Gene regulation in health and disease

像C.Elgans这样的简单生物体与人类的基因数量相似，尽管它只由几千个细胞组成，而人类则有数万亿个细胞。因此，这种复杂性的大幅增加与基因本身无关，而是与使用它们的组合的复杂性有关。因此，复杂的哺乳动物生命是建立在对基因使用（表达）的精确控制上的;它们何时何地被打开和关闭以及它们的表达水平。控制基因表达的“开关”位于基因组的“非编码”区域，而不是形成蛋白质生产蓝图的区域。然而，这代表了总基因组的约98%，并且激活这些开关的DNA代码在每种细胞类型中是不同的，因此理解控制基因表达的系统是非常复杂的。然而，了解这些机制对人类健康极其重要，因为与所有常见人类疾病（心脏病，癌症，痴呆症，多发性硬化症等）相关的近90%的遗传基因都位于该区域内，并改变这些开关的活性。我们使用实验，计算和机器学习方法的组合来理解基因调控的基本原理，以解码常见的人类疾病遗传学。我们使用这些方法来了解受这些遗传学影响的基因和细胞功能，以最终指导治疗开发。

A simple organism like C.Elgans has similar numbers of genes as a human even though it is made of only a few thousand cells compared to the many trillions in a human. This massive increase in complexity is therefore not linked to the genes themselves, but rather to the complexity of the combinations in which they are used. Therefore, complex mammalian life is founded on exquisite control of gene usage (expression); when and where they are switched on and off and their level of expression. The “switches” that control gene expression are located in the “non-coding” region of the genome rather than the regions that form the blueprint for production of the proteins of which we are made. However, this represents ~98% of the total genome and the DNA code that activates these switches is different in each cell type so understanding the systems that control gene expression is extremely complex. However, understanding these mechanisms is extremely important for human heath as nearly 90% of the genetics linked to all common human diseases (Heart disease, cancer, dementia, multiple sclerosis etc) lie within this region and change the activity of these switches. We use a combination of experimental, computational and machine learning approaches to understand the basic principles of gene regulation to decode common human disease genetics. We use these approaches to understand the genes and cellular functions affected by these genetics to ultimately guide therapeutic development.