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首页> 外文期刊>BMC Systems Biology >Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets
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Protein interaction network topology uncovers melanogenesis regulatory network components within functional genomics datasets

机译:蛋白质相互作用网络拓扑揭示了功能基因组学数据集中的黑色素生成调控网络成分

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Background RNA-mediated interference (RNAi)-based functional genomics is a systems-level approach to identify novel genes that control biological phenotypes. Existing computational approaches can identify individual genes from RNAi datasets that regulate a given biological process. However, currently available methods cannot identify which RNAi screen "hits" are novel components of well-characterized biological pathways known to regulate the interrogated phenotype. In this study, we describe a method to identify genes from RNAi datasets that are novel components of known biological pathways. We experimentally validate our approach in the context of a recently completed RNAi screen to identify novel regulators of melanogenesis. Results In this study, we utilize a PPI network topology-based approach to identify targets within our RNAi dataset that may be components of known melanogenesis regulatory pathways. Our computational approach identifies a set of screen targets that cluster topologically in a human PPI network with the known pigment regulator Endothelin receptor type B (EDNRB). Validation studies reveal that these genes impact pigment production and EDNRB signaling in pigmented melanoma cells (MNT-1) and normal melanocytes. Conclusions We present an approach that identifies novel components of well-characterized biological pathways from functional genomics datasets that could not have been identified by existing statistical and computational approaches.
机译:背景基于RNA介导的干扰(RNAi)的功能基因组学是一种系统级方法,用于识别控制生物表型的新基因。现有的计算方法可以从调节给定生物学过程的RNAi数据集中识别单个基因。但是,当前可用的方法不能确定哪些RNAi筛选“命中”是已知可调节询问表型的特征明确的生物学途径的新组成部分。在这项研究中,我们描述了一种从RNAi数据集中识别基因的方法,该数据集是已知生物学途径的新组成部分。我们在最近完成的RNAi筛查中实验性地验证了我们的方法,以识别黑色素生成的新型调节剂。结果在本研究中,我们利用基于PPI网络拓扑的方法在我们的RNAi数据集中识别可能是已知黑色素生成调节途径的组成部分的靶标。我们的计算方法确定了一组筛选目标,这些目标在拓扑结构上与已知的色素调节剂B型内皮素受体(EDNRB)聚集在人PPI网络中。验证研究表明,这些基因影响色素性黑色素瘤细胞(MNT-1)和正常黑色素细胞的色素生成和EDNRB信号传导。结论我们提出了一种从功能基因组学数据集中识别特征明确的生物途径的新组成部分的方法,而现有的统计和计算方法无法确定这些新组成部分。

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