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Comjean, Aram

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Comjean

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Aram

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Comjean, Aram
Author's Publications: search.filters.isAuthorOfPublication.672360cb-e3d4-4aff-918f-5cc090de1a33

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Now showing 1 - 7 of 7
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    Molecular Interaction Search Tool (MIST): an integrated resource for mining gene and protein interaction data
    (Oxford University Press, 2018) Hu, Yanhui; Vinayagam, Arunachalam; Nand, Ankita; Comjean, Aram; Chung, Verena; Hao, Tong; Mohr, Stephanie; Perrimon, Norbert
    Abstract Model organism and human databases are rich with information about genetic and physical interactions. These data can be used to interpret and guide the analysis of results from new studies and develop new hypotheses. Here, we report the development of the Molecular Interaction Search Tool (MIST; http://fgrtools.hms.harvard.edu/MIST/). The MIST database integrates biological interaction data from yeast, nematode, fly, zebrafish, frog, rat and mouse model systems, as well as human. For individual or short gene lists, the MIST user interface can be used to identify interacting partners based on protein–protein and genetic interaction (GI) data from the species of interest as well as inferred interactions, known as interologs, and to view a corresponding network. The data, interologs and search tools at MIST are also useful for analyzing ‘omics datasets. In addition to describing the integrated database, we also demonstrate how MIST can be used to identify an appropriate cut-off value that balances false positive and negative discovery, and present use-cases for additional types of analysis. Altogether, the MIST database and search tools support visualization and navigation of existing protein and GI data, as well as comparison of new and existing data.
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    Gene2Function: An Integrated Online Resource for Gene Function Discovery
    (Genetics Society of America, 2017) Hu, Yanhui; Comjean, Aram; Mohr, Stephanie; Perrimon, Norbert
    One of the most powerful ways to develop hypotheses regarding the biological functions of conserved genes in a given species, such as humans, is to first look at what is known about their function in another species. Model organism databases and other resources are rich with functional information but difficult to mine. Gene2Function addresses a broad need by integrating information about conserved genes in a single online resource.
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    Reagent and Data Resources for Investigation of RNA Binding Protein Functions in Drosophila melanogaster Cultured Cells
    (Genetics Society of America, 2015) Mohr, Stephanie; Hu, Yanhui; Rudd, Kirstin; Buckner, Michael; Gilly, Quentin; Foster, Blake; Sierzputowska, Katarzyna; Comjean, Aram; Ye, Bing; Perrimon, Norbert
    RNA binding proteins (RBPs) are involved in many cellular functions. To facilitate functional characterization of RBPs, we generated an RNA interference (RNAi) library for Drosophila cell-based screens comprising reagents targeting known or putative RBPs. To test the quality of the library and provide a baseline analysis of the effects of the RNAi reagents on viability, we screened the library using a total ATP assay and high-throughput imaging in Drosophila S2R+ cultured cells. The results are consistent with production of a high-quality library that will be useful for functional genomics studies using other assays. Altogether, we provide resources in the form of an initial curated list of Drosophila RBPs; an RNAi screening library we expect to be used with additional assays that address more specific biological questions; and total ATP and image data useful for comparison of those additional assay results with fundamental information such as effects of a given reagent in the library on cell viability. Importantly, we make the baseline data, including more than 200,000 images, easily accessible online.
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    FlyRNAi.org—the database of the Drosophila RNAi screening center and transgenic RNAi project: 2017 update
    (Oxford University Press, 2017) Hu, Yanhui; Comjean, Aram; Roesel, Charles; Vinayagam, Arunachalam; Flockhart, Ian; Zirin, Jonathan; Perkins, Lizabeth A.; Perrimon, Norbert; Mohr, Stephanie
    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 (http://fgr.hms.harvard.edu) 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.
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    GLAD: an Online Database of Gene List Annotation for Drosophila
    (Ivyspring International Publisher, 2015) Hu, Yanhui; Comjean, Aram; Perkins, Lizabeth A.; Perrimon, Norbert; Mohr, Stephanie
    We present a resource of high quality lists of functionally related Drosophila genes, e.g. based on protein domains (kinases, transcription factors, etc.) or cellular function (e.g. autophagy, signal transduction). To establish these lists, we relied on different inputs, including curation from databases or the literature and mapping from other species. Moreover, as an added curation and quality control step, we asked experts in relevant fields to review many of the lists. The resource is available online for scientists to search and view, and is editable based on community input. Annotation of gene groups is an ongoing effort and scientific need will typically drive decisions regarding which gene lists to pursue. We anticipate that the number of lists will increase over time; that the composition of some lists will grow and/or change over time as new information becomes available; and that the lists will benefit the scientific community, e.g. at experimental design and data analysis stages. Based on this, we present an easily updatable online database, available at www.flyrnai.org/glad, at which gene group lists can be viewed, searched and downloaded.
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    The Drosophila Gene Expression Tool (DGET) for expression analyses
    (BioMed Central, 2017) Hu, Yanhui; Comjean, Aram; Perrimon, Norbert; Mohr, Stephanie
    Background: Next-generation sequencing technologies have greatly increased our ability to identify gene expression levels, including at specific developmental stages and in specific tissues. Gene expression data can help researchers understand the diverse functions of genes and gene networks, as well as help in the design of specific and efficient functional studies, such as by helping researchers choose the most appropriate tissue for a study of a group of genes, or conversely, by limiting a long list of gene candidates to the subset that are normally expressed at a given stage or in a given tissue. Results: We report DGET, a Drosophila Gene Expression Tool (www.flyrnai.org/tools/dget/web/), which stores and facilitates search of RNA-Seq based expression profiles available from the modENCODE consortium and other public data sets. Using DGET, researchers are able to look up gene expression profiles, filter results based on threshold expression values, and compare expression data across different developmental stages, tissues and treatments. In addition, at DGET a researcher can analyze tissue or stage-specific enrichment for an inputted list of genes (e.g., ‘hits’ from a screen) and search for additional genes with similar expression patterns. We performed a number of analyses to demonstrate the quality and robustness of the resource. In particular, we show that evolutionary conserved genes expressed at high or moderate levels in both fly and human tend to be expressed in similar tissues. Using DGET, we compared whole tissue profile and sub-region/cell-type specific datasets and estimated a potential source of false positives in one dataset. We also demonstrated the usefulness of DGET for synexpression studies by querying genes with expression profile similar to the mesodermal master regulator Twist. Conclusion: Altogether, DGET provides a flexible tool for expression data retrieval and analysis with short or long lists of Drosophila genes, which can help scientists to design stage- or tissue-specific in vivo studies and do other subsequent analyses.
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    Zinc Detoxification: A Functional Genomics and Transcriptomics Analysis in Drosophila melanogaster Cultured Cells
    (Genetics Society of America, 2018) Mohr, Stephanie; Rudd, Kirstin; Hu, Yanhui; Song, Wei; Gilly, Quentin; Buckner, Michael; Housden, Benjamin E.; Kelley, Colleen; Zirin, Jonathan; Tao, Rong; Amador, Gabriel; Sierzputowska, Katarzyna; Comjean, Aram; Perrimon, Norbert
    Cells require some metals, such as zinc and manganese, but excess levels of these metals can be toxic. As a result, cells have evolved complex mechanisms for maintaining metal homeostasis and surviving metal intoxication. Here, we present the results of a large-scale functional genomic screen in Drosophila cultured cells for modifiers of zinc chloride toxicity, together with transcriptomics data for wild-type or genetically zinc-sensitized cells challenged with mild zinc chloride supplementation. Altogether, we identified 47 genes for which knockdown conferred sensitivity or resistance to toxic zinc or manganese chloride treatment, and >1800 putative zinc-responsive genes. Analysis of the ‘omics data points to the relevance of ion transporters, glutathione (GSH)-related factors, and conserved disease-associated genes in zinc detoxification. Specific genes identified in the zinc screen include orthologs of human disease-associated genes CTNS, PTPRN (also known as IA-2), and ATP13A2 (also known as PARK9). We show that knockdown of red dog mine (rdog; CG11897), a candidate zinc detoxification gene encoding an ABCC-type transporter family protein related to yeast cadmium factor (YCF1), confers sensitivity to zinc intoxication in cultured cells, and that rdog is transcriptionally upregulated in response to zinc stress. As there are many links between the biology of zinc and other metals and human health, the ‘omics data sets presented here provide a resource that will allow researchers to explore metal biology in the context of diverse health-relevant processes.