Evolution of transcriptional regulatory networks in yeast populations.
Saccharomyces cerevisiae is the most thoroughly studied eukaryote at the cellular, molecular, and genetic level. Recent boost in whole-genome sequencing, array-based allelic variation mapping, and genome-wide transcriptional profiling have unprecedentedly advanced knowledge on cell biology and evolution of this organism. It is now possible to investigate how evolution shapes the functional architecture of yeast genomes and how this architecture relates to the evolution of the regulatory networks controlling the expression of genes that make up an organism. A survey of the information on genetic and whole-genome expression variations in yeast populations shows that a significant score of gene expression variation is dependent on genotype-by-environment interaction. In some cases, large trans effects are the result of mutations in the promoters of key master regulator genes. Yet trans-variation in environmental sensor proteins appears to explain the majority of the expression patterns differentiating strains in natural populations. The challenge is now to use this information to model how individual genetic polymorphisms interact in a condition-dependent fashion to produce phenotypic change. In this study, we show how fruitful application of systems biology to the progress of science and medicine requires the use of evolution as a lens to reconstruct the hierarchical structure of regulation of biological systems. The lessons learned in yeast can be of paramount importance in advancing the application of genomics and systems biology to emerging fields including personalized medicine.
Cavalieri
Duccio
D
Department of Pharmacology, University of Florence, Florence, Italy.
D019143:Evolution, Molecular; D005786:Gene Expression Regulation / Q000502:physiology*; D055442:Metabolome / Q000502:physiology*; D008954:Models, Biological; D010641:Phenotype; D020543:Proteome / Q000378:metabolism*; D012441:Saccharomyces cerevisiae / Q000502:physiology*; D015398:Signal Transduction / Q000502:physiology*; D015533:Transcriptional Activation / Q000502:physiology*
D020543:Proteome