Evidence map›Paper›PMID 35154250›Full record

ReviewFrontiers in genetics2021

Small Open Reading Frames, How to Find Them and Determine Their Function.

Preeti Madhav Kute, Omar Soukarieh, Håkon Tjeldnes, David-Alexandre Trégouët, Eivind Valen

Abstract readReview
In one paragraph

Review in Frontiers in genetics, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers.

0numbers the graph read from it
0cells of the map it votes in
22citing 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

22 citing papers in PubMed.

  1. Review
  2. Article
  3. Review
  4. Article
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  6. Article
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  11. Article
  12. Computational Prediction of Gene Regulation by lncRNAs.Methods in molecular biology (Clifton, N.J.) · 2025
    Article
  13. Review
  14. Review
  15. Noncanonical microprotein regulation of immunity.Molecular therapy : the journal of the American Society of Gene Therapy · 2024
    Review
  16. Article
  17. The Cryptic Bacterial Microproteome.bioRxiv : the preprint server for biology · 2024
    Article
  18. Review
  19. Article
  20. Review
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

5 authors.

Preeti Madhav KuteComputational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.
Omar SoukariehDepartment of Molecular Epidemiology Of Vascular and Brain Disorders, INSERM, BPH, U1219, University of Bordeaux, Bordeaux, France.
Håkon TjeldnesComputational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.
David-Alexandre TrégouëtDepartment of Molecular Epidemiology Of Vascular and Brain Disorders, INSERM, BPH, U1219, University of Bordeaux, Bordeaux, France.
Eivind ValenComputational Biology Unit, Department of Informatics, University of Bergen, Bergen, Norway.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Advances in genomics and molecular biology have revealed an abundance of small open reading frames (sORFs) across all types of transcripts. While these sORFs are often assumed to be non-functional, many have been implicated in physiological functions and a significant number of sORFs have been described in human diseases. Thus, sORFs may represent a hidden repository of functional elements that could serve as therapeutic targets. Unlike protein-coding genes, it is not necessarily the encoded peptide of an sORF that enacts its function, sometimes simply the act of translating an sORF might have a regulatory role. Indeed, the most studied sORFs are located in the 5'UTRs of coding transcripts and can have a regulatory impact on the translation of the downstream protein-coding sequence. However, sORFs have also been abundantly identified in non-coding RNAs including lncRNAs, circular RNAs and ribosomal RNAs suggesting that sORFs may be diverse in function. Of the many different experimental methods used to discover sORFs, the most commonly used are ribosome profiling and mass spectrometry. These can confirm interactions between transcripts and ribosomes and the production of a peptide, respectively. Extensions to ribosome profiling, which also capture scanning ribosomes, have further made it possible to see how sORFs impact the translation initiation of mRNAs. While high-throughput techniques have made the identification of sORFs less difficult, defining their function, if any, is typically more challenging. Together, the abundance and potential function of many of these sORFs argues for the necessity of including sORFs in gene annotations and systematically characterizing these to understand their potential functional roles. In this review, we will focus on the high-throughput methods used in the detection and characterization of sORFs and discuss techniques for validation and functional characterization.

Indexed as

computational toolsmass spectrometryribosome profilingSEPssORFs

Identifiers

PMID35154250
PMCPMC8831751

What OpenQuestion holds

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Registered trials

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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.