenylpropanoid biosynthesis pathway in soybean that benefits human and plant health.

METHODS

In this study, we have profiled seed isoflavone content by HPLC in 1551 soybean accessions grown in Beijing and Hainan for two consecutive years (2017 and 2018) and in Anhui for one year (2017).

RESULTS

A broad range of phenotypic variations was observed for individual and total isoflavone (TIF) content. The TIF content ranged from 677.25 to 5823.29 µg g^-1 in the soybean natural population. Using a genome-wide association study (GWAS) based on 6,149,599 single nucleotide polymorphisms (SNPs), we identified 11,704 SNPs significantly associated with isoflavone contents; 75% of them were located within previously reported QTL regions for isoflavone. Two significant regions on chromosomes 5 and 11 were associated with TIF and malonylglycitin across more than 3 environments. Furthermore, the WGCNA identified eight key modules: black, blue, brown, green, magenta, pink, purple, and turquoise. Of the eight co-expressed modules, brown (r = 0.68***), magenta (r = 0.64***), and green (r = 0.51**) showed a significant positive association with TIF, as well as with individual isoflavone contents. By combining the gene significance, functional annotation, and enrichment analysis information, four hub genes Glyma.11G108100, Glyma.11G107100, Glyma.11G106900, and Glyma.11G109100 encoding, basic-leucine zipper (bZIP) transcription factor, MYB4 transcription factor, early responsive to dehydration, and PLATZ transcription factor respectively were identified in brown and green modules. The allelic variation in Glyma.11G108100 significantly influenced individual and TIF accumulation.

DISCUSSION

The present study demonstrated that the GWAS approach, combined with WGCNA, could efficiently identify isoflavone candidate genes in the natural soybean population.

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.

Genome-wide association studies for soybean epicotyl length in two environments using 3VmrMLM

Germination of soybean seed is the imminent vital process after sowing. The status of plumular axis and radicle determine whether soybean seed can emerge normally. Epicotyl, an organ between cotyledons and first functional leaves, is essential for soybean seed germination, seedling growth and early morphogenesis. Epicotyl length (EL) is a quantitative trait controlled by multiple genes/QTLs. Here, the present study analyzes the phenotypic diversity and genetic basis of EL using 951 soybean improved cultivars and landraces from Asia, America, Europe and Africa. 3VmrMLM was used to analyze the associations between EL in 2016 and 2020 and 1,639,846 SNPs for the identification of QTNs and QTN-by-environment interactions (QEIs)".A total of 180 QTNs and QEIs associated with EL were detected. Among them, 74 QTNs (ELS_Q) and 16 QEIs (ELS_QE) were identified to be associated with ELS (epicotyl length of single plant emergence), and 60 QTNs (ELT_Q) and 30 QEIs (ELT_QE) were identified to be associated with ELT (epicotyl length of three seedlings). Based on transcript abundance analysis, GO (Gene Ontology) enrichment and haplotype analysis, ten candidate genes were predicted within nine genic SNPs located in introns, upstream or downstream, which were supposed to be directly or indirectly involved in the process of seed germination and seedling development., Of 10 candidate genes, two of them (Glyma.04G122400 and Glyma.18G183600) could possibly affect epicotyl length elongation. These results indicate the genetic basis of EL and provides a valuable basis for specific functional studies of epicotyl traits.

Irradiation with carbon ion beams affects soybean nutritional quality in early generations

As people's demand for healthy diet increases, improving soybean seed nutritional quality is becoming as important as yield. Carbon ion beam radiation (CIBR) is an effective method to create soybean mutants, and thus breeding cultivars with better seed nutritional quality. In this study, the high-yield soybean line 'Dongsheng 28' was used, and three CIBR doses (100, 120, and 140 Gy) were used to explore the characteristics of quality separation and variation in the offspring of early mutant populations. Eleven quality traits, including protein, oil, sucrose, soluble sugar, iron (Fe), manganese (Mn), zinc (Zn), cupper (Cu), daidzin, glycitin, and genistin concentrations were analyzed in the M₂ and M₃ generations. The results revealed that the range of protein and oil concentration of all three CIBR doses changed by 38.5-42.9% and 18.8-23.8% in the M₂ and M₃ generations, respectively, while soluble sugar and sucrose concentrations changed by 48.1-123.4 and 22.7-74.7 mg/g, with significant effects by 140 Gy across the two generations. Therefore, around the optimum range, a higher CIBR dose is better for high protein, oil, and sugar varieties selection. In general, irradiation raised isoflavone concentrations, but 140 Gy had an inhibitory effect on isoflavone concentrations in the M₃ generation. Although a variety could not be released in the M₂ or M₃ generation, the results of this study have important guiding significance for the targeted cultivation of specific nutritional quality materials. For instance, a lower irradiation dose is preferable when breeding targets are higher isoflavones and Mn concentrations. It is essential to increase the irradiation dose if the breeding targets contain high levels of protein, oil, sucrose, soluble sugars, Fe, Zn, and Cu.

Genome-wide identification, characterization of Serotonin N-acetyltransferase and deciphering its importance under development, biotic and abiotic stress in soybean

Serotonin N-acetyltransferase (SNAT) is the penultimate enzyme involved in plant melatonin biosynthesis. Identifying its expression under development and stress will reveal the regulatory role in the soybean. To identify and characterize SNAT, we employed genome-wide analysis, gene structure, cis-acting elements, expression, and enzyme activity. We identified seven putative genes by genome-wide analysis and found chloroplast signal peptides in three GmSNATs. To elucidate GmSNATs role, expression datasets of more than a hundred samples related to circadian rhythm, developmental stages, and stress conditions were analysed. Notably, the expression of GmSNAT1 did not show significant expression during biotic and abiotic stress. The GmSNAT1 sequence showed 67.8 and 72.2 % similarities with OsSNAT and AtSNAT, respectively. The Km and Vmax of the purified recombinant GmSNAT1 were 657 μM and 3780 pmol/min/mg, respectively. To further understand the GmSNAT1 role, we supplemented different concentrations of serotonin and melatonin to in-vitro cultures and seed priming. These studies revealed that the GmSNAT1 expression was significantly up-regulated at higher concentrations of serotonin and down-regulated at higher melatonin concentrations. We speculate that a high concentration of melatonin during abiotic, biotic stress, and in-vitro cultures are responsible for regulating GmSNAT1 expression, which may regulate them at the enzyme level during stress in soybean.

Genome wide association study to detect genetic regions related to isoflavone content in a mutant soybean population derived from radiation breeding

Isoflavones are major secondary metabolites that are exclusively produced by legumes, including soybean. Soy isoflavones play important roles in human health as well as in the plant defense system. The isoflavone content is influenced by minor-effect quantitative trait loci, which interact with polygenetic and environmental factors. It has been difficult to clarify the regulation of isoflavone biosynthesis because of its complex heritability and the influence of external factors. Here, using a genotype-by-sequencing-based genome-wide association mapping study, 189 mutant soybean genotypes (the mutant diversity pool, MDP) were genotyped on the basis of 25,646 high-quality single nucleotide polymorphisms (SNPs) with minor allele frequency of >0.01 except for missing data. All the accessions were phenotyped by determining the contents of 12 isoflavones in the soybean seeds in two consecutive years (2020 and 2021). Then, quantitative trait nucleotides (QTNs) related to isoflavone contents were identified and validated using multi-locus GWAS models. A total of 112 and 46 QTNs related to isoflavone contents were detected by multiple MLM-based models in 2020 and 2021, respectively. Of these, 12 and 5 QTNs were related to more than two types of isoflavones in 2020 and 2021, respectively. Forty-four QTNs were detected within the 441-Kb physical interval surrounding Gm05:38940662. Of them, four QTNs (Gm05:38936166, Gm05:38936167, Gm05:38940662, and Gm05:38940717) were located at Glyma.05g206900 and Glyma.05g207000, which encode glutathione S-transferase THETA 1 (GmGSTT1), as determined from previous quantitative trait loci annotations and the literature. We detected substantial differences in the transcript levels of GmGSTT1 and two other core genes (IFS1 and IFS2) in the isoflavone biosynthetic pathway between the original cultivar and its mutant. The results of this study provide new information about the factors affecting isoflavone contents in soybean seeds and will be useful for breeding soybean lines with high and stable concentrations of isoflavones.

Deep polygenic neural network for predicting and identifying yield-associated genes in Indonesian rice accessions

As the fourth most populous country in the world, Indonesia must increase the annual rice production rate to achieve national food security by 2050. One possible solution comes from the nanoscopic level: a genetic variant called Single Nucleotide Polymorphism (SNP), which can express significant yield-associated genes. The prior benchmark of this study utilized a statistical genetics model where no SNP position information and attention mechanism were involved. Hence, we developed a novel deep polygenic neural network, named the NucleoNet model, to address these obstacles. The NucleoNets were constructed with the combination of prominent components that include positional SNP encoding, the context vector, wide models, Elastic Net, and Shannon’s entropy loss. This polygenic modeling obtained up to 2.779 of Mean Squared Error (MSE) with 47.156% of Symmetric Mean Absolute Percentage Error (SMAPE), while revealing 15 new important SNPs. Furthermore, the NucleoNets reduced the MSE score up to 32.28% compared to the Ordinary Least Squares (OLS) model. Through the ablation study, we learned that the combination of Xavier distribution for weights initialization and Normal distribution for biases initialization sparked more various important SNPs throughout 12 chromosomes. Our findings confirmed that the NucleoNet model was successfully outperformed the OLS model and identified important SNPs to Indonesian rice yields.

Variation in Melatonin Contents and Genetic Dissection of Melatonin Biosynthesis in Sesame

In recent years, people have become increasingly interested in bioactive molecules in plants that are beneficial to human health, and melatonin (N-acetyl-5-methoxytryptamine) has attracted research attention due to its excellent performance. In this study, the content of melatonin in oilseeds was investigated. From the results, it was found that sesame is an important natural food source of melatonin intake. Furthermore, the variation in melatonin content was explored in a natural sesame population, and its contents varied from 0.04 to 298.62 ng g^-1. Through a genome-wide association study (GWAS), a candidate gene SiWRKY67 was screened that regulates melatonin content in sesame. The sesame hairy root transformation system was developed and used to verify this gene, and it was found that the overexpression of SiWRKY67 could positively promote the melatonin content in the hairy roots. Our results provide not only a foundation for understanding the genetic structure of melatonin content in sesame seeds but also a reference for the marker-assisted breeding of sesame varieties with high melatonin content.

Applications of Genomic Tools in Plant Breeding: Crop Biofortification

Crop breeding has mainly been focused on increasing productivity, either directly or by decreasing the losses caused by biotic and abiotic stresses (that is, incorporating resistance to diseases and enhancing tolerance to adverse conditions, respectively). Quite the opposite, little attention has been paid to improve the nutritional value of crops. It has not been until recently that crop biofortification has become an objective within breeding programs, through either conventional methods or genetic engineering. There are many steps along this long path, from the initial evaluation of germplasm for the content of nutrients and health-promoting compounds to the development of biofortified varieties, with the available and future genomic tools assisting scientists and breeders in reaching their objectives as well as speeding up the process. This review offers a compendium of the genomic technologies used to explore and create biodiversity, to associate the traits of interest to the genome, and to transfer the genomic regions responsible for the desirable characteristics into potential new varieties. Finally, a glimpse of future perspectives and challenges in this emerging area is offered by taking the present scenario and the slow progress of the regulatory framework as the starting point.

Progress in soybean functional genomics over the past decade

Soybean is one of the most important oilseed and fodder crops. Benefiting from the efforts of soybean breeders and the development of breeding technology, large number of germplasm has been generated over the last 100 years. Nevertheless, soybean breeding needs to be accelerated to meet the needs of a growing world population, to promote sustainable agriculture and to address future environmental changes. The acceleration is highly reliant on the discoveries in gene functional studies. The release of the reference soybean genome in 2010 has significantly facilitated the advance in soybean functional genomics. Here, we review the research progress in soybean omics (genomics, transcriptomics, epigenomics and proteomics), germplasm development (germplasm resources and databases), gene discovery (genes that are responsible for important soybean traits including yield, flowering and maturity, seed quality, stress resistance, nodulation and domestication) and transformation technology during the past decade. At the end, we also briefly discuss current challenges and future directions.

Novel QTL and Meta-QTL Mapping for Major Quality Traits in Soybean

Isoflavone, protein, and oil are the most important quality traits in soybean. Since these phenotypes are typically quantitative traits, quantitative trait locus (QTL) mapping has been an efficient way to clarify their complex and unclear genetic background. However, the low-density genetic map and the absence of QTL integration limited the accurate and efficient QTL mapping in previous researches. This paper adopted a recombinant inbred lines (RIL) population derived from 'Zhongdou27'and 'Hefeng25' and a high-density linkage map based on whole-genome resequencing to map novel QTL and used meta-analysis methods to integrate the stable and consentaneous QTL. The candidate genes were obtained from gene functional annotation and expression analysis based on the public database. A total of 41 QTL with a high logarithm of odd (LOD) scores were identified through composite interval mapping (CIM), including 38 novel QTL and 2 Stable QTL. A total of 660 candidate genes were predicted according to the results of the gene annotation and public transcriptome data. A total of 212 meta-QTL containing 122 stable and consentaneous QTL were mapped based on 1,034 QTL collected from previous studies. For the first time, 70 meta-QTL associated with isoflavones were mapped in this study. Meanwhile, 69 and 73 meta-QTL, respectively, related to oil and protein were obtained as well. The results promote the understanding of the biosynthesis and regulation of isoflavones, protein, and oil at molecular levels, and facilitate the construction of molecular modular for great quality traits in soybean.

The Soybean High Density 'Forrest' by 'Williams 82' SNP-Based Genetic Linkage Map Identifies QTL and Candidate Genes for Seed Isoflavone Content

Isoflavones are secondary metabolites that are abundant in soybean and other legume seeds providing health and nutrition benefits for both humans and animals. The objectives of this study were to construct a single nucleotide polymorphism (SNP)-based genetic linkage map using the ‘Forrest’ by ‘Williams 82’ (F×W82) recombinant inbred line (RIL) population (n = 306); map quantitative trait loci (QTL) for seed daidzein, genistein, glycitein, and total isoflavone contents in two environments over two years (NC-2018 and IL-2020); identify candidate genes for seed isoflavone. The FXW82 SNP-based map was composed of 2075 SNPs and covered 4029.9 cM. A total of 27 QTL that control various seed isoflavone traits have been identified and mapped on chromosomes (Chrs.) 2, 4, 5, 6, 10, 12, 15, 19, and 20 in both NC-2018 (13 QTL) and IL-2020 (14 QTL). The six QTL regions on Chrs. 2, 4, 5, 12, 15, and 19 are novel regions while the other 21 QTL have been identified by other studies using different biparental mapping populations or genome-wide association studies (GWAS). A total of 130 candidate genes involved in isoflavone biosynthetic pathways have been identified on all 20 Chrs. And among them 16 have been identified and located within or close to the QTL identified in this study. Moreover, transcripts from four genes (Glyma.10G058200, Glyma.06G143000, Glyma.06G137100, and Glyma.06G137300) were highly abundant in Forrest and Williams 82 seeds. The identified QTL and four candidate genes will be useful in breeding programs to develop soybean cultivars with high beneficial isoflavone contents.

Iron toxicity-induced regulation of key secondary metabolic processes associated with the quality and resistance of Panax ginseng and Panax quinquefolius

Panax ginseng and Panax quinquefolius can survive for long periods of time in iron toxicity-stressed environments, which cause rusty roots and reduced productivity. To reveal the proteomic changes in these two Panax species in response to iron toxicity stress, plants of these two species were divided into a control group and an iron toxicity-stress group. An isobaric tags for relative and absolute quantitation (iTRAQ) proteomics approach was used to explore the changes in protein accumulation and the potential mechanisms underlying the response to iron toxicity stress in the two Panax species. Proteomic analyses revealed approximately 725 differentially expressed proteins (DEPs) in the iron toxicity-stress and control groups, including 233 and 492 proteins whose expression was upregulated and downregulated, respectively. The expression of DEPs related to photosynthesis was significantly downregulated, and DEPs whose expression was significantly upregulated were associated with redox reactions. Many upregulated DEPs were also involved in pathways such as those involving phenylpropanoid, flavonoid, isoflavone and ginsenoside synthesis. The abundance of some ginsenoside monomers (Rg1 and Rb3) also significantly increased in P. ginseng and P. quinquefolius. Moreover, P. quinquefolius contained 455 DEPs whose expression was higher than that in P. ginseng, including many proteins related to the regulation of ion homeostasis, indicating that P. quinquefolius is more resistant to iron toxicity stress than P. ginseng is.