Evidence map›Paper›PMID 27083402›Full record

ReviewMethods (San Diego, Calif.)2016

Guidelines for the optimal design of miRNA-based shRNAs.

Xavier Bofill-De Ros, Shuo Gu

Open access · goldAbstract readReview
In one paragraph

Review in Methods (San Diego, Calif.), 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 58 papers.

0numbers the graph read from it
0cells of the map it votes in
58citing papers in PubMed
4.2field-weighted citation impact, top 6% 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

58 citing papers in PubMed, 91 citations in OpenAlex.

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  12. Therapeutic AASS inhibition by AAV-miRNA rescues glutaric aciduria type I severe phenotype in mice.Molecular therapy : the journal of the American Society of Gene Therapy · 2025
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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

2 authors at 1 institution in 1 country.

Xavier Bofill-De RosGene Regulation and Chromosome Biology Laboratory, Center For Cancer Research, National Cancer Institute, Frederick, MD, United States.
Shuo GuGene Regulation and Chromosome Biology Laboratory, Center For Cancer Research, National Cancer Institute, Frederick, MD, United States. Electronic address: shuo.gu@nih.gov.
Frederick National Laboratory for Cancer Research · US

Funding

Uncover the mechanisms regulating the biogenesis and decay of miRNAs in cancerZIABC011566 · NCI · DIVISION OF BASIC SCIENCES - NCI · PI GU, SHUO · 2014 to 2025
$16.3M
Intramural NIH HHS ZIA BC011566
6 · The paper itself

Abstract

RNA interference (RNAi) is an extremely useful tool for inhibiting gene expression. It can be triggered by transfected synthetic small interfering RNA (siRNA) or by expressed small hairpin RNA (shRNA). The cellular machinery processes the latter into siRNA in vivo. shRNA is preferred or required in genetic screens and specific RNAi approaches in gene therapy settings. Despite its many successes, the field of shRNAs faces many challenges. Insufficient knockdowns and off-target effects become obstacles for shRNA usage in many applications. Numerous failures are triggered by pitfalls in shRNA design that is often associated with impoverished biogenesis. Here, based on current understanding of the miRNA maturation pathway, we discuss the principles of different shRNA design (pre-miRNA-like, pri-miRNA-like and Ago-shRNA) with an emphasis on the RNA structure. We also provide detailed instructions for an optimal design of pre-miRNA-like shRNA.

Indexed as

AnimalsBase SequenceGene Knockdown TechniquesGenetic TherapyHumansInverted Repeat SequencesMicroRNAsPromoter Regions, GeneticRNA InterferenceRNA, Small InterferingMicroRNAsRNA, Small InterferingGene therapymiRNARNAiRNA structureshRNAsiRNA

Identifiers

PMID27083402
PMCPMC4921303
OpenAlexW2335838865

What OpenQuestion holds

Textmetadata
LicenceTDM
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.