Evidence map›Paper›PMID 39900460›Full record

ReviewGenome research2025

The additional diagnostic yield of long-read sequencing in undiagnosed rare diseases.

Giulia F Del Gobbo, Kym M Boycott

Abstract readReview
In one paragraph

Review in Genome research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 27 papers.

0numbers the graph read from it
0cells of the map it votes in
27citing 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

27 citing papers in PubMed.

  1. Review
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  5. Spectrum of Hereditary Neuropathies in Adult Patients From Serbia.Journal of the peripheral nervous system : JPNS · 2026
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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

2 authors.

Giulia F Del GobboChildren's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada K1H 5B2.ORCID 0000-0001-7368-0033
Kym M BoycottChildren's Hospital of Eastern Ontario Research Institute, University of Ottawa, Ottawa, Ontario, Canada K1H 5B2; kboycott@cheo.on.ca.ORCID 0000-0003-4186-8052

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Long-read sequencing (LRS) is a promising technology positioned to study the significant proportion of rare diseases (RDs) that remain undiagnosed as it addresses many of the limitations of short-read sequencing, detecting and clarifying additional disease-associated variants that may be missed by the current standard diagnostic workflow for RDs. Some key areas where additional diagnostic yields may be realized include: (1) detection and resolution of structural variants (SVs); (2) detection and characterization of tandem repeat expansions; (3) coverage of regions of high sequence similarity; (4) variant phasing; (5) the use of de novo genome assemblies for reference-based or graph genome variant detection; and (6) epigenetic and transcriptomic evaluations. Examples from over 50 studies support that the main areas of added diagnostic yield currently lie in SV detection and characterization, repeat expansion assessment, and phasing (with or without DNA methylation information). Several emerging studies applying LRS in cohorts of undiagnosed RDs also demonstrate that LRS can boost diagnostic yields following negative standard-of-care clinical testing and provide an added yield of 7%-17% following negative short-read genome sequencing. With this evidence of improved diagnostic yield, we discuss the incorporation of LRS into the diagnostic care pathway for undiagnosed RDs, including current challenges and considerations, with the ultimate goal of ending the diagnostic odyssey for countless individuals with RDs.

Indexed as

High-Throughput Nucleotide SequencingRare DiseasesSequence Analysis, DNAUndiagnosed DiseasesGenome, HumanHumans

Identifiers

PMID39900460
PMCPMC12047273

What Socratic holds

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LicenceCC BY-NC
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 Socratic graph.