Literature DB >> 27376474

Performance Characteristics and Validation of Next-Generation Sequencing for Human Leucocyte Antigen Typing.

Eric T Weimer1, Maureen Montgomery2, Rosanne Petraroia2, John Crawford2, John L Schmitz3.   

Abstract

High-resolution human leukocyte antigen (HLA) matching reduces graft-versus-host disease and improves overall patient survival after hematopoietic stem cell transplant. Sanger sequencing has been the gold standard for HLA typing since 1996. However, given the increasing number of new HLA alleles identified and the complexity of the HLA genes, clinical HLA typing by Sanger sequencing requires several rounds of additional testing to provide allele-level resolution. Although next-generation sequencing (NGS) is routinely used in molecular genetics, few clinical HLA laboratories use the technology. The performance characteristics of NGS HLA typing using TruSight HLA were determined using Sanger sequencing as the reference method. In total, 211 samples were analyzed with an overall accuracy of 99.8% (2954/2961) and 46 samples were analyzed for precision with 100% (368/368) reproducibility. Most discordant alleles were because of technical error rather than assay performance. More important, the ambiguity rate was 3.5% (103/2961). Seventy-four percentage of the ambiguities were within the DRB1 and DRB4 loci. HLA typing by NGS saves approximately $6000 per run when compared to Sanger sequencing. Thus, TruSight HLA assay enables high-throughput HLA typing with an accuracy, precision, ambiguity rate, and cost savings that should facilitate adoption of NGS technology in clinical HLA laboratories.
Copyright © 2016 American Society for Investigative Pathology and the Association for Molecular Pathology. Published by Elsevier Inc. All rights reserved.

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Year:  2016        PMID: 27376474     DOI: 10.1016/j.jmoldx.2016.03.009

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


  15 in total

Review 1.  Transplant genetics and genomics.

Authors:  Joshua Y C Yang; Minnie M Sarwal
Journal:  Nat Rev Genet       Date:  2017-03-13       Impact factor: 53.242

2.  Revisiting the potential power of human leukocyte antigen (HLA) genes on relationship testing by massively parallel sequencing-based HLA typing in an extended family.

Authors:  Riga Wu; Haixia Li; Dan Peng; Ran Li; Yinming Zhang; Bo Hao; Erwen Huang; Chenghao Zheng; Hongyu Sun
Journal:  J Hum Genet       Date:  2018-10-22       Impact factor: 3.172

3.  ALPHLARD-NT: Bayesian Method for Human Leukocyte Antigen Genotyping and Mutation Calling through Simultaneous Analysis of Normal and Tumor Whole-Genome Sequence Data.

Authors:  Shuto Hayashi; Takuya Moriyama; Rui Yamaguchi; Shinichi Mizuno; Mitsuhiro Komura; Satoru Miyano; Hidewaki Nakagawa; Seiya Imoto
Journal:  J Comput Biol       Date:  2019-04-03       Impact factor: 1.479

Review 4.  Strategies for the measurements of expression levels and half-lives of HLA class I allotypes.

Authors:  Malini Raghavan; Brogan Yarzabek; Anita J Zaitouna; Sujatha Krishnakumar; Daniel S Ramon
Journal:  Hum Immunol       Date:  2019-02-05       Impact factor: 2.850

5.  Brassica and Sinapis Seeds in Medieval Archaeological Sites: An Example of Multiproxy Analysis for Their Identification and Ethnobotanical Interpretation.

Authors:  Giovanna Bosi; Simona De Felice; Michael J Wilkinson; Joël Allainguillaume; Laura Arru; Juri Nascimbene; Fabrizio Buldrini
Journal:  Plants (Basel)       Date:  2022-08-12

Review 6.  A long road/read to rapid high-resolution HLA typing: The nanopore perspective.

Authors:  Chang Liu
Journal:  Hum Immunol       Date:  2020-05-01       Impact factor: 2.211

7.  High resolution HLA haplotyping by imputation for a British population bioresource.

Authors:  Matt J Neville; Wanseon Lee; Peter Humburg; Daniel Wong; Martin Barnardo; Fredrik Karpe; Julian C Knight
Journal:  Hum Immunol       Date:  2017-01-19       Impact factor: 2.850

8.  HLAProfiler utilizes k-mer profiles to improve HLA calling accuracy for rare and common alleles in RNA-seq data.

Authors:  Martin L Buchkovich; Chad C Brown; Kimberly Robasky; Shengjie Chai; Sharon Westfall; Benjamin G Vincent; Eric T Weimer; Jason G Powers
Journal:  Genome Med       Date:  2017-09-27       Impact factor: 11.117

9.  Next Generation Sequencing: From Research Area to Clinical Practice.

Authors:  Chiara Di Resta; Maurizio Ferrari
Journal:  EJIFCC       Date:  2018-11-07

10.  ALPHLARD: a Bayesian method for analyzing HLA genes from whole genome sequence data.

Authors:  Shuto Hayashi; Rui Yamaguchi; Shinichi Mizuno; Mitsuhiro Komura; Satoru Miyano; Hidewaki Nakagawa; Seiya Imoto
Journal:  BMC Genomics       Date:  2018-11-01       Impact factor: 3.969

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