Mouse

2021
Yanhui Hu, Sudhir Gopal Tattikota, Yifang Liu, Aram Comjean, Yue Gao, Corey Forman, Grace Kim, Jonathan Rodiger, Irene Papatheodorou, Gilberto Dos Santos, Stephanie E Mohr, and Norbert Perrimon. 2021. “DRscDB: A single-cell RNA-seq resource for data mining and data comparison across species.” Comput Struct Biotechnol J, 19, Pp. 2018-2026.Abstract
With the advent of single-cell RNA sequencing (scRNA-seq) technologies, there has been a spike in studies involving scRNA-seq of several tissues across diverse species including Drosophila. Although a few databases exist for users to query genes of interest within the scRNA-seq studies, search tools that enable users to find orthologous genes and their cell type-specific expression patterns across species are limited. Here, we built a new search database, DRscDB (https://www.flyrnai.org/tools/single_cell/web/), to address this need. DRscDB serves as a comprehensive repository for published scRNA-seq datasets for Drosophila and relevant datasets from human and other model organisms. DRscDB is based on manual curation of Drosophila scRNA-seq studies of various tissue types and their corresponding analogous tissues in vertebrates including zebrafish, mouse, and human. Of note, our search database provides most of the literature-derived marker genes, thus preserving the original analysis of the published scRNA-seq datasets. Finally, DRscDB serves as a web-based user interface that allows users to mine gene expression data from scRNA-seq studies and perform cell cluster enrichment analyses pertaining to various scRNA-seq studies, both within and across species.
DRscDB.pdf
Ilia A Droujinine, Amanda S Meyer, Dan Wang, Namrata D Udeshi, Yanhui Hu, David Rocco, Jill A McMahon, Rui Yang, JinJin Guo, Luye Mu, Dominique K Carey, Tanya Svinkina, Rebecca Zeng, Tess Branon, Areya Tabatabai, Justin A Bosch, John M Asara, Alice Y Ting, Steven A Carr, Andrew P McMahon, and Norbert Perrimon. 2021. “Proteomics of protein trafficking by in vivo tissue-specific labeling.” Nat Commun, 12, 1, Pp. 2382.Abstract
Conventional approaches to identify secreted factors that regulate homeostasis are limited in their abilities to identify the tissues/cells of origin and destination. We established a platform to identify secreted protein trafficking between organs using an engineered biotin ligase (BirA*G3) that biotinylates, promiscuously, proteins in a subcellular compartment of one tissue. Subsequently, biotinylated proteins are affinity-enriched and identified from distal organs using quantitative mass spectrometry. Applying this approach in Drosophila, we identify 51 muscle-secreted proteins from heads and 269 fat body-secreted proteins from legs/muscles, including CG2145 (human ortholog ENDOU) that binds directly to muscles and promotes activity. In addition, in mice, we identify 291 serum proteins secreted from conditional BirA*G3 embryo stem cell-derived teratomas, including low-abundance proteins with hormonal properties. Our findings indicate that the communication network of secreted proteins is vast. This approach has broad potential across different model systems to identify cell-specific secretomes and mediators of interorgan communication in health or disease.
2020
Yanhui Hu, Verena Chung, Aram Comjean, Jonathan Rodiger, Fnu Nipun, Norbert Perrimon, and Stephanie E Mohr. 2020. “BioLitMine: Advanced Mining of Biomedical and Biological Literature About Human Genes and Genes from Major Model Organisms.” G3 (Bethesda).Abstract
The accumulation of biological and biomedical literature outpaces the ability of most researchers and clinicians to stay abreast of their own immediate fields, let alone a broader range of topics. Although available search tools support identification of relevant literature, finding relevant and key publications is not always straightforward. For example, important publications might be missed in searches with an official gene name due to gene synonyms. Moreover, ambiguity of gene names can result in retrieval of a large number of irrelevant publications. To address these issues and help researchers and physicians quickly identify relevant publications, we developed BioLitMine, an advanced literature mining tool that takes advantage of the medical subject heading (MeSH) index and gene-to-publication annotations already available for PubMed literature. Using BioLitMine, a user can identify what MeSH terms are represented in the set of publications associated with a given gene of the interest, or start with a term and identify relevant publications. Users can also use the tool to find co-cited genes and a build a literature co-citation network. In addition, BioLitMine can help users build a gene list relevant to a MeSH terms, such as a list of genes relevant to "stem cells" or "breast neoplasms." Users can also start with a gene or pathway of interest and identify authors associated with that gene or pathway, a feature that makes it easier to identify experts who might serve as collaborators or reviewers. Altogether, BioLitMine extends the value of PubMed-indexed literature and its existing expert curation by providing a robust and gene-centric approach to retrieval of relevant information.
4531.full_.pdf
Yanhui Hu, Aram Comjean, Jonathan Rodiger, Yifang Liu, Yue Gao, Verena Chung, Jonathan Zirin, Norbert Perrimon, and Stephanie E Mohr. 2020. “FlyRNAi.org-the 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.
gkaa936.pdf
2019
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.
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.
2017_G3_Hu.pdf Supplemental Methods.pdf Table S1.xlsx
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, Undiagnosed Diseases Network, 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.
2017_Am J Hum Genet_Wang.pdf Supplement.pdf
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
Yanhui Hu, Aram Comjean, Charles Roesel, Arunachalam Vinayagam, Ian Flockhart, Jonathan Zirin, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 10/11/2016. “FlyRNAi.org—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 (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.

2016_Nucl Acids Res_Hu.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
Bahar Yilmazel, Yanhui Hu, Frederic Sigoillot, Jennifer A Smith, Caroline E Shamu, Norbert Perrimon, and Stephanie E Mohr. 2014. “Online GESS: prediction of miRNA-like off-target effects in large-scale RNAi screen data by seed region analysis.” BMC Bioinformatics, 15, Pp. 192.Abstract

BACKGROUND: RNA interference (RNAi) is an effective and important tool used to study gene function. For large-scale screens, RNAi is used to systematically down-regulate genes of interest and analyze their roles in a biological process. However, RNAi is associated with off-target effects (OTEs), including microRNA (miRNA)-like OTEs. The contribution of reagent-specific OTEs to RNAi screen data sets can be significant. In addition, the post-screen validation process is time and labor intensive. Thus, the availability of robust approaches to identify candidate off-targeted transcripts would be beneficial. RESULTS: Significant efforts have been made to eliminate false positive results attributable to sequence-specific OTEs associated with RNAi. These approaches have included improved algorithms for RNAi reagent design, incorporation of chemical modifications into siRNAs, and the use of various bioinformatics strategies to identify possible OTEs in screen results. Genome-wide Enrichment of Seed Sequence matches (GESS) was developed to identify potential off-targeted transcripts in large-scale screen data by seed-region analysis. Here, we introduce a user-friendly web application that provides researchers a relatively quick and easy way to perform GESS analysis on data from human or mouse cell-based screens using short interfering RNAs (siRNAs) or short hairpin RNAs (shRNAs), as well as for Drosophila screens using shRNAs. Online GESS relies on up-to-date transcript sequence annotations for human and mouse genes extracted from NCBI Reference Sequence (RefSeq) and Drosophila genes from FlyBase. The tool also accommodates analysis with user-provided reference sequence files. CONCLUSION: Online GESS provides a straightforward user interface for genome-wide seed region analysis for human, mouse and Drosophila RNAi screen data. With the tool, users can either use a built-in database or provide a database of transcripts for analysis. This makes it possible to analyze RNAi data from any organism for which the user can provide transcript sequences.

2014_BMC Bioinfo_Yilmazel.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
2013
Katharina Thiel, Christoph Heier, Verena Haberl, Peter J Thul, Monika Oberer, Achim Lass, Herbert Jäckle, and Mathias Beller. 2013. “The evolutionarily conserved protein CG9186 is associated with lipid droplets, required for their positioning and for fat storage.” J Cell Sci, 126, Pt 10, Pp. 2198-212.Abstract

Lipid droplets (LDs) are specialized cell organelles for the storage of energy-rich lipids. Although lipid storage is a conserved feature of all cells and organisms, little is known about fundamental aspects of the cell biology of LDs, including their biogenesis, structural assembly and subcellular positioning, and the regulation of organismic energy homeostasis. We identified a novel LD-associated protein family, represented by the Drosophila protein CG9186 and its murine homolog MGI:1916082. In the absence of LDs, both proteins localize at the endoplasmic reticulum (ER). Upon lipid storage induction, they translocate to LDs using an evolutionarily conserved targeting mechanism that acts through a 60-amino-acid targeting motif in the center of the CG9186 protein. Overexpression of CG9186, and MGI:1916082, causes clustering of LDs in both tissue culture and salivary gland cells, whereas RNAi knockdown of CG9186 results in a reduction of LDs. Organismal RNAi knockdown of CG9186 results in a reduction in lipid storage levels of the fly. The results indicate that we identified the first members of a novel and evolutionarily conserved family of lipid storage regulators, which are also required to properly position LDs within cells.

2013_J Cell Sci_Theil.pdf Supplement.pdf
Zheng Yin, Amine Sadok, Heba Sailem, Afshan McCarthy, Xiaofeng Xia, Fuhai Li, Mar Arias Garcia, Louise Evans, Alexis R Barr, Norbert Perrimon, Christopher J Marshall, Stephen TC Wong, and Chris Bakal. 2013. “A screen for morphological complexity identifies regulators of switch-like transitions between discrete cell shapes.” Nat Cell Biol, 15, 7, Pp. 860-71.Abstract

The way in which cells adopt different morphologies is not fully understood. Cell shape could be a continuous variable or restricted to a set of discrete forms. We developed quantitative methods to describe cell shape and show that Drosophila haemocytes in culture are a heterogeneous mixture of five discrete morphologies. In an RNAi screen of genes affecting the morphological complexity of heterogeneous cell populations, we found that most genes regulate the transition between discrete shapes rather than generating new morphologies. In particular, we identified a subset of genes, including the tumour suppressor PTEN, that decrease the heterogeneity of the population, leading to populations enriched in rounded or elongated forms. We show that these genes have a highly conserved function as regulators of cell shape in both mouse and human metastatic melanoma cells.

2013_Nat Cell Bio_Yin.pdf Supplemental Files.zip
2012
Stephanie C Stotz and David E Clapham. 2012. “Anion-sensitive fluorophore identifies the Drosophila swell-activated chloride channel in a genome-wide RNA interference screen.” PLoS One, 7, 10, Pp. e46865.Abstract

When cells swell in hypo-osmotic solutions, chloride-selective ion channels (Cl(swell)) activate to reduce intracellular osmolality and prevent catastrophic cell rupture. Despite intensive efforts to assign a molecular identity to the mammalian Cl(swell) channel, it remains unknown. In an unbiased genome-wide RNA interference (RNAi) screen of Drosophila cells stably expressing an anion-sensitive fluorescent indicator, we identify Bestrophin 1 (dBest1) as the Drosophila Cl(swell) channel. Of the 23 screen hits with mammalian homologs and predicted transmembrane domains, only RNAi specifically targeting dBest1 eliminated the Cl(swell) current (I(Clswell)). We further demonstrate the essential contribution of dBest1 to Drosophila I(Clswell) with the introduction of a human Bestrophin disease-associated mutation (W94C). Overexpression of the W94C construct in Drosophila cells significantly reduced the endogenous I(Clswell). We confirm that exogenous expression of dBest1 alone in human embryonic kidney (HEK293) cells creates a clearly identifiable Drosophila-like I(Clswell). In contrast, activation of mouse Bestrophin 2 (mBest2), the closest mammalian ortholog of dBest1, is swell-insensitive. The first 64 residues of dBest1 conferred swell activation to mBest2. The chimera, however, maintains mBest2-like pore properties, strongly indicating that the Bestrophin protein forms the Cl(swell) channel itself rather than functioning as an essential auxiliary subunit. dBest1 is an anion channel clearly responsive to swell; this activation depends upon its N-terminus.

2012_PLOS One_Stotz.pdf Supplemental Files.zip
Joshua D Stender, Gabriel Pascual, Wen Liu, Minna U Kaikkonen, Kevin Do, Nathanael J Spann, Michael Boutros, Norbert Perrimon, Michael G Rosenfeld, and Christopher K Glass. 2012. “Control of proinflammatory gene programs by regulated trimethylation and demethylation of histone H4K20.” Mol Cell, 48, 1, Pp. 28-38.Abstract

Regulation of genes that initiate and amplify inflammatory programs of gene expression is achieved by signal-dependent exchange of coregulator complexes that function to read, write, and erase specific histone modifications linked to transcriptional activation or repression. Here, we provide evidence for the role of trimethylated histone H4 lysine 20 (H4K20me3) as a repression checkpoint that restricts expression of toll-like receptor 4 (TLR4) target genes in macrophages. H4K20me3 is deposited at the promoters of a subset of these genes by the SMYD5 histone methyltransferase through its association with NCoR corepressor complexes. Signal-dependent erasure of H4K20me3 is required for effective gene activation and is achieved by NF-κB-dependent delivery of the histone demethylase PHF2. Liver X receptors antagonize TLR4-dependent gene activation by maintaining NCoR/SMYD5-mediated repression. These findings reveal a histone H4K20 trimethylation/demethylation strategy that integrates positive and negative signaling inputs that control immunity and homeostasis.

2012_Mol Cell_Stender.pdf Supplemental Files.zip
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
Yanhui Hu, Ian Flockhart, Arunachalam Vinayagam, Clemens Bergwitz, Bonnie Berger, Norbert Perrimon, and Stephanie E Mohr. 2011. “An integrative approach to ortholog prediction for disease-focused and other functional studies.” BMC Bioinformatics, 12, Pp. 357.Abstract

BACKGROUND: Mapping of orthologous genes among species serves an important role in functional genomics by allowing researchers to develop hypotheses about gene function in one species based on what is known about the functions of orthologs in other species. Several tools for predicting orthologous gene relationships are available. However, these tools can give different results and identification of predicted orthologs is not always straightforward. RESULTS: We report a simple but effective tool, the Drosophila RNAi Screening Center Integrative Ortholog Prediction Tool (DIOPT; http://www.flyrnai.org/diopt), for rapid identification of orthologs. DIOPT integrates existing approaches, facilitating rapid identification of orthologs among human, mouse, zebrafish, C. elegans, Drosophila, and S. cerevisiae. As compared to individual tools, DIOPT shows increased sensitivity with only a modest decrease in specificity. Moreover, the flexibility built into the DIOPT graphical user interface allows researchers with different goals to appropriately 'cast a wide net' or limit results to highest confidence predictions. DIOPT also displays protein and domain alignments, including percent amino acid identity, for predicted ortholog pairs. This helps users identify the most appropriate matches among multiple possible orthologs. To facilitate using model organisms for functional analysis of human disease-associated genes, we used DIOPT to predict high-confidence orthologs of disease genes in Online Mendelian Inheritance in Man (OMIM) and genes in genome-wide association study (GWAS) data sets. The results are accessible through the DIOPT diseases and traits query tool (DIOPT-DIST; http://www.flyrnai.org/diopt-dist). CONCLUSIONS: DIOPT and DIOPT-DIST are useful resources for researchers working with model organisms, especially those who are interested in exploiting model organisms such as Drosophila to study the functions of human disease genes.

2011_BMC Bioinfo_Hu.pdf Supplemental Files.zip
2010
Amy M Wiles, Mark Doderer, Jianhua Ruan, Ting-Ting Gu, Dashnamoorthy Ravi, Barron Blackman, and Alexander JR Bishop. 2010. “Building and analyzing protein interactome networks by cross-species comparisons.” BMC Syst Biol, 4, Pp. 36.Abstract

BACKGROUND: A genomic catalogue of protein-protein interactions is a rich source of information, particularly for exploring the relationships between proteins. Numerous systems-wide and small-scale experiments have been conducted to identify interactions; however, our knowledge of all interactions for any one species is incomplete, and alternative means to expand these network maps is needed. We therefore took a comparative biology approach to predict protein-protein interactions across five species (human, mouse, fly, worm, and yeast) and developed InterologFinder for research biologists to easily navigate this data. We also developed a confidence score for interactions based on available experimental evidence and conservation across species. RESULTS: The connectivity of the resultant networks was determined to have scale-free distribution, small-world properties, and increased local modularity, indicating that the added interactions do not disrupt our current understanding of protein network structures. We show examples of how these improved interactomes can be used to analyze a genome-scale dataset (RNAi screen) and to assign new function to proteins. Predicted interactions within this dataset were tested by co-immunoprecipitation, resulting in a high rate of validation, suggesting the high quality of networks produced. CONCLUSIONS: Protein-protein interactions were predicted in five species, based on orthology. An InteroScore, a score accounting for homology, number of orthologues with evidence of interactions, and number of unique observations of interactions, is given to each known and predicted interaction. Our website http://www.interologfinder.org provides research biologists intuitive access to this data.

2010_BMC Sys Bio_Wiles.pdf Supplemental Files.zip

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