Evidence map›Paper›PMID 28766300›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2017

A Cell-Based High-Throughput Method for Identifying Modulators of Alternative Splicing.

Sika Zheng

Abstract read
In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2017. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.

0numbers the graph read from it
0cells of the map it votes in
2citing 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

2 citing papers in PubMed.

  1. Article
  2. Article
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

1 author.

Sika ZhengDivision of Biomedical Sciences, University of California Riverside, 201 School of Medicine Research Building, 900 University Avenue, Riverside, CA, 92521, USA. sika.zheng@ucr.edu.

Funding

Alternative splicing and nonsense-mediated mRNA decay in neural developmentR00MH096807 · NIMH · UNIVERSITY OF CALIFORNIA RIVERSIDE · PI ZHENG, SIKA · 2014 to 2016
$747k
NIMH NIH HHS R00 MH096807
6 · The paper itself

Abstract

Alternative splicing, a key regulatory process of gene expression, is controlled by trans-acting factors that recognize cis-elements in premature RNA transcripts to affect spliceosome assembly and splice site choices. Extracellular stimuli and signaling cascades can converge on RNA binding splicing regulators to affect alternative splicing. Defects in splicing regulation have been associated with various human diseases, and modification of disease-causing splicing events presents great therapeutic promise. Determining splicing regulators and/or upstream modulators has been difficult with low throughput, low sensitivity, and low specificity. IRAS (identifying regulators of alternative splicing) is a novel cell-based high-throughput screening strategy designed specifically to address these challenges and has achieved high throughput, high sensitivity, and high specificity. Here, we describe the IRAS method in detail with a pair of dual-fluorescence minigene reporters that produces GFP and RFP fluorescent signals to assay the two spliced isoforms exclusively. These two complementary mini-gene reporters alter GFP/RFP output ratios in the opposite direction in response to only a true splicing change. False positives from a signal screen do not stimulate opposite changes in GFP/RFP ratios. The reporter pair in conjunction with robotic liquid handlers and arrayed libraries allows IRAS to screen for both positive and negative splicing regulators with high sensitivity and specificity in a high-throughput manner.

Indexed as

Gene LibraryGenes, ReporterAlternative SplicingAnimalsGreen Fluorescent ProteinsHumansRNA Splicing FactorsGreen Fluorescent ProteinsRNA Splicing FactorsAlternative splicingDual-fluorescenceDual-outputGFPHigh-throughput screenIRASMinigeneRFPSplicing regulatorSplicing reporters

Identifiers

PMID28766300
PMCPMC5673682

What OpenQuestion holds

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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.