Review article

2022
Jonathan Zirin, Justin Bosch, Raghuvir Viswanatha, Stephanie E Mohr, and Norbert Perrimon. 2022. “State-of-the-art CRISPR for in vivo and cell-based studies in Drosophila.” Trends Genet, 38, 5, Pp. 437-453.Abstract
For more than 100 years, the fruit fly, Drosophila melanogaster, has served as a powerful model organism for biological and biomedical research due to its many genetic and physiological similarities to humans and the availability of sophisticated technologies used to manipulate its genome and genes. The Drosophila research community quickly adopted CRISPR technologies and, in the 8 years since the first clustered regularly interspaced short palindromic repeats (CRISPR) publications in flies, has explored and innovated methods for mutagenesis, precise genome engineering, and beyond. Moreover, the short lifespan and ease of genetics have made Drosophila an ideal testing ground for in vivo applications and refinements of the rapidly evolving set of CRISPR-associated (CRISPR-Cas) tools. Here, we review innovations in delivery of CRISPR reagents, increased efficiency of cutting and homology-directed repair (HDR), and alternatives to standard Cas9-based approaches. While the focus is primarily on in vivo systems, we also describe the role of Drosophila cultured cells as both an indispensable first step in the process of assessing new CRISPR technologies and a platform for genome-wide CRISPR pooled screens.
2021
Stephanie E Mohr, Sudhir Gopal Tattikota, Jun Xu, Jonathan Zirin, Yanhui Hu, and Norbert Perrimon. 2021. “Methods and tools for spatial mapping of single-cell RNAseq clusters in Drosophila.” Genetics, 217, 4.Abstract
Single-cell RNA sequencing (scRNAseq) experiments provide a powerful means to identify clusters of cells that share common gene expression signatures. A major challenge in scRNAseq studies is to map the clusters to specific anatomical regions along the body and within tissues. Existing data, such as information obtained from large-scale in situ RNA hybridization studies, cell type specific transcriptomics, gene expression reporters, antibody stainings, and fluorescent tagged proteins, can help to map clusters to anatomy. However, in many cases, additional validation is needed to precisely map the spatial location of cells in clusters. Several approaches are available for spatial resolution in Drosophila, including mining of existing datasets, and use of existing or new tools for direct or indirect detection of RNA, or direct detection of proteins. Here, we review available resources and emerging technologies that will facilitate spatial mapping of scRNAseq clusters at high resolution in Drosophila. Importantly, we discuss the need, available approaches, and reagents for multiplexing gene expression detection in situ, as in most cases scRNAseq clusters are defined by the unique coexpression of sets of genes.
2019
Stephanie E. Mohr and Norbert Perrimon. 9/27/2019. “Drosophila melanogaster: a simple system for understanding complexity.” Dis Model Mech, 12, 10. Publisher's VersionAbstract

Understanding human gene function is fundamental to understanding and treating diseases. Research using the model organism Drosophila melanogaster benefits from a wealth of molecular genetic resources and information useful for efficient in vivo experimentation. Moreover, Drosophila offers a balance as a relatively simple organism that nonetheless exhibits complex multicellular activities. Recent examples demonstrate the power and continued promise of Drosophila research to further our understanding of conserved gene functions.

2019_DMM_Mohr.pdf
Andrey A Parkhitko, Patrick Jouandin, Stephanie E Mohr, and Norbert Perrimon. 2019. “Methionine metabolism and methyltransferases in the regulation of aging and lifespan extension across species.” Aging Cell, Pp. e13034.Abstract
Methionine restriction (MetR) extends lifespan across different species and exerts beneficial effects on metabolic health and inflammatory responses. In contrast, certain cancer cells exhibit methionine auxotrophy that can be exploited for therapeutic treatment, as decreasing dietary methionine selectively suppresses tumor growth. Thus, MetR represents an intervention that can extend lifespan with a complementary effect of delaying tumor growth. Beyond its function in protein synthesis, methionine feeds into complex metabolic pathways including the methionine cycle, the transsulfuration pathway, and polyamine biosynthesis. Manipulation of each of these branches extends lifespan; however, the interplay between MetR and these branches during regulation of lifespan is not well understood. In addition, a potential mechanism linking the activity of methionine metabolism and lifespan is regulation of production of the methyl donor S-adenosylmethionine, which, after transferring its methyl group, is converted to S-adenosylhomocysteine. Methylation regulates a wide range of processes, including those thought to be responsible for lifespan extension by MetR. Although the exact mechanisms of lifespan extension by MetR or methionine metabolism reprogramming are unknown, it may act via reducing the rate of translation, modifying gene expression, inducing a hormetic response, modulating autophagy, or inducing mitochondrial function, antioxidant defense, or other metabolic processes. Here, we review the mechanisms of lifespan extension by MetR and different branches of methionine metabolism in different species and the potential for exploiting the regulation of methyltransferases to delay aging.
2017
Ben Ewen-Campen, Stephanie E Mohr, Yanhui Hu, and Norbert Perrimon. 10/9/2017. “Accessing the Phenotype Gap: Enabling Systematic Investigation of Paralog Functional Complexity with CRISPR.” Dev Cell, 43, 1, Pp. 6-9.Abstract
Single-gene knockout experiments can fail to reveal function in the context of redundancy, which is frequently observed among duplicated genes (paralogs) with overlapping functions. We discuss the complexity associated with studying paralogs and outline how recent advances in CRISPR will help address the "phenotype gap" and impact biomedical research.
2016
Benjamin E Housden, Matthias Muhar, Matthew Gemberling, Charles A Gersbach, Didier YR Stainier, Geraldine Seydoux, Stephanie E Mohr, Johannes Zuber, and Norbert Perrimon. 10/31/2016. “Loss-of-function genetic tools for animal models: cross-species and cross-platform differences.” Nat Rev Genet. Publisher's VersionAbstract

Our understanding of the genetic mechanisms that underlie biological processes has relied extensively on loss-of-function (LOF) analyses. LOF methods target DNA, RNA or protein to reduce or to ablate gene function. By analysing the phenotypes that are caused by these perturbations the wild-type function of genes can be elucidated. Although all LOF methods reduce gene activity, the choice of approach (for example, mutagenesis, CRISPR-based gene editing, RNA interference, morpholinos or pharmacological inhibition) can have a major effect on phenotypic outcomes. Interpretation of the LOF phenotype must take into account the biological process that is targeted by each method. The practicality and efficiency of LOF methods also vary considerably between model systems. We describe parameters for choosing the optimal combination of method and system, and for interpreting phenotypes within the constraints of each method.

2016_Nat Rev Gene_Housden.pdf
Stephanie E Mohr, Yanhui Hu, Benjamin Ewen-Campen, Benjamin E Housden, Raghuvir Viswanatha, and Norbert Perrimon. 2016. “CRISPR guide RNA design for research applications.” FEBS J.Abstract

The rapid rise of CRISPR as a technology for genome engineering and related research applications has created a need for algorithms and associated online tools that facilitate design of on-target and effective guide RNAs (gRNAs). Here, we review the state-of-the-art in CRISPR gRNA design for research applications of the CRISPR-Cas9 system, including knockout, activation and inhibition. Notably, achieving good gRNA design is not solely dependent on innovations in CRISPR technology. Good design and design tools also rely on availability of high-quality genome sequence and gene annotations, as well as on availability of accumulated data regarding off-targets and effectiveness metrics. This article is protected by copyright. All rights reserved.

2016_FEBS_Mohr.pdf
2014
Stephanie E Mohr, Yanhui Hu, Kevin Kim, Benjamin E Housden, and Norbert Perrimon. 2014. “Resources for functional genomics studies in Drosophila melanogaster.” Genetics, 197, 1, Pp. 1-18.Abstract

Drosophila melanogaster has become a system of choice for functional genomic studies. Many resources, including online databases and software tools, are now available to support design or identification of relevant fly stocks and reagents or analysis and mining of existing functional genomic, transcriptomic, proteomic, etc. datasets. These include large community collections of fly stocks and plasmid clones, "meta" information sites like FlyBase and FlyMine, and an increasing number of more specialized reagents, databases, and online tools. Here, we introduce key resources useful to plan large-scale functional genomics studies in Drosophila and to analyze, integrate, and mine the results of those studies in ways that facilitate identification of highest-confidence results and generation of new hypotheses. We also discuss ways in which existing resources can be used and might be improved and suggest a few areas of future development that would further support large- and small-scale studies in Drosophila and facilitate use of Drosophila information by the research community more generally.

2014_Genetics_Mohr.pdf
Stephanie E Mohr, Jennifer A Smith, Caroline E Shamu, Ralph A Neumüller, and Norbert Perrimon. 2014. “RNAi screening comes of age: improved techniques and complementary approaches.” Nat Rev Mol Cell Biol, 15, 9, Pp. 591-600.Abstract

Gene silencing through sequence-specific targeting of mRNAs by RNAi has enabled genome-wide functional screens in cultured cells and in vivo in model organisms. These screens have resulted in the identification of new cellular pathways and potential drug targets. Considerable progress has been made to improve the quality of RNAi screen data through the development of new experimental and bioinformatics approaches. The recent availability of genome-editing strategies, such as the CRISPR (clustered regularly interspaced short palindromic repeats)-Cas9 system, when combined with RNAi, could lead to further improvements in screen data quality and follow-up experiments, thus promoting our understanding of gene function and gene regulatory networks.

2014_Nat Rev Mol Cell Bio_Mohr.pdf
Stephanie E Mohr. 2014. “RNAi screening in Drosophila cells and in vivo.” Methods, 68, 1, Pp. 82-8.Abstract

Here, I discuss how RNAi screening can be used effectively to uncover gene function. Specifically, I discuss the types of high-throughput assays that can be done in Drosophila cells and in vivo, RNAi reagent design and available reagent collections, automated screen pipelines, analysis of screen results, and approaches to RNAi results verification.

2014_Methods_Mohr.pdf
2012
Stephanie E Mohr and Norbert Perrimon. 2012. “RNAi screening: new approaches, understandings, and organisms.” Wiley Interdiscip Rev RNA, 3, 2, Pp. 145-58.Abstract

RNA interference (RNAi) leads to sequence-specific knockdown of gene function. The approach can be used in large-scale screens to interrogate function in various model organisms and an increasing number of other species. Genome-scale RNAi screens are routinely performed in cultured or primary cells or in vivo in organisms such as C. elegans. High-throughput RNAi screening is benefitting from the development of sophisticated new instrumentation and software tools for collecting and analyzing data, including high-content image data. The results of large-scale RNAi screens have already proved useful, leading to new understandings of gene function relevant to topics such as infection, cancer, obesity, and aging. Nevertheless, important caveats apply and should be taken into consideration when developing or interpreting RNAi screens. Some level of false discovery is inherent to high-throughput approaches and specific to RNAi screens, false discovery due to off-target effects (OTEs) of RNAi reagents remains a problem. The need to improve our ability to use RNAi to elucidate gene function at large scale and in additional systems continues to be addressed through improved RNAi library design, development of innovative computational and analysis tools and other approaches.

2012_Wiley Interdis Rev_Mohr.pdf
2011
Matthew Booker, Anastasia A Samsonova, Young Kwon, Ian Flockhart, Stephanie E Mohr, and Norbert Perrimon. 2011. “False negative rates in Drosophila cell-based RNAi screens: a case study.” BMC Genomics, 12, Pp. 50.Abstract

BACKGROUND: High-throughput screening using RNAi is a powerful gene discovery method but is often complicated by false positive and false negative results. Whereas false positive results associated with RNAi reagents has been a matter of extensive study, the issue of false negatives has received less attention. RESULTS: We performed a meta-analysis of several genome-wide, cell-based Drosophila RNAi screens, together with a more focused RNAi screen, and conclude that the rate of false negative results is at least 8%. Further, we demonstrate how knowledge of the cell transcriptome can be used to resolve ambiguous results and how the number of false negative results can be reduced by using multiple, independently-tested RNAi reagents per gene. CONCLUSIONS: RNAi reagents that target the same gene do not always yield consistent results due to false positives and weak or ineffective reagents. False positive results can be partially minimized by filtering with transcriptome data. RNAi libraries with multiple reagents per gene also reduce false positive and false negative outcomes when inconsistent results are disambiguated carefully.

2011_BMCGenomics_Booker.pdf Supplement 1.xls Supplement 2.xls
Ralph A Neumüller and Norbert Perrimon. 2011. “Where gene discovery turns into systems biology: genome-scale RNAi screens in Drosophila.” Wiley Interdiscip Rev Syst Biol Med, 3, 4, Pp. 471-8.Abstract

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

2011_Wiley_Neumuller.pdf
2010
Stephanie Mohr, Chris Bakal, and Norbert Perrimon. 2010. “Genomic screening with RNAi: results and challenges.” Annu Rev Biochem, 79, Pp. 37-64.Abstract

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.

2010_Annu Rev Biochem_Mohr.pdf
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
2007
Norbert Perrimon and Bernard Mathey-Prevot. 2007. “Applications of high-throughput RNA interference screens to problems in cell and developmental biology.” Genetics, 175, 1, Pp. 7-16.Abstract

RNA interference (RNAi) in tissue culture cells has emerged as an excellent methodology for identifying gene functions systematically and in an unbiased manner. Here, we describe how RNAi high-throughput screening (HTS) in Drosophila cells are currently being performed and emphasize the strengths and weaknesses of the approach. Further, to demonstrate the versatility of the technology, we provide examples of the various applications of the method to problems in signal transduction and cell and developmental biology. Finally, we discuss emerging technological advances that will extend RNAi-based screening methods.

2007_Genetics_Perrimon.pdf
2006
Christophe J Echeverri and Norbert Perrimon. 2006. “High-throughput RNAi screening in cultured cells: a user's guide.” Nat Rev Genet, 7, 5, Pp. 373-84.Abstract

RNA interference has re-energized the field of functional genomics by enabling genome-scale loss-of-function screens in cultured cells. Looking back on the lessons that have been learned from the first wave of technology developments and applications in this exciting field, we provide both a user's guide for newcomers to the field and a detailed examination of some more complex issues, particularly concerning optimization and quality control, for more advanced users. From a discussion of cell lines, screening paradigms, reagent types and read-out methodologies, we explore in particular the complexities of designing optimal controls and normalization strategies for these challenging but extremely powerful studies.

2006_Nat Rev Gene_Echeverri.pdf
2005
Susan Armknecht, Michael Boutros, Amy Kiger, Kent Nybakken, Bernard Mathey-Prevot, and Norbert Perrimon. 2005. “High-throughput RNA interference screens in Drosophila tissue culture cells.” Methods Enzymol, 392, Pp. 55-73.Abstract

This chapter describes the method used to conduct high-throughput screening (HTs) by RNA interference in Drosophila tissue culture cells. It covers four main topics: (1) a brief description of the existing platforms to conduct RNAi-screens in cell-based assays; (2) a table of the Drosophila cell lines available for these screens and a brief mention of the need to establish other cell lines as well as cultures of primary cells; (3) a discussion of the considerations and protocols involved in establishing assays suitable for HTS in a 384-well format; and (A) a summary of the various ways of handling raw data from an ongoing screen, with special emphasis on how to apply normalization for experimental variation and statistical filters to sort out noise from signals.

2005_Methods Enzym_Armknecht.pdf