bioRxivPlant BiologyPreprint
A transcriptomic atlas of grass senescence reveals divergent underground sink networks limit nitrogen recycling in annuals
Jonathan Odilón Ojeda‐RiveraiD, Elad OreniD, Sheng‐Kai HsuiD, Nicholas K. LepakiD, Thuy LaiD, Jingjing ZhaiiD, Michelle C. StitzeriD, Abou YobiiD, Ruthie AngeloviciiD, Edward S. BuckleriD, M. Cinta RomayiD
Abstract
Senescence enables plants to remobilize and recycle nutrients from aging organs to support growth, reproduction, and survival. In annual crops like maize, nitrogen remobilization from leaves to grain is incomplete, with 30-50% of nitrogen stranded in aboveground tissues and subject to environmental loss. Mitigating nitrogen loss in annual crops could be achieved by leveraging the physiological strategies of perennial grasses, which remobilize nitrogen and other nutrients into underground organs at the end of the growing season, thereby preventing environmental leakage. To uncover the molecular basis of perennial nitrogen recycling to underground organs, we built a transcriptomic atlas from field-grown plants, comprising 2,685 RNA-seq libraries from 14 grass species within the Panicoideae (Poaceae), utilizing maize and sorghum as annual references for comparative analyses. The atlas spans leaves, roots, stalks, and rhizomes across two seasons, from mid-growing season to senescence. Using a photosynthetic index to align the leafs transition from nitrogen sink to source across species, co-expression network analysis revealed that the subnetworks driving leaf nitrogen recycling are preserved across annuals and perennials. However, we discovered that the subnetworks associated with underground sink establishment, specifically those associated with seed-like dormancy and desiccation tolerance pathways, have diverged among annual crop accessions. Our work identifies conserved gene candidates and networks that could be used to reintroduce perennial-like nutrient recycling into annual crops to enhance long-term nutrient retention in the field.
- organism: plant (other)
- assay: bulk RNA-seq
- research focus: cell type annotation
- approach: statistical model
- Citations
- 2
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