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Genome Res DOI:10.1101/gr.146233.112

Arboretum: reconstruction and analysis of the evolutionary history of condition-specific transcriptional modules.

Publication TypeJournal Article
Year of Publication2013
AuthorsRoy, S, Wapinski, I, Pfiffner, J, French, C, Socha, A, Konieczka, J, Habib, N, Kellis, M, Thompson, D, Regev, A
JournalGenome Res
Date Published2013 Jun
KeywordsAlgorithms, Cluster Analysis, Computational Biology, Evolution, Molecular, Gene Duplication, Gene Expression Profiling, Gene Expression Regulation, Heat-Shock Response, Species Specificity, Stress, Physiological, Yeasts

Comparative functional genomics studies the evolution of biological processes by analyzing functional data, such as gene expression profiles, across species. A major challenge is to compare profiles collected in a complex phylogeny. Here, we present Arboretum, a novel scalable computational algorithm that integrates expression data from multiple species with species and gene phylogenies to infer modules of coexpressed genes in extant species and their evolutionary histories. We also develop new, generally applicable measures of conservation and divergence in gene regulatory modules to assess the impact of changes in gene content and expression on module evolution. We used Arboretum to study the evolution of the transcriptional response to heat shock in eight species of Ascomycota fungi and to reconstruct modules of the ancestral environmental stress response (ESR). We found substantial conservation in the stress response across species and in the reconstructed components of the ancestral ESR modules. The greatest divergence was in the most induced stress, primarily through module expansion. The divergence of the heat stress response exceeds that observed in the response to glucose depletion in the same species. Arboretum and its associated analyses provide a comprehensive framework to systematically study regulatory evolution of condition-specific responses.


Alternate JournalGenome Res.
PubMed ID23640720
PubMed Central IDPMC3668358
Grant ListDP1 CA174427 / CA / NCI NIH HHS / United States
R01 CA119176 / CA / NCI NIH HHS / United States
R01 2R01CA119176-01 / CA / NCI NIH HHS / United States