P069 Next generation sequencing based polymorphism and gene expression analysis of umbilical cord blood human leukocyte antigen

Abstract

Aim The aim of this research is to understand the possible functional changes that may result from variations in non-coding areas of HLA. Examining RNA by performing nucleotide sequencing and sequence copy enumeration using next-generation sequencing (NGS) methods may lead to identification of the causes of variation at the gene expression level. Method Mononuclear cells (MC) were isolated using Ficoll-Paque density separation method from 121 umbilical cord blood (UBC) samples which were registered at Tokai University Cord Blood Bank from 2000 through 2012. The total 48 RNA samples were selected based on both quality and quantity of 18 s and 28 s rRNAs. SeqCap RNA Enrichment System with customized capture beads (Roche) was applied for preparation of libraries. Barcoded 24 samples were pooled together and sequenced using MiSeq Reagent Kit v.2 (300-cycle) on MiSeq System (Illumina). DNA typing and calculation of read number in each of alleles were performed by SeaBass (in-house program) and other software. Results In total 110 HLA alleles including 11 A, 22 B, 14 C, 2 DRA, 18 DRB1, 4 DRB3, 2 DRB4, 2 DRB5, 11 DQA1, 13 DQB1, 3 DPA1 and 9 DPB1 were assigned from DNA typing of the 48 samples. Of them, one novel allele was detected in DQB1. In comparison to Class I loci, HLA-B had higher expression than HLA-A and -C which were lower but similar in expression. The expression level of HLA-DR (DRA + DRB1 + DRB3/4/5) was the highest among Class II loci. HLA-DP (DPA1 + DPB1) was higher than HLA-DQ (DQA1 + DQB1). Different expression levels between alpha and beta chains were observed in both HLA-DP and -DQ. HLA-DPB1 expression level was higher than HLA-DPA1. Trend differences among allele expression were observed; for example, HLA-A ∗ 24:02:02, HLA-DQA1 ∗ 03:02, and HLA-DQB1 ∗ 06:04 had higher expression than other alleles. Conclusions This study is the first report of UCB HLA expression level differences in the Japanese population. Our finding potentially provides more advantageous information for bone marrow transplant such as predicting risks of rejections due to higher expression HLA phenotypes. However, analyzing and generating statistic data in detail is necessary before application for clinical utilization.