The broad, long-term objective of the proposed research is to develop a software product that can be used to facilitate the analysis of genetic changes in order to elucidate chromosomal abnormalities that underlie diseases such as autism spectrum disorder, bipolar disorder, and schizophrenia. Recent technological advances allow samples of DNA from patients to be analyzed on single nucleotide polymorphism (SNP) arrays, generating up to millions of data points from each sample. These data must be analyzed to identify chromosomal abnormalities (e.g. DNA mutations, hemizygous or homozygous deletions, or translocations) that confer risk for these diseases. Two main approaches to data analysis include copy number estimates (based on the intensity of hybridization of samples to SNP arrays) and genotype analysis (revealing heterozygosity and homozygosity). Software such as Partek Genomics Suite (GS) exists to perform data analysis and visualization. A goal of this proposal is to add another dimension to the analysis of high density SNP data by incorporating information about the genetic relatedness of individuals into the data analysis repertoire of Partek GS.
The specific aims are as follows. (1) Incorporate SNPtrio into a new Partek GS module. This program analyzes genotype and copy number data from trios consisting of father, mother, and child and produces graphical and tabular descriptions of uniparental inheritance (e.g. uniparental isodisomy in which two copies of a chromosome or chromosomal segment are inherited from one parent;such a mechanism is known to cause a variety of mental retardation and other syndromes). (2) Incorporate SNPduo into PartekGS;this program performs pairwise analyses of SNP data sets, allowing the description of relatedness between individuals (by identity-by-state measurements). This is useful for a variety of purposes including identifying outliers, replicate samples, non-paternity, and confirming the genetic relatedness of members of a pedigree. (3) Incorporate a set of analytic tools that measure meiotic recombination in pedigrees consisting of one, two, or three generations. Such tools may be useful to exclude loci in association studies or to characterize mechanisms by which deletions or duplications occur. The software tools described in aims (1) to (3) will be assembled into a new prototype version of Partek GS.
In aim (4), this prototype will be used to analyze a set of 500,000 SNPs measured in 2,883 individuals from 700 families having two or more individuals affected with autism. This analysis will demonstrate the functionality of the Partek GS prototype, demonstrating the usefulness of incorporating new tools for genetic analysis to discover chromosomal abnormalities that may have roles in autism.

Public Health Relevance

Newly available technologies allow the measurement of millions of variations in DNA sequence between samples from individuals with diseases (such as autism and schizophrenia) relative to unaffected individuals (controls). The proposed research is designed to create software analysis tools that will facilitate the discovery of chromosomal abnormalities in diseases. This may lead to treatments for these disorders, serving a large public health need.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Small Business Innovation Research Grants (SBIR) - Phase I (R43)
Project #
1R43MH086192-01
Application #
7670133
Study Section
Special Emphasis Panel (ZRG1-GGG-J (10))
Program Officer
Grabb, Margaret C
Project Start
2009-06-17
Project End
2010-05-31
Budget Start
2009-06-17
Budget End
2010-05-31
Support Year
1
Fiscal Year
2009
Total Cost
$243,011
Indirect Cost
Name
Partek, Inc.
Department
Type
DUNS #
877038133
City
Chesterfield
State
MO
Country
United States
Zip Code
63005
Stevens, Eric L; Heckenberg, Greg; Baugher, Joseph D et al. (2012) Consanguinity in Centre d'Etude du Polymorphisme Humain (CEPH) pedigrees. Eur J Hum Genet 20:657-67
Stevens, Eric L; Heckenberg, Greg; Roberson, Elisha D O et al. (2011) Inference of relationships in population data using identity-by-descent and identity-by-state. PLoS Genet 7:e1002287