Evidence map›Paper›PMID 24598260›Full record

ArticleNucleic acids research2014

Systematic design and functional analysis of artificial microRNAs.

Jason D Arroyo, Emily N Gallichotte, Muneesh Tewari

Open access · goldAbstract read
In one paragraph

Article in Nucleic acids research, 2014. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing papers in PubMed
0.9field-weighted citation impact, top 26% of its field
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

8 citing papers in PubMed, 19 citations in OpenAlex.

  1. Article
  2. Article
  3. Artificial miRNAs and target-mimics as potential tools for crop improvement.Physiology and molecular biology of plants : an international journal of functional plant biology · 2025
    Review
  4. Advancements in genetic studies of mushrooms: a comprehensive review.World journal of microbiology & biotechnology · 2024
    Review
  5. Article
  6. Review
  7. Article
  8. Synthetic RNAs for Gene Regulation: Design Principles and Computational Tools.Frontiers in bioengineering and biotechnology · 2014
    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 at 1 institution in 1 country.

Jason D ArroyoHuman Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109-1024, USA.
Emily N GallichotteHuman Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109-1024, USA.
Muneesh TewariHuman Biology Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109-1024, USA Clinical Research Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109-1024, USA Public Health Sciences Division, Fred Hutchinson Cancer Research Center, 1100 Fairview Ave N, Seattle, WA 98109-1024, USA mtewari@med.umich.edu.
Fred Hutch Cancer Center · US

Funding

RNA as a Hormone: Systemic Signaling in Mammals via Circulating, Cell-Free SmallR01DK085714 · NIDDK · UNIVERSITY OF MICHIGAN AT ANN ARBOR · PI TEWARI, MUNEESH · 2009 to 2015
$4.0M
NIDDK NIH HHS R01 DK085714NIDDK NIH HHS R01DK085714
6 · The paper itself

Abstract

Unlike short interfering RNAs (siRNAs), which are commonly designed to repress a single messenger RNA (mRNA) target through perfect base pairing, microRNAs (miRNAs) are endogenous small RNAs that have evolved to concurrently repress multiple mRNA targets through imperfect complementarity. MicroRNA target recognition is primarily determined by pairing of the miRNA seed sequence (nucleotides 2-8) to complementary match sites in each mRNA target. Whereas siRNA technology is well established for single target knockdown, the design of artificial miRNAs for multi-target repression is largely unexplored. We designed and functionally analysed over 200 artificial miRNAs for simultaneous repression of pyruvate carboxylase and glutaminase by selecting all seed matches shared by their 3' untranslated regions. Although we identified multiple miRNAs that repressed endogenous protein expression of both genes, seed-based artificial miRNA design was highly inefficient, as the majority of miRNAs with even perfect seed matches did not repress either target. Moreover, commonly used target prediction programs did not substantially discriminate effective artificial miRNAs from ineffective ones, indicating that current algorithms do not fully capture the features important for artificial miRNA targeting and are not yet sufficient for designing artificial miRNAs. Our analysis suggests that additional factors are strong determinants of the efficacy of miRNA-mediated target repression and remain to be discovered.

Indexed as

Gene Knockdown Techniques3' Untranslated RegionsBase SequenceBinding SitesGenes, ReporterGlutaminaseHEK293 CellsHumansMicroRNAsPyruvate CarboxylaseRNA Interference3' Untranslated RegionsGlutaminaseMicroRNAsPyruvate Carboxylase

Identifiers

PMID24598260
PMCPMC4027203
OpenAlexW2157000674

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.