title: Making sense of transcription networks.
abstract: When transcription regulatory networks are compared among distantly related eukaryotes, a number of striking similarities are observed: a larger-than-expected number of genes, extensive overlapping connections, and an apparently high degree of functional redundancy. It is often assumed that the complexity of these networks represents optimized solutions, precisely sculpted by natural selection; their common features are often asserted to be adaptive. Here, we discuss support for an alternative hypothesis: the common structural features of transcription networks arise from evolutionary trajectories of "least resistance"--that is, the relative ease with which certain types of network structures are formed during their evolution.
authors.affiliation: Department of Biochemistry & Biophysics and Department of Microbiology & Immunology, Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA.
authors.forename: Trevor R
authors.initials: TR
authors.lastname: Sorrells
authors.affiliation: Department of Biochemistry & Biophysics and Department of Microbiology & Immunology, Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA. Electronic address: ajohnson@cgl.ucsf.edu.
authors.forename: Alexander D
authors.initials: AD
authors.lastname: Johnson
mesh_terms: D000818:Animals; D018441:Biofilms; D005075:Biological Evolution; D053595:Embryonic Stem Cells; D005658:Fungi / Q000145:classification / Q000235:genetics / Q000378:metabolism; D005786:Gene Expression Regulation; D053263:Gene Regulatory Networks; D010944:Plants / Q000145:classification / Q000235:genetics / Q000378:metabolism