<HashMap><database>biostudies-literature</database><scores/><additional><omics_type>Unknown</omics_type><volume>16(17)</volume><submitter>Athanasopoulou K</submitter><pubmed_abstract>&lt;b>Background:&lt;/b> N6-methyladenosine (m6A), a prevalent mRNA modification, is dynamically regulated by methyltransferases, including METTL3 and METTL14.&lt;b>Materials &amp; methods:&lt;/b> In the current study, we employed a custom hybrid-seq method to identify novel &lt;i>METTL3&lt;/i>/&lt;i>14&lt;/i> transcripts, explore their protein-coding capacities and predict the putative role of the METTL isoforms.&lt;b>Results:&lt;/b> Demultiplexing of the hybrid-seq barcoded datasets unraveled the expression patterns of the newly identified mRNAs in major malignancies as well as in non-malignant cells, providing a deeper understanding of the methylation pathways. Open reading frame query revealed novel METTL3/14 isoforms, broadening our perspective for the structural diversity within METTL family.&lt;b>Conclusion:&lt;/b> Our fi</pubmed_abstract><journal>Epigenomics</journal><pagination>1159-1174</pagination><full_dataset_link>https://www.ebi.ac.uk/biostudies/studies/S-EPMC11457658</full_dataset_link><repository>biostudies-literature</repository><pubmed_title>New insights into the dynamics of m6A epitranscriptome: hybrid-seq identifies novel mRNAs of the m6A writers METTL3/14.</pubmed_title><pmcid>PMC11457658</pmcid><pubmed_authors>Athanasopoulou K</pubmed_authors><pubmed_authors>Adamopoulos PG</pubmed_authors><pubmed_authors>Scorilas A</pubmed_authors></additional><is_claimable>false</is_claimable><name>New insights into the dynamics of m6A epitranscriptome: hybrid-seq identifies novel mRNAs of the m6A writers METTL3/14.</name><description>&lt;b>Background:&lt;/b> N6-methyladenosine (m6A), a prevalent mRNA modification, is dynamically regulated by methyltransferases, including METTL3 and METTL14.&lt;b>Materials &amp; methods:&lt;/b> In the current study, we employed a custom hybrid-seq method to identify novel &lt;i>METTL3&lt;/i>/&lt;i>14&lt;/i> transcripts, explore their protein-coding capacities and predict the putative role of the METTL isoforms.&lt;b>Results:&lt;/b> Demultiplexing of the hybrid-seq barcoded datasets unraveled the expression patterns of the newly identified mRNAs in major malignancies as well as in non-malignant cells, providing a deeper understanding of the methylation pathways. Open reading frame query revealed novel METTL3/14 isoforms, broadening our perspective for the structural diversity within METTL family.&lt;b>Conclusion:&lt;/b> Our fi</description><dates><release>2024-01-01T00:00:00Z</release><publication>2024</publication><modification>2026-04-08T15:18:00.288Z</modification><creation>2026-04-08T04:27:29.574Z</creation></dates><accession>S-EPMC11457658</accession><cross_references><pubmed>39225157</pubmed><doi>10.1080/17501911.2024.2390818</doi></cross_references></HashMap>