Evidence map›Paper›PMID 27341568›Full record

ArticlePloS one2016

Estimating Exceptionally Rare Germline and Somatic Mutation Frequencies via Next Generation Sequencing.

Jordan Eboreime, Soo-Kung Choi, Song-Ro Yoon, Norman Arnheim, Peter Calabrese

Abstract read
In one paragraph

Article in PloS one, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing 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

10 citing papers in PubMed.

  1. Review
  2. Article
  3. Article
  4. Article
  5. Article
  6. Genetic analysis of tri-allelic patterns at the CODIS STR loci.Molecular genetics and genomics : MGG · 2020
    Article
  7. Predicting the Number of Bases to Attain Sufficient Coverage in High-Throughput Sequencing Experiments.Journal of computational biology : a journal of computational molecular cell biology · 2020
    Article
  8. Article
  9. Article
  10. Article
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.

Jordan EboreimeMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA 90089-2910, United States of America.
Soo-Kung ChoiMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA 90089-2910, United States of America.
Song-Ro YoonMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA 90089-2910, United States of America.
Norman ArnheimMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA 90089-2910, United States of America.
Peter CalabreseMolecular and Computational Biology Program, University of Southern California, Los Angeles, CA 90089-2910, United States of America.

Funding

USC/NORRIS COMPREHENSIVE CANCER CENTER (CORE) SUPPORTP30CA014089 · NCI · UNIVERSITY OF SOUTHERN CALIFORNIA · PI Fumito Ito · 1985 to 2026
$181.4M
Research Resource for Human Organs and Tissues (U42)U42OD011158 · OD · NATIONAL DISEASE RESEARCH INTERCHANGE · PI BELL, THOMAS J · 2012 to 2025
$25.0M
GENETIC &MOLECULAR STUDIES OF HUMAN &MOUSE RDNAR01GM036745 · NIGMS · UNIVERSITY OF SOUTHERN CALIFORNIA · PI ARNHEIM, NORMAN, CALABRESE, PETER PAUL · 1985 to 2017
$8.5M
NCI NIH HHS P30 CA014089NIGMS NIH HHS R01 GM036745NIH HHS U42 OD011158
6 · The paper itself

Abstract

We used targeted next generation deep-sequencing (Safe Sequencing System) to measure ultra-rare de novo mutation frequencies in the human male germline by attaching a unique identifier code to each target DNA molecule. Segments from three different human genes (FGFR3, MECP2 and PTPN11) were studied. Regardless of the gene segment, the particular testis donor or the 73 different testis pieces used, the frequencies for any one of the six different mutation types were consistent. Averaging over the C>T/G>A and G>T/C>A mutation types the background mutation frequency was 2.6x10-5 per base pair, while for the four other mutation types the average background frequency was lower at 1.5x10-6 per base pair. These rates far exceed the well documented human genome average frequency per base pair (~10-8) suggesting a non-biological explanation for our data. By computational modeling and a new experimental procedure to distinguish between pre-mutagenic lesion base mismatches and a fully mutated base pair in the original DNA molecule, we argue that most of the base-dependent variation in background frequency is due to a mixture of deamination and oxidation during the first two PCR cycles. Finally, we looked at a previously studied disease mutation in the PTPN11 gene and could easily distinguish true mutations from the SSS background. We also discuss the limits and possibilities of this and other methods to measure exceptionally rare mutation frequencies, and we present calculations for other scientists seeking to design their own such experiments.

Indexed as

Gene FrequencyGerm-Line MutationHigh-Throughput Nucleotide SequencingMutationBase SequenceDNA DamageHumansMutation RatePolymerase Chain Reaction

Identifiers

PMID27341568
PMCPMC4920415

What OpenQuestion holds

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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.