AthMethPre: a web server for the prediction and query of mRNA m6A sites in Arabidopsis thaliana.

N6-Methyladenosine (m6A) is the most prevalent and abundant modification in mRNA that has been linked to many key biological processes. High-throughput experiments have generated m6A-peaks across the transcriptome of A. thaliana, but the specific methylated sites were not assigned, which impedes the understanding of m6A functions in plants. Therefore, computational prediction of mRNA m6A sites becomes emergently important. Here, we present a method to predict the m6A sites for A. thaliana mRNA sequence(s). To predict the m6A sites of an mRNA sequence, we employed the support vector machine to build a classifier using the features of the positional flanking nucleotide sequence and position-independent k-mer nucleotide spectrum. Our method achieved good performance and was applied to a web server to provide service for the prediction of A. thaliana m6A sites. The server also provides a comprehensive database of predicted transcriptome-wide m6A sites and curated m6A-seq peaks from the literature for query and visualization. The AthMethPre web server is the first web server that provides a user-friendly tool for the prediction and query of A. thaliana mRNA m6A sites, which is freely accessible for public use at .

[1]  L. Stein,et al.  JBrowse: a next-generation genome browser. , 2009, Genome research.

[2]  Zhike Lu,et al.  m6A-dependent regulation of messenger RNA stability , 2013, Nature.

[3]  S. Tavazoie,et al.  N6-methyladenosine marks primary microRNAs for processing , 2015, Nature.

[4]  O. Elemento,et al.  Comprehensive Analysis of mRNA Methylation Reveals Enrichment in 3′ UTRs and near Stop Codons , 2012, Cell.

[5]  Q. Cui,et al.  SRAMP: prediction of mammalian N6-methyladenosine (m6A) sites based on sequence-derived features , 2016, Nucleic acids research.

[6]  Martin Madera,et al.  Improving protein secondary structure prediction using a simple k-mer model , 2010, Bioinform..

[7]  Yi Zhang,et al.  A k-mer scheme to predict piRNAs and characterize locust piRNAs , 2011, Bioinform..

[8]  Yang Wang,et al.  N6-methyladenosine modification destabilizes developmental regulators in embryonic stem cells , 2014, Nature Cell Biology.

[9]  M. Kupiec,et al.  Topology of the human and mouse m6A RNA methylomes revealed by m6A-seq , 2012, Nature.

[10]  Gideon Rechavi,et al.  Transcriptome-wide mapping of N6-methyladenosine by m6A-seq based on immunocapturing and massively parallel sequencing , 2013, Nature Protocols.

[11]  Xiaohong Zhu,et al.  Transcriptome-wide high-throughput deep m6A-seq reveals unique differential m6A methylation patterns between three organs in Arabidopsis thaliana , 2015, Genome Biology.

[12]  Wei Chen,et al.  Identification and analysis of the N6-methyladenosine in the Saccharomyces cerevisiae transcriptome , 2015, Scientific Reports.

[13]  Christopher E. Mason,et al.  Single-nucleotide resolution mapping of m6A and m6Am throughout the transcriptome , 2015, Nature Methods.

[14]  K. Chou,et al.  iRNA-Methyl: Identifying N(6)-methyladenosine sites using pseudo nucleotide composition. , 2015, Analytical biochemistry.

[15]  Chih-Jen Lin,et al.  LIBSVM: A library for support vector machines , 2011, TIST.

[16]  Arne Klungland,et al.  A majority of m6A residues are in the last exons, allowing the potential for 3′ UTR regulation , 2015, Genes & development.

[17]  J. Bujnicki,et al.  MODOMICS: a database of RNA modification pathways—2013 update , 2012, Nucleic Acids Res..

[18]  Yu Xue,et al.  MeMo: a web tool for prediction of protein methylation modifications , 2006, Nucleic Acids Res..

[19]  Bernhard E. Boser,et al.  A training algorithm for optimal margin classifiers , 1992, COLT '92.

[20]  Mark Goadrich,et al.  The relationship between Precision-Recall and ROC curves , 2006, ICML.

[21]  Michel Herzog,et al.  MTA Is an Arabidopsis Messenger RNA Adenosine Methylase and Interacts with a Homolog of a Sex-Specific Splicing Factor[W][OA] , 2008, The Plant Cell Online.

[22]  Morteza Mohammad Noori,et al.  Enhanced Regulatory Sequence Prediction Using Gapped k-mer Features , 2014, PLoS Comput. Biol..

[23]  K. Chou,et al.  pRNAm-PC: Predicting N(6)-methyladenosine sites in RNA sequences via physical-chemical properties. , 2016, Analytical biochemistry.

[24]  Schraga Schwartz,et al.  High-Resolution Mapping Reveals a Conserved, Widespread, Dynamic mRNA Methylation Program in Yeast Meiosis , 2013, Cell.

[25]  Zhike Lu,et al.  Unique Features of the m6A Methylome in Arabidopsis thaliana , 2014, Nature Communications.