Adaptive landscapes of transcription factors and their in vivo binding sites in 1135 Arabidopsis thaliana genomes

基因表达是决定生物表型的关键因素，因此基因表达调控的变化是适应和进化的主要力量。基因的表达受几个分子过程控制，包括转录因子（TF）与DNA上的特异性结合位点（TFBS）的结合。基因表达变异的一个来源是顺式调节序列中的点突变，其导致TF结合亲和力改变。为了了解点突变如何影响TF的结合亲和力，开发了由所有可能的具有10个碱基对长度的双链DNA片段组成的蛋白结合微阵列（PBM）。这样的阵列允许将TF的结合亲和力分配给所有连续和有缺口的8聚体。这种组合完整的数据集的一个优点是，它们揭示了所有遗传背景中每个个体突变的影响。因此，使用结合亲和力作为适应的代理，PBM实验的结果是理想的映射表型的基因型和建设适应性景观。适应性景观非常适合研究生物学中的一个中心问题：种群遵循（不遵循）哪些突变路径以及为什么。该研究将首次阐明拟南芥实际群体基因组数据中转录因子结合位点的进化。这样的研究现在是可能的，因为拟议的工作将使用最近公布的数据集。这些包括从世界范围内收集的A. thaliana，PBM实验中确定的313个TF的结合亲和力，1，203种植物的529个体内确定的TF结合位点和转录组的集合。具体来说，该项目是集中在两个主要方面：什么是选择，中立性和上位性的TFBS的演变过程中的作用？进化的可重复性和约束性如何？为了解决这些问题，将采用基因型网络。这些网络中的节点代表基因组中一个TFBS的序列。如果两个节点的潜在序列相差恰好一个核苷酸，则它们是连接的。通过考虑每个结合位点的结合亲和力，可以重建自适应景观。这种方法允许利用丰富的工具集可用于网络分析，并成功地用于调查经验数据。总之，该项目将促进我们对自然种群中TFBS进化的理解。

Gene expression is a crucial factor for determining organismal phenotypes and changes in the regulation of gene expression are consequently major forces in adaptation and evolution. The expression of a gene is controlled by several molecular processes, including the binding of a transcription factor (TF) to specific binding sites (TFBSs) on DNA. One source of variation in gene expression are point mutations in cis-regulatory sequences that lead to altered TF binding affinities. To understand how point mutations affect the binding affinity of a TF, protein binding microarrays (PBM) consisting of all possible double stranded DNA fragments with a length of ten base pairs were developed. Such arrays allow to assign binding affinities of TFs to all contiguous and gapped 8-mers. One beauty of such combinatorically complete data sets is that they uncover the effect of each individual mutation in all genetic backgrounds. Using binding affinities as a proxy for adaptation, the results of PBM experiments are therefore ideal for mapping phenotypes to genotypes and for building adaptive landscapes. Adaptive landscapes are well suited to investigate a central question in biology: which mutational paths are (not) followed by a population and why. The proposed study will for the first time elucidate the evolution of transcription factor binding sites in actual population genomics data of Arabidopsis thaliana. Such studies are now possible, because the proposed work will employ recently published data sets. These include 1,135 genome sequences obtained from a worldwide collection of A. thaliana, binding affinities of 313 TFs determined in PBM experiments, a collection of 529 in vivo determined TF binding sites and transcriptomes of 1,203 plants. Specifically, the project is centered on two main aspects: what are the roles of selection, neutrality and epistasis during the evolution of TFBSs? How repeatable and constraint is the evolution? To address these questions, genotype networks will be employed. These are networks where nodes represent the sequence of one TFBS in the genome. Two nodes are connected if their underlying sequences differ by exactly one nucleotide. By considering binding affinities for each binding site, adaptive landscapes can be reconstructed. This approach allows to take advantage of the rich tool set available for network analysis and was successfully used for investigating empirical data. In summary, the project will advance our understanding of the evolution of TFBSs in natural populations.