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Communication

Quantification and Diversity Analyses of Glucosinolates in 191 Broccoli Genotypes Highlight Valuable Genetic Resources for Molecular Breeding

by
Meijia Yan
1,†,
Chenxue Song
1,†,
Shiwen Su
2,
Junliang Li
1,3,
Zhiwei Hu
1,3,
Sue Lin
1,
Huixi Zou
1,3,
Zheng Tang
2,* and
Xiufeng Yan
1,3,*
1
National and Local Joint Engineering Research Center of Ecological Treatment Technology for Urban Water Pollution, Zhejiang Provincial Key Laboratory for Water Environment and Marine Biological Resources Protection, College of Life and Environmental Science, Wenzhou University, Zhong-Xin Street, Wenzhou 325035, China
2
Wenzhou Vocational College of Science and Technology, Wenzhou 325006, China
3
Institute for Eco-Environmental Research of Sanyang Wetland, Wenzhou University, Ouhai Avenue, Wenzhou 325014, China
*
Authors to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Agronomy 2023, 13(12), 2928; https://doi.org/10.3390/agronomy13122928
Submission received: 19 October 2023 / Revised: 16 November 2023 / Accepted: 27 November 2023 / Published: 28 November 2023
Browse Figures
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Abstract

:
Glucosinolates (GSLs), crucial secondary metabolites in cruciferous vegetables, hydrolyze upon consumption or mechanical damage, forming bioactive compounds with anti-cancer properties, such as glucoraphanin (GRA). Among cruciferous vegetables, broccoli stands out for its high GSL content, which varies significantly among different genotypes. This study aimed to characterize and quantify glucosinolate compounds in broccoli using LC-HRMS2 and UPLC. We identified thirteen GSLs in 191 broccoli genotypes, including seven aliphatic, five indole, and one aromatic glucosinolate. The GSL content in these genotypes ranged from 0.1705 to 5.8174 mg/g (DW). We also explored GSL diversity and content in seven developmental organs, finding high diversity and content in seedling roots and florets. Notably, genotype No. 300 had the highest GSL content (5.8174 mg/g, DW) and GRA (3.1545 mg/g, DW), along with a larger flower bulb diameter (13.4 cm) and a shorter growth stage (11 days), demonstrating its potential for breeding GRA-rich broccoli. To our knowledge, this study encompasses the largest number of broccoli genotypes to date, broadening our understanding of GSLs’ diversity and content in broccoli. These findings may provide valuable resources for future breeding or the commercial cultivation of GRA-rich broccoli.

1. Introduction

Glucosinolates (GSLs) are essential secondary metabolites found in cruciferous plants, with over 156 structures identified [1]. They are categorized into aliphatic, aromatic, and indole groups based on their amino acid precursors [2,3]. Intact GSLs are chemically stable, while isothiocyanates which are formed post-myrosinase degradation display diverse biological activities [4]. In plants, GSLs and myrosinases are stored separately as mechanical injury triggers myrosinase release, hydrolyzing GSLs [5]. Although humans lack myrosinases, residual bacterial colonies in the gastrointestinal tract with myrosinase-like activity can degrade GSLs to form isothiocyanates [6]. Animal studies confirm that GSLs can convert into biologically active products, affecting physiological health [7].
The interest in GSLs and their hydrolysates has spurred the development of extraction and isolation methods. Depending on research needs, GSL analysis methods fall into two categories: intact GSLs and their breakdown products. The chromatography (LC) method is commonly used for GSL quantification [8]. However, the strong polarity of intact GSLs challenges their separation in LC. Many studies have converted intact glucosinolates into desulfoglucosinolates for an easier LC analysis [9,10]. Moreover, several studies have successfully separated different GSLs by adjusting sample preparation techniques, including variations in extraction solvents, concentrations, and durations [8]. Additionally, myrosinase treatment procedures are often incorporated into the extraction process for biological activity studies to enhance the levels of active products, such as sulforaphane [11].
Broccoli (Brassica oleracea var. italica) is notable for its anti-cancer properties, attributed to GSLs, which also influence flavor [12] and disease [13] and pest [14] resistance. Glucoraphanin (GRA), an aliphatic GSL, and its degradation product, sulforaphane (SF), are potent, safe, plant-derived anti-cancer compounds [15]. SF has shown promise in cancer prevention and treatment, influencing cell cycle regulation [16], acting as an anti-inflammatory component [17], and reducing oxidative stress [18]. Dietary SF from plant sources is considered non-toxic, is well-tolerated by the body, and is a naturally occurring substance suitable for clinical studies [19]. Existing research has shown significant variations in GRA content among cruciferous vegetables, with broccoli being the richest source [20].
The broccoli industry in China is undergoing rapid development and boasts the largest broccoli planting area worldwide. Despite this growth, there is an urgent need to improve the independent innovation capacity of the domestic broccoli seed industry. Currently, germplasm resources of broccoli with high anticancer potential and rich GRA content are relatively scarce. Therefore, it is critical to comprehensively characterize the GSL content and diversity of broccoli germplasm and to establish a comprehensive GSL database. This will facilitate the breeding of GRA-rich cultivars. In this study, we investigated the chemical diversity, content, and spatial–temporal distribution of GSLs among 191 broccoli genotypes. The results enhance the understanding of the content and distribution of GSLs in broccoli, providing a valuable resource and scientific evidence for targeted molecular breeding of GRA-rich broccoli.

2. Materials and Methods

2.1. Planting and Collection of Plant Materials

Broccoli samples were cultivated and harvested at the Wenzhou Academy of Agricultural Sciences, located in Tengqiao town (longitude: 120.51° E, latitude: 28.06° N, altitude: 10 m). The planted fields featured cyanoge clay soil, a predominant soil type for triple-cropping paddy fields in southern Zhejiang Province [21]. A total of 191 genotypes of broccoli, obtained through mating crosses over the past decade, were selected for this study. For each genotype, one hundred seeds were planted, and 30 uniformly growing plants were chosen. Ten plants were combined into a single sample, lyophilized, and ground to create a representative specimen. The collected samples encompassed various plant organs, including roots (at the four-euphylla stage), leaves (at the four-euphylla stage), stalks (at the four-euphylla stage), rosette leaves (at the rosette stage), rosette leaves (at the squaring stage), rosette leaves (at the floret stage), and florets (see Figure S1).

2.2. Sample Preparation

GSLs were extracted with minor modifications to the existing protocol [22]. Approximately 30 mg of freeze-dried sample was crushed using a JXFSTPRP-CLN freezing grinder (Jingxin, Shanghai, China) and then mixed with 1.5 mL of 70% methanol and 25 μL of 1.25 mmol/L Glucotropaeolin (Sigma, Dallas, TX, USA), and finally heated at 80 °C for 10 min, followed by centrifugation at 9000 rpm to collect the supernatant. We repeated the extraction process with hot methanol two times. The combined liquid was purified using a DEAE Sephadex A-25 anion-exchange column, which was washed with 2 mL 70% methanol (twice), 5 mL UPH2O (twice), and 2 mL 20 mmol/L acetic acid buffer (pH = 5). Desulfurization was performed overnight with 0.5 mL of sulfatase (Sigma, St. Louis, MO, USA). The desulfurized samples were washed with 500 μL UPH2O three times, followed by vacuum-drying using Concentrator plus (Eppendorf, Hamburg, Germany). The sample was then dissolved in 100 μL UPH2O for analysis.

2.3. Qualitative and Quantitative Analyses of GSLs via UPLC-DAD

The current standard method for glucosinolate analysis involves desulfurizing glucosinolates with sulfatase and then employing an RP-HPLC gradient system for analysis [23]. The content and composition of GSLs were determined via UPLC analysis of the desulfoglucosinolates (dGSLs) following a previously described method [24]. The UPLC analysis was performed using an Agilent 1290 UPLC system equipped with a Waters ACQUITY UPLC HSS T3 column (50 mm × 2.1 mm, 1.8 µm), coupled with photodiode array detection. A gradient elution program was employed with solvent A (water) and solvent B (methanol) as the mobile phase, according to Table S1. The sample holder temperature was maintained at 4 °C during the analysis, while the column temperature was set at 30 °C. The flow rate and injection volume were set at 0.5 mL/min and 5 µL, respectively. The UV detection wavelength was set at 229 nm according to previous studies [25]. Quantification of dGSLs was based on integrative peak areas normalized against a known amount of an internal standard, glucotropaeolin.
The dGSLs, previously analyzed via UPLC as described above, underwent LC–MS analysis for qualitative assessment. LC–MS was performed using an Exion LC system coupled with a quadrupole time-of-flight Triple TOF 5600 mass spectrometer (Sciex, Foster City, CA, USA). The LC conditions and chromatographic column remained consistent with the quantitative analysis method. The mass spectrometer operated in positive ESI mode with optimized MS parameters set as follows: ion spray voltage at 5500 V; turbo spray temperature at 550 °C; curtain gas at 35 psi; nebulizer gas at 55 psi; heater gas at 55 psi; declustering potential at 80 V; collision energy at 25 eV; collision energy spread at 10 eV.

2.4. Statistical Analysis

All assays were conducted in triplicate. The data were processed using SPSS (ver. 22.0). One-way ANOVA and Tukey’s multiple-range test were used to evaluate significant differences (p < 0.05). Correlation analysis, K-mean analysis, and cluster analysis were performed using the OmicStudio tools at https://www.omicstudio.cn/tool (accessed on 20 August 2023) to assess the difference and relationships among GSLs across genotypes and organs in broccoli.

3. Results

3.1. Identifications of GSLs Based on Triple-TOF

Zhejiang Province, a major production and export hub for broccoli in China during winter and spring, is in need of a new form of germplasm development with high GRA content to enhance market competitiveness. In this study, we characterized the florets of 191 broccoli genotypes, identifying 13 glucosinolate compounds in mature florets (Table 1). Meanwhile, modifications to the extraction process of dGSLs (refer to Section 2) and their detection using the UPLC system enhanced separation efficiency and reduced detection time. GSL annotation was performed based on a comprehensive corpus of analytical information from previously reported GSLs and our previously published method [1,24]. This included an accurate mass determination with m/z values (<1 ppm) that aligned with theoretical m/z from published GSL data, as well as reasonable fragmentation patterns and diagnostic neutral loss of 162 Da, corresponding to an anhydroglucose of GSLs [1]. In total, we identified 13 GSLs, comprising seven aliphatic GSLs (glucoiberin (GIB), progoitrin (PRO), sinigrin (SIN), glucoraphanin (GRA), glucoalyssin (GAL), glucoibervirin (GIV), and glucoerucin (GER)); five indole GSLs (glucobrassicin (GBS), 4-methoxyglucobrassicin (4MGBS), neoglucobrassicin (NGBS), 4-hydroxyglucobrassicin (4HGBS), and 1-hydroxyglucobrassicin (1HGBS)); and one aromatic GSL (gluconasturtiin (GNT)) (Figure 1). Table 1 summarizes the retention time, measured masses, calculated masses, accurate masses, mass errors, and MS2 diagnostic ions for the identified dGSLs. Additionally, the MS2 spectrum and mass fragmentation patterns of dGSLs are presented in Figures S2–S4.

3.2. Evaluation of GSLs in Florets Based on 191 Broccoli Genotypes

After establishing the chemical diversity of GSLs in all the samples, we proceeded to quantitatively analyze the content of each component. The results reveal that aliphatic GSLs comprised 45.1%, indole GSLs 53.2%, and aromatic GSLs 1.7% of total GSLs (Figure 2A). Except for SIN, GIV, 1HGBS, GER, and GNT, the remaining eight GSLs were detected in all samples (Table S2), with GBS and GRA being the most abundant (Figure 2B). The GRA content ranged from 0.0260 to 3.1545 mg/g (DW), and GBS from 0.0144 to 1.5767 mg/g (DW). The total GSL content in the 191 broccoli samples ranged from 0.1705 to 5.8174 mg/g (DW), with the highest GSL content being approximately 34 times greater than the lowest (Figure 2C), aligning with previous studies [26]. The Q300 material displayed the highest total GSL and GRA content. We also analyzed the correlation between GSL content and agronomic traits like floret diameter and growth period (Table S3), finding no significant correlations (0.07 between floret diameter and GSL content; 0.17 between growth period and GSL content).

3.3. Evaluation of Total GSLs in Different Organs and Developmental Stages in Broccoli

The content of GSLs in plants is influenced by various factors, including genotype, tissue location, and developmental stage. Therefore, we assessed GSL content across genotypes, organs, and growth stages. K-means analysis clustered the 191 materials based on their GSL content, with the elbow method suggesting k = 3 for optimal clustering (Figure 3A). The materials were categorized into high (14 samples), middle (69 samples), and low (108 samples) GSL content groups (Figure 3B). For a more detailed investigation, we randomly selected six representative samples from each group to examine the GSL content across various organs and developmental stages. The findings revealed higher GSL content in roots, stalks, and leaves during the seedling stage (four-euphylla stage), especially in roots (Figure 3C). However, the GSL content in rosette leaves was relatively low during the rosette, squaring, and floret stages. Notably, florets in the “High” group matched or surpassed root GSL content at the four-euphylla stage. Additionally, the content of GSLs in leaves decreased initially and then increased from the seedling stage to the rosette stage, squaring stage, and floret stage. Overall, florets in the “High” group exhibited relatively high GSL content, presenting a valuable natural GSL source.

3.4. Analysis of GSL Diversity in Different Materials

The initial step in breeding broccoli varieties with high GSL content involves evaluating the distribution and content of GSLs in available broccoli materials. Among all GSLs, glucoraphanin (GRA) has received considerable attention due to its notable anticancer properties. We conducted a detailed analysis of the diversity and content of GSLs in various materials. All samples contained GSLs such as GAL, PRO, GBS, and 4MGBS. However, the remaining nine GSLs were not detected in some organs or developmental stages (see Figure 4). For instance, the rosette leaves during the rosette stage in both the “High” and “Low” groups, as well as those in the squaring stage in the “Middle” group, did not contain glucoiberin (GIB). During the seedling stage, roots exhibited higher levels of GER, 4MGBS, and NGBS, while stalks contained higher levels of GRA, and leaves had higher levels of both GRA and GBS. Overall, there was significant diversity and variation in the distribution of GSLs among roots, stalks, and leaves during the seedling stage (four-euphylla stage), as well as among rosette leaves at different developmental stages (rosette, squaring, and floret stages). This indicates that both the types and content of GSLs vary throughout the entire lifecycle of broccoli.

4. Discussion

In this study, 13 GSLs were identified among 191 broccoli genotypes, aligning with previous research that identified a similar range of GSLs in various numbers of genotypes. The 13 GSLs covered 10 of 12 GSLs identified in 80 broccoli genotypes [26], and 11 of 12 GSLs identified in 6 broccoli genotypes [27]. Notably, our findings predominantly feature aliphatic and indolyl GSLs, with a minor proportion of aromatic GSLs. In contrast, studies exploring GSL diversity in Brassica napus [28], Brassica oleracea var. capitata [29], Brassica pekinensis Rupr. [30], and other Brassica species [31,32,33] revealed a relatively higher proportion of aromatic GSLs, indicating a distinct species preference in GSL distribution. The low proportion of aromatic GSLs in broccoli (about 1%) and the inverse correlation observed between the content of aliphatic and indole GSLs, especially between GRA (aliphatic GSLs) and GBS (indole GSLs), are significant (see Figure 2C). The in vivo synthesis pathways of GSLs have been extensively elucidated, with the core structure being synthesized first [34,35], followed by side chain modification [36,37,38,39]. Research has demonstrated that the synthesis of GSLs is governed by a core complex comprising MYB and bHLH transcription factors (TFs). Notably, MYB TFs are divided into two distinct clades, each specifically regulating the synthesis of either aliphatic or indole GSLs [40]. Future studies could potentially enhance the yield of GRA (aliphatic GSLs) in broccoli via upregulating MYB28/29/76 expression and downregulating MYB34/51/122 expression, steering the core structure toward the aliphatic side chain modification pathway.
The total GSL content in broccoli florets from this study ranged from 0.1705 to 5.8174 mg/g (Figure 2), which is not exceptionally high compared to other cruciferous plants, such as canola (2.9 ± 0.9 mg/g), rapeseed (6.4 ± 1.3 mg/g), and turnip (14 ± 3.4 mg/g) [33]. However, the GRA content in broccoli (0.03 to 3.15 mg/g) is significantly higher than in other cruciferous plants like Chinese cabbage, which contains approximately 0 to 0.46 mg/g [30]. This observation aligns with findings from other studies examining broccoli leaves, which report GRA levels ranging from 0.11 to 0.79 mg/g [27]. In a separate study, Wang et al. treated the florets of ‘Yanxiu’ and ‘Xianglv No. 3’ with methyl Jasmonate, resulting in a GRA content of 1.7 mg/g, lower than that found in our GRA-rich genotypes [41]. Additionally, our research indicates high GSL content in broccoli seedlings, especially in roots, which is consistent with previous findings [26]. However, the limited biomass of seedlings makes the cost of consuming or extracting natural GSLs high. In contrast, the florets of materials with high GSL content offer a more practical option.

5. Conclusions

Conclusively, this study contributes significantly to the GSL database, providing one of the largest datasets to date. The identification of broccoli genotypes with high GSL content, particularly in florets, offers valuable resources for future research and breeding efforts. These high-GSL-content varieties could serve as excellent parental lines for breeding broccoli rich in GSLs. Additionally, comparing genotypes and gene expression between high- and low-GSL-level varieties could further our understanding of GSL genetics and the regulation of GSL-related genes. This research not only adds to our knowledge of GSL distribution in broccoli but also opens avenues for future genetic and breeding work to enhance GSL content, particularly GRA, for its health-promoting properties.

Supplementary Materials

The following supporting information can be downloaded at: https://www.mdpi.com/article/10.3390/agronomy13122928/s1, Figure S1: The collected samples of broccoli from 191 genotypes; Figure S2: MS2 spectrum of aliphatic desulfoglucosinolates in broccoli; Figure S3: MS2 spectrum of indole desulfoglucosinolates in broccoli; Figure S4: MS2 spectrum of aromatic desulfoglucosinolates in broccoli; Table S1: The gradient program for UPLC; Table S2: Qualitative and quantitative analyses of GSLs in the florets of 191 broccoli materials; Table S3: Diameter and growth stage information of broccoli florets; Table S4: The contents of GSLs in different organs and at different developmental stages of 18 broccoli genotypes. Table S5: Weather information for Tengqiao town.

Author Contributions

M.Y.: Validation; Investigation; Data curation; Writing—original draft; C.S.: Validation; Investigation; Data curation; Writing—original draft; S.S.: Formal analysis; Investigation; Resources; Data curation; Writing—original draft; J.L.: Formal data analysis; Investigation; Data curation; Validation; Z.H.: Methodology; Validation; Investigation; S.L.: Conceptualization; Writing—review and editing; H.Z.: Conceptualization; Project administration; Z.T.: Investigation; Resources; Writing—review and editing; X.Y.: Conceptualization; Funding acquisition; Resources. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported by the National Key R&D Program of China (Grant Number: 2022YFE0108300).

Data Availability Statement

Data are contained within the article and Supplementary Materials.

Acknowledgments

We thank Haihong Wen (National and Local Joint Engineering Research Center) for her assistance with the experiments.

Conflicts of Interest

The authors declare no conflict of interest.

Abbreviations

GSLsGlucosinolates
SFSulforaphane
UPH2OUltrapure Water
RP-HPLCReversed-Phase High-Performance Liquid Chromatography
HRMSHigh-Resolution Mass Spectrum
dGSLsDesulfoglucosinolates
LC–MSLiquid Chromatograph–Mass Spectrometer
UPLCUltra Performance Liquid Chromatography
UPLC–UV–MSUltra Performance Liquid Chromatography–Ultraviolet–Mass Spectrometry
ESIElectrospray Ionization
SPSSStatistical Product and Service Solutions
ANOVAAnalysis of Variance
GIBGlucoiberin
PROProgoitrin
SINSinigrin
GRAGlucoraphanin
GALGlucoalyssin
GIVGlucoibervirin
GERGlucoerucin
GBSGlucobrassicin
4MGBS4-Methoxyglucobrassicin
NGBSNeoglucobrassicin
4HGBS4-Hydroxyglucobrassicin
1HGBS1-Hydroxyglucobrassicin
GNTGluconasturtiin
SEESum of Squared Errors
DWDry Weight

References

  1. Blažević, I.; Montaut, S.; Burčul, F.; Olsen, C.E.; Burow, M.; Rollin, P.; Agerbirk, N. Glucosinolate structural diversity, identification, chemical synthesis and metabolism in plants. Phytochemistry 2020, 169, 112100. [Google Scholar] [CrossRef] [PubMed]
  2. Giamoustaris, A.; Mithen, R. Genetics of aliphatic glucosinolates. IV. Side-chain modification in Brassica oleracea. Theor. Appl. Genet. 1996, 93, 1006–1010. [Google Scholar] [CrossRef] [PubMed]
  3. Wittstock, U.; Halkier, B.A. Glucosinolate research in the Arabidopsis era. Trends Plant Sci. 2002, 7, 263–270. [Google Scholar] [CrossRef] [PubMed]
  4. Rask, L.; Andréasson, E.; Ekbom, B.; Eriksson, S.; Pontoppidan, B.; Meijer, J. Myrosinase: Gene family evolution and herbivore defense in Brassicaceae. Plant Mol. Biol. 2000, 42, 93–113. [Google Scholar] [CrossRef]
  5. Andréasson, E.; Jørgensen, L.B.; Höglund, A.S.; Rask, L.; Meijer, J. Different myrosinase and idioblast distribution in Arabidopsis and Brassica napus. Plant Physiol. 2001, 127, 1750–1763. [Google Scholar] [CrossRef] [PubMed]
  6. Mullaney, J.A.; Kelly, W.J.; McGhie, T.K.; Ansell, J.; Heyes, J.A. Lactic acid bacteria convert glucosinolates to nitriles efficiently yet differently from enterobacteriaceae. J. Agric. Food Chem. 2013, 61, 3039–3046. [Google Scholar] [CrossRef]
  7. Elfoul, L.; Rabot, S.; Khelifa, N.; Quinsac, A.; Duguay, A.; Rimbault, A. Formation of allyl isothiocyanate from sinigrin in the digestive tract of rats monoassociated with a human colonic strain of Bacteroides thetaiotaomicron. FEMS Microbiol. Lett. 2001, 197, 99–103. [Google Scholar] [CrossRef]
  8. Almushayti, A.Y.; Brandt, K.; Carroll, M.A.; Scotter, M.J. Current analytical methods for determination of glucosinolates in vegetables and human tissues. J. Chromatogr. A 2021, 1643, 462060. [Google Scholar] [CrossRef]
  9. Qian, H.; Sun, B.; Miao, H.; Cai, C.; Xu, C.; Wang, Q. Variation of glucosinolates and quinone reductase activity among different varieties of Chinese kale and improvement of glucoraphanin by metabolic engineering. Food Chem. 2015, 168, 321–326. [Google Scholar] [CrossRef]
  10. Cai, C.; Miao, H.; Qian, H.; Yao, L.; Wang, B.; Wang, Q. Effects of industrial pre-freezing processing and freezing handling on glucosinolates and antioxidant attributes in broccoli florets. Food Chem. 2016, 210, 451–456. [Google Scholar] [CrossRef]
  11. Sheu, M.J.; Yeh, M.C.; Tsai, M.C.; Wang, C.C.; Chang, Y.L.; Wang, C.J.; Huang, H.P. Glucosinolates Extracts from Brassica juncea Ameliorate HFD-Induced Non-Alcoholic Steatohepatitis. Nutrients 2023, 15, 3497. [Google Scholar] [CrossRef] [PubMed]
  12. Bell, L.; Oloyede, O.O.; Lignou, S.; Wagstaff, C.; Methven, L. Taste and Flavor Perceptions of Glucosinolates, Isothiocyanates, and Related Compounds. Mol. Nutr. Food Res. 2018, 62, e1700990. [Google Scholar] [CrossRef] [PubMed]
  13. Fan, J.; Crooks, C.; Creissen, G.; Hill, L.; Fairhurst, S.; Doerner, P.; Lamb, C. Pseudomonas sax genes overcome aliphatic isothiocyanate-mediated non-host resistance in Arabidopsis. Science 2011, 331, 1185–1188. [Google Scholar] [CrossRef] [PubMed]
  14. Beekwilder, J.; van Leeuwen, W.; van Dam, N.M.; Bertossi, M.; Grandi, V.; Mizzi, L.; Soloviev, M.; Szabados, L.; Molthoff, J.W.; Schipper, B.; et al. The impact of the absence of aliphatic glucosinolates on insect herbivory in Arabidopsis. PLoS ONE 2008, 3, e2068. [Google Scholar] [CrossRef] [PubMed]
  15. Soundararajan, P.; Kim, J.S. Anti-Carcinogenic Glucosinolates in Cruciferous Vegetables and Their Antagonistic Effects on Prevention of Cancers. Molecules 2018, 23, 2983. [Google Scholar] [CrossRef] [PubMed]
  16. Bryant, C.S.; Kumar, S.; Chamala, S.; Shah, J.; Pal, J.; Haider, M.; Seward, S.; Qazi, A.M.; Morris, R.; Semaan, A.; et al. Sulforaphane induces cell cycle arrest by protecting RB-E2F-1 complex in epithelial ovarian cancer cells. Mol. Cancer 2010, 9, 47. [Google Scholar] [CrossRef] [PubMed]
  17. Heiss, E.; Herhaus, C.; Klimo, K.; Bartsch, H.; Gerhäuser, C. Nuclear factor kappa B is a molecular target for sulforaphane-mediated anti-inflammatory mechanisms. J. Biol. Chem. 2001, 276, 32008–32015. [Google Scholar] [CrossRef] [PubMed]
  18. Priya, D.K.; Gayathri, R.; Gunassekaran, G.; Murugan, S.; Sakthisekaran, D. Chemopreventive role of sulforaphane by upholding the GSH redox cycle in pre- and post-initiation phases of experimental lung carcinogenesis. Asian Pac. J. Cancer Prev. 2011, 12, 103–110. [Google Scholar]
  19. Vanduchova, A.; Anzenbacher, P.; Anzenbacherova, E. Isothiocyanate from Broccoli, Sulforaphane, and Its Properties. J. Med. Food 2019, 22, 121–126. [Google Scholar] [CrossRef]
  20. 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]
  21. Fan, B.; Tang, M.; Yao, L.; Zhang, A.; Yin, H.; Yang, W.; Ma, Z.; Xiang, W.; Bao, Z. Germanium fractions in typical paddy soil and its interaction with humic substances. Environ. Sci. Pollut. Res. Int. 2021, 28, 9670–9681. [Google Scholar] [CrossRef]
  22. Wang, J.; Gu, H.; Yu, H.; Zhao, Z.; Sheng, X.; Zhang, X. Genotypic variation of glucosinolates in broccoli (Brassica oleracea var. italica) florets from China. Food Chem. 2012, 133, 735–741. [Google Scholar] [CrossRef]
  23. Ishida, M.; Kakizaki, T.; Ohara, T.; Morimitsu, Y. Development of a simple and rapid extraction method of glucosinolates from radish roots. Breed. Sci. 2011, 61, 208–211. [Google Scholar] [CrossRef]
  24. Lin, H.; Sun, J.; Hu, Z.; Cheng, C.; Lin, S.; Zou, H.; Yan, X. Variation in Glucosinolate Accumulation among Different Sprout and Seedling Stages of Broccoli (Brassica oleracea var. italica). Plants 2022, 11, 1563. [Google Scholar] [CrossRef]
  25. Bréard, D.; Barrit, T.; Sochard, D.; Aligon, S.; Planchet, E.; Teulat, B.; Le Corff, J.; Campion, C.; Guilet, D. Development of a quantification method for routine analysis of glucosinolates and camalexin in brassicaceous small-sized samples by simultaneous extraction prior to liquid chromatography determination. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci. 2022, 1205, 123348. [Google Scholar] [CrossRef] [PubMed]
  26. Li, Z.; Zheng, S.; Liu, Y.; Fang, Z.; Yang, L.; Zhuang, M.; Zhang, Y.; Lv, H.; Wang, Y.; Xu, D. Characterization of glucosinolates in 80 broccoli genotypes and different organs using UHPLC-Triple-TOF-MS method. Food Chem. 2021, 334, 127519. [Google Scholar] [CrossRef]
  27. Ares, A.M.; Nozal, M.J.; Bernal, J.L.; Bernal, J. Optimized extraction, separation and quantification of twelve intact glucosinolates in broccoli leaves. Food Chem. 2014, 152, 66–74. [Google Scholar] [CrossRef]
  28. Missinou, A.A.; de Carvalho, J.F.; Marnet, N.; Delhaye, T.; Hamzaoui, O.; Sayed, D.A.; Guitton, Y.; Lebreton, L.; Langrume, C.; Laperche, A.; et al. Identification and Quantification of Glucosinolates and Phenolics in a Large Panel of Brassica napus Highlight Valuable Genetic Resources for Chemical Ecology and Breeding. J. Agric. Food Chem. 2022, 70, 5245–5261. [Google Scholar] [CrossRef] [PubMed]
  29. Bhandari, S.R.; Rhee, J.; Choi, C.S.; Jo, J.S.; Shin, Y.K.; Lee, J.G. Profiling of Individual Desulfo-Glucosinolate Content in Cabbage Head (Brassica oleracea var. capitata) Germplasm. Molecules 2020, 25, 1860. [Google Scholar] [CrossRef]
  30. Zhou, B.; Huang, W.; Feng, X.; Liu, Q.; Ibrahim, S.A.; Liu, Y. Identification and quantification of intact glucosinolates at different vegetative growth periods in Chinese cabbage cultivars by UHPLC-Q-TOF-MS. Food Chem. 2022, 393, 133414. [Google Scholar] [CrossRef]
  31. Hwang, I.M.; Park, B.; Dang, Y.M.; Kim, S.Y.; Seo, H.Y. Simultaneous direct determination of 15 glucosinolates in eight Brassica species by UHPLC-Q-Orbitrap-MS. Food Chem. 2019, 282, 127–133. [Google Scholar] [CrossRef] [PubMed]
  32. Dong, M.; Tian, Z.; Ma, Y.; Yang, Z.; Ma, Z.; Wang, X.; Li, Y.; Jiang, H. Rapid screening and characterization of glucosinolates in 25 Brassicaceae tissues by UHPLC-Q-exactive orbitrap-MS. Food Chem. 2021, 365, 130493. [Google Scholar] [CrossRef] [PubMed]
  33. Mocniak, L.E.; Elkin, K.R.; Dillard, S.L.; Bryant, R.B.; Soder, K.J. Building comprehensive glucosinolate profiles for brassica varieties. Talanta 2023, 251, 123814. [Google Scholar] [CrossRef]
  34. Mikkelsen, M.D.; Hansen, C.H.; Wittstock, U.; Halkier, B.A. Cytochrome P450 CYP79B2 from Arabidopsis catalyzes the conversion of tryptophan to indole-3-acetaldoxime, a precursor of indole glucosinolates and indole-3-acetic acid. J. Biol. Chem. 2000, 275, 33712–33717. [Google Scholar] [CrossRef] [PubMed]
  35. Piotrowski, M.; Schemenewitz, A.; Lopukhina, A.; Müller, A.; Janowitz, T.; Weiler, E.W.; Oecking, C. Desulfoglucosinolate sulfotransferases from Arabidopsis thaliana catalyze the final step in the biosynthesis of the glucosinolate core structure. J. Biol. Chem. 2004, 279, 50717–50725. [Google Scholar] [CrossRef] [PubMed]
  36. Chen, S.; Glawischnig, E.; Jørgensen, K.; Naur, P.; Jørgensen, B.; Olsen, C.E.; Hansen, C.H.; Rasmussen, H.; Pickett, J.A.; Halkier, B.A. CYP79F1 and CYP79F2 have distinct functions in the biosynthesis of aliphatic glucosinolates in Arabidopsis. Plant J. 2003, 33, 923–937. [Google Scholar] [CrossRef] [PubMed]
  37. Mikkelsen, M.D.; Naur, P.; Halkier, B.A. Arabidopsis mutants in the C-S lyase of glucosinolate biosynthesis establish a critical role for indole-3-acetaldoxime in auxin homeostasis. Plant J. 2004, 37, 770–777. [Google Scholar] [CrossRef] [PubMed]
  38. Grubb, C.D.; Zipp, B.J.; Ludwig-Müller, J.; Masuno, M.N.; Molinski, T.F.; Abel, S. Arabidopsis glucosyltransferase UGT74B1 functions in glucosinolate biosynthesis and auxin homeostasis. Plant J. 2004, 40, 893–908. [Google Scholar] [CrossRef]
  39. Zhang, J.; Wang, H.; Liu, Z.; Liang, J.; Wu, J.; Cheng, F.; Mei, S.; Wang, X. A naturally occurring variation in the BrMAM-3 gene is associated with aliphatic glucosinolate accumulation in Brassica rapa leaves. Hortic. Res. 2018, 5, 69. [Google Scholar] [CrossRef]
  40. Mitreiter, S.; Gigolashvili, T. Regulation of glucosinolate biosynthesis. J. Exp. Bot. 2021, 72, 70–91. [Google Scholar] [CrossRef]
  41. Wang, J.; Mao, S.; Liang, M.; Zhang, W.; Chen, F.; Huang, K.; Wu, Q. Preharvest Methyl Jasmonate Treatment Increased Glucosinolate Biosynthesis, Sulforaphane Accumulation, and Antioxidant Activity of Broccoli. Antioxidants 2022, 11, 1298. [Google Scholar] [CrossRef] [PubMed]
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Figure 1. Structures of desulfoglucosinolates found in Broccoli. Aliphatic dGSLs: glucoiberin (GIB), progoitrin (PRO), sinigrin (SIN), glucoraphanin (GRA), glucoalyssin (GAL), glucoibervirinn (GIV), and glucoerucin (GER). Indole dGSLs: glucobrassicin (GBS), 4-methoxyglucobrassicin (4MGBS), neoglucobrassicin (NGBS), 4-hydroxyglucobrassicin (4HGBS), and 1-hydroxyglucobrassicin (1HGBS). Aromatic dGSLs: glucotropaeolin (GTP), gluconasturtiin (GNT).
Figure 1. Structures of desulfoglucosinolates found in Broccoli. Aliphatic dGSLs: glucoiberin (GIB), progoitrin (PRO), sinigrin (SIN), glucoraphanin (GRA), glucoalyssin (GAL), glucoibervirinn (GIV), and glucoerucin (GER). Indole dGSLs: glucobrassicin (GBS), 4-methoxyglucobrassicin (4MGBS), neoglucobrassicin (NGBS), 4-hydroxyglucobrassicin (4HGBS), and 1-hydroxyglucobrassicin (1HGBS). Aromatic dGSLs: glucotropaeolin (GTP), gluconasturtiin (GNT).
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Figure 2. Concentration and diversity of GSLs in broccoli florets across 191 genotypes. (A) The average percentage of 13 GSLs distributed in all 191 materials. (B) Diverse distribution of GSLs in the 191 broccoli samples. (C) Statistical content of the total GSLs, GRA, and GBS in 191 broccoli samples.
Figure 2. Concentration and diversity of GSLs in broccoli florets across 191 genotypes. (A) The average percentage of 13 GSLs distributed in all 191 materials. (B) Diverse distribution of GSLs in the 191 broccoli samples. (C) Statistical content of the total GSLs, GRA, and GBS in 191 broccoli samples.
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Figure 3. Concentration of GSLs in different organs and developmental stages in broccoli. (A) Relationship between K-value and SEE (sum of the squared errors). (B) K-means analysis of total glucosinolates in 191 materials. All materials were divided into “High” (blue), “middle” (red), and “low” (green) groups according to their GSL contents. The detailed k-mean cluster information is listed in Table S3. (C) The contents of GSLs in different organs and at different developmental stages of 18 broccoli genotypes, including roots (R), stalks (S), leaves (L), rosette-stage rosette leaves (Y), squaring-stage rosette leaves (X), floret-stage rosette leaves (H), and florets (Q). The X-axis represents the number of the broccoli.
Figure 3. Concentration of GSLs in different organs and developmental stages in broccoli. (A) Relationship between K-value and SEE (sum of the squared errors). (B) K-means analysis of total glucosinolates in 191 materials. All materials were divided into “High” (blue), “middle” (red), and “low” (green) groups according to their GSL contents. The detailed k-mean cluster information is listed in Table S3. (C) The contents of GSLs in different organs and at different developmental stages of 18 broccoli genotypes, including roots (R), stalks (S), leaves (L), rosette-stage rosette leaves (Y), squaring-stage rosette leaves (X), floret-stage rosette leaves (H), and florets (Q). The X-axis represents the number of the broccoli.
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Figure 4. Diversity and content analyses of GSLs in broccoli from three clusters (High, Middle, and Low). The X-axis represents the species of GSLs. Q represents florets, H represents floret-stage rosette leaves, Y represents rosette-stage rosette leaves, X represents squaring-stage rosette leaves, L represents leaves, S represents stalks, and R represents roots.
Figure 4. Diversity and content analyses of GSLs in broccoli from three clusters (High, Middle, and Low). The X-axis represents the species of GSLs. Q represents florets, H represents floret-stage rosette leaves, Y represents rosette-stage rosette leaves, X represents squaring-stage rosette leaves, L represents leaves, S represents stalks, and R represents roots.
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Table 1. Identification of GSLs in broccoli.
Table 1. Identification of GSLs in broccoli.
Retention Time (min)Typical NameType of Side ChainSubcategoryFormula (Desulfo)Diagnostic Ions (m/z)Precursor MassFound at MassMass Error (ppm)
1.13Glucoiberin(Rs)-3-(Methylsulfinyl)propylAliphaticC11H21NO7S2182.0299, 118.0316344.083344.08330.3
1.41Progoitrin(2R)-2-Hydroxybut-3-enylAliphaticC11H19NO7S148.0416, 130.0310, 85.0138310.095310.09580.9
1.68SinigrinProp-2-enylAliphaticC10H17NO6S145.0482, 118.0310, 85.0269280.085280.0849−0.2
1.81Glucoraphanin(Rs)-4-(Methylsulfiny)lbutylAliphaticC12H23NO7S2196.0445, 132.0461, 87.0252358.099358.09900.4
3.00Glucoalyssin(Rs)-5-(Methylsulfinyl)pentylAliphaticC13H25NO7S2210.0622, 142.0688372.115372.11480.8
3.534-Hydroxyglucobrassicin4-Hydroxyindol-3-ylmethylIndoleC16H20N2O7S223.0531, 190.0325, 146.0592385.106385.10660.4
4.14Glucoibervirin3-(Methylthio)propylAliphaticC11H21NO6S2166.0340, 118.0303, 85.0273328.088328.08850.7
5.241-Hydroxyglucobrassicin1-Hydroxyindolyl-3-methylIndoleC16H20N2O7S223.0539, 190.0325, 146.0601385.106385.10640.1
5.28GlucotropaeolinBenzylAromaticC14H19NO6S168.0469, 134.0595, 91.0527330.101330.10070.3
5.64Glucoerucin4-(Methylthio)butylAliphaticC12H23NO6S2180.0495, 162.0398, 132.0461342.104342.1039−0.3
6.05GlucobrassicinIndol-3-ylmethylIndoleC16H20N2O6S207.0568, 174.0360, 130.0631369.111369.1112−0.8
7.28GluconasturtiinPhenethylAromaticC15H21NO6S182.0632, 130.0639, 105.0688344.116344.11660.9
7.774-Methoxyglucobrassicin4-Methoxyindol-3-ylmethylIndoleC17H22N2O7S237.0691, 160.0747399.122399.1220−0.1
8.54NeoglucobrassicinN-Methoxyindol-3-ylmethylIndoleC17H22N2O7S237.0677, 206.0487, 130.0625399.122399.12230.7
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Yan, M.; Song, C.; Su, S.; Li, J.; Hu, Z.; Lin, S.; Zou, H.; Tang, Z.; Yan, X. Quantification and Diversity Analyses of Glucosinolates in 191 Broccoli Genotypes Highlight Valuable Genetic Resources for Molecular Breeding. Agronomy 2023, 13, 2928. https://doi.org/10.3390/agronomy13122928

AMA Style

Yan M, Song C, Su S, Li J, Hu Z, Lin S, Zou H, Tang Z, Yan X. Quantification and Diversity Analyses of Glucosinolates in 191 Broccoli Genotypes Highlight Valuable Genetic Resources for Molecular Breeding. Agronomy. 2023; 13(12):2928. https://doi.org/10.3390/agronomy13122928

Chicago/Turabian Style

Yan, Meijia, Chenxue Song, Shiwen Su, Junliang Li, Zhiwei Hu, Sue Lin, Huixi Zou, Zheng Tang, and Xiufeng Yan. 2023. "Quantification and Diversity Analyses of Glucosinolates in 191 Broccoli Genotypes Highlight Valuable Genetic Resources for Molecular Breeding" Agronomy 13, no. 12: 2928. https://doi.org/10.3390/agronomy13122928

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