Next Article in Journal
Effect of Phosphorylation Sites Mutations on the Subcellular Localization and Activity of AGPase Bt2 Subunit: Implications for Improved Starch Biosynthesis in Maize
Previous Article in Journal
Genome-Wide Identification of R2R3-MYB Transcription Factor Family in Tartary Buckwheat (Fagopyrum tataricum) Identifies a Member Involved in Anthocyanin Biosynthesis
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Agronomy
Volume 13
Issue 8
10.3390/agronomy13082118
agronomy-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Comparative Study of Bolting Adaptability between 60Co-Induced Rape and Its Original Material

by
Wei Yan
1,†,
Tailong Tan
1,2,†,
Hao Chen
1,
Haiyan Sun
3,
Rongkui Hui
4,* and
Zhenqian Zhang
1,*
1
College of Agriculture, Hunan Agricultural University, Changsha 410128, China
2
Yuelushan Laboratory, Changsha 410128, China
3
Hainan Key Laboratory of Tropical Microbe Resources, Institute of Tropical Bioscience and Biotechnology, Chinese Academy of Tropical Agricultural Sciences, Haikou 571101, China
4
Institute of Crop Research, Hunan Academy of Agricultural Sciences, Changsha 410125, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2023, 13(8), 2118; https://doi.org/10.3390/agronomy13082118
Submission received: 30 June 2023 / Revised: 17 July 2023 / Accepted: 7 August 2023 / Published: 13 August 2023
(This article belongs to the Section Plant-Crop Biology and Biochemistry)
Browse Figures
Versions Notes

Abstract

:
In southern China, the fresh shoots of rape are used as a high-quality seasonal vegetable owing to their pleasant taste. In this study, we investigated the taste and quality of fresh shoots of Fanmingyoutai, which was derived from WH23 by 60Co mutation. WH23 was used as a control (CK). Physiological indexes, transcriptome analyses, and metabolomics analyses between Fanmingyoutai and CK were studied and the related key differential genes were identified. The results showed that the glucosinolate content of Fanmingyoutai seeds was 51.14% lower than that of CK, and the contents of soluble sugar and vitamin C in the fresh shoots of Fanmingyoutai were 2.1 times and 1.4 times higher, respectively, than CK. Using transcriptome analyses, we identified that the differential genes were involved in glycan biosynthesis and metabolism, energy metabolism, carbohydrate metabolism, and the metabolism of cofactors and vitamins. Metabolomics analyses demonstrated that the contents of sucrose and D-fructose in the fresh shoots of Fanmingyoutai were 1.22 times and 1.15 times higher, respectively, than those in CK. Using qRT-PCR analyses, the expression of SWEET17, STP5, and GSL in the fresh shoots and leaves of Fanmingyoutai was two times higher than that in CK. SWEET17 (involved in sugar production and transport), STP5 (involved in monosaccharide transport), and GSL (involved in glucosinolate accumulation) may be the key functional genes. We concluded that the low glucosinolate content and high sucrose and D-fructose contents may be the main factors affecting the taste of fresh shoots of Fanmingyoutai and CK; SWEET17, STP5, and GSL may be the key related genes. This research provides a reference for the breeding and molecular mechanisms of new edible rape varieties.

1. Introduction

Rape (Brassica napus L.) is an important oil crop. Its fresh shoots are rich in carotenoids, phenolics, minerals, and vitamins [1]. A lower temperature results in fewer pests and diseases at the bolting stage, making it a safe and healthy vegetable [2]. The fresh shoots have an important effect on improving the planting benefits of rape, driving farmers to increase income, enhancing planting enthusiasm, promoting the development of the rape industry, and meeting new demands of consumers [3].
Research on the taste of rape is poor. Phenolic compounds from the hydrolysis of glucosinolates are important when regarding the quality of plant-based foods because they are involved in flavor features [4]. As the glucosinolate content of rape is lower than that of other Brassicaceae family plants, the flavor of fresh shoots is related to the synthesis of glucosinolates in rape [5]. Indole-3-methanol, indole-3-acetonitrile, and other compounds generated by the hydrolysis of indole glucosinolates can promote the generation of antioxidants in the body [6,7]. Research has shown that glucosinolates can affect flowering Chinese cabbage, demonstrating that it is rich in glucosinolates with health-promoting effects and contains five aliphatic, two indole, and one aromatic glucosinolates, but it is unclear whether they affect the fresh shoots of rape [4,8,9]. Saccharide is the main nutrient in the stem; the type and content of sugar in the stem affect the quality and flavor of the stem. Plants rely on sugar for energy to grow, develop, and reproduce [10,11,12]. Sugar production, transport, and metabolic processes convey information not only relating to metabolic processes such as protein, lipid, and nucleic-acid metabolism, but also secondary biomass metabolism [13,14]. The SWEET (sugars will be eventually effluxed transporter) sugar transporter family can fulfill the bidirectional transmembrane transport of carbohydrate substances [15]. The overexpression of the OsSWEET5 gene in rice leads to significant changes in the soluble sugar content in the plant leaf, indicating that OsSWEET5 plays an important role in galactose transport mediated by plants [16]. STPs (sugar transport proteins) are a class of sugar transporters with functions that have been identified more frequently in monosaccharide transporter family genes. These can transport glucose, pentose, xylose, ribose, galactose, fructose, mannose, etc. [17,18]. Vitamin C is an essential substance in the process of plant metabolism. It has important physiological functions such as photosynthesis and growth metabolism; it is also closely related to the synthesis of sugar metabolites [19]. There is little research on sugar metabolites in the fresh shoots of rape.
Most researchers use various omics methods to locate genes, but the complexity and diversity of plant development regulation limits single-omics research. Thus, multi-omics-combined research is increasingly being applied [20,21]. Multi-omics analyses of transcriptomes, metabolomes, and genomes have identified the major and minor loci and candidate genes for seed-coat color and explored the mechanism of flavonoid metabolite biosynthesis in rape. These findings provided a reference to systematically investigate the mechanism of seed-coat color in rape and other plants [22]. Differentially expressed genes and metabolites in rape seedlings were screened under different light conditions by transcriptomes and metabolomes, laying a foundation for the study of the anthocyanin synthesis mechanism [23]. Most of the studies are based on the transcriptomes and metabolomes involved in the stress resistance of rape as well as yield improvement [24,25]. There is little research on the physiological taste and quality of fresh shoots.
In this study, we used transcriptomic and metabolomic analyses to investigate the differential genes affecting the taste of fresh shoots. The physiological and molecular mechanisms were also studied. This research provides a potential gene resource for the breeding and molecular mechanism of fresh shoots.

2. Materials and Methods

2.1. Test Material

The materials used for transcriptomics and metabolomics were (1) Fanmingyoutai, with a growth period of approximately 192 days (15 days fewer than WH23). Using near-infrared spectroscopy, we determined that the seed oil content was 47.61% and the glucosinolate content was 17.12 µmol/g; and (2) WH23 (CK), an early-maturing variety of rape with excellent comprehensive characteristics. Its growth period was approximately 207 days. The seed oil content was 47.34% and the glucosinolate content was 33.48 µmol/g. The two materials were provided by Hunan Agricultural University (Changsha, China).
The materials used for the physiological indexes and gene expression analyses were Ziting No. 2 (CK2), an early- to mid-maturing hybrid variety of red flowering Chinese cabbage bred by Wuhan City Wending Agricultural Biotechnology (Wuhan, China); Youtai 929 (CK3), a rape variety bred by the Changde City Academy of Agriculture (Changde, China) and Forestry with a seed oil content of 45.04% and a glucosinolate content of 26.65 µmol/g; Fengyou112, Ganyou 105, and 20xy1329 (Jiangxi Academy of Agricultural Sciences, Nanchang, China); Xiziyuan No. 1 and Xiziyuan No. 2 (Oil Crops Research Institute, Chinese Academy of Agricultural Sciences, Beijing, China); Dadi 95, Xiangsui 603, K173, KW, and Nongda No. 1 (Hunan Agricultural University, Changsha, China); Y1, Y2, Y3, Y4, Y5, Y6, and Y7 (these seven materials were descendants of Fanmingyoutai with different bolting times); and Huayouza 652, Shishancaitai, Shishan 2017, and Shishan 2019 (Huazhong Agricultural University, Wuhan, China).

2.2. Experimental Methods

2.2.1. Field Layout

The materials were planted in a cultivation base at Hunan Agricultural University (113°09′ E, 28°19′ N). Each plot was 6 m2 in area. The sowing density was 10 plants/row, 5 rows in total; each had 3 replicates.

2.2.2. Sample Collection

WH23 and Fanmingyoutai were selected for transcriptome and metabolism analyses at the bolting stage of the rape. The other remaining samples were retained for the physiological experiment and stored at −80 °C [26].

2.2.3. Physiological Index Analysis

The leaves and fresh shoots of the rape at the bolting stage were measured using a U 8000 spectrophotometer (METASH, Shanghai, China) for vitamin C [27], soluble protein [28], soluble sugar [29], chlorophyll [30], and other physiological indicators. All experiments included three biological replicates; each contained five plants.

2.2.4. Transcriptome Sequencing

The fresh shoots of WH23 and Fanmingyoutai were sequenced using Illumina NovaSeq6000 (Nanjing Parthenogenein Technology Co., Ltd., Nanjing, China). We uploaded the data, ensuring that the deposited data were made public (NCBI; https://www.ncbi.nlm.nih.gov/sra/PRJNA953841 (accessed on 4 April 2023), accession number: PRJNA953841). The differential gene expression was analyzed using DESeq software (version 1.40.2). The conditions used to screen the differentially expressed genes were an expression difference of |log2 fold change| > 1 and a significant p-value of <0.05 [31].

2.2.5. Metabolomics Analysis

The metabolomics analysis was performed by Nanjing Pesennuo Gene Technology Ltd. (Nanjing, China). Metabolites with fold changes of ≥2 and ≤0.5 were selected. The metabolites were mapped to KEGG metabolic pathways for annotation and an enrichment analysis. A pathway with FDR ≤ 0.05 was defined as a pathway that was significantly enriched with differential metabolites [32].

2.2.6. Association Analysis between Transcriptomics and Metabolomics

A pathway-based comprehensive analysis was conducted. KEGG metabolic pathways with significantly enriched genes and metabolites were screened and the association characteristics between the genes and metabolites in the common pathways were analyzed.

2.2.7. Study of the Content of Physiological Indexes and Key Differential Gene Expressions

A correlation analysis of the content of the physiological indexes and gene expressions was conducted. Total RNA was extracted using a TransZol Up Plus RNA Kit (Beijing Chuangcheng Biotechnology Co., Beijing, China). RNA quality and integrity were tested using a 2100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA) and agarose gel electrophoresis. cDNA was synthesized by reverse transcription using a Transcript One-Step RT-PCR Supermix Kit. PCR primers were designed by NCBI and synthesized by Hunan Qingke Biotechnology Company (Changsha, China). A CFX96TM Real-Time System (BIO-RAD, Hercules, CA, USA) was used to analyze the expression of the differential genes. The relative expression of the genes was calculated using the 2−ΔΔCt method [33].

2.2.8. Data Analysis

The data were sorted using Microsoft Excel 2010 software and analyzed using SPSS 22.0 software. Plot and gene expression heat maps were generated based on gene expression levels or log2 values using TBtools software (version 1.108; Chen Chengjie, Guangzhou, China).

3. Results

3.1. Analysis of Agronomic Characteristics

At harvest time (May 2022), the average plant height of Fanmingyoutai was 193.6 cm and the total number of pods was 528. The total number of pods of WH23 was 267 and the average plant height was 184.4 cm. The total number of pods of Youtai 929 was 372 and the average plant height was 186.4 cm. The total number of pods of Fanmingyoutai was 1.97 times greater than that of WH23 and 1.4 times greater than that of Youtai 929. The comprehensive characteristics of Fanmingyoutai were superior.
In January 2023, the average plant height of Fanmingyoutai was 45.9 cm and the total leaf number of the main stem was 9.4. The average plant height of Shishancaitai was 41.2 cm and the total leaf number of the main stem was 5.8. The average plant height of WH23 was 33 cm and the total leaf number of the main stem was 7.3. The bolting time of Fanmingyoutai was later than that of Shishancaitai and earlier than that of WH23. The characteristics of Fanmingyoutai were stable.

3.2. Physiological Index Analysis

3.2.1. Physiological Indicator Analysis of Fresh Shoots

In the bolting stage of the rape, the fresh shoots and leaves of different rape cultivars were selected for the determination of the physiological indexes. All experiments included three biological replicates, each containing five plants. The results of the physiological analysis of fresh shoots (Table 1) demonstrated that the contents of soluble sugar and soluble protein were higher in Fanmingyoutai and its different classifications (Y2 and Y6) than in WH23 (CK1). Fanmingyoutai had a soluble sugar content 1.2 times higher, and vitamin C content 2 times higher, than that of Ziting No. 2 (CK2). In comparison with other common rape varieties (Xiangsui 603, KW, and K173), most of the rape vegetable varieties (Ziting No. 2, Youtai 929, Shishancaitai, and Xiziyuan No. 1) had higher contents of soluble sugars, soluble protein, and vitamin C. The contents of soluble sugar, soluble protein, and vitamin C in the fresh shoots of Fanmingyoutai were not lower than that of the rape vegetable varieties. These results suggested that the taste and nutritional value of Fanmingyoutai were superior to existing rape vegetable varieties; therefore, it could be used as an excellent substitute for red flowering Chinese cabbage or flowering Chinese cabbage.

3.2.2. Analysis of Physiological Indexes of Leaves

We also analyzed the physiological indexes of leaves (Table 2). In the leaves of Fanmingyoutai and its different classifications (Y1, Y2, Y5, Y6, and Y7), the contents of soluble sugar and soluble protein were also high. In comparison with other common rape varieties (Xiangsui 603, KW, K173, etc.) and the rape vegetable varieties (Ziting No. 2, Youtai 929, Shishancaitai, and Xiziyuan No. 1), the content of soluble sugar in the leaves of Fanmingyoutai was the highest. These findings suggested that the leaves of Fanmingyoutai also had a superior taste. Overall, these results provided a valuable contrast in taste between Fanmingyoutai and other rape vegetables. The fresh shoots and leaves of Fanmingyoutai had a superior taste and nutritional value; thus, they could be used as a rape vegetable.

3.3. Omics Analysis

3.3.1. Transcriptomic Analysis

The fresh shoots of WH23 (CK) and Fanmingyoutai at the bolting stage were sequenced. The sequencing data were further filtered. The CK Q20 (percentage of bases with over 99% accuracy) accounted for 97.54% and Q30 (percentage of bases with over 99.9% accuracy) accounted for 93.54%. Fanmingyoutai Q20 (%) accounted for 97.53% and Q30 (%) accounted for 93.54%, indicating that the sequencing results were accurate and reliable. The differential analysis of the gene expression was performed using DESeq. The conditions used to screen the differentially expressed genes were |log2 fold change| > 1 and p < 0.05. There were 3192 differentially expressed genes, including 1726 upregulated genes and 1466 downregulated genes.

KEGG Enrichment Analysis

According to the KEGG enrichment analysis of the DEGs, 118 metabolic pathways showed differences. Among these, 43 showed a p-value below a specific threshold and a false discovery rate of <0.3. These pathways were mainly divided into biosynthesis of other secondary metabolites (9), amino acid metabolism (7), lipid metabolism (4), metabolism of terpenoids and polyketides (4), glycan biosynthesis and metabolism (4), energy metabolism (3), carbohydrate metabolism (3), metabolism of cofactors and vitamins (3), metabolism of other amino acids (2), signal transduction (1), environmental adaptation (1), and membrane transport (1). Figure 1 presents a few of the pathways with the lowest p-values and false discovery rates of <0.3. Glycan biosynthesis and metabolism, energy metabolism, carbohydrate metabolism, and metabolism of cofactors and vitamins were closely related to plant sugar storage, accumulation, and transport, indicating that sugar metabolism mainly affected the fresh shoot taste of Fanmingyoutai.

3.3.2. Metabolomic Analysis

A carbohydrate is a kind of compound of polyhydroxy aldehyde or ketone, and it can generate polyhydroxy aldehydes or ketones after hydrolysis. A carbohydrate is composed of three elements: carbon, hydrogen, and oxygen [34]. More than 50% of the dry weight of the biomass on Earth is composed of sugar polymers. Sugar is not only the basic component and an important nutrient of life, but it also participates in the life activities of many organisms, and it plays an important role in cell recognition, immune protection, metabolic regulation, the fertilization mechanism, morphogenesis, development, cancerization, aging, and other aspects. Carbohydrate analysis is the premise and an important means of studying its transformation and physiological functions in life [13,14]. In this study, the sweet tastes of Fanmingyoutai and WH23 were significantly different.

Sugar Content

A total of 13 kinds of sugars were quantitatively detected in Fanmingyoutai and WH23. It can be seen from Table 3 that the contents of sucrose, D-fructose, glucose, and inositol in the Fanmingyoutai were higher than the WH23, and that the contents of trehalose, L-fucose, L-rhamnose, D-sorbitol, and xylitol had no significant differences.

Screening and KEGG Classification of Differential Metabolites

The annotation results of the significantly different metabolites from the KEGG were classified according to the pathway types in the KEGG. The classification diagram is shown in Figure 2. The differential metabolites involved in the metabolic and environmental information-processing categories mainly focused on metabolism. The main pathways of the differential metabolites were starch and sucrose metabolism, metabolic pathways, galactose metabolism, biosynthesis of secondary metabolites, and ABC transporters. Six metabolites were enriched in the KEGG pathway.

3.3.3. Association Analysis between Transcriptomics and Metabolomics

An association analysis between transcriptomics and metabolomics demonstrated that there were common pathways. These were starch and sucrose metabolism (11 upregulated genes and 16 downregulated genes), galactose metabolism (4 upregulated genes and 2 downregulated genes), and ABC transporters (1 upregulated gene and 7 downregulated genes). Table 4 lists the key differential genes in the common pathways combined with the functional annotation provided by the NCBI.

3.4. Gene Expression and Correlation Analysis

3.4.1. qRT-PCR Analysis of Key Genes

L-gulono-1,4-lactone oxidase (GLOase) is the last step of vitamin C synthesis in animals [35]. In plants, the SWEET family is involved in a variety of developmental processes, among which is sugar transport (for example, phloem loading for long-distance sugar transport, pollen nutrition, nectar secretion, embryonic development, and the maintenance of sugar homeostasis) [36,37]. STPs play a role in the transport, absorption, utilization, and accumulation of monosaccharides and affect the growth and development of plants. A study on the monosaccharide transporter in sugarcane showed that it may be responsible for the absorption of monosaccharides in apoplasts and play an important role in sugar transport in sugarcane leaves [38]. Glucosinolates are divided into three major groups: aliphatic glucosinolates (group I), aromatic glucosinolates (group II), and indolyl glucosinolates (group III) [39,40]. The hydrolysis products of indole glucosinolates in rape have a certain positive value for rape itself and the human body [41].
GLOX (BnaAnng09070D), SWEET17 (BnaC07g33320D), STP5 (BnaC08g06850D), and GSL (BnaC06g21620D) were selected to study their expressions in different rape cultivars at the bolting stage. The qRT-PCR results showed that the sequencing results of the transcriptome were accurate and reliable. Figure 3a demonstrates that the expression of SWEET17 in the fresh shoots was significantly expressed in 12 varieties. The expression level in 13 was 2.2 times greater than that of WH23. The expression of STP5 in 22 was 2.23 times greater than that of WH23, which was consistent with the higher content of soluble sugar in the 24 rape samples. The GSL expression in 15 was 4.3 times greater than that of WH23. Thus, SWEET17, STP5, and GSL may be related key genes.

3.4.2. Correlation Analysis between the Content of the Physiological Indexes and Gene Expression

A correlation analysis was performed between the differential gene expression results and the content of the physiological indicators. Table 5 demonstrates that the expression of the SWEET17 and GSL genes in the fresh shoots was positively correlated with the content of soluble protein (p < 0.05). The expression of the GLOX, SWEET17, STP, and GSL genes was negatively correlated with the content of vitamin C (p < 0.05). In the leaves, the expression of the GLOX gene was negatively correlated with the content of soluble sugar (p < 0.01), the expression of the SWEET17 and STP genes was negatively correlated with the content of soluble protein (p < 0.05), and the expression of the GSL gene was positively correlated with the content of total chlorophyll (p < 0.05).

3.4.3. Field Analysis of Key Genes

To verify the function of the SWEET17 and STP5 genes, NAA—as the downstream metabolite of these genes—was sprayed onto Nongda No.1 at the 4–5 leaf stage [42]. The results demonstrated that one month after a treatment with 80 mg/L NAA, the height of the control was 48 cm (Figure 4a) and that of the NAA treatment was 65 cm (Figure 4b); the bolting period was 10 days earlier than the control. The soluble sugar content and soluble protein content of the fresh shoots (Figure 4c) were 57.84% and 60.15% higher than the control, respectively. The content of soluble protein in the leaves (Figure 4d) was 45.48% higher than the control. In the correlation analysis between the content of physiological indexes and gene expression, the expression of the SWEET17 and GSL genes was positively correlated with the content of soluble protein in the fresh shoots (r = 0.250 and 0.432, respectively). The expression of the STP genes was negatively correlated with the content of soluble protein in the leaves (r = −0.272). This revealed that NAA could also have an effect on the expression of the SWEET17, STP, and GSL genes.

4. Discussion

4.1. Effects of the Content of Physiological Indexes on Fresh Shoot Taste

Flavor is an essential characteristic of food products and has a strong influence on consumer preferences. Glucosinolates are widely found in Brassica plants, especially cruciferous plants, and are known to benefit human health. In flowering Chinese cabbage powder (FCCP), four major GSLs—namely, 2®-hydroxy-3-butenyl glucosinolate, (2S)-2-hydroxy-4pentenyl glucosinolate, 5-(methylthio)pentyl glucosinolate, and 2-phenylethyl glucosinolate—were identified as the key precursors forming odor-active compounds [43]. The glucosinolates of broccoli are regarded as key secondary metabolites as well as the source of isothiocyanate. They contain nitrogen-containing groups, providing broccoli with its pungent odor and bitter taste [44]. In this study, the glucosinolate content of Fanmingyoutai was significantly lower than that of WH23. WH23 was slightly bitter; this may have been one of the reasons for the difference in taste.
Soluble sugar is an important component of carbohydrates. The major components of seed sugar in soybean, sucrose, stachyose, and raffinose comprise 41.3–67.4%, 12.1–35.2%, and 5.2–15.8% of the total soluble sugar, respectively. The proportion of sugar components in soybean seeds considerably affects the quality, digestibility, and nutritional values of soy food [45]. The level and proportion of the nutrient content play a decisive role in vegetable flavor and physiological processes. Sucrose is the main product of photosynthesis and is widely distributed in plants; it is the main form in which plants store, accumulate, and transport sugars. D-fructose is the sweetest of all sugars. It can be used as a signal molecule to regulate plant growth and gene expression [46]. Soluble sugars such as sucrose and fructose are important nutrients in flowering Chinese cabbage, with glucose and fructose playing an important role in its sweetness and flavor [15]. In this study, the contents of sucrose and D-fructose in Fanmingyoutai were higher than WH23; this may have been the reason for the sweet taste of Fanmingyoutai and its superior flavor. Vitamin C is a small molecular compound that is indispensable for the maintenance of normal activities of the body. It participates in various functions such as the redox reaction, collagen synthesis, and detoxification in the body [19]. The vitamin C content of the fresh shoots was significantly higher than that of red flowering stalks and purple flowering stalks [47].

4.2. Key Genes Affecting the Taste of Fresh Shoots

Glucosinolate is abundant in rape. Glucosinolates are synthesized in vegetative organs and transported to seeds through leaves and fresh shoots [5]. Compounds such as indole-3-methyl alcohol and indole-3-acetonitrile, which are formed by the hydrolysis of indole glucosinolates, can promote the generation of antioxidants in the body [6]. In pak choi (Brassica rapa subsp. chinensis), aliphatic GLSs were observed to be the most abundant; the highest levels were of 3-butenyl, 4-pentenyl, and indol-3-ylmethyl [48]. In this study, the glucosinolate content of Fanmingyoutai was 51.14% lower than that of WH23. GSL was highly expressed in the leaves and fresh shoots, indicating that it may affect the taste of Fanmingyoutai.
Sucrose and glucose are the main nutrients in the stem. Their unloading and accumulation in the stem play an important role in the distribution of homologs. The type and content of sugar in the stem affect the quality and flavor of the stem [49]. The sugar synthesized in the source tissues must be transported and distributed to the sink tissues to maintain normal plant growth and development. The transportation and distribution of sucrose, glucose, and fructose require the participation of sugar transporters. MtSWEET11 is a nodule-specific sucrose transporter in Medicago truncatula, participating in the distribution of sucrose in nodules [50]. A few studies on the genome-wide identification and functional characterization of plant SWEET gene families are available, viz., Arabidopsis and Chinese cabbage [51,52]. There is little research on the fresh shoots of rape. SWEET17 was highly expressed in both the leaves and fresh shoots, which may affect sugar production and transport in rape. STPs are a class of sugar transporters in the monosaccharide transporter family genes; these possess greater functional identification and broad-spectrum substrate sugar absorption characteristics. For example, MeSTPs in cassava are mainly expressed in tuberous storage roots, indicating that STPs play an important role in the vegetative growth and sugar accumulation of the tuberous roots of cassava [53]. STP5 was expressed in the fresh shoots and leaves, indicating that it affected monosaccharide transport in the leaves and fresh shoots. It may also have affected the formation of D-fructose in the fresh shoots of Fanmingyoutai. Strengthening the research on the quality characteristics of fresh shoots can widen the utilization value of rape and improve its planting benefit. Genetic engineering technology can be used to cultivate safe, flavorful, and healthy varieties of fresh shoots.

Author Contributions

Z.Z. designed the experiments. T.T. Provided experimental materials. W.Y. conducted the experiments. H.C. and H.S. assisted with experiments in data collection and analysis. R.H. drafted the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research was funded by the Science and Technology Innovation 2030–Major Projects: High-throughput genotype identification, analysis and detection support system construction project (Crop Genotype Identification System Development and Application, Grant 2022ZD0401703), and the Major Research and Development Plans of Hunan Province: Research on Key Technologies of “Double Height” in Rice rapeseed oil rotation (Grant 2021NK2004). The Protection and Utilisation of Agricultural Germplasm Resources in Hunan Province (Grant Xiangcai Nongzhi [2022] No. 23).

Data Availability Statement

The transcriptome data were uploaded to the NCBI database (https://www.ncbi.nlm.nih.gov/sra/PRJNA953841, accession number: PRJNA953841). The datasets supporting the conclusions of this article are included within the article and its additional files.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Yue, L.Q.; Kang, Y.Y.; Zhong, M.; Kang, D.J.; Zhao, P.Y.; Chai, X.R.; Yang, X. Melatonin delays postharvest senescence through suppressing the inhibition of BrERF2/BrERF109 on flavonoid biosynthesis in flowering Chinese cabbage. Int. J. Mol. Sci. 2023, 24, 2933. [Google Scholar] [CrossRef]
  2. Ramirez, D.; Abell’an-Victorio, A.; Beretta, V.; Camargo, A.; Moreno, D.A. Functional ingredients from Brassicaceae species: Overview and perspectives. Int. J. Mol. Sci. 2020, 21, 1998. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  3. Zhang, Z.; Yin, Y.; Li, F.; Wang, J.J.; Fu, T.D. Current situation and development countermeasures of Chinese rapeseed multifunctional development and utilization. Chin. J. Oil Crop Sci. 2018, 40, 618–623. [Google Scholar]
  4. Yue, L.Q.; Kang, Y.Y.; Li, Y.S.; Kang, D.J.; Zhong, M.; Chai, X.R.; Guo, J.X.; Yang, X. 1-Methylcyclopropene promotes glucosinolate biosynthesis through BrWRKY12 mediated jasmonic acid biosynthesis in postharvest flowering Chinese cabbage. Postharvest Biol. Technol. 2023, 203, 112415. [Google Scholar] [CrossRef]
  5. Fahey, J.W.; Zalcmann, A.T.; Talalay, P. The chemical diversity and distribution of glucosinolates and isothiocyanates among plants. Phytochemistry 2001, 56, 5–51. [Google Scholar] [CrossRef]
  6. Mithen, R.F.; Dekker, M.; Verkerk, R.; Rabot, S.; Johnson, I.T. The physiological significance, biosynthesis and bioavailability of glucosinolates in human foods. J. Sci. Food Agric. 2000, 80, 967–984. [Google Scholar] [CrossRef]
  7. Murillo, G.; Mehta, R.G. Cruciferous vegetables and cancer prevention. Nutr. Cancer 2001, 41, 17–28. [Google Scholar] [CrossRef]
  8. Tian, Y.; Deng, F.M.; Qing, Z.X.; Zhao, L.Y.; Peng, P. Advances in understanding the structure and function of glucosinolates in Brassicaceae. Shipin Kexue/Food Sci. 2020, 41, 292–303. [Google Scholar]
  9. Agerbirk, N.; Hansen, C.C.; Kiefer, C.; Hauser, T.P.; Ørgaard, M.; Lange, C.B.A.; Cipollini, D.; Koch, M.A. Comparison of glucosinolate diversity in the crucifer tribe Cardamineae and the remaining order Brassicales highlights repetitive evolutionary loss and gain of biosynthetic steps. Phytochemistry 2021, 185, 112668. [Google Scholar] [CrossRef]
  10. Wang, M.; Zang, L.; Jiao, F.; Perez-Garcia, M.D.; Ogé, L.; Hamama, L.; Le Gourrierec, J.; Sakr, S.; Chen, J. Sugar signaling and post-transcriptional regulation in plants: An overlooked or an emerging topic? Front. Plant Sci. 2020, 11, 578096. [Google Scholar]
  11. Bermejo, C.; Haerizadeh, F.; Takanaga, H.; Chermak, D.; Frommer, W.B. Optical sensors for measuring dynamic changes of cytosolic metabolite levels in yeast. Nat. Protoc. 2011, 6, 1806–1817. [Google Scholar] [CrossRef] [PubMed]
  12. Smeekens, S. Sugar-induced signal transduction in plants. Annu. Rev. Plant Biol. 2000, 51, 49–81. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  13. Gazzarrini, S.; Mccourt, P. Genetic interactions between ABA, ethylene and sugar signaling pathways. Curr. Opin. Plant Biol. 2001, 4, 387–391. [Google Scholar] [CrossRef] [PubMed]
  14. Finkelstein, R.R.; Gibson, S.I. ABA and sugar interactions regulating development: Cross-talk or voices in a crowd? Curr. Opin. Plant Biol. 2002, 5, 26–32. [Google Scholar] [CrossRef]
  15. Chen, L.Q.; Cheung, L.S.; Feng, L.; Tanner, W.; Frommer, W.B. Transport of sugars. Annu. Rev. Biochem. 2015, 84, 865–894. [Google Scholar] [CrossRef]
  16. Zhou, Y.; Liu, L.; Huang, W.; Yuan, M.; Zhou, F.; Li, X.; Lin, Y. Overexpression of OsSWEET5 in rice causes growth retardation and precocious senescence. PLoS ONE 2014, 9, e94210. [Google Scholar] [CrossRef] [Green Version]
  17. Yan, N. Structural advances for the major facilitator superfamily (MFS) transporters. Trends Biochem. Sci. 2013, 38, 151–159. [Google Scholar] [CrossRef]
  18. Julius, B.T.; Leach, K.A.; Tran, T.M.; Mertz, R.A.; Braun, D.M. Sugar transporters in plants: New insights and discoveries. Plant Cell Physiol. 2017, 58, 1442–1460. [Google Scholar] [CrossRef] [Green Version]
  19. Wheeler, G.; Ishikawa, T.; Pornsaksit, V.; Smirnoff, N. Evolution of alternative biosynthetic pathways for vitamin C following plastid acquisition in photosynthetic eukaryotes. eLife 2015, 4, e06369. [Google Scholar] [CrossRef] [Green Version]
  20. Hong, J.; Yang, L.; Zhang, D.; Zhang, D.B.; Shi, J.X. Plant metabolomics: An indispensable system biology tool for plant science. Int. J. Mol. Sci. 2016, 17, 767. [Google Scholar] [CrossRef]
  21. Shu, P.; Zhang, Z.X.; Wu, Y.; Chen, Y.; Li, K.Y.; Deng, H.; Zhang, J.; Zhang, X.; Wang, J.Y.; Liu, Z.B.; et al. A comprehensive metabolic map reveals major quality regulations in red flesh kiwifruit (Actinidia chinensis). New Phytol. 2023, 238, 2064–2079. [Google Scholar] [CrossRef]
  22. Zhao, H.Y.; Shang, G.X.; Yin, N.W.; Chen, S.; Shen, S.L.; Jiang, H.Y.; Tang, Y.S.; Sun, F.J.; Zhao, Y.H.; Niu, Y.C.; et al. Multi-omics analysis reveals the mechanism of seed coat color formation in Brassica rapa L. Theor. Appl. Genet. 2022, 135, 2083–2099. [Google Scholar] [CrossRef]
  23. Teng, S.L.; Li, F.; Qi, L.J.; Guo, T.T.; Zhang, S.P.; Tuo, X.Y.; Luo, Y.X. Analysis of transcriptome and Metabolome of light-induced anthocyanin synthesis in Brassica napus L. seedling. Nat. Sci. Ed. 2021, 49, 134–146. [Google Scholar]
  24. Zhang, T.Y.; Wang, Y.; Liu, Y.; Zhou, T.; Yue, C.P.; Huang, J.Y.; Hua, Y.P. Bioinformatics analysis and core members identification of proline metabolism gene family in Brassica napus L. Acta Crops Sin. 2022, 48, 1977–1995. [Google Scholar]
  25. Tan, M.; Niu, J.; Peng, D.Z.; Cheng, Q.; Luan, M.B.; Zhang, Z.Q. Clone and function Verification of the OPR gene in Brassica napus related to Linoleic Acid Synthesis. BMC Plant Biol. 2022, 22, 192. [Google Scholar] [CrossRef] [PubMed]
  26. Gan, Q.Q.; Luan, M.B.; Hu, M.L.; Liu, Z.S.; Zhang, Z.Q. Functional study of CYP90A1 and ALDH3F1 gene obtained by transcriptome sequencing analysis of Brassica napus seedlings treated with brassinolide. Front. Plant Sci. 2022, 13, 1040511. [Google Scholar]
  27. Wang, C.; Kuang, L.Q.; Pan, Y.Y.; Dun, X.L.; Wang, X.F. An efficient and accurate method for the determination of vitamin C in rapeseed. Chin. J. Oil Crop Sci. 2021, 43, 346–352. [Google Scholar]
  28. Bradford, M.M. A rapid and sensitive method for the quantitation of microgram quantities ofprotein utilizing the principle of protein-dye binding anal. Anal. Biochem. 1976, 72, 248–254. [Google Scholar] [CrossRef]
  29. Dubois, M.; Gilles, K.; Hamilton, J.K.; Rebers, P.A.; Smith, F. A colorimetric method for the determination of sugars. Nature 1951, 168, 167. [Google Scholar] [CrossRef]
  30. Anis, A.S.; Shakil, A.; Muhammad, A.; Nasim, A.Y. Seed priming with 3-epibrassinolide alleviates cadmium stress in cucumis sativus through modulation of antioxidative system and gene expression. Sci. Hortic. 2020, 265, 109203. [Google Scholar]
  31. Kanehisa, M.; Goto, S.; Kawashima, S.; Okuno, Y.; Hattori, M. The KEGG resource for deciphering the genome. Nucleic Acids Res. 2004, 32, D277–D280. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  32. Sun, S.H.; Wang, H.; Xie, J.P.; Su, Y. Simultaneous determination of rhamnose, xylitol, arabitol, fructose, glucose, inositol, sucrose, maltose in jujube (Zizyphus jujube Mill.) extract: Comparison of HPLC-ELSD, LC-ESI-MS/MS and GC-MS. Chem. Cent. J. 2016, 10, 25. [Google Scholar] [PubMed] [Green Version]
  33. Livak, K.J.; Schmittgen, T.D. Analysis of relative gene expression data using real-time quantitative PCR and the 2−ΔΔCT method. Methods 2001, 25, 402–408. [Google Scholar] [CrossRef] [PubMed]
  34. Ma, Y.C.; Zhao, Y.L.; Li, J.W.; Liu, B.; Wang, C.M.; Zhang, M.; Zhang, L.P.; Jiang, X.X.; Mu, G.J. Transcriptome-metabonomicsjoint combined analysis of kernel sugar metabolism in peanut (Arachis hypogaea L.). J. Plant Genet. Resour. 2022, 23, 1143–1154. [Google Scholar]
  35. Ashok, K.J.; Craig, L.N. Metabolic engineering of an alternative pathway for ascorbic acid biosynthesis in plants. Mol. Breed. 2000, 6, 73–78. [Google Scholar]
  36. Chen, L.Q.; Qu, X.Q.; Hou, B.H.; Davide, S.; Sonia, O.; Alisdair, R.F.; Wolf, B.F. Sucrose efflux mediated by SWEET proteins as a key step for phloem transport. Science 2012, 335, 207–211. [Google Scholar] [CrossRef]
  37. Bin, H.; Hao, W.; Wei, F.H.; Jian, B.S.; Yong, Z.; Yong, J.L. SWEET gene family in medicago truncatula: Genome-wide identification, expression and substrate specificity analysis. Plants 2019, 8, 338. [Google Scholar]
  38. Zhao, T.T.; Wang, J.G.; Wang, W.Z.; Feng, C.L.; Feng, X.Y.; Zhang, S.Z. Sequence analysis and tissue expression analysis of monosaccharide transporter gene ShSTP7 in sugarcane. Biotechnol. Bull. 2022, 38, 72–78. [Google Scholar]
  39. Grubb, C.D.; Abel, S. Glucosinolate metabolism and its control. Trends Plant Sci. 2006, 11, 89–100. [Google Scholar] [CrossRef]
  40. Barbara, A.H.; Jonathan, G. Biology and biochemistry of glucosinolates. Annu. Rev. Plant Biol. 2006, 57, 303–333. [Google Scholar]
  41. Albena, D.K.; Rumen, V.K. Glucosinolates and isothiocyanates in health and disease. Trends Mol. Med. 2012, 18, 337–347. [Google Scholar]
  42. Maryam, R.; Hossein, A.; Masoud, T.; Hassan, R. Economic micropropagation of Stevia rebaudiana Bertoni and evaluation of in vitro cultures in order to improve steviol glycosides. Sci. Hortic. 2022, 30, 111372. [Google Scholar]
  43. Zheng, C.; Yang, Y.; Wei, F.; Lv, X.; Xia, Z.R.; Qi, M.; Zhou, Q. Widely targeted metabolomics reveal the glucosinolate profile and odor-active compounds in flowering Chinese cabbage powder. Food Res. Int. 2023, 172, 113121. [Google Scholar] [CrossRef]
  44. Mao, X.; Zhao, X.; Huyan, Z.; Liu, T.; Yu, X. Relationship of Glucosinolate Thermal Degradation and Roasted Rapeseed Oil Volatile Odor. J. Agric. Food Chem. 2019, 67, 11187–11197. [Google Scholar] [CrossRef] [PubMed]
  45. Wilson, R.F. Seed composition. Soybeans Improv. Prod. Uses 2004, 16, 621–667. [Google Scholar]
  46. Jahangir, M.; Kim, H.K.; Choi, Y.H.; Verpoorte, R. Health-Affecting Compounds in Brassicaceae. Compr. Rev. Food Sci. Food Saf. 2010, 8, 31–43. [Google Scholar] [CrossRef]
  47. Theocharis, A.; Clément, C.; Barka, E.A. Physiological and molecular changes in plants grown at low temperatures. Planta 2012, 235, 1091–1105. [Google Scholar] [CrossRef]
  48. Chen, X.; Hanschen, F.S.; Neugart, S.; Schreiner, M.; Vargas, S.A.; Gutschmann, B.; Baldermann, S. Boiling and steaming induced changes in secondary metabolites in three different cultivars of pakchoi (Brassica rapa subsp. chinensis). J. Food Compos. Anal. 2019, 82, 103232. [Google Scholar] [CrossRef]
  49. Nagele, T.; Henkel, S.; Hormiller, I.; Sauter, T.; Sawodny, O.; Ederer, M.; Heyer, A.G. Mathematical modeling of the central carbohydrate metabolism in Arabidopsis reveals a substantial regulatory influence of vacuolar invertase on whole plant carbon metabolism. Plant Physiol. 2010, 153, 260–272. [Google Scholar] [CrossRef] [Green Version]
  50. Kryvoruchko, I.S.; Sinharoy, S.; Torres-Jerez, I.; Sosso, D.; Pislariu, C.I.; Guan, D.; Murray, J.; Benedito, V.A.; Frommer, W.B.; Udvardi, M.K. MtSWEET11, a nodule-specifc sucrose transporter of Medicago truncatula. Plant Physiol. 2016, 171, 554–565. [Google Scholar] [CrossRef] [Green Version]
  51. Wang, L.; Yao, L.; Hao, X.; Li, N.; Qian, W.; Yue, C.; Ding, C.; Zeng, J.; Yang, Y.; Wang, X. Tea plant SWEET transporters: Expression profifiling, sugar transport, and the involvement of CsSWEET16 in modifying cold tolerance in Arabidopsis. Plant Mol. Biol. 2018, 96, 577–592. [Google Scholar] [CrossRef] [PubMed]
  52. Ji, J.L.; Yang, L.M.; Fang, Z.Y.; Zhang, Y.Y.; Zhuang, M.; Lv, H.H.; Wang, Y. Plant SWEET family of sugar transporters: Structure, evolution and biological functions. Biomolecules 2022, 12, 205. [Google Scholar] [PubMed]
  53. Liu, Q.; Dang, H.J.; Chen, Z.J.; Wu, J.Z.; Chen, Y.h.; Chen, S.b.; Luo, L.J. Genome-wide identification, expression, and functional analysis of the sugar transporter gene family in cassava (Manihot esculenta). Int. J. Mol. Sci. 2018, 19, 987. [Google Scholar] [CrossRef] [PubMed] [Green Version]
Agronomy 13 02118 g001
Figure 1. KEGG enrichment map of differential candidate genes in fresh shoots of Fanmingyoutai and WH23.
Figure 1. KEGG enrichment map of differential candidate genes in fresh shoots of Fanmingyoutai and WH23.
Agronomy 13 02118 g001
Agronomy 13 02118 g002
Figure 2. KEGG classification diagram of differential metabolites in fresh shoots of Fanmingyoutai and WH23. The ordinate is the name of the KEGG metabolic pathway. The abscissa is the number of metabolites annotated to this pathway and the proportion of the number to the total number of metabolites annotated.
Figure 2. KEGG classification diagram of differential metabolites in fresh shoots of Fanmingyoutai and WH23. The ordinate is the name of the KEGG metabolic pathway. The abscissa is the number of metabolites annotated to this pathway and the proportion of the number to the total number of metabolites annotated.
Agronomy 13 02118 g002
Agronomy 13 02118 g003
Figure 3. Expression patterns of significantly expressed key genes related to taste in different rape cultivars: (a) expression of fresh shoots in different rape cultivars; (b) expression of leaves in different rape cultivars. 1: Huayouza 652, 2: Fengyou112, 3: Ganyou 105, 4: 20xy1329, 5: K173, 6: KW, 7: Youtai 929, 8: Xiziyuan No. 1, 9: Xiziyuan No. 2, 10: Xiangsui 603, 11: Dadi 95, 12: Nongda No. 1, 13: Y1, 14: Y2, 15: Y3, 16: Fanmingyoutai, 17: Y4, 18: Y5, 19: Y6, 20: Y7, 21: WH23, 22: Shishancaitai, 23: Shishan 2017, 24: Shishan 2019.
Figure 3. Expression patterns of significantly expressed key genes related to taste in different rape cultivars: (a) expression of fresh shoots in different rape cultivars; (b) expression of leaves in different rape cultivars. 1: Huayouza 652, 2: Fengyou112, 3: Ganyou 105, 4: 20xy1329, 5: K173, 6: KW, 7: Youtai 929, 8: Xiziyuan No. 1, 9: Xiziyuan No. 2, 10: Xiangsui 603, 11: Dadi 95, 12: Nongda No. 1, 13: Y1, 14: Y2, 15: Y3, 16: Fanmingyoutai, 17: Y4, 18: Y5, 19: Y6, 20: Y7, 21: WH23, 22: Shishancaitai, 23: Shishan 2017, 24: Shishan 2019.
Agronomy 13 02118 g003
Agronomy 13 02118 g004
Figure 4. Field phenotype map and physiological index histogram: (a) Control. (b) NAA treatment. (c) Histogram of the content of the physiological indexes of fresh shoots. (d) Histogram of the content of the physiological indexes of leaves. All experimental data are expressed as the mean value of three biological replicates. Different letters (a and b) indicate statistically significant differences at the level of p < 0.05.
Figure 4. Field phenotype map and physiological index histogram: (a) Control. (b) NAA treatment. (c) Histogram of the content of the physiological indexes of fresh shoots. (d) Histogram of the content of the physiological indexes of leaves. All experimental data are expressed as the mean value of three biological replicates. Different letters (a and b) indicate statistically significant differences at the level of p < 0.05.
Agronomy 13 02118 g004
Table 1. Physiological index of fresh shoots for different rape cultivars.
Table 1. Physiological index of fresh shoots for different rape cultivars.
Rape CultivarsSoluble Sugar
(mg/g)		Soluble Protein
(mg/g)		Vitamin C
(mg/g)		Total Chlorophyll
(mg/g)
Fanmingyoutai521.44 ± 16.36 a57.27 ± 10.230.14 ± 0.0330.66 ± 0.08 a
Y1239.92 ± 11.56 de28.46 ± 6.180.19 ± 0.0040.12 ± 0.006
Y2328.90 ± 11.29 c97.36 ± 3.65 cd0.19 ± 0.0060.11 ± 0.005
Y3217.31 ± 41.43102.20 ± 4.27 b0.18 ± 0.0130.10 ± 0.002
Y4173.95 ± 6.4049.77 ± 9.100.23 ± 0.0110.15 ± 0.002 d
Y5241.93 ± 8.98 de93.56 ± 53.04 cd0.25 ± 0.0030.13 ± 0.004
Y6259.79 ± 22.78 d82.79 ± 6.12 de0.16 ± 0.0050.09 ± 0.003
Y7222.10 ± 14.70147.43 ± 16.64 a0.28 ± 0.0080.11 ± 0.003
WH23(CK1)252.76 ± 15.08 d2.59 ± 1.740.10 ± 0.0050.09 ± 0.004
Ziting No. 2(CK2)445.58 ± 19.86 b58.78 ± 13.980.07 ± 0.010.44 ± 0.01 b
Youtai 929(CK3)185.82 ± 12.9415.27 ± 4.670.26 ± 0.0820.11 ± 0.001
Shishan 2017233.23 ± 11.7644.90 ± 70.560.32 ± 0.040.12 ± 0.003
Shishan 2019207.02 ± 15.886.34 ± 0.081.01 ± 0.031 a0.07 ± 0.003
Shishancaitai234.51 ± 9.95123.48 ± 13.56 b0.19 ± 0.0060.10 ± 0.004
Xiziyuan No. 1125.65 ± 7.616.45 ± 4.850.25 ± 0.0250.15 ± 0.013 d
Xiziyuan No. 2205.54 ± 3.3820.77 ± 7.410.50 ± 0.002 e0.20 ± 0.031 c
Nongda No. 1193.29 ± 14.1240.91 ± 1.820.31± 0.0030.09 ± 0.019
Huayouza 652223.75 ± 3.1768.64 ± 13.64 bc0.88 ± 0.012 b0.10 ± 0.003
Fengyou112203.13 ± 8.0417.95 ± 12.500.98 ± 0.02 a0.08 ± 0.001
Xiangsui 603173.41 ± 6.158.66 ± 6.100.34 ± 0.0120.08 ± 0.003
KW120.71 ± 6.1730.46 ± 4.570.28 ± 0.020.13 ± 0.010
K173180.59 ± 19.6133.46 ± 3.940.78 ± 0.083 c0.13 ± 0.003
Ganyou 105259.44 ± 5.61 d78.38 ± 9.250.40 ± 0.0050.10 ± 0.016
Dadi 95190.07 ± 5.1535.77 ± 6.040.58 ± 0.006 d0.12 ± 0.003
20xy1329220.60 ± 15.8524.92 ± 8.260.38 ± 0.0070.14 ± 0.013 de
Note: The content of the physiological indexes is the average of the three biological replicate samples for the bolting stage of the rape. The values correspond with the mean average ± standard deviation. Different letters (a, b, c, d, and e) indicate statistically significant differences at a level of p < 0.05.
Table 2. Physiological index of the leaves for different rape cultivars.
Table 2. Physiological index of the leaves for different rape cultivars.
Rape CultivarsSoluble Sugar
(mg/g)		Soluble Protein
(mg/g)		Vitamin C
(mg/g)		Total
Chlorophyll
(mg/g)
Fanmingyoutai438.10 ± 11.35 a36.16 ± 10.450.08 ± 0.0061.50 ± 0.04 a
Y1313.28 ± 4.43 c186.76 ± 21.92 cde0.07 ± 0.0060.51 ± 0.035
Y2193.30 ± 14.03281.00 ± 30.20 a0.07 ± 0.0620.41 ± 0.022
Y3223.82 ± 11.7672.56 ± 7.720.03 ± 0.0120.44 ± 0.026
Y4273.04 ± 21.9361.76 ± 8.620.005 ± 0.0030.40 ± 0.026
Y5199.33 ± 23.02131.58 ± 10.850.02 ± 0.0020.57 ± 0.065
Y6236.19 ± 19.25147.26 ± 14.500.02 ± 0.0050.31 ± 0.033
Y7220.05 ± 8.32246.29 ± 12.25 ab0.04 ± 0.0010.57 ± 0.042
WH23(CK1)155.56 ± 7.85151.27 ± 16.300.03 ± 0.0040.44 ± 0.033
Ziting No. 2(CK2)363.81 ± 13.04 b116.31 ± 28.990.07 ± 0.0631.34 ± 0.02 b
Youtai 929(CK3)156.19 ± 8.6597.57 ± 19.030.03 ± 0.0281.48 ± 0.139 a
Shishan 2017209.99 ± 54.30108.85 ± 12.090.05 ± 0.0010.41 ± 0.021
Shishan 2019129.56 ± 5.96166.04 ± 11.370.42 ± 0.036 a0.36 ± 0.023
Shishancaitai211.48 ± 28.45103.93 ± 15.940.03 ± 0.0010.51 ± 0.021
Xiziyuan No. 1162.23 ± 6.73103.83 ± 85.290.02 ± 0.0060.15 ± 0.035
Xiziyuan No. 2189.06 ± 11.43132.43 ± 6.650.08 ± 0.0140.74 ± 0.029 c
Nongda No. 1250.04 ± 29.76 de188.81 ± 44.41 cd0.04 ± 0.0060.31 ± 0.011
Huayouza 652207.64 ± 1.39139.14 ± 14.330.26 ± 0.025 b0.38 ± 0.016
Fengyou112173.14 ± 7.3082.24 ± 38.910.08 ± 0.0140.66 ± 0.078 e
Xiangsui 603197.71 ± 5.21168.16 ± 14.290.11 ± 0.013 de0.71 ± 0.025 de
KW216.39 ± 24.31275.19 ± 31.45 a0.01 ± 0.0161.04 ± 0.025 c
K173189.32 ± 26.4463.90 ± 51.450.13 ± 0.061 d0.42 ± 0.009
Ganyou 105190.80 ± 11.7763.80 ± 23.210.20 ± 0.008 c0.51 ± 0.016
Dadi 95202.79 ± 20.71220.84 ± 32.28 bc0.04 ± 0.0090.54 ± 0.019
20xy1329170.45 ± 4.65134.04 ± 5.280.05 ± 0.0090.53 ± 0.017
Note: The content of the physiological indexes is the average of the three biological replicate samples for the bolting stage of the rape. The values correspond with the mean average ± standard deviation. Different letters (a, b, c, d, and e) indicate statistically significant differences at a level of p < 0.05.
Table 3. Content of saccharides in fresh shoots of Fanmingyoutai and WH23.
Table 3. Content of saccharides in fresh shoots of Fanmingyoutai and WH23.
IndexSubstance ClassAmount (mg/g)
WH23 (CK)Fanmingyoutai
Maltosedisaccharide0.04 d0.02 d
Sucrosedisaccharide64.82 c78.83 c
Trehalosedisaccharide0.42 d0.48 d
LactosedisaccharideN/AN/A
D-Arabinosemonosaccharide0.05 d0.04 d
D-Fructosemonosaccharide139.19 b160.74 b
L-Fucosemonosaccharide0.01 d0.01 d
D-Galactosemonosaccharide0.40 d0.07 d
Glucosemonosaccharide211.11 a216.72 a
Inositolmonosaccharide1.68 d2.27 d
L-Rhamnosemonosaccharide0.01 d0.02 d
D-Sorbitolmonosaccharide0.01 d0.01 d
Xylitolmonosaccharide0.01 d0.01 d
Note: The content of saccharides in fresh shoots of Fanmingyoutai and WH23 is the average of the three sample biological replicates for the bolting stage of the rape. Different letters (a, b, c and d) indicate statistically significant differences at a level of p < 0.05. N/A indicates no lactose in Fanmingyoutai and WH23.
Table 4. Differential genes in the fresh shoots of Fanmingyoutai and WH23 related to taste.
Table 4. Differential genes in the fresh shoots of Fanmingyoutai and WH23 related to taste.
Gene IDGene SymbolGene DescriptionExpression Regulation
BnaC07g10340DLOC106394983endogenous alpha-amylasedown
BnaA08g05660DLOC106360628beta-amylase 5down
BnaCnng46880DLOC106431371probable sucrose-phosphatase 3adown
BnaA09g30430DLOC106429767sucrose transport protein SUC2down
BnaA09g15290DLOC106391407galactinol synthase 2down
BnaAnng09070DLOC106421594aldehyde oxidase GLOXup
BnaAnng01700DLOC106422717putative phosphatidylglycerolup
BnaA03g47060DLOC106360071bidirectional sugar transporter SWEET14down
BnaC07g33320DLOC106449449bidirectional sugar transporter SWEET17down
BnaC08g06850DLOC106414209sugar transport protein 5 STP5up
BnaC06g21620DLOC106353515indole glucosinolate O-methyltransferase 5 GSLdown
Table 5. Correlation analysis between physiological indexes and differential gene expression.
Table 5. Correlation analysis between physiological indexes and differential gene expression.
IndexGene Expression in the Fresh ShootGene Expression in the Leaves
GLOXSWEET17STPGSLGLOXSWEET17STPGSL
Content of soluble sugar0.0350.1720.0970.021−0.358 **−0.169−0.215−0.035
Content of soluble protein−0.0130.250 *0.0930.432 **−0.152−0.272 *−0.236 *−0.118
Content of vitamin C−0.274 *−0.237 *−0.323 **−0.238 *0.242 *0.004−0.021−0.151
Content of total chlorophyll−0.0970.1270.0570.0950.1400.1920.2040.260 *
* At the 0.05 level (two-tailed), the correlation is significant. ** At the level of 0.01 (two-tailed), the correlation is significant.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Yan, W.; Tan, T.; Chen, H.; Sun, H.; Hui, R.; Zhang, Z. Comparative Study of Bolting Adaptability between 60Co-Induced Rape and Its Original Material. Agronomy 2023, 13, 2118. https://doi.org/10.3390/agronomy13082118

AMA Style

Yan W, Tan T, Chen H, Sun H, Hui R, Zhang Z. Comparative Study of Bolting Adaptability between 60Co-Induced Rape and Its Original Material. Agronomy. 2023; 13(8):2118. https://doi.org/10.3390/agronomy13082118

Chicago/Turabian Style

Yan, Wei, Tailong Tan, Hao Chen, Haiyan Sun, Rongkui Hui, and Zhenqian Zhang. 2023. "Comparative Study of Bolting Adaptability between 60Co-Induced Rape and Its Original Material" Agronomy 13, no. 8: 2118. https://doi.org/10.3390/agronomy13082118

APA Style

Yan, W., Tan, T., Chen, H., Sun, H., Hui, R., & Zhang, Z. (2023). Comparative Study of Bolting Adaptability between 60Co-Induced Rape and Its Original Material. Agronomy, 13(8), 2118. https://doi.org/10.3390/agronomy13082118

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop