Deciphering genetic diversity and inheritance of tomato fruit weight and composition through a systems biology approach

Multi-omics quantitative data of tomato fruit unveils regulation modes of least variable metabolites

BACKGROUND

The composition of ripe fruits depends on various metabolites which content evolves greatly throughout fruit development and may be influenced by the environment. The corresponding metabolism regulations have been widely described in tomato during fruit growth and ripening. However, the regulation of other metabolites that do not show large changes in content have scarcely been studied.

RESULTS

We analysed the metabolites of tomato fruits collected on different trusses during fruit development, using complementary analytical strategies. We identified the 22 least variable metabolites, based on their coefficients of variation. We first verified that they had a limited functional link with the least variable proteins and transcripts. We then posited that metabolite contents could be stabilized through complex regulations and combined their data with the quantitative proteome or transcriptome data, using sparse partial-least-square analyses. This showed shared regulations between several metabolites, which interestingly remained linked to early fruit development. We also examined regulations in specific metabolites using correlations with individual proteins and transcripts, which revealed that a stable metabolite does not always correlate with proteins and transcripts of its known related pathways.

CONCLUSIONS

The regulation of the least variable metabolites was then interpreted regarding their roles as hubs in metabolic pathways or as signalling molecules.

Proteomics of Reproductive Development, Fruit Ripening, and Stress Responses in Tomato

The fruits of the tomato crop (Solanum lycopersicum L.) are increasingly consumed by humans worldwide. Due to their rich nutritional quality, pharmaceutical properties, and flavor, tomato crops have gained a salient role as standout crops among other plants. Traditional breeding and applied functional research have made progress in varying tomato germplasms to subdue biotic and abiotic stresses. Proteomic investigations within a span of few decades have assisted in consolidating the functional genomics and transcriptomic research. However, due to the volatility and dynamicity of proteins in the regulation of various biosynthetic pathways, there is a need for continuing research in the field of proteomics to establish a network that could enable a more comprehensive understanding of tomato growth and development. With this view, we provide a comprehensive review of proteomic studies conducted on the tomato plant in past years, which will be useful for future breeders and researchers working to improve the tomato crop.

Inheritance of Secondary Metabolites and Gene Expression Related to Tomato Fruit Quality

Flavour and nutritional quality are important goals for tomato breeders. This study aimed to shed light upon transgressive behaviors for fruit metabolic content. We studied the metabolic contents of 44 volatile organic compounds (VOCs), 18 polyphenolics, together with transcriptome profiles in a factorial design comprising six parental lines and their 14 F1 hybrids (HF1) among which were five pairs of reciprocal HF1. After cluster analyses of the metabolome dataset and co-expression network construction of the transcriptome dataset, we characterized the mode of inheritance of each component. Both overall and per-cross mode of inheritance analyses revealed as many additive and non-additive modes of inheritance with few reciprocal effects. Up to 66% of metabolites displayed transgressions in a HF1 relative to parental values. Analysis of the modes of inheritance of metabolites revealed that: (i) transgressions were mostly of a single type whichever the cross and poorly correlated to the genetic distance between parental lines; (ii) modes of inheritance were scarcely consistent between the 14 crosses but metabolites belonging to the same cluster displayed similar modes of inheritance for a given cross. Integrating metabolome, transcriptome and modes of inheritance analyses suggested a few candidate genes that may drive important changes in fruit VOC contents.

An IBD-based mixed model approach for QTL mapping in multiparental populations

The identity-by-descent (IBD)-based mixed model approach introduced in this study can detect quantitative trait loci (QTLs) referring to the parental origin and simultaneously account for multilevel relatedness of individuals within and across families. This unified approach is proved to be a powerful approach for all kinds of multiparental population (MPP) designs. Multiparental populations (MPPs) have become popular for quantitative trait loci (QTL) detection. Tools for QTL mapping in MPPs are mostly developed for specific MPPs and do not generalize well to other MPPs. We present an IBD-based mixed model approach for QTL mapping in all kinds of MPP designs, e.g., diallel, Nested Association Mapping (NAM), and Multiparental Advanced Generation Intercross (MAGIC) designs. The first step is to compute identity-by-descent (IBD) probabilities using a general Hidden Markov model framework, called reconstructing ancestry blocks bit by bit (RABBIT). Next, functions of IBD information are used as design matrices, or genetic predictors, in a mixed model approach to estimate variance components for multiallelic genetic effects associated with parents. Family-specific residual genetic effects are added, and a polygenic effect is structured by kinship relations between individuals. Case studies of simulated diallel, NAM, and MAGIC designs proved that the advanced IBD-based multi-QTL mixed model approach incorporating both kinship relations and family-specific residual variances (IBD.MQMkin_F) is robust across a variety of MPP designs and allele segregation patterns in comparison to a widely used benchmark association mapping method, and in most cases, outperformed or behaved at least as well as other tools developed for specific MPP designs in terms of mapping power and resolution. Successful analyses of real data cases confirmed the wide applicability of our IBD-based mixed model methodology.

Decreased sink/source ratio enhances hexose transport in the fruits of greenhouse tomatoes: integration of gene expression and biochemical analyses

To examine the physiological role of hexose transporters in determining the sink strength of individual fruits, the regulation of hexose transporters gene expression was studied when the sink/source ratio was artificially altered under the greenhouse condition; this was done in two cultivars of tomato, i.e. Grandella and Isabella. The sink/source ratio treatments included: saving one fruit per truss (1F), two fruits per truss (2F), three fruits per truss (3F) and no fruit pruning (control). The results showed that fruit thinning could increase starch, sucrose, and hexose contents in the fruits; it could also modulate the activity of the key enzymes and the expression of tomato hexose transporter genes (LeHTs). Based on the relative transcript levels, all examined LeHTs were unregulated at the end of cell division and the cell expansion stage of fruit development, but the strongest expression level observed at the onset of ripening was related to LeHT1 and LeHT2. Given the concomitancy of cell wall invertase (EC 3.2.1.26) activity and the LeHTs relative expression cell wall, invertase activity seemed to be involved in the expression level of LeHTs. The increased trends of the LeHTs expression with the decrease of the sink/source ratio confirmed the role of hexose transporters in determining the sink strength of the tomato fruits.

Dissection of complex traits of tomato in the post-genome era

We present the main advances of dissection of complex traits in tomato by omics, the genes identified to control complex traits and the application of CRISPR/Cas9 in tomato breeding. Complex traits are believed to be under the control of multiple genes, each with different effects and interaction with environmental factors. Advance development of sequencing and molecular technologies has enabled the recognition of the genomic structure of most organisms and the identification of a nearly limitless number of markers that have made it to accelerate the speed of QTL identification and gene cloning. Meanwhile, multiomics have been used to identify the genetic variations among different tomato species, determine the expression profiles of genes in different tissues and at distinct developmental stages, and detect metabolites in different pathways and processes. The combination of these data facilitates to reveal mechanism underlying complex traits. Moreover, mutants generated by mutagens and genome editing provide relatively rich genetic variation for deciphering the complex traits and exploiting them in tomato breeding. In this article, we present the main advances of complex trait dissection in tomato by omics since the release of the tomato genome sequence in 2012. We provide further insight into some tomato complex traits because of the causal genetic variations discovered so far and explore the utilization of CRISPR/Cas9 for the modification of tomato complex traits.

Allele-specific expression and genetic determinants of transcriptomic variations in response to mild water deficit in tomato

Characterizing the natural diversity of gene expression across environments is an important step in understanding how genotype-by-environment interactions shape phenotypes. Here, we analyzed the impact of water deficit onto gene expression levels in tomato at the genome-wide scale. We sequenced the transcriptome of growing leaves and fruit pericarps at cell expansion stage in a cherry and a large fruited accession and their F₁ hybrid grown under two watering regimes. Gene expression levels were steadily affected by the genotype and the watering regime. Whereas phenotypes showed mostly additive inheritance, ~80% of the genes displayed non-additive inheritance. By comparing allele-specific expression (ASE) in the F₁ hybrid to the allelic expression in both parental lines, respectively, 3005 genes in leaf and 2857 genes in fruit deviated from 1:1 ratio independently of the watering regime. Among these genes, ~55% were controlled by cis factors, ~25% by trans factors and ~20% by a combination of both types of factors. A total of 328 genes in leaf and 113 in fruit exhibited significant ASE-by-watering regime interaction, among which ~80% presented trans-by-watering regime interaction, suggesting a response to water deficit mediated through a majority of trans-acting loci in tomato. We cross-validated the expression levels of 274 transcripts in fruit and leaves of 124 recombinant inbred lines (RILs) and identified 163 expression quantitative trait loci (eQTLs) mostly confirming the divergences identified by ASE. Combining phenotypic and expression data, we observed a complex network of variation between genes encoding enzymes involved in the sugar metabolism.

Identification of major loci and genomic regions controlling acid and volatile content in tomato fruit: implications for flavor improvement

Plant metabolites are important to world food security due to their roles in crop yield and nutritional quality. Here we report the metabolic profile of 300 tomato accessions (Solanum lycopersicum and related wild species) by quantifying 60 primary and secondary metabolites, including volatile organic compounds, over a period of 2 yr. Metabolite content and genetic inheritance of metabolites varied broadly, both within and between different genetic groups. Using genotype information gained from 10 000 single nucleotide polymorphism markers, we performed a metabolite genome-wide association mapping (GWAS) study. We identified 79 associations influencing 13 primary and 19 secondary metabolites with large effects at high resolution. Four genome regions were detected, highlighting clusters of associations controlling the variation of several metabolites. Local linkage disequilibrium analysis and allele mining identified possible candidate genes which may modulate the content of metabolites that are of significant importance for human diet and fruit consumption. We precisely characterized two associations involved in fruit acidity and phenylpropanoid volatile production. Taken together, this study reveals complex and distinct metabolite regulation in tomato subspecies and demonstrates that GWAS is a powerful tool for gene-metabolite annotation and identification, pathways elucidation, and further crop improvement.

Systems Biology for Smart Crops and Agricultural Innovation: Filling the Gaps between Genotype and Phenotype for Complex Traits Linked with Robust Agricultural Productivity and Sustainability

In recent years, rapid developments in several omics platforms and next generation sequencing technology have generated a huge amount of biological data about plants. Systems biology aims to develop and use well-organized and efficient algorithms, data structure, visualization, and communication tools for the integration of these biological data with the goal of computational modeling and simulation. It studies crop plant systems by systematically perturbing them, checking the gene, protein, and informational pathway responses; integrating these data; and finally, formulating mathematical models that describe the structure of system and its response to individual perturbations. Consequently, systems biology approaches, such as integrative and predictive ones, hold immense potential in understanding of molecular mechanism of agriculturally important complex traits linked to agricultural productivity. This has led to identification of some key genes and proteins involved in networks of pathways involved in input use efficiency, biotic and abiotic stress resistance, photosynthesis efficiency, root, stem and leaf architecture, and nutrient mobilization. The developments in the above fields have made it possible to design smart crops with superior agronomic traits through genetic manipulation of key candidate genes.

The peach HECATE3-like gene FLESHY plays a double role during fruit development

Tight control of cell/tissue identity is essential for a correct and functional organ patterning, an important component of overall fruit development and eventual maturation and ripening. Despite many investigations regarding the molecular determinants of cell identity in fruits of different species, a useful model able to depict the regulatory networks governing this relevant part of fruit development is still missing. Here we described the peach fruit as a system to link the phenotype of a slow ripening (SR) selection to an altered transcriptional regulation of genes involved in determination of mesocarp cell identity providing insight toward molecular regulation of fruit tissue formation. Morpho-anatomical observations and metabolomics analyses performed during fruit development on the reference cultivar Fantasia, compared to SR, revealed that the mesocarp of SR maintained typical immaturity traits (e.g. small cell size, high amino acid contents and reduced sucrose) throughout development, along with a strong alteration of phenylpropanoid contents, resulting in accumulation of phenylalanine and lignin. These findings suggest that the SR mesocarp is phenotypically similar to a lignifying endocarp. To test this hypothesis, the expression of genes putatively involved in determination of drupe tissues identity was assessed. Among these, the peach HEC3-like gene FLESHY showed a strongly altered expression profile consistent with pit hardening and fruit ripening, generated at a post-transcriptional level. A double function for FLESHY in channelling the phenylpropanoid pathway to either lignin or flavour/aroma is suggested, along with its possible role in triggering auxin-ethylene cross talk at the start of ripening.

Metabolomic profiling in tomato reveals diel compositional changes in fruit affected by source-sink relationships

A detailed study of the diurnal compositional changes was performed in tomato (Solanum lycopersicum cv. Moneymaker) leaves and fruits. Plants were cultivated in a commercial greenhouse under two growth conditions: control and shaded. Expanding fruits and the closest mature leaves were harvested during two different day/night cycles (cloudy or sunny day). High-throughput robotized biochemical phenotyping of major compounds, as well as proton nuclear magnetic resonance and mass spectrometry metabolomic profiling, were used to measure the contents of about 70 metabolites in the leaves and 60 metabolites in the fruits, in parallel with ecophysiological measurements. Metabolite data were processed using multivariate, univariate, or clustering analyses and correlation networks. The shaded carbon-limited plants adjusted their leaf area, decreased their sink carbon demand and showed subtle compositional modifications. For source leaves, several metabolites varied along a diel cycle, including those directly linked to photosynthesis and photorespiration. These metabolites peaked at midday in both conditions and diel cycles as expected. However, transitory carbon storage was limited in tomato leaves. In fruits, fewer metabolites showed diel fluctuations, which were also of lower amplitude. Several organic acids were among the fluctuating metabolites. Diel patterns observed in leaves and especially in fruits differed between the cloudy and sunny days, and between the two conditions. Relationships between compositional changes in leaves and fruits are in agreement with the fact that several metabolic processes of the fruit appeared linked to its momentary supply of sucrose.

Potential of a tomato MAGIC population to decipher the genetic control of quantitative traits and detect causal variants in the resequencing era

Identification of the polymorphisms controlling quantitative traits remains a challenge for plant geneticists. Multiparent advanced generation intercross (MAGIC) populations offer an alternative to traditional linkage or association mapping populations by increasing the precision of quantitative trait loci (QTL) mapping. Here, we present the first tomato MAGIC population and highlight its potential for the valorization of intraspecific variation, QTL mapping and causal polymorphism identification. The population was developed by crossing eight founder lines, selected to include a wide range of genetic diversity, whose genomes have been previously resequenced. We selected 1536 SNPs among the 4 million available to enhance haplotype prediction and recombination detection in the population. The linkage map obtained showed an 87% increase in recombination frequencies compared to biparental populations. The prediction of the haplotype origin was possible for 89% of the MAGIC line genomes, allowing QTL detection at the haplotype level. We grew the population in two greenhouse trials and detected QTLs for fruit weight. We mapped three stable QTLs and six specific of a location. Finally, we showed the potential of the MAGIC population when coupled with whole genome sequencing of founder lines to detect candidate SNPs underlying the QTLs. For a previously cloned QTL on chromosome 3, we used the predicted allelic effect of each founder and their genome sequences to select putative causal polymorphisms in the supporting interval. The number of candidate polymorphisms was reduced from 12 284 (in 800 genes) to 96 (in 54 genes), including the actual causal polymorphism. This population represents a new permanent resource for the tomato genetics community.

Comparative proteomic and metabolomic analyses reveal mechanisms of improved cold stress tolerance in bermudagrass (Cynodon dactylon (L.) Pers.) by exogenous calcium

As an important second messenger, calcium is involved in plant cold stress response, including chilling (<20 °C) and freezing (<0 °C). In this study, exogenous application of calcium chloride (CaCl2 ) improved both chilling and freezing stress tolerances, while ethylene glycol-bis-(β-aminoethyl) ether-N,N,N,N-tetraacetic acid (EGTA) reversed CaCl2 effects in bermudagrass (Cynodon dactylon (L.) Pers.). Physiological analyses showed that CaCl2 treatment alleviated the reactive oxygen species (ROS) burst and cell damage triggered by chilling stress, via activating antioxidant enzymes, non-enzymatic glutathione antioxidant pool, while EGTA treatment had the opposite effects. Additionally, comparative proteomic analysis identified 51 differentially expressed proteins that were enriched in redox, tricarboxylicacid cycle, glycolysis, photosynthesis, oxidative pentose phosphate pathway, and amino acid metabolisms. Consistently, 42 metabolites including amino acids, organic acids, sugars, and sugar alcohols were regulated by CaCl2 treatment under control and cold stress conditions, further confirming the common modulation of CaCl2 treatment in carbon metabolites and amino acid metabolism. Taken together, this study reported first evidence of the essential and protective roles of endogenous and exogenous calcium in bermudagrass response to cold stress, partially via activation of the antioxidants and modulation of several differentially expressed proteins and metabolic homeostasis in the process of cold acclimation.