Dissecting the nutrient partitioning mechanism in rice grain using spatially resolved gene expression profiling.

Rice, a staple food worldwide, contains varying amounts of nutrients in different grain tissues. The underlying molecular mechanism of such distinct nutrient partitioning remains poorly investigated. Here, an optimized rapid laser capture microdissection (LCM) approach was used to individually collect pericarp, aleurone, embryo and endosperm from grains 10 days after fertilization. Subsequent RNA-Seq analysis in these tissues identified 7760 differentially expressed genes. Analysis of promoter sequences of tissue-specific genes identified many known and novel cis-elements important for grain filling and seed development. Using the identified differentially expressed genes, comprehensive spatial gene expression pathways were built for accumulation of starch, proteins, lipids, and iron. The extensive transcriptomic analysis provided novel insights about nutrient partitioning mechanisms; for example, it revealed a gradient in seed storage protein accumulation across the four tissue types analysed. The analysis also revealed that the partitioning of various minerals, such as iron, is most likely regulated through transcriptional control of their transporters. We present the extensive analysis from this study as an interactive online tool that provides a much-needed resource for future functional genomics studies aimed to improve grain quality and seed development. © The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Experimental Biology. All rights reserved. For permissions, please email: journals.permissions@oup.com.

Citation

Hasthi Ram, Anmol Singh, Megha Katoch, Ravneet Kaur, Shaswati Sardar, Shubham Palia, Rohit Satyam, Humira Sonah, Rupesh Deshmukh, Ajay Kumar Pandey, Ishaan Gupta, Tilak Raj Sharma. Dissecting the nutrient partitioning mechanism in rice grain using spatially resolved gene expression profiling. Journal of experimental botany. 2021 Mar 17;72(6):2212-2230

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PMID: 33197257

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