Abstract
Although combinatorial regulation is a common feature in gene regulatory networks, how it evolves and affects network structure and function is not well understood. In S. cerevisiae, the phosphate starvation (PHO) responsive transcription factors Pho4 and Pho2 are required for gene induction and survival during phosphate starvation. In the related human commensal C. glabrata, Pho4 is required but Pho2 is dispensable for survival in phosphate starvation and is only partially required for inducing PHO genes. Phylogenetic survey suggests that reduced dependence on Pho2 evolved in C. glabrata and closely related species. In S. cerevisiae, less Pho2-dependent Pho4 orthologs induce more genes. In C. glabrata, its Pho4 binds to more locations and induces three times as many genes as Pho4 in S. cerevisiae does. Our work shows how evolution of combinatorial regulation allows for rapid expansion of a gene regulatory network's targets, possibly extending its physiological functions.
Highlights
Evolution of gene regulatory networks (GRNs) is a major source of phenotypic diversity (Wray, 2007; Stern and Frankel, 2013; Prud’homme et al, 2006; Gompel et al, 2005; Jones et al, 2012; Wang et al, 1999)
We investigated the evolution of the phosphate starvation (PHO) pathway in a diverse group of yeast species known as Hemiascomycetes (Knop, 2006; Diezmann et al, 2004), which includes but is not limited to S. cerevisiae, C. glabrata, K. lactis, C. albicans and Y. lypolitica, and found that PHO4 and PHO2 are conserved as single copy genes in this group
To understand whether dependence on Pho2 in S. cerevisiae is the ancestral or the derived state and how this property of Pho4 evolved among related species, we surveyed the activity of Pho4 orthologs from 16 species in the Hemiascomycete class
Summary
Evolution of gene regulatory networks (GRNs) is a major source of phenotypic diversity (Wray, 2007; Stern and Frankel, 2013; Prud’homme et al, 2006; Gompel et al, 2005; Jones et al, 2012; Wang et al, 1999). The existing literature on GRN evolution is strongly biased towards developmental networks (Stern, 2010; Peter and Davidson, 2011) While such networks provide attractive attributes, such as visible phenotypes and well-resolved genetic underpinning, it has been suggested that network architecture strongly influences the tempo and mode of its evolution (Erwin and Davidson, 2009; Wittkopp, 2007). It is unclear whether all GRNs follow similar or different rules during their evolution
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