Mosaic epigenetic dysregulation of ectodermal cells in autism spectrum disorder.

DNA mutational events are increasingly being identified in autism spectrum disorder (ASD), but the potential additional role of dysregulation of the epigenome in the pathogenesis of the condition remains unclear. The epigenome is of interest as a possible mediator of environmental effects during development, encoding a cellular memory reflected by altered function of progeny cells. Advanced maternal age (AMA) is associated with an increased risk of having a child with ASD for reasons that are not understood. To explore whether AMA involves covert aneuploidy or epigenetic dysregulation leading to ASD in the offspring, we tested a homogeneous ectodermal cell type from 47 individuals with ASD compared with 48 typically developing (TD) controls born to mothers of ≥35 years, using a quantitative genome-wide DNA methylation assay. We show that DNA methylation patterns are dysregulated in ectodermal cells in these individuals, having accounted for confounding effects due to subject age, sex and ancestral haplotype. We did not find mosaic aneuploidy or copy number variability to occur at differentially-methylated regions in these subjects. Of note, the loci with distinctive DNA methylation were found at genes expressed in the brain and encoding protein products significantly enriched for interactions with those produced by known ASD-causing genes, representing a perturbation by epigenomic dysregulation of the same networks compromised by DNA mutational mechanisms. The results indicate the presence of a mosaic subpopulation of epigenetically-dysregulated, ectodermally-derived cells in subjects with ASD. The epigenetic dysregulation observed in these ASD subjects born to older mothers may be associated with aging parental gametes, environmental influences during embryogenesis or could be the consequence of mutations of the chromatin regulatory genes increasingly implicated in ASD. The results indicate that epigenetic dysregulatory mechanisms may complement and interact with DNA mutations in the pathogenesis of the disorder.

The Wasp System: an open source environment for managing and analyzing genomic data.

The challenges associated with the management, analysis and interpretation of assays based on massively-parallel sequencing (MPS) are both individually complex and numerous. We describe what we believe to be the appropriate solution, one that represents a departure from traditional computational biology approaches. The Wasp System is an open source, distributed package written in Spring/J2EE that creates a foundation for development of an end-to-end solution for MPS-based experiments or clinical tests. Recognizing that one group will be unable to solve these challenges in isolation, we describe a nurtured open source development model that will allow the software to be collectively used, shared and developed. The ultimate goal is to emulate resources such as the Virtual Observatory of the astrophysics community, enabling computationally-inexpert scientists and clinicians to explore and interpret their MPS data. Here we describe the current implementation and development of the Wasp System and the roadmap for its community development.

The Einstein Genome Gateway using WASP - a high throughput multi-layered life sciences portal for XSEDE.

Massively-parallel sequencing (MPS) technologies and their diverse applications in genomics and epigenomics research have yielded enormous new insights into the physiology and pathophysiology of the human genome. The biggest hurdle remains the magnitude and diversity of the datasets generated, compromising our ability to manage, organize, process and ultimately analyse data. The Wiki-based Automated Sequence Processor (WASP), developed at the Albert Einstein College of Medicine (hereafter Einstein), uniquely manages to tightly couple the sequencing platform, the sequencing assay, sample metadata and the automated workflows deployed on a heterogeneous high performance computing cluster infrastructure that yield sequenced, quality-controlled and 'mapped' sequence data, all within the one operating environment accessible by a web-based GUI interface. WASP at Einstein processes 4-6 TB of data per week and since its production cycle commenced it has processed ~ 1 PB of data overall and has revolutionized user interactivity with these new genomic technologies, who remain blissfully unaware of the data storage, management and most importantly processing services they request. The abstraction of such computational complexity for the user in effect makes WASP an ideal middleware solution, and an appropriate basis for the development of a grid-enabled resource - the Einstein Genome Gateway - as part of the Extreme Science and Engineering Discovery Environment (XSEDE) program. In this paper we discuss the existing WASP system, its proposed middleware role, and its planned interaction with XSEDE to form the Einstein Genome Gateway.