Copy number variants (CNVs) - submicroscopic chromosomal deletions or duplications of 50 base pairs to more than a megabase - are a critical component of human genetic variation in both health and disease. Tens of thousands of CNVs are recognized in the human population across all chromosomes. Humans differ at many CNV sites, typically >100 per individual. Because of their size, CNVs often affect gene content and are thus an important contributor to diversity. CNVs have a high de novo mutation rate, with an estimated 1-3% of individuals bearing an allele not present in either parent. Consistently, CNVs are a common mutation in genetic disorders, including intellectual disability, neuropsychiatric disorders, structural birth defects and others, as well as cancer in the form of somatic mutations. Identifying the genetic and environmental factors that determine an individual's risk of forming new CNVs requires that candidate factors be assessed in prospective, hypothesis- driven and controlled experiments. We developed a human in vitro cell system that allows scoring of de novo CNV formation genome-wide in an experimental setting through application of microarrays and/or mate-pair sequencing to manipulated cell clones. This approach demonstrated that two mechanistically distinct replication inhibitors induce CNVs in cell culture, suggesting that any condition that leads to replication stress might induce deleterious CNVs. Many further candidate environmental and genetic CNV risk factors must be studied in this hypothesis-testing approach, but the slow, laborious and expensive nature of current methods has impeded rapid and extensive expanded application. The purpose of this project is to develop improved and rapid methods for experimental CNV detection, which will be achieved by exploiting knowledge gained from prior efforts. Rationally designed assays will be created and compared that have a restricted focus on hotspots of increased CNV formation.
In Aim 1, an in-depth comparison of human fibroblasts and lymphoblastoid cells will be performed with respect to the location of CNV hotspots and their association with fragile sites and transcription units. This will yield a se of characterized hotspots broadly informative to all human CNV formation.
In Aim 2, a series of innovative approaches for high throughput CNV detection will be developed and their utility compared for experimental and screening applications. Optimized tools will be used in future studies to elucidate the mechanisms of CNV formation and how these are modulated by environmental stresses.

Public Health Relevance

Copy number variants (CNVs) - submicroscopic chromosomal deletions or duplications of 50 base pairs to more than a megabase - are a critical component of human genetic variation in health and disease. Identifying the genetic and environmental factors that determine the risk of forming new CNVs requires that candidate factors be assessed in controlled experiments. The project will develop improved methods for experimental CNV detection through a rational approach directed at hotspots of increased CNV formation and use these new assays to test specific hypotheses regarding CNV risk factors.

Agency
National Institute of Health (NIH)
Institute
National Institute of Environmental Health Sciences (NIEHS)
Type
Exploratory/Developmental Grants (R21)
Project #
1R21ES022311-01A1
Application #
8582129
Study Section
Molecular Genetics A Study Section (MGA)
Program Officer
Shaughnessy, Daniel
Project Start
2013-08-06
Project End
2015-06-30
Budget Start
2013-08-06
Budget End
2014-06-30
Support Year
1
Fiscal Year
2013
Total Cost
$224,925
Indirect Cost
$74,925
Name
University of Michigan Ann Arbor
Department
Pathology
Type
Schools of Medicine
DUNS #
073133571
City
Ann Arbor
State
MI
Country
United States
Zip Code
48109
Glover, Thomas W; Wilson, Thomas E (2016) Molecular biology: Breaks in the brain. Nature 532:46-7
Wilson, Thomas E; Arlt, Martin F; Park, So Hae et al. (2015) Large transcription units unify copy number variants and common fragile sites arising under replication stress. Genome Res 25:189-200