Comparative transcriptomics and proteomics analysis of citrus fruit, to improve understanding of the effect of low temperature on maintaining fruit quality during lengthy post-harvest storage (original) (raw)
Abstract
Fruit quality is a very complex trait that is affected by both genetic and non-genetic factors. Generally, low temperature (LT) is used to delay fruit senescence and maintain fruit quality during post-harvest storage but the molecular mechanisms involved are poorly understood. Hirado Buntan Pummelo (HBP; Citrus grandis × C. paradis) fruit were chosen to explore the mechanisms that maintain citrus fruit quality during lengthy LT storage using transcriptome and proteome studies based on digital gene expression (DGE) profiling and two-dimensional gel electrophoresis (2-DE), respectively. Results showed that LT up-regulated stress-responsive genes, arrested signal transduction, and inhibited primary metabolism, secondary metabolism and the transportation of metabolites. Calcineurin B-like protein (CBL)–CBL-interacting protein kinase complexes might be involved in the signal transduction of LT stress, and fruit quality is likely to be regulated by sugar-mediated auxin and abscisic acid (ABA) signalling. Furthermore, ABA was specific to the regulation of citrus fruit senescence and was not involved in the LT stress response. In addition, the accumulation of limonin, nomilin, methanol, and aldehyde, together with the up-regulated heat shock proteins, COR15, and cold response-related genes, provided a comprehensive proteomics and transcriptomics view on the coordination of fruit LT stress responses.
Introduction
The quality of fruit is a combination of attributes, properties, and characteristics that give each commodity value in terms of human food. Consumers are concerned primarily about the colour and flavour of dietary components, as well as aspects of nutritional quality that include energy, vitamins, minerals, dietary fibre, and the many bioactive compounds that enhance human health. During post-harvest storage, soluble sugars, organic acids, and the solid/acid ratio are important components of fruit quality that can be affected by both internal and external factors. Senescence is the most important internal factor that determines storage lifetime and the final quality of fruit. During senescence, cells undergo orderly changes in cell structure, metabolism, and gene expression. Metabolically, carbon assimilation is replaced by catabolism of macromolecules such as proteins, membrane lipids, and RNA (Xue-Xuan et al., 2010). However, no further phenotypic change is observed during post-harvest storage. Therefore physical characters are the main markers of fruit senescence.
Fruit senescence is a developmentally programmed degenerative process that constitutes the final step of fruit development and is controlled by multiple developmental and environmental signals (Qin et al., 2009). Most studies of fruit senescence at the molecular level in climacterical fruit have been focused primarily on ethylene biosynthesis and its signal transduction (Botton et al., 2011), which suggest that fruit senescence is an oxidative phenomenon regulated by ethylene. However, study of the non-ethylene-mediated mechanisms of senescence physiology is of particular interest because it might create new opportunities for controlling fruit senescence (Qin et al., 2009). Citrus fruits are the most economically important subtropical fruits and citrus is becoming a key species in the study of fruit senescence. Unlike the climacterical tomato fruit, whose storage life is controlled by the phytohormone ethylene (Cara and Giovannoni, 2008; Botton et al., 2011), citrus fruits usually undergo gradual changes and no core substance regulating their senescence and post-harvest storage process has been identified. Therefore, analysis of senescence in citrus fruits might provide new insights into the fundamental pathways that contribute to the post-harvest properties of non-climacterical fruit.
Fruit senescence is naturally age-dependent and can be induced by abiotic and biotic factors, including low humidity, high temperature, oxidative stress, and pathogen infections (Alos et al., 2008). The internal signals (phytohormones), including abscisic acid (ABA), auxin, salicylic acid, ethylene, jasmonic acid, and brassinosteroid, also regulate fruit senescence (Ashraf et al., 2010; Sun et al., 2010; Yang et al., 2010). In addition, accumulation of hexoses through shifting cellular carbon flux from metabolism and biosynthesis could serve as signalling molecules that alter the biochemical or developmental processes in fruit (Fidelibus et al., 2008). Thus, studying fruit senescence will enhance understanding of a fundamental biological process and might provide the means to control senescence and improve agricultural traits of crop plants.
Low temperature (LT) has a positive effect on the post-harvest storage of fruit from harvest to human consumption, where lengthy storage for shipping, storing, and marketing is required. During that period, the main sources of damage to fruit are physiological disorders, such as senescence and water loss by evaporation, and pathogenic diseases. LT is usually chosen to extend storage life and maintain fruit quality during post-harvest storage, during which fruit quality declines gradually (Liu et al., 2011). Generally speaking, fruits taste good with a total soluble sugar/total organic acid ratio over 8 and LT is applied in inhibiting the ratio increase. Furthermore, fruit maintains greater flesh firmness and higher concentrations of organic acids and vitamin levels during cold storage. However, little information is available about cold signalling pathways and expression of cold-induced fruit-specific genes. Deciphering the mechanisms underlying LT-delayed fruit senescence will provide better understanding of the response to cold stress. Such knowledge is of great importance in developing breeding strategies designed to maintain fruit quality in post-harvest storage and improve LT tolerance in fruit.
In the past decade, gene expression and protein accumulation in fruit during post-harvest storage at LT has been studied by transcriptomic and proteomic approaches. Transcriptome analysis showed many genes change their expression (Maul et al., 2008; Vizoso et al., 2009) and proteomic analysis identified some differentially expressed proteins (Pan et al., 2009; Tanou et al., 2010; Yun et al., 2010). However, there is little information about fruit senescence and none about signal transduction or the regulation of gene expression in post-harvest fruit. Furthermore, cold-regulated genes have been estimated to represent up to 20% of the genome, and transcriptional responses to LT stress are quite variable, indicating that different sets of biophysical and hormonal signals are integrated into a specific response for different species and tissues (Chinnusamy et al., 2007).
Hirado Buntan Pummelo (HBP; Citrus grandis × C. paradis) is a popular variety of citrus fruit. Earlier, large differences of storage lifetime were found under different storage conditions, especially at different temperatures. Generally, HBPs are stored at ambient temperature (AT, 15–20 °C) for 2–3 months or at LT (8–10 °C) for 4–5 months. There are clear physiological differences between fruit stored under AT and LT, including concentrations of titratable acids, soluble solids, and other components of fruit quality and flavour (Yu et al., 2011). However, insufficient information is available for constructing a map of fruit senescence. The use of large-scale data for gene expression and protein accumulation will become available with the advent of proteomics and transcriptomics technology. LT-storage technology has been used for more than 100 years but little information is available concerning the transcriptional profiles and proteome associated with the maintenance of fruit quality during post-harvest storage under LT. In this study, fruit senescence was investigated at both the mRNA and protein levels to provide better understanding of the maintenance of the quality of citrus fruit during post-harvest storage at LT.
Materials and methods
Sample collection
HBP fruit at a commercially mature stage (ratio of total soluble sugar/total organic acid TSS/TOA greater than 8) was harvested in Changyang County, Hubei Province, China and was transported to Huazhong Agricultural University, Wuhan City, Hubei Province, China. Fruit weighing 150 kg was placed in a cold store at temperatures ranging from 8–10 °C and at a relative humidity of 85–90%. As a comparison, 150 kg fruit was also stored in storage room under AT (15–20 °C and 85–90% relative humidity). Juice sacs of two segments taken from each of ten fruits were sampled at 24, 48, 72, 96, and 120 days after harvest (DAH) and used directly for quality analysis or ground to powder in liquid nitrogen and stored at –80 °C.
Total protein extraction and two-dimensional gel electrophoresis
Proteins were extracted as described previously (Isaacson et al., 2006). Briefly, 6 g of frozen powder was suspended in 15 ml of homogenization medium [50% (v/v) phenol, 0.45 M sucrose, 5 mM EDTA, 0.2% (v/v) 2-mercaptoethanol, 50 mM TRIS–HCl, pH 8.8], shaken for 30 min at 4 °C, and then centrifuged for 30 min at 5000 g. The phenolic phase was collected and five volumes of 0.1 M ammonium acetate in 100% methanol was added to precipitate the proteins. The precipitate was collected by centrifugation for 30 min at 5000 g, washed twice with methanol, and then twice with acetone. After drying in a stream of dry nitrogen gas, protein pellets were dissolved in 0.6 ml of isoelectric focusing (IEF) solubilization buffer (8 M urea, 4% CHAPS, 65 mM DTT, 0.2% ampholine, pH 4–7; Bio-Rad, Hercules, CA, USA). The protein concentration was measured with an RC DC protein assay kit (Bio-Rad) using BSA as the standard. IEF was done essentially as described (Yun et al., 2010) but with slight modification. A 100 μg sample of proteins was used to passively rehydrate the 17 cm pH 4–7 IPG strip overnight. IEF was done in a Protean IEF Cell (Bio-Rad) with the following protocol: 0.5 h at 250 V, 1 h at 1000 V, increased from 1000 to 10,000 V over 5 h, and then 10,000V for 80,000 Vh. After IEF, the strips were equilibrated for 15 min in 6 ml of equilibration buffer (6 M urea, 20 % glycerol, 2% SDS, 0.375 M TRIS–HCl, pH 8.8) containing 130 mM DTT followed by alkylation in 6 ml of 2.5% iodoacetamide in equilibration buffer for 15 min. Second-dimensional sodium dodecyl sulfate/polyacrylamide gel electrophoresis (SDS-PAGE) was done in 15% polyacrylamide gels at 80 V for 0.5 h and then at 180 V for 5.5 h. At least three replicate gels were run for each sample.
Protein staining and image analysis
Proteins in the electrophoresis gels were visualized by staining with silver nitrate. Briefly, gels were fixed in 40% (v/v) ethanol, 10% (v/v) acetic acid for 2 h and sensitized in 30% ethanol, 0.02 M sodium thiosulfate and 0.8 M sodium acetate for 60 min. After four washes (15 min each) with ultrapure water, the gels were immersed in 3.7 mM silver nitrate for 60 min, washed four times (1 min each) with ultrapure water, developed with 0.02% (v/v) formaldehyde and 0.06 M sodium carbonate solution for 4–10 min, and stopped with 5% (v/v) acetic acid for 30 min. The gels were scanned with a GS-710 densitometer (Bio-Rad, USA) then stored at 4 °C.
Spot detection, quantification, and matching were done for each set of gels with PDQuest 2-D analysis software version 7.4 (Bio-Rad). A sample taken from the fruit under AT at 24 DAH was used as the reference (master) gel. Spots with a quality score of <30 were defined as low-quality spots and were not included for further analysis (Yun et al., 2010). Data were normalized as a percentage of the total density of all spots on the corresponding gel and then analysed by two-fold comparative analysis and one-way analysis of variance (ANOVA). Spots with more than two-fold differential accumulation in three independent gels were excised and used for protein identification. Experimental molecular mass and p_I_ were calculated from digitized 2-D electrophoresis images using standard molecular mass marker proteins and IPG strip pH 4–7.
In-gel tryptic digestion
The 108 differentially accumulated proteins were excised manually from four replicate gels. In-gel tryptic digestion was carried out as described (Rabilloud et al., 2008). Briefly, the gel plugs were incubated twice for 30 min with 50 ml of 25 mM NH4HCO3 and 50 ml of acetonitrile. Cysteine residues were reduced by incubating the plugs in 50 ml of 10 mM DTT at 57 °C and alkylated by immersion in 50 ml of 55 mM iodoacetamide. After dehydration with acetonitrile, the proteins were hydrated and digested overnight at room temperature with 10 ml of 12.5 ng ml−1 modified porcine trypsin (Promega, Madison, WI, USA) in 25 mM NH4HCO3. Digestion took place overnight at room temperature and the generated peptides were extracted with 60% acetonitrile in 5% formic acid.
MS analysis and database searching
A sample of each peptide solution was mixed with an equal volume of matrix solution (70% acetonitrile, 0.1% TFA, 10 mg ml−1 α-cyano-4-hydroxycinnamic acid) and then spotted onto a stainless steel target plate. Tryptic peptides were analysed by matrix-assisted laser desorption/ionization time-of-flight tandem mass spectrometry (MALDI-TOF MS/MS) with a mass spectrometer (model 4800; Applied Biosystems, Framingham, MA, USA) to acquire MALDI and MS/MS spectra (Rizzarelli et al., 2006; Yamaguchi et al., 2010). The data were processed with Data Explorer (version 4.4, Applied Biosystems). The resulting peak lists were searched against the Viridiplantae non-redundant protein database at the NCBI homepage (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi) using MASCOT v2.1.03 software (Matrix Science, London, UK). The search was performed using the following settings: green plants trypsin, one missed cleavage, fixed modifications of carbamidomethyl, variable modifications of oxidation, peptide tolerance 100 ppm, fragment mass tolerance ±0.5 Da, peptide charge 1+. Only peptides with MS/MS ion scores significantly (P < 0.05) exceeding the MASCOT identity or extensive homology threshold were reported.
Analysis of physiological characters
Soluble sugars and organic acids were determined by gas chromatography (GC) using an Agilent instrument (model 6890N, Agilent, USA). Fruit flesh (3 g fresh weight) was ground into powder and suspended in 10 ml of 80% ethanol for 15 min at 75 °C in a water bath. It was then subjected to an ultrasonic bath for 45 min and centrifuged at 4000 g for 10 min. The supernatant was collected in a 50 ml volumetric flask. The precipitate was extracted twice with 80% ethanol, and each supernatant was recovered and added to the corresponding volumetric flask. After the addition of 1 ml of standard solution (0.025 g ml−1 phenyl-β-D-glucopyranoside and 0.025 g ml−1 methyl-α-D-glucopyranoside), the supernatant was diluted to 50 ml with 80% ethanol. A 1 ml sample of this stock solution was dried at 60 °C in a rotary evaporator (Concentrator 5301; Eppendorf, Hamburg, Germany) and the dry matter was dissolved in 0.8 ml of 0.3 M hydroxylamine hydrochloride in pyridine then heated at 75 °C for 1 h. Hexamethyl disilazane (0.4 ml) and chlorotrimethylsilane (0.2 ml) were added and the mixture was heated at 75 °C for 2 h. Finally, 0.5 ml of the supernatant was used for GC analysis (Bartolozzi et al., 1997) and three independent replicates were statistically analysed per sample using Student’s t-test.
The concentration of naringin was determined using high-performance liquid chromatography (HPLC). A sample (1 g fresh weight) was extracted in 10 ml of dimethyl sulfoxide/methanol solution (1:1) using an ultrasonic bath for 30 min. After dilution to 10 ml, the extract was filtered using 0.22 μm microporous film and then analysed by HPLC (Waters, USA) as described by Bailey et al. (1993). Ultraviolet absorbance was monitored at a wavelength of 285 nm, and the retention time was 2.6–2.8 min. The standard curve was linear within the range tested (0–100 μg ml−1) and the coefficient of variation was <5% at 50 μg ml−1. Three independent replicates were statistically analysed per sample using Student’s t-test.
Limonin and nomilin were measured by HPLC. Fruit flesh was ground into a powder in liquid nitrogen and then 3 g (fresh weight) was extracted with 15 ml of CH2Cl2 in a Soxhlet extractor (IKA Labortechnik, Staufen, Germany) over 15 cycles. The extract was evaporated to dryness at 60 °C in a rotary evaporator. The residue was dissolved in 1 ml of acetonitrile and filtered through microporous film (0.22 μm pore size). The concentration was determined by HPLC as described (Sun et al., 2005). Three independent replicates were statistically analysed per sample using Student’s t-test.
Ethanol, acetaldehyde, and methanol were extracted essentially as described (Mitcham and McDonald, 1993) but with minor modifications. Juice was collected from two segments of ten fruit (each sample) and stored at –80 °C. Juice samples were thawed, and a 4 ml sample was transferred to a 10 ml vial and capped with a septum. Samples were incubated at 65 °C for 30 min in a water bath. Using a glass syringe, 1 ml of headspace gas was collected and analysed for ethanol, methanol, and acetaldehyde using a GC instrument equipped with a Chromosorb 101 column and a flame ionization detector (Agilent Technologies, Santa Clara, CA, USA). The oven temperature was 110 °C and the injection port temperature was 150 °C. Ethanol, acetaldehyde, and methanol were identified and quantified by comparison to peak areas from gas samples extracted after incubation at 65 °C of 4 ml of a solution containing known concentrations of standards. Three independent replicates were statistically analysed per sample using Student’s t-test.
Total RNA extraction
Total RNA was extracted from the ten frozen samples corresponding to five different storage stages (24, 48, 72, 96, and 120 DAH) according to Liu et al. (2009) with moderate modification. A 3 g sample of powder was suspended in 20 ml of TRIzol reagent buffer (1 M guanidine thiocyanate, 1 M ammonium thiocyanate, 38% water-saturated phenol, 0.2 M sodium acetate, 5% glycerol). After gentle shaking and precipitation at room temperature for 15 min, 10 ml of chloroform was added to the suspension, shaken vigorously for 1 min then left to precipitate for 10 min. After centrifugation at 10,000 g for 15 min at 4 °C, an equal volume (15 ml) of cooled isopropanol was added to the supernatant, shaken gently, and left to precipitate for 10 min. After centrifugation at 10,000 g for 20 min at 4 °C, the pellet was recovered, washed with 5 ml of 75% ethanol, dried for 2–3 min, and then 800 μl of TESAR (10 mM TRIS–HCl, 1 mM EDTA, 1% _N_-lauroylsarcosine sodium salt, pH 8.0), 800 μl of 0.07 M cetyltrimethylammonium bromide, and 800 μl of _N_-butanol were added and the mixture was centrifuged at 12,000 g for 6 min. The supernatant was recovered, 350 μl of 0.2 M NaCl was added, and the mixture was centrifuged at 12,000 g for 5 min. The precipitate was recovered, 50 μl of 3 M sodium acetate and 1 ml of ethanol were added, and the mixture was centrifuged at 12,000 g for 30 min at 4 °C. The precipitate was recovered, 20–50 μl of ultrapure water was added, and the solution was stored at –80 °C. Plastic consumables, ultrapure water, and reagents were treated with diethylpyrocarbonate to limit the degradation of mRNA.
Digital gene-expression profiling
Digital gene-expression (DGE) analysis was undertaken on fruit juice sacs at stage 72 DAH at both AT and LT. Samples (20 μg) of total RNA were sent to the Beijing Genomics Institute (Shenzhen) and prepared and sequenced using the Illumina Cluster Station and Genome Analyzer System (Solexa). Briefly, 6 μg of total RNA was used to purify mRNA with oligo(dT) adsorption on magnetic beads and reverse transcribed, double-stranded cDNA was synthesized, and _Nla_III was used to restrict at the CATG sites from the cDNA. cDNA fragments with the original 3′ ends were purified and Illumina adapter 1 was added at the 5′ ends and then restricted with _Mme_I at 17 bp downstream of the CATG site. Illumina adapter 2 was added at the 3′ ends, which finally acquired tags with different adapters at both ends to form a tag library. After 15 cycles of linear PCR amplification, 85 base strips were purified by TBE-PAGE in 6% polyacrylamide gels. The strips were digested and the single-chain molecules were fixed onto a Solexa Sequencing Chip (flow cell). Each molecule was grown into a single molecule cluster sequencing template through amplification in situ. Four types of nucleotides labelled by four different colours were added for sequencing by synthesis. Each tunnel generated millions of raw reads with a sequencing length of 35 bp.
Analysis of DGE data
Clean tags were generated by removing the 3′ adaptor sequence, empty reads (reads with a 3′ adaptor sequence but no tag), low-quality tags (tags with unknown N′ sequences), tags that were too long or too short, and tags with a copy number of 1. To link the expressed signatures to known genes in the orange, the unigene dataset for orange from The Institute for Genomic Research (TIGR) (http://compbio.dfci.harvard.edu/tgi/cgi-bin/tgi/gimain.pl?gudb=orange), the unigene dataset for Citrus clementina from TIGR (http://compbio.dfci.harvard.edu/cgi-bin/tgi/gimain.pl?gudb=clementine), 597 orange transcription factors (http://planttfdb.cbi.pku.edu.cn/index.php?sp=csi), and 964 sweet orange cDNA sequences from the study laboratory were combined to form a reference gene dataset (Xu et al., 2009), and a preprocessed database of all possible CATG+17 nt tag sequences was created using reference gene sequences. All clean tags were mapped to the reference sequences and no more than 1 nt mismatch was allowed. Clean tags mapped to reference sequences from multiple genes were filtered. The remaining clean tags were designated unambiguous clean tags and the number of these was calculated for each gene and then normalized to the number of transcripts per million (TPM) clean tags (‘t Hoen et al., 2008; Morrissy et al., 2009). Genes expressed differently in two samples were analysed as described (Audic and Claverie, 1997).
Determination of abscisic acid and ascorbic acid content
A 3 g sample (fresh weight) was ground into a powder in liquid nitrogen and extracted with 0.2 mM DTT in acetonitrile for 12 h at 0 °C. The supernatant was collected and condensed to dryness by rotary evaporation at 45 °C. The residue was dissolved in 6 ml of 0.4 M phosphate buffer (pH 8.0), then washed twice with 2 ml of chloroform. Insoluble PVPP (150 mg) was added to the supernatant to remove polyphenol and the aqueous solution (3 ml) was acidified to pH 3.0 with formyl acid and extracted three times with 2 ml of ethyl acetate. The ester phase was collected and condensed at 45 °C and the precipitate was dissolved in 1 ml of chromatographically pure methanol. After passage through a microporous film (0.22 μm pore size), the ABA content was measured by HPLC analysis using a C18 column (150 × 3.9 mm). The analytes were separated using methanol/0.5% acetic acid (45:55, v/v) as the mobile phase and the flow rate was 1 ml min−1. The absorbance at a wavelength of 262.7 nm was measured and three independent replicates were statistically analysed per sample using Student’s t-test.
Ascorbic acid was extracted from a 0.5 g sample (fresh weight) using 4 ml of 0.2% metaphosphoric acid. The extraction was repeated twice and the supernatant was collected and made up to a volume of 10 ml using distilled water. A 1 ml sample of the ml solution was removed and filtered using 0.22 μm microporous film, after which the contents were determined using HPLC. C18 reversed-phase column (Angillent Technology) was used with 0.2% metaphosphoric acid as the mobile phase and the column was eluted at 1 ml/min at 35 °C. UV detection was carried out at 243 nm. Three independent replicates were statistically analysed per sample using Student’s t-test.
Real-time quantitative reverse-transcription PCR verification
A sample of total RNA (∼2 μg) was reverse transcribed for first-strand cDNA synthesis using the RevertAid First Strand cDNA synthesis kit (Fermentas, Lithuania) according to the manufacturer’s instructions. Real-time PCR used gene-specific primer pairs (Supplementary Table S1, available at JXB online) designed with the Primer Express software (Applied Biosystems, Foster City, CA, USA) according to the sequence of the target gene in GenBank and was run on the ABI 7500 Real Time System (Applied Biosystems). Actin (GI:291419797) was used as the standard to normalize the content of cDNA as described (Liu et al., 2009). The primer pairs were: forward, 5′-CCAAGCAGCATGAAGATCAA-3′ reverse: 5′-ATCTGCTGGAAGGTGCTGAG-3′. SYBR Green PCR Master Mix (Applied Biosystems) was used in the quantification of differential expression and 10 μl of the reaction mixture was added to each well. The thermal cycling programme was 50 °C for 2 min, 95 °C for 1 min, and 40 cycles of 95 °C for 15 s and 60 °C for 1 min. Output data were generated by Sequence Detector version 1.3.1 software (Applied Biosystems) and then statistically analysed using Student’s t-test.
Results
Hirado Buntan pummelo (Citrus grandis × C. paradis), a tropical and subtropical horticultural species with good LT tolerance, was used for LT-storage testing as part of an investigation designed to understand the mechanism of LT on maintenance of fruit quality during lengthy post-harvest storage. Fruits were chosen at random to be stored at LT or AT and were sampled at 24, 48, 72, 96, and 120 DAH. A proteome based on two-dimensional gel electrophoresis (2-DE) was used to monitor the overall difference in protein accumulation during storage at LT or AT. The physiological index was measured to show changes in fruit quality. Furthermore, to explore signal transduction pathways involved in the maintenance of fruit quality, comparative DGE profiling analysis was used at the 72 DAH stage (protein accumulation and physiological index in earlier studies indicated that 72 DAH is the crucial stage for maintenance of fruit quality). Endogenous hormones were assayed and the mRNA levels of selected genes were verified using quantitative reverse-transcription PCR.
2-DE gel analysis and identification of LT-storage stress-responsive protein in HBP juice sacs
To exploit the LT-storage stress-specific proteome in juice sacs of HBP fruit, 2-DE and MALDI-TOF MS/MS technology were used in this study. Spots were separated with p_I_ 4–7 and a molecular mass of 10–100 kDa (Fig. 1). Representative gels are shown in Fig. 2 and >1000 spots were resolved reproducibly in each analysis gel. Comparative analysis and statistical analysis (Student’s t-test) revealed a total of 108 spots with significantly different accumulation (P < 0.05) and a difference of more than two-fold at one or more time point(s) between AT and LT storage. The total number of LT down-regulated proteins was at a minimum (40) at 72 DAH; in contrast, the number of LT up-regulated proteins (total) was at a maximum (68) at 72 DAH (Table 1). The results suggest that 72 DAH is a crucial stage if fruit quality is to be maintained by LT for the whole duration of post-harvest storage.
Table 1.
Number of proteins accumulated during storage
| Storage period | LT down-regulated proteins | LT up-regulated proteins | ||||
|---|---|---|---|---|---|---|
| <0.5 | 0.5–1 | Total | 1–2 | >2 | Total | |
| 24 DAH | 14 | 41 | 55 | 30 | 23 | 53 |
| 48 DAH | 10 | 43 | 53 | 33 | 22 | 55 |
| 72 DAH | 15 | 25 | 40 | 44 | 24 | 68 |
| 96 DAH | 18 | 29 | 47 | 44 | 17 | 61 |
| 120 DAH | 22 | 31 | 53 | 27 | 28 | 55 |
| Storage period | LT down-regulated proteins | LT up-regulated proteins | ||||
|---|---|---|---|---|---|---|
| <0.5 | 0.5–1 | Total | 1–2 | >2 | Total | |
| 24 DAH | 14 | 41 | 55 | 30 | 23 | 53 |
| 48 DAH | 10 | 43 | 53 | 33 | 22 | 55 |
| 72 DAH | 15 | 25 | 40 | 44 | 24 | 68 |
| 96 DAH | 18 | 29 | 47 | 44 | 17 | 61 |
| 120 DAH | 22 | 31 | 53 | 27 | 28 | 55 |
A total of 108 differentially accumulated protein spots were detected during low temperature (LT) storage using two-dimensional gel electrophoresis. Protein accumulation regulated by LT was divided into four categories, The first category proteins were down-regulated more than two-fold (<0.5). Second category proteins were down-regulated less than two-fold (0.5–1). Third category proteins were up-regulated less than two-fold (1–2) and fourth category proteins were up-regulated more than two-fold (>2). DAH, days after harvest.
Table 1.
Number of proteins accumulated during storage
| Storage period | LT down-regulated proteins | LT up-regulated proteins | ||||
|---|---|---|---|---|---|---|
| <0.5 | 0.5–1 | Total | 1–2 | >2 | Total | |
| 24 DAH | 14 | 41 | 55 | 30 | 23 | 53 |
| 48 DAH | 10 | 43 | 53 | 33 | 22 | 55 |
| 72 DAH | 15 | 25 | 40 | 44 | 24 | 68 |
| 96 DAH | 18 | 29 | 47 | 44 | 17 | 61 |
| 120 DAH | 22 | 31 | 53 | 27 | 28 | 55 |
| Storage period | LT down-regulated proteins | LT up-regulated proteins | ||||
|---|---|---|---|---|---|---|
| <0.5 | 0.5–1 | Total | 1–2 | >2 | Total | |
| 24 DAH | 14 | 41 | 55 | 30 | 23 | 53 |
| 48 DAH | 10 | 43 | 53 | 33 | 22 | 55 |
| 72 DAH | 15 | 25 | 40 | 44 | 24 | 68 |
| 96 DAH | 18 | 29 | 47 | 44 | 17 | 61 |
| 120 DAH | 22 | 31 | 53 | 27 | 28 | 55 |
A total of 108 differentially accumulated protein spots were detected during low temperature (LT) storage using two-dimensional gel electrophoresis. Protein accumulation regulated by LT was divided into four categories, The first category proteins were down-regulated more than two-fold (<0.5). Second category proteins were down-regulated less than two-fold (0.5–1). Third category proteins were up-regulated less than two-fold (1–2) and fourth category proteins were up-regulated more than two-fold (>2). DAH, days after harvest.
Fig. 1.
Distribution of identified proteins on two-dimensional gel. Differential accumulation analysis was carried out using PDQuest software. Those spots with more than two-fold difference in accumulation over three independently analysed gels were removed from identified gels for MS/MS analysis. The master gel was used for the distribution of successful identified proteins. Red arrows indicate that proteins were up-regulated by low-temperature storage stress compared to ambient-temperature storage. Green arrows indicate that proteins were down-regulated by low-temperature storage stress. Blue arrows indicate that the proteins changed during storage. (This figure is available in colour at JXB online).
Fig. 2.
Representative two-dimensional electrophoresis profiles of proteins from Hirado Buntan Pummelo during post-harvest under ambient temperature and low temperature. The juice sacs from two segments of ten individual fruits were sampled at 24, 48, 72, 96, and 120 days after harvest (DAH), A total of ten samples were harvested from the two storage conditions at 24 d intervals from 3 December 2008 to 1 April 2009. Proteins were extracted using phenol extraction protocol. Proteins (100 μg) were separated in the first dimension on IPG strip (17 cm, pH 4–7) and in the second dimension on a 15% SDS-PAGE gel. Gels were visualized by silver staining.
A total of 108 differentially accumulated protein spots were analysed by MALDI-TOF MS/MS. As citrus genome sequencing has not yet been completed, only 63 spots were successfully identified on the basis of tryptic peptide sequences. The specific locations of proteins on 2-DE gels are shown in the master gel in Fig. 1 and detailed information for the proteins is given in Table 2. To obtain functional information about the proteins identified, the literature and the annotated biochemical and biological functions based on the Blast2GO program was searched. Ten proteins were classified as unknown; the other 53 proteins were classified into seven functional categories. The results showed that the categories with considerable enrichment were metabolism, containing sugars and polysaccharide metabolism (5), secondary metabolism (5), other metabolism (8), protein destination and storage (12), and response to stimulus (12), indicating that these processes play a leading role in the maintenance of fruit quality at LT (Fig. 3A). Proteins with known functions were also categorized using the Blast2GO program based on biochemical activity or cellular position. Hydrolase activity (8), nucleotide binding (9), protein binding (10), and transferase activity (9) were the most abundant biochemical activity categories, which implied that hydrolysis and transportation of substrates are vital for the maintenance of fruit quality (Fig. 3B). For cellular positions, plasma membrane was the largest group of proteins (16), followed by plastid (15), mitochondrion (13), and nucleus (10) (Fig. 3C). These results showed that most of the differentially accumulated proteins are localized to the plasma membrane, plastid, mitochondrion, and nucleus.
Table 2.
Identities of LT-storage stress-responsive proteins in the juice sacs of Hirado Buntan Pummelo fruit
A total of 108 spots were identified using Applied Biosystems 4800 matrix-assisted laser desorption/ionization-time-of-flight tandem mass spectrometry and 63 proteins were successfully identified based on tryptic peptide sequences. As the citrus genome plan has not been completed, the peptide list was searched against Viridiplantae protein. The letter U in the protein identification number shows that the proteins were up-regulated by low temperature (LT) storage stress during storage, the letter D in the protein identification number shows that the proteins were down-regulated by LT, and the letter C represents proteins that had changed expression during storage. Protein accumulation is represented by the column configuration, and accumulation at 24, 48, 72, 96, and 120 DAH (days after harvest) is shown from left to right. Identification and accession numbers (protein name and GI number) are from the National Center for Biotechnology Information database (http://www.ncbi.nlm.nih.gov/guide/). Experimental molecular mass and p_I_ (Exp. M/p_I_) were calculated by PDQest, and mass is shown in kDa. Theoretical molecular mass and p_I_ (Theo. M/p_I_) were available on NCBI. PC, peptide count; MS, mascot score. The protein accumulation under ambient temepature is shown as a white column and the protein accumulation under LT is shown as a gray column.
Table 2.
Identities of LT-storage stress-responsive proteins in the juice sacs of Hirado Buntan Pummelo fruit
A total of 108 spots were identified using Applied Biosystems 4800 matrix-assisted laser desorption/ionization-time-of-flight tandem mass spectrometry and 63 proteins were successfully identified based on tryptic peptide sequences. As the citrus genome plan has not been completed, the peptide list was searched against Viridiplantae protein. The letter U in the protein identification number shows that the proteins were up-regulated by low temperature (LT) storage stress during storage, the letter D in the protein identification number shows that the proteins were down-regulated by LT, and the letter C represents proteins that had changed expression during storage. Protein accumulation is represented by the column configuration, and accumulation at 24, 48, 72, 96, and 120 DAH (days after harvest) is shown from left to right. Identification and accession numbers (protein name and GI number) are from the National Center for Biotechnology Information database (http://www.ncbi.nlm.nih.gov/guide/). Experimental molecular mass and p_I_ (Exp. M/p_I_) were calculated by PDQest, and mass is shown in kDa. Theoretical molecular mass and p_I_ (Theo. M/p_I_) were available on NCBI. PC, peptide count; MS, mascot score. The protein accumulation under ambient temepature is shown as a white column and the protein accumulation under LT is shown as a gray column.
Fig. 3.
Functional categorization of the low-temperature-storage-specific accumulated proteins in Hirado Buntan Pummelo fruit juice sacs. MS data was searched against the Viridiplantae non-redundant protein database at the NCBI homepage (http://www.ncbi.nlm.nih.gov/blast/Blast.cgi) using MASCOT software. A total of 63 proteins were annotated using gene ontology and categorized according to protein function (A), molecular function (B), and cellular component (C). (This figure is available in colour at JXB online).
LT storage maintains fruit quality through decreased physiological index metabolism
Fruit taste is determined by the content and type of soluble sugars and organic acids, which have an impact on the organoleptic quality of fruit. In ripe citrus fruit, the main soluble sugars are sucrose, fructose, and glucose. The main organic acid is citric acid, malic acid, and quinic acid. The trends in organic acid and soluble sugar contents in HBP juice sacs (fresh weight) during post-harvest storage are shown in Fig. 4. The malic acid concentration decreased gradually with increased storage time and obvious difference was observed between 24 DAH and 96 DAH (Fig. 4A). Between 72 DAH and 120 DAH, citric acid, the main organic acid (>90%) in this fruit, showed a greater increase under LT than under AT (Fig. 4B). Sucrose concentration increased during storage and was higher under LT than under AT at 72 DAH, whereas fructose and glucose concentrations were lower at 72 DAH under LT compared to AT (Fig. 4D–F). Taken together, LT maintained/increased the citric acid, sucrose, and TOA concentrations in the fruit but decreased the concentrations of fructose, glucose, TSS, and the ratio of TSS/TOA, especially at 72 DAH. This suggested that 72 DAH was the turning point in the accumulation of hexoses and citric acid under AT and LT, and that 72 DAH is a crucial time point for the levels of both protein and physiological characters.
Fig. 4.
Trends in organic acid and soluble sugar contents in Hirado Buntan Pummelo juice sacs (fresh weight) during post-harvest storage. Malic acid, citric acid, quinic acid, fructose, glucose, and sucrose contents were extracted using 80% methanol and measured using gas chromatography at 24, 48, 72, 96, and 120 d after harvest (DAH). Three individual replicates were used to reduce experimental error. Total organic acid (TOA) and total soluble sugar (TSS) were the sum of the organic acids (malic acid, citric acid, and quinic acid) and the soluble sugars (fructose, glucose, and sucrose), respectively. The accumulation under AT is shown by a white column and the accumulation under LT is shown by a gray column. Different letters (A, B, C, and D) represent statistically significant differences (P < 0.01), analysed using Student’s t-test.
Secondary metabolites are a vital indicator of fruit quality, especially with regards to human health. Fig. 5 shows the indexes of metabolites of secondary metabolism and anaerobic respiration during AT and LT storage. In this study, the concentrations of limonin and nomilin were higher when stored under LT than under AT at 48 DAH and 120 DAH (Fig. 5B, C). In addition, naringin content was higher under LT storage than under AT at 72 DAH and 120 DAH, but lower at 48 DAH (Fig. 5A). Alcohol metabolites, which were found to be volatile organic compounds, are important markers of fruit quality. In this present study, methanol and aldehyde concentrations were higher when fruit was stored under LT than under AT at 48, 96, and 120 DAH (Fig. 5D, E). However, no obvious change was detected in ethanol concentration between LT and AT storage (Fig. 5F). In summary, LT increased the concentrations of limonin, nomilin, methanol, and aldehyde.
Fig. 5.
Indexes of metabolites of secondary metabolism and anaerobic respiration during ambient temperature (AT) and low temperature (LT) storage. Naringin concentration was determined by a method that used solid-phase sample preparation and HPLC. Nomilin and limonin were extracted with 15 ml CH2Cl2 in a Soxhlet extractor and measured using HPLC. Aldehyde, alcohol, and methanol were volatilized using a 65 °C water bath and detected using GC. (A–C) Specific accumulations of naringin, nomilin, and limonin in Hirado Buntan Pummelo juice sacs at 24, 48, 72, 96, and 120 d after harvest (DAH). (D–F) Specific accumulations of aldehyde, alcohol, and methanol. Fresh-weight samples were used. The accumulation under AT is shown by a white column and the accumulation under LT is shown by a gray column. Different letters (A, B, C, and D) represent statistically significant differences (P < 0.01), analysed using Student’s t-test. (This figure is available in colour at JXB online.)
DGE profiling of specific genes in response to LT-storage stress
To further understand the delay of senescence in the fruit at LT, regulation of gene expression was investigated using comparative DGE profiling analysis. According to the proteome data and the physiological index, 72 DAH is the inflection point in the maintenance of fruit quality under different storage conditions. Therefore, samples of 72 DAH at AT and LT were used for the construction of DGE libraries. The level of gene expression at LT and AT is highly correlated (r = 0.999). After removal of the 3′ adaptor sequence, empty reads, low-quality tags, tags too long or too short (leaving tags of 21 nt long), and tags with a copy number of 1, there were 3,430,217 and 3,700,516 successful sequences (clean tags) produced for LT and AT, respectively, and from the clean tag sets, 57,898 and 77,460 distinct tags were observed for LT and AT, respectively (Supplementary Table S2). The distribution of total clean tags was quite similar at LT and AT. Tag copy numbers of 3–5 at AT and LT accounted for 3.33% and 2.86% of total clean tags and contributed 56.2% and 59.89% of total distinct clean tags, respectively, indicating that genes with low transcripts are abundant in both libraries.
To link the tags to known genes, a unigene dataset containing 26,826 contigs and 73,607 singletons was used for DGE tag mapping analysis. The results showed that 7916 and 10,003 genes were detected at LT and AT, respectively (Supplementary Table S2). Gene expression was calculated using the number of clean tags for each gene normalized to TPM according to Morrissy et al. (2009). Analysis of differential expression at LT coared to AT revealed 3133 down-regulated genes and 336 up-regulated genes. Gene ontology categories were assigned to the 3469 genes with significantly differential expression using the Blast2GO program (http://www.blast2go.org/start_blast2go#download_blast2go) to evaluate the potential functions of genes that showed significant transcriptional differences between AT and LT. The genes were finally classified into 13 categories on the basis of biological processes, as shown in Fig. 6A. Primary metabolic process (873), response to stimulus (328), nitrogen compound metabolic process (285), and transport (254) were the major categories, which is consistent with the data for the proteins. The significant enrichment categories classified on the basis of molecular function were protein binding (376), hydrolase activity (355), nucleic acid binding (297), transporter activity (159), and kinase activity (159), which correspond well to the protein data (Fig. 6B). The genes were classified on the basis of cellular components into cytoplasm (1204), plastid (500), mitochondrion (368), plasma membrane (263), and nucleus (253). Among them, plastid, mitochondrion, plasma membrane, and nucleus were the major subcellular organelles in the response to LT-storage stress, which is in accord with the protein data except the cytoplasm category (Fig. 6C).
Fig. 6.
Functional categorization of the genes with significant transcriptional changes between ambient temperature (AT) and low temperature (LT) conditions. Total RNA was extracted from Hirado Buntan Pummelo fruit at 72 DAH under AT and LT stress. After the comparative analysis of digital gene expression profiling, differential expressed genes were annotated using gene ontology and categorized according to biological process (A), molecular function (B), and cellular component (C).
Low abscisic acid at low temperature
ABA is active in fruit developmental processes and ABA-mediated signalling plays an important role in plant responses to cold stress. In this study, the concentration of ABA was lower under LT than AT (Fig. 7A). It decreased sharply under LT at 48 DAH and then maintained a low concentration range during later LT storage. That implied LT decreased ABA concentration during lengthy storage. In addition, ascorbic acid showed no obvious trend with LT-storage stress (Fig. 7B).
Fig. 7.
Abscisic acid (ABA) (A) and ascorbic acid (B) contents under ambient temperature (AT) and low temperature (LT). ABA and ascorbic acid was extracted from Hirado Buntan Pummelo juice sacs (fresh fruit) 24, 48, 72, 96, and 120 days after harvest (DAH). Both were determined using HPLC analysis with a C18 column. The absorbances of ABA and ascorbic acid were 262 nm and 243 nm, respectively. Three individual replicates were used to reduce experimental error. The accumulation at AT is shown by a white column and the accumulation under LT is shown by a gray column. Different letters (A, B, C, and D) represent statistically significant differences (P < 0.01), analysed using Student’s t-test.
LT-stress-induced proteins and genes
In the present study, many proteins were shown to be regulated by cold stress, including cold-responsive (COR) genes, heat-shock proteins (HSPs), temperature-induced lipocalins (TILs), chitinase, cysteine synthase, cysteine protease inhibitor, allyl alcohol dehydrogenase, putative aldehyde dehydrogenase, and mitochondrial aldehyde dehydrogenase (Table 2). In particular, small HSPs and high-molecular-weight HSPs showed a large accumulation under LT (Fig. 8, Table 2). HSPs (CK701553, CN188563, TC14491, TC16014, TC15728, and CB290599) were up-regulated at the mRNA level during storage of fruit at LT (Excel S1). Additionally, some genes, such as TC69, EY747469, CX301947, EY730996, TC112, CN188448, EY669681, TC3575, TC4342, EY715324, TC15065, and TC12193 (Supplementary Excel S1), were up-regulated by LT at 72 DAH, which has been reported for stress response studies.
Fig. 8.
Transcript levels of 28 selected genes at different stages of fruit storage under AT and LT. The relative expression levels were analysed by quantitative real-time reverse-transcription PCR. The gene expression under AT is shown by a white column and the gene expression under LT is shown by a gray column. Different letters (A, B, C, and D) represent statistically significant differences (P < 0.01), analysed using Student’s t-test.
In signal transduction, calcium-related genes (TC17374, DR909130, TC23919, EY730996, CX054024, and TC7333) were up-regulated in response to LT stress, but 21 mRNA transcriptions (TC6871, TC16109, TC21784, EY655246, TC13533, TC19601, TC22565, TC11247, TC22289, TC14057, TC6139, TC13664, TC6325, TC19918, EY756065, TC2423, TC12712, EY705442, TC18120, TC14678 and TC14726) were down-regulated (Excel S1). Interestingly, calcineurin B-like proteins (CBLs) 1 and 4 were up-regulated, whereas CBLs 3 and 10 were down-regulated (Excel S1). Surprisingly, no C-repeat binding factor (CBF) was detected in either the protein data or the DGE data, but COR15, CBF regulated gene, was shown to be up-regulated, which might be because of a potential detection failure of the proteome and transcriptome technology or possibly incomplete citrus genome information.
LT storage delays fruit senescence by inhibiting expression of metabolic genes
A total of 1450 down-regulated genes were detected in DGE were analysed using the BINGO plugin in Cytoscape. The results showed 1036 genes were metabolism-associated genes, mainly concerned with carbohydrate metabolism, nitrogen compound metabolism, lipid metabolism, macromolecule metabolism, secondary metabolism, and alcohol metabolism (Supplementary Data).
A total of 117 genes were involved in carbohydrate metabolism identified in the differential test, 111 of which are down-regulated and six are up-regulated (Table 3). The suppressed genes were involved mainly in glycolysis, the citrate cycle, and other sugar metabolic pathways, including sucrose, starch, glucan, cellulose, and galactose metabolism. It is noteworthy that the mRNA levels of glycosyl-related genes, especially the glycosyl hydrolase family including members 2, 13, 17, 20, 28, and 38, were decreased in response to LT stress (Supplementary Excel S1). Down-regulation of glycosyl hydrolases delays degradation of the plant cell wall (Lee et al., 2007), which is the main parameter of fruit senescence.
Table 3.
Functional categorization of chilling-responsive genes in Hirado Buntan Pummelo fruit
| Term | Total | Up | Down | Graph score |
|---|---|---|---|---|
| Primary metabolic process | 873 | 61 | 812 | 430.5 |
| Response to stimulus | 328 | 43 | 285 | 331.2 |
| Nitrogen compound metabolic process | 285 | 18 | 267 | 64.14 |
| Transport | 254 | 24 | 230 | 224 |
| Protein modification process | 200 | 21 | 179 | 200 |
| Catabolic process | 166 | 13 | 153 | 166 |
| Transcription | 127 | 11 | 116 | 127 |
| Carbohydrate metabolic process | 117 | 6 | 111 | 117 |
| Signalling | 100 | 5 | 95 | 21.98 |
| Translation | 88 | 4 | 84 | 88 |
| Lipid metabolic process | 84 | 2 | 82 | 84 |
| Secondary metabolic process | 31 | 0 | 31 | 31 |
| Cell communication | 10 | 2 | 8 | 9.6 |
| Term | Total | Up | Down | Graph score |
|---|---|---|---|---|
| Primary metabolic process | 873 | 61 | 812 | 430.5 |
| Response to stimulus | 328 | 43 | 285 | 331.2 |
| Nitrogen compound metabolic process | 285 | 18 | 267 | 64.14 |
| Transport | 254 | 24 | 230 | 224 |
| Protein modification process | 200 | 21 | 179 | 200 |
| Catabolic process | 166 | 13 | 153 | 166 |
| Transcription | 127 | 11 | 116 | 127 |
| Carbohydrate metabolic process | 117 | 6 | 111 | 117 |
| Signalling | 100 | 5 | 95 | 21.98 |
| Translation | 88 | 4 | 84 | 88 |
| Lipid metabolic process | 84 | 2 | 82 | 84 |
| Secondary metabolic process | 31 | 0 | 31 | 31 |
| Cell communication | 10 | 2 | 8 | 9.6 |
Total RNA was extracted from fruit at 72 DAH under ambient temperature (AT) and low temperature (LT) stress respectively. After the comparative analysis of digital gene expression profiling, differentially expressed genes were annotated using gene ontology and categorized using biological process terms. Up, number of LT stress up-regulated genes; down, number of LT stress down-regulated genes.
Table 3.
Functional categorization of chilling-responsive genes in Hirado Buntan Pummelo fruit
| Term | Total | Up | Down | Graph score |
|---|---|---|---|---|
| Primary metabolic process | 873 | 61 | 812 | 430.5 |
| Response to stimulus | 328 | 43 | 285 | 331.2 |
| Nitrogen compound metabolic process | 285 | 18 | 267 | 64.14 |
| Transport | 254 | 24 | 230 | 224 |
| Protein modification process | 200 | 21 | 179 | 200 |
| Catabolic process | 166 | 13 | 153 | 166 |
| Transcription | 127 | 11 | 116 | 127 |
| Carbohydrate metabolic process | 117 | 6 | 111 | 117 |
| Signalling | 100 | 5 | 95 | 21.98 |
| Translation | 88 | 4 | 84 | 88 |
| Lipid metabolic process | 84 | 2 | 82 | 84 |
| Secondary metabolic process | 31 | 0 | 31 | 31 |
| Cell communication | 10 | 2 | 8 | 9.6 |
| Term | Total | Up | Down | Graph score |
|---|---|---|---|---|
| Primary metabolic process | 873 | 61 | 812 | 430.5 |
| Response to stimulus | 328 | 43 | 285 | 331.2 |
| Nitrogen compound metabolic process | 285 | 18 | 267 | 64.14 |
| Transport | 254 | 24 | 230 | 224 |
| Protein modification process | 200 | 21 | 179 | 200 |
| Catabolic process | 166 | 13 | 153 | 166 |
| Transcription | 127 | 11 | 116 | 127 |
| Carbohydrate metabolic process | 117 | 6 | 111 | 117 |
| Signalling | 100 | 5 | 95 | 21.98 |
| Translation | 88 | 4 | 84 | 88 |
| Lipid metabolic process | 84 | 2 | 82 | 84 |
| Secondary metabolic process | 31 | 0 | 31 | 31 |
| Cell communication | 10 | 2 | 8 | 9.6 |
Total RNA was extracted from fruit at 72 DAH under ambient temperature (AT) and low temperature (LT) stress respectively. After the comparative analysis of digital gene expression profiling, differentially expressed genes were annotated using gene ontology and categorized using biological process terms. Up, number of LT stress up-regulated genes; down, number of LT stress down-regulated genes.
In this study, all 31 genes of secondary metabolism, mainly flavonoids, carotenoids, vitamins, and proteins, were down-regulated under LT stress (Table 3). In addition, 82 of 84 lipid metabolic genes, which encode phospholipases (TC16578, TC17789, EY686225, and TC13892) and acyl carrier proteins (TC4318, TC13606, TC13779, TC23479, TC6769, TC7499, TC6017, TC13708, and TC4898), were down-regulated by LT in DGE profiling (Supplementary Excel S1).
A total of 198 transporter genes were detected in DGE data, which were analysed using the BINGO plugin in Cytoscape (Supplementary Data). Only eight genes, predicted to encode transporters for urea and water (P < 0.05), were up-regulated by LT and involved in water loss. Many of the genes predicted to encode ion transport, vesicle-mediated transport, mitochondrial transport, protein transport, secretion, and intercellular transport were down-regulated by LT (high reliability, Supplementary Data).
In summary, LT storage maintained fruit quality not only by inhibiting the degradation of macromolecules (such as polysaccharides, proteins, and lipids) and nutritional substances (such as sugars and organic acids), but also by inhibiting the transportation of substrates during lengthy storage.
Signal transduction in citrus fruit senescence is regulated by sugar, auxin, and ABA
Sugars, as crucial components in fruit quality, were also involved in signal transduction. In the present study, the fructose and glucose contents decreased under LT, especially at 72 DAH (Fig. 4). Furthermore, some genes which encode glucose- and fructose-binding proteins (such as TC11892, TC12351, TC13119, TC18748, TC3277, TC608, TC9110, CX046230, TC23285, TC25884, TC4031, and TC4180), which might play a role in signal transduction (Excel S1), were down-regulated by LT.
Auxin is involved in various aspects of growth and development. In the present study, all eight genes which encode auxin response factor proteins (TC13217, TC23352, TC4914, CK936688, TC25995, TC14087, TC10814, and TC19428) were down-regulated under LT and one auxin-repressed protein (TC22895) was up-regulated (Excel S1). It is interesting that all four genes which encode auxin-induced proteins (TC19324, TC8111, EY714452, and TC1904) were down-regulated (Excel S1), and IAA9 (indoleacetic acid-induced protein 9) transcription factor decreased at the protein level during later LT storage (Table 2). This suggests that LT inhibits fruit senescence by down-regulation of auxin-induced proteins or up-regulation of auxin-repressed protein.
The phytohormone ABA is a major endogenous factor and the primary signal that regulates fruit development, maturation, and senescence. In this study, ABA content decreased sharply (by nearly 90%) from 24 DAH to 120 DAH under LT (Fig. 7). ABA-related protein and abscisic stress ripening-like protein was down-accumulated under LT (Table 2), and ABA-related genes, such as ABA-responsive like protein, ABA and ripening-inducible-like protein, ABA-responsive hva22 family protein, and ABA-responsive element-binding protein 2, were down-regulated under LT (Supplementary Excel S1). In addition, differentially expressed genes were detected by DGE (analysed using the CLUGO plugin in Cytoscape). This showed that ABA participated in the regulation of fruit senescence (Supplementary Data). Moreover, no ABA-regulated genes or proteins were up-regulated by LT stress in this study, suggesting that ABA is not involved in the LT stress response in citrus fruit during post-harvest storage. Furthermore, 86 signal transduction genes detected in DGE were analysed using the BINGO plugin in Cytoscape, which showed there was a cross-talk between ABA and auxin-mediated signal transduction (Supplementary Data).
In this study, no ethylene-related protein was found among the differentially accumulated proteins, and few ethylene-related genes were detected in the DGE data. Moreover, down-regulation in the expression of the reactive oxygen species (ROS)-related genes for oxidoreductase, ascorbate peroxidase 2, and superoxide dismutase occurred under LT, especially at 24 and 96 DAH (Fig. 8). Only ascorbate peroxidase 1 was up-regulated under LT (Fig. 8), but AT and LT had little effect on the accumulation of ascorbic acid (Fig. 7B). These results suggest ROS might only play a small role in regulating citrus fruit senescence.
Discussion
Fruit endured LT stress during lengthy storage
In plants, regulation of gene expression is one of the main strategies for defence against LT stress. The hypothesis is that LT-responsive proteins are likely to be involved in cold tolerance (Yan et al., 2006). Many plant genes have been reported as participating in the response to cold stress, including COR genes, HSPs, and TILs. These genes and substances regulate the response to LT stress and are thought to be important in LT stress tolerance.
It has been reported that the CBF COR pathway plays a central role in cold acclimation in Arabidopsis thaliana (Doherty et al., 2009). COR, one of the CBF pathway genes, encodes a novel hydrophilic polypeptide that acts directly as a cryoprotective protein and helps prevent the formation of hexagonal II phase lipids (Steponkus et al., 1998). When COR15 was over-expressed in Arabidopsis, the plant exhibited tolerance to cold stress and so it has been suggested that the accumulation of COR15 is vital for stress tolerance in fruit that stored under LT (Kim et al., 2004).
Five major families of HSPs/chaperones have been recognized, including HSP70, HSP60, HSP90, HSP100, and small HSPs. HSPs are responsible for protein folding, assembly, translocation, and degradation in many cellular processes. They are also involved in stabilizing proteins and membranes and assist in protein refolding under stress (Wang et al., 2004). HSPs can play a crucial role in protecting plants against stress by re-establishing normal protein conformation, thereby helping to maintain cellular homeostasis (Wang et al., 2004).
In addition, TILs have been shown to be responsive to temperature stress, by suppressing sensitivity to oxidative stress, reducing the accumulation of lipid peroxidation products, and alleviating temperature-induced oxidative stress on plant membranes (Chi et al., 2009).
Other proteins are accumulated under LT, such as putative membrane protein, multicatalytic endopeptidase complex, proteasome component, alpha subunit, putative lactoylglutathione lyase, putative glyoxalase I, cysteine protease inhibitor, and harpin binding protein 1 (Table 2). However, little information is available concerning fruit responding directly to LT stress, and the above proteins were detected in cold response plant-omics studies (Guerra et al., 2010; Sobhanian et al., 2010).
In summary, fruit endured LT during post-harvest storage through up-regulation of cold-resistant genes and accumulation of cryoprotective proteins.
Ca2+-dependent signal transduction of LT stress
LT can reduce the fluidity and increase the rigidity of plant cell membranes. Plant cells can sense cold stress through LT-induced changes in membrane fluidity, protein and nucleic acid conformation, and/or concentration of metabolites (Chinnusamy et al., 2007). Ca2+-decoding mechanisms within the plant cell appear to be more complex than those in other organisms (Luan, 2009). The CBL–CBL-interacting protein kinase (CIPK) network represents an example of significantly diverged Ca2+-decoding paradigms that are unique to plants (Hirayama and Shinozaki, 2010). Moreover, a more detailed analysis of the Arabidopsis genome revealed a multigene CBL-encoding family with at least ten members (Luan et al., 2002), and CIPKs are most likely to represent targets of calcium signals sensed and transduced by CBL proteins (Kolukisaoglu et al., 2004). Distinct CBL–CIPK complexes play a role in a different signalling pathway (Luan et al., 2002). It is reported that CBLs 1 and 4 were up-regulated under cold stress in Arabidopsis (Cheong et al., 2003) and CBLs might be correlated with senescence (De Michele et al., 2009). Therefore, CBL–CIPK complexes might be involved in the signal transduction of both LT stress and senescence. In addition, a family of Arabidopsis transcription factors, the CBF proteins, have been reported to control the expression of a regulator of cold-induced genes that increases freezing tolerance (Thomashow, 1999). Surprisingly, in this study, no CBF was detected in the differential expression profiles at the protein or mRNA level but the genes downstream of CBF were up-regulated, which might be the result of detection failure by the proteome and transcriptome technology or incomplete citrus genome information. Supplies of exogenous Ca2+ are no longer available for harvested fruit. However, Ca2+-mediated signal transduction might still be involved in both LT stress response and senescence, because the Ca2+ signal is presented not only by the concentration of Ca2+ but also by its spatial and temporal information (Allen et al., 2001).
LT storage delays fruit senescence by inhibiting expression of metabolic genes
During the post-harvest storage of fruit, although LT caused a decrease in most enzyme activity and inhibited the expression of many genes, fruit quality was still maintained (Jin et al., 2009a). Fruit quality is very complex and is affected by a mixture of sugars, acids, amino acids, minerals, volatile compounds, colour, and flavour, including major biochemical and sensory changes (Ogundiwin et al., 2009). Complex metabolic processes are involved in maximizing and maintaining fruit quality from production and processing through to marketing and consumption (Ogundiwin et al., 2009). In this study, LT storage decreased fruit metabolism, including reducing carbohydrate metabolism, nitrogen compound metabolism, lipid metabolism, macromolecule metabolism, and secondary metabolism. Interestingly, citric acid content was maintained under LT but glucose and fructose concentrations decreased significantly under LT after 72 DAH (Fig. 4). Hexose may be converted to citric acid during lengthy LT storage. Alternatively, glycosyl hydrolases, which catalyse the hydrolysis of glycosidic linkages to release smaller sugars, are extremely common enzymes with roles in nature including the degradation of biomass, such as cellulose and hemicellulose in the plant cell wall (Lopez-Casado et al., 2008). Down-regulation of glycosyl hydrolases delays degradation of the plant cell wall (Lee et al., 2007), and thereby inhibits fruit senescence.
Secondary metabolites are crucial components of fruit quality (Carli et al., 2009). Interestingly, most secondary metabolism genes were down-regulated under LT but the concentrations of naringin, limonin, and nomilin increased under LT. As limonin and nomilin have antioxidant capacity and might be involved in the cold stress response (Sun et al., 2005), the accumulation of naringin, limonin, and nomilin is likely to play a vital role in fruit response to LT stress.
Lipid metabolism has an important cold-tolerance role in plants (Badea and Basu, 2009). Plant membrane lipids have a tendency to change from a gel to a liquid-crystalline phase in response to LT stress by increasing the concentration of unsaturated fatty acids present (Badea and Basu, 2009). Membrane degradation is an early manifestation of senescence (Thompson et al., 1998) and the down-regulation of lipid-degrading genes would inhibit fruit senescence.
Alcohol metabolites, which were found to be volatile organic compounds, have been used for many years for sterilization and for their fungicidal and insecticidal properties (Pesis, 2005). Acetaldehyde and ethanol have been shown to retard senescence and inhibit ethylene production in plants, leading to fewer cold shock-related injuries in various fruits (Pesis, 2005). LT induced the accumulation of acetaldehyde and methanol, which not only inhibited fruit ripening and senescence by the inhibition of respiration and interference with normal biosynthesis (Podd and Van Staden, 1998), but also had an effect on fruit response to LT stress.
Fruit storage is a nutrient-maintaining and self-consuming process. Little information is available on substrate transportation during storage. Out of a total of 198 transporter genes, only eight genes were up-regulated by LT. The remaining genes were down-regulated by LT and are thought to encode for ion transport, vesicle-mediated transport, mitochondrial transport, protein transport, secretion, and intercellular transport. Therefore, the intercommunication of intercellular substrates is not unique. The communication between organelles, between cells, and between juice sac and pericarp is reduced in response to LT stress.
In summary, a distinct feature of fruit senescence is the substantial degradation of macromolecules (such as polysaccharides, proteins, and lipids) and nutritional substances (such as sugars and organic acids) during the latter stages of storage. This study suggests that LT maintained fruit quality mainly by inhibiting fruit senescence and inhibiting the transportation of substrates.
Sugar-, auxin- and ABA-mediated fruit senescence during post-harvest storage
Fruit senescence is the final stage in fruit development and maturation. Senescence is not simply an aging-dependent passive death, it is a tightly organized and controlled process in which cell components are degraded in a coordinated fashion (Xue-Xuan et al., 2010). To date, the ripening mechanisms of climacteric fruit, especially the effect of ethylene, have been well studied (Alexander and Grierson, 2002); Sugars are important signals in the regulation of plant metabolism and development, and sugar accumulation can induce senescence (Wingler and Roitsch, 2008). Moreover, senescence is influenced by plant hormones, including ethylene, ABA, and auxin.
Sugars, which are vital to fruit quality, apparently serve as signalling molecules that might alter the biochemical or developmental processes in the fruit (Jin et al., 2009b). In the present study, the fructose and glucose contents decreased under LT, and some glucose- and fructose-binding proteins were down-regulated by LT, which might play a role in signal transduction (Moore et al., 2003). This does not agree with the plant model, in which sugars are accumulated under LT in response to cold stress (Xue-Xuan et al., 2010). It is likely to be the intrinsic trait of post-harvest citrus fruit. LT decreased the glucose and fructose contents, then the hexose-transferred signal, and, finally, fruit senescence was inhibited.
Evidence suggests that auxin is involved in the senescence process (Lim et al., 2010); however, the role of auxin in senescence has been elusive, particularly because of its involvement in various aspects of growth and development. Most of these processes are initiated and/or mediated through auxin-regulated gene expression (Guilfoyle and Hagen, 2007). Auxin response factors are repressors of auxin signalling, which modulates early auxin-induced gene expression in plants (Tiwari et al., 2003). The decreased auxin response factors accelerated the auxin signal and then inhibited senescence (Lim et al., 2010).
ABA is essential for the induction and maintenance of fruit maturation and senescence (Cara and Giovannoni, 2008). In the present study, LT decreased ABA content, down-regulated ABA-related genesm and delayed fruit senescence. However, ABA is required for plant adaptation to environmental stress and the ABA-mediated stress response is the transcriptional regulation of stress-responsive gene expression (Knight and Knight, 2001). Many genes in vegetative tissues have been reported to be up-regulated under stress conditions (Xue-Xuan et al., 2010). ABA signal transduction might be a characteristic present in citrus fruit during post-harvest storage, which is not involved in LT stress. Ethylene and ROS are reported to be intracellular messengers and have been proven to have a crucial function in the signalling network operation of senescence (Xue-Xuan et al., 2010). As reported in tomato by Zhang et al. (2009), the ABA content possibly precedes ethylene production in fruit flesh. However, in this study no ethylene-related protein was found among the differentially accumulated proteins, and some ethylene-related genes changed their expression slightly. Additionally, endogenous ethylene is ineffective in inducing the ripening and senescence of non-climacteric fruit (Malladi and Burns, 2008), which means ethylene might not participate in ABA-mediated citrus fruit senescence. Moreover, fruit senescence has been reported to be an oxidative phenomenon in apple, which is regulated by ROS through changing the expression profiles of the mitochondrial proteins superoxide dismutase and oxidoreductase (Qin et al., 2009). However, no obvious change in the expression of the ROS-related genes for oxidoreductase, ascorbate peroxidase 2, or superoxide dismutase was found at the protein level or at the mRNA level in this study (Fig. 8), and ascorbic acid showed only a weak linkage with LT storage (Supplementary Data). This suggests ROS may only have a small role to play in the regulation of citrus fruit senescence, which is a result that will need further verification.
Taking the results of this study together, LT-delayed fruit senescence is likely to be regulated by hexose-mediated ABA and the auxin signal pathway.
Conclusion
The results of this study provide a global picture of protein accumulation and changes of gene expression in HBP fruit during post-harvest storage at LT. Interpretation of the data for the proteins and mRNA revealed that some of them have been described in studies of cold-stress responses, indicating the comparability with cold-stress response in living plants and the validity of this work for further in-depth studies. This study has provided new insights into fruit post-harvest storage. During the response to LT stress, chitinase, cysteine synthase, cysteine protease inhibitor, allyl alcohol dehydrogenase, putative aldehyde dehydrogenase, and mitochondrial aldehyde dehydrogenase were up-regulated and there was an accumulation of limonin, nomilin, methanol, and aldehyde. Moreover, ABA does not appear to be involved in LT stress response, which was first discovered in fruit. Ca2+ seems to be involved in signal transfer during LT stress and the CBL–CIPK pathway played a vital role in LT signal transduction. For fruit senescence, hydrolysis-related genes were down-regulated by LT, which delayed fruit softening. Genes involved in carbohydrate metabolism, nitrogen compound metabolism, lipid metabolism, macromolecule metabolism, and secondary metabolism were down-regulated, which maintains fruit quality, and transporter genes were down-regulated, which inhibited the exchange of substrate. All of the gene expression might be regulated by hexose, ABA, and auxin, and they might cross-communicate and work collaboratively in fruit senescence and the LT stress response.
Supplementary material
Supplementary data are available at JXB online.
Supplementary Table S1. Specific primers used in relative quantitative real-time reverse-transcription PCR.
Supplementary Table S2. Summary statistics of DGE tags in LT- and AT-stored HBP fruit juice sacs.
Supplementary Fig. S1. Graphical output of the LT-storage stress down-regulated metabolic genes found in HBP fruit juice sacs.
Supplementary Fig. S2. Graphical output of differentially expressed transporter genes in HBP fruit juice sacs.
Supplementary Fig. S3. Graphical output of differentially expressed signal transduction genes in HBP fruit juice sacs.
Supplementary Fig. S4. Graphical output of differentially expressed signal transduction genes in HBP fruit juice sacs.
Supplementary Excel S1. LT up-regulated and down-regulated genes.
The authors thank Mr Chenrui Hou (Shanghai Applied Protein Technology, China) and Mr Guangwu Guo (Beijing Genomics Institute) for helpful suggestions on the proteome and DGE data analyses, respectively, and Prof Hanhui Kuang (Huazhong Agricultural University) for help in revising the manuscript. This work was supported by Huazhong Agricultural University Scientific & Technological Self-innovation Foundation, the Natural Science Foundation of China (NSFC; no. 30972061 and 30921002), the National Basic research programme of China (973 programme; no. 2011CB100601), the Foundation for the Author of National Excellent Doctoral Dissertation of China (no. 2007B5); and the National Modern Agriculture (Citrus) Technology Systems of China (no. CARS-27).
References
Ethylene biosynthesis and action in tomato: a model for climacteric fruit ripening
,
Journal of Experimental Botany
,
2002
, vol.
53
(pg.
2039
-
2055
)
A defined range of guard cell calcium oscillation parameters encodes stomatal movements
,
Nature
,
2001
, vol.
411
(pg.
1053
-
1057
)
An evaluation of the basis and consequences of a stay-green mutation in the navel negra citrus mutant using transcriptomic and proteomic profiling and metabolite analysis
,
Plant Physiology
,
2008
, vol.
147
(pg.
1300
-
1315
)
The physiological, biochemical and molecular roles of brassinosteroids and salicylic acid in plant processes and salt tolerance
,
Critical Reviews in Plant Sciences
,
2010
, vol.
29
(pg.
162
-
190
)
The significance of digital gene expression profiles
,
Genome Research
,
1997
, vol.
7
(pg.
986
-
995
)
The effect of low temperature on metabolism of membrane lipids in plants and associated gene expression
,
Plant Omics
,
2009
, vol.
2
(pg.
78
-
84
)
Grapefruit juice–felodipine interaction: mechanism, predictability, and effect of naringin
,
Lancet
,
1993
, vol.
53
(pg.
637
-
642
)
Simultaneous determination of soluble sugars and organic acids as their trimethylsilyl derivatives in apricot fruits by gas-liquid chromatography
,
Journal of Chromatography A
,
1997
, vol.
758
(pg.
99
-
107
)
et al.
Signaling pathways mediating the induction of apple fruitlet abscission
,
Plant Physiology
,
2011
, vol.
155
(pg.
185
-
208
)
Molecular biology of ethylene during tomato fruit development and maturation
,
Plant Science
,
2008
, vol.
175
(pg.
106
-
113
)
Use of network analysis to capture key traits affecting tomato organoleptic quality
,
Journal of Experimental Botany
,
2009
, vol.
60
(pg.
3379
-
3386
)
CBL1, a calcium sensor that differentially regulates salt, drought, and cold responses in Arabidopsis
,
The Plant Cell
,
2003
, vol.
15
(pg.
1833
-
1845
)
Temperature-induced lipocalin is required for basal and acquired thermotolerance in Arabidopsis
,
Plant Cell and Environment
,
2009
, vol.
32
(pg.
917
-
927
)
Cold stress regulation of gene expression in plants
,
Trends in Plant Science
,
2007
, vol.
12
(pg.
444
-
451
)
et al.
Transcriptome analysis of Medicago truncatula leaf senescence: similarities and differences in metabolic and transcriptional regulations as compared with Arabidopsis, nodule senescence and nitric oxide signalling
,
New Phytologist
,
2009
, vol.
181
(pg.
563
-
575
)
Roles for Arabidopsis CAMTA transcription factors in cold-regulated gene expression and freezing tolerance
,
The Plant Cell
,
2009
, vol.
21
(pg.
972
-
984
)
Gibberellic acid alters sucrose, hexoses, and their gradients in peel tissues during color break delay in ‘Hamlin’ orange
,
Journal of the American Society for Horticultural Science
,
2008
, vol.
133
(pg.
760
-
767
)
Comparison of developmental and stress-induced nodule senescence in Medicago truncatula
,
Plant Physiology
,
2010
, vol.
152
(pg.
1574
-
1584
)
Auxin response factors
,
Current Opinion in Plant Biology
,
2007
, vol.
10
(pg.
453
-
460
)
Research on plant abiotic stress responses in the post-genome era: past, present and future
,
The Plant Journal
,
2010
, vol.
61
(pg.
1041
-
1052
)
Sample extraction techniques for enhanced proteomic analysis of plant tissues
,
Nature Protocols
,
2006
, vol.
1
(pg.
769
-
774
)
Expression of ROP/RAC GTPase genes in postharvest loquat fruit in association with senescence and cold regulated lignification
,
Postharvest Biology and Technology
,
2009
, vol.
54
(pg.
9
-
14
)
Posttranslational elevation of cell wall invertase activity by silencing its inhibitor in tomato delays leaf senescence and increases seed weight and fruit hexose level
,
The Plant Cell
,
2009
, vol.
21
(pg.
2072
-
2089
)
et al.
A genetic link between cold responses and flowering time through FVE in Arabidopsis thaliana
,
Nature Genetics
,
2004
, vol.
36
(pg.
167
-
171
)
Abiotic stress signalling pathways: specificity and cross-talk
,
Trends in Plant Science
,
2001
, vol.
6
(pg.
262
-
267
)
Calcium sensors and their interacting protein kinases: genomics of the Arabidopsis and rice CBL-CIPK signaling networks
,
Plant Physiology
,
2004
, vol.
134
(pg.
43
-
58
)
Glycosyl hydrolases of cell wall are induced by sugar starvation in Arabidopsis
,
Plant and Cell Physiology
,
2007
, vol.
48
(pg.
405
-
413
)
Auxin response factor 2 (ARF2) plays a major role in regulating auxin-mediated leaf longevity
,
Journal of Experimental Botany
,
2010
, vol.
61
(pg.
1419
-
1430
)
Cold storage duration affects litchi fruit quality, membrane permeability, enzyme activities and energy charge during shelf time at ambient temperature
,
Postharvest Biology and Technology
,
2011
, vol.
60
(pg.
24
-
30
)
Transcriptome analysis of a spontaneous mutant in sweet orange [Citrus sinensis (L.) Osbeck] during fruit development
,
Journal of Experimental Botany
,
2009
, vol.
60
(pg.
801
-
813
)
Plant glycosyl hydrolases and biofuels: a natural marriage
,
Current Opinion in Plant Biology
,
2008
, vol.
11
(pg.
329
-
337
)
The CBL-CIPK network in plant calcium signaling
,
Trends in Plant Science
,
2009
, vol.
14
(pg.
37
-
42
)
Calmodulins and calcineurin B-like proteins: calcium sensors for specific signal response coupling in plants
,
The Plant Cell
,
2002
, vol.
14
(pg.
S389
-
S400
)
CsPLD alpha 1 and CsPLD gamma 1 are differentially induced during leaf and fruit abscission and diurnally regulated in Citrus sinensis
,
Journal of Experimental Botany
,
2008
, vol.
59
(pg.
3729
-
3739
)
Transcriptome profiling of grapefruit flavedo following exposure to low temperature and conditioning treatments uncovers principal molecular components involved in chilling tolerance and susceptibility
,
Plant Cell and Environment
,
2008
, vol.
31
(pg.
752
-
768
)
Respiration rate, internal atmosphere, and ethanol and acetaldehyde accumulation in heat-treated mango fruit
,
Postharvest Biology and Technology
,
1993
, vol.
3
(pg.
77
-
86
)
Role of the Arabidopsis glucose sensor HXK1 in nutrient, light, and hormonal signaling
,
Science
,
2003
, vol.
300
(pg.
332
-
336
)
Next-generation tag sequencing for cancer gene expression profiling
,
Genome Research
,
2009
, vol.
19
(pg.
1825
-
1835
)
A fruit quality gene map of
,
Prunus. BMC Genomics
,
2009
, vol.
10
pg.
587
Comparative proteomics of a lycopene-accumulating mutant reveals the important role of oxidative stress on carotenogenesis in sweet orange (Citrus sinensis [L.] osbeck)
,
Proteomics
,
2009
, vol.
9
(pg.
5455
-
5470
)
The role of the anaerobic metabolites, acetaldehyde and ethanol, in fruit ripening, enhancement of fruit quality and fruit deterioration
,
Postharvest Biology and Technology
,
2005
, vol.
37
(pg.
1
-
19
)
The role of ethanol and acetaldehyde in flower senescence and fruit ripening – a review
,
Plant Growth Regulation
,
1998
, vol.
26
(pg.
183
-
189
)
Proteomic analysis of changes in mitochondrial protein expression during fruit senescence
,
Proteomics
,
2009
, vol.
9
(pg.
4241
-
4253
)
Sweet silver: a formaldehyde-free silver staining using aldoses as developing agents, with enhanced compatibility with mass spectrometry
,
Proteomics
,
2008
, vol.
8
(pg.
4853
-
4861
)
Matrix-assisted laser desorption/ionization time-of-flight/time-of-flight tandem mass spectra of poly(butylene adipate)
,
Rapid Communications in Mass Spectrometry
,
2006
, vol.
20
(pg.
1683
-
1694
)
Salt stress induced differential proteome and metabolome response in the shoots of Aeluropus lagopoides (Poaceae), a halophyte C-4 plant
,
Journal of Proteome Research
,
2010
, vol.
9
(pg.
2882
-
2897
)
Mode of action of the COR15a gene on the freezing tolerance of Arabidopsis thaliana
,
Proceedings of the National Academy of Sciences of the United States of America
,
1998
, vol.
95
(pg.
14570
-
14575
)
Contents and antioxidant capacity of limonin and nomilin in different tissues of citrus fruit of four cultivars during fruit growth and maturation
,
Food Chemistry
,
2005
, vol.
93
(pg.
599
-
605
)
Reciprocity between abscisic acid and ethylene at the onset of berry ripening and after harvest
,
BMC Plant Biology
,
2010
, vol.
10
pg.
257
Deep sequencing-based expression analysis shows major advances in robustness, resolution and inter-lab portability over five microarray platforms
,
Nucleic Acids Research
,
2008
, vol.
36
pg.
e141
Proteomic signatures uncover hydrogen peroxide and nitric oxide cross-talk signaling network in citrus plants
,
Journal of Proteome Research
,
2010
, vol.
9
(pg.
5994
-
6006
)
Plant cold acclimation: freezing tolerance genes and regulatory mechanisms
,
Annual Review of Plant Physiology and Plant Molecular Biology
,
1999
, vol.
50
(pg.
571
-
599
)
Lipid metabolism during plant senescence
,
Progress in Lipid Research
,
1998
, vol.
37
(pg.
119
-
141
)
The roles of auxin response factor domains in auxin-responsive transcription
,
The Plant Cell
,
2003
, vol.
15
(pg.
533
-
543
)
et al.
Comparative EST transcript profiling of peach fruits under different post-harvest conditions reveals candidate genes associated with peach fruit quality
,
BMC Genomics
,
2009
, vol.
10
pg.
423
Role of plant heat-shock proteins and molecular chaperones in the abiotic stress response
,
Trends in Plant Science
,
2004
, vol.
9
(pg.
244
-
252
)
Metabolic regulation of leaf senescence: interactions of sugar signalling with biotic and abiotic stress responses
,
Plant Biology
,
2008
, vol.
10
(pg.
50
-
62
)
Comparative transcripts profiling reveals new insight into molecular processes regulating lycopene accumulation in a sweet orange (Citrus sinensis) red-flesh mutant
,
BMC Genomics
,
2009
, vol.
10
pg.
540
Biotechnological implications from abscisic acid (ABA) roles in cold stress and leaf senescence as an important signal for improving plant sustainable survival under abiotic-stressed conditions
,
Critical Reviews in Biotechnology
,
2010
, vol.
30
(pg.
222
-
230
)
Regulation of growth response to water stress in the soybean primary root. I. Proteomic analysis reveals region-specific regulation of phenylpropanoid metabolism and control of free iron in the elongation zone
,
Plant Cell and Environment
,
2010
, vol.
33
(pg.
223
-
243
)
Comparative proteomic analysis provides new insights into chilling stress responses in rice
,
Molecular & Cellular Proteomics
,
2006
, vol.
5
(pg.
484
-
496
)
Silencing Sl-EBF1 and Sl-EBF2 expression causes constitutive ethylene response phenotype, accelerated plant senescence, and fruit ripening in tomato
,
Journal of Experimental Botany
,
2010
, vol.
61
(pg.
697
-
708
)
Study on quality variation of murcott fruits during low-temperature storage
,
Fujian Journal of Agricultural Sciences
,
2011
(pg.
269
-
274
)
Comparative proteomics analysis of differentially accumulated proteins in juice sacs of ponkan (Citrus reticulata) fruit during postharvest cold storage
,
Postharvest Biology and Technology
,
2010
, vol.
56
(pg.
189
-
201
)
The role of ABA in triggering ethylene biosynthesis and ripening of tomato fruit
,
Journal of Experimental Botany
,
2009
, vol.
60
(pg.
1579
-
1588
)
© 2012 The Author(s).
This is an Open Access article distributed under the terms of the Creative Commons Attribution Non-Commercial License (http://creativecommons.org/licenses/by-nc/3.0), which permits unrestricted non-commercial use, distribution, and reproduction in any medium, provided the original work is properly cited.This paper is available online free of all access charges (see http://jxb.oxfordjournals.org/open\_access.html for further details)