TY - JOUR
T1 - Predict Epitranscriptome Targets and Regulatory Functions of N6-Methyladenosine (m6A) Writers and Erasers
AU - Song, Yiyou
AU - Xu, Qingru
AU - Wei, Zhen
AU - Zhen, Di
AU - Su, Jionglong
AU - Chen, Kunqi
AU - Meng, Jia
N1 - Funding Information:
Supplemental material, Supplement_Table_3 for Predict Epitranscriptome Targets and Regulatory Functions of N6-Methyladenosine (m6A) Writers and Erasers by Yiyou Song, Qingru Xu, Zhen Wei, Di Zhen, Jionglong Su, Kunqi Chen and Jia Meng in Evolutionary Bioinformatics Funding: The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work has been supported by National Natural Science Foundation of China (31671373), Jiangsu University Natural Science Program (16KJB180027), XJTLU Key Program Special Fund (KSF-T-01), and Jiangsu Six Talent Peak Program (XYDXX-118). Declaration of conflicting interests: The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article. Author Contributions JM and KC conceived the idea and designed the research; ZW processed the raw data; YS, QX, and DZ performed the prediction analysis; YS and QX drafted the manuscript first. All authors read, critically revised, and approved the final manuscript. ORCID iD Kunqi Chen https://orcid.org/0000-0002-6025-8957 Supplemental Material Supplemental material for this article is available online.
Publisher Copyright:
© The Author(s) 2019.
PY - 2019
Y1 - 2019
N2 - Currently, although many successful bioinformatics efforts have been reported in the epitranscriptomics field for N6-methyladenosine (m6A) site identification, none is focused on the substrate specificity of different m6A-related enzymes, ie, the methyltransferases (writers) and demethylases (erasers). In this work, to untangle the target specificity and the regulatory functions of different RNA m6A writers (METTL3-METT14 and METTL16) and erasers (ALKBH5 and FTO), we extracted 49 genomic features along with the conventional sequence features and used the machine learning approach of random forest to predict their epitranscriptome substrates. Our method achieved reasonable performance on both the writer target prediction (as high as 0.918) and the eraser target prediction (as high as 0.888) in a 5-fold cross-validation, and results of the gene ontology analysis of their preferential targets further revealed the functional relevance of different RNA methylation writers and erasers.
AB - Currently, although many successful bioinformatics efforts have been reported in the epitranscriptomics field for N6-methyladenosine (m6A) site identification, none is focused on the substrate specificity of different m6A-related enzymes, ie, the methyltransferases (writers) and demethylases (erasers). In this work, to untangle the target specificity and the regulatory functions of different RNA m6A writers (METTL3-METT14 and METTL16) and erasers (ALKBH5 and FTO), we extracted 49 genomic features along with the conventional sequence features and used the machine learning approach of random forest to predict their epitranscriptome substrates. Our method achieved reasonable performance on both the writer target prediction (as high as 0.918) and the eraser target prediction (as high as 0.888) in a 5-fold cross-validation, and results of the gene ontology analysis of their preferential targets further revealed the functional relevance of different RNA methylation writers and erasers.
KW - N-methyladenosine (mA)
KW - RNA methylation
KW - epitranscriptome
KW - random forest
KW - target prediction
UR - http://www.scopus.com/inward/record.url?scp=85073693431&partnerID=8YFLogxK
U2 - 10.1177/1176934319871290
DO - 10.1177/1176934319871290
M3 - Article
AN - SCOPUS:85073693431
SN - 1176-9343
VL - 15
JO - Evolutionary Bioinformatics
JF - Evolutionary Bioinformatics
ER -