Comparative Analysis of Human Genes Frequently and Occasionally Regulated by mA Modification.
10.1016/j.gpb.2018.01.001
- Author:
Yuan ZHOU
1
;
Qinghua CUI
2
Author Information
1. Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China. Electronic address: zhouyuanbioinfo@bjmu.edu.cn.
2. Department of Biomedical Informatics, School of Basic Medical Sciences, Peking University, Beijing 100191, China. Electronic address: cuiqinghua@hsc.pku.edu.cn.
- Publication Type:Journal Article
- Keywords:
Epitranscriptome;
Gene expression regulation;
Gene importance;
Signaling network;
m(6)A
- MeSH:
Adenosine;
analogs & derivatives;
metabolism;
Gene Expression Regulation;
Gene Regulatory Networks;
Humans;
MicroRNAs;
metabolism;
Organ Specificity;
Signal Transduction
- From:
Genomics, Proteomics & Bioinformatics
2018;16(2):127-135
- CountryChina
- Language:English
-
Abstract:
The mA modification has been implicated as an important epitranscriptomic marker, which plays extensive roles in the regulation of transcript stability, splicing, translation, and localization. Nevertheless, only some genes are repeatedly modified across various conditions and the principle of mA regulation remains elusive. In this study, we performed a systems-level analysis of human genes frequently regulated by mA modification (mAfreq genes) and those occasionally regulated by mA modification (mAocca genes). Compared to the mAocca genes, the mAfreq genes exhibit gene importance-related features, such as lower dN/dS ratio, higher protein-protein interaction network degree, and reduced tissue expression specificity. Signaling network analysis indicates that the mAfreq genes are associated with downstream components of signaling cascades, high-linked signaling adaptors, and specific network motifs like incoherent feed forward loops. Moreover, functional enrichment analysis indicates significant overlaps between the mAfreq genes and genes involved in various layers of gene expression, such as being the microRNA targets and the regulators of RNA processing. Therefore, our findings suggest the potential interplay between mA epitranscriptomic regulation and other gene expression regulatory machineries.
