A major goal of human genetics is to identify and discern how genetic variation contributes to variation in human disease risk. Human geneticists have made remarkable progress identifying disease gene variants with large phenotypic effects, but finding the genetic causes of common, complex disorders like autism, has proven more difficult. While family-based linkage studies have identified regions of the genome harboring putative autism susceptibility alleles, the apparent great genetic heterogeneity of the disorder has prevented the identification of disease causing variants.
We aim to reduce this heterogeneity by performing high-throughput, highly accurate microarray-based resequencing of 2 270kb X chromosomes regions among 314 male affected sibpairs from the Autism Genetic Resource Exchange (ACRE) sample collection. The first region contains the FMR1 gene. Fragile X syndrome is caused by a trinucleotide repeat sequence at FMR1 and approximately 20% of patients with this disorder exhibit symptoms consistent with the DSM IV diagnosis of autism. Our goal is to identify others mutations leading to a diagnosis of autism. The second region contains candidate genes in the vicinity of marker DXS1047 that shows suggestive linkage in the AGRE sample. Rare alleles will be confirmed within pedigrees while common alleles will be genotyped across the entire AGRE sample collection. Rapid resequencing can identify disease gene variants, reduce heterogeneity in mapping studies, and provide insight into autism enabling a greater concordance between the patient genotype and autism phenotype. We believe that the approach we propose will eventually be required to dissect human genomic regions harboring susceptibility alleles to common complex diseases like autism, whether these regions are discovered through family-based linkage studies or whole genome association studies in a case-control design. The genetic causes of autism, a common pervasive developmental disorder (FDD), remain largely undiscovered. We propose using DMA chips to resequence genes that may harbor mutations that cause autism. Identifying the genetic basis of autism could enable more rapid diagnostic testing and provide insight into the root causes and eventually pave the way for better treatments of this increasingly common disorder.

Agency
National Institute of Health (NIH)
Institute
National Institute of Mental Health (NIMH)
Type
Research Project (R01)
Project #
5R01MH076439-02
Application #
7128522
Study Section
Special Emphasis Panel (ZMH1-ERB-L (06))
Program Officer
Lehner, Thomas
Project Start
2005-09-30
Project End
2010-07-31
Budget Start
2006-08-01
Budget End
2007-07-31
Support Year
2
Fiscal Year
2006
Total Cost
$552,399
Indirect Cost
Name
Emory University
Department
Genetics
Type
Schools of Medicine
DUNS #
066469933
City
Atlanta
State
GA
Country
United States
Zip Code
30322
Qiao, Ying; Mondal, Kajari; Trapani, Valentina et al. (2014) Variant ATRX syndrome with dysfunction of ATRX and MAGT1 genes. Hum Mutat 35:58-62
Ezewudo, Matthew; Zwick, Michael E (2013) Evaluating rare variants in complex disorders using next-generation sequencing. Curr Psychiatry Rep 15:349
Mondal, Kajari; Ramachandran, Dhanya; Patel, Viren C et al. (2012) Excess variants in AFF2 detected by massively parallel sequencing of males with autism spectrum disorder. Hum Mol Genet 21:4356-64
Mondal, Kajari; Shetty, Amol Carl; Patel, Viren et al. (2011) Targeted sequencing of the human X chromosome exome. Genomics 98:260-5
Patel, Viren C; Mondal, Kajari; Shetty, Amol Carl et al. (2010) Microarray oligonucleotide probe designer (MOPeD): A web service. Open Access Bioinformatics 2:145-155
Shetty, Amol Carl; Athri, Prashanth; Mondal, Kajari et al. (2010) SeqAnt: a web service to rapidly identify and annotate DNA sequence variations. BMC Bioinformatics 11:471
Okou, David T; Locke, Adam E; Steinberg, Karyn M et al. (2009) Combining microarray-based genomic selection (MGS) with the Illumina Genome Analyzer platform to sequence diploid target regions. Ann Hum Genet 73:502-13
Hegde, Madhuri R; Chin, Ephrem L H; Mulle, Jennifer G et al. (2008) Microarray-based mutation detection in the dystrophin gene. Hum Mutat 29:1091-9
Okou, David T; Steinberg, Karyn Meltz; Middle, Christina et al. (2007) Microarray-based genomic selection for high-throughput resequencing. Nat Methods 4:907-9