Scientists have extensively researched the structure and sequence of genetic material and its interactions with proteins in the hope of understanding how our genetics and environment interact in diseases. This research has partly focused on 'epigenetic marks', which are chemical modifications to DNA, RNA, and the associated proteins (known as histones).

 

Epigenetic marks influence when and how genes get switched on or off. They can also instruct cells about how to interpret and use genetic information, influencing various cellular processes. Changes in epigenetic marks therefore significantly impact gene regulation and cellular functions, which means they might contribute to disease. By studying epigenetic marks, researchers can clarify their role in health and disease and potentially discover new avenues for treatment. While researchers can identify and compare epigenetic marks, understanding the correlation between specific modifications and how genes work has remained challenging. To help overcome this, Dr Dan Ohtan Wang and Dr Kandarp Joshi have created a new tool called epidecodeR. The user-friendly tool, published in Briefings in Bioinformatics, enables biologists to quickly check if a modification affects how a gene responds in specific situations.

 

The team used statistical methods to categorize groups of genes based on how many modifications they had. They showed that EpidecodeR can predict the role of specific modifications, such as altering certain proteins or using drugs, and how these could impact gene activity. Researchers also found epidecodeR to be effective in identifying substances that can block another protein, called RNA demethylase, and we explored how changes in proteins called histones might be related to drug abuse. The researchers plan to conduct further studies to improve epidecodeR's accuracy and specificity.