Transcriptome analyses of early cucumber fruit growth identifies distinct gene modules associated with phases of development
© Ando et al.; licensee BioMed Central Ltd. 2012
Received: 17 April 2012
Accepted: 24 September 2012
Published: 2 October 2012
Early stages of fruit development from initial set through exponential growth are critical determinants of size and yield, however, there has been little detailed analysis of this phase of development. In this study we combined morphological analysis with 454 pyrosequencing to study transcript level changes occurring in young cucumber fruit at five ages from anthesis through the end of exponential growth.
The fruit samples produced 1.13 million ESTs which were assembled into 27,859 contigs with a mean length of 834 base pairs and a mean of 67 reads per contig. All contigs were mapped to the cucumber genome. Principal component analysis separated the fruit ages into three groups corresponding with cell division/pre-exponential growth (0 and 4 days post pollination (dpp)), peak exponential expansion (8dpp), and late/post-exponential expansion stages of growth (12 and 16 dpp). Transcripts predominantly expressed at 0 and 4 dpp included homologs of histones, cyclins, and plastid and photosynthesis related genes. The group of genes with peak transcript levels at 8dpp included cytoskeleton, cell wall, lipid metabolism and phloem related proteins. This group was also dominated by genes with unknown function or without known homologs outside of cucurbits. A second shift in transcript profile was observed at 12-16dpp, which was characterized by abiotic and biotic stress related genes and significant enrichment for transcription factor gene homologs, including many associated with stress response and development.
The transcriptome data coupled with morphological analyses provide an informative picture of early fruit development. Progressive waves of transcript abundance were associated with cell division, development of photosynthetic capacity, cell expansion and fruit growth, phloem activity, protection of the fruit surface, and finally transition away from fruit growth toward a stage of enhanced stress responses. These results suggest that the interval between expansive growth and ripening includes further developmental differentiation with an emphasis on defense. The increased transcript levels of cucurbit-specific genes during the exponential growth stage may indicate unique factors contributing to rapid growth in cucurbits.
KeywordsCucumis sativus Exponential fruit growth Fruit maturation Fruit set Fruit surface Gene expression
Fleshy fruits are highly prized for nutritional content, flavor, fragrance, and appearance. While most fruits are eaten when ripe, a subset, including many that for culinary purposes are viewed as vegetables, are consumed immature. Cucumbers (Cucumis sativus), which are used as fresh product and processed into pickles, are typically harvested at the middle or end of the exponential growth phase, 1–2 weeks post-pollination, and approximately 2–3 weeks prior to fruit maturation.
Early fruit development is typified by phases of cell division and expansion . In cucumber fruit, which develop from an enlarged inferior ovary, cell division occurs most rapidly prior to anthesis and then continues more slowly in the first 0–5 days post anthesis [2–5]. This phase largely overlaps with the period of highest respiration . Fruit elongation begins almost immediately after pollination, with the most rapid increase occurring approximately 4–12 days post pollination (dpp) . The rapid increase in cell size mirrors the rapid increase in fruit length, with obvious increase in vacuolization of mesocarp cells, and thickening in epidermal cell walls occurring between 8 and 16 dpp . Cell division and expansion are largely completed by 12–16 dpp, with some variation depending on cultivar and season [4, 6, 7].
In addition to cell division and expansion, early development also includes specialized tissue and organ development and interaction with the abiotic and biotic environment. For example, developing cucumber fruit exhibit a distinct change in susceptibility to the soil-borne, oomycete pathogen, Phytophthora capsici; young fruit are highly susceptible, while older fruit are resistant [8, 9]. There is a sharp transition in susceptibility that occurs at approximately 10–12 dpp coinciding with the end of the period of rapid fruit elongation. This age-related resistance suggests additional kinds of developmental changes occurring in the young cucumber fruit.
Although a limited number of studies have examined gene expression during early fruit development, a picture reflecting cell division and expansion is beginning to emerge based on transcriptomic studies of apple, cucumber, grape, tomato and watermelon. Among the enriched categories associated with tomato fruit set, were genes associated with protein biosynthesis, histones, nucleosome and chromosome assembly and cell cycle, suggesting a profile reflective of active cell division [10–12]. In contrast, various water, sugar and organic acid transport-associated genes were under-represented, but then increased with the transition from cell division to cell expansion. Highly expressed categories of genes expressed in expanding cucumber, as well as apple, grape, tomato, melon and watermelon fruits, included cytoskeleton and cell wall modifying genes such as tubulins, expansins, endo-1,2-B-glucanase, beta glucosidases, pectate lyases, and pectin methylesterases, and transport associated genes such as aquaporins, vacuolar H+ATPases, and phloem-associated proteins [6, 10, 13–18]. The most highly represented transcripts in rapidly expanding cucumber fruit (8 dpp) also were strongly enriched for defense related homologs including, lipid, latex, and defense-related genes, e.g., chitinase, thionin, hevein, snakin, peroxidase, catalase, thioredoxin, and dehydrins .
The early stages of fruit development, including fruit set and exponential growth, are clearly essential for all fruits. However, despite their importance as determinants of fruit size and yield, there has been little detailed analysis of this phase of development. Most studies to date, including recent transcriptomic studies, have focused on late development, or a broad range of developmental stages, with only a single snapshot during early development eg., [19–22]. In this study we combined morphological characterization with transcriptome analysis to provide new insight into important early fruit developmental stages and processes. Our observations, performed at five time points during the period from fruit set through the end of exponential fruit growth, indicate that this is a dynamic period of cucumber fruit development involving an array of internal and external morphological, physiological, and transcriptomic changes that act in concert with phases of active cell division, expansion, and response to the environment. Relative to anthesis and early fruit set, the period of peak- and late-exponential growth includes a large portion of highly represented transcripts, either of unknown function, or without homologs in Arabidopsis, suggesting unique factors contributing to the rapid growth phase in cucurbits. The end of exponential growth was marked by a shift in transcriptome profile characterized by abiotic and biotic stress related genes and significant enrichment for transcription factor gene homologs associated with stress response and development, suggesting that the interval between expansive growth and ripening may include a programmed transition toward enhanced defense.
Results and discussion
Morphological changes during early cucumber fruit development
At anthesis, the exocarp was dark green. Dark green/light green stripes and specks on the surface of the fruit began to emerge around 8 dpp. The fruit surface at anthesis also has a dull appearance due to ‘bloom’ (Figure 1B), a fine white powder primarily composed of silica oxide (SiO2) . The bloom disappeared first from the peduncle end around 4 dpp, then the blossom end by 8 dpp; by 12 dpp, it had disappeared completely, leaving a shiny fruit surface. The cuticle layer showed increased thickness with age. After 12 and 16 dpp it stained more darkly with Sudan IV, indicating increased cutin or wax content that appeared to penetrate between the pallisade cells in the epidermal layer (Figure 1C).
With respect to internal fruit morphology, both placenta and pericarp rapidly expanded from 4–16 dpp. The rate and amount of expansion was very similar for both tissues (Figure 1D). The mesocarp was initially green at 0 and 4 dpp, but became progressively lighter with age. Increase in mesocarp cell size is accompanied bv increased vacuolization between 4 and 12 dpp . The placenta tissue became gelatinous between 8 and 12 dpp and hardening of seed coats occurred between 12 and 16 dpp (Figure 1E).
454 pyrosequencing data
454 pyrosequencing analysis of cDNA libraries prepared from pericarp RNA samples of fruit harvested 0, 4, 8, 12, and 16 days post-pollination provided 1.13 million reads (Additional file 1: Table S1). The resulting data were assembled into 27,859 contigs with a mean length of 834 base pairs (bp). All transcripts were mapped to the assembled cucumber genome of Huang et al. , although in some cases more than one transcript mapped to the same location. The number of the reads per contig ranged from 2 to more than 14,000 with a mean of 67 reads per contig and median of 7 reads/contig. Assembed contig length increased steadily with the number of ESTs/contig, until approximately 30 reads/contig where it leveled off with an average length of approximately 1400 bp (Additional file 2: Figure S1). Similarly, frequency of identification of homologs in Arabidopsis increased with number of ESTs/contig, leveling off at approximately 90% with approximately 30 reads/contig (Additional file 2: Figure S1).
Functional annotation of transcripts represented by greater than 30 ESTs with homologs only identified in cucurbit species
Best BLASTX hit
26 kDa phloem protein [Cucumis sativus]
phloem filament protein; PP1; phloem protein 1 [Cucurbita maxima]
26 kDa phloem lectin [Cucumis sativus]
CRG16 (gibberelin responsive) [Cucumis sativus]
17 kDa phloem lectin [Cucumis sativus]
phloem lectin [Cucurbita argyrosperma subsp. sororia]
poly(A)-binding protein C-terminal interacting protein 6 [Cucumis sativus]
26 kDa phloem lectin [Cucumis melo]
galactose-binding type-2 ribosome-inactivating protein [Momordica charantia]
pathogen induced 4 protein [Cucumis sativus]
expressed protein [Cucumis melo]
pathogen-induced protein CuPi1 [Cucumis sativus]
seed nucellus-specific protein [Citrullus lanatus]
17 kDa phloem lectin [Cucumis sativus]
putative Gly-rich RNA-binding protein [Cucumis sativus]
26 kDa phloem lectin [Cucumis melo]
beta-caryophyllene synthase [Cucumis sativus]
profilin [Cucumis melo]
gag-protease polyprotein [Cucumis melo]
Changes in transcript abundance during early fruit growth
To validate usefulness of the 454 sequence data for analysis of transcript abundance, a set of fourteen genes representing different levels of EST representation/contig across the different fruit ages were selected for quantitative real time (qRT)-PCR analysis (Additional file 3 Figure S2). These included genes such as cyclin-dependent kinase B2;2 with high transcript levels early in development (0–4 dpp) or expansin A5 with higher transcript levels at 8–16 dpp. Comparison of transcript level at a given age relative to baseline expression at 0dpp (56 gene/time comparisons) showed good correspondence between values obtained by 454 sequencing and qRT-PCR (Pearson’s correlation, R2 = 0.85; Additional file 3: Figure S2). There was also good correspondence between the qRT-PCR results obtained from two different growth experiments in the greenhouse (R2 = 0.91), indicating biological reproducibility of patterns of gene expression across fruit ages, and validity of the use of frequency of EST representation in the 454 library as a measure of level of gene expression.
Principal component analysis (PCA) was performed on transcript levels among the libraries from the five fruit ages (Figure 2B). The first two components, which accounted for nearly 90% of the variation, separated the fruit ages into three groups, 0 and 4 dpp, 8 dpp, and 12 and 16 dpp. Examination of fruit growth rate indicated that these age groups correspond with cell division/pre-exponential growth, peak exponential expansion, and late/post-exponential expansion stages of growth, respectively (Figure 2C). Comparison of the transcripts present in each of the age groups showed that the great majority were detected in all three age groups. The fewest unique transcripts were present in the 8 dpp sample, consistent with a developmental gradient of transcription moving from 0–4 to 8 to 12–16 dpp. Both the PCA and Venn Diagram (Figure 2B,D) show the least commonality between the 0–4 and 12–16 dpp age groups.
Cucumber fruit contigs very highly expressed in only one age group (>0.1% representation) at 0–4, 8, or 12–16 dpp
Hit ID Arabidopsis
CRT3 (CALRETICULIN 3); calcium ion binding/unfolded protein binding
PIP3 (PLASMA MEMBRANE INTRINSIC PROTEIN 3); water channel
60S ribosomal protein L34 (RPL34A)
TUB3; GTP binding/GTPase/structural molecule
40S ribosomal protein S25 (RPS25B)
TPI (TRIOSEPHOSPHATE ISOMERASE); triose-phosphate isomerase
PORB (PROTOCHLOROPHYLLIDE OXIDOREDUCTASE B
60S ribosomal protein L17 (RPL17B)
ARS27A (ARABIDOPSIS RIBOSOMAL PROTEIN S27)
40S ribosomal protein S3A (RPS3aA)
ATLP-1; thaumatin-like protein
40S ribosomal protein S9 (RPS9C)
No hits found
60S ribosomal protein L36 (RPL36B)
protein transport protein SEC61 gamma subunit, putative
60S ribosomal protein L31 (RPL31C)
UBQ1 (UBIQUITIN EXTENSION PROTEIN 1)
RPS15AD (ribosomal protein S15A D)
No hits found
GDSL-motif lipase/hydrolase family protein
No hits found
phloem filament protein; PP1; phloem protein 1 [Cucurbita maxima]
ADF3 (ACTIN DEPOLYMERIZING FACTOR 3); actin binding
No hits found
integral membrane family protein
DYL1 (DORMANCY-ASSOCIATED PROTEIN-LIKE 1)
No hits found
No hits found
No hits found
proteasome maturation factor UMP1 family protein
No hits found
zinc finger (AN1-like) family protein
ATCXXS1; protein disulfide isomerase
protease inhibitor/seed storage/lipid transfer protein (LTP) family protein
No hits found
60S ribosomal protein L21 (RPL21C)
MEE59 (maternal effect embryo arrest 59)
ANNAT2 (Annexin Arabidopsis 2); calcium ion binding
No hits found
PSBR (photosystem II subunit R)
No hits found
ATBI1 (BAX INHIBITOR 1)
ATUBC2 (UBIQUITING-CONJUGATING ENZYME 2)
APX1 (ascorbate peroxidase 1); L-ascorbate peroxidase
No hits found
hypothetical protein [Vitis vinifera]
HSP18.2 (heat shock protein 18.2)
OASB (O-ACETYLSERINE (THIOL) LYASE B); cysteine synthase
carbohydrate kinase family
ELF5A-1 (EUKARYOTIC ELONGATION FACTOR 5A-1)
ATJ3; heat shock protein DNAJ homolog, protein binding
CPN20 (CHAPERONIN 20); calmodulin binding
CCR2 (COLD, CIRCADIAN RHYTHM, AND RNA BINDING 2)
ALDH2B4; 3-chloroallyl aldehyde dehydrogenase
DNAJ heat shock N-terminal domain-containing protein
HSP17.6II (17.6 KDA CLASS II HEAT SHOCK PROTEIN)
OASB (O-ACETYLSERINE (THIOL) LYASE B); cysteine synthase
zinc finger (AN1-like) family protein
TCTP (TRANSLATIONALLY CONTROLLED TUMOR PROTEIN)
No hits found
No hits found
26 kDa phloem lectin [Cucumis sativus]
Strikingly, genes with unknown function or without Arabidopsis homologs, dominated the group at 8 dpp, accounting for more than half of the contigs (14/27 genes, 52%).
The exponential growth stage of tomato also was associated with a larger proportion of ESTs with unknown function relative to other ages . Fewer genes with unknown function or without Arabidopsis homologs occurred in the 12–16 dpp group (5/21) and only 1 member of the 0-4dpp group had no assigned putative function or was without a homolog in Arabidopsis.
Fruit set/pre-exponential growth
The group of genes with peak abundance at the 8 dpp, exponential growth stage, included cytoskeleton, cell wall, and water and carbohydrate transport genes. Tubulins, actin-related proteins, extensins, expansins, cellulose synthases, pectinase modifying enzymes, aquaporins, vacuolar H+ATPases, and phloem filament and lectin proteins, were among those strongly represented, as has been observed for other rapidly growing fleshy fruits such as tomato, apple, grape, and watermelon [10, 13–15, 17, 18]. The major latex protein related genes also exhibited peak levels at 8 dpp, including two extremely highly transcribed genes that together accounted for more than 17,000 reads (Additional file 6: Table S4).
Putative homologs of vacuolar ATP synthase subunits B, D, H and P2 [TAIR:At4g38510, At3g58630, At3g42050, At1g19910] showed coordinate transcript abundance, with comparable levels increasing steadily until 8 dpp, and then gradually declining Two very highly represented homologs of the vacuolar aquaporin gene [TAIR:At2g36830], gamma tip tonoplast intrinsic protein, also peaked at 4-8dpp (Additional file 6 Table S4).
All of the cucurbit specific phloem proteins listed in Table 1 and the four putative homologs of the Arabidopsis phloem protein (ATPP) A2 family members observed in the data set peaked somewhat later, at 8–16 dpp with minimal transcript levels at 0 and 4 dpp (Figure 4D). Cucurbits are characterized by a unique and functionally divergent network of extrafascicular phloem external to the vascular bundles [28–30]. The highly expressed proteinaceous phloem filaments, comprised of the cucurbit-specific PP1 proteins, and the more widely distributed PP2 phloem lectin proteins , were found to be primarily associated with the extrafasicular phloem . Strong expression of phloem protein genes during rapid growth has been observed in other studies, including PP1 expression in green stage watermelon fruit [18, 31, 32]. Specific expression of PP2 (a group A member ) was observed in young pumpkin (Cucurbita pepo) hypocotyls, peaking at 12 days after germination in concert with the period of peak growth and vascular differentiation . In contrast, cucumber homologs of the ATPP2-B family had a nearly inverted pattern of transcript levels relative to PP2-A genes, peaking at 0 dpp, and dropping during exponential growth, suggesting possible functional divergence (Figure 4D).
The period of rapid fruit enlargement was also associated with marked changes in fruit surface, including an increase in cuticle thickness as is typically observed during rapid plant growth , and loss of the silica oxide powder based ‘bloom’. The homolog of the Cucurbita moschata silicon transporter [GenBank:327187680; ref. 23] showed age specific transcript abundance peaking at 8 dpp then dropping sharply, coinciding with the time of bloom loss from the middle of the fruit (the region from which samples were taken).
Among the genes identified in other systems to be associated with cuticle biosynthesis are the extracellular GDSL motif lipase/hydrolase proteins and lipid transfer proteins, which have been implicated in lipid transport to extracellular surfaces [33–36]. The cucumber fruit transcriptome set included eleven GDSL motif lipase/hydrolase protein family members that were represented by at least 30 ESTs, including five with more than 100 ESTs. The majority showed peak levels at 8 or 12–16 dpp, with virtually no measured reads until either 8 or 12 dpp (Figure 4B). Twelve lipid transfer protein (LTP) family members with greater than 30 ESTs/contig also were observed in the transcriptome data set, including four with greater than 700 ESTs. As for the GDSL motif lipase/hydrolase protein genes, the majority of the lipid transfer proteins were most highly represented from 8–16 dpp; transcript levels of one gene peaked at 4–8 dpp (Figure 4C).
A homolog of the transcription factor gene SHINE1 [TAIR:At1g15360], which is associated with cuticle production in Arabidopsis (Figure 4B)  also exhibited peak transcript abundance at 8 dpp. Additionally, transcript levels of two cyctochrome P450 family members (CYP86A and CYP77A) that have been associated with cutin biosynthesis ; and two putative beta amyrin synthases, enzymes which have been associated with cuticular wax synthesis in tomato , also peaked at 8dpp (Additional file 4: Table S2). In contrast, two putative GDSL family members and one lipid transfer protein with moderate transcript levels (45–55 ESTs) [homologs of TAIR:At5g62930, At5g03610, and At2g45180, respectively] were observed almost exclusively at 0 dpp, suggesting possible floral, rather than fruit, expression (Additional file 6: Table S4).
Late/post exponential growth
Stress-related genes (response to stress and response to abiotic and biotic stimulus categories) were over-represented at all stages, but considerably more so at 12–16 dpp than at the younger ages of 0–4 and 8 dpp (Figure 3B). The 12+16 dpp age group had the highest representation of abiotic and biotic stress related genes, including a variety of heat shock, redox, biotic defense and ethylene-related transcripts (Additional file 4: Table S2). Of the 120 genes in this group, 44 have high homology with genes associated with plant stress, including at least 13 transcription stress-related factors such as WRKY70 activator of SA-dependent defense; radical induced cell death; ethylene response, salt stress, and heat shock transcription factors (Figure 4E; Additional file 4: Table S2).
Overall, the group of genes with peak abundance at 12+16 dpp was significantly enriched for transcription factor genes (2.48-fold enrichment normalized frequency relative to Arabidopsis; P value = 3.19, E-04) (Figure 3B) accounting for 16% of the top 2.5% set. This may be contrasted with the total cucumber fruit transcriptome data set where transcription and transcription factor activity related genes were represented at a normalized frequency of 0.94 relative to occurrence in the Arabidopsis genome. Transcription factors in the top 2.5% of 0+4 and 8 dpp groups also were represented at a comparable frequency to the Arabidopsis genome, accounting for 3.7% and 4.6% of the gene list, respectively.
In addition to the stress related transcription factors with specific representation at 12–16 dpp, several putative transcription factor homologs were annotated to be associated with development [e.g., embryo sac development (BEL1-LIKE HOMEODOMAIN 1), morphogenesis (anac036/NAC domain containing protein 36), and cell expansion (ATHB-2 homeobox protein) (Additional file 4: Table S4). Furthermore, transcripts of other genes with homologs that have been implicated in development related processes are specifically observed at 12–16 days, such as putative homologs of TCTP (TRANSLATIONALLY CONTROLLED TUMOR PROTEIN); BTB AND TAZ DOMAIN PROTEIN 1; calcium-binding EF hand family protein; seed development related (E12A11); and BAX INHIBITOR 1.
Transcript representation in the youngest ages, 0–4 dpp, was uniquely characterized by genes associated with cell division, cell organization and biogenesis. At 4 dpp, transcription of the cell cycle genes was declining, while chloroplast, photosynthesis, and chloroplast-localized genes were peaking. Transcripts highly abundant during the exponential growth phase, 4–12 dpp, included extensive representation of genes associated with cell structure such as cytoskeleton, vacuoles and cell walls, along with surface lipid metabolism related genes, in concert with the period of greatest increase in cuticle thickness.
A second shift in the transcriptome profile was observed at 12–16 dpp with significant enrichment of abiotic and biotic stress related genes and stress-related and developmental transcription factor gene homologs. The enriched representation of numerous transcription factors relative to earlier ages suggests a programmatic change away from fruit growth, toward defense, and ultimately fruit maturation. This is also the time period where we have observed transition of cucumber fruit from susceptibility to resistance to P. capsici[8, 9]. Classically, fleshy fruit development is described to consist of three stages post pollination: cell division, cell expansion, and ripening . These results suggest that the interval between expansive growth and ripening may include further developmental differentiation; an emphasis on defense would be consistent with the role of fruit in protecting the developing seeds during embryo maturation prior to facilitating seed dispersal.
Finally, approximately 5% of the contigs represented by ≥30 reads either did not have identified putative homologs, or did not have homologs outside of cucurbits suggesting potentially unique genes specific to cucumber or cucurbits. The observation that these genes, as well as genes with homologs but with no annotated function, rarely occurred in the 0–4 dpp group, suggests commonality among processes associated with early fruit set and cell division and/or greater knowledge about the fruit set stage. The predominance of transcripts without non-cucurbit homologs or with unknown predicted functions during the peak exponential growth stage may reflect fewer studies to date about this phase of growth, or unique adaptations of cucurbits to allow for extreme fruit growth rates associated with these species.
Collectively, the transcriptomic information provided by the young cucumber fruit samples coupled with morphological analyses provide an informative picture of early fruit development characterized by phases of active cell division, fruit expansion including novel or uncharacterized genes, and response to the environment, as summarized in Figure 7. The progressive modules of transcript abundance tell a story of cell division, development of photosynthetic capacity, cell expansion and fruit growth, phloem activity, protection of the fruit surface, and finally transition away from fruit growth toward defense and maturation.
Plant material, fruit growth, chlorophyll and cuticle measurements
Sets of 80 cucumber plants per experiment (pickling type, cv. Vlaspik; Seminis Vegetable Seed Inc, Oxnard, CA) were grown in the greenhouse in 3.78 L plastic pots filled with BACCTO (Michigan Peat Co., Houston, TX) media and fertilized once per week. Temperature was kept between 21 to 25°C, supplemental lights were used to provide an 18 h light period. Pest control was performed according to standard management practices. All flowers for each experiment were hand pollinated on a single date (1–2 flowers per plant). The experiment was repeated three times. Prior to the harvests, which were performed at 4 day intervals from 0–16 dpp, fruit were measured for length and diameter, and examined for external appearances including: presence or absence of wax along the length of the fruit; wart development; color patterns (e.g., stripes); and changes in presence, color, and densities of spines. Pericarp and placenta size was measured from the cross section of the fruit after harvest.
Exocarp samples (upper 1 to 2 mm) for chlorophyll measurement were removed by fruit peeler from the center portion of five fruit at each age and stored at – 20°C. Samples were subsequently thawed at room temperature and blotted on paper to remove excess water and 1 g gram portions were immersed in N, N-dimethylformamide for at least 24 hours at 4°C in dark. Total chlorophyll was calculated based on spectrophotometer absorbance measurements at 665 and 647 nm . Samples to measure cuticle thickness were stained with Sudan IV(as per ) and measured using a Spot RT3 Digital Camera System at 200x magnification (SPOT Imaging Solutions, Diagnostic Instruments, Inc., MI).
cDNA library production and 454 sequencing
Randomly assigned groups of twenty fruit were harvested at 0, 4, 8, 12, and 16 dpp and ranked by size; the middle ten fruits were used for RNA extraction. Pericarp samples consisting of exocarp, mesocarp, and placenta tissue but not seeds, were isolated from the center portion of the fruit by razor blade, immediately frozen in liquid nitrogen, and stored at – 80°C until RNA was isolated. Samples from ten fruits were pooled for RNA extraction; RNA and oligo(dT)-primed cDNA sample preparation were based on the procedures of Schilmiller et al.  and Ando and Grumet . Final concentration was assessed by the nanodrop ND-1000 method and subsequent steps for 454 Titanium (0, 4, 1,2, 16 dpp) pyrosequencing analysis were performed by the Michigan State University Research Technology Support Facility (RTSF). Each sample was loaded on a 1/4 plate 454 Pico TiterPlate (454 Life Sciences, a Roche Corporation, CT). The 8 dpp sample was sequenced previously .
Contig assembly and gene annotation
Contigs were assembled by the MSU RTSF Bioinformatics Group. Reads were processed through The Institute for Genomic Research (TIGR) SeqClean pipeline to trim residual sequences from the cDNA preparation, poly(A) tails and other low quality or low complexity regions . Trimmed sequences were assembled into contigs using the TIGR Gene Indices Clustering Tools (TIGCL) . Stringent clustering and alignment parameters were used to limit the size of clusters for assembly. Contigs from the first pass of assembly were then combined and subjected to a second assembly pass with CAP3 . Less stringent alignment parameters were used for this pass to allow for minor sequencing errors or allelic differences in the cDNA sequence. Read data for 8 day post pollination samples is available from the Sequence Read Archive (SRA), accessible through NCBI BioProject ID PRJNA79541. Read data for 0, 4, 12 and 16 dpp samples in SRA as well as assembled contig sequences deposited as Transcriptome Shotgun Assemblies (TSA) and expression profiling data in the Gene Expression Omnibus (GEO) are available through NCBI BioProject ID PRJNA169904.
To estimate relative expression, the number of reads originating from each cDNA library were counted for each contig and reported relative to the total number of reads generated for that library as transcripts per thousand (TPT). The final contigs were subjected to BLASTX search against the green plant subdivision of the NCBI nr protein database and/or the Arabidopsis protein (TAIR9) databases to search for similarity to previously identified genes and assign possible gene functions. BLASTN analysis was performed for highly expressed contigs for which homologs were not identified by BLASTX searches.
The Classification SuperViewer Tool w/Bootstrap web database  was used for GO categorization, determination of normalized frequencies relative to Arabidopsis, and calculation of bootstrap standard deviations, and P-values. Princomp procedure SAS 9.1 (SAS Institute, Cary, NC) was used for principal component analysis. The first two principal components, which explain nearly 90% of the total variation were extracted from the covariance matrix. To examine relative gene expression at each age, the portion of reads for that transcript relative to total reads for the transcript, was calculated for each transcript with >30 reads, for each age. Expression profiles were clustered by K-means method using Cluster 3.0 software .
Total RNA was isolated and assessed for quality and quantity as above. RT reactions were performed using the High Capacity RNA-to-cDNA kit (Applied Biosystems, Foster City, CA). Gene-specific primers (Additional file 7: Table S5) were designed using Primer Express software. ABI Prism 7900HT Sequence Detection System was used for qRT-PCR analysis. Power SYBR Green PCR Master Mix (Applied Biosystems) was used for PCR quantification. Actin from C. sativus was used as an endogenous control and for normalization. Each qRT experiment was repeated three times. PCR products from each gene were quantified with reference to corresponding standard curves.
Days post pollination
Expressed Sequence Tag
Principal Component Analysis
quantitative Real Time PCR.
We thank Dr. Tony Schilmiller for assistance with the cDNA preparation protocol, Ms. Shari Tjugum-Holland of the Michigan State University Research Technology Support Facility for DNA pyrosequencing, Mr. David Munõz and the MSU Statistical Consulting Center for their help with PCA and other statistical analyses, Marivi Colle for microscopy and cuticle analyses, Victor Kayster for chlorophyll measurements, Sue Hammar and Matt Duncan for greenhouse assistance, and Drs. John Ohlrogge and Cornelius Barry for critical reading of the manuscript. This work was in part supported by USDA-SCRI Award No. 2008-51180-04881, the MSU Rackham Foundation, and the Pickle Packers International Agricultural Research Fund.
- Gillaspy G, Ben-David H, Gruissem W: Fruits: A developmental perspective. Plant Cell. 1993, 5: 1439-1451.PubMed CentralView ArticlePubMedGoogle Scholar
- Boonkorkaew P, Hikosaka S, Sugiyama N: Effect of pollination on cell division, cell enlargement, and endogenous hormones in fruit development in a gynoecious cucumber. Scientia Hortic. 2008, 116: 1-7. 10.1016/j.scienta.2007.10.027.View ArticleGoogle Scholar
- Fu FQ, Mao WH, Shi K, Zhou YH, Asami T, Yu JQ: A role of brassinosteroids in early fruit development in cucumber. J Exp Bot. 2008, 9: 2299-2308.View ArticleGoogle Scholar
- Marcelis LFM, Hofman-Eijer LRB: Cell division and expansion in the cucumber fruit. J Hortic Sci. 1993, 68: 665-671.Google Scholar
- Robinson RW, Decker-Walters DS: Cucurbits. 1997, CAB International, New York, NYGoogle Scholar
- Ando K, Grumet R: Transcriptional profiling of rapidly growing cucumber fruit by 454-pyrosequencing analysis. J Amer Soc Hortic Sci. 2010, 135: 291-302.Google Scholar
- Colle M, Shaaban M, Grumet R: Characterization of component factors associated with differences in cucumber fruit size and shape. HortSci. 2011, 46: S281-Google Scholar
- Ando K, Hammar S, Grumet R: Age-related resistance of diverse cucurbit fruits to infection by Phytophthora capsici. J Amer Soc Hortic Sci. 2009, 134: 176-182.Google Scholar
- Gevens AJ, Ando K, Lamour KH, Grumet R, Hausbeck MK: Development of a detached cucumber fruit assay to screen for resistance and effect of fruit age on susceptibility to infection by Phytophthora capsici. Plant Dis. 2006, 90: 1276-1282. 10.1094/PD-90-1276.View ArticleGoogle Scholar
- Lemaire-Chamley M, Petit J, Garcia V, Just D, Baldet P, Germain V, Fagard F, Mouassite M, Cheniclet C, Rothan C: Changes in transcriptional profiles are associated with early fruit tissue specialization in tomato. Plant Physiol. 2005, 139: 750-769. 10.1104/pp.105.063719.PubMed CentralView ArticlePubMedGoogle Scholar
- Pascual L, Blanca JM, Canizares J, Nuez F: Analysis of gene expression during the fruit set of tomato: a comparative approach. Plant Sci. 2007, 173: 609-620. 10.1016/j.plantsci.2007.07.006.View ArticleGoogle Scholar
- Wang H, Schauer N, Usadel B, Frasse P, Zouine M, Hernould M, Latche A, Pech J-C, Fernie AR, Bouzayen M: Regulatory features underlying pollination-dependent and -independent tomato fruit set revealed by transcript and primary metabolite profiling. Plant Cell. 2009, 21: 1428-1452. 10.1105/tpc.108.060830.PubMed CentralView ArticlePubMedGoogle Scholar
- Amemiya T, Kanayama Y, Yamaki S, Yamada K, Shiratake K: Fruit-specific V-ATPase suppression in antisense-transgenic tomato reduces fruit growth and seed formation. Planta. 2006, 223: 1272-1280. 10.1007/s00425-005-0176-x.View ArticlePubMedGoogle Scholar
- Janssen BJ, Thodey K, Schaffer RJ, Alba R, Balakrishnan L, Bishop R, Bowen JH, Crowhurst RN, Gleave AP, Ledger S, McArtney S, Pichler FB, Snowden KC, Ward S: Global gene expression of apple fruit development from the floral bud to ripe fruit. BMC Plant Biol. 2008, 8: 16-10.1186/1471-2229-8-16.PubMed CentralView ArticlePubMedGoogle Scholar
- Lee YP, Yu GH, Seo YS, Han SE, Choi YO, Kim D, Mok IG, Kim WT, Sung SK: Microarray analysis of apple gene expression engaged in early fruit development. Plant Cell Rep. 2007, 26: 917-926. 10.1007/s00299-007-0308-9.View ArticlePubMedGoogle Scholar
- Mascarell-Creus A, Canizares J, Vilarrasa-Blasi J, Mora-Garcia S, Blanca J, Gonzalez-Ibeas D, Saladie M, Roig C, Deleu W, Pico-Silvent B, Lopez-Bigas N, Aranda MA, Garcia-Mas J, Nuez F, Puigdomenech P, Cano-Delgado AI: An oligo-based microarray offers novel transcriptomic approaches for the analysis of pathogen resistance and fruit quality traits in melon (Cucumis melo L.). BMC Genomics. 2009, 10: 467-10.1186/1471-2164-10-467.PubMed CentralView ArticlePubMedGoogle Scholar
- Schlosser J, Olsson N, Weis M, Reid K, Peng F, Lund S, Bowen P: Cellular expansion and gene expression in the developing grape (Vitis vinifera L.). Protoplasma. 2008, 232: 255-265. 10.1007/s00709-008-0280-9.View ArticlePubMedGoogle Scholar
- Wechter WP, Levi A, Harris KR, Davis AR, Fei Z, Katzir N, Giovannoni JJ, Salman-Minkov A, Hernandez A, Thimmapuram J, Tadmor Y, Portnoy V, Trebitsh T: Gene expression in developing watermelon fruit. BMC Genomics. 2008, 9: 275-10.1186/1471-2164-9-275.PubMed CentralView ArticlePubMedGoogle Scholar
- Guo SG, Liu JG, Zheng Y, Huang MY, Zhang HY, Gong GY, He HJ, Ren Y, Zhong SL, Fei ZJ, Xu Y: Characterization of transcriptome dynamics during watermelon fruit development: sequencing, assembly, annotation and gene expression profiles. BMC Genomics. 2011, 12: 454-10.1186/1471-2164-12-454.PubMed CentralView ArticlePubMedGoogle Scholar
- Manganaris GA, Rasori A, Bassi D, Geuna F, Ramina A, Tonutti P, Bonghi C: Comparative transcript profiling of apricot (Prunus armeniaca L. fruit development and on-tree ripening. Tree Genet Genom. 2011, 7: 609-616. 10.1007/s11295-010-0360-4.View ArticleGoogle Scholar
- Portnoy V, Diber A, Pollock S, Karchi H, Lev S, Tzuri G, Harel-Beja R, Forer R, Portnoy VH, Lewinsohn E, Tadmor Y, Burger J, Schaffer A, Katzir N: Use of non-normalized, non-amplified cDNA for 454-based RNA sequencing of fleshy melon fruit. Plant Genome. 2011, 4: 36-46. 10.3835/plantgenome2010.11.0026.View ArticleGoogle Scholar
- Zenoni S, Ferrarani A, Giancomelli E, Xumerle L, Fasoli M, Malerba G, Bellin D, Pezzotti M, Delledonne M: Characterization of transcriptional complexity during berry development in Vitis vinifera using RNA-Seq. Plant Physiol. 2010, 152: 1787-1795. 10.1104/pp.109.149716.PubMed CentralView ArticlePubMedGoogle Scholar
- Mitani N, Yamaji N, Ago Y, Iwasaki K, Ma JF: Isolation and functional characterization of an influx silicon transporter in two pumpkin cultivars contrasting in silicon accumulation. Plant J. 2011, 66: 231-240. 10.1111/j.1365-313X.2011.04483.x.View ArticlePubMedGoogle Scholar
- Huang S, Li R, Zhang Z, Li L, Gu X, Fan W, Lucas WJ, Wang X, Xie B, Ni P, Ren Y, Zhu H, Li J, Lin K, Jin W, Fei Z, Li G, Staub J, Kilian A, van der Vossen EAG, Wu Y, Guo J, He J, Jia J, Ren Y, Tan G, Lu Y, Ruan J, Qian W, Wang M, Huang Q, Li B, Xuan Z, Cao J, San A, Wu Z, Ahang J, Cai Q, Bai Y, Zho B, Han Y, Li Y, Li X, Wang S, Shi Q, Liu S, Cho WK, Kim JY, Xu Y, Heller-Uszynska K, Miao H, Cheng Z, Zhang S, Wu J, Yang Y, Kang H, Li M, Liang H, Ren X, Shi A, Wen M, Jian M, Yang H, Zhang G, Yang Z, Chen R, Liu S, Li J, Ma L, Liu H, Zhou Y, Zhao J, Fang X, Li G, Fang L, Li Y, Liu D, Zheng H, Zhang Y, Qin N, Li Z, Yang G, Yang S, Bolund L, Kristiansen K, Zheng H, Li S, Zhang X, Yang H, Wang J, Sun R, Zhang B, Jiang S, Wang J, Du Y, Li S: The genome of the cucumber, Cucumis sativus L. Nature Genet. 2009, 41: 1275-1281. 10.1038/ng.475.View ArticlePubMedGoogle Scholar
- Provart N, Zhu T: A browser-based functional classification SuperViewer for Arabidopsis genomics. Curr Compu Molec Biol. 2003, 2003: 271-272.Google Scholar
- Van Leene J, Hollunder J, Eeckhout D, Persiau G, Van De Slijke E, Stals H, Van Isterdal G, Verkest A, Neirynck S, Buffel Y, De Bodt S, Maere S, Laukens K, Pharazyn A, Ferreira PCG, Eloy N, Renne C, Meyer C, Faure JD, Steinbrenner J, Beynon J, Larkin JC, Van de Peer Y, Hilson P, Kuiper M, De Veylder L, Van Onckelen H, Inze D, Witters E, De Jaeger G: Targeted interactomics reveals a complex core cell cycle machinery in Arabidopsis thaliana. Molec Sys Biol. 2010, 6: 37-Article 397Google Scholar
- Malladi A, Johnson LK: Expression profiling of cell cycle genes reveals key facilitators of cell production during carpel development, fruit set, and fruit growth in apple (Malus x domestica Borkh.). J Exp Bot. 2011, 62: 205-219. 10.1093/jxb/erq258.PubMed CentralView ArticlePubMedGoogle Scholar
- Clark AM, Jacobsen KR, Bostwick DE, Dannenhoffer JM, Skaggs MI, Thompson GA: Molecular characterization of a phloem specific- gene encoding the filament protein, phloem protein 1 (PP1), from Cucurbita maxima. Plant J. 1997, 12: 49-61. 10.1046/j.1365-313X.1997.12010049.x.View ArticlePubMedGoogle Scholar
- Turgeon R, Wolf S: Phloem transport: Cellular pathways and molecular trafficking. Annu Rev Plant Biol. 2009, 60: 207-221. 10.1146/annurev.arplant.043008.092045.View ArticlePubMedGoogle Scholar
- Zhang B, Tolstikov V, Turnbull C, Hicks LM, Fiehn O: Divergent metabolome and proteome suggest functional independence of dual phloem transport systems in cucurbits. Proc Nat Acad Sci USA. 2010, 107: 13532-13537. 10.1073/pnas.0910558107.PubMed CentralView ArticlePubMedGoogle Scholar
- Dinant S, Clark AM, Zhu YM, Vilaine F, Palauque JC, Kusiak C, Thompson GA: Diversity of the superfamily of phloem lectins (phloem protein 2) in angiosperms. Plant Physiol. 2003, 131: 114-128. 10.1104/pp.013086.PubMed CentralView ArticlePubMedGoogle Scholar
- Dannenhoffer JM, Schulz A, Skaggs MI, Bostwick DE, Thompson GA: Expression of the phloem lectin is developmentally linked to vascular differentiation in cucurbits. Planta. 1997, 201: 405-414. 10.1007/s004250050083.View ArticleGoogle Scholar
- Yeats TH, Howe K, Matas AJ, Buda GJ, Thannhauser TW, Rose JKC: Mining the surface proteome of tomato (Solanum lycopersicum) fruit for proteins associated with cuticle biogenesis. J Exp Bot. 2010, 61: 3759-3771. 10.1093/jxb/erq194.PubMed CentralView ArticlePubMedGoogle Scholar
- Mintz-Oron S, Mandel T, Rogachev I, Feldber L, Lotan O, Yativ M, Wang Z, Jetter R, Venger I, Adato A, Aharoni A: Gene expression and metabolism in tomato fruit surface tissues. Plant Physiol. 2008, 147: 823-851. 10.1104/pp.108.116004.PubMed CentralView ArticlePubMedGoogle Scholar
- Samuels L, Kunst L, Jetter R: Sealing plant surfaces: cuticular wax formation by epidermal cells. Annu Rev Plant Biol. 2008, 59: 683-707. 10.1146/annurev.arplant.59.103006.093219.View ArticlePubMedGoogle Scholar
- Suh MC, Samuels AL, Jetter R, Kunst L, Pollard M, Ohlrogge J, Beisson F: Cuticular lipid composition, surface structure, and gene expression in Arabidopsis stem epidermis. Plant Physiol. 2005, 139: 1649-1665. 10.1104/pp.105.070805.PubMed CentralView ArticlePubMedGoogle Scholar
- Aharoni A, Dixit S, Jetter R, Thoenes E, van Arkel G, Pereira A: The SHINE clade of AP2 domain transcription factors activates wax biosynthesis, alters cuticle properties and confers drought tolerance when overexpressed in Arabidopsis. Plant Cell. 2004, 16: 2463-2480. 10.1105/tpc.104.022897.PubMed CentralView ArticlePubMedGoogle Scholar
- Li-Beisson Y, Pollard M, Sauveplane V, Pinot F, Ohlrogge J, Beisson F: Nanoridges that characterize the surface morphology of flowers require the synthesis of cutin polyester. Proc Nat Acad Sci USA. 2009, 51: 22008-22013.View ArticleGoogle Scholar
- Wang ZH, Guhling O, Yao RN, Li FL, Yeats TH, Rose JKC, Jetter R: Two oxidosqualene cyclases responsible for biosynthesis of tomato fruit cuticular triterpenoids. Plant Physiol. 2011, 155: 540-552. 10.1104/pp.110.162883.PubMed CentralView ArticlePubMedGoogle Scholar
- Inskeep WP, Bloom PR: Extinction coefficients of chlorophyll a and b in N, N-dimethylformanide and 80% acetone. Plant Physiol. 1985, 77: 483-485. 10.1104/pp.77.2.483.PubMed CentralView ArticlePubMedGoogle Scholar
- Buda GJ, Isaacson T, Matas AJ, Paolillo DJ, Rose JK: Three-dimensional imaging of plant cuticle architecture using confocal scanning laser microscopy. Plant J. 2009, 60: 378-385. 10.1111/j.1365-313X.2009.03960.x.View ArticlePubMedGoogle Scholar
- Schilmiller AL, Schauvinhold I, Larson M, Xu M, Charbonneaua AL, Schmidt A, Wilkerson C, Last RL, Pichersky E: Monoterpenes in the glandular trichomes of tomato are synthesized from a neryl diphosphate precursor rather than geranyl diphosphate. Proc Nat Acad Sci USA. 2009, 106: 0865-10870.View ArticleGoogle Scholar
- The Institute for Genomic Research (TIGR).http://compbio.dfci.harvard.edu/tgi/software,
- Pertea G, Huang X, Liang F, Antonescu V, Sultana R, Karamycheva S, Lee Y, White J, Cheung F, Parvizi B, Tsai J, Quackenbush J: TIGR gene indices clustering tools (TIGCL): a software system for fast clustering of large EST databases. Bioinformatics. 2003, 19: 651-652. 10.1093/bioinformatics/btg034.View ArticlePubMedGoogle Scholar
- Huang X, Madan A: CAP3: A DNA sequence assembly program. Genome Res. 1999, 9: 868-877. 10.1101/gr.9.9.868.PubMed CentralView ArticlePubMedGoogle Scholar
- DeHoon MJL, Imoto S, Nolan J, Miyano S: Open source clustering software. Bioinformatics. 2004, 20: 1453-1454. 10.1093/bioinformatics/bth078. LINK http://bioinformatics.oupjournals.orgView ArticleGoogle Scholar
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