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Abstract：
Gene regulation is essential to placental function and fetal development. We built a genome-scale transcriptional regulatory network (TRN) of the human placenta using digital genomic footprinting and transcriptomic data. We integrated 475 transcriptomes and 12 DNase hypersensitivity datasets from placental samples to globally and quantitatively map transcription factor (TF)-target gene interactions. In an independent dataset, the TRN model predicted target gene expression with an out-of-sample R2 greater than 0.25 for 73% of target genes. We performed siRNA knockdowns of four TFs and achieved concordance between the predicted gene targets in our TRN and differences in expression of knockdowns with an accuracy of >0.7 for three of the four TFs. Our final model contained 113,158 interactions across 391 TFs and 7712 target genes and is publicly available. We identified 29 TFs which were significantly enriched as regulators for genes previously associated with preterm birth, and eight of these TFs were decreased in preterm placentas.
摘要：
基因调控对胎盘功能和胎儿发育至关重要。我们使用数字基因组足迹和转录组数据构建了人类胎盘的基因组尺度转录调控网络（TRN）。我们整合了来自胎盘样品的475个转录组和12个DNase超敏反应数据集，以全局和定量地绘制转录因子（TF）-靶基因相互作用。在独立的数据集中，TRN模型预测了73%靶基因的样品外R2大于0.25的靶基因表达。我们进行了四种TF的siRNA敲除,并且实现了我们的TRN中预测的基因靶标与敲除的表达差异之间的一致性,对于四种TF中的三种,准确度>0.7。我们的最终模型包含391TFs和7712个靶基因的113,158个相互作用，并且是公开可用的。我们确定了29个TFs，这些TFs作为先前与早产相关的基因的调节因子，在早产胎盘中，这些TFs中有8个减少。
