The first steps of embryogenesis lack transcription and rely on maternal mRNAs stored in oocytes. Thus, maternal mRNA stability is tightly regulated. A-to-I RNA editing is the most common RNA modification, which is important for normal embryonic development and regulation of innate immunity. Using dozens high-throughput sequencing databases, we are testing if edited mRNAs are inherited to prevent activation of the immunity system against self RNA in the next generations.
A-to-I RNA editing is the most prevalent type of RNA editing in metazoans. As part of this project, we generated RESIC, an efficient pipeline that combines several approaches for the detection and classification of RNA editing sites. The pipeline can be used for all organisms and can use any number of RNA-sequencing datasets as input. Testing this tool on SARS-CoV-2 infection, our analysis implies the involvement of RNA editing in conceiving the unpredicted phenotype of COVID-19 disease.
Differential Expression Analysis (DEA) of RNA-sequencing data is frequently performed for detecting key genes, affected across different conditions. Preceding reliability-testing of the input material is crucial for consistent and strong results, yet can be challenging. In this project, we generated a tool: Biological Sequence Expression Kit (BiSEK) – a UI-based platform for DEA, dedicated to a reliable inquiry.
BiSEK is based on a novel algorithm to track discrepancies between the data and the statistical model design.