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联系起来。它的主要目的是为婴儿提供生长所需的所有营养和氧气，同时从婴儿的血液中清除废物和二氧化碳。如果胎盘没有正常发育或功能，这可能会导致妊娠并发症，对婴儿产生巨大的影响，不是在分娩后立即，而是在以后的生活中。细胞是胎盘等复杂组织的基本单位。不同细胞类型之间的细胞表型和功能非常不同。正是我们基因的编码和活动（称为表达）最终决定了哪些细胞产生以及它们如何表现。这是通过对DNA的“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，这些甲基倾向于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，一类被称为印记基因的基因被证明对胎盘的发育和功能至关重要。这些独特调控的基因在表观遗传学上被“打开”，并且仅从母本或父本拷贝表达，而不是两者都表达。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甲基化显着减少，这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研究。此外，胎盘含有数百个在其他组织中未发现的独特印记基因，其表达通常以DNA甲基化独立的方式随着妊娠而降低。这表明其他表观遗传机制负责观察到的下调。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内健康衰老的机制。在本申请中，我们试图了解胎盘中的甲基化如何在妊娠的不同时间点影响其他表观遗传标记，以及这最终如何影响印记基因表达（目标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，以确定基因组的哪个区域与不同的表观遗传特征相关，以及这如何影响发育（目标2.1和3）。此外，由于我们预期样本中的变异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）。为了确保最大的成功机会，我们已经建立了一个团队，其中包括负责技术开发的研究人员在英国国家基因组能力在厄勒姆研究所和计算专家的数据分析。在使用极其强大的计算机和专门的计算机程序进行分析之后（目标2.3），我们将比较不同时间和不同细胞类型内的胎盘来源数据，以鉴定对妊娠-年龄相关表达变化重要的区域，特别是印记基因，我们随后将去除或改变印记基因以确定功能性（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).