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Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes

Siddharth Sethi, David Zhang, Sebastian Guelfi, View ORCID ProfileZhongbo Chen, Sonia Garcia-Ruiz, Mina Ryten, Harpreet Saini, View ORCID ProfileJuan A. Botia
doi: https://doi.org/10.1101/2021.03.08.434412
Siddharth Sethi
1Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, United Kingdom
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
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David Zhang
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
3NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
4Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, UK
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Sebastian Guelfi
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
5Verge Genomics, South San Francisco, CA 94080, USA
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Zhongbo Chen
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
3NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
4Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, UK
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  • ORCID record for Zhongbo Chen
Sonia Garcia-Ruiz
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
3NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
4Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, UK
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Mina Ryten
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
3NIHR Great Ormond Street Hospital Biomedical Research Centre, University College London, London, UK
4Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London WC1E 6BT, UK
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  • For correspondence: mina.ryten@ucl.ac.uk
Harpreet Saini
1Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, United Kingdom
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Juan A. Botia
2Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK
6Department of Information and Communications Engineering, University of Murcia, Spain
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  • ORCID record for Juan A. Botia
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Abstract

There is growing evidence for the importance of 3’ untranslated region (3’UTR) dependent regulatory processes. However, our current human 3’UTR catalogue is incomplete. Here, we developed a machine learning-based framework, leveraging both genomic and tissue-specific transcriptomic features to predict previously unannotated 3’UTRs. We identify unannotated 3’UTRs associated with 1,513 genes across 39 human tissues, with the greatest abundance found in brain. These unannotated 3’UTRs were significantly enriched for RNA binding protein (RBP) motifs and exhibited high human lineage-specificity. We found that brain-specific unannotated 3’UTRs were enriched for the binding motifs of important neuronal RBPs such as TARDBP and RBFOX1, and their associated genes were involved in synaptic function and brain- related disorders. Our data is shared through an online resource F3UTER (https://astx.shinyapps.io/F3UTER/). Overall, our data improves 3’UTR annotation and provides novel insights into the mRNA-RBP interactome in the human brain, with implications for our understanding of neurological and neurodevelopmental diseases.

Competing Interest Statement

The authors have declared no competing interest.

Copyright 
The copyright holder for this preprint is the author/funder, who has granted bioRxiv a license to display the preprint in perpetuity. It is made available under a CC-BY-NC-ND 4.0 International license.
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Posted March 09, 2021.
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Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes
Siddharth Sethi, David Zhang, Sebastian Guelfi, Zhongbo Chen, Sonia Garcia-Ruiz, Mina Ryten, Harpreet Saini, Juan A. Botia
bioRxiv 2021.03.08.434412; doi: https://doi.org/10.1101/2021.03.08.434412
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Leveraging omic features with F3UTER enables identification of unannotated 3’UTRs for synaptic genes
Siddharth Sethi, David Zhang, Sebastian Guelfi, Zhongbo Chen, Sonia Garcia-Ruiz, Mina Ryten, Harpreet Saini, Juan A. Botia
bioRxiv 2021.03.08.434412; doi: https://doi.org/10.1101/2021.03.08.434412

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