Evidence map›Paper›PMID 32731881›Full record

ArticleGenome medicine2020

A pipeline for complete characterization of complex germline rearrangements from long DNA reads.

Satomi Mitsuhashi, Sachiko Ohori, Kazutaka Katoh, Martin C Frith, Naomichi Matsumoto

Open access · goldAbstract read
In one paragraph

Article in Genome medicine, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing papers in PubMed
5.9field-weighted citation impact, top 3% 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

21 citing papers in PubMed, 40 citations in OpenAlex.

  1. Article
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  9. Biallelic structural variations withinLife science alliance · 2023
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  10. Review
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  12. Long-read sequencing improves diagnostic rate in neuromuscular disorders.Acta myologica : myopathies and cardiomyopathies : official journal of the Mediterranean Society of Myology · 2023
    Review
  13. Article
  14. Article
  15. Review
  16. Towards population-scale long-read sequencing.Nature reviews. Genetics · 2021
    Review
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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

5 authors at 3 institutions in 1 country.

Satomi MitsuhashiDepartment of Human Genetics, Yokohama City University Graduate School of Medicine, Fukuura 3-9, Kanazawa-ku, Yokohama, 236-0004, Japan.
Sachiko OhoriDepartment of Human Genetics, Yokohama City University Graduate School of Medicine, Fukuura 3-9, Kanazawa-ku, Yokohama, 236-0004, Japan.
Kazutaka KatohResearch Institute for Microbial Diseases, Osaka University, Suita, Japan.
Martin C FrithArtificial Intelligence Research Center, National Institute of Advanced Industrial Science and Technology (AIST), 2-3-26 Aomi, Koto-ku, Tokyo, 135-0064, Japan. mcfrith@edu.k.u-tokyo.ac.jp.
Naomichi MatsumotoDepartment of Human Genetics, Yokohama City University Graduate School of Medicine, Fukuura 3-9, Kanazawa-ku, Yokohama, 236-0004, Japan. naomat@yokohama-cu.ac.jp.ORCID 0000-0001-9846-6500
Yokohama City University · JPNational Institute of Advanced Industrial Science and Technology · JPThe Open University of Japan · JP

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMany genetic/genomic disorders are caused by genomic rearrangements. Standard methods can often characterize these variations only partly, e.g., copy number changes or breakpoints. It is important to fully understand the order and orientation of rearranged fragments, with precise breakpoints, to know the pathogenicity of the rearrangements.

methodsWe performed whole-genome-coverage nanopore sequencing of long DNA reads from four patients with chromosomal translocations. We identified rearrangements relative to a reference human genome, subtracted rearrangements shared by any of 33 control individuals, and determined the order and orientation of rearranged fragments, with our newly developed analysis pipeline.

resultsWe describe the full characterization of complex chromosomal rearrangements, by filtering out genomic rearrangements seen in controls without the same disease, reducing the number of loci per patient from a few thousand to a few dozen. Breakpoint detection was very accurate; we usually see ~ 0 ± 1 base difference from Sanger sequencing-confirmed breakpoints. For one patient with two reciprocal chromosomal translocations, we find that the translocation points have complex rearrangements of multiple DNA fragments involving 5 chromosomes, which we could order and orient by an automatic algorithm, thereby fully reconstructing the rearrangement. A rearrangement is more than the sum of its parts: some properties, such as sequence loss, can be inferred only after reconstructing the whole rearrangement. In this patient, the rearrangements were evidently caused by shattering of the chromosomes into multiple fragments, which rejoined in a different order and orientation with loss of some fragments.

conclusionsWe developed an effective analytic pipeline to find chromosomal aberration in congenital diseases by filtering benign changes, only from long read sequencing. Our algorithm for reconstruction of complex rearrangements is useful to interpret rearrangements with many breakpoints, e.g., chromothripsis. Our approach promises to fully characterize many congenital germline rearrangements, provided they do not involve poorly understood loci such as centromeric repeats.

Indexed as

Gene RearrangementGenome-Wide Association StudyGerm-Line MutationChromosome AberrationsChromosome BreakpointsGenetic Association StudiesGenetic Predisposition to DiseaseGenome, HumanGenomicsHigh-Throughput Nucleotide SequencingHumansTranslocation, GeneticWhole Genome SequencingChromosomal translocations/rearrangementsChromothripsisLong read sequencingStructural variation

Identifiers

PMID32731881
PMCPMC7393826
OpenAlexW3046682179

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LicenceCC BY
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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.