Abstract
Stress recovery may prove to be a promising approach to increase plant performance and, theoretically, mRNA instability may facilitate faster recovery. Transcriptome (RNA-seq, qPCR, sRNA-seq, and PARE) and methylome profiling during repeated excess-light stress and recovery was performed at intervals as short as 3 min. We demonstrate that 87% of the stress-upregulated mRNAs analyzed exhibit very rapid recovery. For instance, HSP101 abundance declined 2-fold every 5.1 min. We term this phenomenon rapid recovery gene downregulation (RRGD), whereby mRNA abundance rapidly decreases promoting transcriptome resetting. Decay constants (k) were modeled using two strategies, linear and nonlinear least squares regressions, with the latter accounting for both transcription and degradation. This revealed extremely short half-lives ranging from 2.7 to 60.0 min for 222 genes. Ribosome footprinting using degradome data demonstrated RRGD loci undergo cotranslational decay and identified changes in the ribosome stalling index during stress and recovery. However, small RNAs and 5ʹ-3ʹ RNA decay were not essential for recovery of the transcripts examined, nor were any of the six excess light-associated methylome changes. We observed recovery-specific gene expression networks upon return to favorable conditions and six transcriptional memory types. In summary, rapid transcriptome resetting is reported in the context of active recovery and cellular memory.
| Original language | English (US) |
|---|---|
| Pages (from-to) | 1836-1863 |
| Number of pages | 28 |
| Journal | Plant Cell |
| Volume | 29 |
| Issue number | 8 |
| DOIs | |
| State | Published - 2017 |
Bibliographical note
Funding Information:This work was supported by the Australian Research Council Centre of Excellence in Plant Energy Biology (CE140100008). P.A.C. and D.R.G. were supported by Grains Research and Development Council scholarships (GRS184 and GRS10683), and S.R.E. was supported by an Australian Research Council Discovery Early Career Researcher Award (DE150101206). R.L. was supported by an Australian Research Council Future Fellowship (FT120100862) and a Sylvia and Charles Viertel Senior Medical Research Fellowship. We thank Teresa Neeman for extensive statistical advice on modeling decay kinetics, Britta Förster for assistance with chlorophyll fluorescence measurements, John Maindonald for assistance with R programming and statistical analysis, The Genome Discovery Unit and the Statistical Consulting Unit at the Australian National University (ANU) for assistance with experimental design and analysis, the Myers lab for providing the PARE protocol, and Tony Millar and Robert Allen for valuable advice and discussions. We also acknowledge The Biomolecular Resource Facility and the ANU for performing Illumina sequencing and The Australian Plant Phenomics Facility at the ANU for providing phenotyping and growth facilities. This research was undertaken with the assistance of resources from the National Computational Infrastructure, which is supported by the Australian Government.
Publisher Copyright:
© 2017 ASPB.