Increasing seed oil content is one of the most important breeding goals for soybean due to a high global demand for edible vegetable oil. However, genetic improvement of seed oil content has been difficult in soybean because of the complexity of oil metabolism. Determining the major variants and molecular mechanisms conferring oil accumulation is critical for substantial oil enhancement in soybean and other oilseed crops. In this study, we evaluated the seed oil contents of 219 diverse soybean accessions across six different environments and dissected the underlying mechanism using a high-resolution genome-wide association study (GWAS). An environmentally stable quantitative trait locus (QTL), GqOil20, significantly associated with oil content was identified, accounting for 23.70% of the total phenotypic variance of seed oil across multiple environments. Haplotype and expression analyses indicate that an oleosin protein-encoding gene (GmOLEO1), colocated with a leading single nucleotide polymorphism (SNP) from the GWAS, was significantly correlated with seed oil content. GmOLEO1 is predominantly expressed during seed maturation, and GmOLEO1 is localized to accumulated oil bodies (OBs) in maturing seeds. Overexpression of GmOLEO1 significantly enriched smaller OBs and increased seed oil content by 10.6% compared with those of control seeds. A time-course transcriptomics analysis between transgenic and control soybeans indicated that GmOLEO1 positively enhanced oil accumulation by affecting triacylglycerol metabolism. Our results also showed that strong artificial selection had occurred in the promoter region of GmOLEO1, which resulted in its high expression in cultivated soybean relative to wild soybean, leading to increased seed oil accumulation. The GmOLEO1 locus may serve as a direct target for both genetic engineering and selection for soybean oil improvement. Soybean seed oil is an important quality trait targeted during domestication and breeding. However, the molecular mechanism of soybean oil regulation is largely unknown due to its complex genetic architecture and environmental sensitivity. In this paper, we integrated GWAS across multiple environments, haplotype analysis, genetic transformation, and diversity analysis to study the genetic architecture of oil content and the underlying mechanism in soybean. This combined analysis enabled us to identify an environmentally stable QTL (GqOil20) and functionally verified that GmOLEO1 positively regulates total seed oil accumulation in soybean seeds. In addition, we found that GmOLEO1 showed a higher level of expression in cultivated soybean seeds than in wild soybean seeds, possibly as the result of the positive selection of the promoter, resulting in seed oil accumulation. Moreover, we identified an elite GmOLEO1 haplotype that correlated strongly with high oil content in soybean, holding great potential for assisting oil improvement in soybean breeding. Our study provided a new genetic resource for oil content improvement in soybean and other oilseed crops.

Previous studies have revealed a significant genetic relationship between phosphorus (P)-efficiency and photosynthesis-related traits in soybean. In this study, we used proteome profiling in combination with expression analysis, biochemical investigations, and leaf ultrastructural analysis to identify the underlying physiological and molecular responses. The expression analysis and ultrastructural analysis showed that the photosynthesis key genes were decreased at transcript levels and the leaf mesophyll and chloroplast were severely damaged after low-P stress. Approximately 55 protein spots showed changes under low-P condition by mass spectrometry, of which 17 were involved in various photosynthetic processes. Further analysis revealed the depression of photosynthesis caused by low-P stress mainly involves the regulation of leaf structure, adenosine triphosphate (ATP) synthesis, absorption and transportation of CO₂, photosynthetic electron transport, production of assimilatory power, and levels of enzymes related to the Calvin cycle. In summary, our findings indicated that the existence of a stringent relationship between P supply and the genomic control of photosynthesis in soybean. As an important strategy to protect soybean photosynthesis, P could maintain the stability of cell structure, up-regulate the enzymes’ activities, recover the process of photosystem II (PSII), and induce the expression of low-P responsive genes and proteins.

Photosynthesis is the basis of plant growth and development, and is seriously affected by low phosphorus (P) stress. However, few studies have reported for the genetic foundation of photosynthetic response to low P stress in soybean. To address this issue, 219 soybean accessions were genotyped by 292,035 high-quality single nucleotide polymorphisms (SNPs) and phenotyped under normal and low P conditions in 2015 and 2016. These datasets were used to identify quantitative trait nucleotides (QTNs) for photosynthesis-related traits using mrMLM, ISIS EM-BLASSO, pLARmEB, FASTmrMLM, FASTmrEMMA, and pKWmEB methods. As a result, 159 QTNs within 31 genomic regions were found to be associated with four photosynthesis-related traits under different P stress conditions. Among the 31 associated regions, five (q7-2, q8-1, q9, q13-1, and q20-2) were detected commonly under both normal and low P conditions, indicating the insensitivity of these candidate genes to low P stress; five were detected only under normal P condition, indicating the sensitivity of these candidate genes to low P stress; six were detected only under low P condition, indicating the tolerantness of these candidate genes to low P stress; 20 were reported in previous studies. Around the 159 QTNs, 52 candidate genes were mined. These results provide the important information for marker-assisted breeding in soybean and further reveal the basis for the application of P tolerance to photosynthetic capacity.

Plant productivity relies on photosynthesis, and the photosynthetic process relies on phosphorus (P). The genetic basis of photosynthesis and P efficiency (PE) affecting yield has been separately characterized in various crop plants. However, the genetic relationship between PE and photosynthesis remains to be elucidated. In this study, we used a combined analysis of phenotypic correlation, linkage mapping and expression analysis to dissect the relationship between PE and photosynthesis. We found significant phenotypic correlations between PE and photosynthetic related traits, particularly under low P stress. A total of 172 QTLs for both traits were detected and classified into 29 genomic regions. 12 (41.4 %) of 29 regions were detected to be associated with both PE and photosynthetic related traits. Three major QTLs, q14-2, q15-2, and q19-2, were found to be associated with both traits and explained 6.6 to 58.9 % of phenotypic variation. A photosynthetic-specific QTL cluster, q12-1, was detected under both normal and low P conditions, suggesting that genes responsible for this region were less effected by low P stress, and could be used in high photosynthetic efficiency breeding programs. In addition, several candidate genes with significantly differential expression upon low P stress, such as a purple acid phosphatase gene (Glyma.19G193900) within q19-2 region, were considered as promising candidates involved in regulating both soybean PE and photosynthetic capacity. Our results reveal a significant genetic relationship between PE and photosynthetic traits, and uncover several major genomic regions specific or common to these traits. The markers linked closely to these major QTLs may be used for selection of soybean varieties with improved P efficiency and photosynthetic capacity.