in vivo RNAi fly stocks and vectors

To date the TRiP has generated over 12,000 Drosophila RNAi stocks, and developed efficient vectors for RNAi that work in all tissues. For a detailed description of the the TRiP in vivo RNAi approach click here.

TRiP fly stock collections

  • TRiPSoma- for effective knockdown in somatic cells
  • TRiPGermline- for effective knockdown in the germline
  • Human Disease Transgenic RNAi Project (HuDis-TRiP) - targeting orthologs of genes associated with human diseases
  • TRiP Toolbox - injection stocks for labs wishing to generate their own RNAi lines and commonly used GAL4 lines with UAS-Dcr2 to enhance knockdown
  • Controls- TRiP stocks for use as experimental controls
  • Download an .XLS file of current TRiP stocks, including detailed information on hairpin design and target(s)

Community Access to the TRiP Stocks

The Transgenic RNAi Project continues to make new RNAi fly stocks for the community and to maintain and improve the current library of TRiP RNAi stocks available at BDSC.

  • All completed stocks are annotated on the TRiP website and on FlyBase, and transferred as soon as possible to the BDSC for distribution to the community
  • If a TRiP stock has not yet been deposited at the BDSC, please contact the TRiP facility at HMS and we will send it to you
  • If use of any of the TRiP stocks results in data that is included in a manuscript for publication, the TRiP requests that a version of the following statement be included in the Acknowledgements section: "We thank the TRiP at Harvard Medical School (NIH/NIGMS R01-GM084947) for providing transgenic RNAi fly stocks used in this study"

Nominating genes for TRiP production

  • Selections will be in keeping with the BDSC mandate of one mutation per gene
  • We will meet the needs of screeners at the Drosophila RNAi Screening Center (DRSC) for in vivo follow-up studies subsequent to cell-based screens
  • We will meet the needs of the Drosophila community for in vivo phenotypic analyses through a nomination process. In keeping with our NIH/NIGMS funding, priority will go to nominations that help to fill in the phenotype gap and overcome issues associated with pleiotropy

To nominate a gene(s), the PI of the lab should send a letter to that includes an explanation of why the specific gene is being nominated.

TRiP vectors

  • Knockdown vectors - 1st and 2nd generation VALIUM and WALIUM vectors and QUAS vector for transgenic RNAi
  • Overexpression vectors - VALIUM10-moe, VALIUM10-roe, WALIUM10-moe, and WALIUM10-roe for in vivo overexpression.
  • mENTRY - a Gateway donor/entry vector with multiple cloning site
  • TRiP vectors, including vermillion and white versions of vectors for over-expression, are available through the DF/HCC Plasmid Resource Core, a plasmid repository at the DNA Resource Core at Harvard Medical School
  • We would be happy to place the vectors with additional repositories at community request.


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, 31 Oct, 10/31/2016. 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.

Lizabeth A Perkins, Laura Holderbaum, Rong Tao, Yanhui Hu, Richelle Sopko, Kim McCall, Donghui Yang-Zhou, Ian Flockhart, Richard Binari, Hye-Seok Shim, Audrey Miller, Amy Housden, Marianna Foos, Sakara Randkelv, Colleen Kelley, Pema Namgyal, Christians Villalta, Lu-Ping Liu, Xia Jiang, Qiao Huan-Huan, Xia Wang, Asao Fujiyama, Atsushi Toyoda, Kathleen Ayers, Allison Blum, Benjamin Czech, Ralph Neumuller, Dong Yan, Amanda Cavallaro, Karen Hibbard, Don Hall, Lynn Cooley, Gregory J Hannon, Ruth Lehmann, Annette Parks, Stephanie E Mohr, Ryu Ueda, Shu Kondo, Jian-Quan Ni, and Norbert Perrimon. 2015. “The Transgenic RNAi Project at Harvard Medical School: Resources and Validation..” Genetics, 3, 201: 843-52, 2015 Nov.Abstract

To facilitate large-scale functional studies in Drosophila, the Drosophila Transgenic RNAi Project (TRiP) at Harvard Medical School (HMS) was established along with several goals: developing efficient vectors for RNAi that work in all tissues, generating a genome-scale collection of RNAi stocks with input from the community, distributing the lines as they are generated through existing stock centers, validating as many lines as possible using RT-qPCR and phenotypic analyses, and developing tools and web resources for identifying RNAi lines and retrieving existing information on their quality. With these goals in mind, here we describe in detail the various tools we developed and the status of the collection, which is currently composed of 11,491 lines and covering 71% of Drosophila genes. Data on the characterization of the lines either by RT-qPCR or phenotype is available on a dedicated website, the RNAi Stock Validation and Phenotypes Project (RSVP,, and stocks are available from three stock centers, the Bloomington Drosophila Stock Center (United States), National Institute of Genetics (Japan), and TsingHua Fly Center (China).

Richelle Sopko, Marianna Foos, Arunachalam Vinayagam, Bo Zhai, Richard Binari, Yanhui Hu, Sakara Randklev, Lizabeth A Perkins, Steven P Gygi, and Norbert Perrimon. 2014. “Combining genetic perturbations and proteomics to examine kinase-phosphatase networks in Drosophila embryos..” Dev Cell, 1, 31: 114-27, 2014 Oct 13.Abstract

Connecting phosphorylation events to kinases and phosphatases is key to understanding the molecular organization and signaling dynamics of networks. We have generated a validated set of transgenic RNA-interference reagents for knockdown and characterization of all protein kinases and phosphatases present during early Drosophila melanogaster development. These genetic tools enable collection of sufficient quantities of embryos depleted of single gene products for proteomics. As a demonstration of an application of the collection, we have used multiplexed isobaric labeling for quantitative proteomics to derive global phosphorylation signatures associated with kinase-depleted embryos to systematically link phosphosites with relevant kinases. We demonstrate how this strategy uncovers kinase consensus motifs and prioritizes phosphoproteins for kinase target validation. We validate this approach by providing auxiliary evidence for Wee kinase-directed regulation of the chromatin regulator Stonewall. Further, we show how correlative phosphorylation at the site level can indicate function, as exemplified by Sterile20-like kinase-dependent regulation of Stat92E.

Stephanie E Mohr. 2014. “RNAi screening in Drosophila cells and in vivo..” Methods, 1, 68: 82-8, 2014 Jun 15.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.

Dong Yan, Ralph A Neumüller, Michael Buckner, Kathleen Ayers, Hua Li, Yanhui Hu, Donghui Yang-Zhou, Lei Pan, Xiaoxi Wang, Colleen Kelley, Arunachalam Vinayagam, Richard Binari, Sakara Randklev, Lizabeth A Perkins, Ting Xie, Lynn Cooley, and Norbert Perrimon. 2014. “A regulatory network of Drosophila germline stem cell self-renewal..” Dev Cell, 4, 28: 459-73, 2014 Feb 24.Abstract

Stem cells possess the capacity to generate two cells of distinct fate upon division: one cell retaining stem cell identity and the other cell destined to differentiate. These cell fates are established by cell-type-specific genetic networks. To comprehensively identify components of these networks, we performed a large-scale RNAi screen in Drosophila female germline stem cells (GSCs) covering ∼25% of the genome. The screen identified 366 genes that affect GSC maintenance, differentiation, or other processes involved in oogenesis. Comparison of GSC regulators with neural stem cell self-renewal factors identifies common and cell-type-specific self-renewal genes. Importantly, we identify the histone methyltransferase Set1 as a GSC-specific self-renewal factor. Loss of Set1 in neural stem cells does not affect cell fate decisions, suggesting a differential requirement of H3K4me3 in different stem cell lineages. Altogether, our study provides a resource that will help to further dissect the networks underlying stem cell self-renewal.

Joshua M Shulman, Selina Imboywa, Nikolaos Giagtzoglou, Martin P Powers, Yanhui Hu, Danelle Devenport, Portia Chipendo, Lori B Chibnik, Allison Diamond, Norbert Perrimon, Nicholas H Brown, Philip L De Jager, and Mel B Feany. 2014. “Functional screening in Drosophila identifies Alzheimer's disease susceptibility genes and implicates Tau-mediated mechanisms..” Hum Mol Genet, 4, 23: 870-7, 2014 Feb 15.Abstract

Using a Drosophila model of Alzheimer's disease (AD), we systematically evaluated 67 candidate genes based on AD-associated genomic loci (P < 10(-4)) from published human genome-wide association studies (GWAS). Genetic manipulation of 87 homologous fly genes was tested for modulation of neurotoxicity caused by human Tau, which forms neurofibrillary tangle pathology in AD. RNA interference (RNAi) targeting 9 genes enhanced Tau neurotoxicity, and in most cases reciprocal activation of gene expression suppressed Tau toxicity. Our screen implicates cindr, the fly ortholog of the human CD2AP AD susceptibility gene, as a modulator of Tau-mediated disease mechanisms. Importantly, we also identify the fly orthologs of FERMT2 and CELF1 as Tau modifiers, and these loci have been independently validated as AD susceptibility loci in the latest GWAS meta-analysis. Both CD2AP and FERMT2 have been previously implicated with roles in cell adhesion, and our screen additionally identifies a fly homolog of the human integrin adhesion receptors, ITGAM and ITGA9, as a modifier of Tau neurotoxicity. Our results highlight cell adhesion pathways as important in Tau toxicity and AD susceptibility and demonstrate the power of model organism genetic screens for the functional follow-up of human GWAS.