Guided activation as a model for transcription factor networks determining cell fate

我们身体中数百种不同的细胞类型包含相同的遗传指令，但由于它们表达不同的基因而产生不同的蛋白质。基因表达是由一类被称为转录因子（tf）的蛋白质控制的。因此，tf决定了细胞类型的差异，当发生故障时，会引起广泛的疾病状态。tf识别基因组中的精确序列以找到它们的靶基因。众所周知，tf在群体中更有效地访问目标基因，但我们仍然不了解这些tf簇一旦与基因组中的目标序列结合，是如何激活基因表达的。我们将通过最先进的实验技术和计算方法来解决生物学中的这个基本问题。总的来说，这些结果将为如何建立细胞状态提供新的见解，与有效的细胞重编程和特定细胞类型的产生直接相关。

The hundreds of different cell types in our body contain the same genetic instructions but produce different proteins because they express different genes. Gene expression is controlled by a class of proteins, called transcription factors (TFs). Therefore, TFs determine the differences in cell types and, when malfunctioning, cause a wide range of disease states. TFs recognize precise sequences in the genome to find their target genes. It is well established that TFs access their target genes much more efficiently when they operate in groups, but we still do not understand how these clusters of TFs, once bound to their target sequences in the genome, activate gene expression. We will address this fundamental question in biology through state-of- the-art experimental technologies and computational methods. Collectively, these results will provide new insight into how cell states are established, with direct relevance for efficient cell reprogramming and the generation of specific cell types.