Literature DB >> 30794984

Rational "Error Elimination" Approach to Evaluating Molecular Barcoded Next-Generation Sequencing Data Identifies Low-Frequency Mutations in Hematologic Malignancies.

Saradhi Mallampati1, Dzifa Y Duose2, Michael A Harmon3, Meenakshi Mehrotra4, Rashmi Kanagal-Shamanna4, Stephanie Zalles4, Ignacio I Wistuba2, Xiaoping Sun5, Rajyalakshmi Luthra6.   

Abstract

The emergence of highly sensitive molecular diagnostic approaches, such as droplet digital PCR, has allowed the accurate identification of low-frequency variant alleles in clinical specimens; however, the multiplex capabilities of droplet digital PCR for variant detection are inadequate. The incorporation of molecular barcodes or unique IDs into next-generation sequencing libraries through PCR has enabled the detection of low-frequency variant alleles across multiple genomic regions. However, rational library preparation and sequencing data analytic strategies that integrate molecular barcodes have rarely been applied to clinical settings. In this study, we evaluated the parameters that are crucial in the use of molecular barcodes in next-generation sequencing for genotyping clinical specimens from patients with hematologic malignancies. The uniform incorporation of molecular barcodes into DNA templates through PCR was found to be crucial, and the extent of uniformity was governed by multiple interdependent variables. An error elimination strategy was developed for removing sequencing background errors by using molecular barcode sequence information as an alternative to the conventional error correction approach. This approach was successfully used to identify mutations with frequencies as low as 0.15%, and the clonal heterogeneity of hematologic malignancies was revealed. These findings have implications for elucidating heterogeneity and temporal and spatial clonal evolution, evaluating response to therapy, and monitoring relapse in patients with hematologic malignancies.
Copyright © 2019 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2019        PMID: 30794984      PMCID: PMC6521894          DOI: 10.1016/j.jmoldx.2019.01.008

Source DB:  PubMed          Journal:  J Mol Diagn        ISSN: 1525-1578            Impact factor:   5.568


  39 in total

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Authors:  John R ten Bosch; Wayne W Grody
Journal:  J Mol Diagn       Date:  2008-10-02       Impact factor: 5.568

2.  Detection and quantification of rare mutations with massively parallel sequencing.

Authors:  Isaac Kinde; Jian Wu; Nick Papadopoulos; Kenneth W Kinzler; Bert Vogelstein
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3.  Detection of ultra-rare mutations by next-generation sequencing.

Authors:  Michael W Schmitt; Scott R Kennedy; Jesse J Salk; Edward J Fox; Joseph B Hiatt; Lawrence A Loeb
Journal:  Proc Natl Acad Sci U S A       Date:  2012-08-01       Impact factor: 11.205

4.  The real cost of sequencing: higher than you think!

Authors:  Andrea Sboner; Xinmeng Jasmine Mu; Dov Greenbaum; Raymond K Auerbach; Mark B Gerstein
Journal:  Genome Biol       Date:  2011-08-25       Impact factor: 13.583

Review 5.  Targeting oncogenic Ras signaling in hematologic malignancies.

Authors:  Ashley F Ward; Benjamin S Braun; Kevin M Shannon
Journal:  Blood       Date:  2012-08-16       Impact factor: 22.113

6.  Identification of errors introduced during high throughput sequencing of the T cell receptor repertoire.

Authors:  Phuong Nguyen; Jing Ma; Deqing Pei; Caroline Obert; Cheng Cheng; Terrence L Geiger
Journal:  BMC Genomics       Date:  2011-02-11       Impact factor: 3.969

7.  Genomic analysis of the clonal origins of relapsed acute lymphoblastic leukemia.

Authors:  Charles G Mullighan; Letha A Phillips; Xiaoping Su; Jing Ma; Christopher B Miller; Sheila A Shurtleff; James R Downing
Journal:  Science       Date:  2008-11-28       Impact factor: 47.728

Review 8.  Mutational heterogeneity in human cancers: origin and consequences.

Authors:  Jesse J Salk; Edward J Fox; Lawrence A Loeb
Journal:  Annu Rev Pathol       Date:  2010       Impact factor: 23.472

9.  Sequence-specific error profile of Illumina sequencers.

Authors:  Kensuke Nakamura; Taku Oshima; Takuya Morimoto; Shun Ikeda; Hirofumi Yoshikawa; Yuh Shiwa; Shu Ishikawa; Margaret C Linak; Aki Hirai; Hiroki Takahashi; Md Altaf-Ul-Amin; Naotake Ogasawara; Shigehiko Kanaya
Journal:  Nucleic Acids Res       Date:  2011-05-16       Impact factor: 16.971

10.  Identification and correction of systematic error in high-throughput sequence data.

Authors:  Frazer Meacham; Dario Boffelli; Joseph Dhahbi; David I K Martin; Meromit Singer; Lior Pachter
Journal:  BMC Bioinformatics       Date:  2011-11-21       Impact factor: 3.169

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