of biological circuits
Cells are constantly "making decisions" - monitoring their environment, modulating their metabolism and 'deciding' whether to divide, differentiate or die. For this, they use biochemical circuits composed of interacting genes and proteins. Advances over the past decades have mapped many of these circuits. Still, can we infer the underlying logic from the detailed circuit structure? Can we deduce the selection forces that shaped these circuits during evolution? What are the principles that govern the design and function of these circuits and how similar or different are they from principles that guide the design of man-made machines? The interplay between variability and robustness is a hallmark of biological computation: Biological systems are inherently noisy, yet control their behavior precisely. Research projects in our lab quantify biological variability and identify its genetic origins, examine how variability is buffered by molecular circuits and investigate whether variability can in fact be employed to improve cellular computation. We encourage a multi-disciplinary approach, combining wet-lab experiments, dynamic-system theory and computational data analysis. This is achieved through fruitful interactions between students with backgrounds in physics, biology, computer science, mathematics and chemistry.
Naama Barkai Lab
Department of Molecular Genetics
Weizmann Institute of Science
Accumulation of cis- and trans-regulatory variations is associated with phenotypic divergence of a complex trait between yeast species
Offir Lupo, Gat Krieger, Felix Jonas, Naama Barkai
Gene regulatory variations accumulate during evolution and alter gene expression. While the importance of expression variation in phenotypic evolution is well established, the molecular basis remains largely unknown. Here, we examine two closely related yeast species, Saccharomyces cerevisiae and Saccharomyces paradoxus, which show phenotypical differences in morphology and cell cycle progression when grown in the same environment. By profiling the cell cycle transcriptome and binding of key transcription factors (TFs) in the two species and their hybrid, we show that changes in expression levels and dynamics of oscillating genes are dominated by upstream trans-variations. We find that multiple cell cycle regulators show both cis- and trans-regulatory variations, which alters their expression in favor of the different cell cycle phenotypes. Moreover, we show that variations in the cell cycle TFs, Fkh1, and Fkh2 affect both the expression of target genes, and the binding specificity of an interacting TF, Ace2. Our study reveals how multiple variations accumulate and propagate through the gene regulatory network, alter TFs binding, contributing to phenotypic changes in cell cycle progression.