The Evolution of Combinatorial Gene Regulation in Fungi

Abstract

It is widely suspected that gene regulatory networks are highly plastic. The rapid turnover of transcription factor binding sites has been predicted on theoretical grounds and has been experimentally demonstrated in closely related species. We combined experimental approaches with comparative genomics to focus on the role of combinatorial control in the evolution of a large transcriptional circuit in the fungal lineage. Our study centers on Mcm1, a transcriptional regulator that, in combination with five cofactors, binds roughly 4% of the genes in Saccharomyces cerevisiae and regulates processes ranging from the cell-cycle to mating. In Kluyveromyces lactis and Candida albicans, two other hemiascomycetes, we find that the Mcm1 combinatorial circuits are substantially different. This massive rewiring of the Mcm1 circuitry has involved both substantial gain and loss of targets in ancient combinatorial circuits as well as the formation of new combinatorial interactions. We have dissected the gains and losses on the global level into subsets of functionally and temporally related changes. One particularly dramatic change is the acquisition of Mcm1 binding sites in close proximity to Rap1 binding sites at 70 ribosomal protein genes in the K. lactis lineage. Another intriguing and very recent gain occurs in the C. albicans lineage, where Mcm1 is found to bind in combination with the regulator Wor1 at many genes that function in processes associated with adaptation to the human host, including the white-opaque epigenetic switch. The large turnover of Mcm1 binding sites and the evolution of new Mcm1–cofactor interactions illuminate in sharp detail the rapid evolution of combinatorial transcription networks.

Transcription factor function and promoter architecture govern the evolution of bacterial regulons

“…The evolution of certain transcriptional regulators in yeast has been ascribed to changes in protein-protein interactions caused by a few amino acid substitutions (1,2,32), whereas the reported cases in higher eukaryotes typically involve whole-domain gains or losses (6). (However, some examples in which a few amino acid substitutions seem to be responsible for functional changes have also been reported (7,33).)…”

“…These changes are in addition to the well-established transcriptional rewiring events whereby the promoters of conserved genes in related species differ in the presence/absence of TF binding site(s) (1,37,38). While there are a few reports of evolutionary changes in eukaryotic TFs contributing to the modification of gene-regulatory networks (6)(7)(8)33), alterations in gene regulation and phenotypic differences in eukaryotes have been ascribed primarily to gains and/or losses of TF binding sites (3,5,10).…”

“…cis-regulatory elements ͉ horizontal gene transfer ͉ PhoP ͉ Salmonella ͉ Yersinia G ene regulatory networks undergo major modifications over time, and these modifications provide an important source of phenotypic diversity among closely related organisms (1,2). In principle, these modifications may result from changes in cisregulatory sequences and/or from alterations in the deployment and/or activity of the transcription factors (TFs) that act on these sequences.…”

Signatures of combinatorial regulation in intrinsic biological noise

“…Despite the apparent importance of combinatorial regulation (12)(13)(14)(15)(16)(17)(18)(19), knowledge of it is presently limited to a few well-studied examples such as the mediation of the response to endocrine signaling by nonsteroid nuclear receptors (12) and the regulation of Oct genes by POU and SOX in pluripotent mammalian cells (13). We believe that the approach presented here will be useful for probing transcription factor synergies and thus expanding our understanding of combinatorial regulation.…”

“…In higher organisms, many genes are regulated by a large number of transcription factors, often with multiple binding sites for each factor (9)(10)(11). It is increasingly clear that the action of many such regulators depends on their molecular context (12)(13)(14)(15)(16)(17)(18)(19). Because CRIFs are capable of encoding arbitrarily complex modes of regulation, they will likely be even more useful for describing the control of transcription in these systems than in the simpler prokaryotic ones.…”