Abstract

Human leukocyte antigen (HLA) genes encode for immunoproteins, which recognize the self and non-self cell or organ types. Prior to the organ transplantation, the HLA class I (exon 1 and 2) and class II (exon 2) genes are constantly investigated to find HLA match between donor and recipients through low resolution technologies like serology, RFLP, PCR, Sanger and Next Generation Sequencing (Gowda et al 2016). There are many problems associated with low resolution HLA typing; only partial or limited information for HLA genes variations, more organ transplant rejection (graft vs host and vice-versa), lower life-span expectation after transplantation, and patients are maintained under anti-immune suppression drugs for a long period of time and expensive. Recently, Malali Gowda has developed a novel methodology to capture full-length of class I and II HLA genes and sequence using long read sequencing platforms such as Oxford Nanopore or PacBio (Gowda M, 2018). This technology is robust to sequence all the elements (UTRs, exons and introns) of class I and II genes. HLA allele calling is highly complex task, there are devoid of methods to sequence and resolve maternal and paternal alleles from HLA loci. To overcome these challenges, deep learning computing algorithms were used to develop HLA allele calling software called TULITA (Shivaram and Gowda 2018). HLA allelic sequence information from our technology is not only best for organ transplantation, it will also provide HLA allelic association with infectious (HIV, Hepatitis, Malaria, Tuberculosis, Leprosy, Leishmaniasis, etc) and autoimmune (Psoriasis, Ankylosing Spondylitis, Type 1 Diabetes Mellitus, Multiple Sclerosis, Rheumatoid Arthritis, etc) diseases.

Full Length Super-Resolution HLA typing is the most accurate method to provide one-time-one-stop solution to decode HLA alleles from any individuals and populations. Indian population is genetically diverse and an untapped HLA gene pool. The vision of this technology is ‘Make-in-India’ concept, established a network of institutes across India to decoder HLA gene pool from various populations. Full length HLA allelic information may act as “personalized predictive health record” for an individual and save many lives.