Evidence map›Paper›PMID 26152304›Full record

ArticleNucleic acids research2015

A new method to prevent carry-over contaminations in two-step PCR NGS library preparations.

Volkhard Seitz, Sigrid Schaper, Anja Dröge, Dido Lenze, Michael Hummel, Steffen Hennig

Abstract read
In one paragraph

Article in Nucleic acids research, 2015. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 25 papers.

0numbers the graph read from it
0cells of the map it votes in
25citing 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

25 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

6 authors.

Volkhard SeitzInstitute of Pathology, Charité-University Medicine Berlin, Campus Benjamin Franklin, Berlin, Germany HS Diagnomics GmbH, Berlin, Germany volkhard.seitz@charite.de.
Sigrid SchaperHS Diagnomics GmbH, Berlin, Germany.
Anja DrögeHS Diagnomics GmbH, Berlin, Germany.
Dido LenzeInstitute of Pathology, Charité-University Medicine Berlin, Campus Benjamin Franklin, Berlin, Germany.
Michael HummelInstitute of Pathology, Charité-University Medicine Berlin, Campus Benjamin Franklin, Berlin, Germany michael.hummel@charite.de.
Steffen HennigHS Diagnomics GmbH, Berlin, Germany hennig@hsdiagnomics.de.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Two-step PCR procedures are an efficient and well established way to generate amplicon libraries for NGS sequencing. However, there is a high risk of cross-contamination by carry-over of amplicons from first to second amplification rounds, potentially leading to severe misinterpretation of results. Here we describe a new method able to prevent and/or to identify carry-over contaminations by introducing the K-box, a series of three synergistically acting short sequence elements. Our K-boxes are composed of (i) K1 sequences for suppression of contaminations, (ii) K2 sequences for detection of possible residual contaminations and (iii) S sequences acting as separators to avoid amplification bias. In order to demonstrate the effectiveness of our method we analyzed two-step PCR NGS libraries derived from a multiplex PCR system for detection of T-cell receptor beta gene rearrangements. We used this system since it is of high clinical relevance and may be affected by very low amounts of contaminations. Spike-in contaminations are effectively blocked by the K-box even at high rates as demonstrated by ultra-deep sequencing of the amplicons. Thus, we recommend implementation of the K-box in two-step PCR-based NGS systems for research and diagnostic applications demanding high sensitivity and accuracy.

Indexed as

DNA ContaminationHigh-Throughput Nucleotide SequencingSequence Analysis, DNACell LineComputational BiologyGene LibraryHumansPolymerase Chain Reaction

Identifiers

PMID26152304
PMCPMC4787772

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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.