AUTHOR=Zhang Lin , Chen Shutao , Ma Jiani , Liu Zhaoyang , Liu Hui 

TITLE=REW-ISA V2: A Biclustering Method Fusing Homologous Information for Analyzing and Mining Epi-Transcriptome Data

JOURNAL=Frontiers in Genetics

VOLUME=12

YEAR=2021

URL=https://www.frontiersin.org/journals/genetics/articles/10.3389/fgene.2021.654820

DOI=10.3389/fgene.2021.654820

ISSN=1664-8021

ABSTRACT=<p><bold>Background:</bold> Previous studies have shown that N6-methyladenosine (m<sup>6</sup>A) is related to many life processes and physiological and pathological phenomena. However, the specific regulatory mechanism of m<sup>6</sup>A sites at the systematic level is not clear. Therefore, mining the RNA co-methylation patterns in the epi-transcriptome data is expected to explain the specific regulation mechanism of m<sup>6</sup>A.</p><p><bold>Methods:</bold> Considering that the epi-transcriptome data contains homologous information (the genes corresponding to the m<sup>6</sup>A sites and the cell lines corresponding to the experimental conditions), rational use of this information will help reveal the regulatory mechanism of m<sup>6</sup>A. Therefore, based on the RNA expression weighted iterative signature algorithm (REW-ISA), we have fused homologous information and developed the REW-ISA V2 algorithm.</p><p><bold>Results:</bold> Then, REW-ISA V2 was applied in the MERIP-seq data to find potential local function blocks (LFBs), where sites are hyper-methylated simultaneously across the specific conditions. Finally, REW-ISA V2 obtained fifteen LFBs. Compared with the most advanced biclustering algorithm, the LFBs obtained by REW-ISA V2 have more significant biological significance. Further biological analysis showed that these LFBs were highly correlated with some signal pathways and m<sup>6</sup>A methyltransferase.</p><p><bold>Conclusion:</bold> REW-ISA V2 fuses homologous information to mine co-methylation patterns in the epi-transcriptome data, in which sites are co-methylated under specific conditions.</p>