Genomes evolve and diversify through di?erent mechanisms, including small point mutations, but also larger, structural variations (SV). SVs can be mediated by simple repeats and microhomology based recombination (termed 'progressive SVs' in this proposal). However, progressive SV mechanisms cannot explain all forms of large genomic variation; sometimes, more 'complex mechanisms' are needed; examples include Breakage Fusion Bridge, and Chromothripsis. Moreover, there is little understanding of the genetic mechanisms of genome instability that lead to complex SV formation. It is suspected that random viral genome insertions into the genome can on occasion disrupt key genes, causing genome instability and hyper-variability. To address these problems, the proposal will design and implement computational methods to (a) reconstruct and validate episomal structures of viral genome insertions; (b) determine if genomic sequence sampled from tumor genomes has a signature of complex variation; and, (b) phase and sub-type regions with complex SV including KIR and HLA; As clinical/translational applications of genomics come to the forefront, the impact of complex SVs on the phenotype of an individual become increasingly important. Understanding the computational signatures of BFB and Chromothripsis will help sub-type and characterize cancers. The knowledge of KIR/HLA sub-type will be correlated with immune related phenotypes, and the reconstruction of viral episomes will help clarify the etiology of virus mediated cancers. Thus, the proposed set of computational tools will directly impact the translational/medical aspect of genomics.

Public Health Relevance

The proposed computational tools will be used to detect complex structural variations in human genomes, and will provide a starting point for understanding their role in disease. The development of computational signatures of BFB and Chromothripsis will help sub-type and characterize cancers; similarly, the knowledge of KIR/HLA sub- type could be correlated with immune related phenotypes, and the reconstruction of viral episomes will help clarify the etiology of virus mediated cancers. Thus, the proposed set of computational tools will have an immediate and long term impact on human health.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM114362-04
Application #
9616279
Study Section
Genomics, Computational Biology and Technology Study Section (GCAT)
Program Officer
Krasnewich, Donna M
Project Start
2016-01-01
Project End
2019-12-31
Budget Start
2019-01-01
Budget End
2019-12-31
Support Year
4
Fiscal Year
2019
Total Cost
Indirect Cost
Name
University of California, San Diego
Department
Biostatistics & Other Math Sci
Type
Schools of Arts and Sciences
DUNS #
804355790
City
La Jolla
State
CA
Country
United States
Zip Code
92093
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