TitleComparative analyses of low, medium and high-resolution HLA typing technologies for human populations
Publication TypeJournal Article
Year of Publication2016
AuthorsGowda M., Ambardar S., Dighe N., Manjunath A., Shankaralingu C., Hallappa P., Harting J., Ranade S., Jagannathan L., Krishna S.
JournalJournal of Clinical & Cellular Immunology
Start Page399-406

Human Leukocyte Antigen (HLA) encoding genes are part of the major histocompatibility complex (MHC) on human chromosome 6. This region is one of the most polymorphic regions in the human genome. Prior knowledge of HLA allelic polymorphisms is clinically important for matching donor and recipient during organ/tissue transplantation. HLA allelic information is also useful in predicting immune responses to various infectious diseases, genetic disorders and autoimmune conditions. India harbors over a billion people and its population is untapped for HLA allelic diversity. In this study, we explored and compared three HLA typing methods for South Indian population, using Sequence-Specific Primers (SSP), NGS (Roche/454) and single- molecule sequencing (PacBio RS II) platforms. Over 1020 DNA samples were typed at low resolution using SSP method to determine the major HLA alleles within the South Indian population. These studies were followed up with medium resolution HLA typing of 80 samples based on exonic sequences on the Roche/454 sequencing system and high-resolution (6-8 digit) typing of 8 samples for HLA alleles of class I genes (HLA-A, B and C) and class II genes (HLA-DRB1 and DQB1) using PacBio RS II platform. The long reads delivered by SMRT technology, covered the full-length class I and class II genes/alleles in contiguous reads including untranslated regions, exons and introns, which provided phased SNP information. We have identified three novel alleles from PacBio data that were verified by Roche 454 sequencing. This is the first case study of HLA typing using second and third generation NGS technologies for an Indian population. The PacBio platform is a promising platform for large-scale HLA typing for establishing an HLA database for the untapped ethnic populations of India.