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Article

Transcriptome Analysis of Ethylene-Related Genes in Chlorine Dioxide-Treated Fresh-Cut Cauliflower

by
Weiwei Jin
1,2,
Qiaojun Jiang
1,2,
Haijun Zhao
1,3,
Fengxian Su
1,2,
Yan Li
1,2,* and
Shaolan Yang
4
1
Institute of Food Science, Wenzhou Academy of Agricultural Science, Wenzhou 325006, China
2
Southern Zhejiang Key Laboratory of Crop Breeding, Wenzhou 325006, China
3
College of Life Science and Engineering, Lanzhou University of Technology, Lanzhou 730050, China
4
College of Horticulture, Qingdao Agricultural University, Qingdao 266109, China
*
Author to whom correspondence should be addressed.
Genes 2024, 15(8), 1102; https://doi.org/10.3390/genes15081102
Submission received: 29 July 2024 / Revised: 16 August 2024 / Accepted: 20 August 2024 / Published: 21 August 2024
(This article belongs to the Special Issue Gene Regulation of Ripening, Senescence and Stress Resistance in Horticultural Crops)
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Abstract

:
Chlorine dioxide (ClO2) is widely used for the quality preservation of postharvest horticultural plants. However, the molecular mechanism of how ClO2 works is not clear. The purpose of this study was to understand ethylene-related molecular signaling in ClO2-treated fresh-cut cauliflower florets. Transcriptome analysis was used to investigate ethylene-related gene regulation. A total of 182.83 Gb clean data were acquired, and the reads of each sample to the unique mapped position of the reference genome could reach more than 85.51%. A sum of 2875, 3500, 4582 and 1906 differential expressed genes (DEGs) were identified at 0 d, 4 d, 8 d and 16 d between the control group and ClO2-treated group, respectively. DEGs were enriched in functions such as ‘response to oxygen-containing compounds’ and ‘phosphorylation’, as well as MAPK signaling pathway, plant hormone transduction pathway and so on. Genes, including OXI1, MPK3, WRKY22 and ERF1, which are located at the junction of wounding, pathogen attack, pathogen infection or ethylene signal transduction pathways, were up-regulated in response to stress. ETR and CTR1 (both up-regulated), as well as three down-regulated genes, including BolC5t34953H (a probable NAC), BolC1t05767H (a probable NAC) and BolC2t06548H (a probable ERF13), might work as negative regulators for ethylene signal transduction. In conclusion, ethylene-related genes and pathways are involved in ClO2 treatment, which might enhance stress resistance and have a negative feedback mechanism.

1. Introduction

Cruciferae vegetables are widely cultivated in the world. They are rich in nutrition and health-promoting components, e.g., glucosinolates and isothiocyanates, which may help reduce the risk of cancer [1,2,3,4]. Currently, fresh-cut vegetables have become more popular among consumers because of their convenience [5]. Cauliflower (Brassica oleracea L. var. botrytis), as one of the largest varieties of Cruciferae vegetables, patently accounts for a large proportion of the ready-to-eat market. However, fresh-cut cauliflower is more susceptible to microbes due to mechanical injury, resulting in faster quality deterioration, including senescence, mildew and decay [6]. Lots of treatments, such as ultrasound, gamma irradiation, electrostatic field and packaging, have been applied to fresh-cut cauliflower for quality maintenance and shelf-life extending [6,7,8,9,10]. But there are few reports on the effect of chlorine dioxide (ClO2) treatment on the preservation of fresh-cut cauliflower.
ClO2 has been used as a Class A1 disinfectant for food preservation around the world [11,12]. The broad antimicrobial effect of ClO2 on bacteria, fungi, spores and virus is well known, as well as the higher oxidative capacity with the lower concentration and shorter treatment time of ClO2 compared to chlorine [13]. A treatment of 60 mg·L−1 ClO2 for 10 min on fresh-cut coriander could decrease the total number of aerobic bacterial colonies to 2.1 lg CFU/g [14]. In addition to sterilization, ClO2 shows superiority for the postharvest storage of horticultural produce [15]. A treatment of 100 mg·L−1 ClO2 for 20 min could inhibit enzymatic browning and prolong the shelf-life of fresh-cut asparagus lettuce to 14 d [16]. The activities of enzymes related to senescence and lignification in fresh-cut bamboo were effectively inhibited after treatment with 28 mg·L−1 ClO2 plus chitosan coating [17]. Lin et al. found by transcriptome analysis that 50 mg·L−1 ClO2 could effectively keep the floret green and delay the senescence process of fresh-cut broccoli [18].
As a kind of phytohormone, ethylene is known for its role in the ripening of horticultural plants, eventually leading to senescence [19]. In addition, ethylene also plays a significant role in pathogens, heat and cold stress responses [20,21,22,23]. Lin et al. reported that ClO2 treatment could inhibit ethylene biosynthesis through the regulation of ethylene-responsive transcription factor (ERF) expression and delay the yellowing of fresh-cut broccoli [18]. But how ClO2 treatment affects ethylene-related gene expression in fresh-cut cauliflower remains unknown.
To reveal the effect of ClO2 treatment on fresh-cut cauliflower at the molecular level, a transcriptome analysis of ethylene-related genes in fresh-cut cauliflower florets regulated by ClO2 treatment was carried out in this study. DEGs regulated by ClO2 treatment were screened out, and the signaling pathways involved in DEGs were analyzed. This study may enrich comprehension and lay the foundation for further research on the function mechanism of ClO2 treatment.

2. Materials and Methods

2.1. Experimental Materials and Treatment Methods

Fresh white cauliflowers (Brassica oleracea L. var. botrytis) were harvested from the farm of Wenzhou Academy of Agricultural Sciences and were transported directly to Southern Zhejiang Key Laboratory of Crop Breeding within 1 h. Cauliflowers were selected for uniformity of size, weight and absence of any defect, mechanical injury or decay. After manual removal of outer leaves, cauliflower was cut into individual florets of 4–5 cm length. The cutting board, knife and hands were sterilized with 50 mg·L−1 sodium hypochlorite solution (pH 6.5).
The cauliflower florets were divided randomly into two groups and were immersed in deionized water (the control group, CK) or 100 mg·L−1 chlorine dioxide solutions (the treatment group, T) for 15 min and then air-dried. Subsequently, each group of florets weighting approximately 200 g was packaged in a polyethylene film bag (thickness: 6 μm, dimensions = 40 cm × 35 cm) and then stored under 4 °C ± 1 and 85 ± 5% RH in a refrigerator. Samples were collected at 0, 4, 8 and 16 d after cold storage and frozen in liquid nitrogen and stored at −80 °C for further study. Three biological replicates of each sample were used in the experiments.

2.2. RNA-Seq Analysis

The cauliflower floret samples were sent to Shanghai Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China) for RNA sequencing and bioinformatics analysis. Total RNA was extracted from the cauliflower florets. A quality evaluation of isolated RNA including purity and concentration, integrity and RNA quality number (RQN) was performed by NanoDrop 2000, agarose gel electrophoresis and Agilent 5300, respectively. Single cDNA library construction required that the total RNA of all samples was 1 μg, the concentration was greater than 30 ng·μL−1, RQN > 6.5, and OD260/OD280 was between 1.8 and 2.0.
The library preparation was sequenced on the Illumina NovaSeq X Plus platform. Fastp software (version 0.23.4, https://github.com/OpenGene/fastp, accessed on 5 July 2024) was used to filter out repetitive redundant sequences and low-quality sequences from the raw reads to obtain high-quality sequences (clean reads) for subsequent analysis. Reads were mapped to the Boleracea HDEM Genome database (https://www.genoscope.cns.fr/externe/plants/chromosomes.html, accessed on 5 July 2024) by using Hisat2 software (version 2.2.1, https://daehwankimlab.github.io/hisat2/, accessed on 5 July 2024). Stringtie software (version 2.2.1, https://ccb.jhu.edu/software/stringtie/, accessed on 5 July 2024) was used for reference-based assembly and quantification.
The expression levels of genes were calculated using FPKM (fragments per kilobase of transcript per million fragments mapped) with RSEM software (version 1.3.3, http://deweylab.biostat.wisc.edu/rsem/, accessed on 8 July 2024). DESeq2 software (version 1.42.0, https://bioconductor.org/packages/release/bioc/html/DESeq2.html, accessed on 8 July 2024) was used to standardize the read count of differential expressed genes (DEGs) between the CK group and T group of cauliflower florets. DEGs were screened by |log2 (fold change)| ≥ 1 and Padj value < 0.05. BLAST+ software (version 2.9.0, https://ftp.ncbi.nlm.nih.gov/blast/executables/blast+/2.9.0/, accessed on 8 July 2024) was used to compare DEGs with Gene Ontology (GO) and KEGG (Kyoto Encyclopedia of Genes and Gnomes) databases. GO enrichment analysis of DEGs was performed using Goatools software (version 1.4.4, https://pypi.org/project/goatools/, accessed on 8 July 2024). A KEGG signaling pathway enrichment analysis of DEGs was performed using R script. Both analyses required Padj value < 0.05 as the criterion for enrichment.

3. Results

3.1. Transcriptome Sequencing Quality Assessment

To explore the regulation of ethylene-related genes after ClO2 treatment, transcriptome analysis was performed on 24 cauliflower floret samples using RNA-Seq technology. 182.83 Gb of clean data were acquired, and each sample received approximately 6.53 Gb of clean data, with the proportion of Q30 bases exceeding 96.42%. The clean data of each sample were mapped to the reference genome for sequence comparison. The comparison rate ranged from 89.55% to 90.48%, and the reads of each sample to the unique mapped position of the reference genome could reach more than 85.51%. Descriptive statistics on the quality of the transcriptome sequencing of cauliflower florets treated with ClO2 are shown in Table 1.
PCA calculation was executed on the transcriptome data to detect the similarity and variability between the ClO2 treatment (T) and the control (CK) groups. The results are shown in Figure 1. The principal component 1 (PC1) accounted for 37.09% of the variance and principal component 2 (PC2) accounted for 15.49% of the variance. Both at the level of PC1 and PC2, the T group samples at 4 d and 8 d were well separated from the CK group samples at the same time point, respectively. However, the differentiation between the T group and CK group at the early storage time (0 d) and the ending storage time (16 d) was less apparent. The results showed that clear separation between ClO2 treatment and control samples was observed during the middle storage period. The biological replicates were mainly grouped along PC2, which suggests larger variations between experimental treatments than biological replicates. And it is clear that samples at 0 d showed the greatest variation when compared with samples at other time points.

3.2. Identification and Analysis of DEGs

The results of DEG screening from CK and T groups of cauliflower florets are shown in Figure 2. Fold change (FC) represents the ratio of gene expression between CK and T groups. When the value of |log2 (FC) | was greater than 1, the gene was identified as an up-regulated expression; otherwise, it was down-regulated.
The number of DEGs during the whole storage exhibited a pattern of initial increase followed by subsequent decrease. At 0 d, 1159 DEGs were up-regulated, and 1716 DEGs were down-regulated in the ClO2 group compared with the control. The numbers of up-regulated DEGs increased until 8 d and then declined significantly at 16 d, which was consistent with the trend of total DEGs. The results of DEGs between the ClO2 treatment and control groups were consistent with those of PCA analysis from Figure 1.
The Venn diagram of DEGs during storage is shown in Figure 3. Among all DEGs, 183 genes exhibited presence at every storage time in the ClO2 and control groups, and further study on the 183 genes was conducted subsequently. 499 DEGs were shared between D0_T vs D0_CK and D16_T vs D16_CK, which was the least number among the pair-wise comparison of all samples.

3.3. Go Function Analysis of DEGs

GO functional analysis showed that the DEGs were mainly annotated to biological processes and molecular functions at 0 d and 8 d (Figure 4A,C). DEGs in the biological process categories were mainly associated with response to many kinds of conditions, such as oxygen-containing compounds, hormones, abiotic stimulus, etc. It was found that ‘response to oxygen-containing compound’ was the most enriched annotation at 0 d, 4 d and 16 d (Figure 4A,B,D). Functional enrichment to the ‘phosphorylation’ of DEGs came out at 4 d, which was the top five enriched annotations of biological processes (Figure 4B). ‘Protein phosphorylation, phosphorylation and defense response’ were the top three enriched biological process functions successively among DEGs at 8 d, while the first and the third function had not come out before (Figure 4C). Additionally, it was found that the enrichment of DEGs to ‘molecular function’ increased until 8 d and then declined at 16 d which meant more catalytic activity and binding function were executed. Compared with 0 d and 8 d, there was a little change in 4 d and 16 d, that is, the DEGs were also annotated to cellular components (Figure 4B,D). The only subgroup of the cellular component was the plasma membrane.

3.4. KEGG Enrichment Analysis of DEGs

The 20 most enriched KEGG pathways of every storage time are shown in Figure 5. At the 0 d time point, DEGs were significantly enriched in the pathways of the MAPK signaling pathway, plant hormone signal transduction, ribosome biogenesis in eukaryotes, linoleic acid metabolism, plant–pathogen interaction and cutin, suberine and wax biosynthesis (Figure 5A), while at the 4 d time point, DEGs were significantly enriched in all the 20 pathways, and the top 5 enriched pathways were the MAPK signaling pathway, plant hormone signal transduction, glycolysis/gluconeogenesis, plant–pathogen interaction and the biosynthesis of various plant secondary metabolites (Figure 5B). At 8 d, the top 5 enriched pathways were plant–pathogen interaction, starch and sucrose metabolism, biosynthesis of various plant secondary metabolites, cyanoamino acid metabolism and the MAPK signaling pathway (Figure 5C). At 16 d, the top 5 enriched pathways were MAPK signaling pathway, starch and sucrose metabolism, cyanoamino acid metabolism, carotenoid biosynthesis and plant hormone signal transduction (Figure 5D). The analysis revealed that the MAPK signaling pathway and plant hormone signal transduction both exhibited significantly at every storage time.

3.5. DEGs Involved in Ethylene-Related Response

As DEGs were significantly enriched in the MAPK signaling pathway, plant hormone signal transduction and other pathways that might be related to plant ethylene, a further study of DEGs related to ethylene was carried out.
About 20 genes were screened out based on GO enrichment analyses (Table 2). All of them showed significant differences in expression between the CK and T groups at 4 d, and the value of Log2FC of 4 d is shown in Table 2. Among them, three genes were down-regulated, including BolC5t34953H (a probable NAC), BolC1t05767H (a probable NAC) and BolC2t06548H (a probable ERF113). The former two genes were annotated as a ‘positive regulation of ethylene biosynthetic process’. However, they were down-regulated in ClO2-treated samples, which might suggest that ClO2 treatment could delay the ethylene biosynthetic process. The latter one was a member of the ERF family, and it might negatively control ethylene biosynthesis, while the other 8 ERF and 2 probable ERF genes (BolC1t01080H, BolC6t38599H, BolC4t28768H, BolC3t17122H, BolC8t48489H, BolC3t14461H, BolC7t43635H, BolC9t55823H, BolC3t18401H and BolC9t53913H) behaved oppositely. BolC1t04038H (ETR), BolC2t09157H (MKK9), BolC3t12569H (MPK4) and BolC9t54716H (Rboh) were all involved in the MAPK signaling pathway, and they need further comprehensive analysis. The last three genes are new in KEGG database and need further excavation.
A total of 22 genes were found up-regulated in ethylene-related signaling pathways, including the MAPK signaling pathway and plant hormone signal transduction, based on KEGG enrichment analyses (Figure 6). Except for FLS2 (BolC9t55719H), ETR, CTR1 (BolC1t01812H), ERF1 and ANP1 (BolC5t34783H), which were up-regulated only at 4 d, the other genes were up-regulated both at 4 d and 8 d (Figure 7).
As samples were fresh-cut products, the wounding branch of the MAPK pathway was initiated. In group T, CaM4 (BolC4t26580H, BolC9t53342H, BolC6t37076H, BolC4t26192H and BolC9t53448H), RbohD (BolC9t54716H, BolC7t44400H and BolC2t10212H) and OXI1 (BolC7t41531H) were up-regulated significantly for maintaining the homeostasis of ROS. OXI1 was also involved in the pathogen attack branch of the MAPK pathway, and the WRKY22 (BolC9t53005H) at the end of the branch was up-regulated for the defense of cell death and H2O2 production. ETR and CTR1 were up-regulated in the pathogen attack branch by ClO2 treatment. The difference in ETR between CK and T was significantly increased at 4 d and 16 d, while the difference in CTR1 was only significantly increased at 4 d (Figure 7). Finally, the last downstream gene PDF1.2 (BolC2t09321H) was up-regulated by ERF1 for defense response. Besides ETR and CTR1, ERF1 and ERF2 (BolC7t43635H, BolC9t55823H) that are involved in plant ethylene signal transduction were also up-regulated in the T group. For the pathogen infection branch, FLS2, MPK3 (BolC3t19268H), WRKY22 and ACS6 (BolC5t28842H, BolC9t56371H) were found up-regulated for early defense response to pathogen and ethylene synthesis.

4. Discussion

Fresh-cut vegetables provide not only nutrients but also great convenience for cooking. However, they face a more arduous storage process than fresh products because of mechanical injury. Many reports have explored the antimicrobial mechanism of ClO2 and its effect on the postharvest management of horticultural products, e.g., spinach, cherry tomato [24,25,26,27,28]. Besides previous research from the physiological perspective, research is increasingly focusing on the molecular mechanism of how ClO2 acts in postharvest management.
In our study, the transcriptome method was used to investigate ethylene-related gene regulation in fresh-cut cauliflower florets under ClO2 conditions during storage. An RNA-seq analysis revealed that 2875, 3500, 4582 and 1906 DEGs were regulated at 0 d, 4 d, 8 d and 16 d, respectively (Figure 2). The Venn diagram of DEGs showed that 183 genes were existent at every storage time among all the DEGs (Figure 3). Then, genes related with ethylene were screened out based on GO and KEGG enrichment analyses.
According to RNA-seq, five and three members of CaM4 and RbohD gene families are DEGs, respectively. CaM plays a critical role in Ca2+-modulated signaling processes and helps plants adapt to abiotic stress, while RBOH plays an important role in ROS production [29,30]. RbohD is mainly responsible for stress-induced ROS burst, while RbohF, up-regulated by CaM4, is responsible for the transient accumulation of superoxide in Arabidopsis [31]. PpRbohE is also up-regulated in trehalose-treated peach fruit in the ROS signaling pathway for resistance against chilling stress [32]. Similarly, the up-regulation of CaM4 and RbohD in ClO2-treated cauliflower might be responsible for the maintenance of the homeostasis of ROS as being fresh-cut is a kind of abiotic stress and would inevitably lead to the production of ROS.
OXI1 was reported to be activated by light, and it could enhance plant immunity through regulating responses and programmed cell death (PCD) [33,34]. In this study, OXI1 was located on the junction of wounding and pathogen attack cascade. It was up-regulated and might induce the downstream gene ANP1 that plays an important role in tomato and eggplant to mitigate the infection of Tuta absoluta [35]. FLS2 that is up-regulated in pathogen infection cascade in ClO2-treated cauliflower is a receptor for flg22 and indirectly affecting the immunity of Arabidopsis [36]. Similar results and more detailed interactions have been reported in strawberry and rice [37,38].
The WRKY family is one of the largest transcript factor families in higher plants. WRKY22-like, WRKY33 and WRKY30 were down-regulated by high-oxygen-modified atmospheric packaging treatment on fresh-cut broccoli for mitigating oxidative damage from ROS accumulation [39]. Oppositely, PpWRKY40, PpWRKY45, PpWRKY69 and PpWRKY71 were up-regulated by trehalose treatment on peach fruit for promoting cold resistance; meanwhile, ROS-mediated antioxidant capability was promoted to eliminate excessive ROS production [32]. Our results showed that WRKY22 was up-regulated by ClO2 treatment. Considering the pathway in which WRKY22 is involved, it might function as an early defense response for pathogens. On the other hand, WRKY22 might function to induce ethylene biosynthesis by activating ACS6 expression (pathogen infection cascade) and promoting H2O2 accumulation (pathogen attack cascade). A similar function has been reported in carnation and oilseed rape [40,41]. DcWRKY33 activated DcACS1 and promoted petal senescence of fresh-cut carnation [40]. BnaWGR1 activated RbohD and RbohF through binding to their promoters for the accumulation of H2O2, MDA and accelerated leaf senescence in oilseed rape [41].
As mentioned above, ACS6, located downstream of WRKY22, was up-regulated in ClO2-treated cauliflower for ethylene biosynthesis in response to pathogen infection stress. However, LeACS2 and LeACS4 were down-regulated by ClO2 treatment for the suppression of ethylene biosynthesis to delay the ripening of postharvest tomato [42]. Similar results were reported in ready-to-eat broccoli and fresh-cut ‘Hami’ melon by ClO2 treatment [18,43]. Different results might suggest the different roles of ethylene in biography processes.
Both NACs and ERFs are large transcript factor families like WRKYs. SNAC4 could positively regulate ethylene synthesis by activating SACS8 to promote tomato fruit ripening [44]. DkNAC9 interacts with DkERF8/16 to activate DkEGase1, and DkERF18 activates DkACS2, both of which lead to persimmon fruit softening [45,46]. Herein, BolC5t34953H, BolC1t05767H and BolC2t06548H were all significantly down-regulated by ClO2 treatment (Table 2, Figure 7), which suggests that they may negatively regulate ethylene biosynthesis. Furthermore, ETR and CTR1, two negative regulators of ethylene response, were up-regulated by ClO2 treatment [47,48]. In summary, these five genes might be responsible for the suppression of ethylene biosynthesis.
Wang et al. reported the bidirectional regulation mechanisms of ethylene biosynthesis, where ACS2 and ACS6 were up-regulated by MPK3 and MPK6 in Arabidopsis to induce ethylene biosynthesis for pathogen defense, while ERF1A was triggered by MPK3 and MPK6 for the negative-feedback regulation of ethylene biosynthesis [49]. In our study, most genes including MPK3 and ACS6 (except for ETR and CTR1) up-regulated by ClO2 treatment might be responsible for inducing ethylene biosynthesis for pathogen defense and wounding defense. BolC5t34953H, BolC1t05767H and BolC2t06548H and ETR and CTIR1 regulated by ClO2 treatment might be responsible for the suppression of ethylene biosynthesis. A similar mechanism might be found where genes regulate ethylene biosynthesis for both positive and negative sides and eventually delay the senescence of ClO2-treated fresh-cut cauliflower florets. However, more evidence should be found.

5. Conclusions

In this study, transcriptome analysis was conducted on ClO2-treated fresh-cut cauliflower florets. DEGs related to ethylene biosynthesis and ethylene signal transduction were screened and analyzed. Results showed that ethylene-related genes and pathways were involved in stress response in fresh-cut cauliflower florets during postharvest low-temperature storage. The up-regulation of genes including OXI1, MPK3, WRKY22 and ERF1 was a response to wounding, pathogen attack or infection defense. ETR, CTR1, BolC5t34953H, BolC1t05767H and BolC2t06548H involved in the ethylene signal transduction pathway might work as negative regulators for ethylene signal transduction. The two-side regulation showed that ethylene-related genes and pathways were involved in ClO2 treatment, which might enhance stress resistance and have a negative feedback mechanism for food preservation.

Author Contributions

Conceptualization, W.J., S.Y., Y.L.; methodology, W.J. and S.Y.; software, H.Z.; validation, F.S. and Q.J.; formal analysis, W.J.; investigation, W.J.; resources, W.J. and Y.L.; data curation, W.J.; writing—original draft preparation, W.J.; writing—review and editing, W.J. and Q.J.; visualization, W.J.; supervision, W.J.; project administration, W.J.; funding acquisition, W.J. and Y.L. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Public Welfare Technology Application Research Project of Zhejiang Province (LGN21C200002) and Major scientific and technological project of Wenzhou (ZN2020001).

Institutional Review Board Statement

Not applicable.

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article. The original contributions presented in this study are included in the article. Further inquiries can be directed to the corresponding author.

Conflicts of Interest

The authors declare no conflicts of interest. All authors have read and agreed to the published version of the manuscript.

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Figure 1. PCA analysis of transcriptome data in ClO2 (T) and control (CK) group during storage.
Figure 1. PCA analysis of transcriptome data in ClO2 (T) and control (CK) group during storage.
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Figure 2. Analysis of DEGs in different comparison periods in ClO2 (T) and control (CK) group of fresh-cut cauliflower florets during storage.
Figure 2. Analysis of DEGs in different comparison periods in ClO2 (T) and control (CK) group of fresh-cut cauliflower florets during storage.
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Figure 3. Venn diagram of DEGs in ClO2 (T) and control (CK) group of fresh-cut cauliflower florets during storage.
Figure 3. Venn diagram of DEGs in ClO2 (T) and control (CK) group of fresh-cut cauliflower florets during storage.
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Figure 4. GO functional enrichment analysis of DEGs at 0 d (A), 4 d (B), 8 d (C) and 16 d (D).
Figure 4. GO functional enrichment analysis of DEGs at 0 d (A), 4 d (B), 8 d (C) and 16 d (D).
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Figure 5. KEGG pathway enrichment analysis of DEGs at 0 d (A), 4 d (B), 8 d (C) and 16 d (D).
Figure 5. KEGG pathway enrichment analysis of DEGs at 0 d (A), 4 d (B), 8 d (C) and 16 d (D).
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Figure 6. Up-regulated DEGs screened from ethylene-related pathways. Different color represents different pathway.
Figure 6. Up-regulated DEGs screened from ethylene-related pathways. Different color represents different pathway.
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Figure 7. Expression analysis of DEGs involved in ethylene-related pathways.
Figure 7. Expression analysis of DEGs involved in ethylene-related pathways.
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Table 1. Statistics of RNA-Seq quality in cauliflower.
Table 1. Statistics of RNA-Seq quality in cauliflower.
Sample_IDClean Reads% > Q30GC ContentMapped ReadsMultiple Mapped ReadsUnique Mapped Reads
D0_CK_14825670896.5246.55%90.45%4.75%85.7%
D0_CK_24766845296.6546.4%90.34%4.33%86.01%
D0_CK_34922707896.6746.67%90.48%4.23%86.25%
D0_T_14390279896.7146.22%90.2%3.81%86.39%
D0_T_25242685696.7546.21%90.27%4.49%85.78%
D0_T_35518812296.6346.17%90.19%4.51%85.68%
D4_CK_15718356496.5646.18%89.8%3.09%86.71%
D4_CK_25012139296.5946.15%89.76%2.95%86.8%
D4_CK_34744896496.6246.09%89.84%3.29%86.55%
D4_T_15179031296.5346.39%90.15%4.36%85.79%
D4_T_25503551096.6146.29%90.0%4.49%85.51%
D4_T_34602986296.4246.26%90.07%4.16%85.92%
D8_CK_15637155896.6846.14%89.67%3.34%86.33%
D8_CK_24688849896.6145.98%89.7%3.1%86.6%
D8_CK_34770811296.5446.24%89.66%3.26%86.39%
D8_T_15200063496.6546.38%90.13%4.17%85.96%
D8_T_24925895296.6346.19%90.11%4.08%86.03%
D8_T_34883976696.746.19%90.24%4.06%86.17%
D16_CK_15558181896.5346.16%89.7%2.99%86.7%
D16_CK_24735787496.6246.11%89.67%3.31%86.36%
D16_CK_35915286696.746.08%89.79%3.46%86.33%
D16_T_15249384096.5446.06%89.88%3.17%86.71%
D16_T_25045852896.546%89.73%3.3%86.42%
D16_T_35491189096.6946.17%89.55%3.23%86.33%
At each time point, there were three biological replicates from every single individual cauliflower floret. Each sample represented a biological replicate individually to form a unique library separately. CK: control; T: ClO2 treatment. D0_CK and D0_T represented samples at 0 day after storage. D4_CK and D4_T represented samples at 4 days after storage, and so on.
Table 2. Ethylene-related DEGs screened out based on GO enrichment analyses.
Table 2. Ethylene-related DEGs screened out based on GO enrichment analyses.
Gene IDGene Description/AnnotationLog2FC (4 d)
BolC5t34953Hprobable NAC; positive regulation of ethylene biosynthetic process−2.24
BolC1t05767Hprobable NAC; positive regulation of ethylene biosynthetic process−1.64
BolC2t06548Hprobable ethylene-responsive transcription factor ERF113−1.44
BolC1t01080Hethylene-responsive transcription factor 1A2.36
BolC6t38599Hethylene-responsive transcription factor ERF0734.29
BolC4t28768Hethylene-responsive transcription factor ERF0716.08
BolC3t17122Hethylene-responsive transcription factor RAP2-31.14
BolC8t48489Hethylene-responsive transcription factor 1A3.00
BolC3t14461Hethylene-responsive transcription factor 11.29
BolC7t43635Hethylene-responsive transcription factor 21.60
BolC9t55823Hethylene-responsive transcription factor 21.23
BolC3t18401Hprobable ethylene-responsive transcription factor1.83
BolC9t53913Hprobable ethylene-responsive transcription factor7.66
BolC1t04038HEthylene receptor (ETR)1.81
BolC2t09157HMitogen-activated protein kinase kinase 9 (MKK9)1.14
BolC3t12569HMPK4; ethylene-dependent systemic resistance3.10
BolC9t54716HReceptor burst oxidase homolog (Rboh)1.87
BolC5t34361Hethylene-activated signaling pathway1.11
BolC9t58400Hethylene-activated signaling pathway5.12
BolC6t39722Hethylene-activated signaling pathway4.63
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Jin, W.; Jiang, Q.; Zhao, H.; Su, F.; Li, Y.; Yang, S. Transcriptome Analysis of Ethylene-Related Genes in Chlorine Dioxide-Treated Fresh-Cut Cauliflower. Genes 2024, 15, 1102. https://doi.org/10.3390/genes15081102

AMA Style

Jin W, Jiang Q, Zhao H, Su F, Li Y, Yang S. Transcriptome Analysis of Ethylene-Related Genes in Chlorine Dioxide-Treated Fresh-Cut Cauliflower. Genes. 2024; 15(8):1102. https://doi.org/10.3390/genes15081102

Chicago/Turabian Style

Jin, Weiwei, Qiaojun Jiang, Haijun Zhao, Fengxian Su, Yan Li, and Shaolan Yang. 2024. "Transcriptome Analysis of Ethylene-Related Genes in Chlorine Dioxide-Treated Fresh-Cut Cauliflower" Genes 15, no. 8: 1102. https://doi.org/10.3390/genes15081102

APA Style

Jin, W., Jiang, Q., Zhao, H., Su, F., Li, Y., & Yang, S. (2024). Transcriptome Analysis of Ethylene-Related Genes in Chlorine Dioxide-Treated Fresh-Cut Cauliflower. Genes, 15(8), 1102. https://doi.org/10.3390/genes15081102

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