Making sense of transcription networks

Trevor R Sorrells; Alexander D Johnson

doi:10.1016/j.cell.2015.04.014

Making sense of transcription networks

Cell. 2015 May 7;161(4):714-23. doi: 10.1016/j.cell.2015.04.014.

Authors

Trevor R Sorrells¹, Alexander D Johnson²

Affiliations

¹ Department of Biochemistry & Biophysics and Department of Microbiology & Immunology, Tetrad Graduate Program, University of California, San Francisco, San Francisco, CA 94158, USA.
² 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.

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.

Publication types

Research Support, N.I.H., Extramural
Research Support, U.S. Gov't, Non-P.H.S.
Review

MeSH terms

Animals
Biofilms
Biological Evolution*
Embryonic Stem Cells
Fungi / classification
Fungi / genetics
Fungi / metabolism
Gene Expression Regulation
Gene Regulatory Networks*
Plants / classification
Plants / genetics
Plants / metabolism

Grants and funding

R01 GM037049/GM/NIGMS NIH HHS/United States