Sethi, Siddharth;
Zhang, David;
Guelfi, Sebastian;
Chen, Zhongbo;
Garcia-Ruiz, Sonia;
Olagbaju, Emmanuel O;
Ryten, Mina;
... Botia, Juan A; + view all
(2022)
Leveraging omic features with F3UTER enables identification of unannotated 3'UTRs for synaptic genes.
Nature Communications
, 13
, Article 2270. 10.1038/s41467-022-30017-z.
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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 develop 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 1,563 genes across 39 human tissues, with the greatest abundance found in the brain. These unannotated 3'UTRs are significantly enriched for RNA binding protein (RBP) motifs and exhibit high human lineage-specificity. We find that brain-specific unannotated 3'UTRs are enriched for the binding motifs of important neuronal RBPs such as TARDBP and RBFOX1, and their associated genes are involved in synaptic function. Our data is shared through an online resource F3UTER ( https://astx.shinyapps.io/F3UTER/ ). Overall, our data improves 3'UTR annotation and provides additional insights into the mRNA-RBP interactome in the human brain, with implications for our understanding of neurological and neurodevelopmental diseases.
Type: | Article |
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Title: | Leveraging omic features with F3UTER enables identification of unannotated 3'UTRs for synaptic genes |
Location: | England |
Open access status: | An open access version is available from UCL Discovery |
DOI: | 10.1038/s41467-022-30017-z |
Publisher version: | https://doi.org/10.1038/s41467-022-30017-z |
Language: | English |
Additional information: | © The Author(s) 2022. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/ licenses/by/4.0/. |
Keywords: | 3' Untranslated Regions, Humans, RNA, Messenger, Transcriptome |
UCL classification: | UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology > Neurodegenerative Diseases UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences UCL UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Brain Sciences > UCL Queen Square Institute of Neurology UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health > Genetics and Genomic Medicine Dept UCL > Provost and Vice Provost Offices > School of Life and Medical Sciences > Faculty of Population Health Sciences > UCL GOS Institute of Child Health |
URI: | https://discovery.ucl.ac.uk/id/eprint/10147942 |
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