SUMMARY: UCLA researchers in the department of Medicine, Hematology and Oncology have developed software which facilitates the clinically relevant investigation of genetic antigen heterogeneity within human leukocytes
BACKGROUND:
Human leukocyte antigen system is a critical component of the immune system. A major part of this is a series of genes which encode for proteins that present antigens to the surface of T-cells. These antigens are what recognize threats and communicate that information to the cell and body. Given the criticality of these genes in the immune system is not surprising that there are many clinical implications in disease as well as immunity. Investigating the genetic heterogeneity of the genes that encode for the system is quintessential to understanding and designing targets to mitigate the effects of many immune related diseases. A difficulty in investigating this genetic heterogeneity is in the alignment of DNA and RNA sequencing results. This limitation has curtailed our understanding of genetic differences and their contribution to disease phenotypes. While there are tools to perform individual parts of this analysis, a centralized framework and toolkit for sequencing data and allele analysis is lacking. Development of such a system would facilitate tremendous progress in understanding how genetic heterogeneity within the human leukocyte antigen system contributes to disease and could lead to multiple clinical approaches to treating the numerous immune-based diseases that affect a significant portion of the population.
INNOVATION:
UCLA researchers have developed the Human Leukocyte Antigen Haplotype Analysis Toolkit (HLA-HAT) which is a unified framework to process DNA and RNA sequencing data using graph-based alignment into a custom reference genome. This framework utilizes DNA and RNA sequencing to align and construct custom reference genomes and allows its users to conduct the analysis of those assembled genomes at the single allele level. Combined with current genomic approaches, this innovation will allow clinicians to analyze the genome at the single allele level to study allelic imbalance as well as loss of allelic heterogeneity which are major causes of immune disease.
POTENTIAL APPLICATIONS:
ADVANTAGES:
DEVELOPMENT-TO-DATE:
A full version of the software has been created and made available.