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BMC Genomics

, 17:228

Transcriptomic methods


BackgroundInference of gene regulation from expression data may help to unravel regulatory mechanisms involved in complex diseases or in the action of specific drugs. A challenging task for many researchers working in the field of systems biology is to build up an experiment with a limited budget and produce a dataset suitable to reconstruct putative regulatory modules worth of biological validation.

ResultsHere, we focus on small-scale gene expression screens and we introduce a novel experimental set-up and a customized method of analysis to make inference on regulatory modules starting from genetic perturbation data, e.g. knockdown and overexpression data. To illustrate the utility of our strategy, it was applied to produce and analyze a dataset of quantitative real-time RT-PCR data, in which interferon-α IFN-α transcriptional response in endothelial cells is investigated by RNA silencing of two candidate IFN-α modulators, STAT1 and IFIH1. A putative regulatory module was reconstructed by our method, revealing an intriguing feed-forward loop, in which STAT1 regulates IFIH1 and they both negatively regulate IFNAR1. STAT1 regulation on IFNAR1 was object of experimental validation at the protein level.

ConclusionsDetailed description of the experimental set-up and of the analysis procedure is reported, with the intent to be of inspiration for other scientists who want to realize similar experiments to reconstruct gene regulatory modules starting from perturbations of possible regulators. Application of our approach to the study of IFN-α transcriptional response modulators in endothelial cells has led to many interesting novel findings and new biological hypotheses worth of validation.

KeywordsIFN-α modulators Gene regulatory modules RNA silencing Experimental set-up Small-scale gene expression screens AbbreviationsIFN-αinterferon-α

GRNsgene regulatory networks

FFLfeed-forward loop

qRT-PCRquantitative real-time RT-PCR

CTcycle threshold

HUVECshuman umbilical vein endothelial cells

TFstranscription factors

Stefano Indraccolo and Gianna Maria Toffolo are joint senior authors.

Electronic supplementary materialThe online version of this article doi:10.1186-s12864-016-2525-5 contains supplementary material, which is available to authorized users.

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