RNA-binding proteins contribute to the formation of ribonucleoprotein (RNP) granules by phase transition, but regulatory mechanisms are not fully understood. Conserved fission yeast NDR (Nuclear Dbf2-Related) kinase Orb6 governs cell morphogenesis in part by spatially controlling Cdc42 GTPase. Here we describe a novel, independent function for Orb6 kinase in negatively regulating the recruitment of RNA-binding protein Sts5 into RNPs to promote polarized cell growth. We find that Orb6 kinase inhibits Sts5 recruitment into granules, its association with processing (P) bodies, and degradation of Sts5-bound mRNAs by promoting Sts5 interaction with 14-3-3 protein Rad24. Many Sts5-bound mRNAs encode essential factors for polarized cell growth, and Orb6 kinase spatially and temporally controls the extent of Sts5 granule formation. Disruption of this control system affects cell morphology and alters the pattern of polarized cell growth, revealing a role for Orb6 kinase in the spatial control of translational repression that enables normal cell morphogenesis.
Pubmed ID: 27474797 RIS Download
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Commercial antibody vendor which supplies antibodies and other products to life science researchers.
View all literature mentionsA division of Applied Biosystems selling products for the isolation, detection, quantification, amplification, and characterization of RNA.
View all literature mentionsThe Database of Protein Disorder (DisProt) is a curated database that provides information about proteins that lack fixed 3D structure in their putatively native states, either in their entirety or in part. Users can BLAST sequences, browse by protein name, or view by protein function and functional subclass.
View all literature mentionsDigital microscopy software for research microscopy. It comes standard with drivers to control numerous instruments in and around the microscope. When online, data is acquired in a native-3D format over time, color and specimen locations in customizable experiment protocols. Data can be analyzed by a wide variety of tools for image processing including mathematical operations, statistics functions, analysis scripting and import to/export from MATLAB. Additional modules are available for special applications ranging from deconvolution to photomanipulation to multiphoton.
View all literature mentionsThis unknown targets
View all literature mentionsThis unknown targets Raised against a peptide mapping near the C-terminus of c-Myc of human origin.
View all literature mentionsThis monoclonal targets α-tubulin
View all literature mentionsThis monoclonal targets 6-His Purified
View all literature mentionsThis unknown targets Rat IgG (H&L)
View all literature mentionsThis polyclonal targets RABBIT IgG (H&L) IRDye800 Pre-adsorbed
View all literature mentionsThis monoclonal targets Tubulin
View all literature mentionsThis unknown targets Mouse IgG (H&L) Antibody DyLight 800 Conjugated
View all literature mentionsOpen source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
View all literature mentionsBioinformatics resource system including web server and web service for functional annotation and enrichment analyses of gene lists. Consists of comprehensive knowledgebase and set of functional analysis tools. Includes gene centered database integrating heterogeneous gene annotation resources to facilitate high throughput gene functional analysis.
View all literature mentionsRMAExpress is a standalone GUI program for Windows (and Linux) to compute gene expression summary values for Affymetrix Genechip data using the Robust Multichip Average expression summary and to carry out quality assessment using probe-level metrics. It does not require R nor is it dependent on any component of the BioConductor project. If focuses on processing 3'' IVT expression arrays, exon and WT gene arrays. What is RMA? RMA is the Robust Multichip Average. It consists of three steps: a background adjustment, quantile normalization (see the Bolstad et al reference) and finally summarization. Some references (currently published) for the RMA methodology are: Bolstad, B.M., Irizarry R. A., Astrand, M., and Speed, T.P. (2003), A Comparison of Normalization Methods for High Density Oligonucleotide Array Data Based on Bias and Variance. Bioinformatics 19(2):185-193 Supplemental information Rafael. A. Irizarry, Benjamin M. Bolstad, Francois Collin, Leslie M. Cope, Bridget Hobbs and Terence P. Speed (2003), Summaries of Affymetrix GeneChip probe level data Nucleic Acids Research 31(4):e15 Irizarry, RA, Hobbs, B, Collin, F, Beazer-Barclay, YD, Antonellis, KJ, Scherf, U, Speed, TP (2002) Exploration, Normalization, and Summaries of High Density Oligonucleotide Array Probe Level Data. Accepted for publication in Biostatistics. [Abstract, PDF, PS, Complementary Color Figures-PDF, Software] What do I need? You will need the appropriate CDF and CEL files for your dataset. For Exon and WT Gene arrays, the PGF and CLF should be used instead of the CDF file to build a CDFRME file. The process for doing this is explained in the user manual. Some pre-built CDFRME files are also available. CDFRME files HuEx_CDFRME.zip (95.9MB) HuGene_CDFRME.zip (5.5MB) MoEx_CDFRME.zip (79.6MB) MoGene_CDFRME.zip (6.3MB) RaEx_CDFRME.zip (48.4MB) RaGene_CDFRME.zip (5.7MB) Can I use affy/BioConductor instead? Of course. Hypothetically you will get the same results from both places, provided you have consistent settings in affy/BioConductor and RMAExpress. Some people prefer the power and flexibility of R and others like the point and click simplicity of a GUI. RMAExpress caters to the second option. Since RMAExpress outputs the computed expression values to a text file, you may of course load the expression measures into R and use features of Bioconductor for the analysis of your gene expression values. You can of course open the results file in any other application that supports importing plain text files. Will I get the same results as I would using affy/Bioconductor? Yes. The results from RMAExpress should be consistent. What are the machine requirements? A good rule of thumb is the more RAM you have the better. I would recommend at least 1GB, though 512MB will work in most situations. At this point the program has been tested using Windows 2000, Windows XP, Windows Vista and Linux. Most recently I have had a report of over 10,000 arrays processed in a single session. Can I do any quality assessment? Yes, store the residuals when you compute the expression values. Then you may examine chip pseudo-images of the residuals. Note that high positive residuals are colored increasingly read and low negative residuals are colored increasingly blue. To better interpret these images and gain a better feel for what is typical you may visit the PLM Image Gallery where images for a number of different datasets are shown. Access to the NUSE and RLE quality assessment metrics is also provided. How do I download and install it? Click here for the current release Windows version. Use the installer to install the program. The current release version number is 1.0 (released June 29, 2008). A pre-built linux version is not currently available, but you may build it using the source code. You can download pre-release versions from the following table (the release versions will be more stable, the development versions may have features that are incomplete or will be removed or altered before the next release was supported by the PGA U01 HL66583.
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 mentionsThis unknown targets
View all literature mentionsOpen source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
View all literature mentionsThis unknown targets Raised against a peptide mapping near the C-terminus of c-Myc of human origin.
View all literature mentionsThis unknown targets
View all literature mentionsThis unknown targets
View all literature mentionsThis unknown targets Raised against a peptide mapping near the C-terminus of c-Myc of human origin.
View all literature mentionsOpen source Java based image processing software program designed for scientific multidimensional images. ImageJ has been transformed to ImageJ2 application to improve data engine to be sufficient to analyze modern datasets.
View all literature mentions