Screenshot of online tools

Navigating our online tools -- orthologs, literature mining, qPCR primers, and so much more!

February 14, 2019

We have been taking a critical look at how we organize our online tools on the Online Tools Overview page. And more generally, we have been thinking about new ways to spread the word about the many resources in our suite of online tools. One way that we at the DRSC like to think about these tools is how they fit into the start-to-finish order of events in a screen or other experimental project. Various tools help define lists of genes to be studied, help identify reagents for the study,...

Read more about Navigating our online tools -- orthologs, literature mining, qPCR primers, and so much more!
Figure 2 from Housden et al 2017 PNAS

Variable Dose Analysis: a new DRSC-supported cell screen approach that leverages existing reagents to perform robust screens

December 1, 2017

We are excited to report the publication of a paper from Benjamin Housden and colleagues describing development and use of the Variable Dose Analysis (VDA) approach. Ben developed a way to use existing TRiP shRNA plasmids originally developed for fly stock production in a new, effective approach to high-throughput cell screening.

The VDA approach is particularly useful for combinatorial approaches that are acutely sensitive to assay robustness. The screen Ben and colleagues report focused on synthetic effects in Drosophila tumor model cells.  The...

Read more about Variable Dose Analysis: a new DRSC-supported cell screen approach that leverages existing reagents to perform robust screens
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.
Julia Wang, Rami Al-Ouran, Yanhui Hu, Seon-Young Kim, Ying-Wooi Wan, Michael F Wangler, Shinya Yamamoto, Hsiao-Tuan Chao, Aram Comjean, Stephanie E Mohr, Stephanie E Mohr, Norbert Perrimon, Zhandong Liu, and Hugo J Bellen. 6/1/2017. “MARRVEL: Integration of Human and Model Organism Genetic Resources to Facilitate Functional Annotation of the Human Genome.” Am J Hum Genet, 100, 6, Pp. 843-853.Abstract
One major challenge encountered with interpreting human genetic variants is the limited understanding of the functional impact of genetic alterations on biological processes. Furthermore, there remains an unmet demand for an efficient survey of the wealth of information on human homologs in model organisms across numerous databases. To efficiently assess the large volume of publically available information, it is important to provide a concise summary of the most relevant information in a rapid user-friendly format. To this end, we created MARRVEL (model organism aggregated resources for rare variant exploration). MARRVEL is a publicly available website that integrates information from six human genetic databases and seven model organism databases. For any given variant or gene, MARRVEL displays information from OMIM, ExAC, ClinVar, Geno2MP, DGV, and DECIPHER. Importantly, it curates model organism-specific databases to concurrently display a concise summary regarding the human gene homologs in budding and fission yeast, worm, fly, fish, mouse, and rat on a single webpage. Experiment-based information on tissue expression, protein subcellular localization, biological process, and molecular function for the human gene and homologs in the seven model organisms are arranged into a concise output. Hence, rather than visiting multiple separate databases for variant and gene analysis, users can obtain important information by searching once through MARRVEL. Altogether, MARRVEL dramatically improves efficiency and accessibility to data collection and facilitates analysis of human genes and variants by cross-disciplinary integration of 18 million records available in public databases to facilitate clinical diagnosis and basic research.
Yanhui Hu, Aram Comjean, Stephanie E Mohr, The FlyBase Consortium, and Norbert Perrimon. 8/7/2017. “Gene2Function: An Integrated Online Resource for Gene Function Discovery.” G3 (Bethesda).Abstract
One of the most powerful ways to develop hypotheses regarding biological functions of conserved genes in a given species, such as in humans, is to first look at what is known about function in another species. Model organism databases (MODs) and other resources are rich with functional information but difficult to mine. Gene2Function (G2F) addresses a broad need by integrating information about conserved genes in a single online resource.
Arunachalam Vinayagam, Travis E Gibson, Ho-Joon Lee, Bahar Yilmazel, Charles Roesel, Yanhui Hu, Young Kwon, Amitabh Sharma, Yang-Yu Liu, Norbert Perrimon, and Albert-László Barabási. 5/3/2016. “Controllability analysis of the directed human protein interaction network identifies disease genes and drug targets.” Proc Natl Acad Sci U S A, 113, 18, Pp. 4976-81.Abstract

The protein-protein interaction (PPI) network is crucial for cellular information processing and decision-making. With suitable inputs, PPI networks drive the cells to diverse functional outcomes such as cell proliferation or cell death. Here, we characterize the structural controllability of a large directed human PPI network comprising 6,339 proteins and 34,813 interactions. This network allows us to classify proteins as "indispensable," "neutral," or "dispensable," which correlates to increasing, no effect, or decreasing the number of driver nodes in the network upon removal of that protein. We find that 21% of the proteins in the PPI network are indispensable. Interestingly, these indispensable proteins are the primary targets of disease-causing mutations, human viruses, and drugs, suggesting that altering a network's control property is critical for the transition between healthy and disease states. Furthermore, analyzing copy number alterations data from 1,547 cancer patients reveals that 56 genes that are frequently amplified or deleted in nine different cancers are indispensable. Among the 56 genes, 46 of them have not been previously associated with cancer. This suggests that controllability analysis is very useful in identifying novel disease genes and potential drug targets.

Huajin Wang, Michel Becuwe, Benjamin E Housden, Chandramohan Chitraju, Ashley J Porras, Morven M Graham, Xinran N Liu, Abdou Rachid Thiam, David B Savage, Anil K Agarwal, Abhimanyu Garg, Maria-Jesus Olarte, Qingqing Lin, Florian Fröhlich, Hans Kristian Hannibal-Bach, Srigokul Upadhyayula, Norbert Perrimon, Tomas Kirchhausen, Christer S Ejsing, Tobias C Walther, and Robert V Farese. 2016. “Seipin is required for converting nascent to mature lipid droplets.” Elife, 5.Abstract

How proteins control the biogenesis of cellular lipid droplets (LDs) is poorly understood. Using Drosophila and human cells, we show here that seipin, an ER protein implicated in LD biology, mediates a discrete step in LD formation-the conversion of small, nascent LDs to larger, mature LDs. Seipin forms discrete and dynamic foci in the ER that interact with nascent LDs to enable their growth. In the absence of seipin, numerous small, nascent LDs accumulate near the ER and most often fail to grow. Those that do grow prematurely acquire lipid synthesis enzymes and undergo expansion, eventually leading to the giant LDs characteristic of seipin deficiency. Our studies identify a discrete step of LD formation, namely the conversion of nascent LDs to mature LDs, and define a molecular role for seipin in this process, most likely by acting at ER-LD contact sites to enable lipid transfer to nascent LDs.

Amino acid alignment of the fly paralogs kek1 and kek2

DIOPT 6.0 released -- with eggNOG and paralog searches added

November 29, 2016

DIOPT 6.0 went live this week. Newly added features include results from eggNOG, bringing the total number of alrogithms incorporated in our integrated search tool to 14. In addition, you can now search for paralogs. To do this, choose the same species for input and output. Examples for fly-fly and human-human paralog searches are shown. As always, your feedback is welcome.


Read more about DIOPT 6.0 released -- with eggNOG and paralog searches added
Yanhui Hu, Aram Comjean, Charles Roesel, Arunachalam Vinayagam, Ian Flockhart, Jonathan Zirin, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 10/11/2016. “—the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update.” Nucleic Acids Research. Publisher's VersionAbstract

The FlyRNAi database of the Drosophila RNAi Screening Center (DRSC) and Transgenic RNAi Project (TRiP) at Harvard Medical School and associated DRSC/TRiP Functional Genomics Resources website ( serve as a reagent production tracking system, screen data repository, and portal to the community. Through this portal, we make available protocols, online tools, and other resources useful to researchers at all stages of high-throughput functional genomics screening, from assay design and reagent identification to data analysis and interpretation. In this update, we describe recent changes and additions to our website, database and suite of online tools. Recent changes reflect a shift in our focus from a single technology (RNAi) and model species (Drosophila) to the application of additional technologies (e.g. CRISPR) and support of integrated, cross-species approaches to uncovering gene function using functional genomics and other approaches.

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.