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Open AccessJournal ArticleDOI

A Discovery Resource of Rare Copy Number Variations in Individuals with Autism Spectrum Disorder

TLDR
Of the 615 ASD cases analyzed on both SNP and CGH arrays, it was found that 13,572 of 21,346 of the CNVs were exclusively detected by the CGH array, which serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection.
Abstract
The identification of rare inherited and de novo copy number variations (CNVs) in human subjects has proven a productive approach to highlight risk genes for autism spectrum disorder (ASD). A variety of microarrays are available to detect CNVs, including single-nucleotide polymorphism (SNP) arrays and comparative genomic hybridization (CGH) arrays. Here, we examine a cohort of 696 unrelated ASD cases using a high-resolution one-million feature CGH microarray, the majority of which were previously genotyped with SNP arrays. Our objective was to discover new CNVs in ASD cases that were not detected by SNP microarray analysis and to delineate novel ASD risk loci via combined analysis of CGH and SNP array data sets on the ASD cohort and CGH data on an additional 1000 control samples. Of the 615 ASD cases analyzed on both SNP and CGH arrays, we found that 13,572 of 21,346 (64%) of the CNVs were exclusively detected by the CGH array. Several of the CGH-specific CNVs are rare in population frequency and impact previously reported ASD genes (e.g., NRXN1, GRM8, DPYD), as well as novel ASD candidate genes (e.g., CIB2, DAPP1, SAE1), and all were inherited except for a de novo CNV in the GPHN gene. A functional enrichment test of gene-sets in ASD cases over controls revealed nucleotide metabolism as a potential novel pathway involved in ASD, which includes several candidate genes for follow-up (e.g., DPYD, UPB1, UPP1, TYMP). Finally, this extensively phenotyped and genotyped ASD clinical cohort serves as an invaluable resource for the next step of genome sequencing for complete genetic variation detection.

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Citations
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Journal ArticleDOI

Finding the Genomic Basis of Local Adaptation: Pitfalls, Practical Solutions, and Future Directions.

TL;DR: The promises and challenges of these genome scan methods are reviewed, including correcting for the confounding influence of a species’ demographic history, biases caused by missing aspects of the genome, matching scales of environmental data with population structure, and other statistical considerations.
Journal ArticleDOI

Meta-analysis of GWAS of over 16,000 individuals with autism spectrum disorder highlights a novel locus at 10q24.32 and a significant overlap with schizophrenia

Richard Anney, +214 more
- 22 May 2017 - 
TL;DR: A significant genetic correlation with schizophrenia and association of ASD with several neurodevelopmental-related genes such as EXT1, ASTN2, MACROD2, and HDAC4 is identified and identified.
References
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Journal ArticleDOI

PLINK: A Tool Set for Whole-Genome Association and Population-Based Linkage Analyses

TL;DR: This work introduces PLINK, an open-source C/C++ WGAS tool set, and describes the five main domains of function: data management, summary statistics, population stratification, association analysis, and identity-by-descent estimation, which focuses on the estimation and use of identity- by-state and identity/descent information in the context of population-based whole-genome studies.
Journal ArticleDOI

The STRING database in 2011: functional interaction networks of proteins, globally integrated and scored

TL;DR: An update on the online database resource Search Tool for the Retrieval of Interacting Genes (STRING), which provides uniquely comprehensive coverage and ease of access to both experimental as well as predicted interaction information.
Journal ArticleDOI

Integrating common and rare genetic variation in diverse human populations

David Altshuler, +68 more
- 02 Sep 2010 - 
TL;DR: An expanded public resource of genome variants in global populations supports deeper interrogation of genomic variation and its role in human disease, and serves as a step towards a high-resolution map of the landscape of human genetic variation.
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