Identifying unique regulatory elements related to polymorphic imprinting and gestational aging in the placenta

胎盘在怀孕期间生长并附着在子宫壁上。它通过脐带将母亲和婴儿连接起来。它的主要目的是为婴儿提供生长所需的所有营养和氧气，同时清除婴儿血液中的废物和二氧化碳。如果胎盘发育或功能不正常，这可能导致妊娠并发症，对婴儿产生巨大的影响，不是在分娩后立即出现，而是在以后的生活中。细胞是复杂组织（如胎盘）的基本单位。不同细胞类型之间的细胞表型和功能差异很大。我们基因的编码和活动（称为表达）最终决定了产生哪些细胞及其行为方式。这是通过对DNA进行“表观遗传”修饰来实现的。表观遗传调控的一种形式是通过用甲基标记基因组的某些区域来实现的，甲基往往充当基因表达的半永久性阻断。然而，DNA甲基化并不是单独起作用的，有不同的相互作用机制有助于表观遗传调控。近年来，一类被称为印迹基因的基因已被证明对胎盘的发育和功能至关重要。这些独特的调控基因在表观遗传学上是“开启”的，只从母体或父亲的拷贝中表达，而不是同时表达。胎盘是迷人的，因为它具有独特的表观遗传特征，与所有其他组织相比，DNA甲基化明显更少，在怀孕期间会发生微妙的变化。这种独特的低甲基化状态对表观遗传信息附加层的分层后果尚未被研究。此外，胎盘中含有数百种在其他组织中未发现的独特印迹基因，这些基因的表达通常随着妊娠以DNA甲基化独立的方式减少。这表明其他表观遗传机制对观察到的下调负责。我们对这一现象的理解一直受到阻碍，因为我们不知道胎盘中健康衰老的机制。在本应用中，我们试图了解胎盘甲基化如何影响妊娠不同时间点的其他表观遗传标记，以及这最终如何影响印迹基因表达（目的1.1-1.2）。为了实现这一目标，我们将利用并在某些情况下改进最新技术，以确定基因组的哪些区域与不同的表观遗传特征相关，以及这些特征如何影响发育（目标2.1和3）。此外，由于我们预计样本中的可变性和细胞类型特异性特征，我们将分析分离的单细胞，使我们能够识别在“批量”胎盘活检中不明显的模式（目标2.2）。为了最大限度地确保我们以前的经验成功建立的机会，我们已经建立了一个团队，其中包括在厄勒姆研究所的英国国家基因组学能力负责技术开发的研究人员和数据分析的计算专家。在使用功能极其强大的计算机和专门的计算机程序（目标2.3）进行分析之后，我们将比较不同时间和不同细胞类型的胎盘来源数据，以确定对胎龄相关表达变化（特别是印迹基因）重要的区域，我们随后将删除或改变印迹基因以确定其功能（目标4）。

The placenta grows during pregnancy and is attached to the wall of the womb. It links the mother to the baby via the umbilical cord. Its main purpose is to supply the baby with all nutrients and oxygen required for growth, whilst removing waste products and carbon dioxide from the baby's blood. If the placenta does not develop or function correctly, this can lead to pregnancy complications that have huge consequences for the baby, not immediately following delivery, but later in life. Cells are the fundamental unit of complex tissues such as the placenta. Cell phenotype and function are very different between the different cell types. It is the code and activity (referred to as expression) of our genes that are ultimately responsible for defining which cells are produced and how they behave. This is achieved by 'epigenetic' modifications to the DNA. One form of epigenetic regulation is achieved by marking certain regions of the genome with methyl groups that tend to act as a semi-permanent block for gene expression. However, DNA methylation does not act alone, there are different interactive mechanisms that help in epigenetic regulation. In recent years a class of genes, known as imprinted genes, have been shown to be essential for placenta development and function. These uniquely regulated genes are epigenetically turned "on" and expressed solely from the maternal or paternal copy, but not both. The placenta is fascinating as it has a unique epigenetic profile having significantly less DNA methylation compared to all other tissues, which subtly changes during pregnancy. The hierarchical consequences of this unique hypomethylated state on the addition layers of epigenetic information have not been investigated. Furthermore, the placenta harbours hundreds of unique imprinted genes not found in other tissues, the expression of which generally decrease with gestation in a DNA methylation independent manner. This suggests other epigenetic mechanisms are responsible for the observed downregulation. Our understanding of this phenomenon has been hindered by the fact we do not know the mechanisms responsible for healthy aging within the placenta. In this application, we seek to understand how methylation in placenta influences other epigenetic marks at different time point in pregnancy and how this ultimately impacts on imprinted gene expression (Objectives 1.1-1.2). To achieve this, we will utilize, and in some cases improve, the latest technologies to identify which area of the genome are associated with different epigenetic signatures and how this influence development (Objectives 2.1 & 3). Furthermore, since we anticipate variability and cell-type specific signatures within our samples, we will profile isolated single-cells, allowing for us to identify patterns which would not be evident in "bulk" placenta biopsies (Objective 2.2). To ensure maximum chance of success building of our previous experiences, we have established a team that includes researchers responsible for technical development at the UK National Capability in Genomics at the Earlham Institute and computational experts for data analysis. Following the analysis using extremely powerful computers and specialised computer programs (Objective 2.3) we will compare our placenta-derived data across time, and within difference cells- types, to identify regions important for gestation-age related expression changes, especially for imprinted genes, which we will subsequently be remove or alter to determine functionality (Objective 4).