Seed Oil Biosynthesis & Crop Quality Lipidomics

Seed Oil Biosynthesis and Crop Oil Quality Lipidomics Service

Creative Proteomics provides high-resolution lipidomics to decode the molecular mechanisms of seed oil biosynthesis and storage lipid accumulation. We empower agricultural researchers and plant breeders to transition from bulk fat measurements to precise metabolic readouts, delivering absolute quantification of triacylglycerols, structural lipids, and free fatty acids.

Key capabilities

  • Seed Lipid Accumulation Profiling: Map the dynamic conversion of carbohydrates into storage triacylglycerols (TAGs) and diacylglycerols (DAGs) across precise developmental grain-filling time-courses.
  • Fatty Acid Composition Optimization: Quantify specific polyunsaturated fatty acids (PUFAs) and sterols to guide nutritional and industrial crop trait engineering.
  • Acyltransferase Pathway Validation: Track lipid fluxes and regioisomer distributions in gene-edited or mutant breeding lines to validate targeted pathway interventions.
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  • Technical Advantages
  • Case Studies
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Situational Solution Matrix for Crop Oil Quality Improvement

Seed oil projects rarely begin with a platform decision. They usually begin with a real research question. The most useful workflow is staged, combining broad discovery with focused validation.

Developmental Stage Mapping for Seed Filling and Oil Accumulation

Situation

A lab samples developing seeds, embryos, or cotyledons across multiple time points and needs to determine when storage lipids increase most strongly and whether the key transition occurs in phosphatidic acid, diacylglycerol, phosphatidylcholine-associated remodeling, or terminal TAG assembly.

Goal

Build a stage-resolved seed oil biosynthesis analysis workflow that defines the most informative harvest window for pathway analysis, RNA-seq integration, and functional validation.

Recommended path

Discovery → Validation

Recommended services
Plant Seeds Untargeted Lipidomics Service, Plant Lipidomics Analysis, Targeted Lipidomics Service, Glycerolipids Analysis Service, Glycerophospholipids Analysis Service, Fatty Acid Profiling and Quantification Service, Fatty Acid Methyl Ester Analysis Service
What you will get

A developmental lipid map showing how TAG, DAG, PA, PC, PE, and major fatty acid pools change across seed filling and maturation, together with a clearer basis for choosing the stage most suitable for transcriptomics, gene-expression validation, or targeted follow-up.

High-Oil versus Low-Oil Cultivar Comparison

Situation

A breeding or translational crop team sees clear oil-content differences between cultivars, but bulk oil data does not explain whether the superior line is better because of storage-lipid accumulation, precursor routing, or a more favorable fatty acid profile.

Goal

Separate oil quantity from oil quality and identify the lipid classes and molecular signatures most useful for line ranking and marker nomination.

Recommended path

Discovery → Validation

Recommended services
Plant Seeds Untargeted Lipidomics Service, Targeted Lipidomics Service, Glycerolipids Analysis Service, Glycerophospholipids Analysis Service, Free Fatty Acids Analysis Service, Fatty Acid Profiling and Quantification Service, Fatty Acid Methyl Ester Analysis Service
What you will get

A comparison-ready lipid signature that distinguishes storage-lipid abundance from composition-driven oil quality traits and helps determine whether a cultivar should be advanced for higher oil yield, improved fatty acid quality, or both.

Oleic Acid Improvement, Linoleic Acid Control, and Oil Quality Optimization

Situation

An oilseed program is focused on oleic acid enrichment, linoleic acid control, oxidative stability, nutritional positioning, or industrial oil characteristics and needs more than a simple percentage readout.

Goal

Generate fatty acid composition analysis in seeds while retaining enough lipid context to determine whether the observed trait is broad, class-specific, developmentally regulated, or linked to free fatty acid turnover.

Recommended path

Validation → Optional Discovery

Recommended services
Fatty Acid Profiling and Quantification Service, Fatty Acid Methyl Ester Analysis Service, Free Fatty Acids Analysis Service, Targeted Lipidomics Service, Glycerolipids Analysis Service, Glycerophospholipids Analysis Service
What you will get

A composition-focused dataset that quantifies major and minor fatty acid species, class-level lipid context, and pathway-relevant shifts that help explain whether the trait reflects stable oil quality improvement or a narrower metabolic effect.

TAG Pathway Validation after Gene Editing or Transgene Work

Situation

A team edits or overexpresses DGAT, PDAT, FAD2, SAD, WRI1, GPAT, LPAT, or related regulators and needs biochemical evidence that seed lipid metabolism changed in the expected direction.

Goal

Determine whether the perturbation affects precursor fatty acid pools, acyl editing within phospholipids, DAG availability, terminal TAG deposition, or multiple points in the pathway.

Recommended path

Discovery → Validation → Deep Insight

Recommended services
Plant Seeds Untargeted Lipidomics Service, Untargeted Lipidomics Profiling Service, Targeted Lipidomics Service, Glycerolipids Analysis Service, Glycerophospholipids Analysis Service, Free Fatty Acids Analysis Service, Fatty Acid Profiling and Quantification Service
What you will get

A pathway-facing lipid readout that links genotype to phenotype with more mechanistic detail than bulk oil assays alone, supporting publication, internal R&D decisions, and the next round of engineering.

Breeding Population Screening and Marker Nomination

Situation

A breeding program is moving from a few reference lines to a larger comparison set and needs reproducible lipid or fatty acid markers that can support selection without requiring full discovery profiling on every sample.

Goal

Translate discovery-stage signals into a validation-ready panel for broader screening and line classification.

Recommended path

Discovery subset → Validation panel

Recommended services
Plant Seeds Untargeted Lipidomics Service, Targeted Lipidomics Service, Glycerolipids Analysis Service, Free Fatty Acids Analysis Service, Fatty Acid Profiling and Quantification Service, Fatty Acid Methyl Ester Analysis Service
What you will get

A practical marker strategy that uses representative materials for broader discovery and then moves the strongest lipid or fatty acid signals into higher-throughput validation across larger populations.

Spatial Lipid Heterogeneity in Seed Tissues

Situation

Whole-seed extracts are informative but may mask tissue-level differences in embryo, cotyledon, endosperm, or peripheral tissues. The project requires spatial context to explain ambiguous bulk lipidomics results or localized oil deposition.

Goal

Add tissue-resolved information to seed oil biosynthesis analysis and directly assess where key lipid species accumulate.

Recommended path

Discovery → Deep Insight

Recommended services
Plant Seeds Untargeted Lipidomics Service, Targeted Lipidomics Service, Glycerolipids Analysis Service, Glycerophospholipids Analysis Service, MALDI-Imaging Lipidomics Services
What you will get

High-resolution spatial lipid information that complements abundance profiling and helps explain tissue-specific metabolism, seed structure effects, and localized enrichment of storage or membrane lipids.

Technical Advantages in Plant Lipidomics

Creative Proteomics utilizes flagship-tier mass spectrometry platforms, including the Sciex QTRAP® 6500+ and Thermo Orbitrap Exploris™ 480, overcoming the intense matrix interference inherent to high-fat seed samples.

Advanced Regioisomer Resolution

The structural arrangement of fatty acids on the glycerol backbone heavily influences oil properties. We utilize optimized, ultra-long UHPLC gradients to achieve baseline separation of critical TAG isomers, providing the precision needed for advanced crop oil quality lipidomics.

Strict Plant Ex Vivo Lipolysis Prevention

Endogenous lipases in plant seeds activate rapidly upon harvest. We enforce sub-second liquid nitrogen quenching and utilize biphasic extraction systems designed specifically for plant tissues. This halts lipase activity immediately, ensuring that quantified FFAs and DAGs accurately represent in vivo metabolism.

Absolute Quantification via Isotope Dilution

Establishing clear phenotypic markers for breeding requires undeniable quantitative accuracy. We routinely spike >50 stable isotope-labeled (Deuterated/13C) internal standards into our targeted workflows. This fundamentally eliminates matrix suppression effects, controlling the Coefficient of Variation (CV) to < 15% across large-scale crop screening cohorts.

Selected Case Studies

Publication: Integrated lipidomic and transcriptomic analyses reveal the mechanism of lipid biosynthesis and accumulation during seed development in sesame. Frontiers in Plant Science, 2023. DOI: 10.3389/fpls.2023.1211040
Study Profile: Developmental Lipidomics in Sesame Seeds.

Developmental Lipidomics in Sesame Seeds

Why this matters to customers

This study closely matches projects that need to identify the decisive developmental window for oil accumulation and connect lipid changes to candidate biosynthetic genes. It is particularly useful for teams planning stage-based sampling, multi-omics integration, or pathway validation.

What the study shows

Sesame seeds sampled at 9, 21, and 33 days after flowering were analyzed by LC-MS lipidomics, GC-MS fatty acid analysis, and transcriptomics. The study reported 481 lipids and showed that most fatty acids and storage-related lipids increased most strongly at the middle and late stages, with accompanying expression changes in genes including ACCase, FAD2, DGAT, GPAT, LPAT, PAP, and WRI1-like regulators.

Heatmap showing stage-specific lipid changes in developing sesame seeds for seed oil biosynthesis and crop oil quality lipidomics.
Heatmaps of content changes of lipids in developing seed.
Publication: Visualizing the Distribution of Lipids in Peanut Seeds by MALDI Mass Spectrometric Imaging. Foods, 2022. DOI: 10.3390/foods11233888
Study Profile: Spatial Lipid Heterogeneity in Peanut Seeds.

Spatial Lipid Heterogeneity in Peanut Seeds

Why this matters to customers

This study is relevant when whole-seed extraction does not fully explain the phenotype and the project depends on understanding where lipids accumulate inside the seed rather than only how much is present overall.

What the study shows

Using MALDI-MSI on seed sections from three peanut cultivars, the authors identified 103 metabolites including 34 lipids and showed that PCs, LPCs, and PE were enriched mainly in the inner seed region, while TG and PA species showed strongly heterogeneous spatial patterns. For customers, this provides a concrete example of when imaging-based lipidomics adds value to bulk profiling.

MALDI imaging map of peanut seed lipids showing tissue-specific distribution for seed oil biosynthesis and crop oil quality lipidomics.
MALDI-MSI of representative glycerolipids in different peanut seeds.
Publication: Transcriptome Analysis Reveals Key Genes Involved in Fatty Acid and Triacylglycerol Accumulation in Developing Sunflower Seeds. Genes, 2025. DOI: 10.3390/genes16040393
Study Profile: Sunflower Fatty Acid Regulation and Oil Quality Traits.

Sunflower Fatty Acid Regulation and Oil Quality Traits

Why this matters to customers

This study fits projects focused on composition-driven oil quality, especially when the goal is to connect fatty acid data with developmental timing and genes controlling desaturation or TAG accumulation.

What the study shows

The study profiled developing sunflower embryos across five stages using fatty acid analysis and RNA-seq and linked mature oil composition, dominated by unsaturated fatty acids, to desaturase- and TAG-related genes including FAD2-1, SAD, FATA, PDAT2, and DGAT2. It provides a relevant model for customers working on oleic and linoleic balance, breeding selection, and composition-linked quality optimization.

Heatmap of sunflower desaturase genes associated with seed oil quality traits in crop oil quality lipidomics.
Heat map showing the expression levels of desaturase genes.

Frequently Asked Questions

How does lipidomics resolve complex TAG regioisomers in seed oil analysis?
The position of fatty acids on the glycerol backbone (regioisomers) dictates oil quality. We resolve these highly similar structures utilizing optimized, ultra-long UHPLC gradients combined with high-resolution MS/MS fragmentation. The specific fragmentation patterns allow us to definitively identify the sn-1, sn-2, and sn-3 positions of the fatty acyl chains, providing critical insights for crop oil quality lipidomics.
What is the minimum sample weight required for seed lipidomic profiling?
Due to the extreme sensitivity of our mass spectrometry platforms, we require very little starting material. Typically, 50-100 milligrams of dried or fresh seed tissue is sufficient to provide comprehensive, quantitative profiling of both highly abundant TAGs and trace-level signaling lipids.
How do your protocols prevent the ex vivo lipolysis of TAGs into FFAs during extraction?
Plant seeds contain highly active lipases. We prevent ex vivo lipolysis by enforcing strict liquid nitrogen quenching immediately upon sample collection. During the extraction phase, we utilize specialized biphasic solvent mixtures and maintain cryogenic temperatures, immediately denaturing lipases and ensuring that quantified FFA levels reflect true in vivo biology.
Can your platform simultaneously quantify storage lipids (TAGs) and membrane structural lipids?
Yes. Our analytical workflows are designed to capture a broad dynamic range. Through advanced data-dependent acquisition (DDA) methods and targeted MRM scanning, we can simultaneously quantify the highly abundant storage TAGs alongside lower-abundance membrane structural lipids like phosphatidylcholines (PC) and phosphatidylethanolamines (PE).
Are these lipidomics workflows applicable to non-model oilseed crops?
Absolutely. While much research focuses on Arabidopsis or Soybean, our LC-MS/MS platforms and extensive lipid databases are species-agnostic. We regularly process samples from diverse, non-model oilseeds such as Camelina, Pennycress, Jatropha, and various specialty nuts or seeds used for industrial or nutritional applications.
How does spatial mass spectrometry (MALDI-MSI) enhance seed biology research?
Traditional lipidomics requires homogenizing the entire seed, losing spatial context. MALDI-Imaging Lipidomics allows us to analyze intact seed cross-sections. This generates high-resolution spatial maps showing exactly where specific lipids accumulate—for instance, differentiating lipid storage in the endosperm versus the embryo—providing crucial insights for targeted developmental breeding.
Do you provide absolute quantification for specific polyunsaturated fatty acids (PUFAs)?
Yes. For nutritional crop improvement, we offer targeted fatty acid profiling that provides absolute molar quantification of essential PUFAs, including specific Omega-3 and Omega-6 species. This data is essential for verifying the success of breeding programs aimed at improving the health profile of edible seed oils.
Can your bioinformatics team integrate seed lipidomics data with transcriptomics?
Yes. Seed lipid accumulation is tightly regulated at the gene expression level. Our bioinformatics services include multi-omics integration, where we map quantitative lipidomic shifts directly against transcriptomic datasets (like RNA-Seq). This highlights specific acyltransferases or desaturases driving the observed lipid phenotype, accelerating marker-assisted breeding.

References

  1. Integrated lipidomic and transcriptomic analyses reveal the mechanism of lipid biosynthesis and accumulation during seed development in sesame. Frontiers in Plant Science, 2023. https://doi.org/10.3389/fpls.2023.1211040
  2. Visualizing the Distribution of Lipids in Peanut Seeds by MALDI Mass Spectrometric Imaging. Foods, 2022. https://doi.org/10.3390/foods11233888
  3. Transcriptome Analysis Reveals Key Genes Involved in Fatty Acid and Triacylglycerol Accumulation in Developing Sunflower Seeds. Genes, 2025. https://doi.org/10.3390/genes16040393
  4. Proteolytic activation of fatty acid synthase signals pan-stress resolution. Nature Metabolism, 2023. https://doi.org/10.1038/s42255-023-00939-z
  5. WI12 Rhg1 interacts with DELLAs and mediates soybean cyst nematode resistance through hormone pathways. Plant Biotechnology Journal, 2022. https://doi.org/10.1111/pbi.13709
* Our services can only be used for research purposes and Not for clinical use.

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