Genome-wide identification and analysis of soybean acyl-ACP thioesterase gene family reveals the role of GmFAT to improve fatty acid composition in soybean seed

Disruption of the endoplasmic reticulum-localized fatty acyl-ACP thioesterase IPF1 caused partial male sterility in rice

The fatty acyl ACP thioesterases, catalyzing the final step of fatty acid synthesis in the plastid, regulate various critical processes in plants, including seed oil accumulation, seed development, plant growth, and drought tolerance. However, their roles in male fertility have seldom been demonstrated. In this study, the function of a newly FAT, Impaired Pollen Fertility 1 (IPF1) in male fertility was investigated. IPF1 expressed prominently in microspores and tapetum. IPF1 specifically located in the endoplasmic reticulum. IPF1 knock-out mutants produced by the CRISPR/Cas9 system displayed significant reduction in seed-setting rate compared to WT. The decreased seed-setting rate in the ipf1 mutants was found to be attributed to the defects of pollen viability, not the female gamete fertility. The aborted pollen in the ipf1 mutants showed impaired pollen wall formation and diminished lipid deposition. Consistently, the expression levels of six genes critical to pollen wall formation and lipid metabolism (GPAT3, OsC6, DPW2, OsPKS1, OsPKS2, and OsSTRL2) were significantly decreased in the ipf1 mutant. Taken together, these results demonstrate that IPF1 regulates rice pollen fertility through the modulation of lipid synthesis.

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.

Discovery of two tightly linked soybean genes at the qSCN10 (O) locus conferring broad-spectrum resistance to soybean cyst nematode

Soybean cyst nematode (SCN, Heterodera glycine Ichinohe) is a major threat to global soybean yield. Resistance genes at the rhg1 locus from PI 88788 are majorly utilized in 95% of the U.S. breeding programs. Continuous use of this resistance source leads to a shift in the virulence of SCN populations and overcomes host resistance. Therefore, it is necessary to identify alternative SCN resistance sources to combat this ever-changing pest. Previously, we identified an exotic soybean line, PI 567516C, which carries a novel qSCN10 (O) locus for SCN resistance demonstrating different resistance responses compared to the known rhg1 and Rhg4 loci. Here, we narrowed the qSCN10 QTL region to 142-kb (containing 20 genes). Based on gene expression, gene ontology, in-silico analysis, and QTL-based haplotyping, two genes were identified for functional characterization. Overexpression of the transcription factor TGA1-related and Shugoshin C-terminus in the SCN-susceptible Williams 82 reduced the cyst number by 6.4-fold (84.6%) and 5.3-fold (81.2%), respectively. GmTGA1-10 and GmSCT-10 Tilling mutants showed high cyst numbers. The two genes associated with the qSCN10 QTL have significant potential to reduce the SCN population. They also offer an alternative source of durable SCN resistance that is independent of rhg1 and Rhg4.

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.

The identification and expression analysis of walnut Acyl-ACP thioesterases

Walnuts (Juglans regia L.), renowned for their nutritional potency, are a rich source of unsaturated fatty acids. Their regular intake plays a pivotal role in health maintenance and recuperation from a myriad of ailments. Fatty acyl-acyl carrier protein thioesterases, which orchestrate the hydrolysis of acyl-ACP thioester bonds, thereby yielding fatty acids of varying chain lengths, are instrumental in augmenting plant fatty acid content and modulating the balance between saturated and unsaturated fatty acids. Despite some investigative efforts into the synthesis and metabolic pathways of fatty acids in walnuts, our comprehension of Fat in walnuts remains rudimentary. This research undertook a comprehensive characterization of the JrFat family, predicated on the complete genome sequence of walnuts, leading to the identification of 8 JrFat genes and an exploration of their protein physicochemical properties. Utilizing Arabidopsis and soybean Fat genes as outgroups, JrFat genes can be categorized into 5 distinct subgroups, three of which encompass a pair of homologous gene pairs. These genes have demonstrated remarkable conservation throughout the evolutionary process, with highly analogous conserved base sequences. The promoter region of JrFats genes predominantly harbors light response and plant hormone response regulatory elements, with no discernible disparity in promoter elements among different JrFats. Predictive analyses indicate that JrFats proteins engage extensively with walnut fatty acid synthesis and metabolism-associated proteins. qRT-PCR analysis reveals an initial surge in the expression of JrFats during the development of walnut kernels, which either stabilizes or diminishes following the hard core period. Homologous gene pairs exhibit analogous expression patterns, and the expression trajectory of JrFats aligns with the dynamic accumulation of fatty acids in kernels. The expression of JrFatA2 exhibits a strong correlation with the content of Alpha-linolenic acid, while the expression of JrFatB2 is inversely correlated with the content of two saturated fatty acids. Collectively, these findings enrich our understanding of fatty acid synthesis and metabolism in walnuts and furnish gene resources for enhancing the content and ratio of fatty acids in walnuts.

The acyl-acyl carrier protein thioesterases GmFATA1 and GmFATA2 are essential for fatty acid accumulation and growth in soybean

Acyl-acyl carrier protein (ACP) thioesterases (FAT) hydrolyze acyl-ACP complexes to release FA in plastids, which ultimately affects FA biosynthesis and profiles. Soybean GmFATA1 and GmFATA2 are homoeologous genes encoding oleoyl-ACP thioesterases whose role in seed oil accumulation and plant growth has not been defined. Using CRISPR/Cas9 gene editing mutation of Gmfata1 or 2 led to reduced leaf FA content and growth defect at the early seedling stage. In contrast, no homozygous double mutants were obtained. Combined this indicates that GmFATA1 and GmFATA2 display overlapping, but not complete functional redundancy. Combined transcriptomic and lipidomic analysis revealed a large number of genes involved in FA synthesis and FA chain elongation are expressed at reduced level in the Gmfata1 mutant, accompanied by a lower triacylglycerol abundance at the early seedling stage. Further analysis showed that the Gmfata1 or 2 mutants had increased composition of the beneficial FA, oleic acid. The growth defect of Gmfata1 could be at least partially attributed to reduced acetyl-CoA carboxylase activity, reduced abundance of five unsaturated monogalactosyldiacylglycerol lipids, and altered chloroplast morphology. On the other hand, overexpression of GmFATA in soybean led to significant increases in leaf FA content by 5.7%, vegetative growth, and seed yield by 26.9%, and seed FA content by 23.2%. Thus, overexpression of GmFATA is an effective strategy to enhance soybean oil content and yield.

Multi-omics-driven advances in the understanding of triacylglycerol biosynthesis in oil seeds

Vegetable oils are rich sources of polyunsaturated fatty acids and energy as well as valuable sources of human food, animal feed, and bioenergy. Triacylglycerols, which are comprised of three fatty acids attached to a glycerol backbone, are the main component of vegetable oils. Here, we review the development and application of multiple-level omics in major oilseeds and emphasize the progress in the analysis of the biological roles of key genes underlying seed oil content and quality in major oilseeds. Finally, we discuss future research directions in functional genomics research based on current omics and oil metabolic engineering strategies that aim to enhance seed oil content and quality, and specific fatty acids components according to either human health needs or industrial requirements.

Deep Learning Model for Classifying and Evaluating Soybean Leaf Disease Damage

Soybean (Glycine max (L.) Merr.) is a major source of oil and protein for human food and animal feed; however, soybean crops face diverse factors causing damage, including pathogen infections, environmental shifts, poor fertilization, and incorrect pesticide use, leading to reduced yields. Identifying the level of leaf damage aids yield projections, pesticide, and fertilizer decisions. Deep learning models (DLMs) and neural networks mastering tasks from abundant data have been used for binary healthy/unhealthy leaf classification. However, no DLM predicts and categorizes soybean leaf damage severity (five levels) for tailored pesticide use and yield forecasts. This paper introduces a novel DLM for accurate damage prediction and classification, trained on 2930 near-field soybean leaf images. The model quantifies damage severity, distinguishing healthy/unhealthy leaves and offering a comprehensive solution. Performance metrics include accuracy, precision, recall, and F1-score. This research presents a robust DLM for soybean damage assessment, supporting informed agricultural decisions based on specific damage levels and enhancing crop management and productivity.

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.

Identification of QTL for kernel weight and size and analysis of the pentatricopeptide repeat (PPR) gene family in cultivated peanut (Arachis hypogaea L.)

Peanut (Arachis hypogaea L.) is an important oilseed crop worldwide. Improving its yield is crucial for sustainable peanut production to meet increasing food and industrial requirements. Deciphering the genetic control underlying peanut kernel weight and size, which are essential components of peanut yield, would facilitate high-yield breeding. A high-density single nucleotide polymorphism (SNP)-based linkage map was constructed using a recombinant inbred lines (RIL) population derived from a cross between the variety Yuanza9102 and a germplasm accession wt09-0023. Kernel weight and size quantitative trait loci (QTLs) were co-localized to a 0.16 Mb interval on Arahy07 using inclusive composite interval mapping (ICIM). Analysis of SNP, and Insertion or Deletion (INDEL) markers in the QTL interval revealed a gene encoding a pentatricopeptide repeat (PPR) superfamily protein as a candidate closely linked with kernel weight and size in cultivated peanut. Examination of the PPR gene family indicated a high degree of collinearity of PPR genes between A. hypogaea and its diploid progenitors, Arachis duranensis and Arachis ipaensis. The candidate PPR gene, Arahy.JX1V6X, displayed a constitutive expression pattern in developing seeds. These findings lay a foundation for further fine mapping of QTLs related to kernel weight and size, as well as validation of candidate genes in cultivated peanut.

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.

Expression of malic enzyme reveals subcellular carbon partitioning for storage reserve production in soybeans

Central metabolism produces amino and fatty acids for protein and lipids that establish seed value. Biosynthesis of storage reserves occurs in multiple organelles that exchange central intermediates including two essential metabolites, malate, and pyruvate that are linked by malic enzyme. Malic enzyme can be active in multiple subcellular compartments, partitioning carbon and reducing equivalents for anabolic and catabolic requirements. Prior studies based on isotopic labeling and steady-state metabolic flux analyses indicated malic enzyme provides carbon for fatty acid biosynthesis in plants, though genetic evidence confirming this role is lacking. We hypothesized that increasing malic enzyme flux would alter carbon partitioning and result in increased lipid levels in soybeans. Homozygous transgenic soybean plants expressing Arabidopsis malic enzyme alleles, targeting the translational products to plastid or outside the plastid during seed development, were verified by transcript and enzyme activity analyses, organelle proteomics, and transient expression assays. Protein, oil, central metabolites, cofactors, and acyl-acyl carrier protein (ACPs) levels were quantified overdevelopment. Amino and fatty acid levels were altered resulting in an increase in lipids by 0.5-2% of seed biomass (i.e. 2-9% change in oil). Subcellular targeting of a single gene product in central metabolism impacts carbon and reducing equivalent partitioning for seed storage reserves in soybeans.

Genetic and Metabolite Variability among Commercial Varieties and Advanced Lines of Vicia faba L

Vicia faba L. (faba bean) is one of the most promising pulse crops due to its nutritional value and high nitrogen fixation capacity. The aim of the present study was to compare the genetic diversity and the seed metabolite profiles of five genetic materials of faba bean. Specifically, three newly developed advanced lines (KK18, KK14 and KK10) and two commercial cultivars (POLIKARPI and TANAGRA), were evaluated for this purpose. Genetic diversity among populations was assessed by SCoT molecular markers. Through UPGMA dendrogram, genetic distances between populations were estimated. Untargeted metabolomics analysis of the seeds was performed employing GC/EI/MS. The cultivar POLYKARPI exhibited the highest polymorphism. All varieties showed a higher within-cultivars and advanced lines variability than between. POLYKARPI and KK14 had the lowest genetic distances, while KK18 and TANAGRA presented the highest ones. The advanced line KK18 displayed the best nutritional profile, the highest concentration of desirable metabolites (lactic acid and trehalose), the lowest concentration of anti-nutritional factors (oxalic acid) and the lowest concentration of saturated fatty acids (palmitic and stearic acid). According to the results of the present study, KK18 line is a very promising material for further exploration and utilization in breeding programs.

Bioengineering of Soybean Oil and Its Impact on Agronomic Traits

Soybean is a major oil crop and is also a dominant source of nutritional protein. The 20% seed oil content (SOC) of soybean is much lower than that in most oil crops and the fatty acid composition of its native oil cannot meet the specifications for some applications in the food and industrial sectors. Considerable effort has been expended on soybean bioengineering to tailor fatty acid profiles and improve SOC. Although significant advancements have been made, such as the creation of high-oleic acid soybean oil and high-SOC soybean, those genetic modifications have some negative impacts on soybean production, for instance, impaired germination or low protein content. In this review, we focus on recent advances in the bioengineering of soybean oil and its effects on agronomic traits.

Genome-wide identification and analysis of the IQM gene family in soybean

IQM, a plant-specific calmodulin-binding protein, plays multiple roles in plant growth and development. Although a comprehensive analysis has been carried out on the IQM family genes in Arabidopsis and rice, the number and functions of IQM genes in other species have not been explored. In this study, we identified 15 members of the soybean (Glycine max) IQM gene family using BLASTP tools. These members were distributed on 12 soybean chromosomes and constitute six pairs caused by fragment duplication events. According to phylogeny, the 15 genes were divided into three subfamilies (I, II, and III), and members of the same subfamily had similar gene and protein structures. Yeast two-hybrid experiments revealed that the IQ motif is critical for the binding of GmIQM proteins to GmCaM, and its function is conserved in soybean, Arabidopsis, and rice. Based on real-time PCR, the soybean IQM genes were strongly induced by PEG and NaCl, suggesting their important biological functions in abiotic stress responses. Overall, this genome-wide analysis of the soybean IQM gene family lays a solid theoretical foundation for further research on the functions of GmIQM genes and could serve as a reference for the improvement and breeding of soybean stress resistance traits.

Identification of QTN-by-environment interactions and their candidate genes for soybean seed oil-related traits using 3VmrMLM

Introduction

Although seed oil content and its fatty acid compositions in soybean were affected by environment, QTN-by-environment (QEIs) and gene-by-environment interactions (GEIs) were rarely reported in genome-wide association studies.

Methods

The 3VmrMLM method was used to associate the trait phenotypes, measured in five to seven environments, of 286 soybean accessions with 106,013 SNPs for detecting QTNs and QEIs.

Results

Seven oil metabolism genes (GmSACPD-A, GmSACPD-B, GmbZIP123, GmSWEET39, GmFATB1A, GmDGAT2D, and GmDGAT1B) around 598 QTNs and one oil metabolism gene GmFATB2B around 54 QEIs were verified in previous studies; 76 candidate genes and 66 candidate GEIs were predicted to be associated with these traits, in which 5 genes around QEIs were verified in other species to participate in oil metabolism, and had differential expression across environments. These genes were found to be related to soybean seed oil content in haplotype analysis. In addition, most candidate GEIs were co-expressed with drought response genes in co-expression network, and three KEGG pathways which respond to drought were enriched under drought stress rather than control condition; six candidate genes were hub genes in the co-expression networks under drought stress.

Discussion

The above results indicated that GEIs, together with drought response genes in co-expression network, may respond to drought, and play important roles in regulating seed oil-related traits together with oil metabolism genes. These results provide important information for genetic basis, molecular mechanisms, and soybean breeding for seed oil-related traits.

QTL Mapping of Palmitic Acid Content Using Specific-Locus Amplified Fragment Sequencing (SLAF-Seq) Genotyping in Soybeans (Glycine max L.)

Soybeans are essential crops that supply protein and oil. The composition and contents of soybean fatty acids are relevant to human health and have a significant relationship with soybean oil processing and applications. Identifying quantitative trait locus (QTL) genes related to palmitic acid could facilitate the development of a range of nutritive soybean cultivars using molecular marker-assisted selection. In this study, we used a cultivar with higher palmitic acid content, ‘Dongnong42’, and a lower palmitic acid content cultivar, ‘Hobbit’, to establish F2:6 recombinant inbred lines. A high-density genetic map containing 9980 SLAF markers was constructed and distributed across 20 soybean chromosomes. The genetic map contained a total genetic distance of 2602.58 cM and an average genetic distance of 0.39 cM between adjacent markers. Two QTLs related to palmitic acid content were mapped using inclusive composite interval mapping, explaining 4.2–10.1% of the phenotypic variance in three different years and environments, including the QTL included in seed palmitic 7-3, which was validated by developing SSR markers. Based on the SNP/Indel and significant differential expression analyses of Dongnong42 and Hobbit, two genes, Glyma.15g119700 and Glyma.15g119800, were selected as candidate genes. The high-density genetic map, QTLs, and molecular markers will be helpful for the map-based cloning of palmitic acid content genes. These could be used to accelerate breeding for high nutritive value cultivars via molecular marker-assisted breeding.

4D genetic networks reveal the genetic basis of metabolites and seed oil-related traits in 398 soybean RILs

Background

The yield and quality of soybean oil are determined by seed oil-related traits, and metabolites/lipids act as bridges between genes and traits. Although there are many studies on the mode of inheritance of metabolites or traits, studies on multi-dimensional genetic network (MDGN) are limited.

Results

In this study, six seed oil-related traits, 59 metabolites, and 107 lipids in 398 recombinant inbred lines, along with their candidate genes and miRNAs, were used to construct an MDGN in soybean. Around 175 quantitative trait loci (QTLs), 36 QTL-by-environment interactions, and 302 metabolic QTL clusters, 70 and 181 candidate genes, including 46 and 70 known homologs, were previously reported to be associated with the traits and metabolites, respectively. Gene regulatory networks were constructed using co-expression, protein–protein interaction, and transcription factor binding site and miRNA target predictions between candidate genes and 26 key miRNAs. Using modern statistical methods, 463 metabolite–lipid, 62 trait–metabolite, and 89 trait–lipid associations were found to be significant. Integrating these associations into the above networks, an MDGN was constructed, and 128 sub-networks were extracted. Among these sub-networks, the gene–trait or gene–metabolite relationships in 38 sub-networks were in agreement with previous studies, e.g., oleic acid (trait)–GmSEI–GmDGAT1a–triacylglycerol (16:0/18:2/18:3), gene and metabolite in each of 64 sub-networks were predicted to be in the same pathway, e.g., oleic acid (trait)–GmPHS–d-glucose, and others were new, e.g., triacylglycerol (16:0/18:1/18:2)–GmbZIP123–GmHD-ZIPIII-10–miR166s–oil content.

Conclusions

This study showed the advantages of MGDN in dissecting the genetic relationships between complex traits and metabolites. Using sub-networks in MGDN, 3D genetic sub-networks including pyruvate/threonine/citric acid revealed genetic relationships between carbohydrates, oil, and protein content, and 4D genetic sub-networks including PLDs revealed the relationships between oil-related traits and phospholipid metabolism likely influenced by the environment. This study will be helpful in soybean quality improvement and molecular biological research.

Supplementary Information

The online version contains supplementary material available at 10.1186/s13068-022-02191-1.

Identification of AhFatB genes through genome-wide analysis and knockout of AhFatB reduces the content of saturated fatty acids in peanut (Arichis hypogaea L.)

Peanut (Arachis hypogaea L.) is an allotetraploid oilseed crop worldwide due to its abundant high-quality oil production. Peanut oil stability and quality are determined by the relative proportions of saturated fatty acids (SFAs) and unsaturated fatty acids (UFAs). The principle approach to minimize the content of SFAs in peanut is to reduce the content of palmitic acid, which is linked to cardiovascular disease. Acyl-acyl carrier protein thioesterases (FATs) determine the types and levels of fatty acids that are exported them from the plastids. Two different classes of FAT have been classified into two families in plants, FatA and FatB. Among them, AhFatB has become the primary objective to genetically reduce the content of palmitic acid in peanut. Here, we identified 18 AhFatB genes in A. hypogaea genome and grouped into four major subfamilies through gene structures and phylogenetic relationships. Expression profiling of AhFatB genes was assessed using the publicly available RNA-seq data and qRT-PCR in 22 tissues. Using the CRISPR/Cas9 system, we designed two sgRNAs to edit the homologs AhFatB genes Arahy.4E7QKU and Arahy.L4EP3N, and identified different types of mutations. Additionally, we discovered mutations at Arahy.4E7QKU exhibited low palmitic acid and high oleic acid phenotypes. The obtained peanut mutants with altered SFAs content have great potential for improving peanut oil quality for human health.

Transcriptomic Analysis Reveals the Regulatory Networks and Hub Genes Controlling the Unsaturated Fatty Acid Contents of Developing Seed in Soybean

Soybean [Glycine max (L.) Merr.] is one of the most important crops, which produces about 25% of the world's edible oil. The nutritional value of soybean oil depends mostly on the relative contents of three unsaturated fatty acids (UFAs), i.e., oleic acid, linoleic acid (LA), and linolenic acid. However, the biosynthetic mechanism of UFAs remains largely unknown, and there are few studies on RNA-seq analysis of developing seeds. To identify the candidate genes and related pathways involved in the regulation of UFA contents during seed development in soybean, two soybean lines with different UFA profiles were selected from 314 cultivars and landraces originated from Southern China, and RNA-seq analysis was performed in soybean seeds at three developmental stages. Using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) enrichment analysis, a series of genes and pathways related to fatty acid metabolism were identified, and 40 days after flowering (DAF) was found to be the crucial period in the formation of UFA profiles. Further, weighted gene co-expression network analysis identified three modules with six genes whose functions were highly associated with the contents of oleic and LA. The detailed functional investigation of the networks and hub genes could further improve the understanding of the underlying molecular mechanism of UFA contents and might provide some ideas for the improvement in fatty acids profiles in soybean.

Domestication and improvement genes reveal the differences of seed size- and oil-related traits in soybean domestication and improvement

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Due to reduced diversity, it is essential to map domesticated and improved genes.

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13 known and 442 candidate genes were mined for seed size- and oil-related traits.

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All the genes were used to explain trait changes in domestication and improvement.

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56 domesticated and 15 improved genes may be valuable for future soybean breeding.

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This study provides useful gene resources for future breeding and biology research.

To address domestication and improvement studies of soybean seed size- and oil-related traits, a series of domesticated and improved regions, loci, and candidate genes were identified in 286 soybean accessions using domestication and improvement analyses, genome-wide association studies, quantitative trait locus (QTL) mapping and bulked segregant analyses in this study. As a result, 534 candidate domestication regions (CDRs) and 458 candidate improvement regions (CIRs) were identified in this study and integrated with those in five and three previous studies, respectively, to obtain 952 CDRs and 538 CIRs; 1469 loci for soybean seed size- and oil-related traits were identified in this study and integrated with those in Soybase to obtain 433 QTL clusters. The two results were intersected to obtain 245 domestication and 221 improvement loci for the above traits. Around these trait-related domestication and improvement loci, 7 domestication and 7 improvement genes were found to be truly associated with these traits, and 372 candidate domestication and 87 candidate improvement genes were identified using gene expression, SNP variants in genome, miRNA binding, KEGG pathway, DNA methylation, and haplotype analysis. These genes were used to explain the trait changes in domestication and improvement. As a result, the trait changes can be explained by their frequencies of elite haplotypes, base mutations in coding region, and three factors affecting their expression levels. In addition, 56 domestication and 15 improvement genes may be valuable for future soybean breeding. This study can provide useful gene resources for future soybean breeding and molecular biology research.