Loc4Lnc: Accurate prediction of long noncoding RNA subcellular localization via enhanced RNA sequence representation

Abstract

Long noncoding RNAs (lncRNAs) are crucial in gene regulation, chromatin architecture, and cellular differentiation, playing significant roles in various diseases and serving as potential biomarkers and therapeutic targets. Understanding their precise subcellular localization is essential for elucidating their functions in biological pathways. Current methods for predicting lncRNA subcellular localization face challenges in capturing long-range interactions within sequences. Deep learning models often struggle with feature extraction that adequately represents these distant dependencies, leading to limited predictive accuracy. We develop Loc4Lnc, a deep learning framework for predicting lncRNA subcellular localization. The model integrates convolutional layers and transformer blocks to effectively capture both local sequence motifs and long-range dependencies within RNA sequences, followed by classification using TextCNN. Using the RNALocate v2.0 database, we constructed a benchmark dataset covering five subcellular locations (cytoplasm, nucleus, cytosol, chromatin, and exosome). The performance of the model is evaluated against existing feature extraction methods and existing predictors. Results of the Loc4Lnc study demonstrate significant improvements in predicting lncRNA subcellular localization. The model achieved a prediction accuracy of 0.636 on an independent test set, outperforming existing methodologies. Comparative evaluations showed that it consistently surpassed traditional feature extraction methods and state-of-the-art predictors, highlighting its robustness and effectiveness in accurately classifying lncRNAs across five distinct subcellular locations. Loc4Lnc effectively captures long-range interactions and optimizes information flow between distal elements, providing an effective predictive tool for the subcellular localization of lncRNAs and laying the foundation for future research on the regulation of gene expression and cellular functions by lncRNAs.

Keywords

lncRNA / long sequence analysis / subcellular localization

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The Author(s). Quantitative Biology published by John Wiley & Sons Australia, Ltd on behalf of Higher Education Press.