Guan Lab

Department of Computational Medicine & Bioinformatics
Wed, 11/06/2013 - 10:15 -- gl_admin
TitleComparative gene expression between two yeast species.
Publication TypeJournal Article
Year of Publication2013
AuthorsGuan Y, Dunham MJ, Troyanskaya OG, Caudy AA
JournalBMC Genomics
Volume14
Pagination33
Date Published2013
ISSN1471-2164
KeywordsEvolution, Molecular, Gene Expression Profiling, Gene Expression Regulation, Fungal, Genetic Variation, Saccharomyces cerevisiae, Species Specificity, Statistics as Topic
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.

DOI10.1186/1471-2164-14-33
Alternate JournalBMC Genomics
PubMed ID23324262
PubMed Central IDPMC3556494
Grant List5P41RR011823-17 / RR / NCRR NIH HHS / United States
8 P41 GM103533-17 / GM / NIGMS NIH HHS / United States
P41 GM103533 / GM / NIGMS NIH HHS / United States
P50 GM071508 / GM / NIGMS NIH HHS / United States
R01 GM071966 / GM / NIGMS NIH HHS / United States
R01HG005998 / HG / NHGRI NIH HHS / United States
/ / Canadian Institutes of Health Research / Canada