Abstract
Metabolic regulation is important during seed germination for the establishment of seedling. The germination strategy of mangosteen (Garcinia mangostana L.) seed is thought to be unique due to its recalcitrant characteristic (sensitive to coldness and drying). To investigate the metabolic changes during seed germination, we performed metabolomics analysis on germinating mangosteen seed sown after zero, one, three, five, seven and nine days. Sampled mangosteen seeds were subjected to methanol extraction prior analysis using Liquid Chromatography-Time of Flight-Mass Spectrometry (LC-TOF-MS). MS data were further analyzed using ProfileAnalysis (version 2.1). This is one of the earliest reports in metabolite identification and profiling of mangosteen seed at different germination stages. This data article refers to the article entitled “Metabolite profiling of mangosteen seed germination highlights metabolic changes related to carbon utilization and seed protection” (Mazlan et al., 2019) [1].
Keywords: Garcinia mangostana L., Recalcitrant seed, Germination, LC-MS, Metabolomics
Specifications table
| Subject area | Biology |
| More specific subject area | Metabolomics |
| Type of data | Table |
| How data was acquired | Dionex liquid chromatography platform (Ultimate 3000 UHPLC+, Thermo Scientific) coupled with a MicroTOF-QIII (Bruker, Germany) MS system with electrospray ionization (ESI) in positive mode was used to obtain mass spectrometry data. |
| Data format | Analyzed data in XLSX format. |
| Experimental factors | Mangosteen seed at different germination stages (seed sown after zero, one, three, five, seven and nine days) extracted using methanol solvent. |
| Experimental features | LC-TOF-MS was used to analyze methanol extract of seed samples and acquired raw data were processed using ProfileAnalysis (version 2.1) and MS Excel 2016 for tabulation. |
| Data source location | UKM Bangi, Malaysia (2.922662 °N, 101.786690 °E) |
| Data accessibility | Data is within this article |
| Related research article | O. Mazlan, W.M. Aizat, N. S. A. Zuddin, S.N. Baharum, N.M. Noor, Metabolite profiling of mangosteen seed germination highlights metabolic changes related to carbon utilization and seed protection [1] |
Value of the data
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The LC-MS platform enables a comprehensive metabolite profiling for mangosteen seed germination at different stages (zero, one, three, five, seven and nine days after sowing).
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This permits the identification of metabolites or potential biomarkers during the germination of mangosteen seed which is known to be recalcitrant (sensitive to cold and dry conditions).
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Understanding metabolic expression and regulation in mangosteen seed germination may provide valuable insights towards developing better preservation strategy for this recalcitrant seed.
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Furthermore, this data can be analyzed in conjunction with the transcriptome data [2] for an integrated examination of metabolic pathways of recalcitrant seed germination in mangosteen.
1. Data
Data presented in this manuscript are related to the earlier report entitled “Metabolite profiling of mangosteen seed germination highlights metabolic changes related to carbon utilization and seed protection” [1]. It consists of retention time (RT) to molecular ions’ mass over charge ratio (m/z) listed as table in XLSX format. To create the table, raw LC-MS data of six mangosteen seed germination stages (zero, one, three, five, seven and nine days after sowing) with three biological replicates per stage were analyzed using ProfileAnalysis and tabulated using MS Excel as per [3].
2. Experimental design, materials and methods
2.1. Plant materials
Mature fruits were picked from mangosteen tree plots at Universiti Kebangsaan Malaysia, Bangi, Malaysia. Preparation for seed de-pulping, cleaning, planting and selecting seeds for extraction followed Mazlan et al. [1].
2.2. Metabolite extraction
Methanol extraction of seed employed methods detailed by Roessner et al. [4] with modifications [1], [5].
2.3. Liquid Chromatography-Mass Spectrometry (LC-MS) protocol
Dried samples were resolubilized in methanol. This study adheres to Glauser et al. [6] method with adjustments as detailed in [1] and [5]. Separation of compound utilizing liquid chromatography system (Ultimate 3000 UHPLC+, Thermo Scientific, USA) outfitted with a C18 column was performed as per Mamat et al. [7].
2.4. Mass spectrometry data treatment and handling
MS raw data (.d format) were imported into ProfileAnalysis 2.1 (Bruker, Germany) for bucketing using Find Molecular Features settings as per Mamat et al. [7] with smoothing width: 2 [3]. Bucket generation was set as follows: advanced bucketing feature calculated using parameters from time alignment, time range 2.00 minutes until 30.00 minutes, mass range 50 m/z to 1000 m/z, normalization is by sum of bucket values in analysis. Then, the data were exported to Microsoft Excel 2016 for tabulation.
Acknowledgements
The project was supported by UKM Research University Grants (DLP-2013-011 and GUP-2015-051). OM was sponsored by Skim Zamalah Universiti Kebangsaan Malaysia.
Footnotes
Transparency document associated with this article can be found in the online version at https://doi.org/10.1016/j.dib.2018.11.072.
Supplementary data associated with this article can be found in the online version at https://doi.org/10.1016/j.dib.2018.11.072.
Contributor Information
Wan Mohd Aizat, Email: wma@ukm.edu.my.
Normah Mohd Noor, Email: normah@ukm.edu.my.
Transparency document. Supplementary material
Transparency document
.
Appendix A. Supplementary material
Supplementary material
.
References
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Associated Data
This section collects any data citations, data availability statements, or supplementary materials included in this article.
Supplementary Materials
Transparency document
Supplementary material