bioRxivMolecular BiologyPreprint
Alternative mRNA polyadenylation bridges mitochondrion-to-nucleus communication in Arabidopsis
Huifang Jia, Weike ZengiD, Xiaoyan ZhangiD, Jiedi Li, Xinyue Bao, Yanming Zhao, Lingjun ZhuiD, Chongyang MaiD, Fengling WangiD, Xiangqian GuoiD, Chun‐Peng SongiD, Liuyin MaiD, Xiaohong ZhuiD
Abstract
Mitochondria produce signals besides energy and metabolites that influence plant growth and fitness. However, how mitochondrial signals are relayed to other cellular compartments is largely unknown. By applying poly(A)-site RNA-sequencing (PAS-seq) to wildtype Arabidopsis seedlings and a mutant in the histone demethylase JMJ30 treated with the mitochondrial electron transfer chain inhibitor antimycin A (AA), we identified a previously undefined mitochondrion-to-nucleus communication pathway by which mitochondrial functional state regulates co-transcriptionally alternative polyadenylation (APA) of nuclear mRNA. We observed a global shortening of 3' untranslated regions (UTRs) as a molecular signature of AA-activated mitochondrial retrograde response (MRR), which contributed in part to translational regulation of auxin response and cell wall biogenesis. JMJ30 regulated AA-induced 3' UTR shortening, resulting in more transcripts with shortened 3' UTRs upon AA treatment in a JMJ30 gain-of-function mutant and overexpression lines. We also report on the JMJ30-interacting protein CPSF30, a cleavage and polyadenylation specificity factor that recruits JMJ30 to modulate H3K27me3 status at its target loci. Our study illustrates how epigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness. One-sentence summaryEpigenetic modification and APA coordinate mitochondrion-to-nucleus communication to allow cells to rapidly respond to changes in mitochondrial functional state and shape plant growth and fitness.
- organism: Arabidopsis
- assay: bulk RNA-seq
- research focus: differential expression
- research focus: gene regulatory network inference
- research focus: database / resource
- approach: statistical model
- Citations
- 0
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