Identification of Transcription Factors, Biological Pathways, and Diseases as Mediated by N6-methyladenosine Using Tensor Decomposition-Based Unsupervised Feature Extraction

N6-methyladenosine (m6A) editing is the most common RNA modification known to contribute to various biological processes. Nevertheless, the mechanism by which m6A regulates transcription is unclear. Recently, it was proposed that m6A controls transcription through histone modification, although no c...

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Bibliographic Details
Published inApplied sciences Vol. 11; no. 1; p. 213
Main Authors Taguchi, Y-h., Dharshini, S. Akila Parvathy, Gromiha, M. Michael
Format Journal Article
LanguageEnglish
Published Basel MDPI AG 01.01.2021
Subjects
Alzheimer's disease
Biological activity
Datasets
Decomposition
Diseases
Editing
Embryo cells
feature extraction
Gene expression
Genes
histone modification
Histones
N6-methyladenosine
RNA modification
Stem cell transplantation
Stem cells
tensor decomposition
Transcription factors
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Summary:N6-methyladenosine (m6A) editing is the most common RNA modification known to contribute to various biological processes. Nevertheless, the mechanism by which m6A regulates transcription is unclear. Recently, it was proposed that m6A controls transcription through histone modification, although no comprehensive analysis using this dataset was performed. In this study, we applied tensor decomposition (TD)-based unsupervised feature extraction (FE) to a dataset composed of mouse embryonic stem cells (mESC) and a human cancer cell line (HEC-1-A) and successfully identified two sets of genes significantly overlapping between humans and mice (63 significantly overlapped genes among a total of 16,763 genes common to the two species). These significantly overlapped genes occupy at most 10% genes from both gene sets. Using these two sets of genes, we identified transcription factors (TFs) that m6A might recruit, biological processes that m6A might contribute to, and diseases that m6A might cause; they also largely overlap with each other. Since they were commonly identified using two independent datasets, the results regarding these TFs, biological processes, and diseases should be highly robust and trustworthy. It will help us to understand the mechanisms by which m6A contributes to biological processes.
ISSN:2076-3417
2076-3417
DOI:10.3390/app11010213