Data from: Constitutive metabolomic profile of a transgressive segregant of rice with superior salinity tolerance potentials due to unique morphological features and well-modulated growth
Data files
Feb 27, 2026 version files 14.79 MB
-
Lipidomics_Negative_Ion_Mode_FL510_normalized.csv
644.70 KB
-
Lipidomics_negative_ion_mode_raw_data.csv
1.18 MB
-
Lipidomics_positive_Ion_Mode_FL510_normalized.csv
1.01 MB
-
Lipidomics_positive_ion_mode_raw_data.csv
2.49 MB
-
Metabolomics_Negative_Ion_Mode_FL510_normalized.csv
1.18 MB
-
Metabolomics_Negative_Ion_Mode_FL510_raw_data.csv
2.88 MB
-
Metabolomics_Positive_Ion_Mode_FL510_normalized.csv
1.58 MB
-
Metabolomics_Positive_Ion_Mode_FL510_raw_data.csv
3.83 MB
-
README.md
2.58 KB
Abstract
Understanding the nature of non-parental phenotypes created by transgressive segregation is important in creating novel genetic recombinants that can withstand different environmental conditions for crop production. FL510, a transgressive salinity-tolerant rice genotype from a cross between IR29 (xian/indica; salt-sensitive) and Pokkali (indica/aus; salt-tolerant), has tolerance mechanisms active under control conditions and improves survival upon the onset of salinity. This study compares normal-state metabolomes and lipidomes of FL510 with those of its parents. Principal component analysis (PCA) of the identified analytes showed clear and expected similarity between FL510 and Pokkali, while partial least squares discriminant analysis (PLS-DA) emphasized overlaps between the metabolic profiles of IR29 and FL510. The analysis identified metabolites with inherited patterns of abundance from either parent in FL510 and those with unique, non-parental abundances, and these were supported by differential expression of key pathway-related genes identified through transcriptome analysis. Strigolactone precursor production was identified as a key feature in FL510, which may help explain its unique architecture that is beneficial for osmotic stress. We also identified a divergence between productivity under ideal environments, leading to free radical production versus tempered production that offers better survival under marginal growing conditions. FL510 showed an inheritance of hormone and amino acid abundances from Pokkali, which further explains some of its architectural and previously studied stress-response features. Meanwhile, the similarity of FL510 with IR29 in terms of flavonoid indicates an inheritance of productivity and is consistent with previous reports of induction for these molecules under stress, rather than being active under control conditions.
Dataset DOI: 10.5061/dryad.3ffbg79x5
Description of the data and file structure
Samples: Leaf blades from one-month-old plants
Genotypes: FL510 (transgressive salt tolerant recombinant inbred line); IR29 (salt sensitive parent); Pokkali (salt tolerant parent)
Dataset: metabolites identified through shotgun approach. Four total datasets are included, as metabolites were detected from the metabolome (aqueous phase extract) and lipidome (organic phase extract) at both positive and negative ion modes. Each file contains a tab for raw values and a tab for values normalized with a set internal standard listed on row 1. QC sample peaks are also included. These samples were combined extracts from the three genotypes listed above and were used to ensure run quality for the experimental samples run on the machine. Any empty cells represent data not available.
Files and variables
Files in this set are as listed:
- Lipidomics_Negative_Ion_Mode_FL510_normalized.csv
- Lipidomics_negative_ion_mode_raw_data.csv
- Lipidomics_positive_Ion_Mode_FL510_normalized.csv
- Lipidomics_positive_ion_mode_raw_data.csv
- Metabolomics_Negative_Ion_Mode_FL510_normalized.csv
- Metabolomics_Negative_Ion_Mode_FL510_raw_data.csv
- Metabolomics_Positive_Ion_Mode_FL510_normalized.csv
- Metabolomics_Positive_Ion_Mode_FL510_raw_data.csv
3. NORMALIZED files comprise of mass spectrometry values standardized using a preset internal standard metabolite added to the sample. The specific metabolite used is listed at the top of each NORMALIZED data file.
4. RAW files comprise mass spectrometry values without standardization with the internal standard metabolite.
5. Key variables in each table are:
a. Name - name of the metabolite identified
b. Formula - chemical formula of metabolite identified
c. Annot. DeltaMass [ppm] - mass of identified metabolite as detected
d. Calc. MW - theoretical mass of the identified metabolite
e. m/z - mass to charge ratio
f. RT[min] - retention time
g. Area [Sample name+Rep] - quantity of sample
h. Ratio and log2 fold - quantities relative from one sample to another, as a ratio or as log2 fold ratio
i. P-value - statistical significance of the ratio
j. Adj. P-value - P-value with Bonferroni correction
Peak ratings are quality control measures used by the machine to validate results (ThermoFisher)
