Development of New KIR and HLA Genotyping Method
The amount of genomic information being gathered in the NCBI Sequence Read Archive (NCBI SRA) has been increasing exponentially over the past 8 years. Although the volume of genomic data being stored has recently reached the 2000 terabyte mark, methods for analyzing these data have struggled to keep pace, especially in the area of reinterpreting sequence for highly variable genomic regions. My honors thesis work will focus on development of new methods for immunogenetic data analysis, creating interoperable systems based on publicly available data. This summers project involves the integration of the PING software tool, developed by Dr. Paul Norman, Senior Research Scientist at Stanford University and Dr. Jill Hollenbach, Assistant Professor at UCSF, with the NCBI SRA and the Immuno Polymorphism Database-KIR (IPD-KIR). The integration of PING with these databases will create a new, seamless method of killer-cell immunoglobulin-like receptor (KIR) genotyping for the whole genome and whole exome data that is publicly available on the NCBI SRA, and, ultimately will be expanded to include human leukocyte antigen (HLA) analysis. This new method will allow for the complete sequencing of KIR genes, the benefits of which will be shown by duplicating and expanding upon a study done on the association of chronic Hepatitis B (CHB) to KIR alleles. This will be done without having to do any fieldwork or sample collecting by using genomic information publicly available on the NCBI SRA. Because I am using PING and genome sequences instead of PCR, the KIR genotyping will be faster and more accurate, and the results will be completely reproducible because the information and tools will all be publicly available.
Message to Sponsor
- Major: Biochemistry
- Sponsor: Rose Hills
- Mentor: Jill Hollenbach, Neurology