Periodic Reporting for period 1 - UNDERPIN (Untranslated regions of RNAs and protein networks in pathological phase separation: UNDERPIN)
Reporting period: 2023-08-01 to 2025-07-31
Neurodegenerative diseases—including Alzheimer's disease, Parkinson's disease, and multiple sclerosis—are among the most common age-related conditions. With populations ageing globally, the prevalence of neurodegenerative disorders is increasing, owing in part to the extensions in lifespan. Currently, there is no cure for any of these diseases.
Increasing evidence indicates that RNA dysregulation is a shared driver of these disorders. In particular, mutations and aberrant expression of RNA-binding proteins (RBPs) frequently give rise to altered RNA–RBP interaction networks that contribute to neurodegenerative disease.
RNA–RBP interaction are essential for the assembly of stress granules, transient cellular compartments, that act as storage hubs to safeguard RNAs and proteins during stress. Under chronic stress, when RBPs are mutated or dysregulated stress granule dynamics fail and can seed pathological aggregates. However, the causal links between RNA control, stress granule persistence, and RBP aggregation remain incompletely defined.
UNDERPIN seeks to elucidate how mutations within RNA regulatory regions modulate the expression of RBPs, perturb their interaction networks, and ultimately affect stress granule formation. We combined computational and experimental approaches to assess the effects of single-nucleotide mutations in mRNAs encoding RBPs, thereby clarifying the mechanisms that underpin RBP regulatory networks.
Increasing evidence indicates that RNA dysregulation is a shared driver of these disorders. In particular, mutations and aberrant expression of RNA-binding proteins (RBPs) frequently give rise to altered RNA–RBP interaction networks that contribute to neurodegenerative disease.
RNA–RBP interaction are essential for the assembly of stress granules, transient cellular compartments, that act as storage hubs to safeguard RNAs and proteins during stress. Under chronic stress, when RBPs are mutated or dysregulated stress granule dynamics fail and can seed pathological aggregates. However, the causal links between RNA control, stress granule persistence, and RBP aggregation remain incompletely defined.
UNDERPIN seeks to elucidate how mutations within RNA regulatory regions modulate the expression of RBPs, perturb their interaction networks, and ultimately affect stress granule formation. We combined computational and experimental approaches to assess the effects of single-nucleotide mutations in mRNAs encoding RBPs, thereby clarifying the mechanisms that underpin RBP regulatory networks.
UNDERPIN delivers a unified computational–experimental framework to reveal how untranslated regions (UTRs) tune RNA-binding protein (RBP) expression and shape stress granule (SG) formation and dynamics.
Firstly, we built a transcript-resolved resources of disease-relevant UTR variants by integrating DisGeNET and GWAS data (1,984 and 1,467 entries, respectively) and annotating each with RNA structure, predicted RNA–protein/RNA–RNA contacts, expression context and proximity to experimentally mapped binding sites. Two open tools were released to the community: PRALINE, a database that ranks single-nucleotide variants with condensate-relevant annotations (predicted and experimentally validated protein–protein, protein–RNA and RNA–RNA, for proteins liquid–liquid phase separation and liquid–solid phase separation propensities, and for RNA the predicted secondary structure content RNA structure), published in Bioinformatics with my controbution), and catRAPID 2.2 – RNA Modifications, which predicts how m6A, A-to-I and pseudouridine reshape protein–RNA binding (published in Molecular Therapy – Nucleic Acids, with my contribution). In addition, we are working on an interactome-based framework to define eQTLs and pQTLs, paving the way to rank UTR variants by their effect on protein production.
Secondly, after prioritising the TARDBP 3′ UTR—encoding TDP-43 and harbouring three variants likely linked to neurodegenerative disease—I profiled its protein interactome with and without each variant using RNA–protein interaction detection (RaPID) coupled to mass spectrometry. TDP-43 is a recurrent hallmark across neurodegeneration, with nuclear loss and cytosolic inclusions; this pathology occurs in ~97% of ALS, ~50% of FTD, and 40–60% of AD, while mutations explain ~5% of familial ALS. The RaPID datasets map how the variants reshape the interaction network and potentially alter post-transcriptional regulation; the interactome is defined and pathway-level analyses to pinpoint variant-affected processes are underway. Functionally, I found that nucleotide changes in the 3′ UTR modulate TDP-43 translation during recovery from stress, when SG disassemble, thereby shifting the timing of translation re-engagement. To generalise the observations, I combined AHARIBO with RNA-seq to interrogate the translatome during stress and recovery and to estimate genome-wide translation-restart kinetics for SG-enriched RBP mRNAs (ongoing work).
Lastly, I adopted an RBP-centric strategy to characterise the function and mode of action of SAM68 (KHDRBS1)—an RBP that partitions into SGs and is implicated in the pathogenesis of fragile X–associated tremor/ataxia syndrome. We refined its binding landscape by iCLIP2 and investigated SAM68-mediated post-transcriptional regulation via its interactions with 5′ UTRs of target mRNAs. Beyond this, SAM68 is a key regulator of alternative splicing, and our data indicate it promotes the formation of numerous circular RNAs (circRNAs), adding a further layer of post-transcriptional control (manuscript under revision).
Taken together, these findings illuminate how UTRs govern RBP levels and SG dynamics, and pave the way for targeted validation and UTR-aware therapeutic exploration.
Firstly, we built a transcript-resolved resources of disease-relevant UTR variants by integrating DisGeNET and GWAS data (1,984 and 1,467 entries, respectively) and annotating each with RNA structure, predicted RNA–protein/RNA–RNA contacts, expression context and proximity to experimentally mapped binding sites. Two open tools were released to the community: PRALINE, a database that ranks single-nucleotide variants with condensate-relevant annotations (predicted and experimentally validated protein–protein, protein–RNA and RNA–RNA, for proteins liquid–liquid phase separation and liquid–solid phase separation propensities, and for RNA the predicted secondary structure content RNA structure), published in Bioinformatics with my controbution), and catRAPID 2.2 – RNA Modifications, which predicts how m6A, A-to-I and pseudouridine reshape protein–RNA binding (published in Molecular Therapy – Nucleic Acids, with my contribution). In addition, we are working on an interactome-based framework to define eQTLs and pQTLs, paving the way to rank UTR variants by their effect on protein production.
Secondly, after prioritising the TARDBP 3′ UTR—encoding TDP-43 and harbouring three variants likely linked to neurodegenerative disease—I profiled its protein interactome with and without each variant using RNA–protein interaction detection (RaPID) coupled to mass spectrometry. TDP-43 is a recurrent hallmark across neurodegeneration, with nuclear loss and cytosolic inclusions; this pathology occurs in ~97% of ALS, ~50% of FTD, and 40–60% of AD, while mutations explain ~5% of familial ALS. The RaPID datasets map how the variants reshape the interaction network and potentially alter post-transcriptional regulation; the interactome is defined and pathway-level analyses to pinpoint variant-affected processes are underway. Functionally, I found that nucleotide changes in the 3′ UTR modulate TDP-43 translation during recovery from stress, when SG disassemble, thereby shifting the timing of translation re-engagement. To generalise the observations, I combined AHARIBO with RNA-seq to interrogate the translatome during stress and recovery and to estimate genome-wide translation-restart kinetics for SG-enriched RBP mRNAs (ongoing work).
Lastly, I adopted an RBP-centric strategy to characterise the function and mode of action of SAM68 (KHDRBS1)—an RBP that partitions into SGs and is implicated in the pathogenesis of fragile X–associated tremor/ataxia syndrome. We refined its binding landscape by iCLIP2 and investigated SAM68-mediated post-transcriptional regulation via its interactions with 5′ UTRs of target mRNAs. Beyond this, SAM68 is a key regulator of alternative splicing, and our data indicate it promotes the formation of numerous circular RNAs (circRNAs), adding a further layer of post-transcriptional control (manuscript under revision).
Taken together, these findings illuminate how UTRs govern RBP levels and SG dynamics, and pave the way for targeted validation and UTR-aware therapeutic exploration.
This MSCA project (UNDERPIN) employs a multidisciplinary approach—combining computational prediction, cutting-edge assays, cell biology, and molecular biology—to decipher how untranslated regions (UTRs) regulate RNA-binding proteins (RBPs) involved in stress granule (SG) formation, and how post-transcriptional control of these RBPs shapes SG dynamics, especially in the presence of pathogenic variants.
Innovative aspects include:
1) Release of open, curated resources and interoperable datasets, plus predictive tools for RBP–RNA interactions and reproducible pipelines enabling UTR-centric, condensate-aware variant interpretation and routine UTR-aware target prioritisation.
2) RBP–RNA interaction datasets: (i) a variant-aware interactome of the TARDBP 3′ UTR; (ii) a SAM68-centred interactome of its RNA targets.
3) Quantitative characterisation of translation recovery after SG formation providing insight into an underexplored phase of the stress response.
Understanding how cells orchestrate stress responses through UTR features and RBP–RNA interactions is crucial for diagnostics developers, biotech, and pharma. This knowledge can facilitate the development of early biomarkers and RNA/UTR-engineering strategies to modulate protein synthesis in disease, highlighting the project’s socio-economic value.
Innovative aspects include:
1) Release of open, curated resources and interoperable datasets, plus predictive tools for RBP–RNA interactions and reproducible pipelines enabling UTR-centric, condensate-aware variant interpretation and routine UTR-aware target prioritisation.
2) RBP–RNA interaction datasets: (i) a variant-aware interactome of the TARDBP 3′ UTR; (ii) a SAM68-centred interactome of its RNA targets.
3) Quantitative characterisation of translation recovery after SG formation providing insight into an underexplored phase of the stress response.
Understanding how cells orchestrate stress responses through UTR features and RBP–RNA interactions is crucial for diagnostics developers, biotech, and pharma. This knowledge can facilitate the development of early biomarkers and RNA/UTR-engineering strategies to modulate protein synthesis in disease, highlighting the project’s socio-economic value.