Evidence map›Paper›PMID 26792894›Full record

ArticleNucleic acids research2016

Re-evaluation of G-quadruplex propensity with G4Hunter.

Amina Bedrat, Laurent Lacroix, Jean-Louis Mergny

Abstract read
In one paragraph

Article in Nucleic acids research, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 371 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
371citing papers in PubMed, 1 pooled it
–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

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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

371 citing papers in PubMed, 1 synthesis or guideline pooled it.

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311 more citing papers are in PubMed but not listed here.

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.

Amina BedratUniversité de Bordeaux, ARNA Laboratory, F-33000 Bordeaux, France Inserm U1212, CNRS UMR 5320, IECB, F-33600 Pessac, France.
Laurent LacroixCNRS-Université de Toulouse UMR5099, F-31000 Toulouse, France laurent.lacroix@inserm.fr.
Jean-Louis MergnyUniversité de Bordeaux, ARNA Laboratory, F-33000 Bordeaux, France Inserm U1212, CNRS UMR 5320, IECB, F-33600 Pessac, France jean-louis.mergny@inserm.fr.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Critical evidence for the biological relevance of G-quadruplexes (G4) has recently been obtained in seminal studies performed in a variety of organisms. Four-stranded G-quadruplex DNA structures are promising drug targets as these non-canonical structures appear to be involved in a number of key biological processes. Given the growing interest for G4, accurate tools to predict G-quadruplex propensity of a given DNA or RNA sequence are needed. Several algorithms such as Quadparser predict quadruplex forming propensity. However, a number of studies have established that sequences that are not detected by these tools do form G4 structures (false negatives) and that other sequences predicted to form G4 structures do not (false positives). Here we report development and testing of a radically different algorithm, G4Hunter that takes into account G-richness and G-skewness of a given sequence and gives a quadruplex propensity score as output. To validate this model, we tested it on a large dataset of 392 published sequences and experimentally evaluated quadruplex forming potential of 209 sequences using a combination of biophysical methods to assess quadruplex formation in vitro. We experimentally validated the G4Hunter algorithm on a short complete genome, that of the human mitochondria (16.6 kb), because of its relatively high GC content and GC skewness as well as the biological relevance of these quadruplexes near instability hotspots. We then applied the algorithm to genomes of a number of species, including humans, allowing us to conclude that the number of sequences capable of forming stable quadruplexes (at least in vitro) in the human genome is significantly higher, by a factor of 2-10, than previously thought.

Indexed as

Genome, HumanG-QuadruplexesAlgorithmsCircular DichroismDNAGenome, MitochondrialHumansMitochondriaDNA

Identifiers

PMID26792894
PMCPMC4770238

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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.