HIGH-THROUGHPUT SHOTGUN SEQUENCING OF THE HLA-DQA1 GENE USING NEXT GENERATION SEQUENCING.

Aim We have evaluated a long-range PCR and high-throughput shotgun sequencing approach to better characterize the extent of sequence variation throughout the entire genomic HLA-DQA1 gene using next generation sequencing (NGS). Methods Multiple primer pairs were designed with forward primers located within the 5’-UTR and reverse primers located within the 3’-UTR to amplify the complete genomic HLA-DQA1 gene. Primers were then validated for successful amplification of all major HLA-DQA1 allele groups (HLA-DQA1∗01-∗06). Library preparation and sequencing were performed using the Ion Torrent PGM system (Life Technologies). Pseudogene and off-target co-amplification were estimated by alignment to the human reference genome and HLA-DQA2. Genotype assignments were obtained by aligning exonic and intronic sequence reads to the IMGT-HLA database using software provided by Life Technologies and Omixon. Results Sequence analysis of 18 homo- and 90 heterozygous samples demonstrated not only complete concordance with genotypes previously typed by Luminex PCR-SSOP method (One Lambda) but also higher resolution genotypes obtained by shotgun sequencing data without ambiguity. Alignments incorporating intronic and flanking sequences were able to reliably detect intronic variations including insertions and deletions. Conclusions Our results provide support for the use of short-read high-throughput shotgun sequencing data for accurate and cost-effective HLA genotyping by NGS. Reliable sequence is obtained by long range amplification even when read length is constrained by the currently available technology. Informatics development is also key. The supplementary sequence information including definition of novel alleles due to intronic and untranslated sequence variation provides a framework for defining further allelic clusters and higher resolution DQA1 types that may also prove useful for disease association studies. Yamamoto: Life Technologies: Grant Research. Mallempati: Life Technologies: Grant Research. Bialozynski: Life Technologies: Employee. Shi: Life Technologies: Employee. Major: Life Technologies: Grant Research. Hague: Life Technologies: Grant Research. Dinauer: Life Technologies: Employee. Tyan: Life Technologies: Grant Research. Fernandez-Vina: Life Technologies: Grant Research. Anderson: Life Technologies: Grant Research.