Evidence map›Paper›PMID 31873213›Full record

ArticleNature biotechnology2020

Single-cell analysis of structural variations and complex rearrangements with tri-channel processing.

Ashley D Sanders, Sascha Meiers, Maryam Ghareghani, David Porubsky, Hyobin Jeong, M Alexandra C C van Vliet, Tobias Rausch, Paulina Richter-Pechańska, Joachim B Kunz, Silvia Jenni and 13 more

Abstract read
In one paragraph

Article in Nature biotechnology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 48 papers.

0numbers the graph read from it
0cells of the map it votes in
48citing 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

48 citing papers in PubMed.

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  9. Review
  10. Structural variant and nucleosome occupancy dynamics postchemotherapy in a HER2+ breast cancer organoid model.Proceedings of the National Academy of Sciences of the United States of America · 2025
    Article
  11. Article
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  13. Review
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  20. The two sides of chromosomal instability: drivers and brakes in cancer.Signal transduction and targeted therapy · 2024
    Review
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

23 authors.

Ashley D Sanders *European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0003-3945-0677
Sascha Meiers *European Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
Maryam Ghareghani *Center for Bioinformatics, Saarland University, Saarbrücken, Germany.
David Porubsky *Center for Bioinformatics, Saarland University, Saarbrücken, Germany.
Hyobin JeongEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
M Alexandra C C van VlietEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
Tobias RauschEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-5773-5620
Paulina Richter-PechańskaMolecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.ORCID http://orcid.org/0000-0001-6727-6317
Joachim B KunzMolecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.
Silvia JenniDivision of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland.
Davide BologniniEuropean Molecular Biology Laboratory, Genomics Core Facility, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-8735-8093
Gabriel M C LongoEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
Benjamin RaederEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-9494-8884
Venla KinanenEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.
Jürgen ZimmermannEuropean Molecular Biology Laboratory, Genomics Core Facility, Heidelberg, Germany.
Vladimir BenesEuropean Molecular Biology Laboratory, Genomics Core Facility, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-0352-2547
Martin SchrappeDepartment of Pediatrics, University Hospital Schleswig-Holstein, Campus Kiel, Kiel, Germany.
Balca R MardinEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany.ORCID http://orcid.org/0000-0002-3903-9354
Andreas E KulozikMolecular Medicine Partnership Unit, European Molecular Biology Laboratory, University of Heidelberg, Heidelberg, Germany.
Beat BornhauserDivision of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland.
Jean-Pierre BourquinDivision of Pediatric Oncology, University Children's Hospital, Zürich, Switzerland.
Tobias MarschallCenter for Bioinformatics, Saarland University, Saarbrücken, Germany. t.marschall@mpi-inf.mpg.de.ORCID http://orcid.org/0000-0002-9376-1030
Jan O KorbelEuropean Molecular Biology Laboratory, Genome Biology Unit, Heidelberg, Germany. jan.korbel@embl.de.ORCID http://orcid.org/0000-0002-2798-3794

Funding

An Integrative Analysis of Structural Variation for the 1000 Genomes ProjectU41HG007497 · NHGRI · JACKSON LABORATORY · PI LEE, CHARLES · 2013 to 2017
$13.0M
European Research Council 336045European Research Council 773026NHGRI NIH HHS U41 HG007497
6 · The paper itself

Abstract

Structural variation (SV), involving deletions, duplications, inversions and translocations of DNA segments, is a major source of genetic variability in somatic cells and can dysregulate cancer-related pathways. However, discovering somatic SVs in single cells has been challenging, with copy-number-neutral and complex variants typically escaping detection. Here we describe single-cell tri-channel processing (scTRIP), a computational framework that integrates read depth, template strand and haplotype phase to comprehensively discover SVs in individual cells. We surveyed SV landscapes of 565 single cells, including transformed epithelial cells and patient-derived leukemic samples, to discover abundant SV classes, including inversions, translocations and complex DNA rearrangements. Analysis of the leukemic samples revealed four times more somatic SVs than cytogenetic karyotyping, submicroscopic copy-number alterations, oncogenic copy-neutral rearrangements and a subclonal chromothripsis event. Advancing current methods, single-cell tri-channel processing can directly measure SV mutational processes in individual cells, such as breakage-fusion-bridge cycles, facilitating studies of clonal evolution, genetic mosaicism and SV formation mechanisms, which could improve disease classification for precision medicine.

Indexed as

Genomic Structural VariationCell LineChromothripsisClonal EvolutionComputational BiologyGene RearrangementHumansINDEL MutationLeukemiaSequence InversionSingle-Cell AnalysisTranslocation, Genetic

Identifiers

PMID31873213
PMCPMC7612647

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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.