TY - JOUR
T1 - Accurate Typing of Human Leukocyte Antigen Class I Genes by Oxford Nanopore Sequencing
AU - Liu, Chang
AU - Xiao, Fangzhou
AU - Hoisington-Lopez, Jessica
AU - Lang, Kathrin
AU - Quenzel, Philipp
AU - Duffy, Brian
AU - Mitra, Robi D.
N1 - Funding Information:
Supported by the Washington University Hematology Scholars K12 award K12-HL087107-07 (C.L.), NIH grants U01MH109133 and R01NS076993 (R.D.M.), and Children's Discovery Institute grant MC-II-2016-533 (R.D.M.).
Publisher Copyright:
© 2018 American Society for Investigative Pathology and the Association for Molecular Pathology
PY - 2018/7
Y1 - 2018/7
N2 - Oxford Nanopore Technologies' MinION has expanded the current DNA sequencing toolkit by delivering long read lengths and extreme portability. The MinION has the potential to enable expedited point-of-care human leukocyte antigen (HLA) typing, an assay routinely used to assess the immunologic compatibility between organ donors and recipients, but the platform's high error rate makes it challenging to type alleles with accuracy. We developed and validated accurate typing of HLA by Oxford nanopore (Athlon), a bioinformatic pipeline that i) maps nanopore reads to a database of known HLA alleles, ii) identifies candidate alleles with the highest read coverage at different resolution levels that are represented as branching nodes and leaves of a tree structure, iii) generates consensus sequences by remapping the reads to the candidate alleles, and iv) calls the final diploid genotype by blasting consensus sequences against the reference database. Using two independent data sets generated on the R9.4 flow cell chemistry, Athlon achieved a 100% accuracy in class I HLA typing at the two-field resolution.
AB - Oxford Nanopore Technologies' MinION has expanded the current DNA sequencing toolkit by delivering long read lengths and extreme portability. The MinION has the potential to enable expedited point-of-care human leukocyte antigen (HLA) typing, an assay routinely used to assess the immunologic compatibility between organ donors and recipients, but the platform's high error rate makes it challenging to type alleles with accuracy. We developed and validated accurate typing of HLA by Oxford nanopore (Athlon), a bioinformatic pipeline that i) maps nanopore reads to a database of known HLA alleles, ii) identifies candidate alleles with the highest read coverage at different resolution levels that are represented as branching nodes and leaves of a tree structure, iii) generates consensus sequences by remapping the reads to the candidate alleles, and iv) calls the final diploid genotype by blasting consensus sequences against the reference database. Using two independent data sets generated on the R9.4 flow cell chemistry, Athlon achieved a 100% accuracy in class I HLA typing at the two-field resolution.
UR - http://www.scopus.com/inward/record.url?scp=85048956834&partnerID=8YFLogxK
U2 - 10.1016/j.jmoldx.2018.02.006
DO - 10.1016/j.jmoldx.2018.02.006
M3 - Article
C2 - 29625249
AN - SCOPUS:85048956834
SN - 1525-1578
VL - 20
SP - 428
EP - 435
JO - Journal of Molecular Diagnostics
JF - Journal of Molecular Diagnostics
IS - 4
ER -