Experimental and Computational Methods for Guiding Identification and Characterization of Epitranscriptome Proteins
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Lydia M. Contreras | Matthew R. Burroughs | Juan C. Gonzalez-Rivera | Antonio Cordova | J. González-Rivera | L. Contreras | Matthew Burroughs | Antonio Cordova | Juan González-Rivera
[1] A. Caflisch,et al. Selectively disrupting m6A-dependent protein-RNA interactions with fragments. , 2020, ACS chemical biology.
[2] Chuan He,et al. N6-methyladenosine-dependent RNA structural switches regulate RNA-protein interactions , 2015, Nature.
[3] Wei Chen,et al. Identifying RNA 5-methylcytosine sites via pseudo nucleotide compositions. , 2016, Molecular bioSystems.
[4] M. Kupiec,et al. Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq , 2012, Nature.
[5] U. Ohler,et al. Deep neural networks for interpreting RNA-binding protein target preferences. , 2020, Genome research.
[6] Thomas Schwarzl,et al. Discovery of RNA-binding proteins and characterization of their dynamic responses by enhanced RNA interactome capture , 2018, Nature Communications.
[7] S. Hazen,et al. Activated leukocytes oxidatively damage DNA, RNA, and the nucleotide pool through halide-dependent formation of hydroxyl radical. , 2000, Biochemistry.
[8] Zhiyong Zhang,et al. METTL3 and ALKBH5 oppositely regulate m6A modification of TFEB mRNA, which dictates the fate of hypoxia/reoxygenation-treated cardiomyocytes , 2019, Autophagy.
[9] R. Jessberger,et al. Precise hit: adeno-associated virus in gene targeting , 2005, Nature Reviews Microbiology.
[10] Chengqi Yi,et al. N6-Methyladenosine in Nuclear RNA is a Major Substrate of the Obesity-Associated FTO , 2011, Nature chemical biology.
[11] Jun Li,et al. Transcriptome-Wide Mapping of RNA 5-Methylcytosine in Arabidopsis mRNAs and Noncoding RNAs , 2017, Plant Cell.
[12] C. Hall,et al. The design of a peptide sequence to inhibit HIV replication: a search algorithm combining Monte Carlo and self-consistent mean field techniques , 2014, Journal of biomolecular structure & dynamics.
[13] Yongli Yao,et al. Cytoplasmic m1A reader YTHDF3 inhibits trophoblast invasion by downregulation of m1A-methylated IGF1R , 2020, Cell Discovery.
[14] Xiao-Min Liu,et al. Programmable RNA N6-methyladenosine editing by CRISPR-Cas9 conjugates , 2019, Nature Chemical Biology.
[15] Huiqing Zhou,et al. Programmable RNA-Guided RNA Effector Proteins Built from Human Parts , 2019, Cell.
[16] Ruth J. Muschel,et al. Corrigendum: Cancer cells that survive radiation therapy acquire HIF-1 activity and translocate toward tumour blood vessels , 2013, Nature Communications.
[17] Abdulrahim A. Sajini,et al. Loss of 5-methylcytosine alters the biogenesis of vault-derived small RNAs to coordinate epidermal differentiation , 2019, Nature Communications.
[18] Jia Meng,et al. m6A Reader: Epitranscriptome Target Prediction and Functional Characterization of N6-Methyladenosine (m6A) Readers , 2020, Frontiers in Cell and Developmental Biology.
[19] Hong-Bin Shen,et al. Recent methodology progress of deep learning for RNA–protein interaction prediction , 2019, Wiley interdisciplinary reviews. RNA.
[20] Hai-Cheng Yi,et al. RPI-SE: a stacking ensemble learning framework for ncRNA-protein interactions prediction using sequence information , 2020, BMC Bioinformatics.
[21] Ralph E. Kleiner,et al. In vitro selection with a site-specifically modified RNA library reveals the binding preferences of N6-methyladenosine (m6A) reader proteins. , 2019, Biochemistry.
[22] Lydia M. Contreras,et al. Cellular RNA is chemically modified by exposure to air pollution mixtures , 2015, Inhalation toxicology.
[23] Y. Gong,et al. N6-methyladenine RNA modification and cancers. , 2018, American journal of cancer research.
[24] Yuri Motorin,et al. Detecting RNA modifications in the epitranscriptome: predict and validate , 2017, Nature Reviews Genetics.
[25] Stefan Hüttelmaier,et al. Recognition of RNA N6-methyladenosine by IGF2BP Proteins Enhances mRNA Stability and Translation , 2018, Nature Cell Biology.
[26] Joseph M Jakubowski,et al. Computational evolution of an RNA-binding protein towards enhanced oxidized-RNA binding , 2019, Computational and structural biotechnology journal.
[27] E. Seeberg,et al. AlkB restores the biological function of mRNA and tRNA inactivated by chemical methylation. , 2004, Molecular cell.
[28] Chuan He,et al. FTO-dependent demethylation of N6-methyladenosine regulates mRNA splicing and is required for adipogenesis , 2014, Cell Research.
[29] Samie R Jaffrey,et al. Reading, writing and erasing mRNA methylation , 2019, Nature Reviews Molecular Cell Biology.
[30] C. Hall,et al. Simulation study of the ability of a computationally‐designed peptide to recognize target tRNALys3 and other decoy tRNAs , 2016, Protein science : a publication of the Protein Society.
[31] Asuka A. Orr,et al. A high-throughput and rapid computational method for screening of RNA post-transcriptional modifications that can be recognized by target proteins. , 2018, Methods.
[32] Ling-Ling Chen,et al. N6-Methyladenosines Modulate A-to-I RNA Editing. , 2018, Molecular cell.
[33] Federico Agostini,et al. Predicting protein associations with long noncoding RNAs , 2011, Nature Methods.
[34] T. Ishii,et al. Specific binding of PCBP1 to heavily oxidized RNA to induce cell death , 2018, Proceedings of the National Academy of Sciences.
[35] Chengqi Yi,et al. Epitranscriptome sequencing technologies: decoding RNA modifications , 2016, Nature Methods.
[36] Chuan He,et al. N6-methyladenosine (m6A) recruits and repels proteins to regulate mRNA homeostasis , 2017, Nature Structural &Molecular Biology.
[37] Yousheng Shu,et al. A novel m6A reader Prrc2a controls oligodendroglial specification and myelination , 2018, Cell Research.
[38] Lijia Ma,et al. A metabolic labeling method detects m6A transcriptome-wide at single base resolution , 2020, Nature Chemical Biology.
[39] Ya-Zhou Sun,et al. RNA methylation and diseases: experimental results, databases, Web servers and computational models , 2019, Briefings Bioinform..
[40] A. Rentmeister,et al. Sequence-specific m6A demethylation in RNA by FTO fused to RCas9 , 2019, RNA.
[41] Xing Gao,et al. Integration of deep feature representations and handcrafted features to improve the prediction of N6-methyladenosine sites , 2019, Neurocomputing.
[42] Q. Zou,et al. Gene2vec: gene subsequence embedding for prediction of mammalian N6-methyladenosine sites from mRNA , 2018, RNA.
[43] Chuan He,et al. N 6 -methyladenosine Modulates Messenger RNA Translation Efficiency , 2015, Cell.
[44] Wayne O. Miles,et al. Beyond CLIP: advances and opportunities to measure RBP–RNA and RNA–RNA interactions , 2019, Nucleic acids research.
[45] M. Scholle,et al. A Mass Spectrometric Assay of METTL3/METTL14 Methyltransferase Activity , 2020, SLAS discovery : advancing life sciences R & D.
[46] Thomas Haselhorst,et al. Unravelling the Role of O-glycans in Influenza A Virus Infection , 2018, Scientific Reports.
[47] S. Futaki,et al. Programmable RNA methylation and demethylation using PUF RNA binding proteins. , 2020, Chemical communications.
[48] Martin Vingron,et al. ssHMM: extracting intuitive sequence-structure motifs from high-throughput RNA-binding protein data , 2016, bioRxiv.
[49] Chuan He,et al. FTO-Mediated Formation of N6-Hydroxymethyladenosine and N6-Formyladenosine in Mammalian RNA , 2013, Nature Communications.
[50] Xuerui Yang,et al. Mettl3-/Mettl14-mediated mRNA N6-methyladenosine modulates murine spermatogenesis , 2017, Cell Research.
[51] Samie R. Jaffrey,et al. Reading m6A in the Transcriptome: m6A-Binding Proteins. , 2017, Trends in cell biology.
[52] C. Hall,et al. Molecular recognition mechanism of peptide chain bound to the tRNALys3 anticodon loop in silico , 2015, Journal of biomolecular structure & dynamics.
[53] Samir Adhikari,et al. 5-methylcytosine promotes mRNA export — NSUN2 as the methyltransferase and ALYREF as an m5C reader , 2017, Cell Research.
[54] Cai-Guang Yang,et al. Targeting Epitranscriptomic Proteins for Therapeutic Intervention. , 2020, Biochemistry.
[55] Zhongwei Li,et al. Human polynucleotide phosphorylase reduces oxidative RNA damage and protects HeLa cell against oxidative stress. , 2008, Biochemical and biophysical research communications.
[56] Gajendra P. S. Raghava,et al. Prediction of uridine modifications in tRNA sequences , 2014, BMC Bioinformatics.
[57] Hao Lin,et al. XG-PseU: an eXtreme Gradient Boosting based method for identifying pseudouridine sites , 2019, Molecular Genetics and Genomics.
[58] K. Chou,et al. iRNA-PseColl: Identifying the Occurrence Sites of Different RNA Modifications by Incorporating Collective Effects of Nucleotides into PseKNC , 2017, Molecular therapy. Nucleic acids.
[59] Chao Xu,et al. A Radioactivity-Based Assay for Screening Human m6A-RNA Methyltransferase, METTL3-METTL14 Complex, and Demethylase ALKBH5 , 2016, Journal of biomolecular screening.
[60] Cross-talk between m6A and m1A regulators, YTHDF2 and ALKBH3 fine-tunes mRNA expression , 2019, bioRxiv.
[61] M. Sekiguchi,et al. Binding capacity of human YB-1 protein for RNA containing 8-oxoguanine. , 2002, Biochemistry.
[62] K. Chou,et al. iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. , 2015, Analytical biochemistry.
[63] Lydia M. Contreras,et al. Understanding the Functional Impact of VOC-Ozone Mixtures on the Chemistry of RNA in Epithelial Lung Cells. , 2020, Research report.
[64] Ralph E. Kleiner,et al. RNA Chemical Proteomics Reveals the N6-Methyladenosine (m6A)-Regulated Protein-RNA Interactome. , 2017, Journal of the American Chemical Society.
[65] Ming Zhang,et al. Accurate RNA 5-methylcytosine site prediction based on heuristic physical-chemical properties reduction and classifier ensemble. , 2018, Analytical biochemistry.
[66] Jionglong Su,et al. WHISTLE: a high-accuracy map of the human N6-methyladenosine (m6A) epitranscriptome predicted using a machine learning approach , 2019, Nucleic acids research.
[67] Xiujuan Lei,et al. Bioinformatics approaches for deciphering the epitranscriptome: Recent progress and emerging topics , 2020, Computational and structural biotechnology journal.
[68] Olivier Elemento,et al. 5′ UTR m6A Promotes Cap-Independent Translation , 2015, Cell.
[69] Bifeng Yuan,et al. ALKBH1 demethylates N3-methylcytidine in mRNA of mammals. , 2019, ACS chemical biology.
[70] Janusz M Bujnicki,et al. Computational modeling of protein-RNA complex structures. , 2014, Methods.
[71] Xuemei Chen,et al. YTHDF2 Binds to 5-Methylcytosine in RNA and Modulates the Maturation of Ribosomal RNA. , 2019, Analytical chemistry.
[72] Amit Sagar,et al. Recent Advances in Machine Learning Based Prediction of RNA-protein Interactions. , 2019, Protein and peptide letters.
[73] K. Schulten,et al. Molecular Mechanism of Processive 3' to 5' RNA Translocation in the Active Subunit of the RNA Exosome Complex. , 2016, Journal of the American Chemical Society.
[74] Henning Urlaub,et al. Human METTL16 is a N6‐methyladenosine (m6A) methyltransferase that targets pre‐mRNAs and various non‐coding RNAs , 2017, EMBO reports.
[75] David S. Goodsell,et al. RCSB Protein Data Bank: biological macromolecular structures enabling research and education in fundamental biology, biomedicine, biotechnology and energy , 2018, Nucleic Acids Res..
[76] J. Bähler,et al. In silico characterization and prediction of global protein–mRNA interactions in yeast , 2011, Nucleic acids research.
[77] J. Simpson,et al. New Twists in Detecting mRNA Modification Dynamics , 2020, Trends in Biotechnology.
[78] Chuan He,et al. Post-transcriptional gene regulation by mRNA modifications , 2016, Nature Reviews Molecular Cell Biology.
[79] J. Mauer,et al. FTO controls reversible m6Am RNA methylation during snRNA biogenesis , 2019, Nature Chemical Biology.
[80] Ralph E. Kleiner,et al. YTHDF2 recognition of N1-methyladenosine (m1A)-modified RNA is associated with transcript destabilization. , 2019, ACS chemical biology.
[81] David R. Liu,et al. Programmable m6A modification of cellular RNAs with a Cas13-directed methyltransferase , 2020, Nature Biotechnology.
[82] A. Caflisch,et al. A Reader-Based Assay for m6A Writers and Erasers. , 2019, Analytical chemistry.
[83] Lydia M. Contreras,et al. Post-transcriptional air pollution oxidation to the cholesterol biosynthesis pathway promotes pulmonary stress phenotypes , 2020, Communications Biology.
[84] Schraga Schwartz,et al. TRUB1 is the predominant pseudouridine synthase acting on mammalian mRNA via a predictable and conserved code. , 2017, Genome research.
[85] Yan-Hui Li,et al. PPUS: a web server to predict PUS-specific pseudouridine sites , 2015, Bioinform..
[86] Arne Klungland,et al. ALKBH5 is a mammalian RNA demethylase that impacts RNA metabolism and mouse fertility. , 2013, Molecular cell.
[87] Yinsheng Wang,et al. Identification of YTH Domain-Containing Proteins as the Readers for N1-Methyladenosine in RNA. , 2018, Analytical chemistry.
[88] Stefanie M. Kellner,et al. NAIL‐MS in E. coli Determines the Source and Fate of Methylation in tRNA , 2018, Chembiochem : a European journal of chemical biology.
[89] C. Hall,et al. Amino Acid Signature Enables Proteins to Recognize Modified tRNA , 2014, Biochemistry.
[90] K. Nakayama,et al. Human proteins that specifically bind to 8-oxoguanine-containing RNA and their responses to oxidative stress. , 2010, Biochemical and biophysical research communications.
[91] Miao Yu,et al. A METTL3-METTL14 complex mediates mammalian nuclear RNA N6-adenosine methylation , 2013, Nature chemical biology.
[92] Lydia M. Contreras,et al. RNA oxidation in chromatin modification and DNA-damage response following exposure to formaldehyde , 2020, Scientific Reports.
[93] Yu-Sheng Chen,et al. Dynamic transcriptomic m6A decoration: writers, erasers, readers and functions in RNA metabolism , 2018, Cell Research.
[94] K. Jung,et al. NAIL-MS reveals the repair of 2-methylthiocytidine by AlkB in E. coli , 2019, Nature Communications.
[95] W. Gilbert,et al. Messenger RNA modifications: Form, distribution, and function , 2016, Science.
[96] Zhike Lu,et al. m6A-dependent regulation of messenger RNA stability , 2013, Nature.
[97] A. Masoudi-Nejad,et al. RPINBASE: An online toolbox to extract features for predicting RNA-protein interactions. , 2020, Genomics.
[98] M. Sekiguchi,et al. Human polynucleotide phosphorylase protein in response to oxidative stress. , 2006, Biochemistry.
[99] C. Felser,et al. Imaging and writing magnetic domains in the non-collinear antiferromagnet Mn3Sn , 2019, Nature Communications.
[100] Max J. Kellner,et al. RNA editing with CRISPR-Cas13 , 2017, Science.
[101] Hong-min Liu,et al. Development of formaldehyde dehydrogenase‐coupled assay and antibody‐based assays for ALKBH5 activity evaluation , 2019, Journal of pharmaceutical and biomedical analysis.
[102] Mark Sherman,et al. Computational approaches in design of nucleic acid-based therapeutics. , 2018, Current opinion in biotechnology.
[103] Zefeng Wang,et al. Expanding RNA binding specificity and affinity of engineered PUF domains , 2018, Nucleic acids research.
[104] Hui Ding,et al. iRNA(m6A)-PseDNC: Identifying N6-methyladenosine sites using pseudo dinucleotide composition. , 2018, Analytical biochemistry.
[105] Chuan He,et al. Targeted m6A Reader Proteins To Study Epitranscriptomic Regulation of Single RNAs. , 2018, Journal of the American Chemical Society.
[106] Cindy Q. Tang,et al. Author Correction: Identifying long-term stable refugia for relict plant species in East Asia , 2018, Nature Communications.
[107] Xin-Yuan Fu,et al. Three distinct 3-methylcytidine (m3C) methyltransferases modify tRNA and mRNA in mice and humans , 2017, The Journal of Biological Chemistry.
[108] P. Agris,et al. Post-Transcriptional Modifications of RNA: Impact on RNA Function and Human Health , 2016 .
[109] M. Wainberg,et al. Multiple forms of tRNA(Lys3) in HIV-1. , 1996, Biochemical and biophysical research communications.
[110] Magnar Bjørås,et al. Human and bacterial oxidative demethylases repair alkylation damage in both RNA and DNA , 2003, Nature.
[111] Yan Huang,et al. RNAm5Cfinder: A Web-server for Predicting RNA 5-methylcytosine (m5C) Sites Based on Random Forest , 2018, Scientific Reports.