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Mechanical force orchestrates a myriad of cellular events including inhibition of axon regeneration, by locally activating the mechanosensitive ion channel Piezo enriched at the injured axon tip. However, the cellular mechanics underlying Piezo localization and function remains poorly characterized. We show that the RNA repair/splicing enzyme Rtca acts upstream of Piezo to modulate its expression and transport/targeting to the plasma membrane via Rab10 GTPase, whose expression also relies on Rtca.

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SRP9/SRP14 is a protein heterodimer that plays a critical role in the signal recognition particle through its interaction with the scaffolding signal recognition particle RNA (7SL). SRP9/SRP14 binding to 7SL is mediated through a conserved structural motif that is shared with the primate-specific Alu RNA. Alu RNA are transcription products of Alu elements, a retroelement that comprises ~10% of the human genome.

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Article Synopsis
  • Human plasma contains short structured RNAs called FLEXI RNAs, which have potential for use as biomarkers; a study identified over 9,000 different FLEXIs in human cell lines, highlighting their specific expression patterns depending on the cell type.
  • Researchers found 126 RNA-binding proteins (RBPs) that interact with FLEXI RNAs, which include factors involved in splicing, transcription, and cell growth, showing that these proteins play a significant role in regulating the RNA's functions.
  • The study also revealed that certain groups of RBPs tend to bind to FLEXIs from functionally related genes, indicating that these RBPs may work together to coordinate the expression of genes
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Exploring functional conservation in silico: a new machine learning approach to RNA-editing.

Brief Bioinform

May 2024

Departament de Genètica, Microbiologia i Estadística, Facultat de Biologia, Universitat de Barcelona, Av. Digonal 643, 08028 Barcelona, Spain.

Around 50 years ago, molecular biology opened the path to understand changes in forms, adaptations, complexity, or the basis of human diseases through myriads of reports on gene birth, gene duplication, gene expression regulation, and splicing regulation, among other relevant mechanisms behind gene function. Here, with the advent of big data and artificial intelligence (AI), we focus on an elusive and intriguing mechanism of gene function regulation, RNA editing, in which a single nucleotide from an RNA molecule is changed, with a remarkable impact in the increase of the complexity of the transcriptome and proteome. We present a new generation approach to assess the functional conservation of the RNA-editing targeting mechanism using two AI learning algorithms, random forest (RF) and bidirectional long short-term memory (biLSTM) neural networks with an attention layer.

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