Xingjie Ren, Jin Sun, Benjamin E Housden, Yanhui Hu, Charles Roesel, Shuailiang Lin, Lu-Ping Liu, Zhihao Yang, Decai Mao, Lingzhu Sun, Qujie Wu, Jun-Yuan Ji, Jianzhong Xi, Stephanie E Mohr, Jiang Xu, Norbert Perrimon, and Jian-Quan Ni. 2013. “
Optimized gene editing technology for Drosophila melanogaster using germ line-specific Cas9.” Proc Natl Acad Sci U S A, 110, 47, Pp. 19012-7.
AbstractThe ability to engineer genomes in a specific, systematic, and cost-effective way is critical for functional genomic studies. Recent advances using the CRISPR-associated single-guide RNA system (Cas9/sgRNA) illustrate the potential of this simple system for genome engineering in a number of organisms. Here we report an effective and inexpensive method for genome DNA editing in Drosophila melanogaster whereby plasmid DNAs encoding short sgRNAs under the control of the U6b promoter are injected into transgenic flies in which Cas9 is specifically expressed in the germ line via the nanos promoter. We evaluate the off-targets associated with the method and establish a Web-based resource, along with a searchable, genome-wide database of predicted sgRNAs appropriate for genome engineering in flies. Finally, we discuss the advantages of our method in comparison with other recently published approaches.
2013_PNAS_Ren.pdf
Supplement.pdf Arunachalam Vinayagam, Yanhui Hu, Meghana Kulkarni, Charles Roesel, Richelle Sopko, Stephanie E Mohr, and Norbert Perrimon. 2013. “
Protein complex-based analysis framework for high-throughput data sets.” Sci Signal, 6, 264, Pp. rs5.
AbstractAnalysis of high-throughput data increasingly relies on pathway annotation and functional information derived from Gene Ontology. This approach has limitations, in particular for the analysis of network dynamics over time or under different experimental conditions, in which modules within a network rather than complete pathways might respond and change. We report an analysis framework based on protein complexes, which are at the core of network reorganization. We generated a protein complex resource for human, Drosophila, and yeast from the literature and databases of protein-protein interaction networks, with each species having thousands of complexes. We developed COMPLEAT (http://www.flyrnai.org/compleat), a tool for data mining and visualization for complex-based analysis of high-throughput data sets, as well as analysis and integration of heterogeneous proteomics and gene expression data sets. With COMPLEAT, we identified dynamically regulated protein complexes among genome-wide RNA interference data sets that used the abundance of phosphorylated extracellular signal-regulated kinase in cells stimulated with either insulin or epidermal growth factor as the output. The analysis predicted that the Brahma complex participated in the insulin response.
2013_Sci Sig_Vinayagam.pdf
Supplemental Files.zip 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.
AbstractThe 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 Yanhui Hu, Charles Roesel, Ian Flockhart, Lizabeth Perkins, Norbert Perrimon, and Stephanie E Mohr. 2013. “
UP-TORR: online tool for accurate and Up-to-Date annotation of RNAi Reagents.” Genetics, 195, 1, Pp. 37-45.
AbstractRNA interference (RNAi) is a widely adopted tool for loss-of-function studies but RNAi results only have biological relevance if the reagents are appropriately mapped to genes. Several groups have designed and generated RNAi reagent libraries for studies in cells or in vivo for Drosophila and other species. At first glance, matching RNAi reagents to genes appears to be a simple problem, as each reagent is typically designed to target a single gene. In practice, however, the reagent-gene relationship is complex. Although the sequences of oligonucleotides used to generate most types of RNAi reagents are static, the reference genome and gene annotations are regularly updated. Thus, at the time a researcher chooses an RNAi reagent or analyzes RNAi data, the most current interpretation of the RNAi reagent-gene relationship, as well as related information regarding specificity (e.g., predicted off-target effects), can be different from the original interpretation. Here, we describe a set of strategies and an accompanying online tool, UP-TORR (for Updated Targets of RNAi Reagents; www.flyrnai.org/up-torr), useful for accurate and up-to-date annotation of cell-based and in vivo RNAi reagents. Importantly, UP-TORR automatically synchronizes with gene annotations daily, retrieving the most current information available, and for Drosophila, also synchronizes with the major reagent collections. Thus, UP-TORR allows users to choose the most appropriate RNAi reagents at the onset of a study, as well as to perform the most appropriate analyses of results of RNAi-based studies.
2013_Genetics_Hu.pdf
Supplement.pdf