Camilla B. Hill

Whole genome mapping of agronomic and metabolic traits to identify novel quantitative trait loci in bread wheat grown in a water-limited environment

Comparison of the agronomic and metabolic trait variation between drought-sensitive and drought-tolerant wheat crosses uncovers novel correlations between agronomic traits and the levels of certain metabolites as well as important regions on the wheat genome that require further investigation. Drought is a major environmental constraint responsible for grain yield losses of bread wheat (Triticum aestivum) in many parts of the world. Progress in breeding to improve complex multigene traits, such as drought stress tolerance, has been limited by high sensitivity to environmental factors, low trait heritability, and the complexity and size of the hexaploid wheat genome. In order to obtain further insight into genetic factors that affect yield under drought, we measured the abundance of 205 metabolites in flag leaf tissue sampled from plants of 179 cv Excalibur/Kukri F1-derived doubled haploid lines of wheat grown in a field experiment that experienced terminal drought stress. Additionally, data on 29 agronomic traits that had been assessed in the same field experiment were used. A linear mixed model was used to partition and account for nongenetic and genetic sources of variation, and quantitative trait locus analysis was used to estimate the genomic positions and effects of individual quantitative trait loci. Comparison of the agronomic and metabolic trait variation uncovered novel correlations between some agronomic traits and the levels of certain primary metabolites, including metabolites with either positive or negative associations with plant maturity-related or grain yield-related traits. Our analyses demonstrate that specific regions of the wheat genome that affect agronomic traits also have distinct effects on specific combinations of metabolites. This approach proved valuable for identifying novel biomarkers for the performance of wheat under drought and could facilitate the identification of candidate genes involved in drought-related responses in bread wheat.

Detection of QTL for metabolic and agronomic traits in wheat with adjustments for variation at genetic loci that affect plant phenology

Mapping of quantitative trait loci associated with levels of individual metabolites (mQTL) was combined with the mapping of agronomic traits to investigate the genetic basis of variation and co-variation in metabolites, agronomic traits, and plant phenology in a field-grown bread wheat population. Metabolome analysis was performed using liquid chromatography-mass spectrometry resulting in identification of mainly polar compounds, including secondary metabolites. A total of 558 metabolic features were obtained from the flag leaves of 179 doubled haploid lines, of which 197 features were putatively identified, mostly as alkaloids, flavonoids and phenylpropanoids. Coordinated genetic control was observed for several groups of metabolites, such as organic acids influenced by two loci on chromosome 7A. Five major phenology-related loci, which were introduced as cofactors in the analyses, differed in their impact upon metabolic and agronomic traits with QZad-aww-7A having more impact on the expression of both metabolite and agronomic QTL than Ppd-B1, Vrn-A1, Eps, and QZad-aww-7D. This QTL study validates the utility of combining agronomic and metabolomic traits as an approach to identify potential trait enhancement targets for breeding selection and reinforces previous results that demonstrate the importance of including plant phenology in the assessment of useful traits in this wheat mapping population.

Characterization of Ion Contents and Metabolic Responses to Salt Stress of Different Arabidopsis AtHKT1;1 Genotypes and Their Parental Strains

Plants employ several strategies to maintain cellular ion homeostasis under salinity stress, including mediating ion fluxes by transmembrane transport proteins and adjusting osmotic pressure by accumulating osmolytes. The HKT (high-affinity potassium transporter) gene family comprises Na(+) and Na(+)/K(+) transporters in diverse plant species, with HKT1;1 as the only member in Arabidopsis thaliana. Cell-type-specific overexpression of AtHKT1;1 has been shown to prevent shoot Na(+) overaccumulation under salinity stress. Here, we analyzed a broad range of metabolites and elements in shoots and roots of different AtHKT1;1 genotypes and their parental strains before and after salinity stress, revealing a reciprocal relationship of metabolite differences between an AtHKT1;1 knockout line (hkt1;1) and the AtHKT1;1 overexpressing lines (E2586 UAS GAL4 :HKT1;1 and J2731*UAS GAL4 :HKT1;1). Although levels of root sugars were increased after salt stress in both AtHKT1;1 overexpressing lines, E2586 UAS GAL4 :HKT1;1 showed higher accumulation of the osmoprotectants trehalose, gentiobiose, and melibiose, whereas J2731*UAS GAL4 :HKT1;1 showed higher levels of sucrose and raffinose, compared with their parental lines, respectively. In contrast, the knockout line hkt1;1 showed strong increases in the levels of the tricarboxylic acid (TCA) cycle intermediates in the shoots after salt treatment. This coincided with a significant depletion of sugars, suggesting that there is an increased rate of carbon influx into the TCA cycle at a constant rate of C-efflux from the cycle, which might be needed to support plant survival during salt stress. Using correlation analysis, we identified associations between the Na(+) content and several sugars, suggesting that regulation of sugar metabolism is important in plant responses to salinity stress.

Cell-type specific H+-ATPase activity enables root K+ retention and mediates acclimation to salinity

The differential sensitivity of various root tissues to salt stress is not related to their ability to exclude or sequester sodium but rather is determined by the differences in their ability to retain potassium. While the importance of cell type specificity in plant adaptive responses is widely accepted, only a limited number of studies have addressed this issue at the functional level. We have combined electrophysiological, imaging, and biochemical techniques to reveal the physiological mechanisms conferring higher sensitivity of apical root cells to salinity in barley (Hordeum vulgare). We show that salinity application to the root apex arrests root growth in a highly tissue- and treatment-specific manner. Although salinity-induced transient net Na+ uptake was about 4-fold higher in the root apex compared with the mature zone, mature root cells accumulated more cytosolic and vacuolar Na+, suggesting that the higher sensitivity of apical cells to salt is not related to either enhanced Na+ exclusion or sequestration inside the root. Rather, the above differential sensitivity between the two zones originates from a 10-fold difference in K+ efflux between the mature zone and the apical region (much poorer in the root apex) of the root. Major factors contributing to this poor K+ retention ability are (1) an intrinsically lower H+-ATPase activity in the root apex, (2) greater salt-induced membrane depolarization, and (3) a higher reactive oxygen species production under NaCl and a larger density of reactive oxygen species-activated cation currents in the apex. Salinity treatment increased (2- to 5-fold) the content of 10 (out of 25 detected) amino acids in the root apex but not in the mature zone and changed the organic acid and sugar contents. The causal link between the observed changes in the root metabolic profile and the regulation of transporter activity is discussed.

De novo transcriptome assembly and analysis of differentially expressed genes of two barley genotypes reveal root-zone-specific responses to salt exposure

Plant roots are the first organs sensing and responding to salinity stress, manifested differentially between different root types, and also at the individual tissue and cellular level. High genetic diversity and the current lack of an assembled map-based sequence of the barley genome severely limit barley research potential. We used over 580 and 600 million paired-end reads, respectively, to create two de novo assemblies of a barley landrace (Sahara) and a malting cultivar (Clipper) with known contrasting responses to salinity. Generalized linear models were used to statistically access spatial, treatment-related, and genotype-specific responses. This revealed a spatial gene expression gradient along the barley root, with more differentially expressed transcripts detected between different root zones than between treatments. The root transcriptome also showed a gradual transition from transcripts related to sugar-mediated signaling at the root meristematic zone to those involved in cell wall metabolism in the elongation zone, and defense response-related pathways toward the maturation zone, with significant differences between the two genotypes. The availability of these additional transcriptome reference sets will serve as a valuable resource to the cereal research community, and may identify valuable traits to assist in breeding programmes.

Salt-stress induced alterations in the root lipidome of two barley genotypes with contrasting responses to salinity

Changes in lipid metabolism and composition as well as in distinct lipid species have been linked with altered plant growth, development and responses to environmental stresses including salinity. However, there is little information available in the literature focusing on lipids in roots under soil-related stresses such as salinity. Barley (Hordeum vulgare L.) is a major cereal grain and, as a glycophyte, suffers substantial yield loss when grown under saline conditions. Relatively little is understood of adaptation and tolerance mechanisms involving lipids and lipid metabolism in barley roots during development and under exposure to salinity stress. In this study we investigated the lipid composition of barley roots of Clipper and Sahara - two genotypes with contrasting responses to salinity - before and after salinity stress using a combination of three lipidomics techniques: Fatty acid compositional analysis, untargeted lipid profiling, and targeted analysis to profile quantitatively the individual molecular species of key plant lipid classes. Our results provide new insight into the effect of salinity on fatty acid profiles and key lipid classes within barley roots of two different genotypes, which is discussed in the context of current knowledge of the root metabolic responses of cereal crops to salinity stress.

A Quantitative Profiling Method of Phytohormones and Other Metabolites Applied to Barley Roots Subjected to Salinity Stress

As integral parts of plant signaling networks, phytohormones are involved in the regulation of plant metabolism and growth under adverse environmental conditions, including salinity. Globally, salinity is one of the most severe abiotic stressors with an estimated 800 million hectares of arable land affected. Roots are the first plant organ to sense salinity in the soil, and are the initial site of sodium (Na+) exposure. However, the quantification of phytohormones in roots is challenging, as they are often present at extremely low levels compared to other plant tissues. To overcome this challenge, we developed a high-throughput LC-MS method to quantify ten endogenous phytohormones and their metabolites of diverse chemical classes in roots of barley. This method was validated in a salinity stress experiment with six barley varieties grown hydroponically with and without salinity. In addition to phytohormones, we quantified 52 polar primary metabolites, including some phytohormone precursors, using established GC-MS and LC-MS methods. Phytohormone and metabolite data were correlated with physiological measurements including biomass, plant size and chlorophyll content. Root and leaf elemental analysis was performed to determine Na+ exclusion and K+ retention ability in the studied barley varieties. We identified distinct phytohormone and metabolite signatures as a response to salinity stress in different barley varieties. Abscisic acid increased in the roots of all varieties under salinity stress, and elevated root salicylic acid levels were associated with an increase in leaf chlorophyll content. Furthermore, the landrace Sahara maintained better growth, had lower Na+ levels and maintained high levels of the salinity stress linked metabolite putrescine as well as the phytohormone metabolite cinnamic acid, which has been shown to increase putrescine concentrations in previous studies. This study highlights the importance of root phytohormones under salinity stress and the multi-variety analysis provides an important update to analytical methodology, and adds to the current knowledge of salinity stress responses in plants at the molecular level.

Genetic Architecture of Flowering Phenology in Cereals and Opportunities for Crop Improvement.

Cereal crop species including bread wheat (Triticum aestivum L.), barley (Hordeum vulgare L.), rice (Oryza sativa L.), and maize (Zea mays L.) provide the bulk of human nutrition and agricultural products for industrial use. These four cereals are central to meet future demands of food supply for an increasing world population under a changing climate. A prerequisite for cereal crop production is the transition from vegetative to reproductive and grain-filling phases starting with flower initiation, a key developmental switch tightly regulated in all flowering plants. Although studies in the dicotyledonous model plant Arabidopsis thaliana build the foundations of our current understanding of plant phenology genes and regulation, the availability of genome assemblies with high-confidence sequences for rice, maize, and more recently bread wheat and barley, now allow the identification of phenology-associated gene orthologs in monocots. Together with recent advances in next-generation sequencing technologies, QTL analysis, mutagenesis, complementation analysis, and RNA interference, many phenology genes have been functionally characterized in cereal crops and conserved as well as functionally divergent genes involved in flowering were found. Epigenetic and other molecular regulatory mechanisms that respond to environmental and endogenous triggers create an enormous plasticity in flowering behavior among cereal crops to ensure flowering is only induced under optimal conditions. In this review, we provide a summary of recent discoveries of flowering time regulators with an emphasis on four cereal crop species (bread wheat, barley, rice, and maize), in particular, crop-specific regulatory mechanisms and genes. In addition, pleiotropic effects on agronomically important traits such as grain yield, impact on adaptation to new growing environments and conditions, genetic sequence-based selection and targeted manipulation of phenology genes, as well as crop growth simulation models for predictive crop breeding, are discussed.

Metabolomics, Standards, and Metabolic Modeling for Synthetic Biology in Plants

Life on earth depends on dynamic chemical transformations that enable cellular functions, including electron transfer reactions, as well as synthesis and degradation of biomolecules. Biochemical reactions are coordinated in metabolic pathways that interact in a complex way to allow adequate regulation. Biotechnology, food, biofuel, agricultural, and pharmaceutical industries are highly interested in metabolic engineering as an enabling technology of synthetic biology to exploit cells for the controlled production of metabolites of interest. These approaches have only recently been extended to plants due to their greater metabolic complexity (such as primary and secondary metabolism) and highly compartmentalized cellular structures and functions (including plant-specific organelles) compared with bacteria and other microorganisms. Technological advances in analytical instrumentation in combination with advances in data analysis and modeling have opened up new approaches to engineer plant metabolic pathways and allow the impact of modifications to be predicted more accurately. In this article, we review challenges in the integration and analysis of large-scale metabolic data, present an overview of current bioinformatics methods for the modeling and visualization of metabolic networks, and discuss approaches for interfacing bioinformatics approaches with metabolic models of cellular processes and flux distributions in order to predict phenotypes derived from specific genetic modifications or subjected to different environmental conditions.

LC-MS profiling to link metabolic and phenotypic diversity in plant mapping populations.

Numerous studies have revealed the extent of genetic, phenotypic, and metabolic variation between different plant cultivars/varieties. We present a specialized protocol for large-scale targeted and untargeted metabolite profiling for samples from large plant mapping populations using both reversed-phase and aqueous normal-phase LC-MS. This methodology provides a fast and combined targeted/nontargeted workflow as a powerful tool to discriminate related plant phenotypes and describes methods to combine mass features and agronomic traits to link phenotypic to metabolic traits independent of putative metabolite identities. This easily reproducible analytical strategy, in combination with a sophisticated data processing and analysis workflow, can be applicable to a wide range of plant mapping populations.