Evidence map›Paper›PMID 30393377›Full record

ArticleGenetics in medicine : official journal of the American College of Medical Genetics2019

eKLIPse: a sensitive tool for the detection and quantification of mitochondrial DNA deletions from next-generation sequencing data.

David Goudenège, Celine Bris, Virginie Hoffmann, Valerie Desquiret-Dumas, Claude Jardel, Benoit Rucheton, Sylvie Bannwarth, Veronique Paquis-Flucklinger, Anne Sophie Lebre, Estelle Colin and 5 more

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In one paragraph

Article in Genetics in medicine : official journal of the American College of Medical Genetics, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 35 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
35citing papers in PubMed, 1 pooled it
1.8field-weighted citation impact, top 14% 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

35 citing papers in PubMed, 1 synthesis or guideline pooled it, 55 citations in OpenAlex.

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  13. The human OPA1Cellular and molecular life sciences : CMLS · 2024
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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

15 authors at 6 institutions in 1 country.

David GoudenègeMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Celine BrisMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Virginie HoffmannMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Valerie Desquiret-DumasMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Claude JardelBiochemistry Department and Genetics Center, APHP, GHU Pitié-Salpêtrière, Paris, France.
Benoit RuchetonBiochemistry Department and Genetics Center, APHP, GHU Pitié-Salpêtrière, Paris, France.
Sylvie BannwarthUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Veronique Paquis-FlucklingerUniversité Côte d'Azur, CHU de Nice, INSERM, CNRS, IRCAN, Nice, France.
Anne Sophie LebreCHU Reims, Hôpital Maison Blanche, Pole de biologie, Service de génétique, Reims, France.
Estelle ColinMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Patrizia Amati-BonneauMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Dominique BonneauMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Pascal ReynierMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Guy LenaersMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France.
Vincent ProcaccioMitoLab, UMR CNRS 6015-INSERM U1083, MitoVasc Institute, Angers University, Angers, France. ViProcaccio@chu-angers.fr.
Inserm · FRCentre National de la Recherche Scientifique · FRUniversité d'Angers · FRAssistance Publique – Hôpitaux de Paris · FRInstitut de Recherche sur le Cancer et le Vieillissement de Nice · FRUniversité de Reims Champagne-Ardenne · FR

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

purposeAccurate detection of mitochondrial DNA (mtDNA) alterations is essential for the diagnosis of mitochondrial diseases. The development of high-throughput sequencing technologies has enhanced the detection sensitivity of mtDNA pathogenic variants, but the detection of mtDNA rearrangements, especially multiple deletions, is still poorly processed. Here, we present eKLIPse, a sensitive and specific tool allowing the detection and quantification of large mtDNA rearrangements from single and paired-end sequencing data.

methodsThe methodology was first validated using a set of simulated data to assess the detection sensitivity and specificity, and second with a series of sequencing data from mitochondrial disease patients carrying either single or multiple deletions, related to pathogenic variants in nuclear genes involved in mtDNA maintenance.

resultseKLIPse provides the precise breakpoint positions and the cumulated percentage of mtDNA rearrangements at a given gene location with a detection sensitivity lower than 0.5% mutant. eKLIPse software is available either as a script to be integrated in a bioinformatics pipeline, or as user-friendly graphical interface to visualize the results through a Circos representation ( https://github.com/dooguypapua/eKLIPse ).

conclusionThus, eKLIPse represents a useful resource to study the causes and consequences of mtDNA rearrangements, for further genotype/phenotype correlations in mitochondrial disorders.

Indexed as

Base SequenceDNA, MitochondrialGenetic Association StudiesHigh-Throughput Nucleotide SequencingHumansMitochondriaMitochondrial DiseasesSequence Analysis, DNASequence DeletionSoftwareDNA, Mitochondrialmitochondrial diseasesmitochondrial genomemtDNA deletionsnext-generation sequencingsoft clipping

Identifiers

PMID30393377
OpenAlexW2898970691

What OpenQuestion holds

Textmetadata
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.