Browse views: by Year, by Function, by GLF, by Subfunction, by Conference, by Journal

Identification of novel mammalian growth regulatory factors by genome-scale quantitative image analysis.

Harada, Josephine and Bower, Kristen and Orth, Anthony and Callaway, Scott and Nelson, Christian and Laris, Casey and Hogenesch, John and Vogt, Peter and Chanda, Sumit (2005) Identification of novel mammalian growth regulatory factors by genome-scale quantitative image analysis. Genome Research, 15 (8). pp. 1136-1144. ISSN 1088-9051

Abstract

Functional profiling technologies using arrayed collections of genome-scale siRNA and cDNA arrayed libraries enable the comprehensive global analysis of gene function. However, the current repertoire of high-throughput detection methodologies has limited the scope of cellular phenotypes that can be studied. In this report, we describe the systematic identification of mammalian growth-regulatory factors achieved through the integration of automated microscopy, pattern recognition analysis, and cell-based functional genomics. The effects of 7364 human and mouse proteins, encoded by individually arrayed cDNAs, upon proliferation and viability in U2OS osteosarcoma cells were evaluated in a live-cell, kinetic assay using quantitative image analysis. Overexpression of more than 86 cDNAs (1.15%) conferred dramatic increases in the proliferation, as determined cell enumeration. These included several known growth regulators, as well as previously uncharacterized ones (LRRK1, Ankrd25). In addition, novel functional roles for two genes (5033414D02Rik, 2810429O05Rik), now termed Gatp1 and Gatp2, respectively, were identified. Further analysis demonstrated that these encoded proteins promoted cellular proliferation and transformation in primary cells. Conversely, cells depleted for Gatp1 underwent apoptosis upon serum reduction, suggesting that Gatp1 is essential for cell survival under growth-factor-restricted conditions. Taken together, our findings offer new insight into the regulation of cellular growth and proliferation, and demonstrate the value and feasibility of assessing cellular phenotypes through genome-level computational image analysis.

Item Type: Article
Related URLs:
Additional Information: free final full text version available at publisher's official URL and at PubMedCentral; archiving not formally supported by this publisher
Related URLs:
Date Deposited: 14 Dec 2009 14:02
Last Modified: 31 Jan 2013 01:22
URI: https://oak.novartis.com/id/eprint/249

Search

Email Alerts

Register with OAK to receive email alerts for saved searches.