Email updates

Keep up to date with the latest news and content from BMC Genomics and BioMed Central.

Open Access Highly Accessed Research article

Global regulatory architecture of human, mouse and rat tissue transcriptomes

Ajay Prasad1, Suchitra Suresh Kumar1, Christophe Dessimoz345, Stefan Bleuler2, Oliver Laule2, Tomas Hruz24, Wilhelm Gruissem1 and Philip Zimmermann12*

  • * Corresponding author: Philip Zimmermann phz@nebion.com

  • † Equal contributors

Author Affiliations

1 Department of Biology, ETH Zurich, 8092 Zurich, Switzerland

2 Nebion AG, Hohlstrasse 515, 8048 Zurich, Switzerland

3 Swiss Institute of Bioinformatics, Universitätstr. 6, 8092 Zurich, Switzerland

4 Department of Computer Science, ETH Zurich, 8092 Zurich, Switzerland

5 University College London, Gower Street, London, WC1E 6BT, UK

For all author emails, please log on.

BMC Genomics 2013, 14:716  doi:10.1186/1471-2164-14-716

Published: 20 October 2013

Abstract

Background

Predicting molecular responses in human by extrapolating results from model organisms requires a precise understanding of the architecture and regulation of biological mechanisms across species.

Results

Here, we present a large-scale comparative analysis of organ and tissue transcriptomes involving the three mammalian species human, mouse and rat. To this end, we created a unique, highly standardized compendium of tissue expression. Representative tissue specific datasets were aggregated from more than 33,900 Affymetrix expression microarrays. For each organism, we created two expression datasets covering over 55 distinct tissue types with curated data from two independent microarray platforms. Principal component analysis (PCA) revealed that the tissue-specific architecture of transcriptomes is highly conserved between human, mouse and rat. Moreover, tissues with related biological function clustered tightly together, even if the underlying data originated from different labs and experimental settings. Overall, the expression variance caused by tissue type was approximately 10 times higher than the variance caused by perturbations or diseases, except for a subset of cancers and chemicals. Pairs of gene orthologs exhibited higher expression correlation between mouse and rat than with human. Finally, we show evidence that tissue expression profiles, if combined with sequence similarity, can improve the correct assignment of functionally related homologs across species.

Conclusion

The results demonstrate that tissue-specific regulation is the main determinant of transcriptome composition and is highly conserved across mammalian species.