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Cited by 375RNA modifications and cancerEpigenetics and DNA MethylationRNA regulation and disease

A protocol for RNA methylation differential analysis with MeRIP-Seq data and exomePeak R/Bioconductor package

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Meng, Jia, Lu, Zhiliang, Liu, Hui, Zhang, Lin, Zhang, Shaowu, Chen, Yidong, Rao, Manjeet K., Huang, Yufei·2014·Methods
DOI 10.1016/j.ymeth.2014.06.008PMC PMC4194139
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Abstract

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. The exomePeak R/Bioconductor package is freely available from Bioconductor: http://www.bioconductor.org/packages/release/bioc/html/exomePeak.html.

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Authors
Meng, J., Lu, Z., Liu, H., Zhang, L., Zhang, S., Chen, Y., Rao, M. K., & Huang, Y.
Affiliations
  • Xi’an Jiaotong-Liverpool University (CN)
  • China University of Mining and Technology (CN)
  • The University of Texas at San Antonio Health Science Center (US)
Corresponding author
  • Meng, Jia
  • Huang, Yufei
ORCID
Venue
Methods
Publisher
Elsevier BV
Published
2014-10
Volume
69
Issue
3
Pages
274-281
ISSN
1046-2023 (ISSN-L)
DOI
10.1016/j.ymeth.2014.06.008
PMC
PMC4194139
OpenAlex
W2044676948
Cited by
375
References
7
Citations by year
2026: 35 · 2025: 43 · 2024: 56 · 2023: 54 · 2022: 61 · 2021: 47 · 2020: 24 · 2019: 16 · 2018: 12 · 2017: 10 · 2016: 7 · 2015: 5 · 2014: 5
FWCI
3.69
Type
journal article
Language
en
Open access
Licence
www.elsevier.com/tdm/userlicense/1.0/ (tdm)
Locations
  • Methods (publishedVersion)
  • PubMed (publishedVersion)
  • PubMed Central (acceptedVersion)
Funders
  • 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 (G12MD007591)
Topics
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA modifications and cancer
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › Epigenetics and DNA Methylation
  • Life Sciences › Biochemistry, Genetics and Molecular Biology › Molecular Biology › RNA regulation and disease
Keywords
MeRIP-seq, RNA methylation, N6-methyladenosine, epitranscriptomics, post-transcriptional RNA modification, motif discovery, read mapping, Bioconductor package, data analysis protocols
MeSH terms
Animals, Base Sequence, Humans, RNA, RNA Processing, Post-Transcriptional, RNA, Messenger, Software, Sequence Analysis, RNA, DNA Methylation, Epigenomics

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