LIN, Ya-Hui, DODD, Jennifer E, CUTILLO, Luisa, CASTELLI, Lydia M, MIHAYLOV, Simeon R, NORRIS, Karl, HIGGINBOTTOM, Adrian, WALSH, Matthew J, COOPER-KNOCK, Johnathan, HIGHLEY, J Robin, GRANATA, Ilaria, EVANS, Caroline A, GUARRACINO, Mario R, CAMPBELL, Susan, DICKMAN, Mark J, SHAW, Pamela J, MILO, Marta and HAUTBERGUE, Guillaume M (2024). GRASPS: a simple-to-operate translatome technology reveals omics-hidden disease-associated pathways in TDP-43-related amyotrophic lateral sclerosis. [Pre-print] (Unpublished) [Pre-print]
Preprints have not been peer-reviewed. They should not be relied on to guide clinical practice or health related behaviour and should not be regarded as conclusive or be reported in news media as established information.
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2024.03.04.583294v1.full.pdf - Pre-print
Available under License Creative Commons Attribution No Derivatives.
2024.03.04.583294v1.full.pdf - Pre-print
Available under License Creative Commons Attribution No Derivatives.
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Abstract
Transcriptomes and translatomes measure genome-wide levels of total and ribosome-associated RNAs. A few hundred translatomes were reported over >250,000 transcriptomes highlighting the challenges of identifying translating RNAs. Here, we used a human isogenic inducible model of TDP-43-linked amyotrophic lateral sclerosis, which exhibits altered expression of thousands of transcripts, as a paradigm for the direct comparison of whole-cell, cytoplasmic and translating RNAs, showing broad uncoupling and poor correlation between disease-altered transcripts. Moreover, based on precipitation of endogenous ribosomes, we developed GRASPS (Genome-wide RNA Analysis of Stalled Protein Synthesis), a simple-to-operate translatome technology. Remarkably, GRASPS identified three times more differentially-expressed transcripts with higher fold changes and statistical significance, providing unprecedented opportunities for data modeling at stringent filtering and discovery of previously omics-missed disease-relevant pathways, which functionally map on dense gene regulatory networks of protein-protein interactions. Based on its simplicity and robustness, GRASPS is widely applicable across disciplines in the biotechnologies and biomedical sciences.
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