Cyclebase 3.0: a multi-organism database on cell-cycle regulation and phenotypes.
TLDR
In Cyclebase version 3.0, the content of the database is updated to reflect changes to genome annotation, added new mRNA and protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases.Abstract:
The eukaryotic cell division cycle is a highly regulated process that consists of a complex series of events and involves thousands of proteins. Researchers have studied the regulation of the cell cycle in several organisms, employing a wide range of high-throughput technologies, such as microarray-based mRNA expression profiling and quantitative proteomics. Due to its complexity, the cell cycle can also fail or otherwise change in many different ways if important genes are knocked out, which has been studied in several microscopy-based knockdown screens. The data from these many large-scale efforts are not easily accessed, analyzed and combined due to their inherent heterogeneity. To address this, we have created Cyclebase—available at http://www.cyclebase.org—an online database that allows users to easily visualize and download results from genome-wide cell-cycle-related experiments. In Cyclebase version 3.0, we have updated the content of the database to reflect changes to genome annotation, added new mRNA and protein expression data, and integrated cell-cycle phenotype information from high-content screens and model-organism databases. The new version of Cyclebase also features a new web interface, designed around an overview figure that summarizes all the cell-cycle-related data for a gene.read more
Citations
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Human haematopoietic stem cell lineage commitment is a continuous process
Lars Velten,Simon Haas,Simon Raffel,Simon Raffel,Sandra Blaszkiewicz,Saiful Islam,Bianca P. Hennig,Christoph Hirche,Christoph Lutz,Eike C. Buss,Daniel Nowak,Tobias Boch,Wolf-Karsten Hofmann,Anthony D. Ho,Wolfgang Huber,Andreas Trumpp,Marieke A.G. Essers,Lars M. Steinmetz,Lars M. Steinmetz +18 more
TL;DR: Flow cytometric, transcriptomic and functional data at single-cell resolution are integrated to quantitatively map early differentiation of human HSCs towards lineage commitment and provide a basis for the understanding of haematopoietic malignancies.
Journal ArticleDOI
Computational assignment of cell-cycle stage from single-cell transcriptome data.
Antonio Scialdone,Kedar Nath Natarajan,Luis R. Saraiva,Valentina Proserpio,Sarah A. Teichmann,Oliver Stegle,John C. Marioni,Florian Buettner +7 more
TL;DR: Five established supervised machine learning methods and a custom-built predictor for allocating cells to their cell-cycle stage on the basis of their transcriptome are described and compared and it is found that a PCA-based approach and the custom predictor performed best.
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CancerSEA: a cancer single-cell state atlas.
Huating Yuan,Min Yan,Guanxiong Zhang,Wei Liu,Chunyu Deng,Gaoming Liao,Liwen Xu,Tao Luo,Haoteng Yan,Zhilin Long,Aiai Shi,Tingting Zhao,Yun Xiao,Xia Li +13 more
TL;DR: CancerSEA is the first dedicated database that aims to comprehensively explore distinct functional states of cancer cells at the single-cell level, and provides functional state-associated PCG/lncRNA repertoires across all cancers, in specific cancers, and in individual cancer single- cell datasets.
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SCnorm: robust normalization of single-cell RNA-seq data
Rhonda Bacher,Li-Fang Chu,Ning Leng,Audrey P. Gasch,James A. Thomson,Ron Stewart,Michael A. Newton,Christina Kendziorski +7 more
TL;DR: SCnorm is introduced for accurate and efficient normalization of single-cell RNA-seq data and addresses the problem of artifacts that bias downstream analyses.
Journal ArticleDOI
Population snapshots predict early haematopoietic and erythroid hierarchies
Betsabeh Khoramian Tusi,Samuel L. Wolock,Caleb Weinreb,Yung Hwang,Daniel Hidalgo,Rapolas Zilionis,Ari Waisman,Jun R. Huh,Allon M. Klein,Merav Socolovsky +9 more
TL;DR: It is found that the cell cycle is progressively remodelled during erythroid development and during a sharp transcriptional switch that ends the colony-forming progenitor stage and activates terminal differentiation, and provides insights into lineage development in vivo.
References
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Journal ArticleDOI
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
TL;DR: 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.
Journal ArticleDOI
Functional profiling of the Saccharomyces cerevisiae genome.
Guri Giaever,Angela M. Chu,Li Ni,Carla Connelly,Linda Riles,Steeve Veronneau,Sally Dow,Ankuta Lucau-Danila,Keith Anderson,Bruno André,Adam P. Arkin,Anna Astromoff,Mohamed El Bakkoury,Rhonda Bangham,Rocío Benito,Sophie Brachat,Stefano Campanaro,Matt Curtiss,Karen Davis,Adam M. Deutschbauer,K. D. Entian,Patrick Flaherty,Françoise Foury,David J. Garfinkel,Mark Gerstein,Deanna Gotte,Ulrich Güldener,Johannes H. Hegemann,Svenja Hempel,Zelek S. Herman,Daniel F. Jaramillo,Diane E. Kelly,Steven L. Kelly,Peter Kötter,Darlene LaBonte,David C. Lamb,Ning Lan,Hong Liang,Hong Liao,Lucy Y. Liu,Chuanyun Luo,Marc Lussier,Rong Mao,Patrice Menard,Siew Loon Ooi,José L. Revuelta,Christopher J. Roberts,Matthias Rose,Petra Ross-Macdonald,Bart Scherens,Greg Schimmack,Brenda Shafer,Daniel D. Shoemaker,Sharon Sookhai-Mahadeo,Reginald Storms,Jeffrey N. Strathern,Giorgio Valle,Marleen Voet,Guido Volckaert,Ching Yun Wang,Teresa R. Ward,Julie Wilhelmy,Elizabeth A. Winzeler,Yonghong Yang,Grace Yen,Elaine M. Youngman,Kexin Yu,Howard Bussey,Jef D. Boeke,Michael Snyder,Peter Philippsen,Ronald W. Davis,Mark Johnston +72 more
TL;DR: It is shown that previously known and new genes are necessary for optimal growth under six well-studied conditions: high salt, sorbitol, galactose, pH 8, minimal medium and nystatin treatment, and less than 7% of genes that exhibit a significant increase in messenger RNA expression are also required for optimal Growth in four of the tested conditions.
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.
Journal ArticleDOI
Identification of Genes Periodically Expressed in the Human Cell Cycle and Their Expression in Tumors
Michael L. Whitfield,Gavin Sherlock,Alok J. Saldanha,John I. Murray,Catherine A. Ball,Karen E. Alexander,John C. Matese,Charles M. Perou,Myra M. Hurt,Patrick O. Brown,David Botstein +10 more
TL;DR: The genome-wide program of gene expression during the cell division cycle in a human cancer cell line (HeLa) was characterized using cDNA microarrays to provide a comprehensive catalog of cell cycle regulated genes that can serve as a starting point for functional discovery.
Journal ArticleDOI
Quantitative Phosphoproteomics Reveals Widespread Full Phosphorylation Site Occupancy During Mitosis
Jesper V. Olsen,Michiel Vermeulen,Anna Santamaria,Chanchal Kumar,Martin L. Miller,Martin L. Miller,Lars Juhl Jensen,Florian Gnad,Jürgen Cox,Thomas Skøt Jensen,Erich A. Nigg,Søren Brunak,Søren Brunak,Matthias Mann +13 more
TL;DR: High-resolution mass spectrometry–based proteomics was applied to investigate the proteome and phosphoproteome of the human cell cycle on a global scale and quantified 6027 proteins and 20,443 unique phosphorylation sites and their dynamics, finding that nuclear proteins and proteins involved in regulating metabolic processes have high phosphorylated site occupancy in mitosis, suggesting that these proteins may be inactivated by phosphorylate in mitotic cells.
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