Plants respond to low temperatures by altering the mRNA abundance of thousands of genes contributing to numerous physiological and metabolic processes that allow them to adapt. At the post‐transcriptional level, these cold stress‐responsive transcripts undergo alternative splicing, microRNA‐mediated regulation and alternative polyadenylation, amongst others. Recently, m6A, m5C and other mRNA modifications that can affect the regulation and stability of RNA were discovered, thus revealing another layer of post‐transcriptional regulation that plays an important role in modulating gene expression. The importance of m6A in plant growth and development has been appreciated, although its significance under stress conditions is still underexplored. To assess the role of m6A modifications during cold stress responses, methylated RNA immunoprecipitation sequencing was performed in Arabidopsis seedlings esposed to low temperature stress (4°C) for 24 h. This transcriptome‐wide m6A analysis revealed large‐scale shifts in this modification in response to low temperature stress. Because m6A is known to affect transcript stability/degradation and translation, we investigated these possibilities. Interestingly, we found that cold‐enriched m6A‐containing transcripts demonstrated the largest increases in transcript abundance coupled with increased ribosome occupancy under cold stress. The significance of the m6A epitranscriptome on plant cold tolerance was further assessed using the
After transcription, a messenger RNA (mRNA) is further post‐transcriptionally regulated by several features including RNA secondary structure and covalent RNA modifications (specifically N6‐methyladenosine, m6A). Both RNA secondary structure and m6A have been demonstrated to regulate mRNA stability and translation and have been independently linked to plant responses to soil salinity levels. However, the effect of m6A on regulating RNA secondary structure and the combinatorial interplay between these two RNA features during salt stress response has yet to be studied. Here, we globally identify RNA‐protein interactions and RNA secondary structure during systemic salt stress. This analysis reveals that RNA secondary structure changes significantly during salt stress, and that it is independent of global changes in RNA‐protein interactions. Conversely, we find that m6A is anti‐correlated with RNA secondary structure in a condition‐dependent manner, with salt‐specific m6A correlated with a decrease in mRNA secondary structure during salt stress. Taken together, we suggest that salt‐specific m6A deposition and the associated loss of RNA secondary structure results in increases in mRNA stability for transcripts encoding abiotic stress response proteins and ultimately increases in protein levels from these stabilized transcripts. In total, our comprehensive analyses reveal important post‐transcriptional regulatory mechanisms involved in plant long‐term salt stress response and adaptation.
more » « less- NSF-PAR ID:
- 10456156
- Publisher / Repository:
- Wiley Blackwell (John Wiley & Sons)
- Date Published:
- Journal Name:
- Plant Direct
- Volume:
- 4
- Issue:
- 7
- ISSN:
- 2475-4455
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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SUMMARY mta mutant in which the major m6A methyltransferase gene was mutated. Compared to the wild‐type, along with the differences inCBFs andCOR gene expression levels, themta mutant exhibited hypersensitivity to cold treatment as determined by primary root growth, biomass, and reactive oxygen species accumulation. Furthermore, and most importantly, both non‐acclimated and cold‐acclimatedmta mutant demonstrated hypersensitivity to freezing tolerance. Taken together, these findings suggest a critical role for the epitranscriptome in cold tolerance of Arabidopsis. -
INTRODUCTION Eukaryotes contain a highly conserved signaling pathway that becomes rapidly activated when adenosine triphosphate (ATP) levels decrease, as happens during conditions of nutrient shortage or mitochondrial dysfunction. The adenosine monophosphate (AMP)–activated protein kinase (AMPK) is activated within minutes of energetic stress and phosphorylates a limited number of substrates to biochemically rewire metabolism from an anabolic state to a catabolic state to restore metabolic homeostasis. AMPK also promotes prolonged metabolic adaptation through transcriptional changes, decreasing biosynthetic genes while increasing expression of genes promoting lysosomal and mitochondrial biogenesis. The transcription factor EB (TFEB) is a well-appreciated effector of AMPK-dependent signals, but many of the molecular details of how AMPK controls these processes remain unknown. RATIONALE The requirement of AMPK and its specific downstream targets that control aspects of the transcriptional adaptation of metabolism remain largely undefined. We performed time courses examining gene expression changes after various mitochondrial stresses in wild-type (WT) or AMPK knockout cells. We hypothesized that a previously described interacting protein of AMPK, folliculin-interacting protein 1 (FNIP1), may be involved in how AMPK promotes increases in gene expression after metabolic stress. FNIP1 forms a complex with the protein folliculin (FLCN), together acting as a guanosine triphosphate (GTP)–activating protein (GAP) for RagC. The FNIP1-FLCN complex has emerged as an amino acid sensor to the mechanistic target of rapamycin complex 1 (mTORC1), involved in how amino acids control TFEB activation. We therefore examined whether AMPK may regulate FNIP1 to dominantly control TFEB independently of amino acids. RESULTS AMPK was found to govern expression of a core set of genes after various mitochondrial stresses. Hallmark features of this response were activation of TFEB and increases in the transcription of genes specifying lysosomal and mitochondrial biogenesis. AMPK directly phosphorylated five conserved serine residues in FNIP1, suppressing the function of the FLCN-FNIP1 GAP complex, which resulted in dissociation of RagC and mTOR from the lysosome, promoting nuclear translocation of TFEB even in the presence of amino acids. FNIP1 phosphorylation was required for AMPK to activate TFEB and for subsequent increases in peroxisome proliferation–activated receptor gamma coactivator 1-alpha (PGC1α) and estrogen-related receptor alpha (ERRα) mRNAs. Cells in which the five serines in FNIP1 were mutated to alanine were unable to increase lysosomal and mitochondrial gene expression programs after treatment with mitochondrial poisons or AMPK activators despite the presence and normal regulation of all other substrates of AMPK. By contrast, neither AMPK nor its control of FNIP1 were needed for activation of TFEB after amino acid withdrawal, illustrating the specificity to energy-limited conditions. CONCLUSION Our data establish FNIP1 as the long-sought substrate of AMPK that controls TFEB translocation to the nucleus, defining AMPK phosphorylation of FNIP1 as a singular event required for increased lysosomal and mitochondrial gene expression programs after metabolic stresses. This study also illuminates the larger biological question of how mitochondrial damage triggers a temporal response of repair and replacement of damaged mitochondria: Within early hours, AMPK-FNIP1–activated TFEB induces a wave of lysosome and autophagy genes to promote degradation of damaged mitochondria, and a few hours later, TFEB–up-regulated PGC1⍺ and ERR⍺ promote expression of a second wave of genes specifying mitochondrial biogenesis. These insights open therapeutic avenues for several common diseases associated with mitochondrial dysfunction, ranging from neurodegeneration to type 2 diabetes to cancer. Mitochondrial damage activates AMPK to phosphorylate FNIP1, stimulating TFEB translocation to the nucleus and sequential waves of lysosomal and mitochondrial biogenesis. After mitochondrial damage, activated AMPK phosphorylates FNIP1 (1), causing inhibition of FLCN-FNIP1 GAP activity (2). This leads to accumulation of RagC in its GTP-bound form, causing dissociation of RagC, mTORC1, and TFEB from the lysosome (3). TFEB is therefore not phosphorylated and translocates to the nucleus, inducing transcription of lysosomal or autophagy genes, with parallel increases in NT-PGC1α mRNA (4), which, in concert with ERRα (5), subsequently induces mitochondrial biogenesis (6). CCCP, carbonyl cyanide m-chlorophenylhydrazone; CLEAR, coordinated lysosomal expression and regulation; GDP, guanosine diphosphate; P, phosphorylation. [Figure created using BioRender]more » « less
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null (Ed.)Abstract Ribonucleotides within the various RNA molecules in eukaryotes are marked with more than 160 distinct covalent chemical modifications. These modifications include those that occur internally in messenger RNA (mRNA) molecules such as N6-methyladenosine (m6A) and 5-methylcytosine (m5C), as well as those that occur at the ends of the modified RNAs like the non-canonical 5′ end nicotinamide adenine dinucleotide (NAD+) cap modification of specific mRNAs. Recent findings have revealed that covalent RNA modifications can impact the secondary structure, translatability, functionality, stability and degradation of the RNA molecules in which they are included. Many of these covalent RNA additions have also been found to be dynamically added and removed through writer and eraser complexes, respectively, providing a new layer of epitranscriptome-mediated post-transcriptional regulation that regulates RNA quality and quantity in eukaryotic transcriptomes. Thus, it is not surprising that the regulation of RNA fate mediated by these epitranscriptomic marks has been demonstrated to have widespread effects on plant development and the responses of these organisms to abiotic and biotic stresses. In this review, we highlight recent progress focused on the study of the dynamic nature of these epitranscriptome marks and their roles in post-transcriptional regulation during plant development and response to environmental cues, with an emphasis on the mRNA modifications of non-canonical 5′ end NAD+ capping, m6A and several other internal RNA modifications.more » « less
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N 6-methyladenosine (m6A) regulates stability and translation of messenger RNA (mRNA) in various biological processes. In this work, we show that knockout of the m6A writerMettl3 or the nuclear readerYthdc1 in mouse embryonic stem cells increases chromatin accessibility and activates transcription in an m6A-dependent manner. We found that METTL3 deposits m6A modifications on chromosome-associated regulatory RNAs (carRNAs), including promoter-associated RNAs, enhancer RNAs, and repeat RNAs. YTHDC1 facilitates the decay of a subset of these m6A-modified RNAs, especially elements of the long interspersed element-1 family, through the nuclear exosome targeting–mediated nuclear degradation. Reducing m6A methylation by METTL3 depletion or site-specific m6A demethylation of selected carRNAs elevates the levels of carRNAs and promotes open chromatin state and downstream transcription. Collectively, our results reveal that m6A on carRNAs can globally tune chromatin state and transcription. -
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Abstract Motivation Alternative polyadenylation (polyA) sites near the 3′ end of a pre-mRNA create multiple mRNA transcripts with different 3′ untranslated regions (3′ UTRs). The sequence elements of a 3′ UTR are essential for many biological activities such as mRNA stability, sub-cellular localization, protein translation, protein binding and translation efficiency. Moreover, numerous studies in the literature have reported the correlation between diseases and the shortening (or lengthening) of 3′ UTRs. As alternative polyA sites are common in mammalian genes, several machine learning tools have been published for predicting polyA sites from sequence data. These tools either consider limited sequence features or use relatively old algorithms for polyA site prediction. Moreover, none of the previous tools consider RNA secondary structures as a feature to predict polyA sites.
Results In this paper, we propose a new deep learning model, called DeepPASTA, for predicting polyA sites from both sequence and RNA secondary structure data. The model is then extended to predict tissue-specific polyA sites. Moreover, the tool can predict the most dominant (i.e. frequently used) polyA site of a gene in a specific tissue and relative dominance when two polyA sites of the same gene are given. Our extensive experiments demonstrate that DeepPASTA signisficantly outperforms the existing tools for polyA site prediction and tissue-specific relative and absolute dominant polyA site prediction.
Availability and implementation https://github.com/arefeen/DeepPASTA
Supplementary information Supplementary data are available at Bioinformatics online.
