Mathematical and bioinformatics based tools to explore the impact of gene editing on the geometric principles governing the 3D structure of the genome

基因编辑可能会对目标基因附近的基因的表达产生不可预见的后果。鉴于使用CRISPR/Cas9技术进行临床基因编辑以修复疾病突变的前景，显然需要了解这些技术对基因组三维结构的影响。因此，该项目将应用和开发基于数学和生物信息学的工具，从用于人类表观遗传学图谱和最先进成像技术的大规模“基因组”数据集探索基因组三维结构的几何原理。然后，我们将研究定向基因编辑对3D基因组结构的影响。具体地说，这个项目将首先使用染色质确认分析来研究基因组的拓扑结构。具体地说，我们将应用一种等位基因特异性染色质确认分析策略，称为捕获HIC(C-HIC)。这是HIC方法的一种变体，它允许以比标准HIC方法更高的分辨率来丰富和绘制感兴趣的基因组区域。我们将要研究的基因组区域是DIRAS3/GNG12-AS1系统，它表现出负的基因非自主性。具体地说，DIRAS3/GNG12-AS1的转录水平在细胞周期中呈负相关。这种负相关性可以通过启动子竞争模型来解释，在该模型中，一个基因的启动子活性降低了启动子在另一个基因上的可及性。这种模式需要染色质环来使启动子非常接近。因此，这表明染色质构象可能在转录干扰和基因簇的调节中发挥重要作用。此外，DNA周围的结构化环境定义了基因表达的表观遗传因素。公众对表观遗传学的研究越来越感兴趣，以及表观遗传学如何解释生活方式选择对DNA的影响。基因编辑将如何影响遗传健康也引起了公众和健康的强烈兴趣。首先，我们的研究结果将形成一个平台，可以在此平台上开发算法，预测基因编辑技术可以安全和更准确地针对基因组的哪些区域。数据驱动的生物学和生物医学科学的系统方法为大规模分析多种细胞和生物特征提供了手段。这个项目的新奇之处在于，我们将是第一批使用这些数据来了解三维结构如何影响我们基因组工作的人之一。

Gene editing can have unforeseen consequences on the expression of genes adjacent to the targeted gene. Given the prospect for clinical gene editing to repair disease mutations, using CRISPR/Cas9 technology, there is a clear need to understand the impact of these technologies on the 3D structure of the genome. As such this project will apply and develop mathematical and bioinformatics based tools to explore the geometric principles governing the 3D structure of the genome from large-scale 'omic' data sets for human epigenetic profiles and state-of-the art imaging technologies. We will then examine the impact of targeted gene editing on the 3D genome structure. Specifically this project will first investigate the topological structure of the genome using chromatin confirmation analysis. Specifically we will apply an allele specific chromatin confirmation analysis strategy, known as Capture HiC (C-HiC). This is a variation of the HiC methodology which allows the genomic region of interest to be enriched and mapped at a much greater resolution than standard HiC methodologies. The genomic region of interest we will be investigating is the DIRAS3/GNG12-AS1 system which displays negative gene non-autonomy. Specifically it is known that the transcription levels of DIRAS3/GNG12-AS1 are inversely correlated during the cell cycle. This negative correlation may be explained via a promoter competition model whereby the promotor activity of one gene reduces the accessibility of the promotor on the other gene. This model necessitates chromatin looping to bring the promotors into close proximity. As such, this suggests that chromatin conformation may play an important role in transcriptional interference and the regulation of clusters of genes.In addition, the structured environment around the DNA is what defines epigenetic factors of gene expression. There is a growing public interest in epigenetics research and how epigenetics can explain the effects of life style choices on the DNA. There is also a strong public and health interest in how gene editing will affect genetic health. In the first instance the results of our study will form a platform that can be built upon to develop algorithms for predicting which regions of the genome can be safely and more precisely targeted by gene editing technologies. Data driven biology and systems approaches to biomedical sciences provide the means for large scale analysis of multiple cellular and biological features. The novelty of this project is that we will be among the first to use such data to understand how three dimensional structures affect the working of our genome.