期刊
METHODS
卷 69, 期 3, 页码 274-281出版社
ACADEMIC PRESS INC ELSEVIER SCIENCE
DOI: 10.1016/j.ymeth.2014.06.008
关键词
RNA methylation; MeRIP-Seq; exomePeak; Differential RNA methylation; N6-methyladenosine (m6A)
资金
- National Natural Science Foundation of China [61170134, 81373469, 61201408]
- National Institutes of Health [NIH-NCIP30CA54174]
- National Science Foundation [CCF-0546345]
- Qatar National Research Fund [09-874-3-235]
- Fundamental Research Funds for the Central Universities [2014QNA84, 2014QNB47]
- Jiangsu Natural Science Foundation [SBK2014041258]
- China Postdoctoral Science Foundation [2012M511816]
- National Institute on Minority Health and Health Disparities from the National Institutes of Health [G12MD007591]
- Division of Computing and Communication Foundations
- Direct For Computer & Info Scie & Enginr [1246073] Funding Source: National Science Foundation
Despite the prevalent studies of DNA/Chromatin related epigenetics, such as, histone modifications and DNA methylation, RNA epigenetics has not drawn deserved attention until a new affinity-based sequencing approach MeRIP-Seq was developed and applied to survey the global mRNA N6-methyladenosine (m(6)A) in mammalian cells. As a marriage of ChIP-Seq and RNA-Seq, MeRIP-Seq has the potential to study the transcriptome-wide distribution of various post-transcriptional RNA modifications. We have previously developed an R/Bioconductor package 'exomePeak' for detecting RNA methylation sites under a specific experimental condition or the identifying the differential RNA methylation sites in a case control study from MeRIP-Seq data. Compared with other relatively well studied data types such as ChIP-Seq and RNA-Seq, the study of MeRIP-Seq data is still at very early stage, and existing protocols are not optimized for dealing with the intrinsic characteristic of MeRIP-Seq data. We therein provide here a detailed and easy-to-use protocol of using exomePeak R/Bioconductor package along with other software programs for analysis of MeRIP-Seq data, which covers raw reads alignment, RNA methylation site detection, motif discovery, differential RNA methylation analysis, and functional analysis. Particularly, the rationales behind each processing step as well as the specific method used, the best practice, and possible alternative strategies are briefly discussed. (C) 2014 Elsevier Inc. All rights reserved.
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