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.