Deconvoluting gene activity and cell-of-origin of platelet DNA

血小板 DNA 的基因活性和细胞起源解卷积

• 批准号: 2600600
• 金额: --
• 依托单位: University of Oxford
• 依托单位国家: 英国
• 项目类别: Studentship
• 财政年份: 2021
• 资助国家: 英国
• 起止时间: 2021 至 无数据
• 项目状态: 未结题
• 来源: https://gtr.ukri.org/projects?ref=studentship-2600600
• 关键词: Deconvoluting; gene; activity; cell; origin

Platelets are small cells in the blood that are fundamental to haemostasis, blood vessel maintenance and play a role in immune responses. When cells die, they release the DNA from their nucleus into the blood, resulting in cell-free DNA (cfDNA) in blood plasma. We recently demonstrated that although platelets do not contain a nucleus, they 'vacuum' cfDNA fragments from blood and protect them from degradation. They may play a key role in the clearance of cfDNA, and act as biosensors to relay information between different type of cells. The project will focus on studying the newly discovered DNA in platelets and investigate whether we can determine the cell type the DNA fragments are coming from. If platelet DNA is rich in such information, we will train a machine learning algorithm to predict gene activity and cell of origin from platelet DNA patterns. This would pave the way for a new method in routine health monitoring, applicable with a simple blood test.

血小板是血液中的小细胞，对止血、血管维护和免疫反应起着重要作用。当细胞死亡时，它们将DNA从细胞核释放到血液中，导致血浆中的无细胞DNA(CfDNA)。我们最近证明，尽管血小板不含核，但它们从血液中‘真空’cfDNA片段，并保护它们免受降解。它们可能在cfDNA的清除中发挥关键作用，并作为生物传感器在不同类型的细胞之间传递信息。该项目将专注于研究新发现的血小板中的DNA，并调查我们能否确定DNA片段来自哪种细胞类型。如果血小板DNA含有丰富的此类信息，我们将训练一种机器学习算法，根据血小板DNA模式预测基因活性和细胞来源。这将为常规健康监测的新方法铺平道路，适用于简单的血液测试。