Evidence map›Paper›PMID 35477703›Full record

ArticleNature communications2022

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, Emmanuel O Olagbaju, Mina Ryten, Harpreet Saini, Juan A Botia

Abstract read
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In one paragraph

Article in Nature communications, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed.

  1. Article
  2. Review
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Siddharth SethiAstex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK.ORCID 0000-0002-4398-4295
David ZhangGenetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, WC1E 6BT, UK.
Sebastian GuelfiDepartment of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK.
Zhongbo ChenDepartment of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK.ORCID 0000-0001-6668-7202
Sonia Garcia-RuizDepartment of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK.ORCID 0000-0003-4913-5312
Emmanuel O OlagbajuGenetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, WC1E 6BT, UK.
Mina Ryten *Genetics and Genomic Medicine, Great Ormond Street Institute of Child Health, University College London, London, WC1E 6BT, UK. mina.ryten@ucl.ac.uk.ORCID 0000-0001-9520-6957
Harpreet Saini *Astex Pharmaceuticals, 436 Cambridge Science Park, Cambridge, UK.
Juan A Botia *Department of Neurodegenerative Disease, Institute of Neurology, University College London, London, UK.

Funding

Medical Research Council MR/N008324/1
6 · The paper itself

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.

Indexed as

Transcriptome3' Untranslated RegionsHumansRNA, Messenger3' Untranslated RegionsRNA, Messenger

Identifiers

PMID35477703
PMCPMC9046390

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.