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.

高通量技术的新近进展正推动经验型基因型-表型（genotype-phenotype, GP）图谱研究成为前沿热点。本研究借助蛋白质结合微阵列（protein binding microarrays）的数据，针对转录因子（transcription factor, TF）结合偏好的经验型GP图谱展开研究。在此图谱中，每个基因型均为一段DNA序列，该DNA序列的表型即为其结合一个或多个转录因子的能力。我们采用基因型网络（genotype networks）对该GP图谱进行研究：其中节点代表具有相同表型的基因型，若两个节点对应的基因型仅存在单个微小突变差异，则二者之间存在连边。我们针对涵盖生命三大界（动物界、植物界与真菌界）的3个真核物种的525个转录因子，刻画了其所有潜在结合位点空间内基因型网络的结构与排布特征，由此为经验型GP图谱的架构提供了高分辨率的刻画。在诸多研究发现中，我们证明此类基因型网络兼具“小世界”与同配性特征，且彼此普遍存在相互重叠与交互关联。我们还借助拟南芥（Arabidopsis thaliana）的多态性数据，阐释了基因型网络结构如何在体内影响转录因子结合位点的演化。最后，我们结合调控进化的研究背景对本研究的各项发现展开了讨论。