Single-nucleotide modifications of RNA, or RNA editing, is an important regulatory
mechanism in the cell. However, understanding of its regulation is far from complete,
as transcriptome-wide quantitation of the RNA editing is complicated and requires
developement of new computational approaches. Most tools for RNA editing analysis
are limited to the search of potential editing sites and do not support the analysis of
differential editing (DEd). On the other hand, great number of approaches exists for
analysis of differential methylation (DM), specifically, bisulfite sequencing, which is
similar in data modality to the RNA editing. In this project we aimed to evaluate
applicability of existing tools and statistical approaches for analyses of bisulfite
sequencing data, for discovery of DEd events.
We attempted to identify DEd sites and genes in the RNASeq data of BT20 cell line.
The samples were prepared either under hypoxia or in normoxia, three replicates per
condition. Previously, in a work by Irina Shchukina, a tool for discovery of A to I
RNA editing events in RNASeq data was developed. The output of this tool listing
editing sites determined in the cell line was used as the data for the subsequent
analysis. edgeR pipeline for analysis of DM was modified here to apply for the DEd
analysis both at single-nucleotide and at gene level. As the result we obtained lists of
DEd sites and genes in the sample, and found that RNA editing of approximately 100
genes is enhanced under hypoxia. GO-enrichement analysis of the gene list revealed
that RNA editing is enhanced during hypoxia in genes acting in ribosome biogenesis,
mitochondrial translation, and transcriptional regulation associated with hypoxia.
Thus, edgeR DM pipeline can be used for differential RNA editing analysis. Slides