Evidence map›Paper›PMID 34527193›Full record

ReviewComputational and structural biotechnology journal2021

Application of long-read sequencing to the detection of structural variants in human cancer genomes.

Yoshitaka Sakamoto, Suzuko Zaha, Yutaka Suzuki, Masahide Seki, Ayako Suzuki

Abstract readReview
In one paragraph

Review in Computational and structural biotechnology journal, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.

0numbers the graph read from it
0cells of the map it votes in
31citing 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

31 citing papers in PubMed.

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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.

Yoshitaka SakamotoDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan.
Suzuko ZahaDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan.
Yutaka SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan.
Masahide SekiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan.
Ayako SuzukiDepartment of Computational Biology and Medical Sciences, Graduate School of Frontier Sciences, The University of Tokyo, 5-1-5 Kashiwanoha, Kashiwa, Chiba 277-8561, Japan.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

In recent years, the so-called long-read sequencing technology has had a substantial impact on various aspects of genome sciences. Here, we introduce recent studies of cancerous structural variants (SVs) using long-read sequencing technologies, namely Pacific Biosciences (PacBio) sequencers, Oxford Nanopore Technologies (ONT) sequencers, and linked-read methods. By taking advantage of long-read lengths, these technologies have enabled the precise detection of SVs, including long insertions by transposable elements, such as LINE-1. In addition to SV detection, the epigenome status (including DNA methylation and haplotype information) surrounding SV loci has also been unveiled by long-read sequencing technologies, to identify the effects of SVs. Among the various research fields in which long-read sequencing has been applied, cancer genomics has shown the most remarkable advances. In fact, many studies are beginning to shed light on the detection of SVs and the elucidation of their complex structures in various types of cancer. In the particular case of cancers, we summarize the technical limitations of the application of this technology to the analysis of clinical samples. We will introduce recent achievements from this viewpoint. However, a similar approach will be started for other applications in the near future. Therefore, by complementing the current short-read sequencing analysis, long-read sequencing should reveal the complex nature of human genomes in their healthy and disease states, which will open a new opportunity for a better understanding of disease development and for a novel strategy for drug development.

Indexed as

Cancer genomeLong-read sequencingStructural variant

Identifiers

PMID34527193
PMCPMC8350331

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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.