LncRNA Subcellular Localization Signals – Are the Two Ends Equal? A Machine Learning Analysis Across Multiple Cell Lines

In this work, we studied the question of whether the two ends of long non-coding ribonucleic acids (lncRNAs) (i.e., the 5′ end and 3′end) carry similar information about subcellular localization of lncRNAs. We considered this problem from three viewpoints using machine learning models: (1) consideration of the classification performance of the machine learning models using features from defined regions (or segments) along the sequence, (2) correlation-based analysis using models built on regions/segments along the LncRNA sequence, and (3) analysis of the relative positions of predicted lncRNA localization motifs along the LncRNA sequence. Our results and observations suggest that the 5′ region of the lncRNA sequences (the prefixes) tend to carry more localization signals when compared with the 3′ region (the suffixes) of the sequences. These could have implications on how we use machine learning models for improved analysis of lncRNA subcellular localization.