Reporter-Based Synthetic Genetic Array Analysis: A Functional Genomics Approach for Investigating Transcript or Protein Abundance Using Fluorescent Proteins in Saccharomyces cerevisiae

2017 ◽  
pp. 613-629 ◽  
Author(s):  
Hendrikje Göttert ◽  
Mojca Mattiazzi Usaj ◽  
Adam P. Rosebrock ◽  
Brenda J. Andrews
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Functional Genomics ◽  
Fluorescent Proteins ◽  
Protein Abundance ◽  
Synthetic Genetic Array ◽  
Array Analysis

scholarly journals Synthetic Genetic Array Analysis in Saccharomyces cerevisiae Provides Evidence for an Interaction Between RAT8/DBP5 and Genes Encoding P-Body Components

Genetics ◽  
2008 ◽  
Vol 179 (4) ◽  
pp. 1945-1955 ◽  
Author(s):  
John J. Scarcelli ◽  
Susan Viggiano ◽  
Christine A. Hodge ◽  
Catherine V. Heath ◽  
David C. Amberg ◽  
...  
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Synthetic Genetic Array ◽  
Array Analysis ◽  
Genes Encoding ◽  
Body Components

Functional Genomics Using the Saccharomyces cerevisiae Yeast Deletion Collections

2016 ◽  
Vol 2016 (9) ◽  
pp. pdb.top080945
Author(s):  
Corey Nislow ◽  
Lai Hong Wong ◽  
Amy Huei-Yi Lee ◽  
Guri Giaever
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Functional Genomics ◽  
Yeast Deletion

scholarly journals FRET Microscopy in Yeast

Biosensors ◽  
2019 ◽  
Vol 9 (4) ◽  
pp. 122 ◽  
Author(s):  
Skruzny ◽  
Pohl ◽  
Abella
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Fluorescent Proteins ◽  
Resonance Energy Transfer ◽  
Resonance Energy ◽  
Living Cells ◽  
Bioactive Molecules ◽  
Biophysical Processes ◽  
Microscopy Method ◽  
Fret Biosensors

Förster resonance energy transfer (FRET) microscopy is a powerful fluorescence microscopy method to study the nanoscale organization of multiprotein assemblies in vivo. Moreover, many biochemical and biophysical processes can be followed by employing sophisticated FRET biosensors directly in living cells. Here, we summarize existing FRET experiments and biosensors applied in yeasts Saccharomyces cerevisiae and Schizosaccharomyces pombe, two important models of fundamental biomedical research and efficient platforms for analyses of bioactive molecules. We aim to provide a practical guide on suitable FRET techniques, fluorescent proteins, and experimental setups available for successful FRET experiments in yeasts.

scholarly journals Unification of Protein Abundance Datasets Yields a Quantitative Saccharomyces cerevisiae Proteome

Cell Systems ◽  
2018 ◽  
Vol 6 (2) ◽  
pp. 192-205.e3 ◽  
Author(s):  
Brandon Ho ◽  
Anastasia Baryshnikova ◽  
Grant W. Brown
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Protein Abundance

scholarly journals Genetically encoded fluorescent tags

2017 ◽  
Vol 28 (7) ◽  
pp. 848-857 ◽  
Author(s):  
Kurt Thorn
Keyword(s):  
Flow Cytometry ◽  
Nucleic Acid ◽  
Light Microscopy ◽  
Cell Biology ◽  
Fluorescent Proteins ◽  
Protein Sequences ◽  
Biological Properties ◽  
Protein Abundance ◽  
Fluorescent Tags ◽  
Exogenous Fluorophores

Genetically encoded fluorescent tags are protein sequences that can be fused to a protein of interest to render it fluorescent. These tags have revolutionized cell biology by allowing nearly any protein to be imaged by light microscopy at submicrometer spatial resolution and subsecond time resolution in a live cell or organism. They can also be used to measure protein abundance in thousands to millions of cells using flow cytometry. Here I provide an introduction to the different genetic tags available, including both intrinsically fluorescent proteins and proteins that derive their fluorescence from binding of either endogenous or exogenous fluorophores. I discuss their optical and biological properties and guidelines for choosing appropriate tags for an experiment. Tools for tagging nucleic acid sequences and reporter molecules that detect the presence of different biomolecules are also briefly discussed.

scholarly journals Saccharomyces cerevisiae G1 cyclins differ in their intrinsic functional specificities.

1996 ◽  
Vol 16 (12) ◽  
pp. 6794-6803 ◽  
Author(s):  
K Levine ◽  
K Huang ◽  
F R Cross
Keyword(s):  
Saccharomyces Cerevisiae ◽  
Cell Cycle ◽  
Substrate Specificity ◽  
Gene Dosage ◽  
Quantitative Model ◽  
Protein Abundance ◽  
Triple Mutant ◽  
Functional Assays ◽  
Functional Differences

The three budding yeast CLN genes appear to be functionally redundant for cell cycle Start: any single CLN gene is sufficient to promote Start, while the cln1 cln2 cln3 triple mutant is Start defective and inviable. Both quantitative and apparently qualitative differences between CLN genes have been reported, but available data do not in general allow distinction between qualitative functional differences as opposed to simply quantitative differences in expression or function. To determine if there are intrinsic qualitative differences between Cln proteins, we compared CLN2, CLN3, and crippled (but still partially active) CLN2 genes in a range of assays that differentiate genetically between CLN2 and CLN3. The results suggest that different potencies of Cln2, Cln3, and Cln2 mutants in functional assays cannot be accounted for by a simple quantitative model for their action, since Cln3 is at least as active as Cln2 and much more active than the Cln2 mutants in driving Swi4/Swi6 cell cycle box (SCB)-regulated transcription and cell cycle initiation in cln1 cln2 cln3 bck2 strains, but Cln3 has little or no activity in other assays in which Cln2 and the Cln2 mutants function. Differences in Cln protein abundance are unlikely to account for these results. Cln3-associated kinase is therefore likely to have an intrinsic in vivo substrate specificity distinct from that of Cln2-associated kinase, despite their functional redundancy. Consistent with the idea that Cln3 may be the primary transcriptional activator of CLN1, CLN2, and other genes, the activation of CLN2 transcription was found to be sensitive to the gene dosage of CLN3 but not to the gene dosage of CLN2.

Synthetic Genetic Array Analysis

2016 ◽  
Vol 2016 (4) ◽  
pp. pdb.prot088807 ◽  
Author(s):  
Elena Kuzmin ◽  
Michael Costanzo ◽  
Brenda Andrews ◽  
Charles Boone
Keyword(s):  
Synthetic Genetic Array ◽  
Array Analysis
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