Evidence map›Paper›PMID 29444662›Full record

ArticleBMC genomics2018

A systematic approach to RNA-associated motif discovery.

Tian Gao, Jiang Shu, Juan Cui

Abstract read
In one paragraph

Article in BMC genomics, 2018. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 18 papers.

0numbers the graph read from it
0cells of the map it votes in
18citing 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

18 citing papers in PubMed.

  1. Article
  2. Beyond the Bubble: A Debate on microRNA Sorting Into Extracellular Vesicles.Laboratory investigation; a journal of technical methods and pathology · 2025
    Review
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  6. Article
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  9. Article
  10. The mScience immunology · 2021
    Article
  11. Review
  12. Regulation of exosome production and cargo sorting.International journal of biological sciences · 2021
    Review
  13. Article
  14. The Messenger Apps of the cell: Extracellular Vesicles as Regulatory Messengers of Microglial Function in the CNS.Journal of neuroimmune pharmacology : the official journal of the Society on NeuroImmune Pharmacology · 2020
    Review
  15. Review
  16. Review
  17. Article
  18. 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

3 authors.

Tian GaoSystems Biology and Biomedical Informatics (SBBI) Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
Jiang ShuSystems Biology and Biomedical Informatics (SBBI) Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA.
Juan CuiSystems Biology and Biomedical Informatics (SBBI) Laboratory, Department of Computer Science and Engineering, University of Nebraska-Lincoln, Lincoln, NE, 68588, USA. jcui@unl.edu.

Funding

The role of stress in the fetal origin of obesity and metabolic dysfunctionP20GM104320 · NIGMS · UNIVERSITY OF NEBRASKA LINCOLN · PI ZEMPLENI, JANOS · 2014 to 2024
$24.9M
NIGMS NIH HHS P20 GM104320NIH HHS 1P20GM104320University of Nebraska-Lincoln (US) Food for Health Seed Grant
6 · The paper itself

Abstract

backgroundSequencing-based large screening of RNA-protein and RNA-RNA interactions has enabled the mechanistic study of post-transcriptional RNA processing and sorting, including exosome-mediated RNA secretion. The downstream analysis of RNA binding sites has encouraged the investigation of novel sequence motifs, which resulted in exceptional new challenges for identifying motifs from very short sequences (e.g., small non-coding RNAs or truncated messenger RNAs), where conventional methods tend to be ineffective. To address these challenges, we propose a novel motif-finding method and validate it on a wide range of RNA applications.

resultsWe first perform motif analysis on microRNAs and longer RNA fragments from various cellular and exosomal sources, and then validate our prediction through literature search and experimental test. For example, a 4 bp-long motif, GUUG, was detected to be responsible for microRNA loading in exosomes involved in human colon cancer (SW620). Additional performance comparisons in various case studies have shown that this new approach outperforms several existing state-of-the-art methods in detecting motifs with exceptional high coverage and explicitness.

conclusionsIn this work, we have demonstrated the promising performance of a new motif discovery approach that is particularly effective in current RNA applications. Important discoveries resulting from this work include the identification of possible RNA-loading motifs in a variety of exosomes, as well as novel insights in sequence features of RNA cargos, i.e., short non-coding RNAs and messenger RNAs may share similar loading mechanism into exosomes. This method has been implemented and deployed as a new webserver named MDS

Indexed as

Base SequenceBinding SitesCell Line, TumorComputational BiologyExosomesHigh-Throughput Nucleotide SequencingHumansInternetMicroRNAsNucleotide MotifsReproducibility of ResultsRNA, MessengerMicroRNAsRNA, MessengerExosomal RNAsExosomesGraph algorithmsmicroRNAsMotif findingShort sequences

Identifiers

PMID29444662
PMCPMC5813387

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.