Identifying genotype-by-environment interactions in the metabolism of germinating arabidopsis seeds using generalized genetical genomics

Screening and functional verification of drought resistance-related genes in castor bean seeds

Drought is one of the natural stresses that greatly impact plants. Castor bean (Ricinus communis L.) is an oil crop with high economic value. Drought is one of the factors limiting castor bean growth. The drought resistance mechanisms of castor bean have become a research focus. In this study, we used castor germinating embryos as experimental materials, and screened genes related to drought resistance through physiological measurements, proteomics and metabolomics joint analysis; castor drought-related genes were subjected to transient silencing expression analysis in castor leaves to validate their drought-resistant functions, and heterologous overexpression and backward complementary expression in Arabidopsis thaliana, and analysed the mechanism of the genes' response to the participation of Arabidopsis thaliana in drought-resistance.Three drought tolerance-related genes, RcECP 63, RcDDX 31 and RcA/HD1, were obtained by screening and analysis, and transient silencing of expression in castor leaves further verified that these three genes corresponded to drought stress, and heterologous overexpression and back-complementary expression of the three genes in Arabidopsis thaliana revealed that the function of these three genes in drought stress response.In this study, three drought tolerance related genes, RcECP 63, RcDDX 31 and RcA/HD1, were screened and analysed for gene function, which were found to be responsive to drought stress and to function in drought stress, laying the foundation for the study of drought tolerance mechanism in castor bean.

A guided network estimation approach using multi-omic information

INTODUCTION

In systems biology, an organism is viewed as a system of interconnected molecular entities. To understand the functioning of organisms it is essential to integrate information about the variations in the concentrations of those molecular entities. This information can be structured as a set of networks with interconnections and with some hierarchical relations between them. Few methods exist for the reconstruction of integrative networks.

OBJECTIVE

In this work, we propose an integrative network reconstruction method in which the network organization for a particular type of omics data is guided by the network structure of a related type of omics data upstream in the omic cascade. The structure of these guiding data can be either already known or be estimated from the guiding data themselves.

METHODS

The method consists of three steps. First a network structure for the guiding data should be provided. Next, responses in the target set are regressed on the full set of predictors in the guiding data with a Lasso penalty to reduce the number of predictors and an L2 penalty on the differences between coefficients for predictors that share edges in the network for the guiding data. Finally, a network is reconstructed on the fitted target responses as functions of the predictors in the guiding data. This way we condition the target network on the network of the guiding data.

CONCLUSIONS

We illustrate our approach on two examples in Arabidopsis. The method detects groups of metabolites that have a similar genetic or transcriptomic basis.

Predicting plasticity of rosette growth and metabolic fluxes in Arabidopsis thaliana

Plants can rapidly mitigate the effects of suboptimal growth environments by phenotypic plasticity of fitness-traits. While genetic variation for phenotypic plasticity offers the means for breeding climate-resilient crop lines, accurate genomic prediction models for plasticity of fitness-related traits are still lacking. Here, we employed condition- and accession-specific metabolic models for 67 Arabidopsis thaliana accessions to dissect and predict plasticity of rosette growth to changes in nitrogen availability. We showed that specific reactions in photorespiration, linking carbon and nitrogen metabolism, as well as key pathways of central carbon metabolism exhibited substantial genetic variation for flux plasticity. We also demonstrated that, in comparison with a genomic prediction model for fresh weight (FW), genomic prediction of growth plasticity improves the predictability of FW under low nitrogen by 58.9% and by additional 15.4% when further integrating data on plasticity of metabolic fluxes. Therefore, the combination of metabolic and statistical modeling provides a stepping stone in understanding the molecular mechanisms and improving the predictability of plasticity for fitness-related traits.

Exogenous Spermidine Promotes Germination of Aged Sorghum Seeds by Mediating Sugar Metabolism

Starch, a substance stored in seeds, is the main source of energy for germination in sorghum seeds. However, as the seeds age, the catabolism of seed starch is affected, thereby seriously damaging germination ability. In this study, we aimed to understand how exogenous spermidine promoted germination in aged sorghum seed. Our phenotypic analysis indicated that exogenous spermidine not only significantly improved the germination rate, germination potential, germination index, and vigor index of aged seeds, but also increased the root and shoot length after germination. Further, physiological analysis showed that exogenous spermidine increased the content of soluble sugar by upregulating the activity of amylase and sucrose invertase. Exogenous spermidine also improved the activities of key enzymes in glycolysis, the tricarboxylic acid cycle, and the pentose phosphate pathway of aged sorghum seeds. Interestingly, exogenous spermidine protected the mitochondrial structure of aged seeds, which was consistent with the increase in the respiration rate and ATP content during seed germination. Moreover, qRT-PCR analysis revealed that exogenous spermidine induced the expression of key genes related to starch and sugar metabolism in aged sorghum seeds. In conclusion, our study demonstrated that exogenous spermidine promoted aged sorghum seed germination by regulating starch and sugar metabolism.

High-throughput phenotyping of physiological traits for wheat resilience to high temperature and drought stress

Interannual and local fluctuations in wheat crop yield are mostly explained by abiotic constraints. Heatwaves and drought, which are among the top stressors, commonly co-occur, and their frequency is increasing with global climate change. High-throughput methods were optimized to phenotype wheat plants under controlled water deficit and high temperature, with the aim to identify phenotypic traits conferring adaptative stress responses. Wheat plants of 10 genotypes were grown in a fully automated plant facility under 25/18 °C day/night for 30 d, and then the temperature was increased for 7 d (38/31 °C day/night) while maintaining half of the plants well irrigated and half at 30% field capacity. Thermal and multispectral images and pot weights were registered twice daily. At the end of the experiment, key metabolites and enzyme activities from carbohydrate and antioxidant metabolism were quantified. Regression machine learning models were successfully established to predict plant biomass using image-extracted parameters. Evapotranspiration traits expressed significant genotype-environment interactions (G×E) when acclimatization to stress was continuously monitored. Consequently, transpiration efficiency was essential to maintain the balance between water-saving strategies and biomass production in wheat under water deficit and high temperature. Stress tolerance included changes in carbohydrate metabolism, particularly in the sucrolytic and glycolytic pathways, and in antioxidant metabolism. The observed genetic differences in sensitivity to high temperature and water deficit can be exploited in breeding programmes to improve wheat resilience to climate change.

Key Metabolite Differences Between Korean Pine (Pinus koraiensis) Seeds With Primary Physiological Dormancy and No-Dormancy

Pinus Koraiensis seeds have physiological dormancy. Cold stratification releases seed dormancy. The changes in metabolite profiles of dormant seeds and cold stratified seeds during shorter incubation time in a favorable condition for seed germination have been studied. However, a more-long-term detection of the changes in metabolites in dormant seeds can identify the real metabolic pathways responsible for dormancy. Metabolite composition was investigated in embryo and megagametophyte of primary physiological dormant seeds (DS) of P. Koraiensis collected at 0, 1, 2, 4, and 6 weeks of incubation and of non-primary physiological dormant seeds (NDS) sampled at 0 and 1 week of incubation, seed coat rupture stage, and radicle protrusion stage. Embryos contained higher levels of most metabolites than megagametophyte. Strong accumulation of most metabolites in DS occurred at 1 and 4 weeks of incubation. A larger reduction in the relative levels of most phosphorylated sugars and amino acids in NDS was found between 1-week-incubation and seed coat rupture stage. The relative levels of metabolites involved in carbohydrate metabolism, especially the pentose phosphate pathway (PPP) and tricarboxylic acid (TCA) cycle, were higher in the embryos of 4-week-incubated DS, but the relative contents of intermediate metabolites of most amino acid metabolism were lower compared to 1-week-incubated NDS. We suggested that the disturbed carbohydrate metabolism and amino acid metabolism in the embryos of DS after 4 weeks of incubation maybe related to primary dormancy. Our study provides information for a better understanding of the mechanism of seed dormancy.

Metabolite Profile of Xylem Sap in Cotton Seedlings Is Changed by K Deficiency

Xylem sap, belonging to the plant apoplast, not only provides plant tissues with inorganic and organic substances but also facilitates communication between the roots and the leaves and coordinates their development. This study investigated the effects of potassium (K) deficiency on the morphology and the physiology of cotton seedlings as well as pH, mineral nutrient contents, and metabolites of xylem sap. In particular, we compared changes in root-shoot communication under low K (LK) and normal K (NK, control) levels. Compared to control, LK stress significantly decreased seedling biomass (leaf, stem, and root dry weight; stem and root length; root surface area and root volume) and the levels of K, Na (sodium), Mg (magnesium), Fe (iron), and Zn (zinc) in xylem sap. A total of 82 metabolites in sap analyzed by high-performance liquid chromatography-tandem mass spectrometry (HPLC-MS/MS) showed significant differences between the two conditions; among these, 38 were up-regulated more than 2-fold, while the others were down-regulated less than 0.5-fold. In particular, several metabolites found in the cell membrane including three cholines (glycerophosphatecholine, 2-hexenylcholine, and caproylcholine) and desglucocoroloside and others such as malondialdehyde, α-amino acids and derivatives, sucrose, and sugar alcohol significantly increased under LK stress, indicating that cell membranes were damaged and protein metabolism was abnormal. It is worth noting that glycerophosphocholine was up-regulated 29-fold under LK stress, indicating that it can be used as an important signal of root-shoot communication. Furthermore, in pathway analyses, 26 metabolites were matched to Kyoto Encyclopedia of Genes and Genomes (KEGG) pathways; L-aspartic acid, which was associated with 10 KEGG pathways, was the most involved metabolite. Overall, K deficiency reduced the antioxidant capacity of cotton seedlings and led to a metabolic disorder including elevated levels of primary metabolites and inhibited production of secondary metabolites. This eventually resulted in decreased biomass of cotton seedlings under LK stress. This study lays a solid foundation for further research on targeted metabolites and signal substances in the xylem sap of cotton plants exposed to K deficiency.

Network Analysis Prioritizes DEWAX and ICE1 as the Candidate Genes for Major eQTL Hotspots in Seed Germination of Arabidopsis thaliana

Seed germination is characterized by a constant change of gene expression across different time points. These changes are related to specific processes, which eventually determine the onset of seed germination. To get a better understanding on the regulation of gene expression during seed germination, we performed a quantitative trait locus mapping of gene expression (eQTL) at four important seed germination stages (primary dormant, after-ripened, six-hour after imbibition, and radicle protrusion stage) using Arabidopsis thaliana Bay x Sha recombinant inbred lines (RILs). The mapping displayed the distinctness of the eQTL landscape for each stage. We found several eQTL hotspots across stages associated with the regulation of expression of a large number of genes. Interestingly, an eQTL hotspot on chromosome five collocates with hotspots for phenotypic and metabolic QTL in the same population. Finally, we constructed a gene co-expression network to prioritize the regulatory genes for two major eQTL hotspots. The network analysis prioritizes transcription factors DEWAX and ICE1 as the most likely regulatory genes for the hotspot. Together, we have revealed that the genetic regulation of gene expression is dynamic along the course of seed germination.

Seed quality and carbon primary metabolism

Improving seed quality is amongst the most important challenges of contemporary agriculture. In fact, using plant varieties with better germination rates that are more tolerant to stress during seedling establishment may improve crop yield considerably. Therefore, intense efforts are currently being devoted to improve seed quality in many species, mostly using genomics tools. However, despite its considerable importance during seed imbibition and germination processes, primary carbon metabolism in seeds is less studied. Our knowledge of the physiology of seed respiration and energy generation and the impact of these processes on seed performance have made limited progress over the past three decades. In particular, (isotope-assisted) metabolomics of seeds has only been assessed occasionally, and there is limited information on possible quantitative relationships between metabolic fluxes and seed quality. Here, we review the recent literature and provide an overview of potential links between metabolic efficiency, metabolic biomarkers, and seed quality and discuss implications for future research, including a climate change context.

The interaction between genotype and maternal nutritional environments affects tomato seed and seedling quality

Seed and seedling traits are affected by the conditions of the maternal environment, such as light, temperature, and nutrient availability. In this study, we have investigated whether different maternally applied nitrate and phosphate concentrations affect the seed and seedling performance of two closely related tomato species: Solanum lycopersicum cv. Money maker and Solanum pimpinellifolium accession CGN14498. We observed large differences for seed and seedling traits between the two species. Additionally, we have shown that for nitrate most of the seed and seedling traits were significantly affected by genotype-environment interactions (G×E). The effect of the maternal environment was clearly visible in the primary metabolites of the dry seeds. For example, we could show that the amount of γ-aminobutyric acid (GABA) in Money maker seeds was affected by the differences in the maternal environments and was positively correlated with seed germination under high temperature. Overall, compared with phosphate, nitrate had a larger effect on seed and seedling performance in tomato. In general, the different responses to the maternal environments of the two tomato species showed a major role for G×E in shaping seed and seedling traits.

Transcriptomic Analysis of Seed Germination Under Salt Stress in Two Desert Sister Species (Populus euphratica and P. pruinosa)

As a major abiotic stress, soil salinity limits seed germination and plant growth, development and production. Seed germination is highly related not only to the seedlings survival rate but also subsequent vegetative growth. Populus euphratica and P. pruinosa are closely related species that show a distinguished adaptability to salinity stress. In this study, we performed an integrative transcriptome analyses of three seed germination phases from P. euphratica and P. pruinosa under salt stress. A two-dimensional data set of this study provides a comprehensive view of the dynamic biochemical processes that underpin seed germination and salt tolerance. Our analysis identified 12831 differentially expressed genes (DEGs) for seed germination processes and 8071 DEGs for salt tolerance in the two species. Furthermore, we identified the expression profiles and main pathways in each growth phase. For seed germination, a large number of DEGs, including those involved in energy production and hormonal regulation pathways, were transiently and specifically induced in the late phase. In the comparison of salt tolerance between the two species, the flavonoid and brassinosteroid pathways were significantly enriched. More specifically, in the flavonoid pathway, FLS and F3'5'H exhibited significant differential expression. In the brassinosteroid pathway, the expression levels of DWF4, BR6OX2 and ROT3 were notably higher in P. pruinosa than in P. euphratica. Our results describe transcript dynamics and highlight secondary metabolite pathways involved in the response to salt stress during the seed germination of two desert poplars.

Proteomic analysis of tree peony (Paeonia ostii 'Feng Dan') seed germination affected by low temperature

Seed germination is a critical process that is influenced by various factors. In the present study, the effect of low temperature (4 °C) on tree peony seed germination was investigated. Compared to seeds maintained at 25 °C, germination was inhibited when seeds were kept at 4 °C. Furthermore, low-temperature exposure of seeds resulted in a delay in water uptake, starch degradation, and soluble sugar consumption and a subsequent increase in soluble protein levels. Two-dimensional gel electrophoresis (2-DE) proteomic analysis identified 100 protein spots. Comparative analysis indicated that low-temperature exposure apparently mainly affected glycolysis and the tricarboxylic acid (TCA) cycle, while also significantly affecting proteometabolism-related factors. Moreover, low-temperature exposure led to the induction of abscisic acid, whereas the gibberellin pathway was not affected. Further comparison of the two temperature conditions showed that low-temperature exposure delays carbohydrate metabolism, adenosine triphosphate (ATP) production, respiration, and proteolysis and increases defense response factors. To further examine the obtained proteomic findings, four genes were evaluated by quantitative polymerase chain reaction (qPCR). The obtained transcriptional results for the GAPC gene coincided with the translational results, thus further suggesting that the delay in glycolysis may play a key role in low-temperature-induced inhibition of seed germination. However, the other three genes examined, which included FPP synthase, PCNT115, and endochitinase, showed non-correlative transcriptional and translational profiles. Our results suggest that the exposure of tree peony seeds to low temperature results in a delay in the degradation of starch and other metabolites, which in turn affects glycolysis and some other processes, thereby ultimately inhibiting seed germination.

Dormancy release and germination of Taxus yunnanensis seeds during wet sand storage

Dormancy is an innate constraint on germination that occurs across all life forms. In this study, we investigated the seed dormancy release and germination characters of Taxus yunnanensis by exploring the seed morphology, permeability, germination inhibitors, endogenous hormones, and embryo germination in vitro during wet sand storage. Our results showed that seeds and embryos grew to a critical size to germination and permeability increased with the extension of storage. Seed coat and kernel methanol extracts reduced Brassica campestris seed vigor index. The in vitro embryo germination rate increased by 12.20% after storage for 30–360 d, whereas seed germination occurred after 450 d. Gibberellic acid and zeatin riboside contents were relatively stable, whereas abscisic acid (ABA) content decreased; indole acetic acid (IAA) content and the IAA/ABA ratio showed increasing trends. These results indicate that ABA is the key inhibitor of germination in Taxus. The chemical(s) in seed coat and kernel cause the inhibition of seed germination. Taken together, Taxus seeds have morphophysiological dormancy, in which the embryos can continue to grow and hormone imbalance inhibits further development and germination. Further, seed dormancy is active even during the middle of storage and shows “double peaks” during the entire dormancy process.

Metabolite profiling and associated gene expression reveal two metabolic shifts during the seed-to-seedling transition in Arabidopsis thaliana

Metabolic and transcriptomic correlation analysis identified two distinctive profiles involved in the metabolic preparation for seed germination and seedling establishment, respectively. Transcripts were identified that may control metabolic fluxes. The transition from a quiescent metabolic state (dry seed) to the active state of a vigorous seedling is crucial in the plant's life cycle. We analysed this complex physiological trait by measuring the changes in primary metabolism that occur during the transition in order to determine which metabolic networks are operational. The transition involves several developmental stages from seed germination to seedling establishment, i.e. between imbibition of the mature dry seed and opening of the cotyledons, the final stage of seedling establishment. We hypothesized that the advancement of growth is associated with certain signature metabolite profiles. Metabolite-metabolite correlation analysis underlined two specific profiles which appear to be involved in the metabolic preparation for seed germination and efficient seedling establishment, respectively. Metabolite profiles were also compared to transcript profiles and although transcriptional changes did not always equate to a proportional metabolic response, in depth correlation analysis identified several transcripts that may directly influence the flux through metabolic pathways during the seed-to-seedling transition. This correlation analysis also pinpointed metabolic pathways which are significant for the seed-to-seedling transition, and metabolite contents that appeared to be controlled directly by transcript abundance. This global view of the transcriptional and metabolic changes during the seed-to-seedling transition in Arabidopsis opens up new perspectives for understanding the complex regulatory mechanism underlying this transition.

Differentially expressed genes during the imbibition of dormant and after-ripened seeds - a reverse genetics approach

BACKGROUND

Seed dormancy, defined as the incapability of a viable seed to germinate under favourable conditions, is an important trait in nature and agriculture. Despite extensive research on dormancy and germination, many questions about the molecular mechanisms controlling these traits remain unanswered, likely due to its genetic complexity and the large environmental effects which are characteristic of these quantitative traits. To boost research towards revealing mechanisms in the control of seed dormancy and germination we depend on the identification of genes controlling those traits.

METHODS

We used transcriptome analysis combined with a reverse genetics approach to identify genes that are prominent for dormancy maintenance and germination in imbibed seeds of Arabidopsis thaliana. Comparative transcriptomics analysis was employed on freshly harvested (dormant) and after-ripened (AR; non-dormant) 24-h imbibed seeds of four different DELAY OF GERMINATION near isogenic lines (DOGNILs) and the Landsberg erecta (Ler) wild type with varying levels of primary dormancy. T-DNA knock-out lines of the identified genes were phenotypically investigated for their effect on dormancy and AR.

RESULTS

We identified conserved sets of 46 and 25 genes which displayed higher expression in seeds of all dormant and all after-ripened DOGNILs and Ler, respectively. Knock-out mutants in these genes showed dormancy and germination related phenotypes.

CONCLUSIONS

Most of the identified genes had not been implicated in seed dormancy or germination. This research will be useful to further decipher the molecular mechanisms by which these important ecological and commercial traits are regulated.

Genetic dissection of metabolite variation in Arabidopsis seeds: evidence for mQTL hotspots and a master regulatory locus of seed metabolism

To gain insight into genetic factors controlling seed metabolic composition and its relationship to major seed properties, an Arabidopsis recombinant inbred line (RIL) population, derived from accessions Col-0 and C24, was studied using an MS-based metabolic profiling approach. Relative intensities of 311 polar primary metabolites were used to identify associated genomic loci and to elucidate their interactions by quantitative trait locus (QTL) mapping. A total of 786 metabolic QTLs (mQTLs) were unequally distributed across the genome, forming several hotspots. For the branched-chain amino acid leucine, mQTLs and candidate genes were elucidated in detail. Correlation studies displayed links between metabolite levels, seed protein content, and seed weight. Principal component analysis revealed a clustering of samples, with PC1 mapping to a region on the short arm of chromosome IV. The overlap of this region with mQTL hotspots indicates the presence of a potential master regulatory locus of seed metabolism. As a result of database queries, a series of candidate regulatory genes, including bZIP10, were identified within this region. Depending on the search conditions, metabolic pathway-derived candidate genes for 40-61% of tested mQTLs could be determined, providing an extensive basis for further identification and characterization of hitherto unknown genes causal for natural variation of Arabidopsis seed metabolism.

AraQTL - workbench and archive for systems genetics in Arabidopsis thaliana

Genetical genomics studies uncover genome-wide genetic interactions between genes and their transcriptional regulators. High-throughput measurement of gene expression in recombinant inbred line populations has enabled investigation of the genetic architecture of variation in gene expression. This has the potential to enrich our understanding of the molecular mechanisms affected by and underlying natural variation. Moreover, it contributes to the systems biology of natural variation, as a substantial number of experiments have resulted in a valuable amount of interconnectable phenotypic, molecular and genotypic data. A number of genetical genomics studies have been published for Arabidopsis thaliana, uncovering many expression quantitative trait loci (eQTLs). However, these complex data are not easily accessible to the plant research community, leaving most of the valuable genetic interactions unexplored as cross-analysis of these studies is a major effort. We address this problem with AraQTL (http://www.bioinformatics.nl/Ara QTL/), an easily accessible workbench and database for comparative analysis and meta-analysis of all published Arabidopsis eQTL datasets. AraQTL provides a workbench for comparing, re-using and extending upon the results of these experiments. For example, one can easily screen a physical region for specific local eQTLs that could harbour candidate genes for phenotypic QTLs, or detect gene-by-environment interactions by comparing eQTLs under different conditions.

Network-Guided GWAS Improves Identification of Genes Affecting Free Amino Acids

Amino acids are essential for proper growth and development in plants. Amino acids serve as building blocks for proteins but also are important for responses to stress and the biosynthesis of numerous essential compounds. In seed, the pool of free amino acids (FAAs) also contributes to alternative energy, desiccation, and seed vigor; thus, manipulating FAA levels can significantly impact a seed's nutritional qualities. While genome-wide association studies (GWAS) on branched-chain amino acids have identified some regulatory genes controlling seed FAAs, the genetic regulation of FAA levels, composition, and homeostasis in seeds remains mostly unresolved. Hence, we performed GWAS on 18 FAAs from a 313-ecotype Arabidopsis (Arabidopsis thaliana) association panel. Specifically, GWAS was performed on 98 traits derived from known amino acid metabolic pathways (approach 1) and then on 92 traits generated from an unbiased correlation-based metabolic network analysis (approach 2), and the results were compared. The latter approach facilitated the discovery of additional novel metabolic interactions and single-nucleotide polymorphism-trait associations not identified by the former approach. The most prominent network-guided GWAS signal was for a histidine (His)-related trait in a region containing two genes: a cationic amino acid transporter (CAT4) and a polynucleotide phosphorylase resistant to inhibition with fosmidomycin. A reverse genetics approach confirmed CAT4 to be responsible for the natural variation of His-related traits across the association panel. Given that His is a semiessential amino acid and a potent metal chelator, CAT4 orthologs could be considered as candidate genes for seed quality biofortification in crop plants.

Metabolomic analysis of tomato seed germination

INTRODUCTION

Seed germination is inherently related to seed metabolism, which changes throughout its maturation, desiccation and germination processes. The metabolite content of a seed and its ability to germinate are determined by underlying genetic architecture and environmental effects during development.

OBJECTIVE

This study aimed to assess an integrative approach to explore genetics modulating seed metabolism in different developmental stages and the link between seed metabolic- and germination traits.

METHODS

We have utilized gas chromatography-time-of-flight/mass spectrometry (GC-TOF/MS) metabolite profiling to characterize tomato seeds during dry and imbibed stages. We describe, for the first time in tomato, the use of a so-called generalized genetical genomics (GGG) model to study the interaction between genetics, environment and seed metabolism using 100 tomato recombinant inbred lines (RILs) derived from a cross between Solanum lycopersicum and Solanum pimpinellifolium.

RESULTS

QTLs were found for over two-thirds of the metabolites within several QTL hotspots. The transition from dry to 6 h imbibed seeds was associated with programmed metabolic switches. Significant correlations varied among individual metabolites and the obtained clusters were significantly enriched for metabolites involved in specific biochemical pathways.

CONCLUSIONS

Extensive genetic variation in metabolite abundance was uncovered. Numerous identified genetic regions that coordinate groups of metabolites were detected and these will contain plausible candidate genes. The combined analysis of germination phenotypes and metabolite profiles provides a strong indication for the hypothesis that metabolic composition is related to germination phenotypes and thus to seed performance.

Bulked sample analysis in genetics, genomics and crop improvement

Biological assay has been based on analysis of all individuals collected from sample populations. Bulked sample analysis (BSA), which works with selected and pooled individuals, has been extensively used in gene mapping through bulked segregant analysis with biparental populations, mapping by sequencing with major gene mutants and pooled genomewide association study using extreme variants. Compared to conventional entire population analysis, BSA significantly reduces the scale and cost by simplifying the procedure. The bulks can be built by selection of extremes or representative samples from any populations and all types of segregants and variants that represent wide ranges of phenotypic variation for the target trait. Methods and procedures for sampling, bulking and multiplexing are described. The samples can be analysed using individual markers, microarrays and high-throughput sequencing at all levels of DNA, RNA and protein. The power of BSA is affected by population size, selection of extreme individuals, sequencing strategies, genetic architecture of the trait and marker density. BSA will facilitate plant breeding through development of diagnostic and constitutive markers, agronomic genomics, marker-assisted selection and selective phenotyping. Applications of BSA in genetics, genomics and crop improvement are discussed with their future perspectives.

Proteomics analysis reveals distinct involvement of embryo and endosperm proteins during seed germination in dormant and non-dormant rice seeds

Seed germination is a complex trait which is influenced by many genetic, endogenous and environmental factors, but the key event(s) associated with seed germination are still poorly understood. In present study, the non-dormant cultivated rice Yannong S and the dormant Dongxiang wild rice seeds were used as experimental materials, we comparatively investigated the water uptake, germination time course, and the differential proteome of the effect of embryo and endosperm on germination of these two types of seeds. A total of 231 and 180 protein spots in embryo and endosperm, respectively, showed a significant change in abundance during germination. We observed that the important proteins associated with seed germination included those involved in metabolism, energy production, protein synthesis and destination, storage protein, cell growth and division, signal transduction, cell defense and rescue. The contribution of embryo and endosperm to seed germination is different. In embryo, the proteins involved in amino acid activation, sucrose cleavage, glycolysis, fermentation and protein synthesis increased; in endosperm, the proteins involved in sucrose cleavage and glycolysis decreased, and those with ATP and CoQ synthesis and proteolysis increased. Our results provide some new knowledge to understand further the mechanism of seed germination.

Galactinol as marker for seed longevity

Reduced seed longevity or storability is a major problem in seed storage and contributes to increased costs in crop production. Here we investigated whether seed galactinol contents could be predictive for seed storability behavior in Arabidopsis, cabbage and tomato. The analyses revealed a positive correlation between galactinol content and seed longevity in the three species tested, which indicates that this correlation is conserved in the Brassicaceae and beyond. Quantitative trait loci (QTL) mapping in tomato revealed a co-locating QTL for galactinol content and seed longevity on chromosome 2. A candidate for this QTL is the GALACTINOL SYNTHASE gene (Solyc02g084980.2.1) that is located in the QTL interval. GALACTINOL SYNTHASE is a key enzyme of the raffinose family oligosaccharide (RFO) pathway. To investigate the role of enzymes in the RFO pathway in more detail, we applied a reverse genetics approach using T-DNA knock-out lines in genes encoding enzymes of this pathway (GALACTINOL SYNTHASE 1, GALACTINOL SYNTHASE 2, RAFFINOSE SYNTHASE, STACHYOSE SYNTHASE and ALPHA-GALACTOSIDASE) and overexpressors of the cucumber GALACTINOL SYNTHASE 2 gene in Arabidopsis. The galactinol synthase 2 mutant and the galactinol synthase 1 galactinol synthase 2 double mutant contained the lowest seed galactinol content which coincided with lower seed longevity. These results show that galactinol content of mature dry seed can be used as a biomarker for seed longevity in Brassicaceae and tomato.

Seed vigour and crop establishment: extending performance beyond adaptation

Seeds are central to crop production, human nutrition, and food security. A key component of the performance of crop seeds is the complex trait of seed vigour. Crop yield and resource use efficiency depend on successful plant establishment in the field, and it is the vigour of seeds that defines their ability to germinate and establish seedlings rapidly, uniformly, and robustly across diverse environmental conditions. Improving vigour to enhance the critical and yield-defining stage of crop establishment remains a primary objective of the agricultural industry and the seed/breeding companies that support it. Our knowledge of the regulation of seed germination has developed greatly in recent times, yet understanding of the basis of variation in vigour and therefore seed performance during the establishment of crops remains limited. Here we consider seed vigour at an ecophysiological, molecular, and biomechanical level. We discuss how some seed characteristics that serve as adaptive responses to the natural environment are not suitable for agriculture. Past domestication has provided incremental improvements, but further actively directed change is required to produce seeds with the characteristics required both now and in the future. We discuss ways in which basic plant science could be applied to enhance seed performance in crop production.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

The Arabidopsis MYB96 Transcription Factor Is a Positive Regulator of ABSCISIC ACID-INSENSITIVE4 in the Control of Seed Germination

Seed germination is a key developmental transition that initiates the plant life cycle. The timing of germination is determined by the coordinated action of two phytohormones, gibberellin and abscisic acid (ABA). In particular, ABA plays a key role in integrating environmental information and inhibiting the germination process. The utilization of embryonic lipid reserves contributes to seed germination by acting as an energy source, and ABA suppresses lipid degradation to modulate the germination process. Here, we report that the ABA-responsive R2R3-type MYB transcription factor MYB96, which is highly expressed in embryo, regulates seed germination by controlling the expression of abscisic acid-insensitive4 (ABI4) in Arabidopsis (Arabidopsis thaliana). In the presence of ABA, germination was accelerated in MYB96-deficient myb96-1 seeds, whereas the process was significantly delayed in MYB96-overexpressing activation-tagging myb96-ox seeds. Consistently, myb96-1 seeds degraded a larger extent of lipid reserves even in the presence of ABA, while reduced lipid mobilization was observed in myb96-ox seeds. MYB96 directly regulates ABI4, which acts as a repressor of lipid breakdown, to define its spatial and temporal expression. Genetic analysis further demonstrated that ABI4 is epistatic to MYB96 in the control of seed germination. Taken together, the MYB96-ABI4 module regulates lipid mobilization specifically in the embryo to ensure proper seed germination under suboptimal conditions.

Metabolic patterns associated with the seasonal rhythm of seed survival after dehydration in germinated seeds of Schismus arabicus

BACKGROUND

Seed of Shismus arabicus, a desert annual, display a seasonal tolerance to dehydration. The occurrence of a metabolic seasonal rhythm and its relation with the fluctuations in seed dehydration tolerance was investigated.

RESULTS

Dry seeds metabolism was the least affected by the season, while the metabolism of germinated and dehydrated seeds exhibit distinct seasonal patterns. Negative associations exist between amino acids, sugars and TCA cycle intermediates and seed survival, while positive relations exist with seed germination. In contrast, associations between the level of secondary metabolites identified in the dehydrated seeds and survival percentage were evenly distributed in positive and negative values, suggesting a functional role of these metabolites in the establishment of seed dehydration tolerance.

CONCLUSION

Our results indicate the occurrence of metabolic biorhythms in germinating and dehydrating seeds associated with seasonal changes in germination and, more pronouncedly, in seed dehydration tolerance. Increased biosynthesis of protective compounds (polyphenols) in dehydrating seeds during the winter season at the expenses of central metabolites likely contributes to the respective enhanced dehydration tolerance monitored.

Advanced phenotyping and phenotype data analysis for the study of plant growth and development

Due to an increase in the consumption of food, feed, fuel and to meet global food security needs for the rapidly growing human population, there is a necessity to breed high yielding crops that can adapt to the future climate changes, particularly in developing countries. To solve these global challenges, novel approaches are required to identify quantitative phenotypes and to explain the genetic basis of agriculturally important traits. These advances will facilitate the screening of germplasm with high performance characteristics in resource-limited environments. Recently, plant phenomics has offered and integrated a suite of new technologies, and we are on a path to improve the description of complex plant phenotypes. High-throughput phenotyping platforms have also been developed that capture phenotype data from plants in a non-destructive manner. In this review, we discuss recent developments of high-throughput plant phenotyping infrastructure including imaging techniques and corresponding principles for phenotype data analysis.

Dissecting the phenotypic components of crop plant growth and drought responses based on high-throughput image analysis

Significantly improved crop varieties are urgently needed to feed the rapidly growing human population under changing climates. While genome sequence information and excellent genomic tools are in place for major crop species, the systematic quantification of phenotypic traits or components thereof in a high-throughput fashion remains an enormous challenge. In order to help bridge the genotype to phenotype gap, we developed a comprehensive framework for high-throughput phenotype data analysis in plants, which enables the extraction of an extensive list of phenotypic traits from nondestructive plant imaging over time. As a proof of concept, we investigated the phenotypic components of the drought responses of 18 different barley (Hordeum vulgare) cultivars during vegetative growth. We analyzed dynamic properties of trait expression over growth time based on 54 representative phenotypic features. The data are highly valuable to understand plant development and to further quantify growth and crop performance features. We tested various growth models to predict plant biomass accumulation and identified several relevant parameters that support biological interpretation of plant growth and stress tolerance. These image-based traits and model-derived parameters are promising for subsequent genetic mapping to uncover the genetic basis of complex agronomic traits. Taken together, we anticipate that the analytical framework and analysis results presented here will be useful to advance our views of phenotypic trait components underlying plant development and their responses to environmental cues.

A new method to infer causal phenotype networks using QTL and phenotypic information

In the context of genetics and breeding research on multiple phenotypic traits, reconstructing the directional or causal structure between phenotypic traits is a prerequisite for quantifying the effects of genetic interventions on the traits. Current approaches mainly exploit the genetic effects at quantitative trait loci (QTLs) to learn about causal relationships among phenotypic traits. A requirement for using these approaches is that at least one unique QTL has been identified for each trait studied. However, in practice, especially for molecular phenotypes such as metabolites, this prerequisite is often not met due to limited sample sizes, high noise levels and small QTL effects. Here, we present a novel heuristic search algorithm called the QTL+phenotype supervised orientation (QPSO) algorithm to infer causal directions for edges in undirected phenotype networks. The two main advantages of this algorithm are: first, it does not require QTLs for each and every trait; second, it takes into account associated phenotypic interactions in addition to detected QTLs when orienting undirected edges between traits. We evaluate and compare the performance of QPSO with another state-of-the-art approach, the QTL-directed dependency graph (QDG) algorithm. Simulation results show that our method has broader applicability and leads to more accurate overall orientations. We also illustrate our method with a real-life example involving 24 metabolites and a few major QTLs measured on an association panel of 93 tomato cultivars. Matlab source code implementing the proposed algorithm is freely available upon request.

Physiological and biochemical responses of Ricinus communis seedlings to different temperatures: a metabolomics approach

BACKGROUND

Compared with major crops, growth and development of Ricinus communis is still poorly understood. A better understanding of the biochemical and physiological aspects of germination and seedling growth is crucial for the breeding of high yielding varieties adapted to various growing environments. In this context, we analysed the effect of temperature on growth of young R. communis seedlings and we measured primary and secondary metabolites in roots and cotyledons. Three genotypes, recommended to small family farms as cash crop, were used in this study.

RESULTS

Seedling biomass was strongly affected by the temperature, with the lowest total biomass observed at 20°C. The response in terms of biomass production for the genotype MPA11 was clearly different from the other two genotypes: genotype MPA11 produced heavier seedlings at all temperatures but the root biomass of this genotype decreased with increasing temperature, reaching the lowest value at 35°C. In contrast, root biomass of genotypes MPB01 and IAC80 was not affected by temperature, suggesting that the roots of these genotypes are less sensitive to changes in temperature. In addition, an increasing temperature decreased the root to shoot ratio, which suggests that biomass allocation between below- and above ground parts of the plants was strongly affected by the temperature. Carbohydrate contents were reduced in response to increasing temperature in both roots and cotyledons, whereas amino acids accumulated to higher contents. Our results show that a specific balance between amino acids, carbohydrates and organic acids in the cotyledons and roots seems to be an important trait for faster and more efficient growth of genotype MPA11.

CONCLUSIONS

An increase in temperature triggers the mobilization of carbohydrates to support the preferred growth of the aerial parts, at the expense of the roots. A shift in the carbon-nitrogen metabolism towards the accumulation of nitrogen-containing compounds seems to be the main biochemical response to support growth at higher temperatures. The biochemical changes observed in response to the increasing temperature provide leads into understanding plant adaptation to harsh environmental conditions, which will be very helpful in developing strategies for R. communis crop improvement research.

Genotype×environment interaction QTL mapping in plants: lessons from Arabidopsis

Plant growth and development are influenced by the genetic composition of the plant (G), the environment (E), and the interaction between them (G×E). To produce suitable genotypes for multiple environments, G×E should be accounted for and assessed in plant-breeding programs. Here, we review the genetic basis of G×E and its consequence for quantitative trait loci (QTL) mapping in biparental and genome-wide association (GWA) mapping populations. We also consider the implications of G×E for understanding plant fitness trade-offs and evolutionary ecology.

Genetic architecture of naturally occurring quantitative traits in plants: an updated synthesis

Deciphering the genetic and molecular bases of quantitative variation is a long-standing challenge in plant biology because it is essential for understanding evolution and for accelerating plant breeding. Recent multi-trait analyses at different phenotypic levels are uncovering the pleiotropy and the genetic regulation underlying high-level complex traits. Thus, the number of known causal loci, genes and nucleotide polymorphisms is expanding. Current plant causal catalogs contain ∼400 genes and natural polymorphisms revealing several dysfunctional allelic series that involve multiple mutations. In addition, repeated evolution of quantitative traits mediated by large effect alleles is found across plant phylogeny. Finally, systematic analyses of genetic and environmental interactions are beginning to elucidate the molecular mechanisms of relevant interactions.

Orchestration of plant defense systems: genes to populations

Research over the past decades has made immense progress in identifying some genes and mechanisms underlying plant defense against biotic organisms. The recent movement towards systems biology approaches has increased mechanistic knowledge, revealing a need for understanding how all the genes and mechanisms integrate to create a response to any given biotic interaction. This begins with evidence that diverse molecular patterns converge, suggesting that the plant perceives signals not the interacting species. These signals then coordinate across regulatory networks via molecular interactions and cause non-cell autonomous responses in neighboring and systemic cells. Finally, the identification of transporters is showing that plant defenses are harmonized across tissues and even show the potential for coordination across individuals within a population.

Exploring the Arabidopsis sulfur metabolome

Sulfur plays a crucial role in protein structure and function, redox status and plant biotic stress responses. However, our understanding of sulfur metabolism is limited to identified pathways. In this study, we used a high-resolution Fourier transform mass spectrometric approach in combination with stable isotope labeling to describe the sulfur metabolome of Arabidopsis thaliana. Databases contain roughly 300 sulfur compounds assigned to Arabidopsis. In comparative analyses, we showed that the overlap of the expected sulfur metabolome and the mass spectrometric data was surprisingly low, and we were able to assign only 37 of the 300 predicted compounds. By contrast, we identified approximately 140 sulfur metabolites that have not been assigned to the databases to date. We used our method to characterize the γ-glutamyl transferase mutant ggt4-1, which is involved in the vacuolar breakdown of glutathione conjugates in detoxification reactions. Although xenobiotic substrates are well known, only a few endogenous substrates have been described. Among the specifically altered sulfur-containing masses in the ggt4-1 mutant, we characterized one endogenous glutathione conjugate and a number of further candidates for endogenous substrates. The small percentage of predicted compounds and the high proportion of unassigned sulfur compounds identified in this study emphasize the need to re-evaluate our understanding of the sulfur metabolome.