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

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 Drosophila Genome Resource Center (DGRC) in Bloomington, IN, USA. Look for VALIUM and WALIUM plasmids in their online vectors catalog.


Xiangzhao Yue, Yongkang Liang, Zhishuang Wei, Jun Lv, Yongjin Cai, Xiaobin Fan, Wenqing Zhang, and Jie Chen. 2021. “Genome-wide in vitro and in vivo RNAi screens reveal Fer3 to be an important regulator of kkv transcription in Drosophila.” Insect Sci.Abstract
Krotzkopf verkehrt (kkv) is a key enzyme that catalyzes the synthesis of chitin, an important component of the Drosophila epidermis, trachea, and other tissues. Here, we report the use of comprehensive RNA interference (RNAi) analyses to search for kkv transcriptional regulators. A cell-based RNAi screen identified 537 candidate kkv regulators on a genome-wide scale. Subsequent use of transgenic Drosophila lines expressing RNAi constructs enabled in vivo validation, and we identified six genes as potential kkv transcriptional regulators. Weakening of the kkvDsRed signal, an in vivo reporter indicating kkv promoter activity, was observed when the expression of Akirin, NFAT, 48 related 3 (Fer3), or Autophagy-related 101(Atg101) was knocked down in Drosophila at the 3rd-instar larval stage; whereas we observed disoriented taenidial folds on larval tracheae when Lines (lin) or Autophagy-related 3(Atg3) was knocked down in the tracheae. Fer3, in particular, has been shown to be an important factor in the activation of kkv transcription via specific binding with the kkv promoter. The genes involved in the chitin synthesis pathway were widely affected by the downregulation of Fer3. Furthermore, Atg101, Atg3, Akirin, Lin, NFAT, Pnr and Abd-A showed the potential complex mechanism of kkv transcription are regulated by an interaction network with bithorax complex components. Our study revealed the hitherto unappreciated diversity of modulators impinging on kkv transcription and opens new avenues in the study of kkv regulation and chitin biosynthesis. This article is protected by copyright. All rights reserved.
Yanhui Hu, Aram Comjean, Jonathan Rodiger, Yifang Liu, Yue Gao, Verena Chung, Jonathan Zirin, Norbert Perrimon, and Stephanie E Mohr. 2020. “ database of the Drosophila RNAi screening center and transgenic RNAi project: 2021 update.” Nucleic Acids Res.Abstract
The FlyRNAi database at the Drosophila RNAi Screening Center and Transgenic RNAi Project (DRSC/TRiP) provides a suite of online resources that facilitate functional genomics studies with a special emphasis on Drosophila melanogaster. Currently, the database provides: gene-centric resources that facilitate ortholog mapping and mining of information about orthologs in common genetic model species; reagent-centric resources that help researchers identify RNAi and CRISPR sgRNA reagents or designs; and data-centric resources that facilitate visualization and mining of transcriptomics data, protein modification data, protein interactions, and more. Here, we discuss updated and new features that help biological and biomedical researchers efficiently identify, visualize, analyze, and integrate information and data for Drosophila and other species. Together, these resources facilitate multiple steps in functional genomics workflows, from building gene and reagent lists to management, analysis, and integration of data.
Jonathan Zirin, Yanhui Hu, Luping Liu, Donghui Yang-Zhou, Ryan Colbeth, Dong Yan, Ben Ewen-Campen, Rong Tao, Eric Vogt, Sara VanNest, Cooper Cavers, Christians Villalta, Aram Comjean, Jin Sun, Xia Wang, Yu Jia, Ruibao Zhu, Ping Peng, Jinchao Yu, Da Shen, Yuhao Qiu, Limmond Ayisi, Henna Ragoowansi, Ethan Fenton, Senait Efrem, Annette Parks, Kuniaki Saito, Shu Kondo, Liz Perkins, Stephanie E Mohr, Jianquan Ni, and Norbert Perrimon. 2020. “Large-Scale Transgenic Resource Collections for Loss- and Gain-of-Function Studies.” Genetics.Abstract
The Transgenic RNAi Project (TRiP), a functional genomics platform at Harvard Medical School, was initiated in 2008 to generate and distribute a genome-scale collection of RNAi fly stocks. To date, the TRiP has generated >15,000 RNAi fly stocks. As this covers most genes, we have largely transitioned to development of new resources based on CRISPR technology. Here, we present an update on our libraries of publicly available RNAi and CRISPR fly stocks, and focus on the TRiP-CRISPR overexpression (TRiP-OE) and TRiP-CRISPR knockout (TRiP-KO) collections. TRiP-OE stocks express sgRNAs targeting upstream of a gene transcription start site. Gene activation is triggered by co-expression of catalytically dead Cas9 (dCas9) fused to an activator domain, either VP64-p65-Rta (VPR) or Synergistic Activation Mediator (SAM). TRiP-KO stocks express one or two sgRNAs targeting the coding sequence of a gene or genes. Cutting is triggered by co-expression of Cas9, allowing for generation of indels in both germline and somatic tissue. To date, we have generated more than 5,000 CRISPR-OE or -KO stocks for the community. These resources provide versatile, transformative tools for gene activation, gene repression, and genome engineering.
Michael D Rotelli, Anna M Bolling, Andrew W Killion, Abraham J Weinberg, Michael J Dixon, and Brian R Calvi. 2019. “An RNAi Screen for Genes Required for Growth of Wing Tissue.” G3 (Bethesda), 9, 10, Pp. 3087-3100.Abstract
Cell division and tissue growth must be coordinated with development. Defects in these processes are the basis for a number of diseases, including developmental malformations and cancer. We have conducted an unbiased RNAi screen for genes that are required for growth in the wing, using GAL4-inducible short hairpin RNA (shRNA) fly strains made by the Drosophila RNAi Screening Center. shRNA expression down the center of the larval wing disc using , and the central region of the adult wing was then scored for tissue growth and wing hair morphology. Out of 4,753 shRNA crosses that survived to adulthood, 18 had impaired wing growth. FlyBase and the new Alliance of Genome Resources knowledgebases were used to determine the known or predicted functions of these genes and the association of their human orthologs with disease. The function of eight of the genes identified has not been previously defined in The genes identified included those with known or predicted functions in cell cycle, chromosome segregation, morphogenesis, metabolism, steroid processing, transcription, and translation. All but one of the genes are similar to those in humans, and many are associated with disease. Knockdown of , a subunit of the Myb-MuvB transcription factor, or β, a gene involved in protein folding and trafficking, resulted in a switch from cell proliferation to an endoreplication growth program through which wing tissue grew by an increase in cell size (hypertrophy). It is anticipated that further analysis of the genes that we have identified will reveal new mechanisms that regulate tissue growth during development.
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.

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.