Comprehensive Identification of Cell Cycle–regulated Genes of the Yeast Saccharomyces cerevisiae by Microarray Hybridization
Paul T. Spellman,Gavin Sherlock,Gavin Sherlock,Michael Q. Zhang,Vishwanath R. Iyer,Kirk R. Anders,Michael B. Eisen,Patrick O. Brown,Patrick O. Brown,David Botstein,Bruce Futcher +10 more
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TLDR
A comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle is created, and it is found that the mRNA levels of more than half of these 800 genes respond to one or both of these cyclins.Abstract:
We sought to create a comprehensive catalog of yeast genes whose transcript levels vary periodically within the cell cycle. To this end, we used DNA microarrays and samples from yeast cultures sync...read more
Citations
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Discovering local structure in gene expression data: the order-preserving submatrix problem.
TL;DR: A probabilistic model in which an OPSM is hidden within an otherwise random matrix is defined, and an efficient algorithm is developed for finding the hidden OPSM in the random matrix.
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Human-mouse genome comparisons to locate regulatory sites.
TL;DR: This work found that 98% of experimentally defined sequence-specific binding sites of skeletal-muscle-specific transcription factors are confined to the 19% of human sequences that are most conserved in the orthologous rodent sequences, and found that in using this restriction, the binding specificities of all three major muscle- specific transcription factors can be computationally identified.
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Widespread aneuploidy revealed by DNA microarray expression profiling.
Timothy P. Hughes,Christopher J. Roberts,Hongyue Dai,Allan R. Jones,Michael R. Meyer,David J. Slade,Julja Burchard,Sally Dow,Teresa R. Ward,Matthew J. Kidd,Stephen H. Friend,Matthew J. Marton +11 more
TL;DR: The general usefulness of expression profiles for nearly 300 Saccharomyces cerevisiae deletion mutants, obtained recently, is demonstrated, with implications for interpreting whole-genome expression data, particularly from cells known to suffer genomic instability, such as malignant or immortalized cells.
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New Components of a System for Phosphate Accumulation and Polyphosphate Metabolism in Saccharomyces cerevisiae Revealed by Genomic Expression Analysis
TL;DR: The phenotype of the phm5 mutant suggests that PHM5 (YDR452w) is essential for normal catabolism of polyP in the yeast vacuole, and the results reveal important new features of a genetic system that plays a critical role in P(i) acquisition and polyP metabolism in yeast.
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The use and analysis of microarray data
TL;DR: The different ways to analyse large sets of microarray data are reviewed, including the questions that can be asked and the challenges in interpreting the measurements.
References
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Cluster analysis and display of genome-wide expression patterns
TL;DR: A system of cluster analysis for genome-wide expression data from DNA microarray hybridization is described that uses standard statistical algorithms to arrange genes according to similarity in pattern of gene expression, finding in the budding yeast Saccharomyces cerevisiae that clustering gene expression data groups together efficiently genes of known similar function.
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TL;DR: Unlike other quantitative PCR methods, real-time PCR does not require post-PCR sample handling, preventing potential PCR product carry-over contamination and resulting in much faster and higher throughput assays.
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TL;DR: DNA microarrays containing virtually every gene of Saccharomyces cerevisiae were used to carry out a comprehensive investigation of the temporal program of gene expression accompanying the metabolic shift from fermentation to respiration, and the expression patterns of many previously uncharacterized genes provided clues to their possible functions.
Book ChapterDOI
Getting started with yeast.
TL;DR: The yeast Saccharomyces cerevisiae is now recognized as a model system representing a simple eukaryote whose genome can be easily manipulated and made particularly accessible to gene cloning and genetic engineering techniques.
Journal ArticleDOI
A Genome-Wide Transcriptional Analysis of the Mitotic Cell Cycle
Raymond J. Cho,Michael J. Campbell,Elizabeth A. Winzeler,Lars M. Steinmetz,Andrew R. Conway,Lisa Wodicka,Tyra G. Wolfsberg,Andrei Gabrielian,David Landsman,David J. Lockhart,Ronald W. Davis +10 more
TL;DR: The genome-wide characterization of mRNA transcript levels during the cell cycle of the budding yeast S. cerevisiae indicates a mechanism for local chromosomal organization in global mRNA regulation and links a range of human genes to cell cycle period-specific biological functions.