Evolving Boolean Networks with RNA Editing
This work addresses the problem of understanding RNA editing mechanisms in genetic networks for researchers in computational biology, but it is incremental as it builds on abstract models without direct real-world application.
The paper investigates how RNA editing, which alters transcribed RNA sequences, can be selected through simulated evolution in Boolean genetic regulatory networks under single and multicellular scenarios, showing that dynamic sequence alteration via a guide RNA-inspired mechanism can evolve.
The editing of transcribed RNA by other molecules such that the form of the final product differs from that specified in the corresponding DNA sequence is ubiquitous. This paper uses an abstract, tunable Boolean genetic regulatory network model to explore aspects of RNA editing. In particular, it is shown how dynamically altering expressed sequences via a guide RNA-inspired mechanism can be selected for by simulated evolution under various single and multicellular scenarios.