Max Delbrück Center for Molecular Medicine, Berlin 13125, Germany.
Experimentelle Nephrologie, KIMIII, Universitätsklinikum Jena, Friedrich-Schiller-Universität, Jena 07743, Germany.
Nucleic Acids Res. 2014 May;42(9):5436-46. doi: 10.1093/nar/gku231. Epub 2014 Apr 11.
There are groups of genes that need coordinated repression in multiple contexts, for example if they code for proteins that work together in a pathway or in a protein complex. Redundancy of biological regulatory networks implies that such coordinated repression might occur at both the pre- and post-transcriptional level, though not necessarily simultaneously or under the same conditions. Here, we propose that such redundancy in the global regulatory network can be detected by the overlap between the putative targets of a transcriptional repressor, as identified by a ChIP-seq experiment, and predicted targets of a microRNA (miRNA). To test this hypothesis, we used publicly available ChIP-seq data of the neural transcriptional repressor RE1 silencing transcription factor (REST) from 15 different cell samples. We found 20 miRNAs, each of which shares a significant amount of predicted targets with REST. The set of predicted associations between these 20 miRNAs and the overlapping REST targets is enriched in known miRNA targets. Many of the detected miRNAs have functions related to neural identity and glioblastoma, which could be expected from their overlap in targets with REST. We propose that the integration of experimentally determined transcription factor binding sites with miRNA-target predictions provides functional information on miRNAs.
有一些基因群需要在多种情况下协调抑制，例如，如果它们编码的蛋白质在途径或蛋白质复合物中协同工作。生物调控网络的冗余性意味着这种协调抑制可能发生在转录前和转录后水平，尽管不一定同时或在相同条件下。在这里，我们提出，通过 ChIP-seq 实验确定的转录抑制因子的假定靶标与 microRNA（miRNA）的预测靶标之间的重叠，可以检测到全局调控网络中的这种冗余性。为了验证这一假设，我们使用了来自 15 种不同细胞样本的神经转录抑制因子 RE1 沉默转录因子（REST）的公开可用的 ChIP-seq 数据。我们发现了 20 个 miRNA，每个 miRNA 都与 REST 有大量的预测靶标共享。这 20 个 miRNA 与重叠 REST 靶标之间的预测关联集在已知的 miRNA 靶标中富集。许多检测到的 miRNA 具有与神经身份和神经胶质瘤相关的功能，这可以从它们与 REST 的靶标重叠中得到预期。我们提出，将实验确定的转录因子结合位点与 miRNA 靶标预测相结合，可以为 miRNA 提供功能信息。
