Identification of Rare Coding Variation in Autism Spectrum Disorders by Deep Resequencing

Background: Multiple rare variants play an important role in the etiology of autism spectrum disorders (ASD).  The study of rare variants has proven to be more important for identifying pathological mechanisms and for the conceptualization of new therapeutic targets.

Objectives: To identify rare variants in ASD by direct resequencing large numbers of ASD candidate genes.

Methods: As part of our long term strategy, methods for large scale variant detection are being developed, including methods of sample pooling, target enrichment, and high-throughput sequencing (HTS).

Results: In our pilot study we assessed 13 genes in 288-576 unrelated ASD cases using rapid, optimized Sanger sequencing. Our strategy was to screen for de novo nonsense (or missense) variants.  Candidate genes were selected based on a potential role in ASD etiology, including synaptic cell adhesion molecules, genes in the 2q37 region, and other genes. While we identified nonsense changes in two genes, none were de novo. More recently, we have expanded our studies to larger numbers of genes using a pooling strategy and HTS on the Illumina platform. Careful pooling (10 fold to 50 fold) was carried out using three rounds of quantification. We are comparing Agilent, Nimblegen, and Raindance methods for target enrichment, followed by HTS. We are also comparing three platforms for rare variant calling. Raindance has some theoretical limits but proves useful in the case of a lower number of amplicons. The comparative studies are ongoing.

Conclusions: Deep resequencing studies represent the next phase in gene discovery in ASDs. By the careful comparison of available methods, we are identifying cost effective and efficient methods for rapid rare variants discovery in ASD.