Author
Listed:
- Rudolf S N Fehrmann
- Hendrik J M de Jonge
- Arja ter Elst
- André de Vries
- Anne G P Crijns
- Alida C Weidenaar
- Frans Gerbens
- Steven de Jong
- Ate G J van der Zee
- Elisabeth G E de Vries
- Willem A Kamps
- Robert M W Hofstra
- Gerard J te Meerman
- Eveline S J M de Bont
Abstract
It has been hypothesized that the net expression of a gene is determined by the combined effects of various transcriptional system regulators (TSRs). However, characterizing the complexity of regulation of the transcriptome is a major challenge. Principal component analysis on 17,550 heterogeneous human microarray experiments revealed that 50 orthogonal factors (hereafter called TSRs) are able to capture 64% of the variability in expression in a wide range of experimental conditions and tissues. We identified gene clusters controlled in the same direction and show that gene expression can be conceptualized as a process influenced by a fairly limited set of TSRs. Furthermore, TSRs can be linked to biological functions, as we demonstrate a strong relation between TSR-related gene clusters and biological functionality as well as cellular localization, i.e. gene products of similarly regulated genes by a specific TSR are located in identical parts of a cell. Using 3,934 diverse mouse microarray experiments we found striking similarities in transcriptional system regulation between human and mouse. Our results give biological insights into regulation of the cellular transcriptome and provide a tool to characterize expression profiles with highly reliable TSRs instead of thousands of individual genes, leading to a >500-fold reduction of complexity with just 50 TSRs. This might open new avenues for those performing gene expression profiling studies.
Suggested Citation
Rudolf S N Fehrmann & Hendrik J M de Jonge & Arja ter Elst & André de Vries & Anne G P Crijns & Alida C Weidenaar & Frans Gerbens & Steven de Jong & Ate G J van der Zee & Elisabeth G E de Vries & Will, 2008.
"A New Perspective on Transcriptional System Regulation (TSR): Towards TSR Profiling,"
PLOS ONE, Public Library of Science, vol. 3(2), pages 1-10, February.
Handle:
RePEc:plo:pone00:0001656
DOI: 10.1371/journal.pone.0001656
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