A zebrafish cloud computational resource for environmental health science research

Zebrafish (Danio Rerio) is a valuable model organism for studying a wide spectrum of complex human disorders as well as for understanding vertebrate development. Furthermore, zebrafish studies provide a unique advantage in linking environmental factors to human diseases, such as neurological disorders and reproductive dysfunction, through experiments that use large numbers of synchronously developing embryos drawn from an unparalleled array of normal, mutant, transgenic and knock-out fish lines. The ease of studying embryogenesis with large numbers of genomically identical zebrafish provides great opportunities to facilitate the investigation of disease susceptibility and the effects of developmental exposure to environmental toxins on the genomic and epigenomic levels. Investigators, however, require reproducible, efficient, low-cost yet powerful computational tools in order to analyze emergent large datasets from whole genome DNA, RNA or epigenetic sequencing. The Zebrafish Cloud Computational Resource (ZCCR) is a computing cluster and bioinformatics toolset for the zebrafish and human environmental health research community. The resource includes state-of-the-art next-generation sequencing (NGS) analysis tools integrated into Galaxy to create a standardized bioinformatics workflow system. Galaxy provides a graphical user interface for transparent, reproducible bioinformatics workflows, promoting collaborative refinement of the parameters for parsing and analyzing NGS experiments. We will implement the NGS pipeline on both the university (UW-Milwaukee) computing cluster and on Amazon Web Services. Both options allow users to launch analysis within minutes with automatically scaled computational resources fitting the load of Galaxy's NGS analysis job queue. ZCCR will greatly promote global collaboration among environmental health science researchers to test the general hypothesis that toxicity due to environmental stressors emerges through a limited number of common pathways while taking the unique advantage of zebrafish and cloud-based NGS pipelines.