PLoS ONE (Sep 2009)

The FunGenES database: a genomics resource for mouse embryonic stem cell differentiation.

  • Herbert Schulz,
  • Raivo Kolde,
  • Priit Adler,
  • Irène Aksoy,
  • Konstantinos Anastassiadis,
  • Michael Bader,
  • Nathalie Billon,
  • Hélène Boeuf,
  • Pierre-Yves Bourillot,
  • Frank Buchholz,
  • Christian Dani,
  • Michael Xavier Doss,
  • Lesley Forrester,
  • Murielle Gitton,
  • Domingos Henrique,
  • Jürgen Hescheler,
  • Heinz Himmelbauer,
  • Norbert Hübner,
  • Efthimia Karantzali,
  • Androniki Kretsovali,
  • Sandra Lubitz,
  • Laurent Pradier,
  • Meena Rai,
  • Jüri Reimand,
  • Alexandra Rolletschek,
  • Agapios Sachinidis,
  • Pierre Savatier,
  • Francis Stewart,
  • Mike P Storm,
  • Marina Trouillas,
  • Jaak Vilo,
  • Melanie J Welham,
  • Johannes Winkler,
  • Anna M Wobus,
  • Antonis K Hatzopoulos,
  • Functional Genomics in Embryonic Stem Cells Consortium

DOI
https://doi.org/10.1371/journal.pone.0006804
Journal volume & issue
Vol. 4, no. 9
p. e6804

Abstract

Read online

Embryonic stem (ES) cells have high self-renewal capacity and the potential to differentiate into a large variety of cell types. To investigate gene networks operating in pluripotent ES cells and their derivatives, the "Functional Genomics in Embryonic Stem Cells" consortium (FunGenES) has analyzed the transcriptome of mouse ES cells in eleven diverse settings representing sixty-seven experimental conditions. To better illustrate gene expression profiles in mouse ES cells, we have organized the results in an interactive database with a number of features and tools. Specifically, we have generated clusters of transcripts that behave the same way under the entire spectrum of the sixty-seven experimental conditions; we have assembled genes in groups according to their time of expression during successive days of ES cell differentiation; we have included expression profiles of specific gene classes such as transcription regulatory factors and Expressed Sequence Tags; transcripts have been arranged in "Expression Waves" and juxtaposed to genes with opposite or complementary expression patterns; we have designed search engines to display the expression profile of any transcript during ES cell differentiation; gene expression data have been organized in animated graphs of KEGG signaling and metabolic pathways; and finally, we have incorporated advanced functional annotations for individual genes or gene clusters of interest and links to microarray and genomic resources. The FunGenES database provides a comprehensive resource for studies into the biology of ES cells.