LoDEI: a robust and sensitive tool to detect transcriptome-wide differential A-to-I editing in RNA-seq data

Area of Science:

• Molecular Biology
• Genetics
• Bioinformatics

Background:

• RNA editing, specifically adenosine-to-inosine (A-to-I) editing mediated by Adenosine Deaminases Acting on RNA (ADAR), is a crucial post-transcriptional modification.
• A-to-I editing plays significant roles in human disease and immune regulation, driving interest in therapeutic applications using base editors.
• Accurate detection of differential A-to-I editing is essential for understanding its biological and therapeutic implications but remains a challenge.

Purpose of the Study:

• To develop a sensitive method for detecting differential A-to-I RNA editing in RNA sequencing datasets.
• To address the unmet need for analyzing the dynamics of A-to-I editing in biological and therapeutic contexts.

Main Methods:

• Introduction of the local differential editing index (LoDEI), a novel approach for detecting differential A-to-I editing.
• Utilizing a sliding-window strategy combined with empirical q-value calculation for enhanced detection sensitivity.
• Validation of LoDEI on both known and novel biological datasets.

Main Results:

• LoDEI demonstrates superior performance in detecting A-to-I editing sites compared to existing methods at the same false-discovery rate.
• The study identified that the oncogene MYCN actively increases A-to-I editing.
• A specific small non-coding RNA was found to reduce A-to-I editing levels.

Conclusions:

• LoDEI provides a sensitive and effective tool for analyzing differential A-to-I RNA editing.
• The findings highlight the regulatory roles of MYCN and specific small non-coding RNAs in modulating A-to-I editing.
• This advancement facilitates deeper investigation into the functional consequences of RNA editing in health and disease.