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Tissue-specific differences in metabolites and transcripts contribute to the heterogeneity of ricinoleic acid accumulation in Ricinus communis L. (castor) seeds

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Abstract

Introduction

Castor (Ricinus communis L.) seeds are valued for their production of oils which can comprise up to 90% hydroxy-fatty acids (ricinoleic acid). Castor oil contains mono-, di- and tri- ricinoleic acid containing triacylglycerols (TAGs). Although the enzymatic synthesis of ricinoleic acid is well described, the differential compartmentalization of these TAG molecular species has remained undefined.

Objectives

To examine the distribution of hydroxy fatty acid accumulation within the endosperm and embryo tissues of castor seeds.

Methods

Matrix assisted laser desorption/ionization mass spectrometry imaging was used to map the distribution of triacylglycerols in tissue sections of castor seeds. In addition, the endosperm and embryo (cotyledons and embryonic axis) tissues were dissected and extracted for quantitative lipidomics analysis and Illumina-based RNA deep sequencing.

Results

This study revealed an unexpected heterogeneous tissue distribution of mono-, di- and tri- hydroxy-triacylglycerols in the embryo and endosperm tissues of castor seeds. Pathway analysis based on transcript abundance suggested that distinct embryo- and endosperm-specific mechanisms may exist for the shuttling of ricinoleic acid away from phosphatidylcholine (PC) and into hydroxy TAG production. The embryo-biased mechanism appears to favor removal of ricinoleic acid from PC through phophatidylcholine: diacylglycerol acyltransferase while the endosperm pathway appears to remove ricinoleic acid from the PC pool by preferences of phospholipase A (PLA2α) and/or phosphatidylcholine: diacylglycerol cholinephosphotransferase.

Conclusions

Collectively, a combination of lipidomics and transcriptomics analyses revealed previously undefined spatial aspects of hydroxy fatty acid metabolism in castor seeds. These studies underscore a need for tissue-specific studies as a means to better understand the regulation of triacylglycerol accumulation in oilseeds.

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Data accessibility

The RNA sequences collected for this manuscript have been deposited in the Gene Expression Omnibus (GEO) repository at the National Center for Biotechnology Information (NCBI) under the accession GSE119624 where it is freely accessible without restriction.

References

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Acknowledgements

This work was supported in part by the U.S Department of Energy, Office of Science, BES-Physical Biosciences program (DE-SC0016536 to KDC; DE-SC0012704 to JS), by the National Science Foundation (Grant DBI 1117680, X-H Y, JS), and by a UNT-dissertation summer stipend to Drew Sturtevant. The UNT Orbitrap XL mass spectrometer and cryostat facilities were supported in part by a grant from the Hoblitzelle Foundation. The transcriptomics data were collected and reads processed for analysis by the UNT- BioDiscovery Genomics Core Facility.

Funding

This research was funded in part by research contracts from the United States Department of Energy, Office of Science, Basic Energy Sciences (DE-SC0016536 to KDC; DE-SC0012704 to JS), a grant award from the National Science Foundation (DBI 1117680, X-H Y, JS), and by a UNT-dissertation summer stipend to Drew Sturtevant.

Author information

Authors and Affiliations

Authors

Contributions

The MALDI-MSI imaging and transcriptome sequencing and analysis were completed by DS. TR completed the MALDI-MS and ESI-MS analysis of lipid extracts. Bioinformatics support was contributed by DB, supervised by RA. XY grew and collected plant material and performed the real-time, quantitative-PCR (RT-qPCR) analyses on developing seeds. KC and JS supervised experiments at UNT and Brookhaven National Laboratory, respectively. DS, TR, and KC drafted the manuscript. All authors contributed to editing of the manuscript.

Corresponding author

Correspondence to Kent D. Chapman.

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Conflict of interest

All authors declare that they have no conflicts of interest.

Research involving human and animal participants

This article does not contain any studies with human participants or animals performed by any of the authors.

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Electronic supplementary material

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11306_2018_1464_MOESM1_ESM.png

Supplementary material 1 ESI-MS spectrum of extracted castor oil and overlapping dehydrated m/z peaks. Mass spectrum of directly infused extracted castor oil from m/z 875 to 960 indicating peaks of protonated dehydrated hydroxy-TAG and their respective corresponding ammoniated parent ions. (PNG 112 KB)

11306_2018_1464_MOESM2_ESM.png

Supplementary material 2 Principal components analysis (PCA) of variant genes between castor endosperm and embryo tissues. PCA of endosperm (blue) and embryo (red) tissues at first (47.82% variance) and second (14.08% variance) principal components. (PNG 115 KB)

11306_2018_1464_MOESM3_ESM.png

Supplementary material 3 Absolute gene transcript levels from select genes of Kennedy and Lands pathways. Box and whisker plots of normalized counts for transcripts of genes in the Kennedy or Lands pathways significantly greater (A) or lower (B) in endosperm tissues (gray) relative to embryo tissues (white). (n = 6, *q < 0.05, **q < 0.01) (PNG 528 KB)

11306_2018_1464_MOESM4_ESM.png

Supplementary material 4 Absolute gene transcript levels from select genes of lipid droplet packaging proteins. Box and whisker plots of normalized counts for transcripts significantly greater (A) or lower (B, Seipin2) in endosperm tissues (gray) relative to embryo tissues (white). (n = 6, *q < 0.05, **q < 0.01) (PNG 727 KB)

11306_2018_1464_MOESM5_ESM.png

Supplementary material 5 Relative transcript levels of select genes in the endosperm and embryos of 30 DAF seeds determined by RT-qPCR. Expression levels of FAH, GPAT9 and PDAT1 genes in endosperm showed no significant difference from their expression in the embryo (p > 0.05), whereas PDAT2 showed a significant difference between the embryo and endosperm (p < 0.0001). RT-qPCR values are presented relative to the expression of each gene in the embryo. All data are means SD (n = 3 independent biological replicates), and p values were calculated using mean crossing point deviation analysis computed by the relative expression (REST) software algorithm (Pfaffl et al. 2002). (PNG 31 KB)

Supplementary material 6 (DOCX 11 KB)

Supplementary material 7 (DOCX 11 KB)

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Sturtevant, D., Romsdahl, T.B., Yu, XH. et al. Tissue-specific differences in metabolites and transcripts contribute to the heterogeneity of ricinoleic acid accumulation in Ricinus communis L. (castor) seeds. Metabolomics 15, 6 (2019). https://doi.org/10.1007/s11306-018-1464-3

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