Uncovering Mechanisms of Cell-type-specific Gene Expression in Rice

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• Dr Leonie Luginbuehl, Molecular Physiology Group, Department of Plant Sciences
• Thursday 27 January 2022, 13:00-14:00
• Online.

If you have a question about this talk, please contact Kumari Billakurthi.

Photosynthetic capacity is regulated by several environmental and endogenous factors, such as light and cell type. In plant species that use the ancestral C3 photosynthesis pathway, carbon fixation primarily takes place in leaf mesophyll cells, while bundle sheath cells show a reduced photosynthetic capacity. An important step in the evolution of the more efficient C4 photosynthesis pathway is the activation of photosynthesis in bundle sheath cells and the partitioning of photosynthetic reactions between these two cell types. This requires that photosynthetic genes are expressed in a cell-type-specific manner. While previous efforts to understand cell-type-specific gene expression have focused on C4 species, essentially nothing is known about the cis-regulatory sequences or transcription factors that regulate cell-type-specific gene expression in shoots of C3 grasses. Using single-nuclei RNA -sequencing, we generated a single-cell gene expression atlas of shoots of the C3 crop rice during development in the light. This approach identified 18 cell populations that show both common and unique transcriptional responses to light. To further understand the regulation of gene expression in rice bundle sheath and mesophyll cells, we characterized genome-wide accessible chromatin regions in these two cell types using ATAC -sequencing. Our analysis revealed hundreds of chromatin regions that are differentially accessible between rice mesophyll and bundle sheath cells and are associated with the cell-type-preferential expression of the corresponding genes. Within these accessible chromatin regions, we identified a number of cis-elements and transcription factors as candidates for regulating gene expression in mesophyll and bundle sheath cells. Using these data, we aim to generate a quantitative gene network model for the regulation of cell-type-specific gene expression in rice leaves.

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