Tomato (Solanum lycopersicum) is an established model for studying fruit biology; however, most studies of tomato fruit growth and ripening are based on homogenized pericarp, and do not consider the internal tissues, or the expression signatures of individual cell and tissue types. We present a spatiotemporally resolved transcriptome analysis of tomato fruit ontogeny, using laser microdissection (LM) or hand dissection coupled with RNA-Seq analysis. Regulatory and structural gene networks, including families of transcription factors and hormone synthesis and signaling pathways, are defined across tissue and developmental spectra. The ripening program is revealed as comprising gradients of gene expression, initiating in internal tissues then radiating outward, and basipetally along a latitudinal axis. We also identify spatial variations in the patterns of epigenetic control superimposed on ripening gradients. Functional studies elucidate previously masked regulatory phenomena and relationships, including those associated with fruit quality traits, such as texture, color, aroma, and metabolite profiles.

SUMMARYFruit set in angiosperms marks the transition from flowering to fruit production and a commitment to seed dispersal. Studies with Solanum lycopersicum (tomato) fruit have shown that pollination and subsequent fertilization induce the biosynthesis of several hormones, including auxin and gibberellins (GAs), which stimulate fruit set. Circumstantial evidence suggests that the gaseous hormone ethylene may also influence fruit set, but this has yet to be substantiated with molecular or mechanistic data. Here, we examined fruit set at the biochemical and genetic levels, using hormone and inhibitor treatments, and mutants that affect auxin or ethylene signaling. The expression of system-1 ethylene biosynthetic genes and the production of ethylene decreased during pollination-dependent fruit set in wild-type tomato and during pollination-independent fruit set in the auxin hypersensitive mutant iaa9-3. Blocking ethylene perception in emasculated flowers, using either the ethylene-insensitive Sletr1-1 mutation or 1-methylcyclopropene (1-MCP), resulted in elongated parthenocarpic fruit and increased cell expansion, whereas simultaneous treatment with the GA biosynthesis inhibitor paclobutrazol (PAC) inhibited parthenocarpy. Additionally, the application of the ethylene precursor 1-aminocyclopropane-1-carboxylic acid (ACC) to pollinated ovaries reduced fruit set. Furthermore, Sletr1-1 parthenocarpic fruits did not exhibit increased auxin accumulation, but rather had elevated levels of bioactive GAs, most likely reflecting an increase in transcripts encoding the GA-biosynthetic enzyme SlGA20ox3, as well as a reduction in the levels of transcripts encoding the GA-inactivating enzymes SlGA2ox4 and SlGA2ox5. Taken together, our results suggest that ethylene plays a role in tomato fruit set by suppressing GA metabolism.

Dry seeds contain translatable, long-lived mRNAs that are stored during seed maturation. Early studies using transcriptional inhibitors supported the view that protein synthesis during the initial phase of germination occurs on long-lived mRNA templates. Rice seeds were treated with the transcriptional inhibitor actinomycin D (Act D), and the embryonic proteins translated from long-lived mRNAs during germination were identified using a proteomic analysis. De novo transcription was not required for germination of rice seeds, since >80% of seeds germinated when transcription was prevented by treatment with Act D. In contrast, germination was completely inhibited in the presence of cycloheximide, an inhibitor of translation. Thus, de novo protein synthesis is necessary for germination of rice seeds. The proteomic analysis revealed that 20 proteins are up-regulated during germination, even after Act D treatment. Many of the up-regulated proteins are involved in carbohydrate metabolism and cytoskeleton formation. These results indicate that some of the germination-specific proteins involved in energy production and maintenance of cell structure in rice seeds are synthesized from long-lived mRNAs. The timing of translation of eight up-regulated proteins was clearly later than that of the other up-regulated proteins under conditions in which transcription was inhibited by Act D, suggesting that translation of long-lived mRNAs in rice seeds is regulated according to the germination phase.

Yield is the most important breeding trait of crops. For fruit-bearing plants such as Solanum lycopersicum (tomato), fruit formation directly affects yield. The final fruit size depends on the number and volume of cell layers in the pericarp of the fruit, which is determined by the degree of cell division and expansion in the fertilized ovaries. Thus, fruit yield in tomato is predominantly determined by the efficiency of fruit set and the final cell number and size of the fruits. Through domestication, tomato fruit yield has been markedly increased as a result of mutations associated with fruit size and genetic studies have identified the genes that influence the cell cycle, carpel number and fruit set. Additionally, several lines of evidence have demonstrated that plant hormones control fruit set and size through the delicate regulation of genes that trigger physiological responses associated with fruit expansion. In this review, we introduce the key genes involved in tomato breeding and describe how they affect the physiological processes that contribute to tomato yield.

SummaryWith the development of new high-throughput DNA sequencing technologies and decreasing costs, large gene expression datasets are being generated at an accelerating rate, but can be complex to visualize. New, more interactive and intuitive tools are needed to visualize the spatiotemporal context of expression data and help elucidate gene function. Using tomato fruit as a model, we have developed the Tomato Expression Atlas to facilitate effective data analysis, allowing the simultaneous visualization of groups of genes at a cell/tissue level of resolution within an organ, enhancing hypothesis development and testing in addition to candidate gene identification. This atlas can be adapted to different types of expression data from diverse multicellular species.Availability and ImplementationThe Tomato Expression Atlas is available at http://tea.solgenomics.net/. Source code is available at https://github.com/solgenomics/Tea.Supplementary information Supplementary data are available at Bioinformatics online.

Parthenocarpy, or pollination-independent fruit set, is an attractive trait for fruit production and can be induced by increased responses to the phytohormone gibberellin (GA), which regulates diverse aspects of plant development. GA signaling in plants is negatively regulated by DELLA proteins. A loss-of-function mutant of tomato DELLA (SlDELLA), procera (pro) thus exhibits enhanced GA-response phenotypes including parthenocarpy, although the pro mutation also confers some disadvantages for practical breeding. This study identified a new milder hypomorphic allele of SlDELLA, procera-2 (pro-2), which showed weaker GA-response phenotypes than pro. The pro-2 mutant contains a single nucleotide substitution, corresponding to a single amino acid substitution in the SAW subdomain of the SlDELLA. Accumulation of the mutated SlDELLA transcripts in wild-type (WT) resulted in parthenocarpy, while introduction of intact SlDELLA into pro-2 rescued mutant phenotypes. Yeast two-hybrid assays revealed that SlDELLA interacted with three tomato homologues of GID1 GA receptors with increasing affinity upon GA treatment, while their interactions were reduced by the pro and pro-2 mutations. Both pro and pro-2 mutants produced higher fruit yields under high temperature conditions, which were resulted from higher fruit set efficiency, demonstrating the potential for genetic parthenocarpy to improve yield under adverse environmental conditions.

Fruit set is the process whereby ovaries develop into fruits after pollination and fertilization. The process is induced by the phytohormone gibberellin (GA) in tomatoes, as determined by the constitutive GA response mutant procera. However, the role of GA on the metabolic behavior in fruit-setting ovaries remains largely unknown. This study explored the biochemical mechanisms of fruit set using a network analysis of integrated transcriptome, proteome, metabolome, and enzyme activity data. Our results revealed that fruit set involves the activation of central carbon metabolism, with increased hexoses, hexose phosphates, and downstream metabolites, including intermediates and derivatives of glycolysis, the tricarboxylic acid cycle, and associated organic and amino acids. The network analysis also identified the transcriptional hub gene SlHB15A, that coordinated metabolic activation. Furthermore, a kinetic model of sucrose metabolism predicted that the sucrose cycle had high activity levels in unpollinated ovaries, whereas it was shut down when sugars rapidly accumulated in vacuoles in fruit-setting ovaries, in a time-dependent manner via tonoplastic sugar carriers. Moreover, fruit set at least partly required the activity of fructokinase, which may pull fructose out of the vacuole, and this could feed the downstream pathways. Collectively, our results indicate that GA cascades enhance sink capacities, by up-regulating central metabolic enzyme capacities at both transcriptional and posttranscriptional levels. This leads to increased sucrose uptake and carbon fluxes for the production of the constituents of biomass and energy that are essential for rapid ovary growth during the initiation of fruit set.

This protocol enables transcriptome profiling of specific cell or tissue types that are isolated from tomato using laser microdissection (LM). To prepare tissue for LM, fruit samples are first fixed in optimal cutting temperature (OCT) medium and frozen in molds. The tissue is then sectioned using a cryostat before being dissected using an LM instrument. The RNAs contained in the harvested cells are purified and subjected to two rounds of amplification to yield sufficient quantities of RNA to generate cDNA libraries. Unlike several other techniques that are used to isolate specific cell types, LM has the advantage of being readily applied to any plant species without having to generate transgenic plants. Using the protocols described here, LM-mediated cell-type transcriptomic analysis of two samples requires ∼8 d from tissue harvest to RNA sequencing (RNA-seq), whereas each additional sample, up to a total of 12 samples, requires ∼1 additional day for the LM step. RNA obtained using this method has been successfully used for deep-coverage transcriptome profiling, which is a particularly effective strategy for identifying genes that are differentially expressed between cell or tissue types.