2016
DOI: 10.1038/ncb3300
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A combined binary interaction and phenotypic map of C. elegans cell polarity proteins

Abstract: The establishment of cell polarity is an essential process for the development of multicellular organisms and the functioning of cells and tissues. Here, we combine large-scale protein interaction mapping with systematic phenotypic profiling to study the network of physical interactions that underlies polarity establishment and maintenance in the nematode Caenorhabditis elegans. Using a fragment-based yeast two-hybrid strategy, we identified 439 interactions between 296 proteins, as well as the protein regions… Show more

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Cited by 32 publications
(25 citation statements)
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References 60 publications
(74 reference statements)
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“…Sequences encoding the PAR-6 PDZ domain and full-length NOCA-1d were PCR amplified from a mixedstage cDNA library using primers par-6_F: 5'-ggaggcgcgccATGATTGTGCCAGAAGCTCATCG, par-6_R: 5'-ggagcggccgcTCAGGCGTTCGGTGTTCCTTGTT, noca-1d_F: 5'-ggaggcgcgccATGAATATTTGTTGTTGTGG and noca-1d_R: 5'-ggagcggccgcCTATTGAACTCTGCATACAT. PCR products were digested with AscI and NotI, and cloned into Gal4-DB vector pMB28 and Gal4-AD vector pMB29, respectively (Koorman et al, 2016). The resulting plasmids were transformed into Saccharomyces cerevisiae strains Y8930 (MATα) and Y8800 (MATa) (Yu et al, 2008) using the Te/ LiAc transformation method (Schiestl and Gietz, 1989).…”
Section: Yeast Two-hybrid Analysismentioning
confidence: 99%
“…Sequences encoding the PAR-6 PDZ domain and full-length NOCA-1d were PCR amplified from a mixedstage cDNA library using primers par-6_F: 5'-ggaggcgcgccATGATTGTGCCAGAAGCTCATCG, par-6_R: 5'-ggagcggccgcTCAGGCGTTCGGTGTTCCTTGTT, noca-1d_F: 5'-ggaggcgcgccATGAATATTTGTTGTTGTGG and noca-1d_R: 5'-ggagcggccgcCTATTGAACTCTGCATACAT. PCR products were digested with AscI and NotI, and cloned into Gal4-DB vector pMB28 and Gal4-AD vector pMB29, respectively (Koorman et al, 2016). The resulting plasmids were transformed into Saccharomyces cerevisiae strains Y8930 (MATα) and Y8800 (MATa) (Yu et al, 2008) using the Te/ LiAc transformation method (Schiestl and Gietz, 1989).…”
Section: Yeast Two-hybrid Analysismentioning
confidence: 99%
“…The relative ease with which phenotypic screens can be performed in C. elegans by RNAi continues to make integration of interactomic and phenotypic data attractive. We recently combined Y2H-based interactome mapping with phenotypic profiling to generate an integrated network of C. elegans cell polarity proteins [23] . We identified 100 physically interacting protein pairs for which RNAi-mediated depletion caused a defect in the same polarity-related process [23] .…”
Section: Binary Interactome Mapping – C Elegans Amentioning
confidence: 99%
“…We recently combined Y2H-based interactome mapping with phenotypic profiling to generate an integrated network of C. elegans cell polarity proteins [23] . We identified 100 physically interacting protein pairs for which RNAi-mediated depletion caused a defect in the same polarity-related process [23] . Moreover, by using a fragment-based approach we were able to delineate the regions that mediate the identified interactions, and used this information to demonstrate that an interaction between PAR-6 and PAC-1 is essential for the establishment of radial polarity [23] .…”
Section: Binary Interactome Mapping – C Elegans Amentioning
confidence: 99%
“…A “complete” understanding of gene regulation during development would include determining the dependencies of gene expression on TFs and cis‐ regulatory sequences, chromatin state, protein–protein interactions, DNA replication timing, and other genomic features. Significant existing resources exist from in vitro and whole‐organism studies (e.g., Araya et al, ; Boyle et al, ; Fuxman Bass et al, ; Koorman et al, ; Li et al, ; Narasimhan et al, ; Niu et al, ; Pourkarimi, Bellush, & Whitehouse, ; Rodriguez‐Martinez et al, ; Zisoulis et al, ), but new methods will be needed to drive them to single cell resolution across the organism. Models of gene regulation can take more mechanism forms, such as thermodynamic models (Sherman & Cohen, ), can be based on computational machine learning approaches (Fowlkes et al, ), or take more abstract forms such as “network” models (e.g., Gunsalus et al, ; I. Lee et al, ; I. Lee et al, ).…”
Section: A Framework For Developmental Systems Biologymentioning
confidence: 99%