PubReading [302] - The evolution, evolvability and engineering of gene regulatory DNA - E. Vaishnav, A. Regev et al.

Mutations in non-coding regulatory DNA sequences can alter gene expression, organismal phenotype and fitness1–3. Constructing complete fitness landscapes, in which DNA sequences are mapped to fitness, is a long-standing goal in biology, but has remained elusive because it is challenging to generalize reliably to vast sequence spaces4–6. Here we build sequence-to-expression models that capture fitness landscapes and use them to decipher principles of regulatory evolution. Using millions of randomly sampled promoter DNA sequences and their measured expression levels in the yeast Saccharomyces cerevisiae, we learn deep neural network models that generalize with excellent prediction performance, and enable sequence design for expression engineering. Using our models, we stud ...