Approaches for Modes of Action Study of Long Non-Coding RNAs: From Single Verification to Genome-Wide Determination

Abstract

Long non-coding RNAs (lncRNAs) are transcripts longer than 200 nucleotides (nt) that are not translated into known functional proteins. This broad definition covers a large collection of transcripts with diverse genomic origins, biogenesis, and modes of action. Thus, it is very important to choose appropriate research methodologies when investigating lncRNAs with biological significance. Multiple reviews to date have summarized the mechanisms of lncRNA biogenesis, their localization, their functions in gene regulation at multiple levels, and also their potential applications. However, little has been reviewed on the leading strategies for lncRNA research. Here, we generalize a basic and systemic mind map for lncRNA research and discuss the mechanisms and the application scenarios of ‘up-to-date’ techniques as applied to molecular function studies of lncRNAs. Taking advantage of documented lncRNA research paradigms as examples, we aim to provide an overview of the developing techniques for elucidating lncRNA interactions with genomic DNA, proteins, and other RNAs. In the end, we propose the future direction and potential technological challenges of lncRNA studies, focusing on techniques and applications.

Underground communication: Long non-coding RNA signaling in the plant rhizosphere

“…The conventional approach to studying lncRNAs involves understanding the temporal transcription pattern of a specific lncRNA (“when” it is transcribed), documenting its associated phenotypic characteristics (“what” phenotypes it relates to), establishing its identity (“who” it is), determining its subcellular localization (“where” it localizes), and unraveling its mode of action (“how” it functions) ( Chen, 2022 ; Tao et al., 2023 ). It is particularly important to identify the phenotypes linked to an lncRNA and to ensure its biological relevance to the observed phenotype, addressing the “what” and “when” aspects ( Chen, 2022 ).…”