Plant material and treatments

Cherry tomatoes (Lycopersicon esculentum var. cerasiforme ‘XinTaiyang’) were grown in the greenhouses of Transfar Agriculture Co., Ltd (Xiaoshan, Zhejiang, China), which provided a standard culture temperature from 20°C to 25°C and relative humidity (RH) from 70% to 85%. With the permission of the company manager Li Laichun, fruits at mature green (MG) stage were harvested in June 2014 and immediately transported to the laboratory under ambient conditions. For sampling, fruit sepal and seeds were discarded and the dissected pericarps were quickly frozen in liquid nitrogen and stored at -80°C before subsequent analysis.

Effect of exogenous ABA and NDGA treatments on fruit ripening

The MG fruits of uniform size and free from external blemishes or infections were selected and divided into three groups in random. With the utilization of sterilized micro-syringe, the fruits of each group were uniformly injected with 25 μL aqueous solution of either ABA (10 mM) or NDGA (1 mM), and distilled water was served as the control. The injection method and the ABA/NDGA concentrations were applied as the optimum, which were obtained on the basis of a sum of preliminary experiments. After treatments, fruits were then stored at 20°C, 90% RH in the dark for 18 days. Fruits of each treatment were sampled every 3 days for measurement of ABA content, ethylene production, ACC content and ethylene biosynthesis enzymes. During the storage, samples on the 9^th day after treatments, corresponding approximately the breaker stage of tomato fruit ripening, were selected as the well characterized stage for RNA-sequencing, which presented the most evident distinctions in ripening process among the three treatments (Fig 1).

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Fig 1. Effects of exogenous ABA and NDGA treatments on tomato phenotypes and phytohormone-related physiological indexes during storage at 20°C.

(A) The morphological differences between the tomato fruits treated with exogenous ABA or NDGA and the non-treated fruits (CK). (B) Changes in ABA content as influenced by exogenous ABA and NDGA treatments during tomato ripening. (C) Changes in ethylene production as influenced by exogenous ABA and NDGA treatments during tomato ripening. (D) Effects of exogenous treatments on ACC content in tomato fruits. (E) Effects of exogenous treatments on ACS enzyme activities. (F) Effects of exogenous treatments on ACO enzyme activities. Vertical bars represents SE of three biological replicates, and asterisks (*) indicates significant difference (P < 0.05) between the value in ABA or NDGA treated fruits and that in control (CK).

https://doi.org/10.1371/journal.pone.0154072.g001

Effect of exogenous ABA and ABA+1-MCP treatments on fruit ripening

We also set another three groups of fruits to further explore the interplay mechanism between ABA and ethylene in ripening process. By using the injection method described above, the tomatoes of two groups were treated with 25 μL per fruit each of exogenous ABA (10 mM), and the third group of tomatoes was injected with the same amount of distilled water in control. Then one of the group injected with exogenous ABA was treated immediately with 2 μL L^-1 1-MCP for 8 h (preliminary tests have showed the concentration and treatment time of 1-MCP was an ideal method to block ethylene response). The required volume of 1-MCP gas was generated by adding water to powdered formulation in a 15 L desiccators with fruits sealed inside. To reduce experimental errors, the fruits of other two groups (CK and ABA) were also sealed in the same volume of airtight desiccators for the desired exposure period (8 h) respectively, but were not exposed to 1-MCP. Following the treatments, all the fruits were removed from the glassy container and then stored at 20°C, 90% RH. Samples of the three groups were collected every 3 days for the determination of the content of ABA and ethylene production.

Ethylene production

The rates of ethylene produced by whole fruit during ripening were determined according to Bu et al. with slight alterations [30]. Ten cherry tomatoes were enclosed in a 2.0 L airtight container for 2 h at 20°C. A headspace gas sample (1.5 milliliter) was withdrawn using a syringe, and then injected into a gas chromatography (SHIMADZU, GC-2014C PF, Japan) equipped with a flame ionization detector (FID), and a 2000×3 mm column of aluminum oxide at 85°C. Ethylene production was presented as μL∙Kg FW^-1∙h^-1, and the measurement was conducted in three replicates.

Determination of ACC content

ACC content was measured according to Zhang et al. with minor modifications. Powdered pericarp samples (1 g) were homogenized on ice in 10 ml 95% aqueous ethanol (v/v), and then centrifuged at 12000×g for 15 min at 4°C [2]. The supernatant was evaporated to dryness under vacuum at 40°C and the residue was dissolved in 5 ml distilled water. After oxidative conversion, ACC content was determined through ethylene production by gas chromatography (SHIMADZU, GC-2014C PF, Japan) as Lizada and Yang described [31]. ACC concentration of each sample was expressed in nmol∙g^-1 FW and the analysis was repeated three times.

Determination of ACS activity

The determination of ACS activity was based on the method of Li et al. [32]. Pericarp sample (1 g) was added into 5 ml 0.1 mol L^-1 phosphate buffer (pH = 8.0) containing 1 mmol L^-1 EDTA, 1 mmol L^-1 PMSF, 4 mmol L^-1 DTT, 3% PVPP and 10μmol L^-1 pyridoxal phosphate. The extracts were then centrifuged at 12000 × g for 15 min at 4°C. Then 0.5 ml supernatants were added into 1.5 ml HEPES-KOH buffer (pH = 8.0) which contained 250 μmolL^-1 SAM and 10 μmolL^-1 pyridoxal phosphate for further enzyme assays. The ACS activity was presented as nmol∙g^-1 FW∙h^-1, and the determination was conducted three times.

Determination of ACO activity

The method described by Zhang et al. was adopted to measure ACO activity [2]. Fruit pericarp sample (1g) was homogenized in 5 ml solution containing 0.1 M Tris-HCl pH 7.5, 10% glycerine, 30 mM sodium ascorbic acid, 5% polyvinylpyrrolidone (PVP), 5 mM dithiothreitol (DTT), 0.2 mM FeSO₄, and centrifuged at 12000 × g for 15 min at 4°C. Then 0.5 ml above solution was added into 1.5 ml enzyme solution which contained 10% glycerine, 30 mM sodium ascorbic acid, 2.0 mM ACC, 0.1 mM FeSO₄ and 30 mM NaHCO₃, kept at 30°C for half an hour. 1.5 mL headspace gas was injected into the gas chromatography for ACO activity measurement, and the unit was nmol∙g^-1 FW∙h^-1. The assay was conducted triplicates.

Determination of ABA content

ABA was extracted from 1.5 g fruit pericarp tissue using 20 ml 80% methanol (v/v) at 4°C for 12 h, mixed with 1% polyvinylpyrrolidone (PVPP, w/v) as an antioxidant. After centrifugation (12000 × g, 15 min), the supernatant liquid was evaporated under reduced pressure at 35°C. The residue was dissolved in 9 ml 10% methanol − 0.4% acetic acid, and was further eluted through a Sep-Pak C18 cartridge (Waters, Milford, MA, USA) to remove polar compounds. Then the collected solution containing free ABA was also evaporated under vacuum at 35°C. The resulting dried precipitate was dissolved in 1.5 ml of 50% methanol, finally filtered through a 0.45 μm filter membrane and submitted to high-performance liquid chromatography (HPLC, Shimadzu, Kyoto, Japan) for ABA analysis. The mobile phase consisted of 0.4% (v/v) acetic acid (solvent A) and 100% methanol (solvent B). It was eluted with a linear gradient of methanol (45%–60%) at a flow of 1 mL∙min^-1, and the detection wavelength of ABA was 260 nm. The external calibration curves were used for quantification.

RNA extraction, Library construction and Illumina sequencing

Two batches of tomatoes were harvested from two successive weeks in June 2014, which were independently subjected to exogenous treatments (ABA, NDGA and CK) respectively to represent as two biological replicates for sequencing. For each treatment, equal quantities of high-quality RNA which was extracted from 10 individual fruits in the same batch respectively were pooled to form one biological replicate, and so there were two biological replicates for RNA-seq analysis. Total RNA was extracted with the utilization of Total RNA Purification Kit, TRK1001 (LC Science, Houston, TX) following the manufacture’s protocol. Then the quantity and purity of total RNA were evaluated by Agilent 2100 Bioanalyzer and RNA 6000 Nano LabChip Kit (Agilent, CA, USA), and only the sample with RIN (RNA integrity number) ≥ 8.5 was identified as qualified. Magnetic beads with oligo (dT) were used to isolate poly (A) messenger RNA, and divalent cations were added to cut the mRNA into short fragments under elevated temperature. Taking the cleaved RNA fragments as templates, first- and second-strand cDNAs were synthesized using mRNA-Seq sample preparation kit (Illumina, San Diego, USA), and the average length for the final cDNA libraries was 300 bp (±50 bp). After that, the paired-ended sequencing was performed on the six samples (two biological replicates) by Illumina Hiseq2000platform at the LC-BIO (Hangzhou, China) following the vendor’s instruction, generating 374.73 million reads and totally 37.43 Gbps. All the raw sequence data has been deposited at NCBI Sequence Read Archive (SRA) with the accession number GSE75276.

Bioinformatics analysis

Raw reads obtained by Hiseq2000 were filtered to remove low quality reads (i.e. reads containing sequencing adapters; reads containing Ns (unknown sequence) > 5; nucleotide with q quality score lower than 20). The resulting clean reads were submitted for mapping analysis against the tomato genome (ftp://ftp.jgi-psf.org/pub/compgen/phytozome/v9.0/Slycopersicum/asse-mbly/) by using Tophat package [33]. The aligned reads were then processed by Cufflinks version 2.1.1, which were used for further differential expression analysis [33]. The relative abundance of genes was normalized with values for fragments per kilobase of exon per million fragments mapped (FPKM), and the genes expression level in each treatment was all expressed as the average of the two biological replicates. The pairwise comparing mRNA abundance of genes was performed in CK vs ABA and CK vs NDGA treatment, respectively. The genes were identified to be significantly differentially-expressed when their │log₂fold change│≥1 and P value <0.05, while the genes differed by less than 20% (│log₂ fold change│< 0.25) were deemed to not change in transcriptional level, and the other genes were assumed as slightly changed [25]. Besides, using the heatmap command in Multi Experiment Viewer 4.8 (MEV 4.8), the relative gene expression also can be analyzed by Z-score, which was determined according to the formula: Z = (X-μ)/σ, where X is the Log2-transformed relative FPKM value of a gene in a specific sample, and μ and σ represent the mean expression level and standard deviation (SD) of a gene across all samples, respectively [34,35].

Quantitative Real-Time PCR (qRT-PCR)

The qRT-PCR was used not only to measure the transcriptional abundance of genes involved in hormone biosynthesis and signaling across the time course, but also to verify the expression patterns of the 9^th day fruits revealed by the RNA-seq analysis. For each treatment at a specific time point, the total RNA was extracted from 10 randomly selected fruits and was subsequently blended at equal quantity. Then, the three pools of RNA (ABA, NDGA and CK), one representing each treatment at a specific time point, were reverse-transcribed to cDNA with RNA PCR kit (TaKaRa, Japan), respectively. The qRT-PCR was performed on ABI StepOne RT-PCR system in which cDNA was used in 10μL reaction with SYBR Premix ExTaq (TaKaRa, Dalian, China) following the manufacture’s procedure. The relative expressions of genes were calculated with 2^-ΔΔCT method by normalizing to the internal control gene β-actin (Accession NO.U60481.1) [36]. Three replicates were conducted in qRT-PCR analysis, and primer sequences for the analyzed genes were presented in S9 Table. With respect to the validation of transcriptiome data, Pearson’s correlation test was adopted to analyze the correlation significance of genes expression in ABA and NDGA-treated fruits relative to the CK between qRT-PCR and RNA-seq.

Correlation network analysis

A correlation network analysis of ABA and ethylene was conducted based on expression levels of the crucial genes and the physiochemical data, which were measured in different treatments at the key time points during ripening of Day 6, 9, 12 and 15. The present network was determined by the following parameters: the value of Pearson correlation coefficient (ρ), node strength (ns) and the network strength (NS) [37]. As the lines joining the nodes represented correlations, the positive correlations (ρ > 0) were shown in red, while the negative correlations (ρ < 0) were in blue. The edge thickness indicated the strength of the correlation, which was proportional to |ρ| of that particular pair [37]. The node size was proportional to ns which was the average of the |ρ| of a given node with all other nodes (ns = Avg |ρ|), and the NS was the mean of all node strengths (NS = Avg |ns|). The network diagram was visualized as “organic layout” by Cytoscape version 2.8.3 (www.cytoscape.org) [38].

Statistical analysis

For all the biochemical determinations, the statistical analysis were performed with SPSS software and the values were expressed as mean ± standard error (the error bars in figures represented SE of three biological replicates). The significant differences between the ABA or NDGA treatment and CK by the least significant difference test (LSD) for P< 0.05 were indicated with asterisks.

Effects of exogenous ABA/NDGA treatments on tomato ripening and fruit sampling for RNA-seq

Generally, significant physiological and morphological distinctions were observed among the tomatoes with different treatments during the 18 days’ storage (Fig 1). In comparison with control fruits, the application of ABA obviously accelerated ripening process including a series of relevant biological events which have been discussed in our previous study [10], whereas exogenous NDGA treatment led to a observable postponement of ripening in tomato fruits (Fig 1A). As expected, the ABA accumulation in ABA-treated fruits was considerably increased and reached the maximum level 3 days earlier than in control fruits (Fig 1B). In contrast, exogenous NDGA could significantly block the ABA biosynthesis, which consistently suppressed ABA content to a quite low level (Fig 1B). On the other hand, the ethylene production was substantially induced after ABA treatment and reached the peak at the 9^th day, which was precedent relative to that in CK fruits (Fig 1C). A noticeable reduction of ethylene was detected in NDGA-treated fruits, but the inhibition by NDGA was alleviated in the later ripening stage because of the limited period of time for NDGA effectiveness (Fig 1C). As precursor of ethylene, the alterations of ACC content showed a similar trend as ethylene production in response to ABA/NDGA treatments (Fig 1D), consistent with the changes of ACS and ACO activities affected by exogenous applications (Fig 1E and 1F). Based on the results described above, we therefore selected the fruits sampled at the 9^th day, which on average corresponded to around beaker stage of tomato fruit (Fig 1A), as the key time point for RNA-seq analysis, to further investigate the molecular mechanism underlying the influence of ABA on its biosynthetic and signaling pathway as well as that of ethylene during fruit ripening.

A snapshot of tomato mRNA profiling with exogenous treatments

To conduct comparative transcriptome analysis of tomato in response to exogenous applications of ABA and NDGA during fruit ripening, we adopted RNA-seq to generate expression profiles for each of the three groups (ABA, NDGA and CK). Two independent biological replicates were collected for each group, and the principle component analysis (PCA) revealed relatively low biological variability within individual replicates (S1A Fig). After filtering low quality reads, the clean reads ranging from 46.07 to 79.43 million for each cDNA library were mapped to the tomato genome sequence SL2.40 (ITAG2.3) with Tophat (S1 Table) [39]. As shown in S1 Table, 43.21–60.05 million reads were aligned to the reference sequence, accounting for 93.17% of the total reads. Besides, an average of 89.98% of CK, 90.10% of ABA and 89.92% of NDGA reads were matched to a unique genomic location in tomato genome (S1 Table). In our data, a total of 31571 genes expressed in the tomato fruit transcriptome, including 28399 genes in CK, 28161 in ABA and 29875 in NDGA, respectively (S2 Table). In the comparison between CK and ABA-treated samples, the expression of 1256 genes were found to be significantly changed (│log2 fold change│ ≥ 1 and P value < 0.05), including 358 up-regulated and 898 down-regulated genes (S3 Table, S1B Fig). After the treatment with exogenous NDGA, 1091 genes were significantly altered in transcription level compared with control fruits, including 818 up-regulated and 273 down-regulated genes (S4 Table, S1B Fig). With regard to the DEGs, there were more down-regulated genes than up-regulated ones in ABA treatment and the reverse were found in NDGA treatment (S1 Fig), which implied that many genes may respond negatively to ABA in tomato fruit.

To obtain insights into the transcriptional regulatory mechanism of ABA in depth, we identified 1343 transcription factor (TF) genes from 57 families (S5 Table, S2A Fig) according to the PlantTFDB database (http://planttfdb.cbi.pku.edu.cn) by BLAST [40]. Among the detected TFs, a total of 122 genes were differentially expressed in response to exogenous treatments (72 DEGs in ABA and 53 DEGs in NDGA treatment) (S5 Table). Most TFs were down-regulated in ABA-treated fruits and induced by NDGA application, including the genes with well-known involvement in fruit ripening, such as AP2, C2H2, ERF, G2-like, HD-ZIP, MIKC, MYB-related and SBP families (S2A and S2B Fig) [41,42].

The overall expression profiles of ABA metabolism and signaling genes

From RNA-seq data, a total of 84 genes involved in ABA metabolism and signal transduction were identified (Fig 2A, S6 Table). In the ABA biosynthetic pathway (Fig 3), zeaxanthin was epoxidized to violaxanthin by ZEP in a two-step oxidation [43], and the synthesized violaxanthin is subsequently converted to neoxanthin with the catalysis of NSY [44]. NCED functions as a rate-limiting enzyme for ABA biosynthesis, which catalyzes oxidative cleavage of carotenoid to produce C15 intermediate xanthoxin [45]. Then with the reduction of SDR, xanthoxin is converted to ABA-aldehyde [46], which finally forms ABA after oxidation by AAO3 [47]. Besides, molybdenum cofactor (MoCo), which is encoded by ABA3, has been reported to be essential for the catalytic activity of AAO3 [48]. In total, there were 1 ZEP, 3 NSYs, 5 NCEDs, 6 SDRs, 2 AAO3s and 1 ABA3 identified in our transcriptome data (Fig 2A, S6 Table). As the first step of ABA biosynthesis [49], the transcription abundance of LeZEP was significantly down-regulated in ABA treatment, and slightly up-regulated from 27.79 to 43.00 FPKM in NDGA treatment (Fig 3, S6 Table). Although LeNCED1 has been reported as the key gene involved in ABA biosynthesis [50], our data have detected other two NCEDs showing significantly different expression levels in response to exogenous ABA/NDGA treatments. The NCED4 homologue (Solyc08g075490.2) was observed more highly expressed in NDGA-treated fruits (from 0.69 to 2.39 FPKM) accompanied by slight repression in ABA treatment (Fig 3, S6 Table). Similarly, an obviously lower level of LeNCED2 (Solyc08g016720.1) transcripts was detected after ABA application, while the expression was slightly induced 1.46 fold in the fruits treated with NDGA (Fig 3, S6 Table). As for the other genes encoding key elements in ABA biosynthesis, there was not a great deal of difference in transcription with external applications of ABA/NDGA (S6 Table).

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Fig 2. The overall transcriptional profiles of genes involved in biosynthesis and signaling of ABA and ethylene, respectively.

(A) The Fig showed an overview of genes expression related to ABA biosynthesis, deactivation and signaling in different treatments. (B) The Fig showed an overview of genes expression related to ethylene biosynthesis and signaling in different treatments. Analysis of the relative gene expression value (Z-score) was performed using the heatmap command in MEV 4.9.0. Red and green colors indicate relative higher and lower expression values, respectively.

https://doi.org/10.1371/journal.pone.0154072.g002

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Fig 3. Analysis of DEGs involved in the pathway of ABA biosynthesis, deactivation and signaling.

Abbreviations are listed in S10 Table, and other details are the same as in Fig 2.

https://doi.org/10.1371/journal.pone.0154072.g003

The pathways of ABA catabolism are mainly categorized into two types, oxidation and conjugation (Fig 3) [51]. The predominant step of oxidative degradation is the hydroxylation at 8’ position of ABA to yield 8’-OH-ABA, which is mediated by CYP707A (ABA8OX) [52,53]. Even though LeCYP707A2 has been accepted as the key gene in regulating ABA catabolism [50], the LeCYP707A1 (Solyc04g078900.2) was identified as DEG in our data, which showed considerable down-regulation from 2.43 to 0.37 FPKM by ABA, and slight elevation by 1.76 fold in NDGA treatment (Fig 3, S6 Table). In addition, the formation of ABA conjugates (i.e. ABA-GE and ABA-GS) appears to be an alternative means for ABA deactivation [54], and the ABA glucosylation can be catalyzed by UGT [55]. In our data, the expression of UGT73B3 homologue showed significant up-regulation with the application of ABA, and slight decline from 281.88 to 166.83 FPKM in NDGA treatment (Fig 3, S6 Table).

Recent studies have led to the construction of a core ABA signaling pathway (PYR/PYL/RCAR-PP2C-SnRK2) (Fig 3), which emerged as a double negative regulatory module [56]. In the absence of ABA, clade A PP2Cs physically interact with Subclass III SnRK2s, and efficiently repress the ABA signaling via dephosphorylation of SnRK2s [57]. However, the PP2C-dependent negative regulation are disrupted when ABA binds to PYR/PYL/RCAR receptors, allowing SnRK2s activation and subsequent phosphorylation of downstream targets (e.g ABF/AREBs) to trigger various ABA-induced physiological responses [58]. Among the 15 genes of ABA receptors (PYR/PYL/RCAR), one homologue of PYL9/RCAR1 (Solyc08g082180.2) was identified as DEG, showing remarkably increased expression in ABA (2.16 fold) and little decreased level in NDGA-treated samples (Fig 3, S6 Table). Group A of PP2Cs have been reported as major negative regulators of ABA signaling [57], six members of which (i.e. ABI2, HAB1, AHG3, AHG1, HAI2 and HAI3) were identified in our sequencing data (S6 Table). Of the 14 PP2Cs, one HAI2 homologue (Solyc06g051940.2) was significantly down-regulated upon treatment with ABA, and slightly induced from 5.19 to 6.95 FPKM in NDGA treatment (Fig 3, S6 Table). With respect to the proteins belonging to Subclass III of SnRK2 family [59], only the genes encoding SRK2I (SnRK2.3) and SRK2E (OST1/SnRK2.6) were detected in tomato transcriptome (S6 Table). Although no significant difference was observed in SnRK2s expression with exogenous applications, most of them were slightly induced by ABA (from 1.14 to 1.34 fold) and repressed in NDGA treatment (from 1.26 to 1.70 fold) (S6 Table). In addition, the transcription of SnRK2 phosphorylation targets (e.g. ABI5, AREB1/ABF2 and AREB2/ABF4 etc.) did not seem to be affected much by external treatments either (S6 Table).

The overall expression profiles of ethylene biosynthesis and signaling genes

A total of 78 genes related to ethylene biosynthesis and signal transduction were detected in our study (Fig 2B, S7 Table). Ethylene synthesis begins with the formation of SAM from methionine (Fig 4), with the catalyzation of SAMS [60]. By the action of ACS, SAM can be subsequently converted to ACC and finally form ethylene via the catalysis of ACO [61] (Fig 4). All the key enzymes of ethylene biosynthesis are encoded by multigene families, and 4, 9 and 6 genes are annotated with the function as SAMS, ACS and ACO, respectively (S7 Table). From sequencing data, 2 SAMSs (Solyc01g101060.2 and Solyc10g083970.1) were identified as DEG, both of which were evidently repressed by ABA, and slightly enhanced in NDGA-treated fruits (Fig 4, S7 Table). With regards to ACSs, the LeACS4 (Solyc05g050010.2) showed remarkable up-regulation in ABA coupled with moderate reduction in NDGA treatment, and similar alteration was also observed in one analogue of ACS6 (Solyc08g079750.2) (Fig 4, S7 Table). It has been reported that LeACS2 (Solyc01g095080.2) encodes a crucial speed-restricting enzyme of ethylene synthesis in tomato fruit [62]. Our results showed that the expression of LeACS2 was considerably induced 2.29 fold with ABA application and exhibited 2.6 fold reduction in NDGA treatment (Fig 4, S7 Table). Since the genes of ACO family have been reported to show different expression patterns in tomato ripening [63,64], a consistent phenomenon was also observed in our result (S7 Table). Of the six ACOs, the transcription of LeACO1 (Solyc07g049530.2) in our data was coincide with numerous studies showing the highest abundance among all ACOs during tomato ripening [63,65], and the it was detected to be up-regulated from 2156.94 to 3828.27 FPKM in ABA and reduced approximate 4.0 fold at expression level upon NDGA application (Fig 4, S7 Table). However, the other two ACOs (Solyc07g026650.2 and Solyc02g036350.2) showed significant decrease in expression with exogenous ABA as well as slight increase with NDGA (Fig 4, S7 Table).

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Fig 4. Analysis of DEGs involved in the pathway of ethylene biosynthesis and signaling.

Abbreviations are listed in S10 Table, and other details are the same as in Fig 2.

https://doi.org/10.1371/journal.pone.0154072.g004

Considerable genetic and biochemical analyses have contributed to the generation of a primarily linear model for ethylene signaling, which starts from ethylene perception at the membrane and ends with transcriptional regulation in the nucleus (Fig 4) [66]. In the absence of ethylene, the ETR1 can be positively regulated by RTE1 to form receptor-CTR1 complex, which subsequently inhibits the interaction between receptors and EIN2 [67,68]. Of the two genes homologous to Arabidopsis RTE1 identified in our data, one RTE1 paralog (also called as LeGr, Solyc01g104340.1) was more abundantly expressed in NDGA treatment (from 2.05 to 9.54 FPKM), and slightly repressed 1.79 fold by ABA (Fig 4, S7 Table). In Arabidopsis, two F-box proteins ETP1/2 have been assumed to target EIN2 for degradation via 26S proteasome-dependent pathway [69]. However, there were no ETPs detected in tomato transcriptome (S2 Table). The activated CTR1 can directly phosphorylate the C terminal of EIN2, thus preventing signaling to downstream components [70]. Additionally, CTR1 also functions as a Raf-like MAPKKK and activates an unknown MAPK cascade to degrade EIN3 by phosphorylation, which finally suppresses ethylene response [71]. In the presence of ethylene, the receptors bind the hormone with the help of copper cofactor that is supplied by copper transporter RAN1 [72]. Then the receptor complex is disassociated concomitant with inactivated CTR1 releasing from ER membrane, which relieves the suppressive state of EIN2 [70]. The C end of EIN2 is cleaved off and translocates to nuclear where it stabilizes EIN3/EILs and initiates transcriptional response of ERFs [73]. In our study, eight genes homologous to ethylene receptors, and three each for CTR1 and EIN2 as well as six for EIN3/EIL were detected in tomato transcriptome (S7 Table). The LeETR6 (Solyc09g089610.2) was found to be significantly down-regulated in ABA treatment (Fig 4), whose reductions in expression has been reported as critical induction for ethylene response [74]. However, no obvious changes at transcription level of CTR1s, EIN2s and EIN3/EILs were observed in our study (S7 Table), indicating exogenous ABA or NDGA applications had inconspicuous effect on their expression. Among 41 expressed ERFs, LeERF2 (Solyc09g075420.2), LeERF3 (Solyc10g009110.1) and LeERF4 (Solyc05g052030.1) were identified to be significantly down-regulated by ABA treatment, and one ERF4 homologue (Solyc03g006320.1) was expressed 2.56 fold higher in NDGA treatment (Fig 4, S7 Table). Upon ethylene perception, dual MAPK cascades downstream of CTR1 have emerged as positive regulators in ethylene signaling [75]. The activation of MKK9-MPK3/6 module can promote EIN3 stabilization [71], and MKK4/5-MPK3/6 cascade leads to ACS2/6 accumulation which consequently enhances ethylene production [76]. The expression level of MKK9 paralog (also called as LeMKK4, Solyc03g097920.1) was weakly suppressed from 10.86 to 7.00 FPKM by ABA and little induced to 19.69 FPKM with NDGA treatment (S7 Table). In contrast, MKK4 homologue exhibited slight increase in expression by ABA and moderate reduction by NDGA (S7 Table). The downstream MPK6 and MPK3 homologues were found to be either slightly up- or down-regulated by ABA but both remain relatively constant in NDGA-treated fruits (S7 Table). Additionally, LeEBFs and LeXRN4, which encode post-translational regulators in ethylene signaling, did not differ in transcription abundance with exogenous ABA/NDGA treatments (S7 Table).

RT-PCR analysis of representative genes related to ABA metabolism and signaling at different ripening stages

From RNA-seq data of fruits sampled at the 9^th day, the identified DEGs were primarily regarded as representative genes for further analysis of dynamic expression patterns (S6 Table). In this study, three ABA biosynthetic genes and two deactivation related genes were selected to investigate transcription abundance at different time points of fruit ripening (Fig 5A–5E). Compared with CK, LeZEP (Solyc02g090890.2) was down-regulated by ABA treatment during ripening process, whereas the expression level in NDGA-treated fruits was significantly higher than that in control throughout all time points (Fig 5A). With respect to the NCED4 homologue (Solyc08g075490.2) and LeNCED2 (Solyc08g016720.1), the overall expression patterns were observed similar in response to different treatments (Fig 5B and 5C). In the early stage of ripening, the expression of NCED4 homologue and LeNCED2 were obviously elevated by exogenous ABA and reached a maximum level at the 6^th day (Fig 5B and 5C). Upon NDGA treatment, both of them were immediately suppressed at the 3^rd day, and subsequently showed a transitory increase between the 6^th day and 9^th day (Fig 5B and 5C). LeCYP707A1 (Solyc04g078900.2) was involved in the oxidative degradation of ABA, whose transcription exhibited a continuously decreased trend as fruits ripened (Fig 5D). In comparison with CK, the gene in NDGA-treated fruit showed a delayed decline at expression level, while exogenous ABA accelerated the down-regulation of LeCYP707A1 (Fig 5D). On the contrary, the expression of UGT73B3 homologue, which functions in the formation of conjugated ABA, was considerably induced by ABA and repressed in NDGA treatment (Fig 5E). After application with exogenous ABA/NDGA, the homologues of PYL9 (Solyc08g082180.2) and HAI2 (Solyc06g051940.2) were detected to be differentially expressed in ABA signaling pathway (S6 Table). As an important receptor of ABA, up-regulation of PYL9 paralog in ABA treatment was concomitant with down-regulation in NDGA-treated fruits throughout all ripening stages (Fig 5F). HAI2 was known as a main negative regulator in ABA signaling, and its expression showed a reduction in ABA treatment and a significant increase in response to NDGA during ripening process (Fig 5G).

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Fig 5. The expression of DEGs related to ABA metabolism and signaling in CK, ABA and NDGA-treated fruits at different ripening stages.

RT-PCR analysis of ZEP (A), NCED4 (B), NCED5 (C), ABA80X (D), UGT73B3 (E), PYL9 (F) and HAI2 (G) were conducted in CK vs ABA and CK vs NDGA treatment. Numbers under the x-axis represents the different time points during fruit ripening while y-axis shows relative expression in folds between CK and ABA/NDGA-treated fruits. Error bars represents SE of three biological replicates, and asterisks (*) indicates significant difference (P < 0.05) between the value in ABA or NDGA treated-fruits and that in control (CK).

https://doi.org/10.1371/journal.pone.0154072.g005

RT-PCR analysis of representative genes related to ethylene biosynthesis and signaling at different ripening stages

In the sequencing analysis, seven genes related to ethylene biosynthesis were found to be differentially expressed after exogenous ABA or NDGA treatments, including two SAMs, two ACSs and three ACOs (S7 Table). In contrast with CK, the expression of LeSAM1 (Solyc01g101060.2) was considerably reduced by ABA and more abundant in NDGA-treated fruits at most developmental stages (Fig 6A). Distinct from LeSAM1, the transcript level of SAM3 homologue (Solyc10g083970.1) showed a great increase with exogenous ABA and reached the peak at the 3^rd day, but it subsequently declined obviously through the remaining stages of ripening (Fig 6B). However, an obviously delayed expression was observed in NDGA treatment throughout fruit ripening (Fig 6B). From the RT-PCR data, the expression of LeACS2 (Solyc01g095080.2) was detected with significant up-regulation by ABA and suppression by NDGA across the ripening time course (Fig 6C and 6D). Similar to LeACS2, the transcript abundance of LeACS4 (Solyc05g050010.2) was also significantly enhanced by ABA treatment over the entire period of fruit ripening (Fig 6C). Nevertheless, the LeACS4 transcription was considerably repressed by NDGA application until the 9^th day, and then began to increase at the later ripening stage (Fig 6C), which was probably in correlation with the increased ethylene production from Day 9 as the NDGA inhibitory effectiveness gradually eliminated (Fig 1C). Compared with CK, the peaks of these two ACSs transcription abundance were also advanced by about 3 days with the treatment of ABA. Among the three ACOs, LeACO1 (Solyc07g049530.2) was expressed at the highest abundance, which was induced by ABA at all time points and continuously repressed by NDGA until the later stage of ripening (Fig 6G). Although fluctuated expression was observed in other two ACOs (LeACO5 and the ACO4 homologue) by exogenous treatments, both of their expression remained at quite low levels during tomato ripening (Fig 6E and 6F). Therefore, it can be supposed that LeACO1 may play a predominant role among the three ACOs involved in the regulation of ethylene biosynthesis by ABA. With regard to ethylene signaling, five DEGs were selected for examination of expression level at various ripening stages (S7 Table). As a negative regulator in signal transduction, the expression of LeGR was remarkably inhibited by exogenous ABA and accumulated in a much higher amount with NDGA application (Fig 6H). At the early stage of ripening (Day 3–6), LeETR6 (Solyc09g089610.2) was more highly expressed in ABA treatment, but at later stage (Day 12), the gene began to show increased transcription in NDGA-treated fruits (Fig 6I). Among all LeERFs analyzed in tomato fruits, LeERF2 (Solyc09g075420.2) has been reported as the only one to exhibit ripening-associated expression [77,78]. The expression of the LeERF2 was found to be highly expressed at the early stage by exogenous ABA and at the later stage by NDGA treatment (Fig 6J). Intriguingly, the expression of ERF4 homologue (Solyc03g006320.1) was significantly down-regulated by ABA and induced by NDGA through all ripening stages (Fig 6K). While the LeERF3 did not show consistent repression or activation by exogenous treatments, implying it may not be the crucial genes regulated by ABA in ethylene signaling pathway.

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Fig 6. The expression of DEGs related to ethylene biosynthesis and signaling in CK, ABA and NDGA-treated fruits at different ripening stages.

RT-PCR analysis of SAM1 (A), SAM3 (B), ACS1 (C), ACS2 (D), ACO1 (E), ACO4;1 (F), ACO4;2 (G), RTE1 (H), ETR2 (I), EBP (J), ERF4;1 (K) and ERF4;2 (L) were conducted in CK vs ABA and CK vs NDGA treatment. Other details are the same as in Fig 5.

https://doi.org/10.1371/journal.pone.0154072.g006

Exploration of the interaction between ABA and ethylene in fruit ripening

Contrary to the accelerated ripening found in ABA treatment alone, the fruits with ABA+1-MCP application were observed to be remarkably deferred in ripening progress (Fig 7A). The ABA accumulation in ABA+1-MCP treatment remained at a low level until day 9, and then increased rapidly to reach the peak on day 12, which was significantly delayed relative to that of CK and ABA-treated fruits, respectively (Fig 7B). However, there was no marked difference in the maximum level of ABA content between the fruits treated with ABA alone and together with 1-MCP, both of which were apparently higher than that in control fruits (Fig 7B). On the other hand, ethylene production in ABA+1-MCP group was almost completely blocked by 1-MCP for a quite long period (about 9 days after treatment), and then gradually increased to the peak level which was parallel with that in ABA-treated fruits (Fig 7C).

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Fig 7. Effects of exogenous ABA and ABA+1-MCP treatments on tomato phenotypes and phytohormone contents during storage at 20°C.

(A) The morphological differences between the tomato fruits treated with exogenous ABA or ABA+1-MCP and the non-treated fruits (CK). (B) Effects of exogenous ABA and ABA+1-MCP treatments on ABA content during tomato ripening. (C) Effects of exogenous ABA and ABA+1-MCP treatments on ethylene evolution during tomato ripening. Other details are the same as in Fig 1.

https://doi.org/10.1371/journal.pone.0154072.g007

In contrast to the fruits treated with ABA alone, the transcription of the genes LeZEP, NCED4 homologue and LeNCED2 were considerably up-regulated by ABA+1-MCP over the entire period of ripening (Fig 8A–8C). With respect to ABA catabolism, the expression of LeCYP707A1 was induced in ABA+1-MCP group (Fig 8D), whereas significant repression was found in UGT73B3 paralog after the co-application of 1-MCP (Fig 8E). Regarding to the expression of PYL9, the continuous up-regulation by exogenous ABA was substantially weakened upon the treatment with 1-MCP (Fig 8F). However, HAI2 was highly expressed in ABA+1-MCP group throughout fruit ripening, contrary to the down-regulation by ABA treatment (Fig 8G). As an effective inhibitor of ethylene, 1-MCP remarkably suppressed all the representative genes involved in ethylene biosynthesis at all ripening stages with exception of LeSAM1 and SAM3 homologue (Fig 9A–9G). Furthermore, expressions of LeETR6 and LeERF2 which were involved in ethylene signaling remained at consistent low levels after 1-MCP treatment (Fig 9I and 9J). However, the expression of ERF4 homologue was observed to be repressed by ABA treatment and up-regulated by ABA+1-MCP over the entire period of ripening (Fig 9K). Compared with ABA treatment alone, however, increased expression of LeGR was observed in ABA+1-MCP treated fruits during ripening process (Fig 9H, 9K and 9L).

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Fig 8. The expression of DEGs related to ABA metabolism and signaling in CK, ABA and (ABA+1-MCP)-treated fruits at different ripening stages.

RT-PCR analysis of ZEP (A), NCED4 (B), NCED5 (C), ABA80X (D), UGT73B3 (E), PYL9 (F) and HAI2 (G) were conducted in CK vs ABA and CK vs ABA+1-MCP treatment. Other details are the same as in Fig 5.

https://doi.org/10.1371/journal.pone.0154072.g008

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Fig 9. The expression of DEGs related to ethylene biosynthesis and signaling in CK, ABA and (ABA+1-MCP)-treated fruits at different ripening stages.

RT-PCR analysis of SAM1 (A), SAM3 (B), ACS1 (C), ACS2 (D), ACO1 (E), ACO4;1 (F), ACO4;2 (G), RTE1 (H), ETR2 (I), EBP (J), ERF4;1 (K) and ERF4;2 (L) were conducted in CK vs ABA and CK vs ABA+1-MCP treatment. Other details are the same as in Fig 5.

https://doi.org/10.1371/journal.pone.0154072.g009

RNA-seq analysis of ripening-related TFs under exogenous ABA/NDGA treatments

Recent efforts have identified some key TFs for the positive regulation of tomato ripening, including MADS-RIN[79], TAGL1 [80], FUL1 [81], FUL2 [81], CNR [82], NOR [13] and HB-1[83]. In our study, the expression of LeFUL1 was significantly elevated by exogenous ABA, and moderately down-regulated by 1.93 fold with NDGA treatment (S8 Table). MADS-RIN is considered to be an essential regulator of tomato fruit ripening [79], which displayed a slightly up-regulated expression in ABA-treated fruits (1.79 fold), and reduced from 671.87 to 396.67 FPKM by NDGA (S8 Table). Similar patterns of altered expression were also observed in the genes encoding TAGL1, FUL2, CNR and NOR under the different exposures (S8 Table). However, LeHB-1 was expressed at a level 1.48 fold lower in ABA treatment, which was different from the above TF genes (S8 Table). On the other hand, MADS1 has been reported to impact fruit ripening as repressive modulators [84]. Our data showed that the transcription of MADS1 was considerably down-regulated by exogenous ABA and did not differ in NDGA treatment (S8 Table).

qRT-PCR validation of the changes in gene expression from RNA-seq data

In order to confirm the accuracy of RNA-seq results, a total of 35 genes with different expression patterns were selected for qRT-PCR validation, including the 19 representative genes involved in the biosynthesis and signaling of ethylene and ABA for time-course RT-PCR analysis mentioned above. In comparison with CK, the expression of all tested genes in ABA and NDGA-treated fruits revealed similar trends between RNA-seq and qRT–PCR, respectively (S9 Table). Furthermore, the scatterplots performed in our study demonstrated a positive correlation between the log2 fold change determined by RNA-seq and RT-PCR (R² = 0.81 in CK vs ABA; R² = 0.71 in CK vs NDGA), thereby verifying the high reliability of the data obtained from deep sequencing (S3 Fig).