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
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Meiotic Prophase Requires Proteolysis of M Phase Regulators Mediated by the Meiosis-Specific APC/CAma1
Elwy Okaz,Orlando Argüello-Miranda,Aliona Bogdanova,P. K. Vinod,Jesse J. Lipp,Zuzana Markova,Ievgeniia Zagoriy,Bela Novak,Wolfgang Zachariae +8 more
TL;DR: It is shown that an extended prophase I additionally requires the suppression of latent, mitotic cell-cycle controls by the anaphase-promoting complex (APC/C) and its meiosis-specific activator Ama1, which trigger the degradation of M phase regulators and Ndd1, a subunit of a mitotic transcription factor.
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Knowledge discovery in gene-expression-microarray data: mining the information output of the genome
TL;DR: Large-scale RNA assays and gene- expression-microarray studies represent the second wave of the genomics revolution, providing gene-expression data that complement gene-sequence data and help the understanding of the molecular basis of health and disease.
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How much expression divergence after yeast gene duplication could be explained by regulatory motif evolution
Zhongqi Zhang,Jianying Gu,Xun Gu +2 more
TL;DR: The results suggest that duplicate genes tend to be co-expressed but the correlation between motif content and expression similarity is generally poor, only approximately 2-3% of expression variation can be explained by the motif divergence.
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Integrative analysis of genome-scale data by using pseudoinverse projection predicts novel correlation between DNA replication and RNA transcription
Orly Alter,Gene H. Golub +1 more
TL;DR: An integrative data-driven mathematical framework that formulates any number of genome-scale molecular biological data sets in terms of one chosen set of data samples, or of profiles extracted mathematically from data samples), designated the "basis" set is described.
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A high-resolution transcriptome map of cell cycle reveals novel connections between periodic genes and cancer.
Daniel Dominguez,Yi-Hsuan Tsai,Nicholas C. Gomez,Deepak Kumar Jha,Ian J. Davis,Zefeng Wang,Zefeng Wang +6 more
TL;DR: This study defines a core set of 67 genes with robust periodic expression in multiple cell types and suggests new chromatin-associated mechanisms for periodic gene regulation and offers a predictor of cancer patient outcomes.
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: 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.
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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.