@article{10736,
  abstract     = {Predicting function from sequence is a central problem of biology. Currently, this is possible only locally in a narrow mutational neighborhood around a wildtype sequence rather than globally from any sequence. Using random mutant libraries, we developed a biophysical model that accounts for multiple features of σ70 binding bacterial promoters to predict constitutive gene expression levels from any sequence. We experimentally and theoretically estimated that 10–20% of random sequences lead to expression and ~80% of non-expressing sequences are one mutation away from a functional promoter. The potential for generating expression from random sequences is so pervasive that selection acts against σ70-RNA polymerase binding sites even within inter-genic, promoter-containing regions. This pervasiveness of σ70-binding sites implies that emergence of promoters is not the limiting step in gene regulatory evolution. Ultimately, the inclusion of novel features of promoter function into a mechanistic model enabled not only more accurate predictions of gene expression levels, but also identified that promoters evolve more rapidly than previously thought.},
  author       = {Lagator, Mato and Sarikas, Srdjan and Steinrueck, Magdalena and Toledo-Aparicio, David and Bollback, Jonathan P and Guet, Calin C and Tkačik, Gašper},
  issn         = {2050-084X},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{Predicting bacterial promoter function and evolution from random sequences}},
  doi          = {10.7554/eLife.64543},
  volume       = {11},
  year         = {2022},
}

@article{570,
  abstract     = {Most phenotypes are determined by molecular systems composed of specifically interacting molecules. However, unlike for individual components, little is known about the distributions of mutational effects of molecular systems as a whole. We ask how the distribution of mutational effects of a transcriptional regulatory system differs from the distributions of its components, by first independently, and then simultaneously, mutating a transcription factor and the associated promoter it represses. We find that the system distribution exhibits increased phenotypic variation compared to individual component distributions - an effect arising from intermolecular epistasis between the transcription factor and its DNA-binding site. In large part, this epistasis can be qualitatively attributed to the structure of the transcriptional regulatory system and could therefore be a common feature in prokaryotes. Counter-intuitively, intermolecular epistasis can alleviate the constraints of individual components, thereby increasing phenotypic variation that selection could act on and facilitating adaptive evolution. },
  author       = {Lagator, Mato and Sarikas, Srdjan and Acar, Hande and Bollback, Jonathan P and Guet, Calin C},
  issn         = {2050084X},
  journal      = {eLife},
  publisher    = {eLife Sciences Publications},
  title        = {{Regulatory network structure determines patterns of intermolecular epistasis}},
  doi          = {10.7554/eLife.28921},
  volume       = {6},
  year         = {2017},
}