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Updated: May 12, 2026
Integration of Wet and Dry Bench Processes Optimizes Targeted Next-generation Sequencing of Low-quality and Low-quantity Tumor Biopsies
Published on: April 11, 2016
Genotyping of 25 leukemia-associated genes in a single work flow by next-generation sequencing technology with low
Jenny Rinke1, Vivien Schäfer, Mathias Schmidt
1Abteilung für Hämatologie und Internistische Onkologie, Klinik für Innere Medizin II, Universitätsklinikum Jena, Jena, Germany.
Background:
We sought to establish a convenient, sensitive next-generation sequencing (NGS) method for genotyping the 26 most commonly mutated leukemia-associated genes in a single work flow and to optimize this method for low amounts of input template DNA.
Methods:
We designed 184 PCR amplicons that cover all of the candidate genes. NGS was performed with genomic DNA (gDNA) from a cohort of 10 individuals with chronic myelomonocytic leukemia. The results were compared with NGS data obtained from sequencing of DNA generated by whole-genome amplification (WGA) of 20 ng template gDNA. Differences between gDNA and WGA samples in variant frequencies were determined for 2 different WGA kits.
Results:
For gDNA samples, 25 of 26 genes were successfully sequenced with a sensitivity of 5%, which was achieved by a median coverage of 492 reads (range, 308-636 reads) per amplicon. We identified 24 distinct mutations in 11 genes. With WGA samples, we reliably detected all mutations above 5% sensitivity with a median coverage of 506 reads (range, 256-653 reads) per amplicon. With all variants included in the analysis, WGA amplification by the 2 kits tested yielded differences in variant frequencies that ranged from -28.19% to +9.94% [mean (SD) difference, -0.2% (4.08%)] and from -35.03% to +18.67% [mean difference, -0.75% (5.12%)].
Conclusions:
Our method permits simultaneous analysis of a wide range of leukemia-associated target genes in a single sequencing run. NGS can be performed after WGA of template DNA for reliable detection of variants without introducing appreciable bias.
