Between Dec 19, 2024 and Jan 2, 2025, datasets can be submitted to DRUM but will not be processed until after the break. Staff will not be available to answer email during this period, and will not be able to provide DOIs until after Jan 2. If you are in need of a DOI during this period, consider Dryad or OpenICPSR. Submission responses to the UDC may also be delayed during this time.
 

Computational Methods for Sequencing and Interpreting Killer-cell Immunoglobulin-like Receptors (KIRs) at Multiple Resolutions

2021-01
Loading...
Thumbnail Image

Persistent link to this item

Statistics
View Statistics

Journal Title

Journal ISSN

Volume Title

Title

Computational Methods for Sequencing and Interpreting Killer-cell Immunoglobulin-like Receptors (KIRs) at Multiple Resolutions

Published Date

2021-01

Publisher

Type

Thesis or Dissertation

Abstract

The era of personalized genetic medicine has arrived. It is now routine to sequence an individual’s DNA, either whole genome sequences (WGS) or targeted, as part of a patient’s medical plan. One of the exceptions is an ~200 kilobase region in chromosome 19 containing the killer-cell immunoglobulin-like receptors (KIR). These genes encode proteins that influence the actions of natural killer (NK) cells based on whether or not they bind with peptide-bound human leukocyte antigen receptors. This is evolutionary important to fight pathogens and mediate pregnancy. Modern medicine has correlated low-resolution KIR with many diseases and treatments, although the findings are often relatively vague and sometimes contradictory due to low resolution interpretation and/or small cohort sizes. Whether for personal medicine or population studies, the current best practices for KIR genotyping are to determine the presence/absence (PA) or copy number variation (CNV) of each gene using oligo- or primer-based polymerase chain reaction.The goal of our research is to advance DNA sequencing and interpretation of human KIR haplotypes. To that end, we have created algorithms and workflows to enhance interpretations of KIR at resolutions from PA genotyping via short-read WGS to full-haplotype assembly from long-read targeted or whole-genome sequences. First, we developed the first workflow to efficiently and accurately capture, sequence, assemble, and annotate full KIR haplotype sequences. As part of this workflow, we designed small sequences to capture the DNA fragments. Next, we use the alignment pattern of those short sequences across finished KIR haplotypes to define and annotate haplotype structures. The results show, for the first time, that the KIR region is composed of 9 genes in 14 loci. Next, we annotated all 68 reported human haplotypes, aligned them at the structural level, and then refined the alignment down the base level, providing the first KIR haplotype multiple sequence alignment. These efforts have led to this region being the best annotated and most diverse in the human genome reference. We next leveraged the MSA to discover PA markers and leveraged them in the first KIR WGS genotyping application. It was evaluated independently and reported to be at least 97% accurate. These discoveries and inventions are the culmination of several computational methods we have developed that interpret KIR under different typing resolutions. This multi-resolution aspect is crucial to overall understanding; it improves resolution at any given level by leveraging references and/or markers from other resolutions. From low-resolution genotyping from any kind of DNA sequence to the first efficient full-haplotype assembly method, these results advance interpretation of this important genetic region to the personal and population levels.

Description

University of Minnesota Ph.D. dissertation. January 2021 Major: Biomedical Informatics and Computational Biology. Advisor: Rui Kuang. 1 computer file (PDF); 72 pages.

Related to

Replaces

License

Collections

Series/Report Number

Funding information

Isbn identifier

Doi identifier

Previously Published Citation

Other identifiers

Suggested citation

Roe, David. (2021). Computational Methods for Sequencing and Interpreting Killer-cell Immunoglobulin-like Receptors (KIRs) at Multiple Resolutions. Retrieved from the University Digital Conservancy, https://hdl.handle.net/11299/219420.

Content distributed via the University Digital Conservancy may be subject to additional license and use restrictions applied by the depositor. By using these files, users agree to the Terms of Use. Materials in the UDC may contain content that is disturbing and/or harmful. For more information, please see our statement on harmful content in digital repositories.