An iterative pipeline of computational modelling and experimental design for uncovering gene regulatory networks in vertebrates

用于揭示脊椎动物基因调控网络的计算模型和实验设计的迭代流程

• 批准号: BB/H017194/1
• 负责人: Baljinder Mankoo
• 金额: $ 23.59万
• 依托单位: King's College London
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2010
• 资助国家: 英国
• 起止时间: 2010 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FH017194%2F1
• 关键词: iterative; pipeline; computational; modelling; experimental

The behaviour of biological systems is the result of multiple regulatory interactions. Gene regulatory networks (GRNs) are the representation of these complex molecular interactions. They help us to understand how relationships between molecules dictate cell behaviour and are particularly useful to understand the complex dynamical processes driving animal development. The nodes in a GRN represent genes. Links between genes determine which gene products (proteins) regulate which other genes. In this project we focus on transcriptional regulation. This control mechanism regulates which genes are transcribed and expressed in the cell (and eventually which proteins are synthesized). The gene products that regulate transcription are a class of proteins called transcription factors. Transcription factors bind the DNA of target genes and influence the rate at which the target genes are transcribed. Mathematical models can describe how the rate of target gene transcription is affected when transcription factors bind to the DNA, and are useful to understand how cellular-scale behaviours arise from molecular actions. In this project we aim to develop computational methods able to construct GRN models using experimental data that describe gene expression and experimental data that describe the location of bound transcription factor proteins in DNA. An important aspect of the project is the development of a methodology capable of iteratively improving the GRN model by designing the most informative and effective sequence of experiments to be performed. This is particularly important since the experiments to locate binding of transcription factors to DNA are time-consuming and expensive and care should be taken to choose the most useful experiment at each stage. The methodology developed will be used to construct the GRN controlling the development of the second branchial arch (IIBA) in mouse. Branchial arches are transient structures of all vertebrate embryos that will eventually contribute to the face and the neck. Development of the IIBA is controlled by Hoxa2, a member of the large family of Hox transcription factors (TF). Hox TFs regulate morphogenesis along the head-tail axis of all animals with bilateral symmetry, but their mechanism of action is mostly unknown in vertebrates. Uncovering the principles underlying the GRN responsible for IIBA development will help us to understand the function of many other systems that are controlled by Hox proteins in vertebrate embryogenesis.

生物系统的行为是多种调控相互作用的结果。基因调控网络（grn）是这些复杂分子相互作用的代表。它们帮助我们理解分子之间的关系是如何决定细胞行为的，对于理解驱动动物发育的复杂动态过程尤其有用。GRN中的节点代表基因。基因之间的联系决定了哪些基因产物（蛋白质）调节哪些其他基因。在这个项目中，我们专注于转录调控。这种控制机制调节哪些基因在细胞中转录和表达（以及最终合成哪些蛋白质）。调节转录的基因产物是一类被称为转录因子的蛋白质。转录因子结合靶基因的DNA并影响靶基因的转录速率。数学模型可以描述当转录因子与DNA结合时靶基因的转录速率是如何受到影响的，并且有助于理解细胞尺度的行为是如何从分子作用中产生的。在这个项目中，我们的目标是开发能够使用描述基因表达的实验数据和描述结合转录因子蛋白在DNA中的位置的实验数据构建GRN模型的计算方法。该项目的一个重要方面是开发一种能够通过设计要执行的最具信息量和最有效的实验序列来迭代改进GRN模型的方法。这一点尤其重要，因为定位转录因子与DNA结合的实验既耗时又昂贵，在每个阶段都应谨慎选择最有用的实验。该方法将用于构建控制小鼠第二鳃裂弓发育的GRN。鳃弓是所有脊椎动物胚胎的短暂结构，最终会形成面部和颈部。IIBA的发育由Hoxa2控制，Hoxa2是Hox转录因子（TF）大家族的一员。Hox TFs在所有具有双侧对称的动物中沿头尾轴调节形态发生，但其作用机制在脊椎动物中尚不清楚。揭示负责IIBA发育的GRN的基本原理将有助于我们了解脊椎动物胚胎发生中由Hox蛋白控制的许多其他系统的功能。