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Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes


Neumann, B; Walter, T; Hériché, J K; Bulkescher, J; Erfle, H; Conrad, C; Rogers, P; Poser, I; Held, M; Liebel, U; Cetin, C; Sieckmann, F; Pau, G; Kabbe, R; Wünsche, A; Satagopam, V; Schmitz, M H A; Chapuis, C; Gerlich, D W; Schneider, R; Eils, R; Huber, W; Peters, J M; Hyman, A A; Durbin, R; Pepperkok, R; Ellenberg, J (2010). Phenotypic profiling of the human genome by time-lapse microscopy reveals cell division genes. Nature Medicine, 464(7289):721-727.

Abstract

Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.

Despite our rapidly growing knowledge about the human genome, we do not know all of the genes required for some of the most basic functions of life. To start to fill this gap we developed a high-throughput phenotypic screening platform combining potent gene silencing by RNA interference, time-lapse microscopy and computational image processing. We carried out a genome-wide phenotypic profiling of each of the approximately 21,000 human protein-coding genes by two-day live imaging of fluorescently labelled chromosomes. Phenotypes were scored quantitatively by computational image processing, which allowed us to identify hundreds of human genes involved in diverse biological functions including cell division, migration and survival. As part of the Mitocheck consortium, this study provides an in-depth analysis of cell division phenotypes and makes the entire high-content data set available as a resource to the community.

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Additional indexing

Item Type:Journal Article, refereed, original work
Communities & Collections:04 Faculty of Medicine > Institute for Regenerative Medicine (IREM)
Dewey Decimal Classification:610 Medicine & health
Language:English
Date:2010
Deposited On:17 Jan 2011 18:55
Last Modified:16 Aug 2016 10:13
Publisher:Nature Publishing Group
ISSN:1078-8956
Additional Information:Comment in: Nat Methods. 2010 Jun;7(6):421. - Nature. 2010 Apr 1;464(7289):684-5.
Publisher DOI:10.1038/nature08869
PubMed ID:20360735

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