A small number of developmental signaling pathways are used repeatedly throughout development in many different contexts. How these pathways interact with each other and the specific cell context to generate a wide range of appropriate responses remains an important question. The application of genomic and proteomic approaches and imaging at high spatiotemporal resolution are providing answers to this question and revealing new levels of complexity. Here, we discuss pathways as complex networks and examples of how signaling outcomes can be influenced by the temporal nature of the signal, its spatial regulation, and the cell context.
Our ability to modify the Drosophila genome has recently been revolutionized by the development of the CRISPR system. The simplicity and high efficiency of this system allows its widespread use for many different applications, greatly increasing the range of genome modification experiments that can be performed. Here, we first discuss some general design principles for genome engineering experiments in Drosophila and then present detailed protocols for the production of CRISPR reagents and screening strategies to detect successful genome modification events in both tissue culture cells and animals.
Tyrosine phosphorylation plays a significant role in a wide range of cellular processes. The Drosophila genome encodes more than 20 receptor tyrosine kinases and extensive studies in the past 20 years have illustrated their diverse roles and complex signaling mechanisms. Although some receptor tyrosine kinases have highly specific functions, others strikingly are used in rather ubiquitous manners. Receptor tyrosine kinases regulate a broad expanse of processes, ranging from cell survival and proliferation to differentiation and patterning. Remarkably, different receptor tyrosine kinases share many of the same effectors and their hierarchical organization is retained in disparate biological contexts. In this comprehensive review, we summarize what is known regarding each receptor tyrosine kinase during Drosophila development. Astonishingly, very little is known for approximately half of all Drosophila receptor tyrosine kinases.
During development, signaling pathways specify cell fates by activating transcriptional programs in response to extracellular signals. Extensive studies in the past 30 years have revealed that surprisingly few pathways exist to regulate developmental programs and that dysregulation of these can lead to human diseases, including cancer. Although these pathways use distinct signaling components and signaling strategies, a number of common themes have emerged regarding their organization and regulation in time and space. Examples from Drosophila, such as Notch, Hedgehog, Wingless/WNT, BMP (bone morphogenetic proteins), EGF (epidermal growth factor), and FGF (fibroblast growth factor) signaling, illustrate their abilities to act either at a short range or over a long distance, and in some instances to generate morphogen gradients that pattern fields of cells in a concentration-dependent manner. They also show how feedback loops and transcriptional cascades are part of the logic of developmental regulation.
RNA interference (RNAi) provides a powerful reverse genetics approach to analyze gene functions both in tissue culture and in vivo. Because of its widespread applicability and effectiveness it has become an essential part of the tool box kits of model organisms such as Caenorhabditis elegans, Drosophila, and the mouse. In addition, the use of RNAi in animals in which genetic tools are either poorly developed or nonexistent enables a myriad of fundamental questions to be asked. Here, we review the methods and applications of in vivo RNAi to characterize gene functions in model organisms and discuss their impact to the study of developmental as well as evolutionary questions. Further, we discuss the applications of RNAi technologies to crop improvement, pest control and RNAi therapeutics, thus providing an appreciation of the potential for phenomenal applications of RNAi to agriculture and medicine.
The emergence of RNA interference (RNAi) on the heels of the successful completion of the Drosophila genome project was seen by many as the ace in functional genomics: Its application would quickly assign a function to all genes in this organism and help delineate the complex web of interactions or networks linking them at the systemic level. A few years wiser and a number of genome-wide Drosophila RNAi screens later, we reflect on the state of high-throughput RNAi screens in Drosophila and ask whether the initial promise was fulfilled. We review the impact that this approach has had in the field of Drosophila research and chart out strategies to extract maximal benefit from the application of RNAi to gene discovery and pursuit of systems biology.
The Rho family of small GTPases is essential for morphological changes during normal cell development and migration, as well as during disease states such as cancer. Our goal is to identify novel effectors of Rho proteins using a cell-based assay for Rho activity to perform genome-wide functional screens using double stranded RNA (dsRNAs) interference. We aim to discover genes could cause the cell phenotype changed dramatically. Biologists currently attempt to perform the genome-wide RNAi screening to identify various image phenotypes. RNAi genome-wide screening, however, could easily generate more than a million of images per study, manual analysis is thus prohibitive. Image analysis becomes a bottleneck in realizing high content imaging screens. We propose a two-step segmentation approach to solve this problem. First, we determine the center of a cell using the information in the DNA-channel by segmenting the DNA nuclei and the dissimilarity function is employed to attenuate the over-segmentation problem, then we estimate a rough boundary for each cell using a polygon. Second, we apply fuzzy c-means based multi-threshold segmentation and sharpening technology; for isolation of touching spots, marker-controlled watershed is employed to remove touching cells. Furthermore, Voronoi diagrams are employed to correct the segmentation errors caused by overlapping cells. Image features are extracted for each cell. K-nearest neighbor classifier (KNN) is employed to perform cell phenotype classification. Experimental results indicate that the proposed approach can be used to identify cell phenotypes of RNAi genome-wide screens.