{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,2,11]],"date-time":"2026-02-11T13:54:49Z","timestamp":1770818089858,"version":"3.50.1"},"reference-count":60,"publisher":"Oxford University Press (OUP)","issue":"6","license":[{"start":{"date-parts":[[2025,11,8]],"date-time":"2025-11-08T00:00:00Z","timestamp":1762560000000},"content-version":"vor","delay-in-days":7,"URL":"https:\/\/creativecommons.org\/licenses\/by-nc\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":[],"published-print":{"date-parts":[[2025,11,1]]},"abstract":"<jats:title>Abstract<\/jats:title>\n                  <jats:p>Methylation at cytosines in plants influences spatiotemporal gene expression by regulating chromatin structure and accessibility. Some algorithms have been developed to profess DNA methylation, but none of them are capable to tell the condition-specific DNA methylation, making them hardly of any use. Here, we report a first of its kind an explainable Deep Encoders-Decoders generative system, DNA Methylation Recognition Unit (DMRU), which learns the relationship between transcriptome status and DNA methylation states at any given time. It was also found that GC similarity is more relevant to the specificity of DNA methylation patterns than homology, concurring with reports of direct involvement of GC content in providing regulatory switches for DNA accessibility. Leveraging which DMRU could perform with same level of accuracy in a cross-species universal manner. In a comprehensive testing and benchmarking study across a huge volume of experimental data covering 85 different conditions and multiple plant species, it has consistently achieved &amp;gt;90% accuracy. With this all, DMRU brings a completely new chapter in methylated cytosine discovery, giving a strong alternative to costly bisulfite sequencing experiments. DMRU may prove a critical turning point in plant regulatory research and its acceleration.<\/jats:p>","DOI":"10.1093\/bib\/bbaf579","type":"journal-article","created":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T11:08:09Z","timestamp":1762686489000},"source":"Crossref","is-referenced-by-count":1,"title":["DMRU: generative deep learning to unravel condition-specific cytosine methylation in plants"],"prefix":"10.1093","volume":"26","author":[{"given":"Sagar","family":"Gupta","sequence":"first","affiliation":[{"name":"Studio of Computational Biology & Bioinformatics, The Himalayan Centre for High-throughput Computational Biology (HiCHiCoB, A BIC supported by DBT, India), Biotechnology Division , CSIR\u2013Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP 176061 ,","place":["India"]},{"name":"Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad, Uttar Pradesh 201002 ,","place":["India"]}]},{"given":"Anchit","family":"Kumar","sequence":"additional","affiliation":[{"name":"Studio of Computational Biology & Bioinformatics, The Himalayan Centre for High-throughput Computational Biology (HiCHiCoB, A BIC supported by DBT, India), Biotechnology Division , CSIR\u2013Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP 176061 ,","place":["India"]}]},{"given":"Veerbhan","family":"Kesarwani","sequence":"additional","affiliation":[{"name":"Studio of Computational Biology & Bioinformatics, The Himalayan Centre for High-throughput Computational Biology (HiCHiCoB, A BIC supported by DBT, India), Biotechnology Division , CSIR\u2013Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP 176061 ,","place":["India"]},{"name":"Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad, Uttar Pradesh 201002 ,","place":["India"]}]},{"given":"Umesh","family":"Bhati","sequence":"additional","affiliation":[{"name":"Studio of Computational Biology & Bioinformatics, The Himalayan Centre for High-throughput Computational Biology (HiCHiCoB, A BIC supported by DBT, India), Biotechnology Division , CSIR\u2013Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP 176061 ,","place":["India"]},{"name":"Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad, Uttar Pradesh 201002 ,","place":["India"]}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-4004-8047","authenticated-orcid":false,"given":"Ravi","family":"Shankar","sequence":"additional","affiliation":[{"name":"Studio of Computational Biology & Bioinformatics, The Himalayan Centre for High-throughput Computational Biology (HiCHiCoB, A BIC supported by DBT, India), Biotechnology Division , CSIR\u2013Institute of Himalayan Bioresource Technology (CSIR-IHBT), Palampur, HP 176061 ,","place":["India"]},{"name":"Academy of Scientific and Innovative Research (AcSIR) , Ghaziabad, Uttar Pradesh 201002 ,","place":["India"]}]}],"member":"286","published-online":{"date-parts":[[2025,11,8]]},"reference":[{"key":"2025110906075902800_ref1","doi-asserted-by":"publisher","first-page":"149","DOI":"10.1016\/j.bbagrm.2016.08.009","article-title":"Putting DNA methylation in context: from genomes to gene expression in plants","volume":"1860","author":"Niederhuth","year":"2017","journal-title":"Biochim Biophys Acta Gene Regul Mech"},{"key":"2025110906075902800_ref2","doi-asserted-by":"publisher","first-page":"1350","DOI":"10.1126\/science.6262918","article-title":"5-Methylcytosine in eukaryotic DNA","volume":"212","author":"Ehrlich","year":"1981","journal-title":"Science"},{"key":"2025110906075902800_ref3","doi-asserted-by":"publisher","first-page":"315","DOI":"10.1038\/nature08514","article-title":"Human DNA methylomes at base resolution show widespread epigenomic differences","volume":"462","author":"Lister","year":"2009","journal-title":"Nature"},{"key":"2025110906075902800_ref4","doi-asserted-by":"crossref","first-page":"5868","DOI":"10.1093\/nar\/gki901","article-title":"Reduced representation bisulfite sequencing for comparative high-resolution DNA methylation analysis","volume":"33","author":"Meissner","year":"2005","journal-title":"Nucleic Acids Res"},{"key":"2025110906075902800_ref5","doi-asserted-by":"publisher","first-page":"461","DOI":"10.1038\/nmeth.1459","article-title":"Direct detection of DNA methylation during single-molecule, real-time sequencing","volume":"7","author":"Flusberg","year":"2010","journal-title":"Nat Methods"},{"key":"2025110906075902800_ref6","doi-asserted-by":"publisher","first-page":"bbaa099","DOI":"10.1093\/bib\/bbaa099","article-title":"Deep4mC: systematic assessment and computational prediction for DNA N4-methylcytosine sites by deep learning","volume":"22","author":"Xu","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025110906075902800_ref7","doi-asserted-by":"publisher","first-page":"bbaa124","DOI":"10.1093\/bib\/bbaa124","article-title":"DeepTorrent: a deep learning-based approach for predicting DNA N4-methylcytosine sites","volume":"22","author":"Liu","year":"2021","journal-title":"Brief Bioinform"},{"key":"2025110906075902800_ref8","doi-asserted-by":"publisher","first-page":"bbac082","DOI":"10.1093\/bib\/bbac082","article-title":"MGF6mARice: prediction of DNA N6-methyladenine sites in rice by exploiting molecular graph feature and residual block","volume":"23","author":"Liu","year":"2022","journal-title":"Brief Bioinform"},{"key":"2025110906075902800_ref9","doi-asserted-by":"publisher","first-page":"8146","DOI":"10.3390\/ijms25158146","article-title":"DeepPGD: a deep learning model for DNA methylation prediction using temporal convolution, BiLSTM, and attention mechanism","volume":"25","author":"Teragawa","year":"2024","journal-title":"Int J Mol Sci"},{"key":"2025110906075902800_ref10","doi-asserted-by":"publisher","first-page":"104715","DOI":"10.1016\/j.chemolab.2022.104715","article-title":"MaskDNA-PGD: an innovative deep learning model for detecting DNA methylation by integrating mask sequences and adversarial PGD training as a data augmentation method","volume":"232","author":"Zheng","year":"2023","journal-title":"Chemom Intel Lab Syst"},{"key":"2025110906075902800_ref11","first-page":"30","article-title":"Attention is all you need","author":"Vaswani","year":"2017","journal-title":"Adv Neural Inf Process Syst"},{"key":"2025110906075902800_ref12","doi-asserted-by":"publisher","first-page":"142","DOI":"10.1016\/j.ymeth.2022.04.011","article-title":"Deep6mAPred: a CNN and Bi-LSTM-based deep learning method for predicting DNA N6-methyladenosine sites across plant species","volume":"204","author":"Tang","year":"2022","journal-title":"Methods"},{"key":"2025110906075902800_ref13","doi-asserted-by":"publisher","first-page":"bbae324","DOI":"10.1093\/bib\/bbae324","article-title":"PTFSpot: deep co-learning on transcription factors and their binding regions attains impeccable universality in plants","volume":"25","author":"Gupta","year":"2024","journal-title":"Brief Bioinform"},{"key":"2025110906075902800_ref14","doi-asserted-by":"publisher","first-page":"bbad088","DOI":"10.1093\/bib\/bbad088","article-title":"miWords: transformer-based composite deep learning for highly accurate discovery of pre-miRNA regions across plant genomes","volume":"24","author":"Gupta","year":"2023","journal-title":"Brief Bioinform"},{"key":"2025110906075902800_ref15","volume-title":"BERT: Pre-training of Deep Bidirectional Transformers for Language","author":"Devlin"},{"key":"2025110906075902800_ref16","doi-asserted-by":"publisher","first-page":"2077","DOI":"10.1126\/science.1059745","article-title":"Requirement of CHROMOMETHYLASE3 for maintenance of CpXpG methylation","volume":"292","author":"Lindroth","year":"2001","journal-title":"Science"},{"key":"2025110906075902800_ref17","doi-asserted-by":"publisher","first-page":"556","DOI":"10.1038\/nature731","article-title":"Control of CpNpG DNA methylation by the KRYPTONITE histone H3 methyltransferase","volume":"416","author":"Jackson","year":"2002","journal-title":"Nature"},{"key":"2025110906075902800_ref18","doi-asserted-by":"publisher","first-page":"10507","DOI":"10.1128\/MCB.25.23.10507-10515.2005","article-title":"H3 lysine 9 methylation is maintained on a transcribed inverted repeat by combined action of SUVH6 and SUVH4 methyltransferases","volume":"25","author":"Ebbs","year":"2005","journal-title":"Mol Cell Biol"},{"key":"2025110906075902800_ref19","doi-asserted-by":"publisher","first-page":"1166","DOI":"10.1105\/tpc.106.041400","article-title":"Locus-specific control of DNA methylation by the Arabidopsis SUVH5 histone methyltransferase","volume":"18","author":"Ebbs","year":"2006","journal-title":"Plant Cell"},{"key":"2025110906075902800_ref20","doi-asserted-by":"publisher","first-page":"8374","DOI":"10.1073\/pnas.1206638109","article-title":"INVOLVED IN DE NOVO 2-containing complex involved in RNA-directed DNA methylation in Arabidopsis","volume":"109","author":"Ausin","year":"2012","journal-title":"Proc Natl Acad Sci U S A"},{"key":"2025110906075902800_ref21","doi-asserted-by":"publisher","first-page":"1325","DOI":"10.1038\/nsmb.1690","article-title":"IDN1 and IDN2: two proteins required for de novo DNA methylation in Arabidopsis thaliana","volume":"16","author":"Ausin","year":"2009","journal-title":"Nat Struct Mol Biol"},{"key":"2025110906075902800_ref22","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2022.845835","article-title":"i6mA-vote: cross-species identification of DNA N6-methyladenine sites in plant genomes based on ensemble learning with voting","volume":"13","author":"Teng","year":"2022","journal-title":"Front Plant Sci"},{"key":"2025110906075902800_ref23","doi-asserted-by":"publisher","first-page":"219","DOI":"10.1186\/s13059-022-02780-1","article-title":"iDNA-ABF: multi-scale deep biological language learning model for the interpretable prediction of DNA methylations","volume":"23","author":"Jin","year":"2022","journal-title":"Genome Biol"},{"key":"2025110906075902800_ref24","doi-asserted-by":"publisher","first-page":"giad054","DOI":"10.1093\/gigascience\/giad054","article-title":"MuLan-Methyl\u2014multiple transformer-based language models for accurate DNA methylation prediction","volume":"12","author":"Zeng","year":"2023","journal-title":"GigaScience"},{"key":"2025110906075902800_ref25","first-page":"2345","article-title":"MethBERT: applying BERT transformers for nanopore-based DNA methylation detection","volume":"37","author":"Yang","year":"2021","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref26","doi-asserted-by":"publisher","first-page":"597","DOI":"10.1093\/bioinformatics\/btab746","article-title":"CpG-Transformer for imputation of single-cell methylomes","volume":"38","author":"De Waele","year":"2022","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref27","doi-asserted-by":"publisher","first-page":"4586","DOI":"10.1093\/bioinformatics\/btz276","article-title":"DeepSignal: detecting DNA methylation state from Nanopore sequencing reads using deep-learning","volume":"35","author":"Ni","year":"2019","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref28","first-page":"1724","article-title":"PlantDeepMeth: a deep learning model for predicting DNA methylation states in plants","volume":"14","author":"Zhang","year":"2023","journal-title":"Plant Sci"},{"key":"2025110906075902800_ref29","first-page":"1087","article-title":"MethNet: a robust approach to identify regulatory hubs and their distal targets from cancer methylation data","volume":"15","author":"Song","year":"2024","journal-title":"Nat Commun"},{"key":"2025110906075902800_ref30","first-page":"618","article-title":"Grad-CAM: visual explanations from deep networks via gradient-based localization","volume-title":"Proceedings of the IEEE International Conference on Computer Vision (ICCV)","author":"Selvaraju","year":"2017"},{"key":"2025110906075902800_ref31","doi-asserted-by":"publisher","first-page":"2114","DOI":"10.1093\/bioinformatics\/btu170","article-title":"Trimmomatic: a flexible trimmer for Illumina sequence data","volume":"30","author":"Bolger","year":"2014","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref32","doi-asserted-by":"publisher","first-page":"126","DOI":"10.1186\/1471-2164-13-126","article-title":"De novo sequencing and characterization of Picrorhiza kurrooa transcriptome at two temperatures showed major transcriptome adjustments","volume":"13","author":"Gahlan","year":"2012","journal-title":"BMC Genomics"},{"key":"2025110906075902800_ref33","doi-asserted-by":"publisher","first-page":"907","DOI":"10.1038\/s41587-019-0201-4","article-title":"Graph-based genome alignment and genotyping with HISAT2 and HISAT-genotype","volume":"37","author":"Kim","year":"2019","journal-title":"Nat Biotechnol"},{"key":"2025110906075902800_ref34","doi-asserted-by":"publisher","first-page":"e47","DOI":"10.1093\/nar\/gkz114","article-title":"The R package Rsubread is easier, faster, cheaper and better for alignment and quantification of RNA sequencing reads","volume":"47","author":"Liao","year":"2019","journal-title":"Nucleic Acids Res"},{"key":"2025110906075902800_ref35","doi-asserted-by":"publisher","first-page":"1571","DOI":"10.1093\/bioinformatics\/btr167","article-title":"Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications","volume":"27","author":"Krueger","year":"2011","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref36","doi-asserted-by":"publisher","first-page":"giab008","DOI":"10.1093\/gigascience\/giab008","article-title":"Twelve years of SAMtools and BCFtools","volume":"10","author":"Danecek","year":"2021","journal-title":"GigaScience"},{"key":"2025110906075902800_ref37","first-page":"4700","article-title":"Densely connected convolutional","volume":"1","author":"Huang","year":"2017","journal-title":"Networks"},{"key":"2025110906075902800_ref38","volume-title":"Plant Communications"},{"key":"2025110906075902800_ref39","doi-asserted-by":"publisher","first-page":"W56","DOI":"10.1093\/nar\/gkt437","article-title":"DNAshape: a method for the high-throughput prediction of DNA structural features on a genomic scale","volume":"41","author":"Zhou","year":"2013","journal-title":"Nucleic Acids Res"},{"key":"2025110906075902800_ref40","doi-asserted-by":"publisher","first-page":"103381","DOI":"10.1016\/j.isci.2021.103381","article-title":"RBPSpot: learning on appropriate contextual information for RBP binding sites discovery","volume":"24","author":"Sharma","year":"2021","journal-title":"iScience"},{"key":"2025110906075902800_ref41","doi-asserted-by":"publisher","first-page":"388","DOI":"10.1186\/s12864-016-2729-8","article-title":"A systematic, large-scale comparison of transcription factor binding site models","volume":"17","author":"Hombach","year":"2016","journal-title":"BMC Genomics"},{"key":"2025110906075902800_ref42","doi-asserted-by":"publisher","first-page":"e39140","DOI":"10.1016\/j.heliyon.2024.e39140","article-title":"Comprehensive analysis of computational approaches in plant transcription factors binding regions discovery","volume":"10","author":"Jyoti","year":"2024","journal-title":"Heliyon"},{"key":"2025110906075902800_ref43","first-page":"311","volume-title":"Proceedings of the 40th Annual Meeting on Association for Computational Linguistics","author":"Papineni","year":"2002"},{"key":"2025110906075902800_ref44","doi-asserted-by":"publisher","DOI":"10.1128\/ecosalplus.esp-0003-2013","article-title":"DNA methylation","volume":"6","author":"Marinus","year":"2014","journal-title":"EcoSal Plus"},{"key":"2025110906075902800_ref45","doi-asserted-by":"publisher","first-page":"e26","DOI":"10.1371\/journal.pgen.0020026","article-title":"CpG Island methylation in human lymphocytes is highly correlated with DNA sequence, repeats, and predicted DNA structure","volume":"2","author":"Bock","year":"2006","journal-title":"PLoS Genet"},{"key":"2025110906075902800_ref46","doi-asserted-by":"publisher","first-page":"205","DOI":"10.1177\/1352458516649038","article-title":"Integrating genome-wide association studies and gene expression data highlights dysregulated multiple sclerosis risk pathways","volume":"23","author":"Liu","year":"2017","journal-title":"Mult Scler"},{"key":"2025110906075902800_ref47","doi-asserted-by":"publisher","first-page":"2986","DOI":"10.1093\/bioinformatics\/btx316","article-title":"DIRECTION: a machine learning framework for predicting and characterizing DNA methylation and hydroxymethylation in mammalian genomes","volume":"33","author":"Pavlovic","year":"2017","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref48","doi-asserted-by":"publisher","first-page":"215","DOI":"10.1038\/nature06745","article-title":"Shotgun bisulphite sequencing of the Arabidopsis genome reveals DNA methylation patterning","volume":"452","author":"Cokus","year":"2008","journal-title":"Nature"},{"key":"2025110906075902800_ref49","doi-asserted-by":"publisher","first-page":"85","DOI":"10.1016\/j.gde.2013.11.015","article-title":"Genomic patterns and context specific interpretation of DNA methylation","volume":"25","author":"Baubec","year":"2014","journal-title":"Curr Opin Genet Dev"},{"key":"2025110906075902800_ref50","doi-asserted-by":"publisher","first-page":"110443","DOI":"10.1016\/j.ygeno.2022.110443","article-title":"DeepPlnc: bi-modal deep learning for highly accurate plant lncRNA discovery","volume":"114","author":"Ritu","year":"2022","journal-title":"Genomics"},{"key":"2025110906075902800_ref51","doi-asserted-by":"publisher","first-page":"1430","DOI":"10.1101\/gr.199778.115","article-title":"A synergistic DNA logic predicts genome-wide chromatin accessibility","volume":"26","author":"Hashimoto","year":"2016","journal-title":"Genome Res"},{"key":"2025110906075902800_ref52","doi-asserted-by":"publisher","first-page":"1468","DOI":"10.1101\/gr.263228.120","article-title":"Identification of determinants of differential chromatin accessibility through a massively parallel genome-integrated reporter assay","volume":"30","author":"Hammelman","year":"2020","journal-title":"Genome Res"},{"key":"2025110906075902800_ref53","doi-asserted-by":"publisher","first-page":"441","DOI":"10.1534\/g3.114.015545","article-title":"Evolutionary consequences of DNA methylation on the GC content in vertebrate genomes","volume":"5","author":"Mugal","year":"2015","journal-title":"G3 (Bethesda)"},{"key":"2025110906075902800_ref54","doi-asserted-by":"publisher","first-page":"381","DOI":"10.1016\/j.tibs.2014.07.002","article-title":"Absence of a simple code: how transcription factors read the genome","volume":"39","author":"Slattery","year":"2014","journal-title":"Trends Biochem Sci"},{"key":"2025110906075902800_ref55","doi-asserted-by":"publisher","first-page":"605","DOI":"10.1002\/bies.201600005","article-title":"How motif environment influences transcription factor search dynamics: finding a needle in a haystack","volume":"38","author":"Dror","year":"2016","journal-title":"Bioessays"},{"key":"2025110906075902800_ref56","doi-asserted-by":"crossref","DOI":"10.1016\/j.isci.2020.100991","article-title":"iDNA-MS: an integrated computational tool for detecting DNA modification sites in multiple genomes","volume":"23","author":"Lv","year":"2020","journal-title":"iScience"},{"key":"2025110906075902800_ref57","doi-asserted-by":"publisher","first-page":"4603","DOI":"10.1093\/bioinformatics\/btab677","article-title":"iDNA-ABT: advanced deep learning model for detecting DNA methylation with adaptive features and transductive information maximization","volume":"37","author":"Yu","year":"2021","journal-title":"Bioinformatics"},{"key":"2025110906075902800_ref58","doi-asserted-by":"publisher","first-page":"4035","DOI":"10.1242\/dev.01279","article-title":"PETAL LOSS, a trihelix transcription factor gene, regulates perianth architecture in the Arabidopsis flower","volume":"131","author":"Brewer","year":"2004","journal-title":"Development"},{"key":"2025110906075902800_ref59","doi-asserted-by":"publisher","first-page":"901","DOI":"10.2307\/3869458","article-title":"LEAFY interacts with floral homeotic genes to regulate Arabidopsis floral development","volume":"4","author":"Huala","year":"1992","journal-title":"Plant Cell"},{"key":"2025110906075902800_ref60","doi-asserted-by":"publisher","DOI":"10.3389\/fpls.2021.764843","article-title":"Investigating host and parasitic plant interaction by tissue-specific gene analyses on tomato and Cuscuta campestris interface at three haustorial developmental stages","volume":"12","author":"Jhu","year":"2022","journal-title":"Front Plant Sci"}],"container-title":["Briefings in Bioinformatics"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/6\/bbaf579\/65246582\/bbaf579.pdf","content-type":"application\/pdf","content-version":"vor","intended-application":"syndication"},{"URL":"https:\/\/academic.oup.com\/bib\/article-pdf\/26\/6\/bbaf579\/65246582\/bbaf579.pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,11,9]],"date-time":"2025-11-09T11:08:11Z","timestamp":1762686491000},"score":1,"resource":{"primary":{"URL":"https:\/\/academic.oup.com\/bib\/article\/doi\/10.1093\/bib\/bbaf579\/8317202"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2025,11,1]]},"references-count":60,"journal-issue":{"issue":"6","published-print":{"date-parts":[[2025,11,1]]}},"URL":"https:\/\/doi.org\/10.1093\/bib\/bbaf579","relation":{},"ISSN":["1467-5463","1477-4054"],"issn-type":[{"value":"1467-5463","type":"print"},{"value":"1477-4054","type":"electronic"}],"subject":[],"published-other":{"date-parts":[[2025,11]]},"published":{"date-parts":[[2025,11,1]]},"article-number":"bbaf579"}}