Institute for Systems Biology, Seattle, WA, USA; Molecular & Cellular Biology Graduate Program, University of Washington, Seattle, WA, USA; Altius Institute of Biomedical Sciences, Seattle, WA, USA.
Institute of Genome Sciences, University of Maryland School of Medicine, Baltimore, MD, USA; Department of Neurology, Johns Hopkins School of Medicine, Baltimore, MD, USA.
Cell Syst. 2019 Feb 27;8(2):122-135.e7. doi: 10.1016/j.cels.2019.01.002. Epub 2019 Feb 13.
Transcriptional regulatory changes in the developing and adult brain are prominent features of brain diseases, but the involvement of specific transcription factors (TFs) remains poorly understood. We integrated brain-specific DNase footprinting and TF-gene co-expression to reconstruct a transcriptional regulatory network (TRN) model for the human brain. We identified key regulator TFs whose predicted target genes were enriched for differentially expressed genes in the prefrontal cortex of individuals with psychiatric and neurodegenerative diseases. Many of these TFs were further implicated in the same diseases through disruption of their binding sites by disease-associated SNPs and associations of TF loci with disease risk. Using primary human neural stem cells, we validated network predictions that link the TF POU3F2 to schizophrenia and bipolar disorder via both cis- and trans-acting mechanisms. Our models of brain-specific TF binding sites and target genes provide a resource for network analysis of brain diseases.
在发育和成年大脑中，转录调控变化是大脑疾病的显著特征，但特定转录因子（TFs）的参与仍知之甚少。我们整合了大脑特异性 DNase 足迹和 TF-基因共表达，以重建人类大脑的转录调控网络（TRN）模型。我们确定了关键的调节 TF，其预测的靶基因在精神疾病和神经退行性疾病患者的前额叶皮层中差异表达基因中富集。通过疾病相关 SNP 破坏其结合位点以及 TF 基因座与疾病风险的关联，许多这些 TF 进一步涉及到相同的疾病。使用原代人神经干细胞，我们验证了网络预测，即通过顺式和反式作用机制，将 TF POU3F2 与精神分裂症和双相情感障碍联系起来。我们的大脑特异性 TF 结合位点和靶基因模型为大脑疾病的网络分析提供了资源。
