Evidence map›Paper›PMID 41573841›Full record

ArticlebioRxiv : the preprint server for biology2025

Expanding the Genome in a Bottle Truth Set: Detection and Validation of Novel Low-frequency Variants Using High-accuracy NanoSeq.

Yang Zhang, Hsu Chao, Muchun Niu, Christopher M Grochowski, Kavya Kottapalli, Sravya V Bhamidipati, Donna M Muzny, Richard A Gibbs, Chenghang Zong, Harsha Doddapaneni

Abstract readPreprint
In one paragraph

Article in bioRxiv : the preprint server for biology, 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

10 authors.

Yang ZhangQuantative and Computational Biology Graduate Program, Baylor College of Medicine.ORCID 0000-0002-2519-7263
Hsu ChaoHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Muchun NiuDepartment of Molecular and Human Genetics, Baylor College of Medicine.ORCID 0000-0003-3221-3695
Christopher M GrochowskiHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Kavya KottapalliHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Sravya V BhamidipatiHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Donna M MuznyHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Richard A GibbsHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.
Chenghang ZongHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.ORCID 0000-0002-8337-8038
Harsha DoddapaneniHuman Genome Sequencing Center, Baylor College of Medicine, Houston, TX, 77030, USA.

Funding

Comprehensive Somatic Variant Characterization at the HGSCUM1DA058229 · NIDA · BAYLOR COLLEGE OF MEDICINE · PI Harsha Vardhan Doddapaneni, RICHARD A GIBBS · 2023 to 2026
$15.0M
Develop accurate high-coverage and high-throughput single-cell Duplex-seq chemistry and multi-omics platforms for simultaneous profiling of somatic mutation and the transcriptome in single human cellsUG3NS132132 · NINDS · BAYLOR COLLEGE OF MEDICINE · PI ZONG, CHENGHANG · 2023 to 2024
$794k
NIDA NIH HHS UM1 DA058229NINDS NIH HHS UG3 NS132132
6 · The paper itself

Abstract

Somatic mutations record tissue molecular history and inform risk, prognosis, and therapy, yet their variant allele fractions often fall below the reliable detection limit of conventional short-read sequencing. In contrast, duplex sequencing technology featured by NanoSeq applies the principle of single molecule detection and thereby overcomes the limitation. However, the original NanoSeq protocol relies on the restriction enzyme-based genome fragmentation, which constrained its genome coverage to 30-40%. To enable whole-genome discovery with duplex-level fidelity, we pursued two complementary approaches to optimize the NanoSeq protocol: (i) a restriction-enzyme strategy densifies accessible sites using orthogonal 4-bp cutters; and (ii) a workflow using sonication followed by mung bean nuclease with T4 polynucleotide kinase, Klenow fragment and dATP/ddBTP mixture (NanoSeq-MBN) to blunt and repair/A-tailing DNA, while minimizing repair artifacts. We systematically benchmarked their performance using Genome in a Bottle (GIAB) gold-standard sample mixtures. As a result, NanoSeq-MBN achieved near genome-wide, Poisson-like coverage with minimal trinucleotide-context bias and ultra-high accuracy. Beyond variants already present in the GIAB truth set, NanoSeq-MBN identified approximately 120,000-160,000

Indexed as

BenchmarkingGenome in a Bottle (GIAB)Low-Frequency VariantsNanoSeq Duplex SequencingSomatic Mosaicism

Identifiers

PMID41573841
PMCPMC12822697

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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.