Whalen Sean, Truty Rebecca M, Pollard Katherine S
Gladstone Institutes, San Francisco, California, USA.
Division of Biostatistics, Institute for Human Genetics, University of California, San Francisco, San Francisco, California, USA.
Nat Genet. 2016 May;48(5):488-96. doi: 10.1038/ng.3539. Epub 2016 Apr 4.
Discriminating the gene target of a distal regulatory element from other nearby transcribed genes is a challenging problem with the potential to illuminate the causal underpinnings of complex diseases. We present TargetFinder, a computational method that reconstructs regulatory landscapes from diverse features along the genome. The resulting models accurately predict individual enhancer-promoter interactions across multiple cell lines with a false discovery rate up to 15 times smaller than that obtained using the closest gene. By evaluating the genomic features driving this accuracy, we uncover interactions between structural proteins, transcription factors, epigenetic modifications, and transcription that together distinguish interacting from non-interacting enhancer-promoter pairs. Most of this signature is not proximal to the enhancers and promoters but instead decorates the looping DNA. We conclude that complex but consistent combinations of marks on the one-dimensional genome encode the three-dimensional structure of fine-scale regulatory interactions.
区分远端调控元件的基因靶点与其他附近转录基因是一个具有挑战性的问题,它有可能揭示复杂疾病的因果基础。我们提出了TargetFinder,这是一种从基因组中的各种特征重建调控景观的计算方法。由此产生的模型能够准确预测多个细胞系中的单个增强子-启动子相互作用,其错误发现率比使用最接近基因获得的错误发现率小多达15倍。通过评估驱动这种准确性的基因组特征,我们发现了结构蛋白、转录因子、表观遗传修饰和转录之间的相互作用,这些相互作用共同区分了相互作用的和非相互作用的增强子-启动子对。这种特征的大部分并非靠近增强子和启动子,而是修饰了环状DNA。我们得出结论,一维基因组上复杂但一致的标记组合编码了精细尺度调控相互作用的三维结构。