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Open Access Highly Accessed Research article

Comparative gene expression between two yeast species

Yuanfang Guan123, Maitreya J Dunham14*, Olga G Troyanskaya15* and Amy A Caudy16*

Author affiliations

1 Lewis-Sigler Institute for Integrative Genomics, Princeton University, Princeton, NJ 08544, USA

2 Department of Molecular Biology, Princeton University, Princeton, NJ 08544, USA

3 Current Address: Department of Computational Medicine & Bioinformatics, University of Michigan, Ann Arbor, MI 48109, USA

4 Department of Genome Sciences, University of Washington, Seattle, WA 98195, USA

5 Department of Computer Science, Princeton University, Princeton, NJ 08540, USA

6 Donnelly Centre for Cellular and Biomolecular Research, University of Toronto, Toronto, Ontario M5S 3E1, Canada

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Citation and License

BMC Genomics 2013, 14:33  doi:10.1186/1471-2164-14-33

Published: 16 January 2013

Abstract

Background

Comparative genomics brings insight into sequence evolution, but even more may be learned by coupling sequence analyses with experimental tests of gene function and regulation. However, the reliability of such comparisons is often limited by biased sampling of expression conditions and incomplete knowledge of gene functions across species. To address these challenges, we previously systematically generated expression profiles in Saccharomyces bayanus to maximize functional coverage as compared to an existing Saccharomyces cerevisiae data repository.

Results

In this paper, we take advantage of these two data repositories to compare patterns of ortholog expression in a wide variety of conditions. First, we developed a scalable metric for expression divergence that enabled us to detect a significant correlation between sequence and expression conservation on the global level, which previous smaller-scale expression studies failed to detect. Despite this global conservation trend, between-species gene expression neighborhoods were less well-conserved than within-species comparisons across different environmental perturbations, and approximately 4% of orthologs exhibited a significant change in co-expression partners. Furthermore, our analysis of matched perturbations collected in both species (such as diauxic shift and cell cycle synchrony) demonstrated that approximately a quarter of orthologs exhibit condition-specific expression pattern differences.

Conclusions

Taken together, these analyses provide a global view of gene expression patterns between two species, both in terms of the conditions and timing of a gene's expression as well as co-expression partners. Our results provide testable hypotheses that will direct future experiments to determine how these changes may be specified in the genome.

Keywords:
Expression divergence; Yeast; Microarray; Data integration; Condition-specific gene expression