AVATAR: highly parallel analysis of variation in transcription factors and their DNA binding sites

摘要 转录因子（TF）与其DNA结合位点之间的相互作用是转录调控的核心。 基因调控网络TF或其DNA结合位点的遗传变异可能有助于 个体之间的特征差异。然而，这些基因之间的相互作用的作用 变异体仍然知之甚少。 用于测定TF（或TF）的DNA结合活性的现有高通量技术 变体）是“1-by-许多”方法，其中测定给定蛋白质与蛋白质的结合。 不同DNA序列的大文库，或者可选地测定蛋白质变体的大文库 一个给定的DNA序列的活性。TF编码变体表征的主要障碍 和DNA非编码变异的一个重要原因是缺乏高通量的“多对多”技术， 将使得能够测试大量TF编码变体的集合与不同的基因库的结合。 DNA结合位点序列;这样的DNA结合位点序列可以代表大的 TF的DNA结合位点基序中的取代的集合，或者替代地推定的顺式调节基序， 变体。 该项目的主要目标是开发新的技术，称为全变异分析， 转录因子亲和力和识别（AVATAR），用于高度并行分析的文库 TF编码变体，用于在其DNA结合位点与变体文库相互作用。我们将 优先考虑与疾病相关的人类TF， 突变或天然存在的多态性，预测会损害DNA结合 活动已经确定。这种技术将允许： 测试对DNA结合活性有精确影响的致腐性TF编码变体 目前无法预测（未发表的结果）;对特异性的更好理解- 确定各种TF类别的残基和TF-DNA“识别规则”; TF结合中TF编码变体和非编码变体之间的潜在遗传相互作用 研究中心（TFBS）。 !

Abstract The interactions between transcription factors (TFs) and their DNA binding sites are central to gene regulatory networks. Genetic variation in TFs or their DNA binding sites can contribute to differences in traits among individuals. However, the role of interactions among such genetic variants remains poorly understood. Existing high-throughput technologies for assaying the DNA binding activities of TFs (or TF variants) are “1-by-many” approaches, in which a given protein is assayed for its binding to a large library of different DNA sequences, or alternatively assay a large library of protein variants for activity from a given DNA sequence. A major hurdle in characterization of TF coding variants and DNA noncoding variants is the lack of a high-throughput “many-by-many” technology that would enable testing of a large collection of TF coding variants for binding to a library of different DNA binding site sequences; such DNA binding site sequences could represent either a large collection of substitutions in a TF's DNA binding site motif, or alternatively putative cis-regulatory variants. The primary goal of this project is to develop novel technology, termed All-Variant Analysis of Transcription factor Affinity and Recognition (AVATAR), for highly parallel analysis of a library of TF coding variants for interaction with a library of variants in their DNA binding sites. We will prioritize human TFs that are associated with diseases and for which disease-associated mutations or naturally occurring polymorphisms predicted to have damaged DNA binding activity have been identified. Such technology would permit: more extensive experimental testing of putatively damaging TF coding variants whose precise effects on DNA binding activity are not currently predictable (unpublished results); an improved understanding of specificity- determining residues and TF-DNA `recognition rules' for various TF classes; and identification of potential genetic interactions between TF coding variants and noncoding variants in TF binding sites (TFBSs). !