bioRxivDevelopmental BiologyPreprint
A genome-wide survey of DNA methylation in Panax notoginseng reveals CHH hyper-methylation regulates the after-ripening and dormancy of recalcitrant seeds
Na Ge, Jin-Shan Jia, Qingyan Wang, Chaolin LiiD, Min Emma HuangiD, Jun‐Wen CheniD
Abstract
DNA methylation plays a crucial role in regulating fruit ripening and seed development. It remains unknown about the dynamic characteristics of DNA methylation and its regulation mechanisms in morpho-physiological dormancy (MPD)-typed seeds with recalcitrant characteristics. The P. notoginseng seeds are defined by the MPD and are characterized by a strong sensitivity to dehydration during the after-ripening process. We performed DNA methylomes, siRNA profiles, and transcriptomes of embryo and endosperm in P. notoginseng seeds at different after-ripening stages. Herein, we find that the CHH hyper-methylation contributes to the global increase in DNA methylation during the after-ripening process of P. notoginseng seeds. The endosperm genome is hyper-methylated compared to the embryo genome. The CHH hyper-methylation is caused by the high expression level of DNA methyltransferase PnCMT2 in the embryo, and PnDRM2 in the endosperm, respectively. The CHH hyper-methylation alters gene transcription levels to regulate the after-ripening and dormancy of recalcitrant seeds. For example, it inhibits the expression of genes in embryo development to make seeds maintain a dormant status, whereas it activates the expression of genes in the hormone-mediated signaling pathway, and energy metabolism to accomplish the MPD-typed seed after-ripening process. Together, our findings reveal a global increase in DNA methylation and its vital driver in gene expression, and thus elucidate how global CHH hyper-methylation regulates the after-ripening in recalcitrant MPD-typed seeds. This work establishes a key role for epigenetics in regulating the dormancy of MPD-typed seeds with recalcitrant characteristics.
- organism: plant (other)
- assay: DNA methylation
- research focus: gene regulatory network inference
- research focus: differential expression
- approach: statistical model
- Citations
- 0
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