The ability to predict how changes in genotype affect phenotype would have wide applications, perhaps most importantly the rational identification of genes whose mutation predisposes an individual to a given disease. In this grant, we propose to develop computational approaches for predicting the phenotypic outcome of genetic perturbations in humans, and to apply these approaches to discover genes associated with polygenic diseases. We focus in particular on discovering genes underlying neural tube defects (NTDs), the second most common cause of human birth defects affecting nearly 1 in 1000 live births world-wide, and the most common permanently disabling birth defect in the United States. Given the extremely polygenic nature of these diseases, it is critical that systems biology-based approaches such as those proposed here be applied to understand their complex genetic basis.
Each specific aim i nvolves development or validation of a distinct approach for associating genes with diseases, in particular neural tube birth defects, with Specific Aim 1 on the application of large-scale gene networks to associate genes with diseases, identifying specific candidate human genes likely to play roles in neural tube defects, Specific Aim 2 on applying comparative evolutionary principles to identify appropriate, non-obvious, animal models of diseases, using this strategy to identify additional candidate neural tube defect genes, and Specific Aim 3 focused on the experimental testing in the model vertebrate animal Xenopus laevis of genes deemed most likely to be associated with human neural tube defects, using first studies of expression of at least 200 genes, followed by knockdown of each of up to 40 genes, validating and characterizing resulting neural tube defects. We will then search for genetic variation in the top roughly 300 candidate genes in DNA from biopsies of human infants with spina bifida, thereby confirming genes'involvement in human NTDs and identifying specific variants underlying neural tube defects. This work will increase our understanding of the genetic basis of neural tube birth defects and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases. Success of these aims will also provide new theoretical methods for linking genes to diseases, a new theoretical framework for comparative analyses of diseases and mutational phenotypes across organisms, may suggest appropriate and new models for selected human diseases, and will provide mechanistic insights into the genetic basis of polygenic diseases in general and of neural tube defect diseases including spina bifida in particular.

Public Health Relevance

Neural tube defects are the second most common cause of human birth defects and the most common permanently disabling birth defect in the United States. The extremely polygenic nature of these diseases complicates traditional methods of finding candidate genes. This grant proposes systems-biology approaches to understand their complex genetic basis, developing and validating approaches for associating genes with polygenic diseases, in particular neural tube birth defects, and ultimately searching for relevant genetic variants in DNA from spina bifida patients. This work will increase our understanding of the genetic basis of neural tube birth defects and will be a step towards developing genetic diagnostics for susceptibility to these debilitating diseases.

Agency
National Institute of Health (NIH)
Institute
National Institute of General Medical Sciences (NIGMS)
Type
Research Project (R01)
Project #
5R01GM067779-08
Application #
8244476
Study Section
Modeling and Analysis of Biological Systems Study Section (MABS)
Program Officer
Krasnewich, Donna M
Project Start
2003-04-01
Project End
2014-03-31
Budget Start
2012-04-01
Budget End
2014-03-31
Support Year
8
Fiscal Year
2012
Total Cost
$268,155
Indirect Cost
$91,737
Name
University of Texas Austin
Department
Chemistry
Type
Schools of Arts and Sciences
DUNS #
170230239
City
Austin
State
TX
Country
United States
Zip Code
78712
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