. Approximately 45% of the human genome is occupied by Mobile genetic Elements (MEs). Small subsets of these are still active and belong to three different families: L1, Alu, and SVA. These active families can generate new copies known as Mobile Element Insertions (MEIs), which can be polymorphic in humans. To find MEIs, large consortia have performed Whole Genome Sequencing (WGS) on a wide range of human populations and diseases, and designed computational tools to analyze the resulting data. One such effort, the 1000 Genomes Project (1KGP), performed WGS on 2,504 individuals from 26 different world populations to discover both MEIs and other human genetic variation. As part of the 1KGP, I designed an algorithm to find MEIs, the Mobile Element Locator Tool (MELT), and performed discovery for all active human ME families. While I found over 16,000 polymorphic MEIs, the 1KGP left several remaining open-ended questions about how these sites could affect human genetic diversity and impact human traits and diseases. For this proposal, I will work to answer some of these questions by designing new computational and sequencing tools. I will then use these tools to test the hypothesis that specific classes of MEs generate the majority of ME-derived genetic diversity among human populations and produce diseases such as cancer. I will approach this question using two aims.
In Aim 1, I will develop computational tools to study how MEs have propagated in the human species. Then, I will adapt these tools to several non-human organisms to develop a model for ME mutagenesis and as a resource for the scientific community. Finally, I will use these new tools and one such model organism, canines, to understand ME distribution and propagation.
In aim 2, I will develop sequencing tools to analyze a particularly active version of the L1 ME. Using this assay I will characterize a large number of active L1s, and subsequently associate these active L1s with ME activity in cancer. Overall, these studies will provide a better understanding of the relationship between MEs and human phenotypes and disease.

Public Health Relevance

. This project aims to discover the underlying mechanisms of how mobile genetic elements are created and their impact on the human genome. To accomplish this, I will use the development of computional and sequencing based tools to characterize regions of the genome and patterns of inheritance that could predispose an individual to mobile genetic element mediated phenotypes or disease. Since mobile genetic elements are drivers for a wide range of genetic disorders and diseases, this project is relevant to the overall goals of the National Institutes of Health.

Agency
National Institute of Health (NIH)
Institute
National Human Genome Research Institute (NHGRI)
Type
Predoctoral Individual National Research Service Award (F31)
Project #
1F31HG009223-01
Application #
9190983
Study Section
Special Emphasis Panel (ZRG1-F08-B (20)L)
Program Officer
Gatlin, Christine L
Project Start
2016-08-08
Project End
2018-08-07
Budget Start
2016-08-08
Budget End
2017-08-07
Support Year
1
Fiscal Year
2016
Total Cost
$29,129
Indirect Cost
Name
University of Maryland Baltimore
Department
Type
Schools of Medicine
DUNS #
188435911
City
Baltimore
State
MD
Country
United States
Zip Code
21201
Gardner, Eugene J; Lam, Vincent K; Harris, Daniel N et al. (2017) The Mobile Element Locator Tool (MELT): population-scale mobile element discovery and biology. Genome Res 27:1916-1929