Polyglutamine (polyQ) diseases are a group of late-onset, progressive neurodegenerative disorders caused by CAG trinucleotide repeat expansion in the coding region of disease genes. The cell nucleus is an important site of pathology in polyQ diseases, and transcriptional dysregulation is one of the pathologic hallmarks observed. In this study, we showed that exportin-1 (Xpo1) regulates the nucleocytoplasmic distribution of expanded polyQ protein. We found that expanded polyQ protein, but not its unexpanded form, possesses nuclear export activity and interacts with Xpo1. Genetic manipulation of Xpo1 expression levels in transgenic Drosophila models of polyQ disease confirmed the specific nuclear export role of Xpo1 on expanded polyQ protein. Upon Xpo1 knockdown, the expanded polyQ protein was retained in the nucleus. The nuclear disease protein enhanced polyQ toxicity by binding to heat shock protein (hsp) gene promoter and abolished hsp gene induction. Further, we uncovered a developmental decline of Xpo1 protein levels in vivo that contributes to the accumulation of expanded polyQ protein in the nucleus of symptomatic polyQ transgenic mice. Taken together, we first showed that Xpo1 is a nuclear export receptor for expanded polyQ domain, and our findings establish a direct link between protein nuclear export and the progressive nature of polyQ neurodegeneration.

Existing transgenic RNAi resources in Drosophila melanogaster based on long double-stranded hairpin RNAs are powerful tools for functional studies, but they are ineffective in gene knockdown during oogenesis, an important model system for the study of many biological questions. We show that shRNAs, modeled on an endogenous microRNA, are extremely effective at silencing gene expression during oogenesis. We also describe our progress toward building a genome-wide shRNA resource.

The adult Drosophila midgut is thought to arise from an endodermal rudiment specified during embryogenesis. Previous studies have reported the presence of individual cells termed adult midgut precursors (AMPs) as well as "midgut islands" or "islets" in embryonic and larval midgut tissue. Yet the precise relationship between progenitor cell populations and the cells of the adult midgut has not been characterized. Using a combination of molecular markers and directed cell lineage tracing, we provide evidence that the adult midgut arises from a molecularly distinct population of single cells present by the embryonic/larval transition. AMPs reside in a distinct basal position in the larval midgut where they remain through all subsequent larval and pupal stages and into adulthood. At least five phases of AMP activity are associated with the stepwise process of midgut formation. Our data shows that during larval stages AMPs give rise to the presumptive adult epithelium; during pupal stages AMPs contribute to the final size, cell number and form. Finally, a genetic screen has led to the identification of the Ecdysone receptor as a regulator of AMP expansion.

BACKGROUND: Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. RESULTS: We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist). CONCLUSIONS: DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

Characterizing the extent and logic of signaling networks is essential to understanding specificity in such physiological and pathophysiological contexts as cell fate decisions and mechanisms of oncogenesis and resistance to chemotherapy. Cell-based RNA interference (RNAi) screens enable the inference of large numbers of genes that regulate signaling pathways, but these screens cannot provide network structure directly. We describe an integrated network around the canonical receptor tyrosine kinase (RTK)-Ras-extracellular signal-regulated kinase (ERK) signaling pathway, generated by combining parallel genome-wide RNAi screens with protein-protein interaction (PPI) mapping by tandem affinity purification-mass spectrometry. We found that only a small fraction of the total number of PPI or RNAi screen hits was isolated under all conditions tested and that most of these represented the known canonical pathway components, suggesting that much of the core canonical ERK pathway is known. Because most of the newly identified regulators are likely cell type- and RTK-specific, our analysis provides a resource for understanding how output through this clinically relevant pathway is regulated in different contexts. We report in vivo roles for several of the previously unknown regulators, including CG10289 and PpV, the Drosophila orthologs of two components of the serine/threonine-protein phosphatase 6 complex; the Drosophila ortholog of TepIV, a glycophosphatidylinositol-linked protein mutated in human cancers; CG6453, a noncatalytic subunit of glucosidase II; and Rtf1, a histone methyltransferase.

Systems biology aims to describe the complex interplays between cellular building blocks which, in their concurrence, give rise to the emergent properties observed in cellular behaviors and responses. This approach tries to determine the molecular players and the architectural principles of their interactions within the genetic networks that control certain biological processes. Large-scale loss-of-function screens, applicable in various different model systems, have begun to systematically interrogate entire genomes to identify the genes that contribute to a certain cellular response. In particular, RNA interference (RNAi)-based high-throughput screens have been instrumental in determining the composition of regulatory systems and paired with integrative data analyses have begun to delineate the genetic networks that control cell biological and developmental processes. Through the creation of tools for both, in vitro and in vivo genome-wide RNAi screens, Drosophila melanogaster has emerged as one of the key model organisms in systems biology research and over the last years has massively contributed to and hence shaped this discipline. WIREs Syst Biol Med 2011 3 471-478 DOI: 10.1002/wsbm.127

To gain insight into how genomic information is translated into cellular and developmental programs, the Drosophila model organism Encyclopedia of DNA Elements (modENCODE) project is comprehensively mapping transcripts, histone modifications, chromosomal proteins, transcription factors, replication proteins and intermediates, and nucleosome properties across a developmental time course and in multiple cell lines. We have generated more than 700 data sets and discovered protein-coding, noncoding, RNA regulatory, replication, and chromatin elements, more than tripling the annotated portion of the Drosophila genome. Correlated activity patterns of these elements reveal a functional regulatory network, which predicts putative new functions for genes, reveals stage- and tissue-specific regulators, and enables gene-expression prediction. Our results provide a foundation for directed experimental and computational studies in Drosophila and related species and also a model for systematic data integration toward comprehensive genomic and functional annotation.

Intestinal epithelia are maintained by intestinal stem cells (ISCs) that divide to replace dying absorptive and secretory cells that make up this tissue. Lineage labeling studies, both in vertebrates and Drosophila, have revealed the relationships between ISCs and their progeny. In addition, a number of signaling pathways involved in ISC proliferation and differentiation have been identified. Further studies will clarify the signals originating from the ISC niche and determine the processes that control the number and uniform distribution of niches throughout the epithelium.

In flies, ecdysone integrates growth with developmental transitions by antagonizing insulin signaling, which links growth with nutritional status. Work in Developmental Cell (Delanoue et. al, 2010) finds that ecdysone represses the transcription factor Myc in the larval fat body to inhibit systemic growth, revealing a mechanism for such coordination.

MicroRNAs (miRNAs) are a class of short noncoding RNAs that regulate protein-coding genes posttranscriptionally. In animals, most known miRNA targeting occurs within the 3'UTR of mRNAs, but the extent of biologically relevant targeting in the ORF or 5'UTR of mRNAs remains unknown. Here, we develop an algorithm (MinoTar-miRNA ORF Targets) to identify conserved regulatory motifs within protein-coding regions and use it to estimate the number of preferentially conserved miRNA-target sites in ORFs. We show that, in Drosophila, preferentially conserved miRNA targeting in ORFs is as widespread as it is in 3'UTRs and that, while far less abundant, conserved targets in Drosophila 5'UTRs number in the hundreds. Using our algorithm, we predicted a set of high-confidence ORF targets and selected seven miRNA-target pairs from among these for experimental validation. We observed down-regulation by the miRNA in five out of seven cases, indicating our approach can recover functional sites with high confidence. Additionally, we observed additive targeting by multiple sites within a single ORF. Altogether, our results demonstrate that the scale of biologically important miRNA targeting in ORFs is extensive and that computational tools such as ours can aid in the identification of such targets. Further evidence suggests that our results extend to mammals, but that the extent of ORF and 5'UTR targeting relative to 3'UTR targeting may be greater in Drosophila.

Adult structures in holometabolous insects such as Drosophila are generated by groups of imaginal cells dedicated to the formation of different organs. Imaginal cells are specified in the embryo and remain quiescent until the larval stages, when they proliferate and differentiate to form organs. The Drosophila tracheal system is extensively remodeled during metamorphosis by a small number of airway progenitors. Among these, the spiracular branch tracheoblasts are responsible for the generation of the pupal and adult abdominal airways. To understand the coordination of proliferation and differentiation during organogenesis of tubular organs, we analyzed the remodeling of Drosophila airways during metamorphosis. We show that the embryonic spiracular branch tracheoblasts are multipotent cells that express the homeobox transcription factor Cut, which is necessary for their survival and normal development. They give rise to three distinct cell populations at the end of larval development, which generate the adult tracheal tubes, the spiracle and the epidermis surrounding the spiracle. Our study establishes the series of events that lead to the formation of an adult tubular structure in Drosophila.

Predicting gene functions by integrating large-scale biological data remains a challenge for systems biology. Here we present a resource for Drosophila melanogaster gene function predictions. We trained function-specific classifiers to optimize the influence of different biological datasets for each functional category. Our model predicted GO terms and KEGG pathway memberships for Drosophila melanogaster genes with high accuracy, as affirmed by cross-validation, supporting literature evidence, and large-scale RNAi screens. The resulting resource of prioritized associations between Drosophila genes and their potential functions offers a guide for experimental investigations.

Protein aggregates are a common pathological feature of most neurodegenerative diseases (NDs). Understanding their formation and regulation will help clarify their controversial roles in disease pathogenesis. To date, there have been few systematic studies of aggregates formation in Drosophila, a model organism that has been applied extensively in modeling NDs and screening for toxicity modifiers. We generated transgenic fly lines that express enhanced-GFP-tagged mutant Huntingtin (Htt) fragments with different lengths of polyglutamine (polyQ) tract and showed that these Htt mutants develop protein aggregates in a polyQ-length- and age-dependent manner in Drosophila. To identify central regulators of protein aggregation, we further generated stable Drosophila cell lines expressing these Htt mutants and also established a cell-based quantitative assay that allows automated measurement of aggregates within cells. We then performed a genomewide RNA interference screen for regulators of mutant Htt aggregation and isolated 126 genes involved in diverse cellular processes. Interestingly, although our screen focused only on mutant Htt aggregation, several of the identified candidates were known previously as toxicity modifiers of NDs. Moreover, modulating the in vivo activity of hsp110 (CG6603) or tra1, two hits from the screen, affects neurodegeneration in a dose-dependent manner in a Drosophila model of Huntington's disease. Thus, other aggregates regulators isolated in our screen may identify additional genes involved in the protein-folding pathway and neurotoxicity.

Identification of the signaling pathways that control the proliferation of stem cells (SCs), and whether they act in a cell or non-cell autonomous manner, is key to our understanding of tissue homeostasis and cancer. In the adult Drosophila midgut, the Jun N-Terminal Kinase (JNK) pathway is activated in damaged enterocyte cells (ECs) following injury. This leads to the production of Upd cytokines from ECs, which in turn activate the Janus kinase (JAK)/Signal transducer and activator of transcription (STAT) pathway in Intestinal SCs (ISCs), stimulating their proliferation. In addition, the Hippo pathway has been recently implicated in the regulation of Upd production from the ECs. Here, we show that the Hippo pathway target, Yorkie (Yki), also plays a crucial and cell-autonomous role in ISCs. Activation of Yki in ISCs is sufficient to increase ISC proliferation, a process involving Yki target genes that promote division, survival and the Upd cytokines. We further show that prior to injury, Yki activity is constitutively repressed by the upstream Hippo pathway members Fat and Dachsous (Ds). These findings demonstrate a cell-autonomous role for the Hippo pathway in SCs, and have implications for understanding the role of this pathway in tumorigenesis and cancer stem cells.

Biological networks are highly complex systems, consisting largely of enzymes that act as molecular switches to activate/inhibit downstream targets via post-translational modification. Computational techniques have been developed to perform signaling network inference using some high-throughput data sources, such as those generated from transcriptional and proteomic studies, but comparable methods have not been developed to use high-content morphological data, which are emerging principally from large-scale RNAi screens, to these ends. Here, we describe a systematic computational framework based on a classification model for identifying genetic interactions using high-dimensional single-cell morphological data from genetic screens, apply it to RhoGAP/GTPase regulation in Drosophila, and evaluate its efficacy. Augmented by knowledge of the basic structure of RhoGAP/GTPase signaling, namely, that GAPs act directly upstream of GTPases, we apply our framework for identifying genetic interactions to predict signaling relationships between these proteins. We find that our method makes mediocre predictions using only RhoGAP single-knockdown morphological data, yet achieves vastly improved accuracy by including original data from a double-knockdown RhoGAP genetic screen, which likely reflects the redundant network structure of RhoGAP/GTPase signaling. We consider other possible methods for inference and show that our primary model outperforms the alternatives. This work demonstrates the fundamental fact that high-throughput morphological data can be used in a systematic, successful fashion to identify genetic interactions and, using additional elementary knowledge of network structure, to infer signaling relations.

Originally identified as a response to starvation in yeast, autophagy is now understood to fulfill a variety of roles in higher eukaryotes, from the maintenance of cellular homeostasis to the cellular response to stress, starvation, and infection. Although genetics and biochemical studies in yeast have identified many components involved in autophagy, the findings that some of the essential components of the yeast pathway are missing in higher organisms underscore the need to study autophagy in more complex systems. This review focuses on the use of the fruitfly, Drosophila melanogaster as a model system for analysis of autophagy. Drosophila is an organism well-suited for genetic analysis and represents an intermediate between yeast and mammals with respect to conservation of the autophagy machinery. Furthermore, the complex biology and physiology of Drosophila presents an opportunity to model human diseases in a tissue specific and analogous context.

Akt represents a nodal point between the Insulin receptor and TOR signaling, and its activation by phosphorylation controls cell proliferation, cell size, and metabolism. The activity of Akt must be carefully balanced, as increased Akt signaling is frequently associated with cancer and as insufficient Akt signaling is linked to metabolic disease and diabetes mellitus. Using a genome-wide RNAi screen in Drosophila cells in culture, and in vivo analyses in the third instar wing imaginal disc, we studied the regulatory circuitries that define dAkt activation. We provide evidence that negative feedback regulation of dAkt occurs during normal Drosophila development in vivo. Whereas in cell culture dAkt is regulated by S6 Kinase (S6K)-dependent negative feedback, this feedback inhibition only plays a minor role in vivo. In contrast, dAkt activation under wild-type conditions is defined by feedback inhibition that depends on TOR Complex 1 (TORC1), but is S6K-independent. This feedback inhibition is switched from TORC1 to S6K only in the context of enhanced TORC1 activity, as triggered by mutations in tsc2. These results illustrate how the Akt-TOR pathway dynamically adapts the routing of negative feedback in response to the activity load of its signaling circuit in vivo.

The progressive loss of muscle strength during aging is a common degenerative event of unclear pathogenesis. Although muscle functional decline precedes age-related changes in other tissues, its contribution to systemic aging is unknown. Here, we show that muscle aging is characterized in Drosophila by the progressive accumulation of protein aggregates that associate with impaired muscle function. The transcription factor FOXO and its target 4E-BP remove damaged proteins at least in part via the autophagy/lysosome system, whereas foxo mutants have dysfunctional proteostasis. Both FOXO and 4E-BP delay muscle functional decay and extend life span. Moreover, FOXO/4E-BP signaling in muscles decreases feeding behavior and the release of insulin from producing cells, which in turn delays the age-related accumulation of protein aggregates in other tissues. These findings reveal an organism-wide regulation of proteostasis in response to muscle aging and a key role of FOXO/4E-BP signaling in the coordination of organismal and tissue aging.

RNA interference (RNAi) is an effective tool for genome-scale, high-throughput analysis of gene function. In the past five years, a number of genome-scale RNAi high-throughput screens (HTSs) have been done in both Drosophila and mammalian cultured cells to study diverse biological processes, including signal transduction, cancer biology, and host cell responses to infection. Results from these screens have led to the identification of new components of these processes and, importantly, have also provided insights into the complexity of biological systems, forcing new and innovative approaches to understanding functional networks in cells. Here, we review the main findings that have emerged from RNAi HTS and discuss technical issues that remain to be improved, in particular the verification of RNAi results and validation of their biological relevance. Furthermore, we discuss the importance of multiplexed and integrated experimental data analysis pipelines to RNAi HTS.

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.