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Identification of potential genes/alleles governing complex seed-protein content (SPC) is essential in marker-assisted breeding for quality trait improvement of chickpea. Henceforth, the present study utilized an integrated genomics-assisted breeding strategy encompassing trait association analysis, selective genotyping in traditional bi-parental mapping population and differential expression profiling for the first-time to understand the complex genetic architecture of quantitative SPC trait in chickpea. For GWAS (genome-wide association study), high-throughput genotyping information of 16376 genome-based SNPs (single nucleotide polymorphism) discovered from a structured population of 336 sequenced desi and kabuli accessions [with 150–200 kb LD (linkage disequilibrium) decay] was utilized. This led to identification of seven most effective genomic loci (genes) associated [10–20% with 41% combined PVE (phenotypic variation explained)] with SPC trait in chickpea. Regardless of the diverse desi and kabuli genetic backgrounds, a comparable level of association potential of the identified seven genomic loci with SPC trait was observed. Five SPC-associated genes were validated successfully in parental accessions and homozygous individuals of an intra-specific desi RIL (recombinant inbred line) mapping population (ICC 12299 × ICC 4958) by selective genotyping. The seed-specific expression, including differential up-regulation (>four fold) of six SPC-associated genes particularly in accessions, parents and homozygous individuals of the aforementioned mapping population with a high level of contrasting SPC (21–22%) was evident. Collectively, the integrated genomic approach delineated diverse naturally occurring novel functional SNP allelic variants in six potential candidate genes regulating SPC trait in chickpea. Of these, a non-synonymous SNP allele-carrying zinc finger transcription factor gene exhibiting strong association with SPC trait was found to be the most promising in chickpea. The informative functionally relevant molecular tags scaled-down essentially have potential to accelerate marker-assisted genetic improvement by developing nutritionally rich chickpea cultivars with enhanced SPC.

Drought is one of the most destructive abiotic stresses that impact the growth, physiology, yield, and nutritional quality of seeds of crop plants. In modern agriculture, the use of nanoparticles can be beneficial due to their large surface area and higher potentiality to enter into the plant leaf during foliar application. This study aims to evaluate the effects of foliar spray containing varying doses (0, 100, and 200 ppm) of the nano-iron (Fe 3 O 4 ) on the growth, physiology, yield, and seed nutritional quality of soybean under drought (40% of field capacity, FC) and well-watered (80% of FC) conditions. Leaf water status, chlorophyll content of leaves, the height of the plant, fresh leaf weight, fresh stem weight, fresh petiole weight, total dry weight, seed yield, and protein and oil content in soybean seeds were found to be suppressed by the applied drought stress. Under both drought (40% of FC) and controlled well-watered (80% of FC) conditions, the foliar application of nano-iron substantially improved the growth, physiology, yield, and quality of soybean seeds. The nanoparticles at 200 ppm increased soybean seed yield by 40.12 and 32.60% in drought and well-watered conditions, respectively, compared to the untreated plants. Furthermore, nano-iron increased the oil content of soybean seeds by 10.14 and 7.87% under drought and well-watered conditions, respectively, compared to the untreated control. Our results indicate that the application of nano-iron improved drought tolerance, yield, and seed quality of soybean, so exogenous foliar sprays of 200 ppm Fe 3 O 4 were more effective than the other treatments in enhancing drought tolerance and can be utilized to reduce losses caused by drought stress in soybean-growing areas.

Summary 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.

Summary 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.

Cultivated peanut (Arachis hypogaea L.) is an important oilseed and cash crop, and seed sucrose content (SSC), seed oil content (SOC) and seed protein content (SPC) are key determinants of seed flavour, texture, and overall quality. Identifying quantitative trait loci (QTLs) and candidate genes associated with SSC, SOC and SPC is therefore of considerable importance for peanut genetics and breeding. In this study, two recombinant inbred line (RIL) populations derived from reciprocal crosses between the lines Jihuatian1 (JHT1) and PI478819 (PI) were used to detect major QTLs for SSC, SOC and SPC through bulked segregant analysis combined with whole‐genome sequencing (BSA‐seq). Multiple lines of evidence supported the homologous gene pair AhSUCA06 and AhSUCA16 as candidate genes underlying the epistatic QTLs qA06.1 and qA16.1, which exhibited major and stable effects across multiple phenotypic evaluations. Furthermore, the function of AhSUCA06 was validated through CRISPR/Cas9‐mediated genetic transformation. Subcellular localization assays using GFP fusion proteins, together with dual‐luciferase reporter assays, demonstrated that AhSUCA06 and AhSUCA16—both containing a DUF7950 domain of previously unknown function—localize to the nucleus and act as transcriptional repressors. In addition, DAP‐seq analysis suggested that these genes may regulate pathways related to glycolysis and gluconeogenesis. Overall, this study provides new insights into the molecular mechanisms underlying the regulation of SSC, SOC and SPC in peanut and offers valuable information to support the genetic improvement of seed quality traits in peanut breeding programs.

Upland cotton ( Gossypium hirsutum ) is the world’s leading fiber crop and one of the most important oilseed crops. Genetic improvement of cotton has primarily focused on fiber yield and quality. However, there is an increased interest and demand for enhanced cottonseed traits, including protein, oil, fatty acids, and amino acids for broad food, feed and biofuel applications. As a byproduct of cotton production, cottonseed is an important source of edible oil in many countries and could also be a vital source of protein for human consumption. The focus of cotton breeding on high yield and better fiber quality has substantially reduced the natural genetic variation available for effective cottonseed quality improvement within Upland cotton. However, genetic variation in cottonseed oil and protein content exists within the genus of Gossypium and cultivated cotton. A plethora of genes and quantitative trait loci (QTLs) (associated with cottonseed oil, fatty acids, protein and amino acids) have been identified, providing important information for genetic improvement of cottonseed quality. Genetic engineering in cotton through RNA interference and insertions of additional genes of other genetic sources, in addition to the more recent development of genome editing technology has achieved considerable progress in altering the relative levels of protein, oil, fatty acid profile, and amino acids composition in cottonseed for enhanced nutritional value and expanded industrial applications. The objective of this review is to summarize and discuss the cottonseed oil biosynthetic pathway and major genes involved, genetic basis of cottonseed oil and protein content, genetic engineering, genome editing through CRISPR/Cas9, and QTLs associated with quantity and quality enhancement of cottonseed oil and protein.

Summary The husk leaf of maize (Zea mays) encases the ear as a modified leaf and plays pivotal roles in protecting the ear from pathogen infection, translocating nutrition for grains and warranting grain yield. However, the natural genetic basis for variation in husk leaf width remains largely unexplored. Here, we performed a genome‐wide association study for maize husk leaf width and identified a 3‐bp InDel (insertion/deletion) in the coding region of the nitrate transporter gene ZmNRT2.5. This polymorphism altered the interaction strength of ZmNRT2.5 with another transporter, ZmNPF5, thereby contributing to variation in husk leaf width. We also isolated loss‐of‐function mutants in ZmNRT2.5, which exhibited a substantial decrease in husk leaf width relative to their controls. We demonstrate that ZmNRT2.5 facilitates the transport of nitrate from husk leaves to maize kernels in plants grown under low‐nitrogen conditions, contributing to the accumulation of proteins in maize seeds. Together, our findings uncovered a key gene controlling maize husk leaf width and nitrate transport from husk leaves to kernels. Identification of the ZmNRT2.5 loci offers direct targets for improving the protein content of maize seeds via molecular‐assisted maize breeding.

Background Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein content (SPC) is a valuable quality trait controlled by multiple genes in soybean. Results In this study, we performed quantitative trait loci (QTL) mapping, QTL-seq, and RNA sequencing (RNA-seq) to reveal the genes controlling protein content in the soybean by using the high protein content variety Nanxiadou 25. A total of 50 QTL for SPC distributed on 14 chromosomes except chromosomes 4, 12, 14, 17, 18, and 19 were identified by QTL mapping using 178 recombinant inbred lines (RILs). Among these QTL, the major QTL q SPC _20–1 and q SPC _20–2 on chromosome 20 were repeatedly detected across six tested environments, corresponding to the location of the major QTL detected using whole-genome sequencing-based QTL-seq. 329 candidate DEGs were obtained within the QTL region of q SPC _20–1 and q SPC _20–2 via gene expression profile analysis. Nine of which were associated with SPC, potentially representing candidate genes. Clone sequencing results showed that different single nucleotide polymorphisms (SNPs) and indels between high and low protein genotypes in Glyma.20G088000 and Glyma.16G066600 may be the cause of changes in this trait. Conclusions These results provide the basis for research on candidate genes and marker-assisted selection (MAS) in soybean breeding for seed protein content.

Soybean ( Glycine max [L.] Merr.) serves as a critical global source of plant-based protein and oil, yet the inverse relationship between seed protein content (PC) and oil content (OC) remains a major barrier to simultaneous improvement. Recent advances in genomics, transcriptomics, and proteomics have elucidated key regulatory genes and networks underlying these traits, including Gm WRI1a , LEC2 , Glyma.20G085100 , and the LAFL transcriptional module. These findings reveal that carbon and nitrogen resource partitioning during seed maturation is tightly coordinated by pleiotropic regulators, many of which mediate metabolic trade-offs that limit dual optimization. Although certain wild soybean loci and “bridge genes” like Gm SWEET39 show potential to partially uncouple PC–OC antagonism, their effects are often context-dependent and modest in scale. This review synthesizes current understanding of the genetic architecture and metabolic frameworks that shape oil and protein accumulation in soybean seeds. It highlights promising molecular breeding strategies—including phase-specific gene regulation, CRISPR-mediated multiplex editing, and the stacking of favorable alleles—to overcome long-standing trade-offs. By leveraging multi-omics integration and functional VAL idation in diverse germplasm, future soybean breeding programs can more effectively develop high-protein, high-oil cultivars tailored to both nutritional and industrial demands.

Soybean is a globally important legume crop that provides a primary source of high-quality vegetable protein and oil. Seed protein and oil content are two valuable quality traits controlled by multiple genes in soybean. In this study, the restricted two-stage multi-locus genome-wide association analysis (RTM-GWAS) procedure was performed to dissect the genetic architecture of seed protein and oil content in a diverse panel of 279 soybean accessions from the Yangtze and Huaihe River Valleys in China. We identified 26 quantitative trait loci (QTLs) for seed protein content and 23 for seed oil content, including five associated with both traits. Among these, 39 QTLs corresponded to previously reported QTLs, whereas 10 loci were novel. As reported previously, the QTL on chromosome 20 was associated with both seed protein and oil content. This QTL exhibited opposing effects on these traits and contributed the most to phenotype variation. From the detected QTLs, 55 and 51 candidate genes were identified for seed protein and oil content, respectively. Among these genes, eight may be promising candidate genes for improving soybean nutritional quality. These results will facilitate marker-assisted selective breeding for soybean protein and oil content traits.