Data from: The architecture of an empirical genotype-phenotype map

Recent advances in high-throughput technologies are bringing the study of
empirical genotype-phenotype (GP) maps to the fore. Here, we use data from
protein binding microarrays to study an empirical GP map of transcription
factor (TF) binding preferences. In this map, each genotype is a DNA
sequence. The phenotype of this DNA sequence is its ability to bind one or
more TFs. We study this GP map using genotype networks, in which nodes
represent genotypes with the same phenotype, and edges connect nodes if
their genotypes differ by a single small mutation. We describe the
structure and arrangement of genotype networks within the space of all
possible binding sites for 525 TFs from three eukaryotic species
encompassing three kingdoms of life (animal, plant, and fungi). We thus
provide a high-resolution depiction of the architecture of an empirical GP
map. Among a number of findings, we show that these genotype networks are
“small-world” and assortative, and that they ubiquitously overlap and
interface with one another. We also use polymorphism data from Arabidopsis
thaliana to show how genotype network structure influences the evolution
of TF binding sites in vivo. We discuss our findings in the context of
regulatory evolution.