The goal of the proposed work is to further develop and extend the functionality of our programs and protocols for the management and exchange of genetic data for the Human Leukocyte Antigen (HLA) and Killer cell Immunoglobulin-like Receptor (KIR) genes. These genes are central to immunity and critically important for human health, and constitute complex genetic systems with extraordinarily high levels of sequence and structural variation. Because these immunogenomic data have been generated using a wide variety of methods and under different nomenclature systems, cross-study data compatibility has remained an important and debilitating limitation to the field. The key element of the work proposed is the integration of the systems and standards that we have developed with existing public resources for the HLA and KIR gene systems to enable both reproducible and easily combined analyses of HLA and KIR data. To accomplish this, we will (1) expand and refine our Toolkit for Immunogenomic Data Exchange and Storage (TIDES) and Push Immunogenomics to the Next Generation (PING) software. We will improve TIDES by extending functionality for the KIR loci, expanding deployment options, expanding search and export capacity, refining the user interface, developing new algorithms for use with our novel Genotype List (GL) String data recording format, and better integrating TIDES with extant analytical software. We will automate our PING pipeline, extend its functionality to HLA class II loci, and integrate PING with TIDES; and (2) integrate PING, TIDES, and our GL Service with existing public registries, tools and databases. We will adapt PING to accept next generation sequencing (NGS) read data from the NCBI Sequence Read Archive (SRA) and Genotype and Phenotype Database (dbGaP), and to generate HLA and KIR genotypes using the NCBI MHC database (dbMHC) SBT Input tool. We will develop a LiftOver tool to manage GL Strings across multiple reference database releases. We will develop an HL7 messaging system that integrates GL Strings, GL Service Uniform Resource Identifiers (URIs) and Genetic Testing Registry (GTR) URIs, allowing the standard exchange of HLA and KIR typing results. We will partner with the NCBI to make these new services publically available, and will release all tools as free open source software. By facilitating ease of immunogenomic data management in this manner we will vastly increase the value of current and future data resources.

Public Health Relevance

Central to immunity and critically important for human health, the Human Leukocyte Antigen (HLA) and Killer- cell Immunoglobulin-like Receptor (KIR) molecules are encoded by complex genetic systems with extraordinarily high levels of variation. The goal of the proposed work is to further develop and refine our software tools for the management and exchange of data for the immunogenomic HLA and KIR genes, and integrate them with existing public data resources. These tools will extend the utility of these valuable data resources to facilitate a coherent, consistent, integrated immunogenomic data management strategy that will streamline and accelerate clinical and basic research, and advance the study of human health and disease with new perspectives and novel approaches.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM109030-03
Application #
9031118
Study Section
Biodata Management and Analysis Study Section (BDMA)
Program Officer
Ravichandran, Veerasamy
Project Start
2014-04-01
Project End
2017-02-28
Budget Start
2016-03-01
Budget End
2017-02-28
Support Year
3
Fiscal Year
2016
Total Cost
Indirect Cost
Name
Children's Hospital & Res Ctr at Oakland
Department
Type
DUNS #
076536184
City
Oakland
State
CA
Country
United States
Zip Code
94609
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Milius, Robert P; Heuer, Michael; George, Mike et al. (2016) The GL service: Web service to exchange GL string encoded HLA & KIR genotypes with complete and accurate allele and genotype ambiguity. Hum Immunol 77:249-256
Le Gall, Caroline; Laurent, Julie; Vince, Nicolas et al. (2016) Multidimensional reduction of multicentric cohort heterogeneity: An alternative method to increase statistical power and robustness. Hum Immunol 77:1024-1029
Norman, Paul J; Hollenbach, Jill A; Nemat-Gorgani, Neda et al. (2016) Defining KIR and HLA Class I Genotypes at Highest Resolution via High-Throughput Sequencing. Am J Hum Genet 99:375-91
Alicata, Claudia; Pende, Daniela; Meazza, Raffaella et al. (2016) Hematopoietic stem cell transplantation: Improving alloreactive Bw4 donor selection by genotyping codon 86 of KIR3DL1/S1. Eur J Immunol 46:1511-7

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