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RNA Biology: Unraveling the Complex Interplay Between Proteins and RNAs in Gene Expression and Regulation, 2nd Edition

A special issue of International Journal of Molecular Sciences (ISSN 1422-0067). This special issue belongs to the section "Molecular Genetics and Genomics".

Deadline for manuscript submissions: 20 August 2026 | Viewed by 175

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Institut de génétique humaine, UMR 9002, CNRS, Université de Montpellier, Gene Regulation Laboratory, 141, Rue de la Cardonille, 34396 Montpellier, France
Interests: transcription; ncRNAs; miRNAs; HIV; cancer
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Special Issue Information

Dear Colleagues,

This Special Issue, titled “RNA Biology: Unraveling the Complex Interplay Between Proteins and RNAs in Gene Expression and Regulation”, delves into the intricate dialog between proteins and RNAs that underpins gene expression and regulation. It highlights the latest advancements in our collective understanding of the diverse roles of RNAs—from their transcriptional genesis to post-transcriptional modifications—in shaping cellular function. We highlight the complexity of interactions between RNAs and proteins, including RNA-binding proteins that coordinate gene expression patterns and cellular responses. Furthermore, we encourage cutting-edge research on the emerging role of non-coding RNAs in gene regulation, epigenetic modifications, and disease pathogenesis. Through these studies, we can gain better insight into the dynamic and multifaceted nature of RNA biology, paving the way for future therapeutic interventions and biotechnological applications.

Dr. Rosemary Kiernan
Guest Editor

Manuscript Submission Information

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Keywords

  • RNA biology
  • protein–RNA interplay
  • gene expression
  • post-transcriptional modifications
  • non-coding RNAs

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Published Papers (1 paper)

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Research

20 pages, 965 KB  
Article
Sequence-Based Models for RNA–Protein Interactions Imputation Might Be Insufficient for Novel Signal Prediction in eCLIP Data
by Arsenii K. Rybakov, Daniil A. Khlebnikov, Daria Y. Ovchinnikova, Arina I. Nikolskaya, Arsenii O. Zinkevich and Andrey A. Mironov
Int. J. Mol. Sci. 2026, 27(3), 1192; https://doi.org/10.3390/ijms27031192 (registering DOI) - 24 Jan 2026
Abstract
Predicting specific RNA–protein interactions remains a challenging task. Despite the existence of numerous methods, a unified approach has yet to emerge. Additional difficulties emerge from the properties of in vivo IP experiments and their systematic biases, such as the overrepresentation of highly expressed [...] Read more.
Predicting specific RNA–protein interactions remains a challenging task. Despite the existence of numerous methods, a unified approach has yet to emerge. Additional difficulties emerge from the properties of in vivo IP experiments and their systematic biases, such as the overrepresentation of highly expressed RNAs. Here, we present the PLERIO machine learning framework, which utilizes eCLIP data for a single protein to reconstruct the full spectrum of its potential interactions with the cellular transcriptome (i.e., both highly expressed and lowly expressed RNAs). In an effort to extrapolate our methodology to a multi-protein paradigm for de novo prediction of RNA–protein interactions on proteins lacking available eCLIP data, we extended our approach to 220 cellular proteins. We then demonstrate that this approach might not be well tailored to the limitations of current in vivo immunoprecipitation data, and may only be meaningful for in vitro experiments such as RNAcompete. Full article
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