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Data from: Decreases in polyunsaturated fatty acid content improve heat stress tolerance during flowering and silicle development in pennycress (Thlaspi arvense L.)

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Apr 28, 2026 version files 229 KB

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Abstract

This dataset contains phenotypic, biochemical, and reproductive measurements from wild-type pennycress (Thlaspi arvense L.) and multiple CRISPR/Cas9-edited lines engineered for increased oleic acid content via mutations in FATTY ACID DESATURASE 2 (FAD2), REDUCED OLEATE DESATURATION1 (ROD1), and FATTY ACID ELONGASE1 (FAE1). The data are organized into 20 tables (Tables S1–S20) comprising quantitative measurements across seed composition, stress physiology, reproductive performance, and agronomic traits under control and elevated temperature conditions.

The dataset includes: (i) fatty acid composition profiles of seeds (Table S1); (ii) pollen viability measurements across a range of temperatures (Tables S2–S3); (iii) seed weight and yield components (Tables S4–S5, S16–S18); (iv) biochemical indicators of stress, including thiobarbituric acid reactive substances (TBARS; Tables S6–S9), proline accumulation (Tables S10–S13), and peroxide content (Tables S14–S15) in leaves and silicles; (v) reproductive success under heat stress, including controlled crossing experiments (Table S19); and (vi) germination time-course data (Table S20). Measurements are reported as quantitative values (e.g., percent composition, viability percentages, concentration units, biomass, and yield metrics) with replication across genotypes and environmental treatments (control vs. heat stress at 34 °C/28 °C).

These data enable investigation of the relationships among fatty acid desaturation, membrane composition, oxidative stress, pollen thermotolerance, and yield stability. The dataset is structured to facilitate reuse in meta-analyses, crop modeling, and comparative studies of lipid metabolism and abiotic stress tolerance in oilseed crops. In particular, the parallel measurements across multiple independent gene-edited lines and environmental conditions support analyses of genotype-by-environment interactions and trait correlations spanning molecular to whole-plant scales.

All data are provided in tabular format suitable for statistical analysis and integration with other omics or phenotypic datasets. There are no human or animal subjects involved, and no ethical restrictions apply. The dataset is released under the terms specified by the repository, permitting reuse with appropriate attribution.