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Microsatellite expansion disorders are pathologically characterized by RNA foci formation and repeat-associated non-AUG (RAN) translation. However, their underlying pathomechanisms and regulation of RAN translation remain unknown. We report that expression of expanded UGGAA (UGGAA) repeats, responsible for spinocerebellar ataxia type 31 (SCA31) in Drosophila, causes neurodegeneration accompanied by accumulation of UGGAA RNA foci and translation of repeat-associated pentapeptide repeat (PPR) proteins, consistent with observations in SCA31 patient brains. We revealed that motor-neuron disease (MND)-linked RNA-binding proteins (RBPs), TDP-43, FUS, and hnRNPA2B1, bind to and induce structural alteration of UGGAA. These RBPs suppress UGGAA-mediated toxicity in Drosophila by functioning as RNA chaperones for proper UGGAA folding and regulation of PPR translation. Furthermore, nontoxic short UGGAA repeat RNA suppressed mutated RBP aggregation and toxicity in MND Drosophila models. Thus, functional crosstalk of the RNA/RBP network regulates their own quality and balance, suggesting convergence of pathomechanisms in microsatellite expansion disorders and RBP proteinopathies.
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http://dx.doi.org/10.1016/j.neuron.2017.02.046 | DOI Listing |
Neurogenetics
September 2025
Nur International University, 54600, Lahore, Punjab, Pakistan.
Huntington's disease (HD) is a progressive, autosomal dominant neurodegenerative disorder characterized by motor dysfunction, cognitive decline, and psychiatric disturbances. It is caused by CAG repeat expansions in the HTT gene, resulting in the formation of mutant huntingtin protein that aggregates and disrupts neuronal function. This review outlines the pathogenesis of HD, including genetic, molecular, and environmental factors.
View Article and Find Full Text PDFBMC Neurol
September 2025
National Health Commission Key Laboratory of Molecular Probes and Targeted Diagnosis and Therapy, Harbin Medical University, Harbin, 150081, China.
Background: Hereditary ataxias (HAs) are neurodegenerative disorders characterized by progressive cerebellar degeneration, with autosomal dominant spinocerebellar ataxias (SCAs) representing the most prevalent subtype. SCA3, the most common form worldwide, is caused by CAG repeat expansions in ATXN3, resulting in pathogenic ataxin-3 aggregation. However, the underlying molecular mechanisms driving disease progression remain incompletely understood.
View Article and Find Full Text PDFGenes (Basel)
July 2025
Victor Babes National Institute of Pathology, 050096 Bucharest, Romania.
Background/objectives: Autism spectrum disorders (ASDs) are neurodevelopmental conditions with early onset of clinical manifestations. ASD etiology is highly heterogeneous, with genetic factors being strong determinants of the behavioral problems and neurodevelopmental deficits. Fragile X syndrome (FXS) (OMIM #300624), caused by the transcriptional silencing of the gene, represents the most common monogenic cause of autism.
View Article and Find Full Text PDFBiol Methods Protoc
August 2025
Département Génomes & Génétique, Institut Pasteur, Université de Paris, CNRS UMR 3525, 25 rue du Dr Roux, 75015, Paris, France.
DNA double-strand breaks (DSBs) represent critical events in genome integrity, arising from both endogenous cellular processes and exogenous factors. These breaks are implicated in various genomic aberrations and chromosomal rearrangements, leading to cancers and genetic disorders. Common and rare fragile sites, containing repetitive elements and non-B DNA structures, are particularly prone to breakage under replication stress, which play a pivotal role in cancer development and genetic diseases.
View Article and Find Full Text PDFCancer Treat Res
August 2025
Department of Medical Oncology, City of Hope National Medical Center, Duarte, CA, USA.
Artificial intelligence (AI) and machine learning (ML) are revolutionizing cancer immunotherapy by addressing the complex interplay between cancer and the immune system. This chapter explores how AI technologies enhance immunotherapy development across multiple domains: antibody design, response prediction, biomarker identification, and T-cell target discovery. In therapeutic antibody design, AI improves efficiency through predictive modeling of antibody-antigen interactions, structure prediction tools, generative models that create novel antibody sequences, and developability optimization.
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