Developing methods and bioinformatics tools for the global analysis of accessible regions in chromatin

开发用于染色质可及区域全局分析的方法和生物信息学工具

• 批准号: BB/F02441X/1
• 负责人: Constanze Bonifer
• 金额: $ 13.5万
• 依托单位: University of Leeds
• 依托单位国家: 英国
• 项目类别: Research Grant
• 财政年份: 2008
• 资助国家: 英国
• 起止时间: 2008 至 无数据
• 项目状态: 已结题
• 来源: https://gtr.ukri.org/projects?ref=BB%2FF02441X%2F1
• 关键词: Developing; methods; bioinformatics; tools; global

One of the great challenges in modern biology is to understand why genetic information is differentially expressed in different cell types. Once we have a firm grip on this, we should be able to reprogram any cell of the body, and turn differentiated cells into stem cells able to become any cell type. That such reprogramming is indeed possible is exemplified by the finding that certain chromosomal translocations produce aberrant transcription factors which turn normal haematopoietic precursor cells into malignant leukaemic cells that only remotely resemble normal cell types. In addition, it was recently shown that only four transcription factors are sufficient to reprogram human fibroblast cells into stem cells. However, leukaemic cells take a long time to develop and it is known that often secondary events, i.e. the activation of other genes are required to fully turn normal cells into cancer cells. Also fibroblast reprogramming occurs with low efficiency, indicating that more than the targets of these four factors need to be activated. If we had methods where we could precisely identify regions of accessible chromatin, we could target these regions using either sequence specific transcription factors or small DNA-binding molecules. In addition, diagnosing regions of chromatin about to be opened up during cell differentiation will greatly enhance our understanding of which genes are activated in development and how. In this proposal we will use highly sensitive techniques enabling identification of such regions. The development of this technology needs a special effort, because it will require the close collaboration between experimental scientists and experts in handling and analysing large molecular data sets. The reason for this is that the experimental scientists will generate vast amounts of DNA sequence data which will then be puzzled together by the bioinformaticians to home in on those sequences in the mouse or human genome that are accessible. This task is anything but trivial.

现代生物学面临的最大挑战之一是理解为什么遗传信息在不同的细胞类型中差异表达。一旦我们牢牢掌握了这一点，我们应该能够重新编程身体的任何细胞，并将分化的细胞转化为能够成为任何细胞类型的干细胞。某些染色体易位产生异常转录因子，将正常的造血前体细胞转化为恶性白血病细胞，这些细胞与正常细胞类型只有很小的相似性。此外，最近显示，仅四种转录因子就足以将人成纤维细胞重编程为干细胞。然而，白血病细胞需要很长时间才能发育，并且众所周知，通常需要次级事件，即其他基因的激活，才能将正常细胞完全转化为癌细胞。成纤维细胞重编程的发生效率也很低，这表明需要激活的不仅仅是这四种因子的靶点。如果我们有方法可以精确地识别可接近的染色质区域，我们可以使用序列特异性转录因子或小的DNA结合分子来靶向这些区域。此外，诊断细胞分化过程中即将开放的染色质区域将大大增强我们对发育中哪些基因被激活以及如何激活的理解。在本提案中，我们将使用高度敏感的技术，使这些地区的识别。这项技术的发展需要特别的努力，因为它需要实验科学家和专家在处理和分析大型分子数据集方面的密切合作。这样做的原因是，实验科学家将产生大量的DNA序列数据，这些数据将被生物信息学家混淆在一起，以找到小鼠或人类基因组中可访问的序列。这项任务绝不是微不足道的。