A systems biology approach toward understanding seed composition in soybean

Integrative transcriptomics reveals association of abscisic acid and lignin pathways with cassava whitefly resistance

BACKGROUND

Whiteflies are a global threat to crop yields, including the African subsistence crop cassava (Manihot esculenta). Outbreaks of superabundant whitefly populations throughout Eastern and Central Africa in recent years have dramatically increased the pressures of whitefly feeding and virus transmission on cassava. Whitefly-transmitted viral diseases threaten the food security of hundreds of millions of African farmers, highlighting the need for developing and deploying whitefly-resistant cassava. However, plant resistance to whiteflies remains largely poorly characterized at the genetic and molecular levels. Knowledge of cassava-defense programs also remains incomplete, limiting characterization of whitefly-resistance mechanisms. To better understand the genetic basis of whitefly resistance in cassava, we define the defense hormone- and Aleurotrachelus socialis (whitefly)-responsive transcriptome of whitefly-susceptible (COL2246) and whitefly-resistant (ECU72) cassava using RNA-seq. For broader comparison, hormone-responsive transcriptomes of Arabidopsis thaliana were also generated.

RESULTS

Whitefly infestation, salicylic acid (SA), jasmonic acid (JA), ethylene (ET), and abscisic acid (ABA) transcriptome responses of ECU72 and COL2246 were defined and analyzed. Strikingly, SA responses were largely reciprocal between the two cassava genotypes and we suggest candidate regulators. While susceptibility was associated with SA in COL2246, resistance to whitefly in ECU72 was associated with ABA, with SA-ABA antagonism observed. This was evidenced by expression of genes within the SA and ABA pathways and hormone levels during A. socialis infestation. Gene-enrichment analyses of whitefly- and hormone-responsive genes suggest the importance of fast-acting cell wall defenses (e.g., elicitor recognition, lignin biosynthesis) during early infestation stages in whitefly-resistant ECU72. A surge of ineffective immune and SA responses characterized the whitefly-susceptible COL2246's response to late-stage nymphs. Lastly, in comparison with the model plant Arabidopsis, cassava's hormone-responsive genes showed striking divergence in expression.

CONCLUSIONS

This study provides the first characterization of cassava's global transcriptome responses to whitefly infestation and defense hormone treatment. Our analyses of ECU72 and COL2246 uncovered possible whitefly resistance/susceptibility mechanisms in cassava. Comparative analysis of cassava and Arabidopsis demonstrated that defense programs in Arabidopsis may not always mirror those in crop species. More broadly, our hormone-responsive transcriptomes will also provide a baseline for the cassava community to better understand global responses to other yield-limiting pests/pathogens.

Soybean Seed Sugars: A Role in the Mechanism of Resistance to Charcoal Rot and Potential Use as Biomarkers in Selection

Charcoal rot, caused by Macrophomina phaseolina, is a major soybean disease resulting in significant yield loss and poor seed quality. Currently, no resistant soybean cultivar is available in the market and resistance mechanisms to charcoal rot are unknown, although the disease is believed to infect plants from infected soil through the roots by unknown toxin-mediated mechanisms. The objective of this research was to investigate the association between seed sugars (sucrose, raffinose, stachyose, glucose, and fructose) and their role as biomarkers in the soybean defense mechanism in the moderately resistant (MR) and susceptible (S) genotypes to charcoal rot. Seven MR and six S genotypes were grown under irrigated (IR) and non-irrigated (NIR) conditions. A two-year field experiment was conducted in 2012 and 2013 at Jackson, TN, USA. The main findings in this research were that MR genotypes generally had the ability to maintain higher seed levels of sucrose, glucose, and fructose than did S genotypes. Conversely, susceptible genotypes showed a higher level of stachyose and lower levels of sucrose, glucose, and fructose. This was observed in 6 out of 7 MR genotypes and in 4 out of 6 S genotypes in 2012; and in 5 out of 7 MR genotypes and in 5 out of 6 S genotypes in 2013. The response of S genotypes with higher levels of stachyose and lower sucrose, glucose, and fructose, compared with those of MR genotypes, may indicate the possible role of these sugars in a defense mechanism against charcoal rot. It also indicates that nutrient pathways in MR genotypes allowed for a higher influx of nutritious sugars (sucrose, glucose, and fructose) than did S genotypes, suggesting these sugars as potential biomarkers for selecting MR soybean plants after harvest. This research provides new knowledge on seed sugars and helps in understanding the impact of charcoal rot on seed sugars in moderately resistant and susceptible genotypes.

Can Soybean Cultivars with Larger Seed Size Produce More Protein, Lipids, and Seed Yield? A Meta-Analysis

Increasing soybean production and ensuring greater access to soybean protein and lipids is critical for global food security and human health. Seed size (i.e., seed weight) is one of the most important agronomic traits of soybean, which not only determines the seed yield, but can also affect the yield of protein and lipids. In China, farmers favor soybean cultivars with large seeds, which they believe produce more protein and lipids; however, experimental evidence supporting this belief is lacking. Therefore, we conducted field experiments from 2017 to 2020 at 35 locations across the Huang-Huai-Hai region (HHH) of China with 64 soybean cultivars. The seed yield, seed protein content, and seed lipids content of soybean, and their relationship with seed size were investigated. The highest seed yield (i.e., seed weight per unit area) was 2996.5 kg ha−1 in the north of HHH. However, the highest seed protein content was found in the south of HHH (42.5%) for the higher temperature, which was significantly higher than that of the middle (41.7%) and north of HHH (40.2%). In contrast, the highest seed lipids content was 20.7% in the north of HHH. Temperature, which had a path coefficient on seed yield of 0.519, can promote soybean seed yield. The correlation analysis indicated that the selection of the large seed size cultivar did not increase seed yield, and even led to a reduction of seed yield under high-yield environmental conditions. The seed protein content of soybean was not increased in the cultivars with large seed sizes. In addition, under different levels of seed lipids content (<20.30% or >20.30%), a significantly negative relationship was found between seed lipids content and hundred seed weight. Therefore, it is recommended that farmers choose to plant cultivars with smaller soybean seed sizes, so as to ensure high and stable soybean seed yield and obtain more vegetable protein and lipids per unit area.

Using transcriptomic and metabolomic data to investigate the molecular mechanisms that determine protein and oil contents during seed development in soybean

Soybean [Glycine max (L.) Merri.] is one of the most valuable global crops. And vegetable soybean, as a special type of soybean, provides rich nutrition in people's life. In order to investigate the gene expression networks and molecular regulatory mechanisms that regulate soybean seed oil and protein contents during seed development, we performed transcriptomic and metabolomic analyses of soybean seeds during development in two soybean varieties that differ in protein and oil contents. We identified a total of 41,036 genes and 392 metabolites, of which 12,712 DEGs and 315 DAMs were identified. Analysis of KEGG enrichment demonstrated that DEGs were primarily enriched in phenylpropanoid biosynthesis, glycerolipid metabolism, carbon metabolism, plant hormone signal transduction, linoleic acid metabolism, and the biosynthesis of amino acids and secondary metabolites. K-means analysis divided the DEGs into 12 distinct clusters. We identified candidate gene sets that regulate the biosynthesis of protein and oil in soybean seeds, and present potential regulatory patterns that high seed-protein varieties may be more sensitive to desiccation, show earlier photomorphogenesis and delayed leaf senescence, and thus accumulate higher protein contents than high-oil varieties.

Seed Development and Protein Accumulation Patterns in Faba Bean (Vicia faba, L.)

A major objective in faba bean breeding is to improve its protein quality by selecting cultivars with enhanced desirable physicochemical properties. However, the protein composition of the mature seed is determined by a series of biological processes occurring during seed growth. Thus, any attempt to explain the final seed composition must consider the dynamics of the seed proteome during seed development. Here, we investigated the proteomic profile of developing faba bean seeds across 12 growth stages from 20 days after pollination (DAP) to full maturity. We analyzed trypsin-digested total protein extracts from the seeds at different growth stages by liquid chromatography-tandem mass spectrometry (LC-MS/MS), identifying 1217 proteins. The functional clusters of these proteins showed that, in early growth stages, proteins related to cell growth, division, and metabolism were most abundant compared to seed storage proteins that began to accumulate from 45 DAP. Moreover, label-free quantification of the relative abundance of seed proteins, including important globulin proteins, revealed several distinct temporal accumulation trends among the protein classes. These results suggest that these proteins are regulated differently and require further understanding of the impact of the different environmental stresses occurring at different grain filling stages on the expression and accumulation of these seed storage proteins.

Suppression of SDP1 Improves Soybean Seed Composition by Increasing Oil and Reducing Undigestible Oligosaccharides

In developing soybean seeds, carbon is partitioned between oil, protein and carbohydrates. Here, we demonstrate that suppression of lipase-mediated turnover of triacylglycerols (TAG) during late seed development increases fatty acid content and decreases the presence of undigestible oligosaccharides. During late stages of embryo development, the fatty acid content of soybean seed decreases while the levels of the oligosaccharides raffinose and stachyose increase. Three soybean genes orthologous to the Arabidopsis lipase gene SUGAR-DEPENDENT1 (SDP1) are upregulated at this time. Suppression of these genes resulted in higher oil levels, with lipid levels in the best lines exceeding 24% of seed weight. In addition, lipase-suppressed lines produced larger seeds compared to wild-type plants, resulting in increases of over 20% in total lipid per seed. Levels of raffinose and stachyose were lower in the transgenic lines, with average reductions of 15% in total raffinose family oligosaccharides observed. Despite the increase in oil, protein content was not negatively impacted and trended higher in the transgenic lines. These results are consistent with a role for SDP1 in turning over TAG to supply carbon for other needs, including the synthesis of oligosaccharides, and offer new strategies to further improve the composition of soybean seeds.

Temporal changes in metabolism late in seed development affect biomass composition

The negative association between protein and oil production in soybean (Glycine max) seed is well-documented. However, this inverse relationship is based primarily on the composition of mature seed, which reflects the cumulative result of events over the course of soybean seed development and therefore does not convey information specific to metabolic fluctuations during developmental growth regimes. In this study, we assessed maternal nutrient supply via measurement of seed coat exudates and metabolite levels within the cotyledon throughout development to identify trends in the accumulation of central carbon and nitrogen metabolic intermediates. Active metabolic activity during late seed development was probed through transient labeling with 13C substrates. The results indicated: (1) a drop in lipid contents during seed maturation with a concomitant increase in carbohydrates, (2) a transition from seed filling to maturation phases characterized by quantitatively balanced changes in carbon use and CO2 release, (3) changes in measured carbon and nitrogen resources supplied maternally throughout development, (4) 13C metabolite production through gluconeogenic steps for sustained carbohydrate accumulation as the maternal nutrient supply diminishes, and (5) oligosaccharide biosynthesis within the seed coat during the maturation phase. These results highlight temporal engineering targets for altering final biomass composition to increase the value of soybeans and a path to breaking the inverse correlation between seed protein and oil content.

Metabolomics as a Tool to Study Underused Soy Parts: In Search of Bioactive Compounds

The valorization of agri-food by-products is essential from both economic and sustainability perspectives. The large quantity of such materials causes problems for the environment; however, they can also generate new valuable ingredients and products which promote beneficial effects on human health. It is estimated that soybean production, the major oilseed crop worldwide, will leave about 597 million metric tons of branches, leaves, pods, and roots on the ground post-harvesting in 2020/21. An alternative for the use of soy-related by-products arises from the several bioactive compounds found in this plant. Metabolomics studies have already identified isoflavonoids, saponins, and organic and fatty acids, among other metabolites, in all soy organs. The present review aims to show the application of metabolomics for identifying high-added-value compounds in underused parts of the soy plant, listing the main bioactive metabolites identified up to now, as well as the factors affecting their production.

Soybean Inoculated With One Bradyrhizobium Strain Isolated at Elevated [CO2] Show an Impaired C and N Metabolism When Grown at Ambient [CO2]

Soybean (Glycine max L.) future response to elevated [CO₂] has been shown to differ when inoculated with B. japonicum strains isolated at ambient or elevated [CO₂]. Plants, inoculated with three Bradyrhizobium strains isolated at different [CO₂], were grown in chambers at current and elevated [CO₂] (400 vs. 700 ppm). Together with nodule and leaf metabolomic profile, characterization of nodule N-fixation and exchange between organs were tested through ¹⁵N₂-labeling analysis. Soybeans inoculated with SFJ14-36 strain (isolated at elevated [CO₂]) showed a strong metabolic imbalance, at nodule and leaf levels when grown at ambient [CO₂], probably due to an insufficient supply of N by nodules, as shown by ¹⁵N₂-labeling. In nodules, due to shortage of photoassimilate, C may be diverted to aspartic acid instead of malate in order to improve the efficiency of the C source sustaining N₂-fixation. In leaves, photorespiration and respiration were boosted at ambient [CO₂] in plants inoculated with this strain. Additionally, free phytol, antioxidants, and fatty acid content could be indicate induced senescence due to oxidative stress and lack of nitrogen. Therefore, plants inoculated with Bradyrhizobium strain isolated at elevated [CO₂] may have lost their capacity to form effective symbiosis at ambient [CO₂] and that was translated at whole plant level through metabolic impairment.

Comparative transcriptome analysis during seeds development between two soybean cultivars

Soybean is one of the important economic crops, which supplies a great deal of vegetable oil and proteins for human. The content of nutrients in different soybean seeds is different, which is related to the expression of multiple genes, but the mechanisms are complicated and still largely uncertain. In this study, to reveal the possible causes of the nutrients difference in soybeans A7 (containing low oil and high protein) and A35 (containing high oil and low protein), RNA-seq technology was performed to compare and identify the potential differential expressed genes (DEGs) at different seed developmental stages. The results showed that DEGs mainly presented at the early stages of seeds development and more DEGs were up-regulated at the early stage than the late stages. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes analysis showed that the DEGs have diverged in A7 and A35. In A7, the DEGs were mainly involved in cell cycle and stresses, while in A35 were the fatty acids and sugar metabolism. Specifically, when the DEGs contributing to oil and protein metabolic pathways were analyzed, the differences between A7 and A35 mainly presented in fatty acids metabolism and seeds storage proteins (SSPs) synthesis. Furthermore, the enzymes, fatty acid dehydrogenase 2, 3-ketoacyl-CoA synthase and 9S-lipoxygenase, in the synthesis and elongation pathways of fatty acids, were revealed probably to be involved in the oil content difference between A7 and A35, the SSPs content might be due to the transcription factors: Leafy Cotyledon 2 and Abscisic acid-intensitive 3, while the sugar transporter, SWEET10a, might contribute to both oil and protein content differences. Finally, six DEGs were selected to analyze their expression using qRT-PCR, and the results were consistent with the RNA-seq results. Generally, the study provided a comprehensive and dynamic expression trends for the seed development processes, and uncovered the potential DEGs for the differences of oil in A7 and A35.

Systematic Multi-Omics Integration (MOI) Approach in Plant Systems Biology

Across all facets of biology, the rapid progress in high-throughput data generation has enabled us to perform multi-omics systems biology research. Transcriptomics, proteomics, and metabolomics data can answer targeted biological questions regarding the expression of transcripts, proteins, and metabolites, independently, but a systematic multi-omics integration (MOI) can comprehensively assimilate, annotate, and model these large data sets. Previous MOI studies and reviews have detailed its usage and practicality on various organisms including human, animals, microbes, and plants. Plants are especially challenging due to large poorly annotated genomes, multi-organelles, and diverse secondary metabolites. Hence, constructive and methodological guidelines on how to perform MOI for plants are needed, particularly for researchers newly embarking on this topic. In this review, we thoroughly classify multi-omics studies on plants and verify workflows to ensure successful omics integration with accurate data representation. We also propose three levels of MOI, namely element-based (level 1), pathway-based (level 2), and mathematical-based integration (level 3). These MOI levels are described in relation to recent publications and tools, to highlight their practicality and function. The drawbacks and limitations of these MOI are also discussed for future improvement toward more amenable strategies in plant systems biology.

Identification and Mapping of Stable QTLs for Seed Oil and Protein Content in Soybean [Glycine max (L.) Merr.]

This research aimed to identify stable quantitative trait loci (QTL) associated with oil and protein content in soybean. A population of 196 recombinant inbred lines (RILs) derived from Huachun 2 × Wayao was used to evaluate these target traits. A high-density genetic linkage map was constructed by using high-throughput genome-wide sequencing technology, which contained 3413 recombination bin markers and spanned 5400.4 cM with an average distance of 1.58 cM between markers. Eighteen stable QTLs controlling oil and protein content were detected. Among them, qOil-11-1 was identified for the first time as a novel QTL, while qOil-5-1, qPro-10-1, and qPro-14-1 were strong and stable QTLs with high log-likelihood (LOD) values. Sixteen differentially expressed genes (DEGs) within these four QTLs were shown to be highly expressed during seed development based on RNA sequencing (RNA-seq) data analysis. Our results may contribute toward gene mining and marker-assisted selection (MAS) for breeding a high-quality soybean in the future.

On the Inverse Correlation of Protein and Oil: Examining the Effects of Altered Central Carbon Metabolism on Seed Composition Using Soybean Fast Neutron Mutants

Protein and oil levels measured at maturity are inversely correlated across soybean lines; however, carbon is in limited supply during maturation resulting in tradeoffs for the production of other reserves including oligosaccharides. During the late stages of seed development, the allocation of carbon for storage reserves changes. Lipid and protein levels decline while concentrations of indigestible raffinose family oligosaccharides (RFOs) increase, leading to a decreased crop value. Since the maternal source of carbon is diminished during seed maturation stages of development, carbon supplied to RFO synthesis likely comes from an internal, turned-over source and may contribute to the reduction in protein and lipid content in mature seeds. In this study, fast neutron (FN) mutagenized soybean populations with deletions in central carbon metabolic genes were examined for trends in oil, protein, sugar, and RFO accumulation leading to an altered final composition. Two lines with concurrent increases in oil and protein, by combined 10%, were identified. A delayed switch in carbon allocation towards RFO biosynthesis resulted in extended lipid accumulation and without compromising protein. Strategies for future soybean improvement using FN resources are described.

Comparative transcriptomic analysis of high- and low-oil Camellia oleifera reveals a coordinated mechanism for the regulation of upstream and downstream multigenes for high oleic acid accumulation

Tea oil camellia (Camellia oleifera) is an important woody oil tree in southern China. However, little is known regarding the molecular mechanisms that contribute to high oleic acid accumulation in tea oil camellia. Herein, we measured the oil content and fatty acid compositions of high- and low-oil tea oil camellia seeds and investigated the global gene expression profiles by RNA-seq. The results showed that at the early, second and third seed developmental stages, a total of 64, 253, and 124 genes, respectively, were significantly differentially expressed between the high- and low-oil cultivars. Gene ontology (GO) enrichment analysis of the identified differentially expressed transcription factors (TFs; ABI3, FUS3, LEC1, WRI1, TTG2 and DOF4.6) revealed some critical GO terms associated with oil biosynthesis and fatty acid accumulation, including glycolysis, zinc ion binding, positive regulation of fatty acid biosynthetic process, triglyceride biosynthetic process, seed coat development, abscisic acid-mediated signaling pathway and embryo development. Comprehensive comparisons of transcriptomic profiles and expression analysis of multigenes based on qRT-PCR showed that coordinated high expression of the upstream genes HAD, EAR and KASI directly increased the relative levels of C16:0-ACP, which provided enough precursor resources for oleic acid biosynthesis. Continuous high expression of the SAD gene accelerated oleic acid synthesis and accumulation, and coordinated low expression of the downstream genes FAD2, FAD3, FAD7, FAD8 and FAE1 decreased the consumption of oleic acid for conversion. The coordinated regulation of these multigenes ensures the high accumulation of oleic acid in the seeds of tea oil camellia. Our data represent a comprehensive transcriptomic study of high- and low-oil tea oil camellia, not only increasing the number of sequences associated with lipid biosynthesis and fatty acid accumulation in public resource databases but also providing a scientific basis for genetic improvement of the oleic acid content in woody oil trees.

Systems biology of seeds: decoding the secret of biochemical seed factories for nutritional security

Seeds serve as biochemical factories of nutrition, processing, bio-energy and storage related important bio-molecules and act as a delivery system to transmit the genetic information to the next generation. The research pertaining towards delineating the complex system of regulation of genes and pathways related to seed biology and nutrient partitioning is still under infancy. To understand these, it is important to know the genes and pathway(s) involved in the homeostasis of bio-molecules. In recent past with the advent and advancement of modern tools of genomics and genetic engineering, multi-layered 'omics' approaches and high-throughput platforms are being used to discern the genes and proteins involved in various metabolic, and signaling pathways and their regulations for understanding the molecular genetics of biosynthesis and homeostasis of bio-molecules. This can be possible by exploring systems biology approaches via the integration of omics data for understanding the intricacy of seed development and nutrient partitioning. These information can be exploited for the improvement of biologically important chemicals for large-scale production of nutrients and nutraceuticals through pathway engineering and biotechnology. This review article thus describes different omics tools and other branches that are merged to build the most attractive area of research towards establishing the seeds as biochemical factories for human health and nutrition.

The metabolic roles of free amino acids during seed development

Amino acids play vital roles in the central metabolism of seeds. They are primarily utilized for the synthesis of seed-storage proteins, but also serve as precursors for the biosynthesis of secondary metabolites and as a source of energy. Here, we aimed at describing the knowledge accumulated in recent years describing the changes occurring in the contents of free amino acids (FAAs) during seed development. Since several essential amino acids are found in low levels in seeds (e.g., Lys, Met, Thr, Val, Leu, Ile and His), or play unique functional roles in seed development (e.g., Pro and the non-proteinogenic γ-aminobutyrate [GABA]), we also briefly describe studies carried out in order to alter their levels in seeds and determine the effects of the manipulation on seed biology. The lion share of these studies highlights strong positive correlations between the biosynthetic pathways of FAAs, meaning that when the levels of a certain amino acid change in seeds, the contents of other FAAs tend to elevate as well. These observations infer a tight regulatory network operating in the biosynthesis of FAAs during seed development.

Integrating proteomics and enzymatic profiling to decipher seed metabolism affected by temperature in seed dormancy and germination

Temperature is an important environmental factor affecting seed dormancy and germination. The mechanism by which temperature induces germination in dormant seeds is however still unclear. Proteomic study has been performed in dormant sunflower seeds during imbibition at permissive and non-permissive temperatures for germination, 20 and 10 °C, respectively. Proteome analysis showed an increase of proteins belonging to metabolism and energy from the first hours of imbibition followed by a decrease of proteins involved in protein metabolism and seed storage in germinating compared to non-germinating seeds. Proteomic study was completed by polysome and proteasome activity assessment and enzymatic profiling on several altered proteins involved in metabolism and energy. Results showed that 20 °C treatment induced the activation of both protein synthesis and degradation processes, the latter being related to proteasome activity during the germination sensu stricto, and to other degradation processes such as proteases during the post-germination. Interestingly, enzymatic profiles showed that TCA cycle and glycolysis were more active in non-germinating seeds in the phase I of the germination sensu stricto. This result suggests the regulation of central metabolism activity in germinating seeds. The control of energy production during imbibition seems to be involved in molecular networks controlling seed dormancy and germination.

Raising orphans from a metadata morass: A researcher's guide to re-use of public 'omics data

More than 15 petabases of raw RNAseq data is now accessible through public repositories. Acquisition of other 'omics data types is expanding, though most lack a centralized archival repository. Data-reuse provides tremendous opportunity to extract new knowledge from existing experiments, and offers a unique opportunity for robust, multi-'omics analyses by merging metadata (information about experimental design, biological samples, protocols) and data from multiple experiments. We illustrate how predictive research can be accelerated by meta-analysis with a study of orphan (species-specific) genes. Computational predictions are critical to infer orphan function because their coding sequences provide very few clues. The metadata in public databases is often confusing; a test case with Zea mays mRNA seq data reveals a high proportion of missing, misleading or incomplete metadata. This metadata morass significantly diminishes the insight that can be extracted from these data. We provide tips for data submitters and users, including specific recommendations to improve metadata quality by more use of controlled vocabulary and by metadata reviews. Finally, we advocate for a unified, straightforward metadata submission and retrieval system.

Molecular characterization of the acquisition of longevity during seed maturation in soybean

Seed longevity, defined as the ability to remain alive during storage, is an important agronomic factor. Poor longevity negatively impacts seedling establishment and consequently crop yield. This is particularly problematic for soybean as seeds have a short lifespan. While the economic importance of soybean has fueled a large number of transcriptome studies during embryogenesis and seed filling, the mechanisms regulating seed longevity during late maturation remain poorly understood. Here, a detailed physiological and molecular characterization of late seed maturation was performed in soybean to obtain a comprehensive overview of the regulatory genes that are potentially involved in longevity. Longevity appeared at physiological maturity at the end of seed filling before maturation drying and progressively doubled until the seeds reached the dry state. The increase in longevity was associated with the expression of genes encoding protective chaperones such as heat shock proteins and the repression of nuclear and chloroplast genes involved in a range of chloroplast activities, including photosynthesis. An increase in the raffinose family oligosaccharides (RFO)/sucrose ratio together with changes in RFO metabolism genes was also associated with longevity. A gene co-expression network analysis revealed 27 transcription factors whose expression profiles were highly correlated with longevity. Eight of them were previously identified in the longevity network of Medicago truncatula, including homologues of ERF110, HSF6AB, NFXL1 and members of the DREB2 family. The network also contained several transcription factors associated with auxin and developmental cell fate during flowering, organ growth and differentiation. A transcriptional transition occurred concomitant with seed chlorophyll loss and detachment from the mother plant, suggesting the activation of a post-abscission program. This transition was enriched with AP2/EREBP and WRKY transcription factors and genes associated with growth, germination and post-transcriptional processes, suggesting that this program prepares the seed for the dry quiescent state and germination.

Metabolomic Profiling of Soybeans (Glycine max L.) Reveals the Importance of Sugar and Nitrogen Metabolism under Drought and Heat Stress

Soybean is an important crop that is continually threatened by abiotic stresses, especially drought and heat stress. At molecular levels, reduced yields due to drought and heat stress can be seen as a result of alterations in metabolic homeostasis of vegetative tissues. At present an incomplete understanding of abiotic stress-associated metabolism and identification of associated metabolites remains a major gap in soybean stress research. A study with a goal to profile leaf metabolites under control conditions (28/24 °C), drought [28/24 °C, 10% volumetric water content (VWC)], and heat stress (43/35 °C) was conducted in a controlled environment. Analyses of non-targeted metabolomic data showed that in response to drought and heat stress, key metabolites (carbohydrates, amino acids, lipids, cofactors, nucleotides, peptides and secondary metabolites) were differentially accumulated in soybean leaves. The metabolites for various cellular processes, such as glycolysis, the tricarboxylic acid (TCA) cycle, the pentose phosphate pathway, and starch biosynthesis, that regulate carbohydrate metabolism, amino acid metabolism, peptide metabolism, and purine and pyrimidine biosynthesis, were found to be affected by drought as well as heat stress. Computationally based regulatory networks predicted additional compounds that address the possibility of other metabolites and metabolic pathways that could also be important for soybean under drought and heat stress conditions. Metabolomic profiling demonstrated that in soybeans, keeping up with sugar and nitrogen metabolism is of prime significance, along with phytochemical metabolism under drought and heat stress conditions.

Integration of omics approaches to understand oil/protein content during seed development in oilseed crops

Oilseed crops, especially soybean (Glycine max) and canola/rapeseed (Brassica napus), produce seeds that are rich in both proteins and oils and that are major sources of energy and nutrition worldwide. Most of the nutritional content in the seed is accumulated in the embryo during the seed filling stages of seed development. Understanding the metabolic pathways that are active during seed filling and how they are regulated are essential prerequisites to crop improvement. In this review, we summarize various omics studies of soybean and canola/rapeseed during seed filling, with emphasis on oil and protein traits, to gain a systems-level understanding of seed development. Currently, most (80-85%) of the soybean and rapeseed reference genomes have been sequenced (950 and 850 megabases, respectively). Parallel to these efforts, extensive omics datasets from different seed filling stages have become available. Transcriptome and proteome studies have detected preponderance of starch metabolism and glycolysis enzymes to be the possible cause of higher oil in B. napus compared to other crops. Small RNAome studies performed during the seed filling stages have revealed miRNA-mediated regulation of transcription factors, with the suggestion that this interaction could be responsible for transitioning the seeds from embryogenesis to maturation. In addition, progress made in dissecting the regulation of de novo fatty acid synthesis and protein storage pathways is described. Advances in high-throughput omics and comprehensive tissue-specific analyses make this an exciting time to attempt knowledge-driven investigation of complex regulatory pathways.

Fluxomics links cellular functional analyses to whole-plant phenotyping

Fluxes through metabolic pathways reflect the integration of genetic and metabolic regulations. While it is attractive to measure all the mRNAs (transcriptome), all the proteins (proteome), and a large number of the metabolites (metabolome) in a given cellular system, linking and integrating this information remains difficult. Measurement of metabolome-wide fluxes (termed the fluxome) provides an integrated functional output of the cell machinery and a better tool to link functional analyses to plant phenotyping. This review presents and discusses sets of methodologies that have been developed to measure the fluxome. First, the principles of metabolic flux analysis (MFA), its 'short time interval' version Inst-MFA, and of constraints-based methods, such as flux balance analysis and kinetic analysis, are briefly described. The use of these powerful methods for flux characterization at the cellular scale up to the organ (fruits, seeds) and whole-plant level is illustrated. The added value given by fluxomics methods for unravelling how the abiotic environment affects flux, the process, and key metabolic steps are also described. Challenges associated with the development of fluxomics and its integration with 'omics' for thorough plant and organ functional phenotyping are discussed. Taken together, these will ultimately provide crucial clues for identifying appropriate target plant phenotypes for breeding.

Seed-Specific Overexpression of the Pyruvate Transporter BASS2 Increases Oil Content in Arabidopsis Seeds

Seed oil is important not only for human and animal nutrition, but also for various industrial applications. Numerous genetic engineering strategies have been attempted to increase the oil content per seed, but few of these strategies have involved manipulating the transporters. Pyruvate is a major source of carbon for de novo fatty acid biosynthesis in plastids, and the embryo's demand for pyruvate is reported to increase during active oil accumulation. In this study, we tested our hypothesis that oil biosynthesis could be boosted by increasing pyruvate flux into plastids. We expressed the known plastid-localized pyruvate transporter BILE ACID:SODIUM SYMPORTER FAMILY PROTEIN 2 (BASS2) under the control of a seed-specific soybean (Glycine max) glycinin-1 promoter in Arabidopsis thaliana. The resultant transgenic Arabidopsis plants (OEs), which expressed high levels of BASS2, produced seeds that were larger and heavier and contained 10-37% more oil than those of the wild type (WT), but were comparable to the WT seeds in terms of protein and carbohydrate contents. The total seed number did not differ significantly between the WT and OEs. Therefore, oil yield per plant was increased by 24-43% in the OE lines compared to WT. Taken together, our results demonstrate that seed-specific overexpression of the pyruvate transporter BASS2 promotes oil production in Arabidopsis seeds. Thus, manipulating the level of specific transporters is a feasible approach for increasing the seed oil content.

Evolutionary Conservation and Divergence of Gene Coexpression Networks in Gossypium (Cotton) Seeds

The cotton genus (Gossypium) provides a superior system for the study of diversification, genome evolution, polyploidization, and human-mediated selection. To gain insight into phenotypic diversification in cotton seeds, we conducted coexpression network analysis of developing seeds from diploid and allopolyploid cotton species and explored network properties. Key network modules and functional associations were identified related to seed oil content and seed weight. We compared species-specific networks to reveal topological changes, including rewired edges and differentially coexpressed genes, associated with speciation, polyploidy, and cotton domestication. Network comparisons among species indicate that topologies are altered in addition to gene expression profiles, indicating that changes in transcriptomic coexpression relationships play a role in the developmental architecture of cotton seed development. The global network topology of allopolyploids, especially for domesticated G. hirsutum, resembles the network of the A-genome diploid more than that of the D-genome parent, despite its D-like phenotype in oil content. Expression modifications associated with allopolyploidy include coexpression level dominance and transgressive expression, suggesting that the transcriptomic architecture in polyploids is to some extent a modular combination of that of its progenitor genomes. Among allopolyploids, intermodular relationships are more preserved between two different wild allopolyploid species than they are between wild and domesticated forms of a cultivated cotton, and regulatory connections of oil synthesis-related pathways are denser and more closely clustered in domesticated vs. wild G. hirsutum. These results demonstrate substantial modification of genic coexpression under domestication. Our work demonstrates how network inference informs our understanding of the transcriptomic architecture of phenotypic variation associated with temporal scales ranging from thousands (domestication) to millions (speciation) of years, and by polyploidy.

Genetic Analysis Workshop 19: methods and strategies for analyzing human sequence and gene expression data in extended families and unrelated individuals

Genetic Analysis Workshop 19 provided a platform for developing and evaluating statistical methods to analyze whole-genome sequence and gene expression data from a pedigree-based sample, as well as whole-exome sequence data from a large cohort of unrelated individuals. In this article we present an overview of the data sets, the GAW experience, and summaries of the contributions arranged into nine methodological themes.

Molecular approaches for genetic improvement of seed quality and characterization of genetic diversity in soybean: a critical review

Soybean is an economically important leguminous crop. Genetic improvements of soybeans have focused on enhancement of seed and oil yield, development of varieties suited to different cropping systems, and breeding resistant/tolerant varieties for various biotic and abiotic stresses. Plant breeders have used conventional breeding techniques for the improvement of these traits in soybean. The conventional breeding process can be greatly accelerated through the application of molecular and genomic approaches. Molecular markers have proved to be a new tool in soybean breeding by enhancing selection efficiency in a rapid and time-bound manner. An overview of molecular approaches for the genetic improvement of soybean seed quality parameters, considering recent applications of marker-assisted selection and 'omics' research, is provided in this article.

Mass Spectrometry in Plant-omics

Plant-omics is rapidly becoming an important field of study in the scientific community due to the urgent need to address many of the most important questions facing humanity today with regard to agriculture, medicine, biofuels, environmental decontamination, ecological sustainability, etc. High-performance mass spectrometry is a dominant tool for interrogating the metabolomes, peptidomes, and proteomes of a diversity of plant species under various conditions, revealing key insights into the functions and mechanisms of plant biochemistry.

A Clade-Specific Arabidopsis Gene Connects Primary Metabolism and Senescence

Nearly immobile, plants have evolved new components to be able to respond to changing environments. One example is Qua Quine Starch (QQS, AT3G30720), an Arabidopsis thaliana-specific orphan gene that integrates primary metabolism with adaptation to environment changes. SAQR (Senescence-Associated and QQS-Related, AT1G64360), is unique to a clade within the family Brassicaceae; as such, the gene may have arisen about 20 million years ago. SAQR is up-regulated in QQS RNAi mutant and in the apx1 mutant under light-induced oxidative stress. SAQR plays a role in carbon allocation: overexpression lines of SAQR have significantly decreased starch content; conversely, in a saqr T-DNA knockout (KO) line, starch accumulation is increased. Meta-analysis of public microarray data indicates that SAQR expression is correlated with expression of a subset of genes involved in senescence, defense, and stress responses. SAQR promoter::GUS expression analysis reveals that SAQR expression increases after leaf expansion and photosynthetic capacity have peaked, just prior to visible natural senescence. SAQR is expressed predominantly within leaf and cotyledon vasculature, increasing in intensity as natural senescence continues, and then decreasing prior to death. In contrast, under experimentally induced senescence, SAQR expression increases in vasculature of cotyledons but not in true leaves. In SAQR KO line, the transcript level of the dirigent-like disease resistance gene (AT1G22900) is increased, while that of the Early Light Induced Protein 1 gene (ELIP1, AT3G22840) is decreased. Taken together, these data indicate that SAQR may function in the QQS network, playing a role in integration of primary metabolism with adaptation to internal and environmental changes, specifically those that affect the process of senescence.

Mathematical models of plant metabolism

Among various modeling approaches in plant metabolic research, applications of Constraint-Based modeling are fast increasing in recent years, apparently driven by current advances in genomics and genome sequencing. Constraint-Based modeling, the functional analysis of metabolic networks at the whole cell or genome scale, is more difficult to apply to plants than to microbes. Here we discuss recent developments in Constraint-Based modeling in plants with focus on issues of model reconstruction and flux prediction. Another topic is the emerging application of integration of Constraint-Based modeling with omics data to increase predictive power. Furthermore, advances in experimental measurements of cellular fluxes by (13)C-Metabolic Flux Analysis are highlighted, including instationary (13)C-MFA used to probe autotrophic metabolism in photosynthetic tissue in the light.

QQS orphan gene regulates carbon and nitrogen partitioning across species via NF-YC interactions

The allocation of carbon and nitrogen resources to the synthesis of plant proteins, carbohydrates, and lipids is complex and under the control of many genes; much remains to be understood about this process. QQS (Qua-Quine Starch; At3g30720), an orphan gene unique to Arabidopsis thaliana, regulates metabolic processes affecting carbon and nitrogen partitioning among proteins and carbohydrates, modulating leaf and seed composition in Arabidopsis and soybean. Here the universality of QQS function in modulating carbon and nitrogen allocation is exemplified by a series of transgenic experiments. We show that ectopic expression of QQS increases soybean protein independent of the genetic background and original protein content of the cultivar. Furthermore, transgenic QQS expression increases the protein content of maize, a C4 species (a species that uses 4-carbon photosynthesis), and rice, a protein-poor agronomic crop, both highly divergent from Arabidopsis. We determine that QQS protein binds to the transcriptional regulator AtNF-YC4 (Arabidopsis nuclear factor Y, subunit C4). Overexpression of AtNF-YC4 in Arabidopsis mimics the QQS-overexpression phenotype, increasing protein and decreasing starch levels. NF-YC, a component of the NF-Y complex, is conserved across eukaryotes. The NF-YC4 homologs of soybean, rice, and maize also bind to QQS, which provides an explanation of how QQS can act in species where it does not occur endogenously. These findings are, to our knowledge, the first insight into the mechanism of action of QQS in modulating carbon and nitrogen allocation across species. They have major implications for the emergence and function of orphan genes, and identify a nontransgenic strategy for modulating protein levels in crop species, a trait of great agronomic significance.

Quantifying plant phenotypes with isotopic labeling & metabolic flux analysis

Analyses of metabolic flux using stable isotopes in plants have traditionally been restricted to tissues with presumed homogeneous cell populations and long metabolic steady states such as developing seeds, cell suspensions, or cultured roots and root tips. It is now possible to describe these and other metabolically more dynamic tissues such as leaves in greater detail using novel methods in mass spectrometry, isotope labeling strategies, and transient labeling-based flux analyses. Such studies are necessary for a systems level description of plant function that more closely represents biological reality, and provides insights into the genes that will need to be modified as natural resources become ever more limited and environments change.

Expanding Omics Resources for Improvement of Soybean Seed Composition Traits

Food resources of the modern world are strained due to the increasing population. There is an urgent need for innovative methods and approaches to augment food production. Legume seeds are major resources of human food and animal feed with their unique nutrient compositions including oil, protein, carbohydrates, and other beneficial nutrients. Recent advances in next-generation sequencing (NGS) together with "omics" technologies have considerably strengthened soybean research. The availability of well annotated soybean genome sequence along with hundreds of identified quantitative trait loci (QTL) associated with different seed traits can be used for gene discovery and molecular marker development for breeding applications. Despite the remarkable progress in these technologies, the analysis and mining of existing seed genomics data are still challenging due to the complexity of genetic inheritance, metabolic partitioning, and developmental regulations. Integration of "omics tools" is an effective strategy to discover key regulators of various seed traits. In this review, recent advances in "omics" approaches and their use in soybean seed trait investigations are presented along with the available databases and technological platforms and their applicability in the improvement of soybean. This article also highlights the use of modern breeding approaches, such as genome-wide association studies (GWAS), genomic selection (GS), and marker-assisted recurrent selection (MARS) for developing superior cultivars. A catalog of available important resources for major seed composition traits, such as seed oil, protein, carbohydrates, and yield traits are provided to improve the knowledge base and future utilization of this information in the soybean crop improvement programs.