Challenges and opportunities in technologies and methods for lncRNA structure determination.

Area of Science:

• Molecular Biology
• Structural Biology
• Genomics

Background:

• Long non-coding RNAs (lncRNAs) are crucial regulators of gene expression and epigenetic modifications.
• Despite numerous identified lncRNA genes, their structure-function relationships are poorly understood.
• Accurate determination of lncRNA structure is essential for elucidating their biological roles.

Purpose of the Study:

• To review the current methodologies for determining lncRNA structure.
• To highlight the limitations of existing experimental and computational approaches.
• To discuss emerging techniques for advancing lncRNA structural studies.

Main Methods:

• Experimental methods: Chemical probing (SHAPE, DMS).
• Computational prediction methods.
• Advanced imaging: Cryo-electron microscopy, atomic force microscopy.
• Machine learning algorithms.

Main Results:

• Existing methods face challenges with RNA dynamics, heterogeneity, and non-physiological conditions (e.g., Mg²⁺ concentration).
• Predicting long-range interactions and pseudoknots remains difficult.
• Emerging techniques show potential for capturing realistic RNA conformations under physiological conditions.

Conclusions:

• Advances in cryo-EM, AFM, and machine learning are crucial for understanding lncRNA architecture and dynamics.
• Accurate structural insights will redefine our understanding of lncRNA functions.
• This knowledge can drive structure-based drug discovery and therapeutic strategies targeting lncRNAs.