Experimental validation and characterization of putative targets of Escargot and STAT, two master regulators of the intestinal stem cells in Drosophila melanogaster.

Many organs contain adult stem cells (ASCs) to replace cells due to damage, disease, or normal tissue turnover. ASCs can divide asymmetrically, giving rise to a new copy of themselves (self-renewal) and a sister that commits to a specific cell type (differentiation). Decades of research have led to the identification of pleiotropic genes whose loss or gain of function affect diverse aspects of normal ASC biology. Genome-wide screens of these so-called genetic "master regulator" (MR) genes, have pointed to hundreds of putative targets that could serve as their downstream effectors. Here, we experimentally validate and characterize the regulation of several putative targets of Escargot (Esg) and the Signal Transducer and Activator of Transcription (Stat92E, a.k.a. STAT), two known MRs in Drosophila intestinal stem cells (ISCs). Our results indicate that regardless of bioinformatic predictions, most experimentally validated targets show a profile of gene expression that is consistent with co-regulation by both Esg and STAT, fitting a rather limited set of co-regulatory modalities. A bioinformatic analysis of proximal regulatory sequences in specific subsets of co-regulated targets identified additional transcription factors that might cooperate with Esg and STAT in modulating their transcription. Lastly, in vivo manipulations of validated targets rarely phenocopied the effects of manipulating Esg and STAT, suggesting the existence of complex genetic interactions among downstream targets of these two MR genes during ISC homeostasis.

NetR and AttR, Two New Bioinformatic Tools to Integrate Diverse Datasets into Cytoscape Network and Attribute Files.

High-throughput technologies have allowed researchers to obtain genome-wide data from a wide array of experimental model systems. Unfortunately, however, new data generation tends to significantly outpace data re-utilization, and most high throughput datasets are only rarely used in subsequent studies or to generate new hypotheses to be tested experimentally. The reasons behind such data underutilization include a widespread lack of programming expertise among experimentalist biologists to carry out the necessary file reformatting that is often necessary to integrate published data from disparate sources. We have developed two programs (NetR and AttR), which allow experimental biologists with little to no programming background to integrate publicly available datasets into files that can be later visualized with Cytoscape to display hypothetical networks that result from combining individual datasets, as well as a series of published attributes related to the genes or proteins in the network. NetR also allows users to import protein and genetic interaction data from InterMine, which can further enrich a network model based on curated information. We expect that NetR/AttR will allow experimental biologists to mine a largely unexploited wealth of data in their fields and facilitate their integration into hypothetical models to be tested experimentally.