Luxembourg Centre for Systems Biomedicine, University of Luxembourg, Belvaux, Luxembourg.
Robotics and Artificial Intelligence, Department of Computer Science, Electrical and Space Engineering, Luleå University of Technology, Luleå, Sweden.
NPJ Syst Biol Appl. 2024 May 29;10(1):59. doi: 10.1038/s41540-024-00387-9.
The discovery of upstream regulatory genes of a gene of interest still remains challenging. Here we applied a scalable computational method to unbiasedly predict candidate regulatory genes of critical transcription factors by searching the whole genome. We illustrated our approach with a case study on the master regulator FOXP3 of human primary regulatory T cells (Tregs). While target genes of FOXP3 have been identified, its upstream regulatory machinery still remains elusive. Our methodology selected five top-ranked candidates that were tested via proof-of-concept experiments. Following knockdown, three out of five candidates showed significant effects on the mRNA expression of FOXP3 across multiple donors. This provides insights into the regulatory mechanisms modulating FOXP3 transcriptional expression in Tregs. Overall, at the genome level this represents a high level of accuracy in predicting upstream regulatory genes of key genes of interest.
目的基因上游调控基因的发现仍然具有挑战性。在这里,我们应用一种可扩展的计算方法,通过搜索整个基因组,无偏地预测关键转录因子的候选调控基因。我们通过人类初始调节性 T 细胞(Treg)的主调控因子 FOXP3 的案例研究来说明我们的方法。虽然已经鉴定出 FOXP3 的靶基因,但它的上游调控机制仍然难以捉摸。我们的方法选择了五个排名最高的候选基因,并通过概念验证实验进行了测试。敲低后,五个候选基因中有三个在多个供体中对 FOXP3 的 mRNA 表达有显著影响。这为调节 Treg 中 FOXP3 转录表达的调控机制提供了新的见解。总的来说,在基因组水平上,这代表了预测关键目的基因上游调控基因的高度准确性。