  Gene regulation involves a hierarchy of events that extend from specific
protein-DNA interactions to the combinatorial assembly of nucleoprotein
complexes. The effects of DNA sequence on these processes have typically been
studied based either on its quantitative connection with single-domain binding
free energies or on empirical rules that combine different DNA motifs to
predict gene expression trends on a genomic scale. The middle-point approach
that quantitatively bridges these two extremes, however, remains largely
unexplored. Here, we provide an integrated approach to accurately predict gene
expression from statistical sequence information in combination with detailed
biophysical modeling of transcription regulation by multidomain binding on
multiple DNA sites. For the regulation of the prototypical lac operon, this
approach predicts within 0.3-fold accuracy transcriptional activity over a
10,000-fold range from DNA sequence statistics for different intracellular
conditions.
