Evidence map›Paper›PMID 40884641›Full record

ArticleMethods in molecular biology (Clifton, N.J.)2025

Detection of Complex Genomic Rearrangements Using Short-Read Whole Genome Sequencing in C. elegans.

Tatiana Maroilley, Maja Tarailo-Graovac

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In one paragraph

Article in Methods in molecular biology (Clifton, N.J.), 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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.

Tatiana MaroilleyDepartments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada.ORCID https://orcid.org/0000-0002-3392-5363
Maja Tarailo-GraovacDepartments of Biochemistry, Molecular Biology and Medical Genetics, Cumming School of Medicine, University of Calgary, Calgary, AB, Canada. maja.tarailograovac@ucalgary.ca.ORCID https://orcid.org/0000-0002-4472-8584

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clinical diagnostic workflows have been focused on exome sequencing and the detection of small protein-coding variants (single-nucleotides, short insertions, and deletions) often overlooking complex genomic rearrangements (CGR). Indeed, detection of CGRs required genome rather than exome sequencing and development of advanced analytical tools. Among the available technologies for genome sequencing, short-read whole genome sequencing (srWGS) is currently the most cost-efficient technology for detecting variants as it covers most of the genome and theoretically allows the detection of the whole spectrum of genomic variations. To develop and assess new workflows for accurate detection of CGRs with srWGS, model organisms such as Caenorhabditis elegans (C. elegans) constitute an excellent biological tool that could be used in a tractable fashion. Indeed, many C. elegans strains called balancers are known to carry CGRs used to balance genomic loci. Balancer C. elegans genomes constitute then a source of known CGRs to assess analytical methods and the compact genome of C. elegans allows reduced sequencing and experimental validation costs but also reduced computational burden while testing computational approaches. Here, we present a complete workflow to detect and validate CGR breakpoints as well as guidelines to interpret their structure using srWGS developed on C. elegans balancers strains.

Indexed as

Caenorhabditis elegansGene RearrangementGenome, HelminthGenomicsWhole Genome SequencingAnimalsComputational BiologyHigh-Throughput Nucleotide SequencingWorkflowC. elegansChromoanagenesisShort-readStructural variantWhole genome sequencing

Identifiers

PMID40884641

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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.