Natural Variation of Plant Metabolism: Genetic Mechanisms, Interpretive Caveats, and Evolutionary and Mechanistic Insights

High variability of perezone content in rhizomes of Acourtia cordata wild plants, environmental factors related, and proteomic analysis

With the aim of exploring the source of the high variability observed in the production of perezone, in Acourtia cordata wild plants, we analyze the influence of soil parameters and phenotypic characteristics on its perezone content. Perezone is a sesquiterpene quinone responsible for several pharmacological effects and the A. cordata plants are the natural source of this metabolite. The chemistry of perezone has been widely studied, however, no studies exist related to its production under natural conditions, nor to its biosynthesis and the environmental factors that affect the yield of this compound in wild plants. We also used a proteomic approach to detect differentially expressed proteins in wild plant rhizomes and compare the profiles of high vs. low perezone-producing plants. Our results show that in perezone-producing rhizomes, the presence of high concentrations of this compound could result from a positive response to the effects of some edaphic factors, such as total phosphorus (Pt), total nitrogen (Nt), ammonium (NH4), and organic matter (O. M.), but could also be due to a negative response to the soil pH value. Additionally, we identified 616 differentially expressed proteins between high and low perezone producers. According to the functional annotation of this comparison, the upregulated proteins were grouped in valine biosynthesis, breakdown of leucine and isoleucine, and secondary metabolism such as terpenoid biosynthesis. Downregulated proteins were grouped in basal metabolism processes, such as pyruvate and purine metabolism and glycolysis/gluconeogenesis. Our results suggest that soil parameters can impact the content of perezone in wild plants. Furthermore, we used proteomic resources to obtain data on the pathways expressed when A. cordata plants produce high and low concentrations of perezone. These data may be useful to further explore the possible relationship between perezone production and abiotic or biotic factors and the molecular mechanisms related to high and low perezone production.

The potential of metabolomics in assessing global compositional changes resulting from the application of CRISPR/Cas9 technologies

Exhaustive analysis of genetically modified crops over multiple decades has increased societal confidence in the technology. New Plant Breeding Techniques are now emerging with improved precision and the ability to generate products containing no foreign DNA and mimic/replicate conventionally bred varieties. In the present study, metabolomic analysis was used to compare (i) tobacco genotypes with and without the CRISPR associated protein 9 (Cas9), (ii) tobacco lines with the edited and non-edited DE-ETIOLATED-1 gene without phenotype and (iii) leaf and fruit tissue from stable non-edited tomato progeny with and without the Cas9. In all cases, multivariate analysis based on the difference test using LC-HRMS/MS and GC-MS data indicated no significant difference in their metabolomes. The variations in metabolome composition that were evident could be associated with the processes of tissue culture regeneration and/or transformation (e.g. interaction with Agrobacterium). Metabolites responsible for the variance included quantitative changes of abundant, well characterised metabolites such as phenolics (e.g. chlorogenic acid) and several common sugars such as fructose. This study provides fundamental data on the characterisation of gene edited crops, that are important for the evaluation of the technology and its assessment. The approach also suggests that metabolomics could contribute to routine product-based analysis of crops/foods generated from New Plant Breeding approaches.

Generalizable approaches for genomic prediction of metabolites in plants

Plant metabolites are important traits for plant breeders seeking to improve nutrition and agronomic performance yet integrating selection for metabolomic traits can be limited by phenotyping expense and degree of genetic characterization, especially of uncommon metabolites. As such, developing generalizable genomic selection methods based on biochemical pathway biology for metabolites that are transferable across plant populations would benefit plant breeding programs. We tested genomic prediction accuracy for >600 metabolites measured by gas chromatography-mass spectrometry (GC-MS) and liquid chromatography-mass spectrometry (LC-MS) in oat (Avena sativa L.) seed. Using a discovery germplasm panel, we conducted metabolite genome-wide association study (mGWAS) and selected loci to use in multikernel models that encompassed metabolome-wide mGWAS results or mGWAS from specific metabolite structures or biosynthetic pathways. Metabolite kernels developed from LC-MS metabolites in the discovery panel improved prediction accuracy of LC-MS metabolite traits in the validation panel consisting of more advanced breeding lines. No approach, however, improved prediction accuracy for GC-MS metabolites. We ranked model performance by metabolite and found that metabolites with similar polarity had consistent rankings of models. Overall, testing biological rationales for developing kernels for genomic prediction across populations contributes to developing frameworks for plant breeding for metabolite traits.

Frequent numerical and structural chromosome changes in early generations of synthetic hexaploid wheat

Modern hexaploid wheat (Triticum aestivum L.; AABBDD) evolved from a hybrid of tetraploid wheat (closely related to Triticum turgidum L. ssp. durum (Desf.) Husn., AABB) and goatgrass (Aegilops tauschii Coss., DD). Variations in chromosome structure and ploidy played important roles in wheat evolution. How these variations occurred and their role in expanding the genetic diversity in modern wheat is mostly unknown. Synthetic hexaploid wheat (SHW) can be used to investigate chromosome variation that occurs during the early generations of existence. SHW lines derived by crossing durum wheat 'Langdon' with twelve Ae. tauschii accessions were analyzed using oligonucelotide probe multiplex fluorescence in situ hybridization (FISH) to metaphase chromosomes and SNP markers. Cluster analysis based on SNP markers categorized them into three groups. Among 702 plants from the S8 and S9 generations, 415 (59.12%) carried chromosome variations involving all 21 chromosomes but with different frequencies for each chromosome and sub-genome. Total chromosome variation frequencies varied between lines, but there was no significant difference among the three groups. The non-random chromosome variations in SHW lines detected in this research may be an indication that similar variations occurred in the early stages of wheat polyploidization and played important roles in wheat evolution.

Combined Transcriptome and Metabolome Analysis of Alfalfa Response to Thrips Infection

Thrips (Thysanoptera: Thripidae) is a major insect pest for alfalfa which can result in decreased plant nutrients, low yields, and even plant death. To identify the differentially expressed genes and metabolites in response to thrips in alfalfa, a combination of metabolomics and transcriptomics was employed using alfalfa (Caoyuan No. 2) with and without thrips infestation. The results showed that the flavonoid biosynthesis and isoflavonoid biosynthesis pathways were the most significantly enriched pathways in response to thrips infection, as shown by the combined transcriptome and metabolome analysis. The transcriptome results showed that SA and JA signal transduction and PAPM-triggered immunity and the MAPK signaling pathway–plant pathways played a crucial role in thrips-induced plant resistance in alfalfa. In addition, we found that thrips infestation could also induce numerous changes in plant primary metabolism, such as carbohydrate and amino acid metabolism as compared to the control. Overall, our results described here should improve fundamental knowledge of molecular responses to herbivore-inducible plant defenses and contribute to the design of strategies against thrips in alfalfa.

Genome-wide association studies: assessing trait characteristics in model and crop plants

GWAS involves testing genetic variants across the genomes of many individuals of a population to identify genotype–phenotype association. It was initially developed and has proven highly successful in human disease genetics. In plants genome-wide association studies (GWAS) initially focused on single feature polymorphism and recombination and linkage disequilibrium but has now been embraced by a plethora of different disciplines with several thousand studies being published in model and crop species within the last decade or so. Here we will provide a comprehensive review of these studies providing cases studies on biotic resistance, abiotic tolerance, yield associated traits, and metabolic composition. We also detail current strategies of candidate gene validation as well as the functional study of haplotypes. Furthermore, we provide a critical evaluation of the GWAS strategy and its alternatives as well as future perspectives that are emerging with the emergence of pan-genomic datasets.

SNPeffect: identifying functional roles of SNPs using metabolic networks

Genetic sources of phenotypic variation have been a focus of plant studies aimed at improving agricultural yield and understanding adaptive processes. Genome-wide association studies identify the genetic background behind a trait by examining associations between phenotypes and single-nucleotide polymorphisms (SNPs). Although such studies are common, biological interpretation of the results remains a challenge; especially due to the confounding nature of population structure and the systematic biases thus introduced. Here, we propose a complementary analysis (SNPeffect) that offers putative genotype-to-phenotype mechanistic interpretations by integrating biochemical knowledge encoded in metabolic models. SNPeffect is used to explain differential growth rate and metabolite accumulation in A. thaliana and P. trichocarpa accessions as the outcome of SNPs in enzyme-coding genes. To this end, we also constructed a genome-scale metabolic model for Populus trichocarpa, the first for a perennial woody tree. As expected, our results indicate that growth is a complex polygenic trait governed by carbon and energy partitioning. The predicted set of functional SNPs in both species are associated with experimentally characterized growth-determining genes and also suggest putative ones. Functional SNPs were found in pathways such as amino acid metabolism, nucleotide biosynthesis, and cellulose and lignin biosynthesis, in line with breeding strategies that target pathways governing carbon and energy partition.

Association analysis of phenotypic and metabolomic changes in Arabidopsis accessions and their F1 hybrids affected by different photoperiod and sucrose supply

Photoperiod and sucrose (Suc) assimilation play important roles in the regulation of plant growth and development. However, it remains unclear how natural variation of plants could contribute to metabolic changes under various growth conditions. Here, we investigated the developmental and metabolomic responses of two natural accessions of Arabidopsis thaliana, Columbia (Col) and C24, and their reciprocal F₁ hybrids grown under four carbon source regimens, i.e., two different photoperiods and the presence or absence of exogenous Suc supply. The effect of exogenous Suc clearly appeared in the growth of Col and the F₁ hybrid but not in C24, whereas long-day conditions had significant positive effects on the growth of all lines. Comparative metabolite profiling of Col, C24, and the F₁ hybrid revealed that changes in metabolite levels, particularly sugars, were highly dependent on genotype-specific responses rather than growth conditions. The presence of Suc led to over-accumulation of seven metabolites, including four sugars, a polyamine, and two amino acids in C24, whereas no such accumulation was observed in the profiles of Col and the F₁ hybrid. Thus, the comparative metabolite profiling revealed that the two parental lines of the hybrid show a distinct difference in sugar metabolism.

Statistical study on the environmental effects on the natural variation of nutritional components in rice varieties

This study was investigated to compare the natural variation of nutrients in rice variety by different environmental factors. Fifteen kinds of rices were used, which were cultivated in two locations for 2 years. All data were analyzed by the various statistical tools to identify the nutritional variations of nutrients. The results of variable importance in the prediction analysis were found to be consistent with the % variability. The nutrient compositions most affected by variety were fatty acids, and next were vitamins, proximate nutrients, minerals, and amino acids in order. The nutrient compositions most affected by location were proximate, followed by minerals, vitamins, fatty acids, and amino acids. For cultivation year, vitamins were most affected and then minerals, fatty acids, proximate nutrients, and amino acids in order. These findings could explain that each kind of nutrients can be naturally varied by different environmental factors.

The Microbial Communities of Leaves and Roots Associated with Turtle Grass (Thalassia testudinum) and Manatee Grass (Syringodium filliforme) are Distinct from Seawater and Sediment Communities, but Are Similar between Species and Sampling Sites

Seagrasses are vital members of coastal systems, which provide several important ecosystem services such as improvement of water quality, shoreline protection, and serving as shelter, food, and nursery to many species, including economically important fish. They also act as a major carbon sink and supply copious amounts of oxygen to the ocean. A decline in seagrasses has been observed worldwide, partly due to climate change, direct and indirect human activities, diseases, and increased sulfide concentrations in the coastal porewaters. Several studies have shown a symbiotic relationship between seagrasses and their microbiome. For instance, the sulfur, nitrogen, and carbon cycles are important biochemical pathways that seem to be linked between the plant and its microbiome. The microbiome presumably also plays a key role in the health of the plant, for example in oxidizing phyto-toxic sulfide into non-toxic sulfate, or by providing protection for seagrasses from pathogens. Two of the most abundant seagrasses in Florida include Thalassiatestudinum (turtle grass) and Syringodium filliforme (manatee grass), yet there is little data on the composition of the microbiome of these two genera. In this study, the microbial composition of the phyllosphere and rhizosphere of Thalassia testudinum and Syringodium filiforme were compared to water and sediment controls using amplicon sequencing of the V4 region of the 16S rRNA gene. The microbial composition of the leaves, roots, seawater, and sediment differ from one another, but are similar between the two species of seagrasses.

Metabolite Profiles of Sugarcane Culm Reveal the Relationship Among Metabolism and Axillary Bud Outgrowth in Genetically Related Sugarcane Commercial Cultivars

Metabolic composition is known to exert influence on several important agronomic traits, and metabolomics, which represents the chemical composition in a cell, has long been recognized as a powerful tool for bridging phenotype-genotype interactions. In this work, sixteen truly representative sugarcane Brazilian varieties were selected to explore the metabolic networks in buds and culms, the tissues involved in the vegetative propagation of this species. Due to the fact that bud sprouting is a key trait determining crop establishment in the field, the sprouting potential among the genotypes was evaluated. The use of partial least square discriminant analysis indicated only mild differences on bud outgrowth potential under controlled environmental conditions. However, primary metabolite profiling provided information on the variability of metabolic features even under a narrow genetic background, typical for modern sugarcane cultivars. Metabolite-metabolite correlations within and between tissues revealed more complex patterns for culms in relation to buds, and enabled the recognition of key metabolites (e.g., sucrose, putrescine, glutamate, serine, and myo-inositol) affecting sprouting ability. Finally, those results were associated with the genetic background of each cultivar, showing that metabolites can be potentially used as indicators for the genetic background.

Dark period transcriptomic and metabolic profiling of two diverse Eutrema salsugineum accessions

Eutrema salsugineum is a model species for the study of plant adaptation to abiotic stresses. Two accessions of E. salsugineum, Shandong (SH) and Yukon (YK), exhibit contrasting morphology and biotic and abiotic stress tolerance. Transcriptome profiling and metabolic profiling from tissue samples collected during the dark period were used to investigate the molecular and metabolic bases of these contrasting phenotypes. RNA sequencing identified 17,888 expressed genes, of which 157 were not in the published reference genome, and 65 of which were detected for the first time. Differential expression was detected for only 31 genes. The RNA sequencing data contained 14,808 single nucleotide polymorphisms (SNPs) in transcripts, 3,925 of which are newly identified. Among the differentially expressed genes, there were no obvious candidates for the physiological or morphological differences between SH and YK. Metabolic profiling indicated that YK accumulates free fatty acids and long-chain fatty acid derivatives as compared to SH, whereas sugars are more abundant in SH. Metabolite levels suggest that carbohydrate and respiratory metabolism, including starch degradation, is more active during the first half of the dark period in SH. These metabolic differences may explain the greater biomass accumulation in YK over SH. The accumulation of 56% of the identified metabolites was lower in F1 hybrids than the mid-parent averages and the accumulation of 17% of the metabolites in F1 plants transgressed the level in both parents. Concentrations of several metabolites in F1 hybrids agree with previous studies and suggest a role for primary metabolism in heterosis. The improved annotation of the E. salsugineum genome and newly identified high-quality SNPs will permit accelerated studies using the standing variation in this species to elucidate the mechanisms of its diverse adaptations to the environment.

Natural Variation in Elicitation of Defense-Signaling Associates to Field Resistance Against the Spot Blotch Disease in Bread Wheat (Triticum aestivum L.)

Spot blotch, caused by the hemibiotropic fungus Bipolaris sorokiniana, is amongst the most damaging diseases of wheat. Still, natural variation in expression of biochemical traits that determine field resistance to spot blotch in wheat remain unaddressed. To understand how genotypic variations relate to metabolite profiles of the components of defense-signaling and the plant performance, as well as to discover novel sources of resistance against spot blotch, we have conducted field studies using 968 wheat genotypes at 5 geographical locations in South-Asia in 2 years. 46 genotypes were identified as resistant. Further, in independent confirmatory trials in subsequent 3 years, over 5 geographical locations, we re-characterized 55 genotypes for their resistance (above 46 along with Yangmai#6, a well characterized resistant genotype, and eight susceptible genotypes). We next determined time-dependent spot blotch-induced metabolite profiles of components of defense-signaling as well as levels of enzymatic components of defense pathway (such as salicylic acid (SA), phenolic acids, and redox components), and derived co-variation patterns with respect to resistance in these 55 genotypes. Spot blotch-induced SA accumulation was negatively correlated to disease progression. Amongst phenolic acids, syringic acid was most strongly inversely correlated to disease progression, indicating a defensive function, which was independently confirmed. Thus, exploring natural variation proved extremely useful in determining traits influencing phenotypic plasticity and adaptation to complex environments. Further, by overcoming environmental heterogeneity, our study identifies germplasm and biochemical traits that are deployable for spot blotch resistance in wheat along South-Asia.

Similarities between plant traits based on their connection to underlying gene functions

Understanding of phenotypes and their genetic basis is a major focus in current plant biology. Large amounts of phenotype data are being generated, both for macroscopic phenotypes such as size or yield, and for molecular phenotypes such as expression levels and metabolite levels. More insight in the underlying genetic and molecular mechanisms that influence phenotypes will enable a better understanding of how various phenotypes are related to each other. This will be a major step forward in understanding plant biology, with immediate value for plant breeding and academic plant research. Currently the genetic basis of most phenotypes remains however to be discovered, and the relatedness of different traits is unclear. We here present a novel approach to connect phenotypes to underlying biological processes and molecular functions. These connections define similarities between different types of phenotypes. The approach starts by using Quantitative Trait Locus (QTL) data, which are abundantly available for many phenotypes of interest. Overrepresentation analysis of gene functions based on Gene Ontology term enrichment across multiple QTL regions for a given phenotype, be it macroscopic or molecular, results in a small set of biological processes and molecular functions for each phenotype. Subsequently, similarity between different phenotypes can be defined in terms of these gene functions. Using publicly available rice data as example, a close relationship with defined molecular phenotypes is demonstrated for many macroscopic phenotypes. This includes for example a link between 'leaf senescence' and 'aspartic acid', as well as between 'days to maturity' and 'choline'. Relationships between macroscopic and molecular phenotypes may result in more efficient marker-assisted breeding and are likely to direct future research aimed at a better understanding of plant phenotypes.

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.

Integrating metabolomics and transcriptomics data to discover a biocatalyst that can generate the amine precursors for alkamide biosynthesis

The Echinacea genus is exemplary of over 30 plant families that produce a set of bioactive amides, called alkamides. The Echinacea alkamides may be assembled from two distinct moieties, a branched-chain amine that is acylated with a novel polyunsaturated fatty acid. In this study we identified the potential enzymological source of the amine moiety as a pyridoxal phosphate-dependent decarboxylating enzyme that uses branched-chain amino acids as substrate. This identification was based on a correlative analysis of the transcriptomes and metabolomes of 36 different E. purpurea tissues and organs, which expressed distinct alkamide profiles. Although no correlation was found between the accumulation patterns of the alkamides and their putative metabolic precursors (i.e., fatty acids and branched-chain amino acids), isotope labeling analyses supported the transformation of valine and isoleucine to isobutylamine and 2-methylbutylamine as reactions of alkamide biosynthesis. Sequence homology identified the pyridoxal phosphate-dependent decarboxylase-like proteins in the translated proteome of E. purpurea. These sequences were prioritized for direct characterization by correlating their transcript levels with alkamide accumulation patterns in different organs and tissues, and this multi-pronged approach led to the identification and characterization of a branched-chain amino acid decarboxylase, which would appear to be responsible for generating the amine moieties of naturally occurring alkamides.

Plant Metabolomics: An Indispensable System Biology Tool for Plant Science

As genomes of many plant species have been sequenced, demand for functional genomics has dramatically accelerated the improvement of other omics including metabolomics. Despite a large amount of metabolites still remaining to be identified, metabolomics has contributed significantly not only to the understanding of plant physiology and biology from the view of small chemical molecules that reflect the end point of biological activities, but also in past decades to the attempts to improve plant behavior under both normal and stressed conditions. Hereby, we summarize the current knowledge on the genetic and biochemical mechanisms underlying plant growth, development, and stress responses, focusing further on the contributions of metabolomics to practical applications in crop quality improvement and food safety assessment, as well as plant metabolic engineering. We also highlight the current challenges and future perspectives in this inspiring area, with the aim to stimulate further studies leading to better crop improvement of yield and quality.

Inter-Species Comparative Analysis of Components of Soluble Sugar Concentration in Fleshy Fruits

The soluble sugar concentration of fleshy fruit is a key determinant of fleshy fruit quality. It affects directly the sweetness of fresh fruits and indirectly the properties of processed products (e.g., alcohol content in wine). Despite considerable divergence among species, soluble sugar accumulation in a fruit results from the complex interplay of three main processes, namely sugar import, sugar metabolism, and water dilution. Therefore, inter-species comparison would help to identify common and/or species-specific modes of regulation in sugar accumulation. For this purpose, a process-based mathematical framework was used to compare soluble sugar accumulation in three fruits: grape, tomato, and peach. Representative datasets covering the time course of sugar accumulation during fruit development were collected. They encompassed 104 combinations of species (3), genotypes (30), and growing conditions (19 years and 16 nutrient and environmental treatments). At maturity, grape showed the highest soluble sugar concentrations (16.5-26.3 g/100 g FW), followed by peach (2.2 to 20 g/100 g FW) and tomato (1.4 to 5 g/100 g FW). Main processes determining soluble sugar concentration were decomposed into sugar importation, metabolism, and water dilution with the process-based analysis. Different regulation modes of soluble sugar concentration were then identified, showing either import-based, dilution-based, or import and dilution dual-based. Firstly, the higher soluble sugar concentration in grape than in tomato is a result of higher sugar importation. Secondly, the higher soluble sugar concentration in grape than in peach is due to a lower water dilution. The third mode of regulation is more complicated than the first two, with differences both in sugar importation and water dilution (grape vs. cherry tomato; cherry tomato vs. peach; peach vs. tomato). On the other hand, carbon utilization for synthesis of non-soluble sugar compounds (namely metabolism) was conserved among the three fruit species. These distinct modes appear to be quite species-specific, but the intensity of the effect may significantly vary depending on the genotype and management practices. These results provide novel insights into the drivers of differences in soluble sugar concentration among fleshy fruits.

Inter-Species Comparative Analysis of Components of Soluble Sugar Concentration in Fleshy Fruits

The soluble sugar concentration of fleshy fruit is a key determinant of fleshy fruit quality. It affects directly the sweetness of fresh fruits and indirectly the properties of processed products (e.g., alcohol content in wine). Despite considerable divergence among species, soluble sugar accumulation in a fruit results from the complex interplay of three main processes, namely sugar import, sugar metabolism, and water dilution. Therefore, inter-species comparison would help to identify common and/or species-specific modes of regulation in sugar accumulation. For this purpose, a process-based mathematical framework was used to compare soluble sugar accumulation in three fruits: grape, tomato, and peach. Representative datasets covering the time course of sugar accumulation during fruit development were collected. They encompassed 104 combinations of species (3), genotypes (30), and growing conditions (19 years and 16 nutrient and environmental treatments). At maturity, grape showed the highest soluble sugar concentrations (16.5-26.3 g/100 g FW), followed by peach (2.2 to 20 g/100 g FW) and tomato (1.4 to 5 g/100 g FW). Main processes determining soluble sugar concentration were decomposed into sugar importation, metabolism, and water dilution with the process-based analysis. Different regulation modes of soluble sugar concentration were then identified, showing either import-based, dilution-based, or import and dilution dual-based. Firstly, the higher soluble sugar concentration in grape than in tomato is a result of higher sugar importation. Secondly, the higher soluble sugar concentration in grape than in peach is due to a lower water dilution. The third mode of regulation is more complicated than the first two, with differences both in sugar importation and water dilution (grape vs. cherry tomato; cherry tomato vs. peach; peach vs. tomato). On the other hand, carbon utilization for synthesis of non-soluble sugar compounds (namely metabolism) was conserved among the three fruit species. These distinct modes appear to be quite species-specific, but the intensity of the effect may significantly vary depending on the genotype and management practices. These results provide novel insights into the drivers of differences in soluble sugar concentration among fleshy fruits.

Environmental and Genetic Factors Associated with Solanesol Accumulation in Potato Leaves

Solanesol is a high value 45-carbon, unsaturated, all-trans-nonaprenol isoprenoid. Recently solanesol has received particular attention because of its utility, both in its own right and as a precursor in the production of numerous compounds used in the treatment of disease states. Solanesol is found mainly in solanaceous crops such as potato, tomato, tobacco and pepper where it accumulates in the foliage. There is considerable potential to explore the extraction of solanesol from these sources as a valuable co-product. In this study we have characterized the genetic variation in leaf solanesol content in a biparental, segregating diploid potato population. We demonstrate that potato leaf solanesol content is genetically controlled and identify several quantitative trait loci associated with leaf solanesol content. Transient over-expression of genes from the methylerythritol 4-phosphate (MEP) and mevalonic acid (MVA) pathways, either singly or in combination, resulted in enhanced accumulation of solanesol in leaves of Nicotiana benthamiana, providing insights for genetically engineering the pathway. We also demonstrate that in potato, leaf solanesol content is enhanced by up to six-fold on exposure to moderately elevated temperature and show corresponding changes in expression patterns of MEP and MVA genes. Our combined approaches offer new insights into solanesol accumulation and strategies for developing a bio-refinery approach to potato production.