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Hyperactivating mutations in Ras signaling are hallmarks of carcinomas. Ras signaling mediates cell fate decisions as well as proliferation during development. It is not known what dictates whether Ras signaling drives differentiation versus proliferation. Here we show that the Hippo pathway is critical for this decision. Loss of Hippo switches Ras activation from promoting cellular differentiation to aggressive cellular proliferation. Transcriptome analysis combined with genetic tests show that this excessive proliferation depends on the synergistic induction of Ras target genes. Using ChIP-nexus, we find that Hippo signaling keeps Ras targets in check by directly regulating the expression of two key downstream transcription factors of Ras signaling: the ETS-domain transcription factor Pointed and the repressor Capicua. Our results highlight how independent signaling pathways can impinge on each other at the level of transcription factors, thereby providing a safety mechanism to keep proliferation in check under normal developmental conditions.
Pubmed ID: 28950103 RIS Download
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Biomaterial supply resource which collects, maintains, and distributes independent transgenic fly lines. Most of the 38,000 fly lines are RNAi lines, but VDRC also maintains a collection of enhancer-GAL4 driver lines. Nearly all lines are in duplicate. Users can search for the stocks or DNA constructs for the gene of interest by entering CG number, synonym, or Transformant ID.
View all literature mentionsUltrafast and memory efficient tool for aligning sequencing reads to long reference sequences. Supports gapped, local, and paired end alignment modes. More suited to finding longer, gapped alignments in comparison with original Bowtie method.
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View all literature mentionsA desktop application for the analysis, visualization and data-mining of large-scale genomic data. It is a versatile microarray tool, incorporating sophisticated algorithms for clustering, visualization, classification, statistical analysis and biological theme discovery. MeV generates informative and interrelated displays of expression and annotation data from single or multiple experiments. A huge array of alrogithms are included in MeV modules, and are available at a button-click, such as K-means clustering, Hierarchical clustering, t-Tests, Significance Analysis of Microarrays, Gene Set Enrichment Analysis, and EASE. Extensive documentation is available for helping new users get started with MeV. A Quickstart Guide provides the tutorial a brand new person will need to get their first dataset loaded and displayed in the program. Returning MEV users will want to check out the release notes to see what new features are available in the latest versions of the program. Tutorials have been written about several of its more involved features.
View all literature mentionsSoftware package for differential gene expression analysis based on the negative binomial distribution. Used for analyzing RNA-seq data for differential analysis of count data, using shrinkage estimation for dispersions and fold changes to improve stability and interpretability of estimates.
View all literature mentionsSoftware ultrafast memory efficient tool for aligning sequencing reads. Bowtie is short read aligner.
View all literature mentionsThe SciCrunch Infrastructure was developed as a cooperative data platform to be used by diverse communities in making data more FAIR.
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