Identifying RNA-binding protein motifs enriched with ALS-associated mutations through a systematic framework.

Abstract

RNA regulation is a complex process involving several essential contributors, such as RNA-binding proteins (RBPs). RBPs bind to RNA via RNA-binding domains (RBDs), which contain small conserved sequences called motifs. Impaired functioning of RBPs has been linked to the development of neurodegenerative and neurodevelopmental diseases. Amyotrophic lateral sclerosis (ALS) is an aggressive motor neuron disease with a poor survival prognosis. Mutations that alter the proper functioning of the RBP TDP-43 have been observed in patients who develop ALS. Motifs are essential for RBPs to bind to RNA; if mutations affect motifs, they could influence RBP binding. For instance, mutations found at the location of motifs in UNC13A disturbed the binding of TDP-43 and affected the degradation process of this mRNA, demonstrating the importance of motifs and the effects mutations have on RBP interactions.

This proposal focuses on developing a framework for identifying motifs, cross-referencing them with ALS patient-derived mutations, and clustering genetic variants that affect the same motifs to determine whether certain motifs are more likely to be targets of mutations than others. Currently, several in silico tools are available to discover RBP motifs using RNA sequences (iDeepS) or secondary structure features (PrismNet). Furthermore, the ENCODE Phase III database contains extensive information on 356 RBPs. This allows the annotation of motifs found with PrismNet and iDeepS, cross-referencing them to ALS-associated mutations, and discovering their role in RNA regulation, thus facilitating a more focused approach to identifying affected RBPs and at-risk RNA regulatory functions.