Year: 2014
Type: article
Abstract: Methyltranscriptome is an exciting new area that studies the mechanisms and functions of methylation in transcripts. The MethylTranscriptome DataBase (MeT-DB, http://compgenomics.utsa.edu/methylation/) is the first comprehensive resource for N6-methyladenosine (m(6)A) in mammalian transcriptome. It includes a database that records publicaly available data sets from methylated RNA immunoprecipitation sequencing (MeRIP-Seq), a recently developed technology for interrogating m(6)A methyltranscriptome. MeT-DB includes ∼ 300 k m(6)A methylation sites in 74 MeRIP-Seq samples from 22 different experimental conditions predicted by exomePeak and MACS2 algorithms. To explore this rich information, MeT-DB also provides a genome browser to query and visualize context-specific m(6)A methylation under different conditions. MeT-DB also includes the binding site data of microRNA, splicing factor and RNA binding proteins in the browser window for comparison with m(6)A sites and for exploring the potential functions of m(6)A. Analysis of differential m(6)A methylation and the related differential gene expression under two conditions is also available in the browser. A global perspective of the genome-wide distribution of m(6)A methylation in all the data is provided in circular ideograms, which also act as a navigation portal. The query results and the entire data set can be exported to assist publication and additional analysis.
Source: Nucleic Acids Research
DOI: 10.1093/nar/gku1024
Language: English
Topic: RNA modifications and cancer
Subfield: Molecular Biology
Domain: Life Sciences
Open Access status: gold
Estimated APC paid: $3,992
Funders: National Science Foundation, Cancer Research Institute, University of Texas at San Antonio, National Natural Science Foundation of China, Natural Science Foundation of Jiangsu Province, National Institutes of Health, Fundamental Research Funds for the Central Universities, National Cancer Institute, National Institute of General Medical Sciences, National Center for Advancing Translational Sciences, National Institute on Minority Health and Health Disparities
Awards: G1281635818, G1329658801, G1568892320, G1802529437, G1825386480, Collaborative Research:Graphical models for characterizing global RNA methylation, G2545609793, G2552195467, G2590787781, G2975828918, G3081769533, G3335728709, G3378181322, Institute for Integration of Medicine & Science: A Partnership to Improve Health, G3910833379, G4280027024, G4703631424, RCMI Center for Interdiscplinary Health Research CIHR, G5323848611, G5356081367, G5517889021, G5971589581, G6105854417, AF: EAGER: Bayesian Factor Modeling of Context-Specific Gene Regulation, G6761208641, G7341503566, G7647881904, G7814350357, G8502137567, G8685888430, G877591353, G8780295424, G8942474622, G956896106
OpenAlex ID: W2143451174