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DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N⁶-methyladenosine on RNA.

ABSTRACT: Models developed using Nanopore direct RNA sequencing data from in vitro synthetic RNA with all adenosine replaced by N⁶-methyladenosine (m⁶A) are likely distorted due to superimposed signals from saturated m⁶A residues. Here, we develop a neural network, DENA, for m⁶A quantification using the sequencing data of in vivo transcripts from Arabidopsis. DENA identifies 90% of miCLIP-detected m⁶A sites in Arabidopsis and obtains modification rates in human consistent to those found by SCARLET, demonstrating its robustness across species. We sequence the transcriptome of two additional m⁶A-deficient Arabidopsis, mtb and fip37-4, using Nanopore and evaluate their single-nucleotide m⁶A profiles using DENA.

SUBMITTER: Qin H

PROVIDER: S-EPMC8762864 | biostudies-literature |

REPOSITORIES: biostudies-literature

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Project description: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, m6 A, m5 C 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 m6 A in plant growth and development has been appreciated, although its significance under stress conditions is still underexplored. To assess the role of m6 A 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 m6 A analysis revealed large-scale shifts in this modification in response to low temperature stress. Because m6 A is known to affect transcript stability/degradation and translation, we investigated these possibilities. Interestingly, we found that cold-enriched m6 A-containing transcripts demonstrated the largest increases in transcript abundance coupled with increased ribosome occupancy under cold stress. The significance of the m6 A epitranscriptome on plant cold tolerance was further assessed using the mta mutant in which the major m6 A methyltransferase gene was mutated. Compared to the wild-type, along with the differences in CBFs and COR gene expression levels, the mta 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-acclimated mta mutant demonstrated hypersensitivity to freezing tolerance. Taken together, these findings suggest a critical role for the epitranscriptome in cold tolerance of Arabidopsis.

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DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N⁶-methyladenosine on RNA.

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OmicsDI is part of the ELIXIR infrastructure

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Dataset Information

DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N6-methyladenosine on RNA.

Similar Datasets

OmicsDI is part of the ELIXIR infrastructure

Tweets

DENA: training an authentic neural network model using Nanopore sequencing data of Arabidopsis transcripts for detection and quantification of N⁶-methyladenosine on RNA.