POWR1 is a domestication gene pleiotropically regulating seed quality and yield in soybean

Loss of phytochromobilin synthase activity leads to larger seeds with higher protein content in soybean

Seed weight is an important agronomic trait that is related to seed size and determines yield in soybean (Glycine max). We previously identified a spontaneous soybean mutant with light green leaves called ygl2. Here, we cloned YGL2, which encodes a phytochromobilin (PΦB) synthase involved in synthesizing the chromophore of the photoreceptor phytochrome. The lesion in ygl2 is a 10-bp deletion, causing a frameshift mutation and a premature stop codon that truncates the encoded protein. In contrast to the wild type, ygl2 lacks PΦB synthase activity and function. This appears to promote cell expansion, thus increasing seed weight. Surprisingly, the ygl2 mutant also exhibits excellent traits including early maturity and high protein content. Moreover, under the condition of dense planting (3 cm), the yield of YGL2 mutant was significantly increased. Mutants harboring ygl2 mutations that we generated via gene editing had enlarged seeds with high protein content. Moreover, the expression levels of the photoperiod sensitive genes (E1, FT2a, FT5a) were lower in the ygl2 mutant than in the wild type. Mutating the YGL2 gene resulted in increased biliverdin content and decreased heme content. We determined that Lhcb4, a chlorophyll a/b binding protein in photosystem II, interacts with YGL2 but not with the mutant version of the protein. We thus identified a mutation in a PΦB synthase gene that enhances seed weight in soybean, providing a promising breeding target for this important crop.

AlphaFold-Guided Bespoke Gene Editing Enhances Field-Grown Soybean Oil Contents

Enhancing the oil or protein content of soybean, a major crop for oil and protein production is highly desirable. GmSWEET10a encodes a sugar transporter that is strongly selected during domestication and breeding, increasing seed size and oil content. GmSWEET10b is functionally similar to GmSWEET10a, yet has not been artificially selected. Here, AlphaFold is used to find that C-terminal variants of GmSWEET10a can endow enhanced or reduced transport activity. Guided by AlphaFold, the functionality is improved for GmSWEET10a in terms of oil content through gene editing. Furthermore, novel GmSWEET10b haplotypes possessing strengthened or weakened sugar-transport capabilities that are absent in nature are engineered. Consequently, soybean oil content or protein content in independent GmSWEET10b gene-edited lines during multi-year and multi-site field trials is consistently increased, without negatively affecting yield. The study demonstrates that the combination of AlphaFold-guided protein design and gene editing has the potential to generate novel beneficial alleles, which can optimize protein function in the context of crop breeding.

Identification of HSSP1 as a regulator of soybean protein content through QTL analysis and Soy-SPCC network

Soybeans (Glycine max L. Merr.) are a major source of plant-based protein for human nutrition and livestock feed. Enhancing the protein content of soybean seeds is vital for meeting growing dietary needs and promoting sustainable agricultural practices. In this study, we first performed QTL (Quantitative Trait Loci) mapping analysis and constructed a Soybean Seed Protein Content Co-expression (Soy-SPCC) network to identify key genes associated with soybean seed protein accumulation. Next, we investigated the role of High Seed Storage Protein1 (HSSP1) in regulating soybean seed protein content through a comprehensive analysis. Functional validation through overexpression and gene knockout experiments demonstrated that HSSP1, a key component of the Soy-SPCC network, significantly influences seed storage protein levels. Particularly, HSSP1 enhances the expression of GmCG1 by binding directly to its cis-acting element, leading to increased protein content in soybean seeds. Furthermore, we performed a molecular module stacking breeding analysis of 120 candidate genes identified from the Soy-SPCC network, including HSSP1, to identify genetic variations associated with protein content. This study provides a novel perspective on soybean protein regulation. The identification of HSSP1 as a critical regulator offers valuable insights for developing high-protein soybean varieties and advancing breeding strategies aimed at improving soybean seed quality.

A R2R3-MYB Transcription Factor of GmMYB62 Regulates Seed-Coat Color and Seed Size in Arabidopsis

The seed-coat color and seed size have an impact on both the evolutionary fitness and the grain yield of crops. Soybean is a major oil crop, and the seed-coat color and seed size exhibit natural diversity among the different soybean varieties. Here, we found an R2R3-MYB transcription factor of GmMYB62, which shows a significant increase in expression as the seed-coat color changes from yellow to black in different soybean varieties. The GmMYB62 was specifically highly expressed in reproductive organs, especially in floral organs in soybeans. The GmMYB62 encodes a nuclear protein that contains two MYB domains. In the phylogenetic analysis, the GmMYB62 was relatively conserved after the divergence of the monocots and dicots, and it also grouped with transcriptional repressors of MYBs in anthocyanin synthesis. The GmMYB62 was overexpressed in Arabidopsis and the seeds displayed a pale-brown coat in GmMYB62 overexpression lines, in contrast to the dark-brown seed coat observed in wild-type of Col-0. The anthocyanin content in the GmMYB62 overexpression lines was dramatically reduced when compared to Col-0. Additionally, the seeds in overexpression lines showed shorter lengths, larger widths, and lower thousand-seed weights than those in Col-0. Furthermore, the genes related to anthocyanin synthesis and seed size regulation were investigated, and expression of eight genes that involved in anthocyanin synthesis pathway, like chalcone synthase (CHS), chalcone isomerase (CHI), flavanone 3-hydroxylase (F3H), and anthocyanidin synthase (ANS) were severely inhibited in the GmMYB62 overexpression lines when compared to Col-0. In addition, the ARGOS-LIKE (ARL), B-Type Cyclin 1 (CYCB1), and enhancer of DA1-1 (EOD3), which govern cell expansion and proliferation, were highly expressed in GmMYB62 overexpression lines when compared to Col-0. Overall, this study sheds new light on the control of seed-coat color and seed size by GmMYB62 and provides potentially valuable targets for improving crop seed quality.

Genome-wide exploration of soybean domestication traits: integrating association mapping and SNP × SNP interaction analyses

Soybean domestication has been essential for crop evolution, adaptation, and modern breeding. Despite advancements in understanding soybean genetics, the genetic basis of DRTs has yet to be fully explored, particularly in the context of genome-wide association studies (GWASs) and gene interaction analyses (epistasis). This study evaluated 198 diverse soybean accessions using 23,574 high-quality SNPs obtained via ddRAD-seq. Nine key DRTs-including those related to seed size (length, width, and thickness), seed coat color, cotyledon color, hypocotyl color, stem growth habit, flower color, pod color, pubescence, and pod-shattering-were phenotyped in two environments. A GWASs conducted via the FarmCPU and BLINK models identified 78 significant SNPs, 14 consistently detected across both environments and models, demonstrating stability. Notably, the SNP rs.Gm16.29778273 linked to pod-shattering resistance. The functional annotation linked three known quantitative trait loci /genes and revealed 11 novel candidate genes associated with DRTs, providing insights into their roles via Gene Ontology (GO) terms. The main effect SNP × SNP interaction analysis revealed that the significant SNP rs.Gm13.16695800 exhibits a pleiotropic effect, controlling both hypocotyl and flower color. Furthermore, 324 epistatic interactions were identified, influencing the expression of DRTs, thereby highlighting the complex genetic architecture underlying these traits. These findings offer valuable insights into domestication and the traits linked to higher yield. They provide a solid foundation for developing marker-assisted selection (MAS) strategies and functional studies to improve soybean breeding for resilient, high-yielding varieties.

Natural variation in the GmVPE1 promoter contributes to phosphorus re-translocation to seeds and improves soybean yield

Phosphorus (P) is an essential yet frequently deficient plant nutrient. Optimizing P distribution and recycling between tissues is vital for improving P utilization efficiency (PUE). Yet, the mechanisms underlying the transport and re-translocation of P within plants remain unclear. Here, wide-ranging natural diversity in seed P allocation and positive correlations among yield traits were found using 190 soybean accessions in field trials. Among them, the P-efficient genotype BX10 outperformed BD2 in assessments of PUE that were largely explained through differences in P redistribution from pods to seeds under low P stress. Pods of BX10 were therefore subjected to transcriptome analysis, and GmVPE1 was identified as a vacuolar Pi transporter to investigate further. Importantly, significant DNA polymorphism in GmVPE1 promoter regions was remarkably associated with seed weight among soybean accessions grown on P-deficient soils. Further analyses suggested that mRNA abundance of GmVPE1 in haplotype 2 (Hap) is significantly higher than that GmVPE1Hap1. GmVPE1 was highly upregulated by P deficiency and preferentially expressed in pods, seeds, and seed coats, which was consistent with GUS staining using transgenic soybean plants carrying pGmVPE1Hap2::GUS. Near-isogenic lines carrying the GmVPE1Hap2 allele, along with stable transgenic soybeans overexpressing GmVPE1 in a GmVPE1Hap1 background, had increases in PUE, more seed setting, and greater yields in both greenhouse and field trials than control plants. In summary, natural variation among GmVPE1 alleles determines genetic expression and subsequent P re-translocation phenotypes, which impacts PUE and yield, and thereby makes this an important genetic resource for soybean molecular breeding.

A genome-wide association study prioritizes VRN1-2 as a candidate gene associated with plant height in soybean

Plant height is an important architectural trait that affects crop growth, yield, and stress resistance. Tremendous efforts have been dedicated to revealing the genetic basis or regulatory mechanism; however, the underlying molecular mechanism remains largely unknown primarily due to the lack of controlling genes. In this study, we conducted a single-nucleotide resolution genome-wide association study (GWAS) of plant height using a diverse soybean panel collected worldwide with 6.7 million genome-wide variants (SNPs and Indels). The GWAS of plant height identified three QTLs on chromosomes 10, 18, and 19, of which the one on chromosome 19 precisely co-localized with Dt1, known as a major stem growth habit-controlling gene. Other loci without reported genes for plant height were regarded to be new. A close investigation within QTL intervals proposed nine genes that were likely involved in the regulation of plant height according to the expression specificity in developing shoot tip meristems. VRN1-2 underlies the significant QTL on chromosome 10 was prioritized as the most promising candidate gene. VRN1-2 shows higher expression in Williams 82 with indeterminate growth habit than Dongnong50 with semi-determinate growth habit across vegetative (V2, V3) and reproductive (R1) growth stages. VRN1-2 carries non-synonymous variants in the coding region that were significantly associated with plant height variation. The GT allele conferring short plant height was likely subjected to artificial selection during domestication. These results provide a source of new loci and genes for further elaborating the regulatory mechanism of plant height and the key variants would facilitate soybean molecular breeding.

Characterization of a G. max × G. soja nested association mapping population and identification of loci controlling seed composition traits from wild soybean

Wild soybean (Glycine soja Siebold & Zucc.) has valuable genetic diversity for improved disease resistance, stress tolerance, seed protein content and seed sulfur-containing amino acid concentrations. Many studies have reported loci controlling seed composition traits based on cultivated soybean populations, but wild soybean has been largely overlooked. In this study, a nested association mapping (NAM) population consisting of 10 families and 1107 recombinant inbred lines was developed by crossing 10 wild accessions with the common cultivar NC-Raleigh. Seed composition of the F6 generation grown at two locations was phenotyped, and genetic markers were identified for each line. The average number of recombination events in the wild soybean-derived population was significantly higher than that in the cultivated soybean-derived population, which resulted in a higher resolution for QTL mapping. Segregation bias in almost all NAM families was significantly biased toward the alleles of the wild soybean parent. Through single-family linkage mapping and association analysis of the entire NAM population, new QTLs with positive allele effects were identified from wild parents, including 5, 6, 18, 9, 16, 17 and 20 for protein content, oil content, total protein and oil content, methionine content, cysteine content, lysine content and threonine content, respectively. Candidate genes associated with these traits were identified based on gene annotations and gene expression levels in different tissues. This is the first study to reveal the genetic characteristics of wild soybean-derived populations, landscapes and the extent of effects of QTLs and candidate genes controlling traits from different wild soybean parents.

The comprehensive regulatory network in seed oil biosynthesis

Plant oils play a crucial role in human nutrition, industrial applications and biofuel production. While the enzymes involved in fatty acid (FA) biosynthesis are well-studied, the regulatory networks governing these processes remain largely unexplored. This review explores the intricate regulatory networks modulating seed oil biosynthesis, focusing on key pathways and factors. Seed oil content is determined by the efficiency of de novo FA synthesis as well as influenced by sugar transport, lipid metabolism, FA synthesis inhibitors and fine-tuning mechanisms. At the center of this regulatory network is WRINKLED1 (WRI1), which plays a conserved role in promoting seed oil content across various plant species. WRI1 interacts with multiple proteins, and its expression level is regulated by upstream regulators, including members of the LAFL network. Beyond the LAFL network, we also discuss a potential nuclear factor-Y (NF-Y) regulatory network in soybean with an emphasis on NF-YA and NF-YB and their associated proteins. This NF-Y network represents a promising avenue for future efforts aimed at enhancing oil accumulation and improving stress tolerance in soybean. Additionally, the application of omics-based approaches is of great significance. Advances in omics technologies have greatly facilitated the identification of gene resources, opening new opportunities for genetic improvement. Importantly, several transcription factors involved in oil biosynthesis also participate in stress responses, highlighting a potential link between the two processes. This comprehensive review elucidates the complex mechanisms underlying the regulation of oil biosynthesis, offering insights into potential biotechnological strategies for improving oil production and stress tolerance in oil crops.

Seed-specific expression of phosphatidate phosphohydrolases increases soybean oil content and seed weight

BACKGROUND

Soybean is a major oil crop and a primary protein source for livestock, and soybean oil is the most common input for biodiesel. Identifying genes that enhance soybean yield and oil content is crucial for breeding programs. Phosphatidic acid (PA) phosphohydrolase (PAH), which dephosphorylates PA to diacylglycerol (DAG), plays a critical role in lipid synthesis, and yet their potential in improving agronomic traits of oil crops remains unexplored.

RESULTS

This study shows that seed-specific expression of AtPAH1/2 enhances PA turnover into DAG and triacylglycerol (TAG) accumulation in soybean seeds. PAH overexpression upregulated the expression of DAG acyltransferase (DGAT) but suppressed phospholipid: DAG acyltransferase (PDAT). In addition, seed-specific expression of AtPAH1/2 increases soybean seed size and weight. Furthermore, analysis of the variation of the soybean PAHs in 4414 soybean accessions indicated that the advantageous effects of GmPAHs on oil content and seed weight were selected during domestication.

CONCLUSION

These findings suggest that targeting PAHs represents a promising strategy for enhancing soybean seed oil content and yield in current cultivars and landraces soybeans.

Soybean2035: A decadal vision for soybean functional genomics and breeding

Soybean, the fourth most important crop in the world, uniquely serves as a source of both plant oil and plant protein for the world's food and animal feed. Although soybean production has increased approximately 13-fold over the past 60 years, the continually growing global population necessitates further increases in soybean production. In the past, especially in the last decade, significant progress has been made in both functional genomics and molecular breeding. However, many more challenges should be overcome to meet the anticipated future demand. Here, we summarize past achievements in the areas of soybean omics, functional genomics, and molecular breeding. Furthermore, we analyze trends in these areas, including shortages and challenges, and propose new directions, potential approaches, and possible outputs toward 2035. Our views and perspectives provide insight into accelerating the development of elite soybean varieties to meet the increasing demands of soybean production.

Pulsating Drought and Insect Herbivory Cause Differential Effects on Soybean (Glycine max) Genotypes That Vary in Canopy Wilting Speed

As a result of climate change, global temperatures are increasing, and water scarcity is on the rise. Soybean [Glycine max (L.) Merr] is one of the most important crops in the world due to its importance as food and feed. One of the major limiting factors for soybean production is drought, which can cause up to 80% reduction in yield. Therefore, growers and plant breeders are turning to soybean accessions that demonstrate better water use efficiency (WUE). However, in addition to drought, insect herbivory by soybean looper (Chrysodeixis includens, SBL) and fall armyworm (Spodoptera frugiperda, FAW) can also reduce soybean yield by feeding on foliar and floral organs. Using soybean accessions that differ in their wilting speed, we examined the relationship between physiological traits associated with WUE, and how they affect both herbivore and host plant growth and development. Results showed that both fast- and slow-wilting genotypes displayed strong overcompensation in terms of growth and development, but slow-wilting genotypes produced higher-quality pods and seeds. Regardless of treatment effects, FAW fed at a significantly higher rate than SBL despite being less specialized to feed on soybeans. While fast-wilting plants produced more pods than slow-wilting plants regardless of treatment, slow-wilting plants produced heavier pods with larger and heavier seeds. Collectively, we show that despite fast-wilting plants overcompensating in pod production and growth traits, slow-wilting plants may still be better fit through seed functions.

Comparative Proteomic Atlas of Two Soybean Varieties with Contrasting Seed Oil and Protein Content

As complex quantitative traits, soybean seed oil and protein contents are governed by dynamic proteome networks that remain largely unknown. Here, we investigated the dynamic changes of the proteome during seed maturation across two soybean varieties with contrasting seed oil and protein content. Through optimizing the detectability of low-abundance proteins and utilizing library-free data-independent acquisition (directDIA) mass spectrometry, we unprecedentedly identified 7414 proteins and 3975 protein groups (PGs), substantially expanding the soybean seed proteome. Among the PGs, 1391 differentially accumulated between the two varieties. By comparing the abundance of PGs between the two varieties, we identified the core and periphery proteome of soybean seeds and revealed that variations in the oil and protein content are primarily attributed to the peripheral proteome, which significantly fluctuated across seed developmental stages. Our work presents a quantitative proteomic atlas underlying the variation of seed oil and protein content in soybean varieties and provides insight into the mechanisms regulating the seed oil and protein content in soybean.

The members of zinc finger-homeodomain (ZF-HD) transcription factors are associated with abiotic stresses in soybean: insights from genomics and expression analysis

BACKGROUND

Zinc finger homeodomain (ZF-HD) belongs to the plant-specific transcription factor (TF) family and is widely involved in plant growth, development and stress responses. Despite their importance, a comprehensive identification and analysis of ZF-HD genes in the soybean (Glycine max) genome and their possible roles under abiotic stress remain unexplored.

RESULTS

In this study, 51 ZF-HD genes were identified in the soybean genome that were unevenly distributed on 17 chromosomes. All GmZF-HD genes contained a conserved ZF-HD_dimer domain and had diverse physicochemical features. Furthermore, the GmZF-HD gene structures exhibited 3 to 10 conserved motifs, and most of them showed intronless gene structures. Phylogenetic analysis categorized them into eight major groups with the highest closeness to dicots including Brassica rapa and Malus domestica. The cis-element analysis recognized plant growth and development (10%), phytohormones (31%) and stress-responsive (59%) elements. Synteny analysis identified 73 segmental and 1 tandem duplicated genes that underwent purifying selection. The collinearity analysis revealed that GmZF-HD genes showed higher homology with dicot species, indicating common ancestors with close evolutionary relationships. A total of 94 gma-miRNAs from 41 diverse miRNA families were identified, targeting 40 GmZF-HD genes, with GmZF-HD6 being most targeted by 7 miRNAs, and gma-miR4993 emerging as the dominant miRNA family. Different TFs including ERF, LBD, BBR-BPC and MYB, etc., were predicted in all 51 GmZF-HD genes upstream regions and visualized in the network. Expression profiling through RNA-Seq showed diverse expressions of GmZF-HD genes in different tissues including seeds, roots, shoots and leaves under diverse conditions. Further, the qRT-PCR analysis demonstrated that all tested GmZF-HD genes were significantly induced in soybean leaves, mainly the GmZF-HD5/6/13/39 and GmZF-HD45 genes were significantly upregulated (2.5 to 8.8 folds) under the tested stress treatments compared to control, highlighting their potential roles in response to stresses in soybean.

CONCLUSION

Overall, this study reveals comprehensive insights into the ZF-HD genes in soybeans and provides a valuable contribution towards functional studies for soybean improvement under stress conditions.

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.

Development and Validation of Kompetitive Allele-Specific Polymerase Chain Reaction Markers for Seed Protein Content in Soybean

Seed protein content is a critical trait in soybean breeding, as it provides a primary source of high-quality protein for both human consumption and animal feed. This study aimed to enhance molecular marker-assisted selection for high-protein soybean varieties by developing Kompetitive Allele-Specific Polymerase Chain Reaction (KASP) markers targeted at loci associated with seed protein content. Nineteen markers with high genotyping efficacy were identified through screening. Utilizing SN76 (a high-protein line) as the male parent and SN49 and DS1 (both low-protein lines) as female parents, 484 F6 generation individuals from these hybrid combinations were selected to validate the predictive accuracy of the 19 KASP markers. Notably, KASP-Pro-1, KASP-Pro-2, and KASP-Pro-3 effectively distinguished genotypes associated with high and low protein content, with prediction accuracies of 68.4%, 75.0%, and 83.3%, respectively. These results underscore the reliability and practical utility of the selected molecular markers, which are located within the genes Glyma.03G219900, Glyma.14G119000, and Glyma.17G074400, respectively. Haplotype analysis and gene pyramiding indicate that these three genes may influence seed protein content. Consequently, these KASP markers can be effectively integrated into genetic and genomic research on soybean seed protein content as well as into marker-assisted breeding.

Exploring SoySNP50K and USDA Germplasm Collection Data to Find New QTLs Associated with Protein and Oil Content in Brazilian Genotypes

Genetic diversity within a germplasm collection plays a vital role in the success of breeding programs. However, comprehending this diversity and identifying accessions with desirable traits pose significant challenges. This study utilized publicly available data to investigate SNP markers associated with protein and oil content in Brazilian soybeans. Through this research, twenty-two new QTLs (Quantitative Trait Loci) were identified, and we highlighted the substantial influence of Roanoke, Lee and Bragg ancestor on the genetic makeup of Brazilian soybean varieties. Our findings demonstrate that certain markers are being lost in modern cultivars, while others maintain or even increase their frequency. These observations indicate genomic regions that have undergone selection during soybean introduction in Brazil and could be valuable in breeding programs aimed at enhancing protein or oil content.

Soybean Oil and Protein: Biosynthesis, Regulation and Strategies for Genetic Improvement

Soybean (Glycine max [L.] Merr.) is one of the world's most important sources of oil and vegetable protein. Much of the energy required for germination and early growth of soybean seeds is stored in fatty acids, mainly as triacylglycerols (TAGs), and the main seed storage proteins are β-conglycinin (7S) and glycinin (11S). Recent research advances have deepened our understanding of the biosynthetic pathways and transcriptional regulatory networks that control fatty acid and protein synthesis in organelles such as the plastid, ribosome and endoplasmic reticulum. Here, we review the composition and biosynthetic pathways of soybean oils and proteins, summarizing the key enzymes and transcription factors that have recently been shown to regulate oil and protein synthesis/metabolism. We then discuss the newest genomic strategies for manipulating these genes to increase the food value of soybeans, highlighting important priorities for future research and genetic improvement of this staple crop.

Glycine soja, PI424025, is a valuable genetic resource to improve soybean seed-protein content and composition

Soybean seed-protein content and composition is important because it contributes over half the value of this $61 billion crop. Historic negative correlation between seed-protein content and oil have been reported. Similarly, negative correlation between seed-protein content and yield have been reported but may be at least in part mitigated by increasing the genetic diversity of the elite soybean germplasm. Improvements in amino acid composition of seed-protein would increase the value of soybean meal and protein for animal and human consumption. We have identified a genetic resource in wild soybean germplasm, PI424025B, with elevated seed-protein, elevated cysteine in the seed and increased sulfur content in the seed. We have developed a population of Recombinant Inbred Lines derived from a cross between NC-Raleigh and PI424025B. We evaluated the carbon, nitrogen and sulfur (C, N and S) content of seeds from the progeny, the parents and other high-seed protein soybean lines. N content and C/N (ratio of C to N) were well correlated with protein content measured by NIR. PI424025B had a N content comparable to high-protein soybean lines and a superior N/S. These traits were inherited by some of the progeny. Quantitative Trait Loci (QTL) associated with high-seed protein were identified on chr2, chr20 and chr15 and colocalizes with well characterized loci on chr 15 and chr 20 known to affect seed-protein content and quality. A potentially unique QTL was identified on Chr15. Unlike the chr20 QTL, the chr15 QTL improved S content relative to N content and was superior to other high seed-protein phenotypes tested. These data indicate that PI424025B is a valuable resource to diversify the genetics of soybean while improving soybean seed-protein content and composition.

Knockdown of β-conglycinin α' and α subunits alters seed protein composition and improves salt tolerance in soybean

Soybean is an important plant source of protein worldwide. Increasing demands for soybean can be met by improving the quality of its seed protein. In this study, GmCG-1, which encodes the β-conglycinin α' subunit, was identified via combined genome-wide association study and transcriptome analysis. We subsequently knocked down GmCG-1 and its paralogues GmCG-2 and GmCG-3 with CRISPR-Cas9 technology and generated two stable multigene knockdown mutants. As a result, the β-conglycinin content decreased, whereas the 11S/7S ratio, total protein content and sulfur-containing amino acid content significantly increased. Surprisingly, the globulin mutant exhibited salt tolerance in both the germination and seedling stages. Little is known about the relationship between seed protein composition and the salt stress response in soybean. Metabonomics and RNA-seq analysis indicated that compared with the WT, the mutant was formed through a pathway that was more similar to that of active salicylic acid biosynthesis; however, the synthesis of cytokinin exhibited greater defects, which could lead to increased expression of plant dehydrin-related salt tolerance proteins and cell membrane ion transporters. Population evolution analysis suggested that GmCG-1, GmCG-2, and GmCG-3 were selected during soybean domestication. The soybean accessions harboring GmCG-1Hap1 presented relatively high 11S/7S ratios and relatively high salt tolerance. In conclusion, knockdown of the β-conglycinin α and α' subunits can improve the nutritional quality of soybean seeds and increase the salt tolerance of soybean plants, providing a strategy for designing soybean varieties with high nutritional value and high salt tolerance.

A strategy for identification and characterization of genic mutations using a temperature-sensitive chlorotic soybean mutant as an example

Screening a transposon-mutagenized soybean population led to the discovery of a recessively inherited chlorotic phenotype. This "y24" phenotype results in smaller stature, weaker stems, and a smaller root system. Genome sequencing identified 15 candidate genes with mutations likely to result in a loss of function. Amplicon sequencing of a segregating population was then used to narrow the list to a single candidate mutation, a single-base change in Glyma.07G102300 that disrupts splicing of the second intron. Single cell transcriptomic profiling indicates that this gene is expressed primarily in mesophyll cells, and RNA sequencing data indicate that it is upregulated in germinating seedlings by cold stress. Previous studies have shown that mutations to Os05g34040, the rice ortholog of Glyma.07G102300, produced a chlorotic phenotype that was more pronounced in cool temperatures. Growing soybean y24 mutants at lower temperatures also resulted in a more severe phenotype. In addition, transgenic expression of wild-type Glyma.07G102300 in the knockout mutant of the Arabidopsis ortholog At4930720 rescues the chlorotic phenotype, further supporting the hypothesis that the mutation in Glyma.07G102300 is causal of the y24 phenotype. The variant analysis strategy used to identify the genes underlying this phenotype provides a template for the study of other soybean mutants.

Transcriptional and Metabolomic Analyses Reveal That GmESR1 Increases Soybean Seed Protein Content Through the Phenylpropanoid Biosynthesis Pathway

Soybeans are an economically vital food crop, which is employed as a key source of oil and plant protein globally. This study identified an EREBP-type transcription factor, GmESR1 (Enhance of Shot Regeneration). GmESR1 overexpression has been observed to significantly increase seed protein content. Furthermore, the molecular mechanism by which GmESR1 affects protein accumulation through transcriptome and metabolomics was also identified. The transcriptomic and metabolomic analyses identified 95 differentially expressed genes and 83 differentially abundant metabolites during the seed mid-maturity stage. Co-analysis strategies revealed that GmESR1 overexpression inhibited the biosynthesis of lignin, cellulose, hemicellulose, and pectin via the phenylpropane biosynthetic pathway, thereby redistributing biomass within cells. The key genes and metabolites impacted by this biochemical process included Gm4CL-like, GmCCR, Syringin, and Coniferin. Moreover, it was also found that GmESR1 binds to (AATATTATCATTAAGTACGGAC) during seed development and inhibits the transcription of GmCCR. GmESR1 overexpression also enhanced sucrose transporter gene expression during seed development and increased the sucrose transport rate. These results offer new insight into the molecular mechanisms whereby GmESR1 increases protein levels within soybean seeds, guiding future molecular-assisted breeding efforts aimed at establishing high-protein soybean varieties.

Molecular and genetic basis of plant architecture in soybean

Plant architecture determines canopy coverage, photosynthetic efficiency, and ultimately productivity in soybean (Glycine max). Optimizing plant architecture is a major goal of breeders to develop high yield soybean varieties. Over the past few decades, the yield per unit area of soybean has not changed significantly; however, rice and wheat breeders have succeeded in achieving high yields by generating semi-dwarf varieties. Semi-dwarf crops have the potential to ensure yield stability in high-density planting environments because they can significantly improve responses to fertilizer input, lodging resistance, and enhance resistance to various abiotic and biotic stresses. Soybean has a unique plant architecture, with leaves, inflorescences, and pods growing at each node; internode number greatly affects the final yield. Therefore, producing high-yielding soybean plants with an ideal architecture requires the coordination of effective node formation, effective internode formation, and branching. Dozens of quantitative trait loci (QTLs) controlling plant architecture have been identified in soybean, but only a few genes that control this trait have been cloned and characterized. Here, we review recent progress in understanding the genetic basis of soybean plant architecture. We provide our views and perspectives on how to breed new high-yielding soybean varieties.

Epistasis and pleiotropy-induced variation for plant breeding

Epistasis refers to nonallelic interaction between genes that cause bias in estimates of genetic parameters for a phenotype with interactions of two or more genes affecting the same trait. Partitioning of epistatic effects allows true estimation of the genetic parameters affecting phenotypes. Multigenic variation plays a central role in the evolution of complex characteristics, among which pleiotropy, where a single gene affects several phenotypic characters, has a large influence. While pleiotropic interactions provide functional specificity, they increase the challenge of gene discovery and functional analysis. Overcoming pleiotropy-based phenotypic trade-offs offers potential for assisting breeding for complex traits. Modelling higher order nonallelic epistatic interaction, pleiotropy and non-pleiotropy-induced variation, and genotype × environment interaction in genomic selection may provide new paths to increase the productivity and stress tolerance for next generation of crop cultivars. Advances in statistical models, software and algorithm developments, and genomic research have facilitated dissecting the nature and extent of pleiotropy and epistasis. We overview emerging approaches to exploit positive (and avoid negative) epistatic and pleiotropic interactions in a plant breeding context, including developing avenues of artificial intelligence, novel exploitation of large-scale genomics and phenomics data, and involvement of genes with minor effects to analyse epistatic interactions and pleiotropic quantitative trait loci, including missing heritability.

High-quality genome of a modern soybean cultivar and resequencing of 547 accessions provide insights into the role of structural variation

Soybean provides protein, oil and multiple health-related compounds. Understanding the effects of structural variations (SVs) on economic traits in modern breeding is important for soybean improvement. Here we assembled the high-quality genome of modern cultivar Nongdadou2 (NDD2) and identified 25,814 SV-gene pairs compared to 29 reported genomes, with 13 NDD2-private SVs validated in 547 deep-resequencing (average = 18.05-fold) accessions, which advances our understanding of genomic variation biology. We found some insertions/deletions involved in seed protein and weight formation, an inversion related to adaptation to drought and a large intertranslocation implicated in a key divergence event in soybean. Of 749,714 SVs from 547 accessions, 6,013 were significantly associated with 22 yield-related and seed-quality-related traits determined in ten location × year environments. We uncovered 1,761 associated SVs that hit genes or regulatory regions, with 12 in GmMQT influencing oil and isoflavone contents. Our work provides resources and insights into SV roles in soybean improvement.

Identification of a Major QTL for Seed Protein Content in Cultivated Peanut (Arachis hypogaea L.) Using QTL-Seq

Peanut (Arachis hypogaea L.) is a great plant protein source for human diet since it has high protein content in the kernel. Therefore, seed protein content (SPC) is considered a major agronomic and quality trait in peanut breeding. However, few genetic loci underlying SPC have been identified in peanuts, and the underlying regulatory mechanisms remain unknown, limiting the effectiveness of breeding for high-SPC peanut varieties. In this study, a major QTL (qSPCB10.1) controlling peanut SPC was identified within a 2.3 Mb interval in chromosome B10 by QTL-seq using a recombinant inbred line population derived from parental lines with high and low SPCs, respectively. Sequence comparison, transcriptomic analysis, and annotation analysis of the qSPCB10.1 locus were performed. Six differentially expressed genes with sequence variations between two parents were identified as candidate genes underlying qSPCB10.1. Further locus interaction analysis revealed that qSPCB10.1 could not affect the seed oil accumulation unless qOCA08.1XH13 was present, a high seed oil content (SOC) allele for a major QTL underlying SOC. In summary, our study provides a basis for future investigation of the genetic basis of seed protein accumulation and facilitates marker-assisted selection for developing high-SPC peanut genotypes.

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.

GWAS and WGCNA Analysis Uncover Candidate Genes Associated with Oil Content in Soybean

Soybean vegetable oil is an important source of the human diet. However, the analysis of the genetic mechanism leading to changes in soybean oil content is still incomplete. In this study, a total of 227 soybean materials were applied and analyzed by a genome-wide association study (GWAS). There are 44 quantitative trait nucleotides (QTNs) that were identified as associated with oil content. A total of six, four, and 34 significant QTN loci were identified in Xiangyang, Hulan, and Acheng, respectively. Of those, 26 QTNs overlapped with or were near the known oil content quantitative trait locus (QTL), and 18 new QTNs related to oil content were identified. A total of 594 genes were located near the peak single nucleotide polymorphism (SNP) from three tested environments. These candidate genes exhibited significant enrichment in tropane, piperidine, and pyridine alkaloid biosynthesiss (ko00960), ABC transporters (ko02010), photosynthesis-antenna proteins (ko00196), and betalain biosynthesis (ko00965). Combined with the GWAS and weighted gene co-expression network analysis (WGCNA), four candidate genes (Glyma.18G300100, Glyma.11G221100, Glyma.13G343300, and Glyma.02G166100) that may regulate oil content were identified. In addition, Glyma.18G300100 was divided into two main haplotypes in the studied accessions. The oil content of haplotype 1 is significantly lower than that of haplotype 2. Our research findings provide a theoretical basis for improving the regulatory mechanism of soybean oil content.

Natural variation in Fatty Acid 9 is a determinant of fatty acid and protein content

Soybean is one of the most economically important crops worldwide and an important source of unsaturated fatty acids and protein for the human diet. Consumer demand for healthy fats and oils is increasing, and the global demand for vegetable oil is expected to double by 2050. Identification of key genes that regulate seed fatty acid content can facilitate molecular breeding of high-quality soybean varieties with enhanced fatty acid profiles. Here, we analysed the genetic architecture underlying variations in soybean seed fatty acid content using 547 accessions, including mainly landraces and cultivars from northeastern China. Through fatty acid profiling, genome re-sequencing, population genomics analyses, and GWAS, we identified a SEIPIN homologue at the FA9 locus as an important contributor to seed fatty acid content. Transgenic and multiomics analyses confirmed that FA9 was a key regulator of seed fatty acid content with pleiotropic effects on seed protein and seed size. We identified two major FA9 haplotypes in 1295 resequenced soybean accessions and assessed their phenotypic effects in a field planting of 424 accessions. Soybean accessions carrying FA9H2 had significantly higher total fatty acid contents and lower protein contents than those carrying FA9H1 . FA9H2 was absent in wild soybeans but present in 13% of landraces and 26% of cultivars, suggesting that it may have been selected during soybean post-domestication improvement. FA9 therefore represents a useful genetic resource for molecular breeding of high-quality soybean varieties with specific seed storage profiles.

Identification of the domestication gene GmCYP82C4 underlying the major quantitative trait locus for the seed weight in soybean

KEY MESSAGE

A major quantitative trait locus (QTL) for the hundred-seed weight (HSW) was identified and confirmed in the two distinct soybean populations, and the target gene GmCYP82C4 underlying this locus was identified that significantly associated with soybean seed weight, and it was selected during the soybean domestication and improvement process. Soybean is a major oil crop for human beings and the seed weight is a crucial goal of soybean breeding. However, only a limited number of target genes underlying the quantitative trait loci (QTLs) controlling seed weight in soybean are known so far. In the present study, six loci associated with hundred-seed weight (HSW) were detected in the first population of 573 soybean breeding lines by genome-wide association study (GWAS), and 64 gene models were predicted in these candidate QTL regions. The QTL qHSW_1 exhibits continuous association signals on chromosome four and was also validated by region association study (RAS) in the second soybean population (409 accessions) with wild, landrace, and cultivar soybean accessions. There were seven genes in qHSW_1 candidate region by linkage disequilibrium (LD) block analysis, and only Glyma.04G035500 (GmCYP82C4) showed specifically higher expression in flowers, pods, and seeds, indicating its crucial role in the soybean seed development. Significant differences in HSW trait were detected when the association panels are genotyped by single-nucleotide polymorphisms (SNPs) in putative GmCYP82C4 promoter region. Eight haplotypes were generated by six SNPs in GmCYP82C4 in the second soybean population, and two superior haplotypes (Hap2 and Hap4) of GmCYP82C4 were detected with average HSW of 18.27 g and 18.38 g, respectively. The genetic diversity of GmCYP82C4 was analyzed in the second soybean population, and GmCYP82C4 was most likely selected during the soybean domestication and improvement process, leading to the highest proportion of Hap2 of GmCYP82C4 both in landrace and cultivar subpopulations. The QTLs and GmCYP82C4 identified in this study provide novel genetic resources for soybean seed weight trait, and the GmCYP82C4 could be used for soybean molecular breeding to develop desirable seed weight in the future.

Genome-Wide Association Studies Prioritize Genes Controlling Seed Size and Reproductive Period Length in Soybean

Hundred-seed weight (HSW) and reproductive period length (RPL) are two major agronomic traits critical for soybean production and adaptation. However, both traits are quantitatively controlled by multiple genes that have yet to be comprehensively elucidated due to the lack of major genes; thereby, the genetic basis is largely unknown. In the present study, we conducted comprehensive genome-wide association analyses (GWAS) of HSW and RPL with multiple sets of accessions that were phenotyped across different environments. The large-scale analysis led to the identification of sixty-one and seventy-four significant QTLs for HSW and RPL, respectively. An ortholog-based search analysis prioritized the most promising candidate genes for the QTLs, including nine genes (TTG2, BZR1, BRI1, ANT, KLU, EOD1/BB, GPA1, ABA2, and ABI5) for HSW QTLs and nine genes (such as AGL8, AGL9, TOC1, and COL4) and six known soybean flowering time genes (E2, E3, E4, Tof11, Tof12, and FT2b) for RPL QTLs. We also demonstrated that some QTLs were targeted during domestication to drive the artificial selection of both traits towards human-favored traits. Local adaptation likely contributes to the increased genomic diversity of the QTLs underlying RPL. The results provide additional insight into the genetic basis of HSW and RPL and prioritize a valuable resource of candidate genes that merits further investigation to reveal the complex molecular mechanism and facilitate soybean improvement.

Future-Proofing Agriculture: De Novo Domestication for Sustainable and Resilient Crops

The worldwide agricultural system confronts a significant challenge represented by the increasing demand for food in the face of a growing global population. This challenge is exacerbated by a reduction in cultivable land and the adverse effects of climate change on crop yield quantity and quality. Breeders actively embrace cutting-edge omics technologies to pursue resilient genotypes in response to these pressing issues. In this global context, new breeding techniques (NBTs) are emerging as the future of agriculture, offering a solution to introduce resilient crops that can ensure food security, particularly against challenging climate events. Indeed, the search for domestication genes as well as the genetic modification of these loci in wild species using genome editing tools are crucial steps in carrying out de novo domestication of wild plants without compromising their genetic background. Current knowledge allows us to take different paths from those taken by early Neolithic farmers, where crop domestication has opposed natural selection. In this process traits and alleles negatively correlated with high resource environment performance are probably eradicated through artificial selection, while others may have been lost randomly due to domestication and genetic bottlenecks. Thus, domestication led to highly productive plants with little genetic diversity, owing to the loss of valuable alleles that had evolved to tolerate biotic and abiotic stresses. Recent technological advances have increased the feasibility of de novo domestication of wild plants as a promising approach for crafting optimal crops while ensuring food security and using a more sustainable, low-input agriculture. Here, we explore what crucial domestication genes are, coupled with the advancement of technologies enabling the precise manipulation of target sequences, pointing out de novo domestication as a promising application for future crop development.

Identification and characterization of a temperature sensitive chlorotic soybean mutant

Screening a transposon-mutagenized soybean population led to the discovery of a recessively inherited chlorotic phenotype. This "vir1" phenotype results in smaller stature, weaker stems, and a smaller root system with smaller nodules. Genome sequencing identified 15 candidate genes with mutations likely to result in a loss of function. Amplicon sequencing of a segregating population was then used to narrow the list to a single candidate mutation, a single-base change in Glyma.07G102300 that disrupts splicing of the second intron. Single cell transcriptomic profiling indicates that this gene is expressed primarily in mesophyll cells and RNA sequencing data indicates it is upregulated in germinating seedlings by cold stress. Previous studies have shown that mutations to Os05g34040, the rice homolog of Glyma.07G102300, produced a chlorotic phenotype that was more pronounced in cool temperatures. Growing soybean vir1 mutants at lower temperatures also resulted in a more severe phenotype. In addition, transgenic expression of wild type Glyma.07G102300 in the knockout mutant of the Arabidopsis homolog At4930720 rescues the chlorotic phenotype, further supporting the hypothesis that the mutation in Glyma.07G102300 is causal of the vir1 phenotype.

SoyMD: a platform combining multi-omics data with various tools for soybean research and breeding

Advanced multi-omics technologies offer much information that can uncover the regulatory mechanisms from genotype to phenotype. In soybean, numerous multi-omics databases have been published. Although they cover multiple omics, there are still limitations when it comes to the types and scales of omics datasets and analysis methods utilized. This study aims to address these limitations by collecting and integrating a comprehensive set of multi-omics datasets. This includes 38 genomes, transcriptomes from 435 tissue samples, 125 phenotypes from 6686 accessions, epigenome data involving histone modification, transcription factor binding, chromosomal accessibility and chromosomal interaction, as well as genetic variation data from 24 501 soybean accessions. Then, common analysis pipelines and statistical methods were applied to mine information from these multi-omics datasets, resulting in the successful establishment of a user-friendly multi-omics database called SoyMD (https://yanglab.hzau.edu.cn/SoyMD/#/). SoyMD provides researchers with efficient query options and analysis tools, allowing them to swiftly access relevant omics information and conduct comprehensive multi-omics data analyses. Another notable feature of SoyMD is its capability to facilitate the analysis of candidate genes, as demonstrated in the case study on seed oil content. This highlights the immense potential of SoyMD in soybean genetic breeding and functional genomics research.

Introgression of a Danbaekkong high-protein allele across different genetic backgrounds in soybean

Soybean meal is a major component of livestock feed due to its high content and quality of protein. Understanding the genetic control of protein is essential to develop new cultivars with improved meal protein. Previously, a genomic region on chromosome 20 significantly associated with elevated protein content was identified in the cultivar Danbaekkong. The present research aimed to introgress the Danbaekkong high-protein allele into elite lines with different genetic backgrounds by developing and deploying robust DNA markers. A multiparent population consisting of 10 F5-derived populations with a total of 1,115 recombinant inbred lines (RILs) was developed using "Benning HP" as the donor parent of the Danbaekkong high-protein allele. A new functional marker targeting the 321-bp insertion in the gene Glyma.20g085100 was developed and used to track the Danbaekkong high-protein allele across the different populations and enable assessment of its effect and stability. Across all populations, the high-protein allele consistently increased the content, with an increase of 3.3% in seed protein. A total of 103 RILs were selected from the multiparent population for yield testing in five environments to assess the impact of the high-protein allele on yield and to enable the selection of new breeding lines with high protein and high yield. The results indicated that the high-protein allele impacts yield negatively in general; however, it is possible to select high-yielding lines with high protein content. An analysis of inheritance of the Chr 20 high-protein allele in Danbaekkong indicated that it originated from a Glycine soja line (PI 163453) and is the same as other G. soja lines studied. A survey of the distribution of the allele across 79 G. soja accessions and 35 Glycine max ancestors of North American soybean cultivars showed that the high-protein allele is present in all G. soja lines evaluated but not in any of the 35 North American soybean ancestors. These results demonstrate that G. soja accessions are a valuable source of favorable alleles for improvement of protein composition.

Regulation of seed traits in soybean

Soybean (Glycine max) is an essential economic crop that provides vegetative oil and protein for humans, worldwide. Increasing soybean yield as well as improving seed quality is of great importance. Seed weight/size, oil and protein content are the three major traits determining seed quality, and seed weight also influences soybean yield. In recent years, the availability of soybean omics data and the development of related techniques have paved the way for better research on soybean functional genomics, providing a comprehensive understanding of gene functions. This review summarizes the regulatory genes that influence seed size/weight, oil content and protein content in soybean. We also provided a general overview of the pleiotropic effect for the genes in controlling seed traits and environmental stresses. Ultimately, it is expected that this review will be beneficial in breeding improved traits in soybean.

Genomic analysis and characterization of new loci associated with seed protein and oil content in soybeans

Breeding for increased protein without a reduction in oil content in soybeans [Glycine max (L.) Merr.] is a challenge for soybean breeders but an expected goal. Many efforts have been made to develop new soybean varieties with high yield in combination with desirable protein and/or oil traits. An elite line, R05-1415, was reported to be high yielding, high protein, and low oil. Several significant quantitative trait loci (QTL) for protein and oil were reported in this line, but many of them were unstable across environments or genetic backgrounds. Thus, a new study under multiple field environments using the Infinium BARCSoySNP6K BeadChips was conducted to detect and confirm stable genomic loci for these traits. Genetic analyses consistently detected a single major genomic locus conveying these two traits with remarkably high phenotypic variation explained (R2 ), varying between 24.2% and 43.5%. This new genomic locus is located between 25.0 and 26.7 Mb, distant from the previously reported QTL and did not overlap with other commonly reported QTL and the recently cloned gene Glyma.20G085100. Homolog analysis indicated that this QTL did not result from the paracentric chromosome inversion with an adjacent genomic fragment that harbors the reported QTL. The pleiotropic effect of this QTL could be a challenge for improving protein and oil simultaneously; however, a further study of four candidate genes with significant expressions in the seed developmental stages coupled with haplotype analysis may be able to pinpoint causative genes. The functionality and roles of these genes can be determined and characterized, which lay a solid foundation for the improvement of protein and oil content in soybeans.

Global analysis of seed transcriptomes reveals a novel PLATZ regulator for seed size and weight control in soybean

Seed size and weight are important factors that influence soybean yield. Combining the weighted gene co-expression network analysis (WGCNA) of 45 soybean accessions and gene dynamic changes in seeds at seven developmental stages, we identified candidate genes that may control the seed size/weight. Among these, a PLATZ-type regulator overlapping with 10 seed weight QTLs was further investigated. This zinc-finger transcriptional regulator, named as GmPLATZ, is required for the promotion of seed size and weight in soybean. The GmPLATZ may exert its functions through direct binding to the promoters and activation of the expression of cyclin genes and GmGA20OX for cell proliferation. Overexpression of the GmGA20OX enhanced seed size/weight in soybean. We further found that the GmPLATZ binds to a 32-bp sequence containing a core palindromic element AATGCGCATT. Spacing of the flanking sequences beyond the core element facilitated GmPLATZ binding. An elite haplotype Hap3 was also identified to have higher promoter activity and correlated with higher gene expression and higher seed weight. Orthologues of the GmPLATZ from rice and Arabidopsis play similar roles in seeds. Our study reveals a novel module of GmPLATZ-GmGA20OX/cyclins in regulating seed size and weight and provides valuable targets for breeding of crops with desirable agronomic traits.

Genome-wide association study and RNA-seq identifies GmWRI1-like transcription factor related to the seed weight in soybean

The cultivated soybean (Glycine max (L.) Merrill) is domesticated from wild soybean (Glycine soja) and has heavier seeds with a higher oil content than the wild soybean. In this study, we identified a novel candidate gene associated with SW using a genome-wide association study (GWAS). The candidate gene GmWRI14-like was detected by GWAS analysis in three consecutive years. By constructing transgenic soybeans overexpressing the GmWRI14-like gene and gmwri14-like soybean mutants, we found that overexpression of GmWRI14-like increased the SW and increased total fatty acid content. We then used RNA-seq and qRT-PCR to identify the target genes directly or indirectly regulated by GmWRI14-like. Transgenic soyabeans overexpressing GmWRI14-like showed increased accumulation of GmCYP78A50 and GmCYP78A69 than non-transgenic soybean lines. Interestingly, we also found that GmWRI14-like proteins could interact with GmCYP78A69/GmCYP78A50 using yeast two-hybrid and bimolecular fluorescence complementation. Our results not only shed light on the genetic architecture of cultivated soybean SW, but also lays a theoretical foundation for improving the SW and oil content of soybeans.

Molecular, genetic, and genomic basis of seed size and yield characteristics in soybean

Soybean (Glycine max L. Merr.) is a crucial oilseed cash crop grown worldwide and consumed as oil, protein, and food by humans and feed by animals. Comparatively, soybean seed yield is lower than cereal crops, such as maize, rice, and wheat, and the demand for soybean production does not keep up with the increasing consumption level. Therefore, increasing soybean yield per unit area is the most crucial breeding objective and is challenging for the scientific community. Moreover, yield and associated traits are extensively researched in cereal crops, but little is known about soybeans' genetics, genomics, and molecular regulation of yield traits. Soybean seed yield is a complex quantitative trait governed by multiple genes. Understanding the genetic and molecular processes governing closely related attributes to seed yield is crucial to increasing soybean yield. Advances in sequencing technologies have made it possible to conduct functional genomic research to understand yield traits' genetic and molecular underpinnings. Here, we provide an overview of recent progress in the genetic regulation of seed size in soybean, molecular, genetics, and genomic bases of yield, and related key seed yield traits. In addition, phytohormones, such as auxin, gibberellins, cytokinins, and abscisic acid, regulate seed size and yield. Hence, we also highlight the implications of these factors, challenges in soybean yield, and seed trait improvement. The information reviewed in this study will help expand the knowledge base and may provide the way forward for developing high-yielding soybean cultivars for future food demands.

A loss-of-function mutant allele of a glycosyl hydrolase gene has been co-opted for seed weight control during soybean domestication

The resultant DNA from loss-of-function mutation can be recruited in biological evolution and development. Here, we present such a rare and potential case of "to gain by loss" as a neomorphic mutation during soybean domestication for increasing seed weight. Using a population derived from a chromosome segment substitution line of Glycine max (SN14) and Glycine soja (ZYD06), a quantitative trait locus (QTL) of 100-seed weight (qHSW) was mapped on chromosome 11, corresponding to a truncated β-1, 3-glucosidase (βGlu) gene. The novel gene hsw results from a 14-bp deletion, causing a frameshift mutation and a premature stop codon in the βGlu. In contrast to HSW, the hsw completely lost βGlu activity and function but acquired a novel function to promote cell expansion, thus increasing seed weight. Overexpressing hsw instead of HSW produced large soybean seeds, and surprisingly, truncating hsw via gene editing further increased the seed size. We further found that the core 21-aa peptide of hsw and its variants acted as a promoter of seed size. Transcriptomic variation in these transgenic soybean lines substantiated the integration hsw into cell and seed size control. Moreover, the hsw allele underwent selection and expansion during soybean domestication and improvement. Our work cloned a likely domesticated QTL controlling soybean seed weight, revealed a novel genetic variation and mechanism in soybean domestication, and provided new insight into crop domestication and breeding, and plant evolution.

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.

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.

GmJAZ3 interacts with GmRR18a and GmMYC2a to regulate seed traits in soybean

Seed weight is usually associated with seed size and is one of the important agronomic traits that determine yield. Understanding of seed weight control is limited, especially in soybean plants. Here we show that Glycine max JASMONATE-ZIM DOMAIN 3 (GmJAZ3), a gene identified through gene co-expression network analysis, regulates seed-related traits in soybean. Overexpression of GmJAZ3 promotes seed size/weight and other organ sizes in stable transgenic soybean plants likely by increasing cell proliferation. GmJAZ3 interacted with both G. max RESPONSE REGULATOR 18a (GmRR18a) and GmMYC2a to inhibit their transcriptional activation of cytokinin oxidase gene G. max CYTOKININ OXIDASE 3-4 (GmCKX3-4), which usually affects seed traits. Meanwhile, the GmRR18a binds to the promoter of GmMYC2a and activates GmMYC2a gene expression. In GmJAZ3-overexpressing soybean seeds, the protein contents were increased while the fatty acid contents were reduced compared to those in the control seeds, indicating that the GmJAZ3 affects seed size/weight and compositions. Natural variation in JAZ3 promoter region was further analyzed and Hap3 promoter correlates with higher promoter activity, higher gene expression and higher seed weight. The Hap3 promoter may be selected and fixed during soybean domestication. JAZ3 orthologs from other plants/crops may also control seed size and weight. Taken together, our study reveals a novel molecular module GmJAZ3-GmRR18a/GmMYC2a-GmCKXs for seed size and weight control, providing promising targets during soybean molecular breeding for better seed traits.

Identification of quantitative trait loci controlling soybean seed protein and oil content

Soybean is a major source of seed protein and oil globally with an average composition of 40% protein and 20% oil in the seed. The goal of this study was to identify quantitative trait loci (QTL) conferring seed protein and oil content utilizing a population constructed by crossing an above average protein content line, PI 399084 to another line that had a low protein content value, PI 507429, both from the USDA soybean germplasm collection. The recombinant inbred line (RIL) population, PI 507429 x PI 399084, was evaluated in two replications over four years (2018-2021); the seeds were analyzed for seed protein and oil content using near-infrared reflectance spectroscopy. The recombinant inbred lines and the two parents were re-sequenced using genotyping by sequencing. A total of 12,761 molecular markers, which came from genotyping by sequencing, the SoySNP6k BeadChip and selected simple sequence repeat (SSR) markers from known protein QTL chromosomal regions were used for mapping. One QTL was identified on chromosome 2 explaining up to 56.8% of the variation for seed protein content and up to 43% for seed oil content. Another QTL identified on chromosome 15 explained up to 27.2% of the variation for seed protein and up to 41% of the variation for seed oil content. The protein and oil QTLs of this study and their associated molecular markers will be useful in breeding to improve nutritional quality in soybean.

Identification of an important QTL for seed oil content in soybean

Seed oil content is one of the most important quantitative traits in soybean (Glycine max) breeding. Here, we constructed a high-density single nucleotide polymorphism linkage map using two genetically similar parents, Heinong 84 and Kenfeng 17, that differ dramatically in their seed oil contents, and performed quantitative trait loci (QTL) mapping of seed oil content in a recombinant inbred line (RIL) population derived from their cross. We detected five QTL related to seed oil content distributed on five chromosomes. The QTL for seed oil content explained over 10% of the phenotypic variation over two years. This QTL was mapped to an interval containing 20 candidate genes, including a previously reported gene, soybean RING Finger 1a (RNF1a) encoding an E3 ubiquitin ligase. Notably, two short sequences were inserted in the GmRNF1a coding region of KF 17 compared to that of HN 84, resulting in a longer protein variant in KF 17. Our results thus provide information for uncovering the genetic mechanisms determining seed oil content in soybean, as well as identifying an additional QTL and highlighting GmRNF1a as candidate gene for modulating seed oil content in soybean.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01384-2.

Major genetic locus with pleiotropism determined seed-related traits in cultivated and wild soybeans

KEY MESSAGE

Here, a novel pleiotropic QTL qSS14 simultaneously regulating four seed size traits and two consistently detected QTLs qSW17 and qSLW02 were identified across multiple years. Seed-related traits were the key agronomic traits that have been artificially selected during the domestication of wild soybean. Identifying the genetic loci and genes that regulate seed size could clarify the genetic variations in seed-related traits and provide novel insights into high-yield soybean breeding. In this study, we used a high-density genetic map constructed by F₁₀ RIL populations from a cross between Glycine max and Glycine soja to detect additive QTLs for seven seed-related traits over the last three years. As a result, we identified one novel pleiotropic QTL, qSS14, that simultaneously controlled four seed size traits (100-seed weight, seed length, seed width, and seed thickness) and two consistently detected QTLs, qSW17, and qSLW02, in multiple years of phenotypic data. Furthermore, we predicted two, two and three candidate genes within these three critical loci based on the parental resequencing data and gene function annotations. And the relative expression of four candidate genes GLYMA_14G155100, GLYMA_17G061000, GLYMA_02G273100, and GLYMA_02G273300 showed significant differences among parents and the extreme materials through qRT-PCR analysis. These findings could facilitate the determination of beneficial genes in wild soybean and contribute to our understanding of the soybean domestication process.

The elite variations in germplasms for soybean breeding

The genetic base of soybean cultivars (Glycine max (L.) Merr.) has been narrowed through selective domestication and specific breeding improvement, similar to other crops. This presents challenges in breeding new cultivars with improved yield and quality, reduced adaptability to climate change, and increased susceptibility to diseases. On the other hand, the vast collection of soybean germplasms offers a potential source of genetic variations to address those challenges, but it has yet to be fully leveraged. In recent decades, rapidly improved high-throughput genotyping technologies have accelerated the harness of elite variations in soybean germplasm and provided the important information for solving the problem of a narrowed genetic base in breeding. In this review, we will overview the situation of maintenance and utilization of soybean germplasms, various solutions provided for different needs in terms of the number of molecular markers, and the omics-based high-throughput strategies that have been used or can be used to identify elite alleles. We will also provide an overall genetic information generated from soybean germplasms in yield, quality traits, and pest resistance for molecular breeding.

Metabolomic Analysis Reveals Domestication-Driven Reshaping of Polyphenolic Antioxidants in Soybean Seeds

Crop domestication has resulted in nutrient losses, so evaluating the reshaping of phytonutrients is crucial for improving nutrition. Soybean is an ideal model due to its abundant phytonutrients and wild relatives. In order to unravel the domestication consequence of phytonutrients, comparative and association analyses of metabolomes and antioxidant activities were performed on seeds of six wild (Glycine soja (Sieb. and Zucc.)) and six cultivated soybeans (Glycine max (L.) Merr.). Through ultra-high performance liquid chromatography-tandem mass spectrometry (UHPLC-MS/MS), we observed a greater metabolic diversity in wild soybeans, which also displayed higher antioxidant activities. (-)-Epicatechin, a potent antioxidant, displayed a 1750-fold greater abundance in wild soybeans than in cultivated soybeans. Multiple polyphenols in the catechin biosynthesis pathway were significantly higher in wild soybeans, including phlorizin, taxifolin, quercetin 3-O-galactoside, cyanidin 3-O-glucoside, (+)-catechin, (-)-epiafzelechin, catechin-glucoside, and three proanthocyanidins. They showed significant positive correlations with each other and antioxidant activities, indicating their cooperative contribution to the high antioxidant activities of wild soybeans. Additionally, natural acylation related to functional properties was characterized in a diverse range of polyphenols. Our study reveals the comprehensive reprogramming of polyphenolic antioxidants during domestication, providing valuable insights for metabolism-assisted fortification of crop nutrition.

Genetic mapping and functional genomics of soybean seed protein

Soybean is an utterly important crop for high-quality meal protein and vegetative oil. Soybean seed protein content has become a key factor in nutrients for livestock feed as well as human dietary consumption. Genetic improvement of soybean seed protein is highly desired to meet the demands of rapidly growing world population. Molecular mapping and genomic analysis in soybean have identified many quantitative trait loci (QTL) underlying seed protein content control. Exploring the mechanisms of seed storage protein regulation will be helpful to achieve the improvement of protein content. However, the practice of breeding higher protein soybean is challenging because soybean seed protein is negatively correlated with seed oil content and yield. To overcome the limitation of such inverse relationship, deeper insights into the property and genetic control of seed protein are required. Recent advances of soybean genomics have strongly enhanced the understandings for molecular mechanisms of soybean with better seed quality. Here, we review the research progress in the genetic characteristics of soybean storage protein, and up-to-date advances of molecular mappings and genomics of soybean protein. The key factors underlying the mechanisms of the negative correlation between protein and oil in soybean seeds are elaborated. We also briefly discuss the future prospects of breaking the bottleneck of the negative correlation to develop high protein soybean without penalty of oil and yield.

Supplementary Information

The online version contains supplementary material available at 10.1007/s11032-023-01373-5.