Bachelor of Science, University of Texas Austin (2006)
Doctor of Philosophy, University of California San Francisco (2011)
Anne Brunet, Postdoctoral Faculty Sponsor
We examine how different transcriptional network structures can evolve from an ancestral network. By characterizing how the ancestral mode of gene regulation for genes specific to a-type cells in yeast species evolved from an activating paradigm to a repressing one, we show that regulatory protein modularity, conversion of one cis-regulatory sequence to another, distribution of binding energy among protein-protein and protein-DNA interactions, and exploitation of ancestral network features all contribute to the evolution of a novel regulatory mode. The formation of this derived mode of regulation did not disrupt the ancestral mode and thereby created a hybrid regulatory state where both means of transcription regulation (ancestral and derived) contribute to the conserved expression pattern of the network. Finally, we show how this hybrid regulatory state has resolved in different ways in different lineages to generate the diversity of regulatory network structures observed in modern species.
View details for DOI 10.1016/j.cell.2012.08.018
View details for Web of Science ID 000309544200012
View details for PubMedID 23021217
Changes in gene regulatory networks are a major source of evolutionary novelty. Here we describe a specific type of network rewiring event, one that intercalates a new level of transcriptional control into an ancient circuit. We deduce that, over evolutionary time, the direct ancestral connections between a regulator and its target genes were broken and replaced by indirect connections, preserving the overall logic of the ancestral circuit but producing a new behaviour. The example was uncovered through a series of experiments in three ascomycete yeasts: the bakers' yeast Saccharomyces cerevisiae, the dairy yeast Kluyveromyces lactis and the human pathogen Candida albicans. All three species have three cell types: two mating-competent cell forms (a and α) and the product of their mating (a/α), which is mating-incompetent. In the ancestral mating circuit, two homeodomain proteins, Mata1 and Matα2, form a heterodimer that directly represses four genes that are expressed only in a and α cells and are required for mating. In a relatively recent ancestor of K. lactis, a reorganization occurred. The Mata1-Matα2 heterodimer represses the same four genes (known as the core haploid-specific genes) but now does so indirectly through an intermediate regulatory protein, Rme1. The overall logic of the ancestral circuit is preserved (haploid-specific genes ON in a and α cells and OFF in a/α cells), but a new phenotype was produced by the rewiring: unlike S. cerevisiae and C. albicans, K. lactis integrates nutritional signals, by means of Rme1, into the decision of whether or not to mate.
View details for DOI 10.1038/nature09560
View details for Web of Science ID 000285344600046
View details for PubMedID 21164485
A number of proteins containing arginine-rich motifs (ARMs) are known to bind RNA and are involved in regulating RNA processing in viruses and cells. Using automated selection methods we have generated a number of aptamers against ARM peptides from various natural proteins. Aptamers bind tightly to their cognate ARMs, with K(d) values in the nanomolar range, and frequently show no propensity to bind to other ARMs or even to single amino acid variants of the cognate ARM. However, at least some anti-ARM aptamers can cross-recognize a limited set of other ARMs, just as natural RNA-binding sites have been shown to exhibit so-called "chameleonism." We expand upon the number of examples of cross-recognition and, using mutational and circular dichroism (CD) analyses, demonstrate that there are multiple mechanisms by which RNA ligands can cross-recognize ARMs. These studies support a model in which individual arginine residues govern binding to an RNA ligand, and the inherent flexibility of the peptide backbone may make it possible for "semi-specific" recognition of a discrete set of RNAs by a discrete set of ARM peptides and proteins.
View details for DOI 10.1261/rna.2167605
View details for Web of Science ID 000233758900012
View details for PubMedID 16314457