Li Jin, Wang Yang, Rao Xi, Wang Yue, Feng Weixing, Liang Hong, Liu Yunlong
College of Automation, Harbin Engineering University, Harbin, Heilongjiang, 150001, China.
Department of Medical and Molecular Genetics, Indiana University School of Medicine, Indianapolis, IN, 46202, USA.
BMC Syst Biol. 2017 Oct 3;11(Suppl 5):89. doi: 10.1186/s12918-017-0465-6.
The ability of a transcription factor to regulate its targets is modulated by a variety of genetic and epigenetic mechanisms. Alternative splicing can modulate gene function by adding or removing certain protein domains, and therefore affect the activity of protein. Reverse engineering of gene regulatory networks using gene expression profiles has proven valuable in dissecting the logical relationships among multiple proteins during the transcriptional regulation. However, it is unclear whether alternative splicing of certain proteins affects the activity of other transcription factors.
In order to investigate the roles of alternative splicing during transcriptional regulation, we constructed a statistical model to infer whether the alternative splicing events of modulator proteins can affect the ability of key transcription factors in regulating the expression levels of their transcriptional targets. We tested our strategy in KIRC (Kidney Renal Clear Cell Carcinoma) using the RNA-seq data downloaded from TCGA (the Cancer Genomic Atlas). We identified 828of modulation relationships between the splicing levels of modulator proteins and activity levels of transcription factors. For instance, we found that the activity levels of GR (glucocorticoid receptor) protein, a key transcription factor in kidney, can be influenced by the splicing status of multiple proteins, including TP53, MDM2 (mouse double minute 2 homolog), RBM14 (RNA-binding protein 14) and SLK (STE20 like kinase). The influenced GR-targets are enriched by key cancer-related pathways, including p53 signaling pathway, TR/RXR activation, CAR/RXR activation, G1/S checkpoint regulation pathway, and G2/M DNA damage checkpoint regulation pathway.
Our analysis suggests, for the first time, that exon inclusion levels of certain regulatory proteins can affect the activities of many transcription factors. Such analysis can potentially unravel a novel mechanism of how splicing variation influences the cellular function and provide important insights for how dysregulation of splicing outcome can lead to various diseases.
转录因子调控其靶标的能力受到多种遗传和表观遗传机制的调节。可变剪接可通过添加或去除某些蛋白质结构域来调节基因功能,从而影响蛋白质的活性。利用基因表达谱对基因调控网络进行反向工程已被证明在剖析转录调控过程中多种蛋白质之间的逻辑关系方面具有重要价值。然而,尚不清楚某些蛋白质的可变剪接是否会影响其他转录因子的活性。
为了研究可变剪接在转录调控中的作用,我们构建了一个统计模型,以推断调节蛋白的可变剪接事件是否会影响关键转录因子调节其转录靶标表达水平的能力。我们使用从TCGA(癌症基因组图谱)下载的RNA-seq数据在KIRC(肾透明细胞癌)中测试了我们的策略。我们确定了调节蛋白的剪接水平与转录因子活性水平之间的828种调节关系。例如,我们发现肾脏中的关键转录因子GR(糖皮质激素受体)蛋白的活性水平可受到多种蛋白质剪接状态的影响,包括TP53、MDM2(小鼠双微体2同源物)、RBM14(RNA结合蛋白14)和SLK(STE20样激酶)。受影响的GR靶标在关键癌症相关途径中富集,包括p53信号通路、TR/RXR激活、CAR/RXR激活、G1/S检查点调节途径和G2/M DNA损伤检查点调节途径。
我们的分析首次表明,某些调节蛋白的外显子包含水平可影响许多转录因子的活性。这种分析可能揭示剪接变异影响细胞功能的新机制,并为剪接结果失调如何导致各种疾病提供重要见解。