In vivo fly RNAi

2010
Sheng Zhang, Richard Binari, Rui Zhou, and Norbert Perrimon. 2010. “A genomewide RNA interference screen for modifiers of aggregates formation by mutant Huntingtin in Drosophila.” Genetics, 184, 4, Pp. 1165-79.Abstract

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.

2010_Genetics_Zhang.pdf Supplemental Files
Norbert Perrimon, Jian-Quan Ni, and Lizabeth Perkins. 2010. “In vivo RNAi: today and tomorrow.” Cold Spring Harb Perspect Biol, 2, 8, Pp. a003640.Abstract

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.

2010_CSHPerspect_Perrimon.pdf
2008
Jian-Quan Ni, Michele Markstein, Richard Binari, Barret Pfeiffer, Lu-Ping Liu, Christians Villalta, Matthew Booker, Lizabeth Perkins, and Norbert Perrimon. 2008. “Vector and parameters for targeted transgenic RNA interference in Drosophila melanogaster.” Nat Methods, 5, 1, Pp. 49-51.Abstract

The conditional expression of hairpin constructs in Drosophila melanogaster has emerged in recent years as a method of choice in functional genomic studies. To date, upstream activating site-driven RNA interference constructs have been inserted into the genome randomly using P-element-mediated transformation, which can result in false negatives due to variable expression. To avoid this problem, we have developed a transgenic RNA interference vector based on the phiC31 site-specific integration method.

2008_Nat Meth_Ni.pdf Supplement.pdf
2006
Meghana M Kulkarni, Matthew Booker, Serena J Silver, Adam Friedman, Pengyu Hong, Norbert Perrimon, and Bernard Mathey-Prevot. 2006. “Evidence of off-target effects associated with long dsRNAs in Drosophila melanogaster cell-based assays.” Nat Methods, 3, 10, Pp. 833-8.Abstract

To evaluate the specificity of long dsRNAs used in high-throughput RNA interference (RNAi) screens performed at the Drosophila RNAi Screening Center (DRSC), we performed a global analysis of their activity in 30 genome-wide screens completed at our facility. Notably, our analysis predicts that dsRNAs containing > or = 19-nucleotide perfect matches identified in silico to unintended targets may contribute to a significant false positive error rate arising from off-target effects. We confirmed experimentally that such sequences in dsRNAs lead to false positives and to efficient knockdown of a cross-hybridizing transcript, raising a cautionary note about interpreting results based on the use of a single dsRNA per gene. Although a full appreciation of all causes of false positive errors remains to be determined, we suggest simple guidelines to help ensure high-quality information from RNAi high-throughput screens.

2006_Nat Meth_Kulkarni.pdf Supplemental Files.zip
Ian Flockhart, Matthew Booker, Amy Kiger, Michael Boutros, Susan Armknecht, Nadire Ramadan, Kris Richardson, Andrew Xu, Norbert Perrimon, and Bernard Mathey-Prevot. 2006. “FlyRNAi: the Drosophila RNAi screening center database.” Nucleic Acids Res, 34, Database issue, Pp. D489-94.Abstract

RNA interference (RNAi) has become a powerful tool for genetic screening in Drosophila. At the Drosophila RNAi Screening Center (DRSC), we are using a library of over 21,000 double-stranded RNAs targeting known and predicted genes in Drosophila. This library is available for the use of visiting scientists wishing to perform full-genome RNAi screens. The data generated from these screens are collected in the DRSC database (http://flyRNAi.org/cgi-bin/RNAi_screens.pl) in a flexible format for the convenience of the scientist and for archiving data. The long-term goal of this database is to provide annotations for as many of the uncharacterized genes in Drosophila as possible. Data from published screens are available to the public through a highly configurable interface that allows detailed examination of the data and provides access to a number of other databases and bioinformatics tools.

2006_Nucl Acids Res_Flockhart.pdf

Pages